birth control research paper introduction

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This algorithm has not been validated for clinical use. IUD indicates intrauterine device; PATH, Pregnancy Attitudes, Timing, and How important is pregnancy prevention.

This algorithm has not been validated for clinical use. BMI indicates body mass index (calculated as weight in kilograms divided by height in meters squared); MEC, Medical Eligibility Criteria for Contraceptive Use.

• Selection, Effectiveness, and Adverse Effects of Contraception—Reply JAMA Comment & Response April 19, 2022 Stephanie Teal, MD, MPH; Alison Edelman, MD, MPH
• Selection, Effectiveness, and Adverse Effects of Contraception JAMA Comment & Response April 19, 2022 Ekaterina Skaritanov, BS; Gianna Wilkie, MD; Lara C. Kovell, MD
• Contraception in Women With Cardiovascular Disease JAMA JAMA Insights August 9, 2022 This JAMA Insights in Women’s Health series summarizes the prevalence of cardiovascular disease among women of childbearing age, the most effective forms of contraception based on the patient’s medical condition and preference, and the risks and adverse effects associated with contraindicated forms of contraception. Kathryn J. Lindley, MD; Stephanie B. Teal, MD, MPH
• Patient Information: Long-Acting Reversible Contraception JAMA JAMA Patient Page October 4, 2022 This JAMA Patient Page describes types of long-acting reversible contraception, how they are placed and removed, and their potential side effects. Elisabeth L. Stark, MD; Aileen M. Gariepy, MD, MPH, MHS; Moeun Son, MD, MSCI
• Patient Information: Medication Abortion JAMA JAMA Patient Page November 1, 2022 This JAMA Patient Page describes medication abortion and its risks and effectiveness. Rebecca H. Cohen, MD, MPH; Stephanie B. Teal, MD, MPH

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Teal S , Edelman A. Contraception Selection, Effectiveness, and Adverse Effects : A Review . JAMA. 2021;326(24):2507–2518. doi:10.1001/jama.2021.21392

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Contraception Selection, Effectiveness, and Adverse Effects : A Review

• 1 Department of OB/GYN, University Hospitals Medical Center and Case Western Reserve University, Cleveland, Ohio
• 2 Department of OB/GYN, Oregon Health & Science University, Portland
• Comment & Response Selection, Effectiveness, and Adverse Effects of Contraception—Reply Stephanie Teal, MD, MPH; Alison Edelman, MD, MPH JAMA
• Comment & Response Selection, Effectiveness, and Adverse Effects of Contraception Ekaterina Skaritanov, BS; Gianna Wilkie, MD; Lara C. Kovell, MD JAMA
• JAMA Insights Contraception in Women With Cardiovascular Disease Kathryn J. Lindley, MD; Stephanie B. Teal, MD, MPH JAMA
• JAMA Patient Page Patient Information: Long-Acting Reversible Contraception Elisabeth L. Stark, MD; Aileen M. Gariepy, MD, MPH, MHS; Moeun Son, MD, MSCI JAMA
• JAMA Patient Page Patient Information: Medication Abortion Rebecca H. Cohen, MD, MPH; Stephanie B. Teal, MD, MPH JAMA

Importance   Many women spend a substantial proportion of their lives preventing or planning for pregnancy, and approximately 87% of US women use contraception during their lifetime.

Observations   Contraceptive effectiveness is determined by a combination of drug or device efficacy, individual fecundability, coital frequency, and user adherence and continuation. In the US, oral contraceptive pills are the most commonly used reversible method of contraception and comprise 21.9% of all contraception in current use. Pregnancy rates of women using oral contraceptives are 4% to 7% per year. Use of long-acting methods, such as intrauterine devices and subdermal implants, has increased substantially, from 6% of all contraceptive users in 2008 to 17.8% in 2016; these methods have failure rates of less than 1% per year. Estrogen-containing methods, such as combined oral contraceptive pills, increase the risk of venous thrombosis from 2 to 10 venous thrombotic events per 10 000 women-years to 7 to 10 venous thrombotic events per 10 000 women-years, whereas progestin-only and nonhormonal methods, such as implants and condoms, are associated with rare serious risks. Hormonal contraceptives can improve medical conditions associated with hormonal changes related to the menstrual cycle, such as acne, endometriosis, and premenstrual dysphoric disorder. Optimal contraceptive selection requires patient and clinician discussion of the patient’s tolerance for risk of pregnancy, menstrual bleeding changes, other risks, and personal values and preferences.

Conclusions and Relevance   Oral contraceptive pills are the most commonly used reversible contraceptives, intrauterine devices and subdermal implants have the highest effectiveness, and progestin-only and nonhormonal methods have the lowest risks. Optimal contraceptive selection incorporates patient values and preferences.

Contraception is defined as an intervention that reduces the chance of pregnancy after sexual intercourse. According to a report from 2013, an estimated 99% of women who have ever had sexual intercourse used at least 1 contraceptive method in their lifetime. 1 Approximately 88% of sexually active women not seeking pregnancy report using contraception at any given time. 2 All nonbarrier contraceptive methods require a prescription or initiation by a clinician. Therefore, contraception is a common reason women 15 to 50 years of age seek health care. 3 This review summarizes current evidence regarding efficacy, adverse effects, and optimal selection of reversible contraceptives. This review uses the terms women and men when the biological expectation for the individual is ovulation or sperm production, respectively.

A search of OVID Medline All, Embase.com, and Ovid Evidence-Based Medicine Reviews–Cochrane Central Register of Controlled Trials for English-language studies was conducted for articles published between January 1, 2000, and June 28, 2021, to identify randomized clinical trials, systematic reviews, and practice guidelines related to contraception or contraceptives. After excluding duplicates and articles not relevant to this review, 2188 articles were identified as potentially relevant via title or abstract content. Thirty-seven articles, consisting of 13 randomized clinical trials, 22 systematic reviews, and 2 guidelines were included. Evidence-based guidelines that used GRADE and systematic reviews were selected for inclusion over individual studies. Clinical practice guidelines from the Society of Family Planning, the World Health Organization, and the American College of Obstetricians and Gynecologists on selected topic areas were reviewed to identify additional key evidence.

The mean age of first sexual intercourse among females in the US is 17 years. 4 Many women typically use contraceptives for approximately 3 decades. 2 The choice of contraceptive is determined by patient preferences, tolerance for contraceptive failure, and adverse effects. Clinicians should elicit patient preferences, identify possible contraindications to specific contraceptives, and facilitate contraceptive initiation and continuation. Clinicians should also be prepared to address misperceptions ( Box ). Some experts recommend screening for contraceptive need at each visit. Two validated screening options, with toolkits available online, are One Key Question and the PATH questions (Pregnancy Attitudes, Timing, and How important is pregnancy prevention). 5 , 6

Commonly Asked Questions About Contraception

What options are available for male contraception? There are currently no Food and Drug Administration–approved contraceptive options for men except condoms. Current male contraceptive methods under evaluation attempt to suppress sperm count to <1 million/mL and include a testosterone plus progestin topical gel.

Are contraceptives associated with increased rates of cancer? Combined hormonal contraceptives, such as combined oral contraceptive pills, protect against endometrial and ovarian cancer. They are associated with an increased risk of early breast cancer diagnosis in current or recent users (ie, within the past 6 mo). The incidence is 68 cases per 100 000 person-years compared with 55 cases per 100 000 nonuser-years. There are no associations of past contraceptive use with increased rates of cancer and there is no association of past contraceptive use and mortality.

Can teenagers use intrauterine devices (IUDs)? Prior guidance suggested restricted use of IUDs by teenagers, nonmonogamous or unmarried, and nulliparous women, but there is no high-quality evidence to support this recommendation. None of these characteristics are true contraindications.

Should all women use the most effective form of contraception? The choice of contraceptive is determined by patient preferences and tolerance for failure. Patients may value other attributes of a method (such as route of administration or bleeding patterns) more highly than effectiveness, and may prefer to have a slightly higher risk of unplanned pregnancy to avoid other adverse effects.

Is the pill as effective for individuals with obesity? Obesity adversely influences contraceptive steroid levels but determining whether this affects contraceptive effectiveness is difficult. The primary reason for contraceptive failure is suboptimal adherence. The use of any method for individuals no matter their weight will prevent more pregnancies than not using a method.

Why are pills not available over the counter (OTC)? Combined hormonal contraceptives are unlikely to be available OTC in the US due to concerns regarding increased rates of thrombosis. Efforts to bring progestin-only pills OTC are progressing.

Quiz Ref ID Reversible contraceptive methods are typically grouped as hormonal (such as progestin-only pills or estrogen-progestin patches) or nonhormonal (condoms, diaphragms) and long-acting (such as intrauterine devices [IUDs]) or short-acting (such as pills). Reversible contraceptive methods can also be grouped by level of effectiveness for pregnancy prevention. Except for behavioral methods, condoms, and spermicide, contraceptive methods are only available by prescription in the US.

Progestins and estrogens are steroid or lipid hormones. Hormonal contraception contains a progestin with or without an estrogen. Progesterone is the only naturally occurring progestin; most contraceptive progestins, such as levonorgestrel and norethindrone, are synthesized from testosterone. Progestins provide a contraceptive effect by suppressing gonadotropin-releasing hormone from the hypothalamus, which lowers luteinizing hormone from the pituitary, which in turn prevents ovulation. 7 , 8 In addition, progestins have direct negative effects on cervical mucus permeability. Progestins reduce endometrial receptivity and sperm survival and transport to the fallopian tube. 9 - 11 Estrogens enhance contraceptive effectiveness by suppressing gonadotropins and follicle-stimulating hormone, preventing the development of a dominant follicle. However, the most important contribution of estrogens to progestin-based contraceptives is the reduction of irregular bleeding. The estrogen component in most combined hormonal contraceptives is ethinylestradiol.

A variety of progestin-only contraceptive methods exists ( Table 1 ). Their effectiveness varies based on dose, potency, and half-life of the progestin as well as user-dependent factors, such as adherence to the prescription schedule. 12 , 13

Progestin-only pills include norethindrone- and drospirenone-containing formulations, which differ in their ability to suppress ovulation. Norethindrone pills contain 300 µg of norethindrone compared with 1000 µg in a typical combined contraceptive pill. The lower amount of progestin in norethindrone pills results in less consistent ovulation suppression and more potential for breakthrough bleeding. The contraceptive efficacy is maintained by other progestin-mediated effects. Drospirenone-only pills contain slightly more progestin than an estrogen and progestin combined hormonal contraception, which aids in ovulation suppression. In one study in which participants delayed their drospirenone-containing pill intake by 24 hours, mimicking a missed dose, ovulation suppression was maintained with only 1 participant of 127 having evidence of ovulation. 14 The benefits of progestin-only contraceptive pills include ease of initiation and discontinuation, fertility return within 1 cycle, safety profile, and minimal effect on hemostatic parameters. 15

Quiz Ref ID Depot medroxyprogesterone acetate (DMPA) is an injectable progestin available in intramuscular (150 mg) and subcutaneous (104 mg) formulations, which are administered at 12- to 14-week intervals. While DMPA is associated with irregular uterine bleeding, this pattern improves with longer duration of use. A systematic review of DMPA-related bleeding patterns (13 studies with 1610 patients using DMPA) found that 46% of those using DMPA were amenorrheic in the 90 days following the fourth dose. 16 DMPA is the only contraceptive method that can delay return to fertility. The contraceptive effect and cycle irregularity can persist for up to 12 months after the last dose, 17 likely due to persistence in adipose tissue and its effectiveness in suppressing the hypothalamic-pituitary-ovarian (HPO) axis. DMPA may be best suited for those who benefit from amenorrhea (eg, patients with developmental disabilities, bleeding diatheses) but not by those who want to conceive quickly after discontinuation. Typical effectiveness of DMPA and progestin-only contraceptive pills is 4 to 7 pregnancies per 100 women in a year. 12 , 18

Quiz Ref ID Progestin-only long-acting methods, such as the levonorgestrel (LNG) IUD and the subdermal implant, have typical effectiveness rates of less than 1 pregnancy per 100 women per year similar to permanent methods, such as tubal ligation or vasectomy ( Table 2 ). 12 , 18 These methods are also associated with return to fertility within 1 cycle after discontinuation. The LNG IUD maintains efficacy for at least 7 years, with amenorrhea rates of up to 20% at 12 months and 40% at 24 months. 19 However, initiation requires an in-person visit with a clinician trained in IUD placement. The etonogestrel subdermal implant is effective for up to 5 years 20 and is easily placed or removed. Initiation and discontinuation also require in-person visits. The bleeding profile of the implant is less predictable and up to 11% of users remove it in the first year due to irregular bleeding. 21 An analysis of 11 studies (923 participants) from Europe, Asia, South America, and the US found that the bleeding pattern in the first 3 months (such as prolonged, frequent, or irregular episodes) is consistent with future bleeding patterns. 21 However, those with frequent or prolonged bleeding in the first 3 months have a 50% chance of improvement in the subsequent 3 months. 21

Combined hormonal methods that contain both estrogen and progestin include the daily oral pill, monthly vaginal ring, and weekly transdermal patch. With full adherence, effectiveness of these methods is 2 pregnancies per 100 users per year. However, typical effectiveness is 4 to 7 pregnancies per 100 women per year, with variability in effectiveness related to the user’s adherence. 12 , 18 The importance of patient adherence to hormonal contraception was recently demonstrated by a cohort study of approximately 10 000 individuals in the US. Pregnancy rates were 4.55 per 100 participant-years for short-acting methods (pills, patch, ring) compared with 0.27 for long-acting reversible methods (IUD, implant). 13 Women younger than 21 years using short-acting methods had higher pregnancy risk as women 21 or older (adjusted hazard ratio, 1.9 [95% CI, 1.2-2.8]). 13 No risk differences by age were observed for the long-acting reversible methods of IUD or implant. Absolute rates were not reported by age stratum.

Combined hormonal contraceptives prevent pregnancy through the same mechanisms as progestin-only methods. Their greatest advantage over progestin-only methods is their ability to produce a consistent, regular bleeding pattern. In a study that compared bleeding diaries from 5257 women using 9 different methods of contraception (nonhormonal, combined hormonal contraception, and progestin-only), approximately 90% of combined hormonal contraception pill users (n = 1003) over a 90-day standard reference period reported regular scheduled withdrawal bleeds while no one experienced amenorrhea. 22 Occasionally, patients do not have a withdrawal bleed during the placebo week. A pregnancy test can be performed if the patient or clinician is concerned about the possibility of pregnancy as the reason for not bleeding. If pregnancy is ruled out, the lack of withdrawal bleeding is due to HPO axis suppression and patients can be reassured that lack of withdrawal bleeding does not indicate a health problem or reduced fertility.

Regardless of the route of delivery, ethinylestradiol and other estrogens are metabolized by the liver and activate the hemostatic system. The most significant risk of combined hormonal contraception is estrogen-mediated increases in venous thrombotic events. 23 - 25 Large international cohort studies have identified the risk of deep vein thrombosis at baseline in reproductive-aged women to be approximately 2 to 10 per 10 000 women-years. The risk associated with combined hormonal contraception is approximately 7 to 10 venous thrombotic events per 10 000 women-years. 26 - 28 The risk of venous thromboembolism is substantially greater in pregnancy. One UK study of 972 683 reproductive-aged women with 5 361 949 person-years of follow-up found a risk of deep vein thrombosis of 20 per 100 000 in women who were not pregnant. This rate increased to 114 per 100 000 women-years in the third trimester of pregnancy and to 421 per 100 000 in the first 3 weeks postpartum. 29 The absolute risk of ischemic stroke in reproductive-aged women not taking combined hormonal contraception is 5 per 100 000 women-years. 25 Combined hormonal contraception is associated with an additional absolute risk of approximately 2 per 100 000 (ie, overall risk of 7 per 100 000). 25 This study did not exclude women who smoked cigarettes or had hypertension. 25

Clinicians who prescribe combined hormonal contraception should counsel women regarding signs and symptoms of arterial and venous thrombosis, especially for women with multiple additional risk factors, including body mass index (calculated as weight in kilograms divided by height in meters squared) at or over 30, smoking, and age older than 35 years. While progestins are not associated with an increase in thromboembolic risks, 30 , 31 US Food and Drug Administration package inserts for these methods contain “class labeling” or the same risks as estrogen and progestin combined hormonal contraceptive methods. Patients at increased risk of thrombosis can be provided a progestin-only, nonestrogen-containing method because this method of contraception does not increase risk of venous thromboembolism. 32

Behavioral contraceptive methods include penile withdrawal before ejaculation and fertility awareness–based methods. Imprecise terms, such as natural family planning , the rhythm method , or other euphemisms may be used by patients when referring to these methods. The effectiveness of withdrawal and fertility awareness depends on patient education, cycle regularity, patient commitment to daily evaluation of symptoms (first morning temperature, cervical mucus consistency), and the patient’s ability to avoid intercourse or ejaculation during the time of peak fertility. Data on pregnancy rates are frequently of poor quality and highly dependent on study design. 33 A meta-analysis of higher-quality prospective studies of women at risk for undesired pregnancy reported failure rates of 22 pregnancies per 100 women-years for fertility awareness methods. 34

Other nonhormonal methods prevent sperm from entering the upper reproductive tract through a physical barrier (condoms and diaphragms) or through agents that kill sperm or impair their motility (spermicides and pH modulators). First-year typical use effectiveness for these methods is 13 pregnancies per 100 women in a year. 12 , 18

The copper-bearing IUD is a highly effective nonhormonal reversible method. 12 , 18 Typical use pregnancy rates are 1% per year. 12 , 18 There is no effect on a user’s HPO axis and thus ovulation and menstrual cyclicity continues. The primary mechanism of action is spermicidal, through direct effects of copper salts and endometrial inflammatory changes. 35 The major challenge with the copper IUD is that it can increase the amount, duration, and discomfort of menses mostly during the first 3 to 6 months of use. 36 IUD use does not increase later risk of tubal infertility. 37 If sexually transmitted infection (STI) testing is indicated, testing can be performed concurrently with IUD placement. 38 - 40 This expedited process of testing for STIs at the time of IUD placement does not increase the risk of pelvic inflammatory disease. The absolute risk of pelvic inflammatory disease after IUD insertion is low in those with (0%-5%) or without (0%-2%) existing gonorrhea or chlamydial infection. 41

Emergency contraception (EC) reduces pregnancy risk when used after unprotected intercourse. The most effective method of EC is a copper IUD, which reduces pregnancy risk to 0.1% when placed within 5 days of unprotected intercourse. 42 A copper IUD also has the added advantage of providing patients with ongoing contraception. LNG IUDs were not previously considered an option for EC. However, in a recent randomized noninferiority trial, women requesting EC who had at least 1 episode of unprotected intercourse within the prior 5 days were randomized to receive a copper IUD (n = 356) or a 52-mg LNG IUD (n = 355). 43 LNG IUD was noninferior to copper IUD (between-group absolute difference, 0.3% [95% CI, −0.9% to 1.8%]). However, the proportion of study participants who had unprotected intercourse midcycle (and therefore were at risk of pregnancy) was not reported. If a patient needs EC and wishes to initiate a 52-mg LNG IUD, it is reasonable to immediately place the IUD plus give an oral EC, 44 given the limited and indirect evidence supporting the LNG IUD alone for EC.

Quiz Ref ID Oral EC consists of a single dose of either a progestin (LNG, 1.5 mg) or an antiprogestin (ulipristal acetate, 30 mg). Both of these agents work by blocking or delaying ovulation. Neither is abortifacient. LNG EC is available over-the-counter; a prescription is needed for ulipristal acetate. The medication should be taken as soon as possible after unprotected intercourse for maximum efficacy but can be taken up to 5 days afterward for ulipristal acetate. 45 - 47 LNG efficacy is diminished after 3 days. Efficacy appears similar between the 2 agents when ingested within the first 72 hours after intercourse (ulipristal acetate EC: 15 pregnancies of 844, LNG EC: 22 pregnancies of 852; reduction in pregnancy without EC use estimated to be 90% less) but pharmacodynamic and clinical studies demonstrated that the ulipristal acetate treatment effect persists up to 120 hours with no pregnancies (0/97). 46 Actual use studies of EC that included 3893 individuals found lower pregnancy prevention rates than expected, which appears to be related to multiple acts of unprotected intercourse both before and after the EC use. 48 , 49 If further acts of unprotected intercourse occur 24 hours after EC use and a regular method of contraception has not been started, EC needs to be taken again. 49 Repeat use of LNG EC results in no serious adverse events; repeat dosing for ulipristal acetate EC has not been specifically studied. 50 Clinicians should review the options for EC with all patients starting a user-controlled method, such as condoms. These patients may be prescribed oral EC to keep at home for immediate use if needed.

Two evidence-based guidelines are available to assist clinicians in evaluating the safety of contraception initiation and use. 32 , 42 These guidelines were developed by the US Centers for Disease Control and Prevention, are updated regularly, and are freely available online and in smartphone apps.

The first is the US Medical Eligibility Criteria for Contraceptive Use 32 (US MEC), which provides information on the safe use of contraceptive methods for women with various medical conditions (eg, diabetes, seizure disorder) and other characteristics (eg, elevated body mass index, tobacco use disorder, postpartum). The US MEC uses a 4-tiered system to categorize level of risk for each disease/contraceptive method combination. 32 The risk tiers are (1) no restrictions exist for use of the contraceptive, (2) advantages generally outweigh theoretical or proven risks although careful follow-up might be required, (3) theoretical or proven risks outweigh advantages of the method and the method usually is not recommended unless other more appropriate methods are not available or acceptable, and (4) the condition represents an unacceptable health risk if the method is used. 32

All clinicians, including advanced practice clinicians, should be familiar with prescribing within US MEC categories 1 and 2 (no restrictions or benefits outweigh risks). For women with underlying health conditions who want to use a category 3 method, such as a woman with a history of breast cancer choosing combined hormonal contraceptives, primary care physicians or specialists should review the detailed evidence listed in the US MEC to advise their patients. Subspecialists in complex family planning who have completed extra fellowship training may provide helpful consultation for patients with multiple contraindications or unusual situations. The US MEC is a guideline, not a mandate. Situations may arise in which specialists recommend an MEC category 3 or 4 method because the alternative to the contraceptive method, pregnancy, places the patient at even greater risk. 32 The US MEC does not include conditions for which there is insufficient evidence to make recommendations, such as aortic aneurysms, Marfan syndrome, or chronic marijuana use. For these patients, clinicians should consider referral to a complex family planning specialist. If the patient needs a method immediately, a progestin-only pill should be considered as a “bridging” method, because these can be used safely by most patients 32 and are more effective than barrier methods such as condoms.

The US MEC addresses common drug interactions with hormonal contraceptives. 32 Contraceptive steroid hormones are metabolized via the hepatic cytochrome P450 pathway. 51 , 52 Drugs that induce this pathway, such as rifampin and barbiturates, or chronic alcohol can impair contraceptive efficacy and drugs that inhibit the pathway, such as valproic acid, cimetidine, or fluconazole, may increase adverse effects. The FDA recognizes a drug-drug interaction as clinically significant if it causes at least a 20% difference in drug levels 53 but an interaction does not necessarily affect contraceptive failure rates. Adherence, continuation, fecundity, and frequency of intercourse also contribute to contraceptive effectiveness. Additionally, most pharmacokinetic studies do not have sufficient statistical power to determine differences in pregnancy rates. The most common drug classes that may interact with hormonal contraceptives are antiretroviral drugs (including efavirenz and ritonavir-boosted protease inhibitors) and anticonvulsant therapies (including carbamazepine, phenytoin, and others). 54 , 55 Evidence from both clinical and pharmacokinetic studies of routinely used antibiotics do not support impaired contraceptive efficacy with concomitant antibiotic prescription, 56 except for rifampin with which ethinylestradiol and progestin area under the curve levels are at least 40% lower. 57 Because the local progestin dose in the LNG IUD is so high, its efficacy is not reduced by drugs that may affect combined hormonal contraceptives, progestin-only contraceptive pills, or the progestin implant. While hormonal contraceptive use can change concentrations of some drugs, 58 this is rarely clinically relevant, except for the reduction in serum concentration of the anticonvulsant lamotrigine.

Another major guideline is the US Selected Practice Recommendations for Contraceptive Use 42 (US SPR, available online or via a smartphone app). The US SPR is organized by contraceptive method. It includes method-specific, up-to-date guidelines, such as how to initiate the method, how to manage bleeding irregularities, and recommended follow-up. For example, the guidelines on IUDs include evidence on medications to ease IUD insertion or IUD management if a pelvic infection occurs. Recommendations related to combined hormonal contraceptives include the number of pill packs that should be provided at initial and return visits or management of vomiting or severe diarrhea while using combined oral contraceptives.

Much of the data on noncontraceptive benefits of hormonal methods come from case-control studies or small comparative trials. However, fair evidence exists that methods that suppress ovulation can be effective in reducing benign ovarian tumors 59 and functional ovarian cysts. 60 Combined hormonal contraceptives diminish hormonally mediated premenstrual dysphoric disorder, with statistically significant mean differences in symptoms, such as headaches, bloating, and fatigue, and functionality scales. 61 The estrogen component of combined hormonal contraception increases hepatic sex hormone–binding globulin, which reduces free testosterone and improves androgen-sensitive conditions, such as acne and hirsutism. Cochrane systematic reviews of combined hormonal contraceptives and both conditions show significant associations with improvement in a variety of measures of acne and hirsutism. 62 , 63 All progestin-containing contraceptives cause endometrial atrophy and, thus, reduce menstrual blood loss and menstrual pain to varying extents. 64 - 66 While progestin-only methods can promote unscheduled or breakthrough bleeding, the total amount of blood loss is reduced and in those with heavy menstrual bleeding, hemoglobin levels can rise by 10 g/L in 12 months. 67 , 68 The LNG IUD has demonstrated efficacy in reduction of heavy menstrual bleeding 69 , 70 (including for women with anticoagulation, fibroids, 71 or hemostatic disorders), primary dysmenorrhea, 36 , 72 endometriosis, 73 adenomyosis, 74 and protection against pelvic infection. 75

Screening for pregnancy is important prior to prescribing contraception. According to the US SPR, clinicians should be “reasonably certain” that the patient is not pregnant. 42 A clinician can be reasonably certain that a woman is not pregnant if she has no symptoms or signs of pregnancy and meets any 1 of the following criteria: (1) is 7 days or less after the start of normal menses; (2) has not had sexual intercourse since the start of last normal menses; (3) has been correctly and consistently using a reliable method of contraception; (4) is 7 days or less after spontaneous or induced abortion; (5) is within 4 weeks’ postpartum; and (5) is fully or nearly fully breastfeeding (exclusively breastfeeding or most [≥85%] of feeds are breastfeeds), amenorrheic, and less than 6 months postpartum.

Quiz Ref ID These criteria have a negative predictive value of 99% to 100%. 76 - 78 A urine pregnancy test (UPT) alone is not sufficient to exclude pregnancy. UPT sensitivity is dependent on when the last act of intercourse occurred, the ovulatory cycle phase, and urine concentration. Sensitivity of UPTs is 90% at the time of a missed period, but only 40% in the week prior. 79 Additionally, a UPT can remain positive up to 4 weeks after delivery, miscarriage, or abortion. 80 , 81 Few other tests are required for safe and effective use of contraception.

Clinicians can offer other indicated preventive health tests at the contraceptive initiation visit, like screening for cervical cancer or STIs. However, these tests are not required for contraceptive use and should not prevent initiation of contraception.

Generally, all methods should be started immediately on prescription regardless of menstrual cycle day—known as the Quick Start protocol. 82 If a hormonal method is initiated within 5 days of the first day of menses, no additional backup method is needed. At other times in the cycle, or when switching from a nonhormonal to a hormonal method, a backup is necessary for 7 days to ensure ovulation suppression. If switching from one hormonal method to another, the switch can occur without a withdrawal bleed or backup.

If a woman reports unprotected intercourse within the 5 days before contraceptive initiation, most sources recommend giving emergency contraception, initiating her desired method, and repeating a UPT 2 to 3 weeks later. 82 - 85 Many studies have demonstrated that exposing an early pregnancy to hormonal contraception is not harmful 86 but delayed initiation increases the risk of undesired pregnancy.

Because comparative effectiveness studies to clearly identify the superiority of one contraceptive pill formulation over another are lacking, selecting a contraceptive pill often depends on patient experience. Monophasic regimens, in which each pill has the same hormone doses, have significant advantages over bi- and triphasic regimens. Cycles can be extended easily by skipping the placebo week and starting the next pack of active pills. If this is attempted with multiphasic regimens, the drop in progestin between phases typically results in breakthrough bleeding. In terms of ethinylestradiol, few patients require a pill containing more than 35 µg/d to prevent breakthrough bleeding. 87 Many clinicians advocate starting with the lowest ethinylestradiol dose to minimize risks. However, there are no data demonstrating that 10- to 20-µg/d ethinylestradiol doses are safer than 35 µg daily, and lower ethinylestradiol doses are associated with more unscheduled vaginal bleeding. 88 Thus, starting with a monophasic preparation containing 30 µg to 35 µg of ethinylestradiol provides the greatest likelihood of a regular bleeding pattern without increasing risk. Ethinylestradiol can be reduced if patients have estrogen-associated adverse effects, such as nausea or breast tenderness.

Many different progestins exist. Progestins differ in in vitro androgenicity, effects on surrogate metabolic markers, or similarity to testosterone. 89 While molecular structures differ, there is no evidence demonstrating that a particular progestin is superior to others. Traditionally, progestins were classified into “generations” by their parent compound and decade of development. This classification is not clinically useful and should be abandoned. 90 Patients sometimes prefer a pill that they used previously, and if no contraindications exist and the cost is acceptable to the patient, it is reasonable to prescribe it ( Figure 1 and Figure 2 ).

Combined hormonal contraceptives can be dosed in a cyclic or continuous fashion. Originally, birth control pills were dosed with 21 days of active drug and a 7-day placebo week to trigger a monthly withdrawal bleed, meant to mimic the natural menstrual cycle. However, many women prefer less frequent withdrawal bleeds. 91 Some women report significant adverse effects 92 during this placebo week, such as migraine, bloating, and pelvic pain, and extended use provides an easy way to manage or eliminate these problems. 61 During the placebo week, there is less suppression of the HPO axis. 93 - 95 For these reasons, many newer contraceptive pills have shorter (eg, 4-day) placebo periods. Further, most monophasic combined hormonal contraceptives can be used as extended use (fewer withdrawal bleeds) by having a 4-day placebo period quarterly or continuously (no withdrawal bleed) by eliminating the placebo altogether. Extended and continuous use are associated with improved typical use efficacy, likely because greater overall HPO axis suppression is achieved, which may offset lapses in user adherence. 96 A new vaginal ring (segesterone acetate/ethinyl estradiol vaginal system) is also available, which is prescribed for 1 year, with the patient removing the ring each month for 7 days. 97

This review has several limitations. First, relatively few randomized clinical trials that directly compared contraceptive methods were available. Therefore, contraceptive methods are typically evaluated by their individual efficacy (pregnancies per person-cycles) and not typically by their relative effectiveness compared with another method. Second, the quality of summarized evidence was not evaluated. Third, some aspects of contraception, such as counseling, noncontraceptive health benefits, ongoing contraceptive innovations, and the effect of cultural values, and patient preferences were not covered in this review.

Oral contraceptive pills are the most commonly used reversible contraceptives, IUDs and subdermal implants have the highest effectiveness, and progestin-only and nonhormonal methods have the lowest risks. Optimal contraceptive selection incorporates patient values and preferences.

Corresponding Author: Stephanie Teal, MD, MPH, Department of OB/GYN, University Hospitals Medical Center and Case Western Reserve University, 11100 Euclid Ave, MAC-5304 Cleveland, OH 44106 ( [email protected] ).

Accepted for Publication: November 10, 2021.

Author Contributions: Drs Teal and Edelman had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design : Both authors.

Acquisition, analysis, or interpretation of data : Both authors.

Drafting of the manuscript : Both authors.

Critical revision of the manuscript for important intellectual content : Edelman.

Administrative, technical, or material support : Both authors.

Supervision : Both authors.

Conflict of Interest Disclosures: Dr Teal reported receiving grants from Merck & Co, Bayer Healthcare, Sebela, and Medicines360, and personal fees from Merck & Co and Bayer Healthcare outside the submitted work. Dr Edelman reported receiving grants from Merck, research funds from HRA Pharma, and royalties from UpToDate outside the submitted work.

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Peer-reviewed

Research Article

Women's perception about contraceptive use benefits towards empowerment: A phenomenological study in Southern Ethiopia

Contributed equally to this work with: Abraham Alano, Lori Hanson

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – original draft

* E-mail: [email protected]

Affiliation School of Public Health, College of Medicine and Health Sciences, Hawassa University, SNNPR, Ethiopia

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing – original draft, Writing – review & editing

Affiliation Department of Community Health and Epidemiology, College of Medicine, University of Saskatchewan, Saskatoon, Canada

• Abraham Alano, 
• Lori Hanson

• Published: September 13, 2018
• https://doi.org/10.1371/journal.pone.0203432
• Reader Comments

Despite the availability of copious information regarding contraceptive use benefits and the factors that influence the uptake of the services, there is little evidence revealing the lived experiences of rural women. Thus, this study was conducted with the purpose of exploring the lived experiences of women regarding contraceptive use and related benefits towards women’s empowerment.

Interpretative phenomenological qualitative methodology was employed to explore the lived experiences of women. Data were collected through focus group discussions and in-depth individual interviews and analyzed using an interpretive phenomenological framework including phases of data immersion, transcribing, coding, theme development and phenomenological interpretation through hermeneutic circle.

The reported lived experiences of rural women revealed that their livelihoods greatly improved in different ways after they began to use contraceptives. The benefits included securing more time, energy and social engagements. Contraceptive use helped women postpone unwanted pregnancies and child births and engage in various income generation activities that not only boosted family incomes but also created opportunity to mobilize the resources for different expenses without waiting for the handouts from their husbands. The women’s experiences also indicated that contraceptive use improved the educational status of their daughters and they experienced improved self-image, better social standing and improved family relations. The experiences further illustrated that contraceptive use was not only emancipatory and transformative, but also created peace and stability in their lives.

The study concludes that contraceptive use, which is part of a woman’s life experience, created remarkable opportunities and achievements. One of these was that women were able to control their bodies, reproduction and fertility which resulted in a higher degree of empowerment. The control of reproduction and fertility has liberated them from worries and entrapment of unplanned and unwanted pregnancies. Moreover, contraceptive use led to wider opportunities in the community, by improving their status and building a sense of empowerment. Creating awareness around the benefits of contraceptive use has the potential to improve community and national development. Based on the result, the study recommends that systems should be established to capitalize on the lessons learned about the lives of current users and expand the remarkable achievements and experiences to non-user counterparts.

Citation: Alano A, Hanson L (2018) Women's perception about contraceptive use benefits towards empowerment: A phenomenological study in Southern Ethiopia. PLoS ONE 13(9): e0203432. https://doi.org/10.1371/journal.pone.0203432

Editor: Vijayaprasad Gopichandran, ESIC Medical College & PGIMSR, INDIA

Received: April 19, 2017; Accepted: August 21, 2018; Published: September 13, 2018

Copyright: © 2018 Alano, Hanson. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All of the relevant data is within the paper and its Supporting Information files. All the names in the transcript data are pseudonyms that do not directly identify study participants. Information related to sharing the data and public communication were informed to the study participants at the time the data was collected.

Funding: Hawassa University, Ethiopia and University of Saskatchewan have sponsored the study field work.

Competing interests: The authors have declared that no competing interest exist.

Introduction

The use of modern contraceptive methods was documented in the early 1960s (Cleland, 2008), albeit with varying levels of utilization around the world [ 1 – 3 ]. The innovative development of safe and effective contraceptive methods has critically benefited humankind in numerous ways [ 4 – 6 ]. The outcomes of contraceptives use include; poverty reduction, reduction of maternal and child mortality, women empowerment by reducing the burden of excess childbearing, and enhancement of environmental sustainability by stabilizing the population of the planet [ 5 , 7 – 10 ]

The link between reproductive rights and women’s empowerment and the role of contraceptive utilization is obvious [ 11 ]. The ability of women to control their sexuality and fertility through proper use of contraceptives is the cornerstone to ensure other aspects of women’s rights and human rights [ 12 , 13 ]. Contraception offers remarkable contributions towards the empowerment of women in multiple ways, including the avoidance of unplanned and unwanted pregnancies, increasing the amount of time between successive pregnancies, and enabling engagement in educational and economically productive activities [ 5 , 14 ].

Despite the observed improvement in contraceptive prevalence rate (CPR) in Ethiopia currently, there is variation across the regions. The great variation in CPR is observed among urban and rural, pastoral and non-pastoral, and region to region. CPR in Addis Ababa is as high as 63% (nearly the global average) and in some pastoral regions as low as 10% [ 15 ]. The CPR in the study area is 25% [ 15 ]. In a similar manner, political and administrative trends in Ethiopia also created power differences between women and men, denying the right and privileges of women (although the current government has clearly attempted to change that through the 1995 constitution). Many additional circumstances affect the status of women and girls, and gender equality between women and men. These factors have been contributing to the difference in contraceptive utilization across the country from region to region, urban to rural dweller, and educated versus uneducated [ 16 – 20 ]. Moreover, lack of comprehensive knowledge about the benefits of contraceptives to the wider domains of women’s lives, inadequate support from the husband/spouse, low service quality, and limited types of contraceptive methods affect contraceptive usage rates [ 21 ]. . Notably, Ethiopia is still suffering from preventable morbidity and mortality of mothers and newborns with one of the highest maternal mortality rates (420 per 100,000 live births) and neonatal mortality rates (of 38 per 1000 live births), as well as high total fertility rates (4.6 children per woman), and the highest unmet need for family planning (26 percent) in the world [ 15 , 22 ].

Despite some encouraging efforts and recent progress in improving access to reproductive health services, including contraceptive methods provisions, Ethiopia remains at lower levels with wide gaps and lags behind in service provision to reach the desired level of contraceptive acceptance, fertility, and accompanying health and empowerment benefits for women.

An important observation discovered in addressing these challenges is that in similar socio-economic, cultural and environmental contexts, some women appear to adopt modern contraceptives while others do not. This trend occurs in almost every part of the Ethiopia where contraceptive services are available [ 15 , 23 ]. Yet, there is little evidence that explains why. The evidence is also elusive regarding how family planning service provision is perceived by the primary beneficiaries (the rural women), whether and how they relate it towards their empowerment, and how it is valued and internalized by them in order to ensure sustained use.

This study was conducted with the purpose of understanding the perceptions regarding women’s contraceptive use and the subsequent benefits towards their empowerment. In addition, the study aimed to narrow the gap between current users and non-users, and focused on women with unmet needs by sharing the experiences of current users and their perceptions regarding contraceptive benefits, all while elucidating factors contributing to sustained contraceptive use.

Materials and methods

The research context.

This study was conducted in three of six districts of Sidama Zone designated by Hawassa University as technology villages for research and technology transfer. These three districts were selected conveniently. The university is situated within this administrative zone and has revitalized its research and community services in order to materialize its contribution to the surrounding communities and ensure its transformation plan. Sidama Zone is one of the thirteen zones in the Southern Nations Nationalities and People’s Regional state (SNNPRG), under the Federal Democratic Government of Ethiopia. Sidama Zone is located in the south-eastern part of the region and is bordered on the south, east and north by the Oromia Region on the west; it borders Wolaita Zone [ 24 ]. According to the population projection based on the 2007 national population census, the zone has a total of 3,471,568 people of which 1,753,142 (50.5 percent) are males and 1,718,426 (49.5 percent) are females. Women of reproductive age are estimated to be 23.8 percent of the total population. Household population size is estimated to be 4.7. Annual population increase is estimated to be 2.9percent [ 25 ].

Study design

Interpretive phenomenological qualitative research approach..

The study was based on the interpretive (hermeneutic) approach appropriate to understand the life world of women, as it focuses on describing the meaning of the individuals and how these meanings, such as the experience of contraceptive use, the phenomenon influences the choices they make, rather than seeking purely descriptive categories of the real, perceived world in narratives of the participants [ 26 ]. It further considers the importance of the expert knowledge of the researcher as a valuable guide to the enquiry. Exploring the life experience related to contraceptive use by employing this approach, clearly offered a unique opportunity to establish a rich and in-depth understanding about the contribution of contraceptives towards the empowerment of women, the improvement of the health of women and their children, and the society at large [ 27 ].

Data collection.

The study employed linguistically competent research assistants and utilized two main data collection methods. In order to capture in-depth information in relation to the topic of interest: focus group discussions (FGDs) and the individual in-depth interviews were used. Research assistants were recruited based on the selection criteria stated in the original thesis document. After recruiting and training the research assistants, health extension workers and local women, the community leaders collaborated in the selection of study participants. The participants were selected based on the following criteria: 1) women who could illustrate the phenomenon, contraceptive use and related benefits in the study kebeles (the smallest administrative unit) 2) women of the reproductive age group using any type of modern contraceptive method before and during the study period 3) women having used contraceptives for at least one year. The following strategies were used to select participants: 1) potential participants (women using contraceptive method) were approached by the community leaders and informed about purposes of the study, 2) names of interested participants for focus groups and individual interviews were submitted to the research assistant and the researcher. A total of 82 women of reproductive age group were included and participated in the focus group discussions which comprised of 7–12 participants in each FGD. For the individual in-depth interview, 18 reproductive age group women from nine kebeles involved. A semi-structured interview guide was developed for the interview and the participants were encouraged to speak up about their experiences. This deepened discussions and reflection on the life experiences of the women [ 28 , 29 ].

Through focus group discussion the experiences and perceived benefits of contraceptive use of women of reproductive age were explored in detail [ 30 ]. Totally nine FGDs were conducted in three selected study districts and nine kebeles (health posts). Eighty-two women of reproductive age who were recruited on the basis of criteria engaged in nine focus group discussions where the number of participants in each session ranged from 7 to 12.

Discussions were arranged in consideration of the time and regularity and viability of rural women. All the discussions were conducted outside of market days and from 10:00–11:30 AM. Women were contacted through the women community leaders and the health extension workers regarding the date, time and place of the discussion. Focus group discussions were conducted in the health post closer to residential areas of the study participants making sure that all participants received equal attention to explore their lived experiences.

Following the focus group discussion, the individual in-depth interviews were carried out with women who had been using contraceptives for a long time (the minimum time considered for this category was 18 months consecutively). A total of 18 individual in-depth interviews were conducted by the research team in the residence of the women and also at the health post based on preferences of the interviewee. For those who were interviewed at their home, the research team was guided by the health extension worker or the community leader or both at the same time. A consent form was read and permission obtained (those who can write signed using pen and those who could not confirmed using their fingerprint) to continue the interview and record the interview in audio-tape and on paper.

Each interviewee was encouraged to talk about her life experience in detail without any apprehension or reservations. The interview continued in such a way for 40 to 60 minutes until the study team agreed that the ideas emerging became repetitious [ 27 ].

Data analysis.

This study used the guiding principles of interpretive phenomenological methodology to explore the lived experiences of women’s’ contraceptive use and their perceptions of related benefits. Interpretive phenomenological analysis enabled viewing the practice or phenomenon in such a way that considers the close interaction between the participants and researchers as instances of their “being in the world” rather than only “being’ itself [ 31 , 32 ]. In a sense, the final presentation of the data thus becomes an inter-subjective representation of the topic of the study. An adapted flow diagram from the interpretive phenomenological analysis (IPA) was used to guide the analysis ( S1 File ).

The process of data transcription and analysis was more complex as three languages were used in the research. The following steps describe the process: transcriptions were made of all the audio-taped materials verbatim, by Sidamigna and then translated first into Amharic and then to English. Materials were also translated back to Amharic by a linguistic professional. The Amharic translation was then given to the research assistant to translate back into Sidamigna, after which the document was reviewed for consistency. The three-step translation was mandatory as the principal investigator (the main researcher is not literate for Sidamigna). Therefore, Sidamigna to Amharic translation was necessary to fully capture the essence of the discussion. Study participants were given a chance to see the transcribed data and summary results and made comments based on their impressions by the help of the research assistants. Field notes were organized under the guiding research questions. Data immersion by the researcher took place by reading the transcripts several times. Repeatedly reading and re-reading the material revealed recurring ideas and concepts. In the data immersion process, several visits were made to the study participants as a first step in identifying descriptive codes and checking preliminary interpretations. The participants commented on some points following an initial description of the issue(s), and these were incorporated into the second round of data analysis with remarks. Margin notes and descriptive coding were then completed for all the materials. Data reduction was done in a step-by-step approach, beginning with the transcripts, followed by descriptive coding, and then distilling the material into themes by bringing similar ideas and concepts together.

Deriving themes was completed with consideration of both emergent themes and the research questions. The analysis made use of the idea of a hermeneutic circle; mainly, the back and forth iterative linking of data from both the perspective of both the researcher and study participants [ 33 ]. Summarized reports were presented to the study participants about the conclusions derived from their shared experiences. Discussions were held with participants about the study guide questions and core concepts of the study. Participant feedback was then considered alongside the experiences of the researcher.

Quality assurance or trustworthiness of the study used four criteria: credibility (truth value), transferability (applicability), dependability (consistency), and conformability (neutrality) suggested in the literature [ 34 – 36 ]. Trustworthiness in this study was ensured through: 1) presenting the summary of transcripts to the study participants to give them an opportunity for further comment; 2) reviewing of the preliminary findings to ensure that the early findings reflect what they know of the women’s lived experiences. 3) sharing the preliminary summary finding with the health managers and service providers to check interpretations; 4) indicating the detailed steps of the field work including the process of data gathering using the overlapping methods of focus groups and individual interviews.

Ethical considerations

The researchers obtained ethical clearance from the University of Saskatchewan Research Ethical Review Board, Canada and Hawassa University Institutional Review Board, Ethiopia[ S4 File ]. Signatures were obtained from the study participants as facilitated by the research assistants in their local language and participants were assured the right to participate or withdraw from the study. Through follow-up sessions, the researcher and research assistant assured that the information gathered during the study was kept confidential. The back and forth translation of transcripts were presented to the study participants after initial analysis summary in order to assure the correctness of the information they offered. Anonymity of the participant’s transcripts and verbal record were maintained by using pseudonyms.

Women’s perception of contraceptive use: Benefits toward empowerment

The study presents how the benefits of contraceptive use were perceived by women in terms of economic, educational and psychological aspects of empowerment. In the same way that women often discussed their experiences with contraceptive use, it discusses changes in the lives and livelihoods of the women and their families in relation to contraceptive service use, both before and after service use.

Economic empowerment.

Study participants collectively expressed that their livelihoods in general were poor before contraceptive service use. It is indicated that when the number of children increases due to uncontrolled fertility, the family plunges into abject poverty. Related to this is the concern of land size in rural communities. All livelihoods are based on agricultural activities where arable land is the main means of subsistence. However, household land size is alarmingly reduced, consequently, the quality and quantity of productivity is diminishing. An experience of Adanech; a 25 year old woman having two children and using contraceptives for three years was explained:

“ I have small plot of land which is also not fertile. What I have done since I started using contraceptive service is that I herd cattle, sell some and earn money out of them. You see, herding cattle is labor intensive. You have to prepare fodder for them. To do so, you have to have enough time. Contraceptive use has averted unwanted pregnancy for me and I am free to use this time for collecting fodder for my cattle .”

Women expressed that after contraceptive service use, their livelihoods have improved in several ways. It is substantiated by the words of Mutarie, a 25 five years old woman with no formal education and a mother of five children:

“ When I gave birth to many children in close gaps, I was unable to go to market. After I have started using this method, I am not waiting on my husband’s hand only. I grow vegetables in my garden such as cabbage and others. I sell some part of these and earn some money and use to eat part of these .”

When women are able to postpone unwanted pregnancies and childbirths, they have more time to plan and engage in non-reproductive issues such as income generation.

“Now I am a merchant working partly in the market . I have no worries like previously as there is no young child who needs my frequent visit . I send older children to school and then work whatever I can do . Contraceptive use has enabled most of us to engage in diverse income generating activities . Some of us became owners of better homes , others bought cattle , ” as evidenced by the words of Workie, a 30 year old woman with non-formal education who used contraceptive method for seven years.

Other women who participated in the study reported that since having more personal time as a result of using contraceptives, they engaged in credit unions, thereby becoming involved in an investment enterprise. These women have appreciated their experience of pregnancy planning for having created wonderful opportunities to improve their income and position in the community. Some women joyfully added that they were newly considered the pride of their husbands. Daetie, a 34 years old woman having 4 children and completed grade eight education, mentioned her experience as:

“ Now I do my work. I have poultry and garden cultivation where I work most of the time. The freedom has created wonderful opportunities for me to get involved in income generating activities and use the income to manage my home properly. I am now considered as a blessing for my husband, who previously abandoned me and my children when we were in living a miserable life .”

Women using contraceptives also reported better use of the limited resources available to them and their families enjoyed the resulting psychosocial benefits.

“We are now capable of taking level actions either to generate or expend income for minor household activities . Therefore , we are freed from looking for handouts and have started to exercise our rights and autonomy . Simultaneously , we learnt how to use our resources in an economic way . We relate all these to contraceptive use as it averted unwanted pregnancies and created opportunities to properly use our time . We no longer have such worries about cries of our young children . Our minds and hearts are cool and restful now”; said Mogise, a 25 year old woman with three children and a grade six education.

Further, study participants articulated that contraceptive use has helped them improve their work culture, both in their family and the community. The capacity to work in various sectors improves, which includes supporting husbands in the field and directly working for oneself. This increases productivity in the field and raises household income. As stated by Janame, a 30 year old woman with a grade seven education, who used contraceptives for seven years, and has four children:

“ Contraceptive use helped me to avoid unwanted pregnancy, and created time and energy for engaging in various outdoor activities, and thereby generates income for my household use. Moreover, contraceptive use has enabled me to help my husband in various outdoor work activities. We have now more cattle, chickens, and better crop yields. My husband works in a more pleasant way than before. We have constructed a better home as compared to the previous time. When taking all this into account, our livelihood has tremendously improved .”

Educational empowerment.

In terms of education, women elaborated on the change in educational status in their family since they started using contraceptives. Being free from pregnancy means being able to move freely wherever they want; be it to school, market, social gatherings, health institutions, etc. Women also mentioned that they are cognizant about the benefits of education to their children’s future:

“I see education for my children as a sole means to escape livelihood challenges and springboard for future prospects . With this intention I am greatly determined to send all my children to school . At this time three of my children are in school… I give more emphasis to my daughters . I have learned enough lessons from my sufferings . ‘What do you talk about ? ’ Had I been well educated , I would never led a life like this . As a result , I am highly motivated to educate my daughters with a particular emphasis . I feel I am lagging behind in many directions , economically , intellectually and socially , for that reason I haven’t succeeded in my educational career . This is why I showed great commitment to my daughters and curious to see if and when they will attain high-level career”; as shared by Dalibe a 30 year old woman with grade six education who used contraceptives for two years.

Remarkably, study participants also connected contraceptive use to enabling those who had dropped out of school to resume their education. Some of the study participants dropped out of school sometime in the past due to forced marriage. They were waiting for the right conditions to continue their schooling.

The following excerpt richly expresses this notion:

“I gave birth to the second child after my older child reached grade nine . After that , I continued my education and received my diploma before giving birth to my third child . What helped me was a contraceptive method . I could have given birth to six or seven children if there hadn’t been a contraceptive service . There are women with such happenings . If I hadn’t used a contraceptive method , my education would have remained at grade eight where I stopped during my marriage . I thank both my Lord and the government who have given us the opportunity . I also became able to be employed at public sector”; according to Mosone, a 27 year old woman with diploma education and two children, who used contraceptives for six years.

The study also revealed the experiences of some women where they had wonderful occasions to communicate with their husbands and plan on their education. Since contraceptives were being used, they were able to plan household education by setting a schedule for the education of both husband and wife. Somane, a 23 year old who completed grade six in school and used contraceptives for three years, shared her life experience by stating:

“ I have also a great desire and plan to continue schooling myself. I’m waiting until my husband completes his schooling, then I will continue. At this time, my husband is attending his school. Therefore, I am unable to attend because if we both leave the house, no one will take care of our daughter and domestic responsibilities .”

Psychological dimension.

Typically, in Ethiopia when a woman cannot regulate her fertility, she has several children in very close succession. This creates an increased burden on the woman’s physical, psychological, and social dimensions. Such a woman cannot properly care for herself, her children, and husband.

“Our lives were about pregnancies and child birth . One comes just after the other in nine-to-ten months’ time . That was the time which we hated ourselves and our children . They were emaciated , not thriving well and not attractive to see . We ourselves were not well-fed , unhygienic and undernourished”; mentioned by Aster; a 25 year old woman who used contraceptives for four years and completed a grade seven education.

Women contrasted such experiences with contraceptive service use, noting how it has created wonderful opportunities for them to either postpone or delay unwanted and unplanned pregnancies. They considered themselves as fortunate people by comparing their improved status to that of their mothers at a similar age. This was substantiated by the experience of Tadelech, a 27 year old woman who completed a grade seven education, and used contraceptives for 12 years:

“ I feel very happy. I feel so because, I am free from the burden of pregnancy, no fear about the unlikely outcomes of it and have time to share for other activities than only the child care. My husband is too. I take the service in agreement with him. I told him about the benefits of the service and he whole heartily supported the idea. In general, I have pleasant feeling about contraceptive services as it has many benefits for a woman like me, for children and community in one way or another. I have accepted contraceptive service for its positive outcomes .”

In addition, women explained that their harsh feelings of the old days had been converted into the “bright shining days”. They explained how they had now reached a point where they could take the time to relax and take some rest in their lives. Women using contraceptives speak of reaching the actualization of considering themselves as fully human–as a person that can stand before anyone without fear. This is demonstrated by the experience of Munushe, a 28 year old woman with four children who used contraceptives for three years:

“I say ‘effoy’, (meaning taking a deep breath and thanking the lord for the comfort I have now . ) I say now ‘effoy’ comparing to my previous non-contraceptive use time , where I was forced to bear children in close manner . During that time , I had little time to care for them and hardly had time to rest . Now through contraceptive use I got relief from that , and for the last four years I have been living in ‘efoyta’ , with peace and rest . Our lives before contraceptive use were full of burdens associated with young children and looking for ways to support them . It made our lives stressful (both I and my husband) , hectic and no ‘effoyta’ . ”

Contraceptive use and women’s empowerment

The present study shows contraception is fundamentally empowering women in four ways: 1) economic empowerment and agency 2) effects on personal autonomy 3) effects on mobility 4) effects on relationship. In this paper we consider economic, educational and psychological aspects.

In general, women’s experiences in this study revealed that contraceptive use is emancipatory and transformative to their lives. When it is said to be emancipatory, contraceptive service played an important role by enabling women to avoid unwanted or mistimed pregnancies and kept them free to be involved in many activities beyond the reproductive horizon. Studies in Bangladesh, the US and West Africa also support the conclusion that contraceptive use has improved women’s ability to be involved in productive work and other socio-cultural aspects by averting unwanted pregnancies[ 37 – 39 ].

Women’s experiences clearly indicated huge livelihood challenges in the study area. They expressed worries that their land size was diminishing, and its productivity decreased, as they were unable to allow the land to rest. Unplanned pregnancies and childbirths further stress household finances. Shiferaw [ 40 ], argues along this line, stating that when there is uncontrolled fertility, the population growth outpaces the capacity of natural resources, resulting in a poverty trap that further aggravates rural livelihoods.

Contraceptive service appears to be one of the mitigating factors in harmonizing the ever-growing demands on the limited resources of the household. Contraceptive use functions to harmonize the family income with family size [ 4 , 10 , 31 ]. Preventing unwanted pregnancies means creating increased opportunities for the household to generate more income. On top of their domestic responsibilities, women are able to engage in economic activities where they can generate income and thus boost their families’ resources. The income they generated helped them invest in the construction of better homes that improved the quality of their lives. Newly obtained free time has enabled women to think carefully about which income generating activity would best match their situation and provide the best return. They are able to think and plan; setting proper priorities to become involved in income generating activities and subsequently, the economic activities enhance decision-making capacity.

Women’s experiences further revealed that when their chances of being involved in income generation increases, their capacity to properly manage resources also improves [ 10 ]. Following the implementation of contraception services, women in the study area became more conscious of the use of resources at the household level taking charge to minimize wastage and control of their older children’s expenses. Further, they learned that they have obtained opportunities to minimize waste and preserve resources for unexpected needs. This is another golden experience that could further improve community and national development through saving and investment.

Education is one of the most influential means for women’s agency. It helps to mitigate household and individual-level poverty and livelihood challenges [ 7 ]. However, women in the rural part of Ethiopia have not been able to fully enjoy the benefits of education. People in the study area discouraged girl’s education by saying that “the best education for a girl is to master domestic work through helping her mother at home.” Another excruciating condition was early marriage, which often ruined girls’ educational chances. A particularly humiliating local saying in the study area, which works against girls’ education, was “let the girl and a dead body leaves the house early”. This was in line with culturally embedded implications that if one invests in a girl it is only benefits others and not the family, as a girl ends up married anyway, which requires resources to be transferred from her parent’s house to her husband’s house.

Girl’s education is also hampered by household work. A mother, heavily burdened with domestic work, often does not wish to send her daughter to school; rather, she prefers her daughter stay home to help her with household duties, feeling that, “what good is an education while I am suffering with continuous domestic work burdens”. This dynamic not only denies the privilege or right of a girl to attend school but also disgraces her human dignity. According to Kruger et al .,[ 41 ], it is argued that women’s oppression results from social arrangements inherent in a society, which can be changed. In connection to that, family dynamics result in women’s subordination since these are based on dominant and subordinate roles legitimized by society.

Some of the women in the study were observed to exhibit changes in their thinking in this regard, stating they wish better futures for their daughters. At least some of the participants discussed how contraceptive use enabled them to send their daughters to school, or to continue their schooling after dropping out due to forced marriages. Contraceptive use has therefore shown that it can emancipate and empower women by allowing some of them to complete their secondary schooling, join tertiary school, graduate, and become employed in better paying jobs, but that it is not a straightforward path.

The connection between economic and educational empowerment is also related to contraceptive use, in that obviating an unplanned pregnancy was helping women generate greater revenue, which could go towards their children’s schooling. This finding is further supported by a USAID report that showed that couples with the means to control their fertility were often able to invest more resources in each child, which ultimately raises the standard of health, education, and wealth in the population [ 42 , 43 ].

A woman’s psychosocial health is affected by several factors. Unregulated fertility is one of the major factors that limit women’s capacity. Women’s experiences have revealed that contraceptive use has helped in myriad ways. It helped the women plan their pregnancy and childbirth and manage their time for personal care and development. Unlike life prior to contraceptive use, they are able to better maintain their cleanliness, improve their self-image, and esteem. They feel proud and fortunate to live in a time with available contraceptive services by which their visibility and status in society can be improved. This finding therefore supports other studies conducted on the influence of women’s perceived body image on their marital and sexual relations. When women perceive that their body image is poor or weak, they can feel poorly motivated to engage various socio-economic and personal affairs [ 44 – 45 ].

When a woman generates her own income, she obtains relative financial autonomy instead of waiting for money from her husband. In rural Ethiopia generally, and in the study area particularly, finances in the care of the husband are often out of reach for expenses related to child care. Conversely, money in the control of a woman can easily be accessed for child care and other family members [ 46 ]. Moreover, when a woman attains otherwise unobtainable finances through contraceptive use and used the money to support her family, she feels proud and confident. Barroso 12 , similarly notes the experiences of women who have control of their sexuality and fertility through the use of contraceptives have created opportunities for them to be involved in other aspects of life outside the mere reproductive dimensions.

Sonifield et al., [ 47 ],argue that “education, employment, income and relationship stability are connected to mental health, happiness and quality of life for individuals and couples. By affecting these central life experiences, access to contraception may also affect mental health and well-being”. The present study reveals that a woman’s experience of psychological empowerment was directly related to personal autonomy following contraceptive use. Some participants equated this to a time when darkness changed into light and nights changed into days. Additionally, the fears related to unregulated and unplanned pregnancies have changed into happy and joyful planned outcomes. Contraceptive use has enabled women to postpone pregnancies to a time when they are ready. Indeed, avoiding an unplanned pregnancy created more time and resources for women to care for their family members and themselves.

Women using contraceptives in the study felt confident and stood firm before society, instead of feeling shy and looked down upon, as they received respect and love from their husbands and other members of society. Women’s attitudes and feelings have changed from the hectic and fearful to satisfied, peaceful and stable. Studies agree with the finding that the ability to delay early childbirth has many advantages such as improved earning potential, ability to send their children to better schools, enabling them to follow up on their children’s school attendance and improved marital relations by reducing domestic burdens [ 48 – 49 ].

Within the study, women’s visibility in society improved because they had enough time to become involved in social activities after completing their domestic work. Women’s capacity to accomplish their duties in the manner that they desire also greatly improved. Cleland, et al., [ 5 ], ascertained that contraceptive use, apart from the socio-economic considerations, allows the attainment of fundamental human rights to choose the number and timing of children. They explain further that contraceptive use created “freedom from the tyranny of excessive fertility” which has been called the fifth freedom, alongside freedom of speech and worship and freedom from want and fear.

Women’s experiences also revealed that they were involved in various community affairs following contraceptive use. They organized themselves into various enterprises where they received credit and were able to mobilize that credit to generate income, save, and spend for their family needs. They were also involved in other community affairs such as leadership positions for development organizations (named as development army), community networks, and model women’s groups in the community. Following contraceptive use, women were able to attend social gatherings, religious ceremonies and access health services. Women’s capacity to discuss family matters with their husbands improved as well. They discussed matters such as household expenses, children’s education, health services use and income generating activities. Women’s experiences in this study correspond with other study findings that when women are able to delay their pregnancy, it helps them reach to the destiny they want and paves the way to becoming involved in socio-economic arenas [ 50 , 51 ].

Decision-making processes and actions are among the core aspects expressing women’s empowerment. It usually relates to the level of power one has in the social system. Women in the developing world in general and in rural areas in particular experience challenges related to a very low social status, which hampers their decision-making capabilities both within the household and at the community level. Their decision-making experiences as they lived through contraceptive use have shown grey areas unlike other dimensions of their empowerment. Women’s experiences in their decision-making revealed that they have relative freedom only for domestic decisions such as cooking food, fetching water, cleaning houses, and washing clothes.

Women’s capacities to make decisions on major family affairs are contingent on their husbands. With the majority of decisions, the husbands are the ones make the final decision. In order to leave their houses, women often need to notify their husbands. The present study revealed that women have the liberty to make decisions only regarding lower-level domestic work; their power to decide on higher-level issues is diminished. Though there have been some improvement in the process of decision-making through household-level discussions, rural Ethiopian women often have less freedom to make their own decisions, thereby indicating the continued imbalance of power between husband and wife. As such, decision-making ability is one of the least privileged and slow-moving aspects of progress in women’s autonomy observed in the study area. Together with contraceptive use, women could benefit from empowering universal affirmative actions. The extraordinary experiences of contraceptive use related benefits should be extended to all other sectors of development.

Limitation and delimitation

One limitation of the study was that it considered only married women, and included participants from only three districts of Ethioipia. The sensitivity of issues surrounding contraceptive utilization may be one factor that limited responses during data collection. Another possible limitation is that the study hasn’t considered current non-users’ perception about the benefits of contraception. Men are also not considered in this study as the prime purpose of the study is to explore the experiences of women.

The delimitation of this study is explicated in terms of the study purpose, the selection of the study area and selection of study participants. The study was carried out with the intention to explore the experiences of female contraceptive users in the Hawassa University research villages, which were established with the intention to observe the impact of university-based research in knowledge generation, technology transfer and the livelihood of the residents.

This study was conducted with the broad aim of improving the overall understanding of policy makers, health service providers, service users, researchers, and activists about women’s perception of contraceptive use towards empowerment and how these experiences would help in improving access and utilization of contraceptives by the current non-user women. Based on the study findings it can be concluded that in the life of Ethiopian women, the overall use of contraception has created a remarkable means to control their bodies, their reproduction and their fertility. Contraceptive use has freed women from worries and traps related to unplanned and unwanted pregnancies and childbirth. It has opened wide opportunities for women and it has offered “peace and stability” in their lives. The study recommends introducing a clear strategy that allows the encouraging experiences of current service-user women to be shared with their non-user counterparts in order to ensure the expansion and sustainability of contraceptive service.

Supporting information

S1 file. data analysis flow diagram adapted from ipa (smith, et al, 2009, pp. 82–100.)..

https://doi.org/10.1371/journal.pone.0203432.s001

S2 File. Transcription of individual in-depth interview.

https://doi.org/10.1371/journal.pone.0203432.s002

S3 File. Transcription of FGD.

https://doi.org/10.1371/journal.pone.0203432.s003

S4 File. IRB document.

https://doi.org/10.1371/journal.pone.0203432.s004

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• Published: 05 January 2021

Knowledge and attitudes towards contraceptives among adolescents and young adults

• Aanchal Sharma   ORCID: orcid.org/0000-0002-9093-0513 1 , 2 ,
• Edward McCabe 3 ,
• Sona Jani 3 ,
• Anthony Gonzalez 4 ,
• Seleshi Demissie 5 &
• April Lee 3  

Contraception and Reproductive Medicine volume  6 , Article number:  2 ( 2021 ) Cite this article

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Despite endorsements supporting the use of intrauterine devices (IUDs) for adolescents and young adult women (AYA), they have limited knowledge about them Male partners can influence contraceptive decisions, however their perceived knowledge about IUDs is lower than their objective knowledge. We aim to establish current AYA baseline contraceptive knowledge and attitudes so providers can better target their sexual health educational interventions.

Females and males, aged 13 to 23 years old, from our suburban adolescent clinic, completed an anonymous survey that assessed their knowledge and attitudes towards methods of contraception, with an emphasis on the IUD.

Completed surveys totaled 130 (99 females/31 males). Demographic results revealed 31.3% Black/African-American, 30.5% Latino/Hispanic, 17.6% White, 3.0% Asian, and 14.5% Other. The majority of participants (80%) were sexually active. The majority (69.5%) stated they/their partner were currently using a contraceptive method; only 2.6% used IUDs. Half of females (56.6%) and 10.1% of males had heard of IUDs. Despite this, male and female participants lacked knowledge regarding specific IUD facts. Of the participants who had used emergency contraception (EC), only 6.4% knew the copper IUD could be used for EC.

Contraceptive knowledge deficits, especially regarding the IUD, continue to exist for AYA patients. Many participants stated they required EC despite “satisfaction” with their birth control method(s) and most were unaware that the copper IUD could be used as EC. These discrepancies highlight the importance of comprehensive contraceptive education for AYA patients. Enhanced and consistent contraceptive options counseling can help providers ensure that their AYA patients make well-informed decisions about family planning, thus improving their quality of life.

Plain English summary

In this study, we demonstrate that barriers of access, awareness and knowledge continue to exist for adolescents and young adults (AYA) when it comes to contraception. Specifically, despite awareness about the intrauterine device (IUD), AYA lack adequate knowledge regarding its utility. The results of our study highlight the need for comprehensive contraception educational initiatives. For example, placing an IUD for emergency contraception could then additionally provide ongoing contraceptive benefits. Curricula that highlight the dual use of the IUD could help AYA see the short- and long-term benefits of using the IUD. This study assesses the baseline contraceptive knowledge and attitudes of AYA, which could inform and help healthcare providers tailor the sexual health education they provide their AYA patients. This would ultimately help AYA patients to overcome the barriers they face when choosing contraceptive methods that are best suited for them. This study affirms the current contraceptive knowledge and beliefs of AYA patients and serves as a jumping-off point for education and provision of contraceptive options counseling.

Introduction/background

The American College of Obstetrics and Gynecology (ACOG) has recommended intrauterine devices (IUDs) as first-line contraceptive choices for parous and nulliparous adolescents [ 1 ]. The American Academy of Pediatrics (AAP) endorses the use of IUDs as contraception to parous adolescents and to those who consistently protect themselves against sexually transmitted infections (STI) [ 2 ]. IUD use has increased over the past decade; however, overall U.S. IUD use remains low [ 3 , 4 , 5 ]. Copper IUDs can also function as emergency contraception (EC), yet its use as such remains limited [ 6 ]. Existing research has revealed that young women have limited knowledge about and access to IUDs [ 7 ]. Despite its effectiveness, overall use of IUDs in the U.S. remains low. Only 12% of current contraceptive users reported long-acting reversible contraception (LARC) use between 2011 and 2013 [ 8 , 9 ]. Studies have explored the reasons for the continued low rate of use and insertion of the IUD in adolescents and young adults despite the recognition that the IUD is a safe and effective contraceptive method [ 10 , 11 ].

Whitaker et al. found that only 40% of 144 female participants aged 14–24 had heard about IUDs; once educated, they began to think positively about IUDs [ 7 ]. However, awareness is not enough. In a 2012 study done by Barrett et al., they found that only 39.4% of subjects who had heard about the IUD were able to identify its features [ 12 ]. Awareness and perceived knowledge of IUDs among males is low in comparison to condoms and birth control pills [ 12 ]. Since male partners can influence the contraceptive decision-making process, it is important that studies are done to understand their perspectives.

This study aims to understand baseline contraceptive knowledge and attitudes of adolescents. This understanding will help healthcare providers improve sexual health education and overcome barriers faced by patients when choosing contraceptives methods that are best suited for them.

Subjects were recruited from Staten Island University Hospital’s adolescent clinic. The study was offered to all patients in this clinical setting, which included male and female patients, aged 13 years old to 23 years old. The study was offered to all new and existing patients over a six-month period, from March 2018 to August 2018. Potential participants were provided with a written document containing information regarding the study and provided verbal consent if they chose to participate. They then completed a twenty-minute anonymous survey, written in English, that assessed their knowledge and overall attitudes towards different methods of contraception, with an emphasis on the IUD. Inclusion criteria consisted of age between 13 to 23 years old and the ability to read and comprehend in English.

The survey consisted of five questions regarding sexual history (including sexually transmitted infection history, pregnancy history, contraception use), three questions about emergency contraceptive use, a section on knowledge about birth control methods which consisted of yes/no and true/false/“I don’t know” questions, and a section on knowledge about the copper IUD which consisted of true/false/“I don’t know” questions. The survey also included demographic questions regarding age, gender, educational level, race/ethnicity, and health insurance status.

The primary objective of this study was to determine adolescent and young adult knowledge of the copper intrauterine device (IUD) as a method of both emergency and long-acting contraceptive method. Assuming that the expected prevalence of knowledge of the copper IUD among adolescents aged 13 to 23 years old is 50%, we estimated that a sample size of approximately 100 subjects would provide us with a two-sided 95% confidence interval for the true prevalence that would extend 10% from the observed prevalence. Within this clinical setting, a total of 131 participants completed the survey. Of the completed surveys, 130 completed surveys met criteria for inclusion in this analysis. One subject was excluded because the participant’s age was beyond the study’s range.

The study design received Northwell Health Institutional Review Board approval prior to implementation. Participants provided verbal informed consent prior to completing the survey. Data collection involved investigators entering responses from completed surveys into a password-protected research database (REDCap). Only investigators listed on this study had access to the data.

Statistical analysis

Demographic and clinical characteristics for the study population were summarized using means with standard deviations for continuous variables and frequencies with percentages for categorical variables. Differences between groups in continuous variables were estimated with independent-sample t test. For categorical variables, either Chi-square test or Fisher’s exact test were used as appropriate. All tests were two-tailed and Differences were considered significant at P  <  0.05. All statistical analyses were performed using SAS software (Statistical Analysis Systems Inc., Cary, NC, USA) Version 9.3.

There were 99 female participants (76.2%) and 31 male participants (23.8%). The mean age of participants was 18.3 years old. The majority (65.3%) of respondents were aged 18–23 years old and about one third (34.7%) were aged 13–17 years old. A majority of respondents were either in high school (38.5%) or college (44.3%). Demographic results revealed 31.3% Black/African-American, 30.5% Latino/Hispanic, 17.6% White, 3.0% Asian, and 14.5% Other. A majority of respondents had health insurance, either private (25.6%) or public (40.2%).

The majority (80%) of participants were sexually active. The majority (82.8%) reported having partners of the opposite sex, 14.1% reported having with partners of the same sex, and 3.0% reported having both partners of the same and opposite sex. Most (69.5%) participants stated they or their partner were currently using a contraceptive method. Of those using birth control, 71% used condoms, 38% used oral contraception pills (OCP), while only 2.6% used IUDs. Approximately one third (36.4%) of total respondents reported a history of EC use by them or their partner(s). The majority (90.5%) of total respondents reported no history of STIs and 90.4% reported no history of pregnancies in themselves or their partner(s).

Most of the participants surveyed were aware of contraceptive methods. Survey results indicated that 100% were aware of male condoms; 89.9% were aware of female condoms; 92.2% were aware of OCPs; 66.7% were aware of IUDs; 63.3% were aware of hormonal implants; 76.2% were aware of injectable contraceptive hormones; 72.1% were aware of hormonal vaginal rings; and 64.8% were aware of hormonal contraceptive patches. Of those who responded that they had heard of the IUD, 84.9% were females and only 15.1% were males [Table  1 ]. Of the participants who responded that they had heard of the IUD, 90.7% were sexually active, 72.1% stated that they themselves or their partner(s) were using a form of contraception, and 49.4% stated they or their partner(s) had used EC in the past ( p  <  0.001) (Table 1 ).

Almost half (49.2%) of participants who responded that they were satisfied with their method of birth control had used EC in the past ( p  <  0.001) (Table  2 ). Of those with a history of EC use by themselves or their partner(s), 83.0% reported that they or their partner(s) were using a method of birth control ( p  <  0.001) (Table  3 ). Only 17.8% who reported a history of EC use knew the copper IUD could be used for EC ( p  <  0.001) (Table 3 ).

The awareness of the IUD was also specifically assessed by gender, sexual history, birth control use, and EC use. Of those who had heard of the IUD, 90.7% reported history of sexual activity and 49.4% reported history of EC use by them or their partner(s) ( p  <  0.001) [Table 2 ]. Despite having heard of IUDs, both male and female participants lacked knowledge regarding the utility of the IUD, whether or not they were sexually active. (Table  4 ) Only 14.1% of those who had heard of the IUD knew that it could be used as EC ( p  <  0.001) (Table 4 ).

Participants were provided with an educational piece at the end of the survey, which stated: “The Intrauterine Device (IUD) is a small T-shaped device about 1 inch long. It is a very effective method of birth control that your health care provider inserts into the uterus. Non-hormonal (copper) and hormonal versions are available. The non-hormonal or copper version can be left in place for up to 10 years. The hormonal version can be left in place for up to 3 to 5 years.” They were subsequently asked if they would use and/or recommend the IUD as a form of birth control. Approximately half of the participants remained neutral despite receiving the education and some provided feedback on their decisions. Some participants listed common misconceptions as their reasons against choosing the IUD in their comment section of the survey. Some participants commented that they still did not have enough knowledge regarding the IUD in general and expressed reluctance to use it or recommend to others.

Participants were also provided with information regarding the copper IUD’s function as form of EC. The statement “Studies have shown that the copper IUD is the most effective form of emergency contraception” was provided to the participants. They were subsequently asked if they would use or recommend the copper IUD as a form of EC. Almost half of the participants remained neutral despite receiving this information and some provided feedback on their decisions. The provided feedback did reveal that some participants did feel like the copper IUD would be a good option for EC after reading the information about the efficacy of the copper IUD.

The results of this study showed that the knowledge base of participants in this study was significantly lacking. When participants were asked about specific IUD contraceptive information, a majority of respondents answered with “I don’t know”. This indicated a gap in the information being presented to this population. Though many claim awareness of the IUD, they failed to understand its function or its side effects. The results of this study were similar to the 2015 study performed by Marshall et al., which found that awareness and perceived knowledge of IUDs among males was low in comparison to condoms and birth control pills [ 12 ]. However, the same study had also shown that young men’s perceived knowledge of IUDs was lower than their objective knowledge, whereas this study reveals that most males did not know much about the utility of the IUD [ 12 ].

Our results revealing only 2.6% of our participants using IUDs mirrored previous studies that demonstrated the low utilization of IUDs in the United States (3–5, and). All of the study participants who had a history of EC use had used emergency contraception in the oral pill formulation. A significant percentage of participants were unaware that the IUD could also be used as a form of EC. Efficacy should play a role in satisfaction with one’s birth control; however, if EC is being accessed, the birth control method may be clearly ineffective. This was consistent with previous studies that have shown that the use of the copper IUD as EC remained limited [ 6 ].

Most participants remained “neutral” after reviewing an education section of the survey on the efficacy of the copper IUD as a contraceptive method. However, the positive responses to the education section of the survey on the efficacy of the copper IUD as a good EC option confirmed the importance of distributing factual written information to adolescents and young adults in order to expand knowledge. Provision of written information should create an opportunity to facilitate this reproductive health decision-making process by stimulating a discussion with their health care provider or health educator.

One strength of this study is that it included male as well as female participants. Another strength of this study is that the survey included questions regarding sexual orientation and gender of sexual partners. These variables have not usually been included in earlier contraception studies.

Our study is not without limitations. One limitation of this study was the small participant size. Our study population was also primarily of one geographical region located in a greater urban community. Further, our survey was only offered in English and required participants to be able to read in English. With a larger and more diverse study population, we might determine other factors involved in the reproductive health decision-making process.

Barriers continue to exist for adolescents and young adults when it comes to contraception - these include, but are not limited to: access, awareness, and knowledge. The IUD remains the first-line contraceptive method offered as recommended by ACOG and the AAP. This study shows that despite awareness about the IUD, adequate knowledge is lacking among adolescents and young adults regarding its utility. The results of this study highlight the importance of committed and consistent comprehensive contraceptive education interventions for adolescent and young adult patients. Future research should include an assessment of the sources of information used by adolescents and young adults to attain their contraceptive knowledge as well as whether or not they received sexual health education as part of their school curricula. Enhanced contraceptive options counseling can help providers ensure that their patients make well-informed decisions about contraceptive methods, thus improving their quality of life.

Availability of data and materials

The datasets during and/or analyzed during the current study available from the corresponding author on reasonable request.

Abbreviations

American Academy of Pediatrics

American College of Obstetrics and Gynecology

Adolescents and young adults

Emergency contraception

Intrauterine device

Oral contraception pill(s)

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Acknowledgements

Not applicable.

Ethics approval and consent to participants

The study design received Northwell Health Institutional Review Board (IRB) approval prior to implementation. IRB #: 17–0802.

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Aanchal Sharma

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Edward McCabe, Sona Jani & April Lee

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AS, AL, and EM were responsible for data collection and analyzed and interpreted the patient data. SJ assisted in data collection. SD performed the statistical analysis. All authors were involved in the conceptualization of this study. All authors read and approved the final manuscript.

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Sharma, A., McCabe, E., Jani, S. et al. Knowledge and attitudes towards contraceptives among adolescents and young adults. Contracept Reprod Med 6 , 2 (2021). https://doi.org/10.1186/s40834-020-00144-3

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Contraception and Birth Control Research Activities and Advances

NICHD relies on several organizational units to study different aspects of contraception, from the biological mechanisms of different methods to the relevant decisions and behaviors of individuals and couples. The information below describes a few of these activities.

Institute Activities and Advances

NICHD has long been a source of funding for and expertise on contraception research. Extramurally, this expertise and support is led by what is now the Contraception Research Branch (CRB) , although it has had slightly different names over the years. For some time, the CRB has focused on supporting and conducting research in contraceptive discovery and development, including dual-use methods that prevent both pregnancy and sexually transmitted diseases (STDs) . The Branch is the largest source of support for research on contraceptive development within the federal government. It has responsibility for discovery, development, and evaluation of contraceptive agents.

The CRB uses a combination of grants and contracts to support and/or conduct activities including (but not limited to):

• Phase I, II, III, or IV clinical trials to evaluate the safety and efficacy of new contraceptive methods for women and men
• Research to develop methods for male contraception, including hormonal and nonhormonal control of sperm production and/or sperm function
• Basic and translational contraceptive research and development that may lead to new hormonal or nonhormonal methods for inhibiting ovulation or fertilization
• Experimental studies in animals to determine the safety and efficacy of novel potential contraceptive agents
• Research to define optimal formulations and dosages of contraceptive agents, spermicidal microbicides, and therapies (in animals and humans)
• Projects, as appropriate, on health effects related to contraceptive use and its relationship with other health issues, such as cancer
• Expertise about contraception and contraceptives that contributes to discussions, reports, and evidence-based recommendations, including those of the Cochrane Collaboration and the World Health Organization

The CRB addresses many of these research topics through cooperative agreements with research centers and research networks. These collaborative approaches are described in the Other Activities and Advances section.

Other extramural Branches—such as the Population Dynamics Branch (PDB) , the Fertility and Infertility (FI) Branch , and the Gynecologic Health and Disease Branch (GHDB) —study different aspects of contraception, but not development or testing of contraceptive agents. For example:

• PDB funds research on demographic, social, and behavioral aspects of sexual behaviors and their relationship to contraceptive use and non-use in both domestic and international populations. These efforts include studies of the determinants and consequences of contraceptive use in men and women, and basic and interventional research on the sexual transmission of HIV and other STDs. A particular focus of Branch-funded research is the interrelationships among pregnancy, pregnancy prevention, and prevention of STDs.
• The FI Branch supports research to alleviate human infertility, uncover new possible pathways to control fertility, and expand fundamental knowledge of processes that underlie human reproduction. Within this context, the FI Branch studies molecular and basic mechanisms of reproductive processes as a way to regulate fertility.
• GHDB supports basic, translational, and clinical research programs related to gynecologic health throughout the reproductive lifespan, starting at puberty and extending through the early menopause. Branch projects include studies to understand and treat gynecological problems, such as endometriosis, uterine fibroids, and heavy menstrual bleeding, including using contraceptive agents in these treatments.

In 2014 to 2015, NICHD convened an expert panel, comprising experts in basic, clinical, and behavioral research and representatives of industry and non-governmental organizations. The panel was charged with assessing the past accomplishments and impact of NICHD's contraceptive research initiatives, the current status of contraception research at and funded by NICHD, and suggestions for future activities and directions in contraception research. Activities of the CRB, PDB, and FI Branch were the focus of the panel's efforts.

The panel presented its findings to the NICHD advisory council in January 2015, and NICHD is in the process of implementing some of the panel's findings and ideas. You can read more about the panel and its findings at Assessment of the Contraceptive Research Activities of the NICHD: Executive Summary (PDF - 138 KB).

The Cell Regulation and Development Affinity Group , part of the Institute's  Division of Intramural Research (DIR) , investigates the molecular basis of peptide hormone control of gonadal function and is working on research to support the development of a male contraceptive.

As NICHD continues shifting the priorities of its various components, its commitment to supporting and conducting contraception research—including development of new contractive compounds—remains.

Other Activities and Advances

• The ability of progestin- and testosterone-based topical gels to inhibit sperm production to provide hormonal contraception for men
• A progesterone receptor modulator, CDB-2914, as an emergency oral contraceptive for women when taken within 72 hours of unprotected intercourse
• The effectiveness of a new female condom to prevent both pregnancy and STDs
• Progestin-based compounds that can prevent pregnancy without increasing the risk of blood clots and other venous thromboembolism-type conditions, especially in obese women
• A progestin- and estradiol-releasing vaginal ring that would be an effective contraceptive without increasing the risk of blood clots and other venous thromboembolism-type conditions, especially in obese women
• Developing a male contraceptive that inhibits an enzyme needed to produce sperm
• Developing a vaginal ring that acts as a contraceptive and also promotes brain health
• Understanding how egg cells develop and mature and how they are released to be fertilized
• Developing new delivery methods for contraceptive agents
• Developing dual-use compounds that protect against sexually transmitted infections and pregnancy
• Conducting translational research to identify or optimize male contraceptive products
• Developing nonhormonal contraception methods that inhibit ovulation
• How mechanisms regulating sperm maturation might be targeted by novel male contraceptives
• How sperm development could be inhibited using l targets, such as by disrupting the tight junctions between Sertoli cells and germ cells
• Testing of injectable form of acyline, a male hormonal contraceptive, to assess safety and ability to suppress spermatogenesis
• Development of an oral contraceptive for men, H2-gamendazole

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birth control , the voluntary limiting of human reproduction , using such means as sexual abstinence , contraception , induced abortion , and surgical sterilization . It includes the spacing as well as the number of children in a family.

Birth control encompasses the wide range of rational and irrational methods that have been used in the attempt to regulate fertility , as well as the response of individuals and of groups within society to the choices offered by such methods. It has been and remains controversial. English economist and demographer Thomas Malthus famously raised the general issue of population control in the 18th century with his theory that the number of people in the world will always tend to outrun the food supply, meaning the betterment of humankind is impossible without stern limits on reproduction. This thinking is commonly referred to as Malthusianism . Coining the phrase "birth control" was American reformer Margaret Sanger in 1914–15 and, like the social movement she founded, the term has been caught up in a quest for acceptance, generating many synonyms: family planning , planned parenthood, responsible parenthood, voluntary parenthood, contraception, fertility regulation, and fertility control.

(Read Thomas Malthus’s 1824 Britannica essay on population.)

Human reproduction involves a range of activities and events, from sexual intercourse through birth , and depends as well on a series of physiological interactions, such as the timing of ovulation within the menstrual cycle . The visible events are central to the transmission of life and have been subject to social and religious control. The invisible factors in human reproduction gave rise early on to speculation and in modern times have become the topic of scientific investigation and manipulation. New knowledge relevant to birth control has diffused at different rates through various social groups and has not always been available to those with the greatest need. Hence, the conflicts and controversies surrounding birth control have been complex and impassioned. The disagreement over birth control arises in part from the debate over what is natural and what is artificial (and, to some, unacceptable). For information on human reproduction in general see reproductive system, human, and pregnancy .

At first glance the species Homo sapiens appears to have low potential for reproduction. Puberty begins late, pregnancy is long, normally only one baby is delivered at a time, and lactation can continue for several years. Yet on the global level there are many more births than deaths every year; in 2015, for example, there were 141 million births compared to just 57 million deaths. In addition, a large percentage of the world’s population lives in urban areas, often at extremely high population densities. In experiments, when mammals are placed in crowded conditions the age of sexual maturity rises, the interval between pregnancies increases, and infant mortality jumps, leading to slower growth in the population. Among humans in analogous crowded conditions, however, in the absence of artificial birth control the opposite situation arises.

In many cases ovulation does not take place in the first several cycles after the onset of menstruation (menarche). Once a woman is fertile, social factors determine whether she is exposed to the opportunity to become pregnant. In preindustrial Britain, couples were expected to form their own nuclear group upon marriage, and many a first-time bride was in her later 20s. By contrast, in contemporary Third World societies that encourage extended families, girls often marry in the early teens.

In all mammals whose reproduction is not tied to seasonal changes, physiological mechanisms ensure the optimum spacing of pregnancies. In Homo sapiens, as in other primates, breast-feeding provides the basis for nature’s own method of birth control. In the few remaining societies of hunters and gatherers , whose way of life may represent the conditions under which most of human evolution took place, women nurse their babies frequently and ovulation and menstruation are suppressed for two to three years after birth. Nomadic women of the !Kung , a group of the San people of southern Africa, use no contraceptives but have a mean interval between births of 44 months and an average of four or five deliveries in a fertile lifetime. Modern methods of birth control substitute for the control over fertility once provided by lactation and permit a degree of control over human reproduction not previously available.

The combination of high infant mortality with relatively low fertility associated with traditional patterns of breast-feeding kept population growth in preagricultural human societies virtually static. Ten thousand years ago the world’s population may have stood at 10 million. Since that time natural restraints on human reproduction have broken down at an accelerating pace. By the beginning of the Christian Era the world’s population was perhaps 300 million. In the mid-1980s it passed the 5 billion mark. Since the Industrial Revolution , and with intensely increasing pressure in the past century, both individuals and societies have had to make important decisions about the use of birth control.

Expanding access to birth control is the surest way to defend women’s right to choose

Subscribe to the center for economic security and opportunity newsletter, isabel v. sawhill and isabel v. sawhill senior fellow emeritus - economic studies , center for economic security and opportunity kai smith kai smith research assistant - the brookings institution, economic studies.

July 30, 2024

The overturning of Roe v. Wade and this term’s Supreme Court abortion cases have understandably kept attention riveted on abortion . But while the abortion battle rages on, people are losing sight of the second front of the war to secure women’s reproductive autonomy: birth control.

As state abortion bans proliferate in the post-Roe era, the use of reliable birth control to prevent unintended pregnancies is more crucial than ever. Moreover, defenders of reproductive rights now must guard against an additional challenge—the offensive far-right conservatives are mounting against contraception.

Unplanned pregnancy is more common than most people realize. According to the latest data from the Centers for Disease Control (CDC), 42% of all pregnancies are unintended, meaning that the pregnancy was either unwanted or seriously mistimed.

While abortion is an important line of defense in preventing unplanned parenthood, it should be a last resort. The easiest way to prevent unplanned parenthood is to prevent an unintended pregnancy from occurring in the first place.

There are compelling reasons to support the use of effective birth control. A long and robust economic literature has shown that improving access to contraception reduces maternal morbidity and mortality. It also leads to healthier babies, less child poverty, better living circumstances for children, and improved educational and career opportunities for women.

In addition, birth control offers the most politically unifying approach to secure women’s reproductive autonomy. While just over one-third of the U.S. public doesn’t think abortion should be legal under any or most circumstances, nearly 9 in 10 approve the use of contraception, including 86% of Republicans. Birth control is also a more effective way to reduce abortion incidence than current state-level abortion bans which so far have not translated into fewer abortions nationwide . But if unplanned pregnancies essentially disappeared, there would be vanishingly few abortions.

And yet, despite birth control’s benefits and broad popularity, some conservatives are now targeting contraception.

Supreme Court Justice Clarence Thomas opened the door to these attacks when he argued that the same legal reasoning used to overturn Roe implies that “in future cases” the Court should “reconsider” Griswold v. Connecticut, the landmark case that established the Constitutional right to contraception in 1965. Since then, legislation to ban or restrict access to certain forms of contraception has already been discussed or proposed in Arkansas, Idaho, Louisiana, Michigan, and Missouri.

The Heritage Foundation as part of its Project 2025 initiative has called for a potential future Trump administration to restrict access to certain types of birth control. When asked about the topic in a recent TV interview , former President Trump said he was “looking at” policies that would restrict access, adding that “some states are going to have different policy than others.” He later walked back those comments, but many of Trump’s actions as president, including his decision to halve the patient capacity of the Title X program that provides affordable birth control and related services, foreshadow what may be his real intentions.

Senator Chuck Schumer recently led an effort to codify the right to contraception nationwide. All but two Senate Republicans present voted against the measure.

Central to Republicans’ attacks against contraception have been efforts by anti-abortion religious groups to falsely equate certain forms of birth control with abortion. That position is contrary to the consensus among medical experts that contraception, unlike abortion, does not terminate pregnancy and instead prevents pregnancy from occurring in the first place. The American College of Obstetricians and Gynecologists, for example, has stated : “None of the FDA-approved contraceptive methods are abortifacients because they do not interfere with a pregnancy and are not effective after a fertilized egg has implanted successfully in the uterus.”

Amid far-right attacks, defenders of women’s reproductive autonomy should focus more attention on effective contraception.

As a safe and virtually foolproof form of birth control, the surging popularity of long-acting reversible contraception (LARC) which includes IUDs and implants is especially promising. For a typical couple using a condom, the risk of pregnancy within five years is 63%. For those relying on the pill, it is 38%. With a LARC, it is less than 4%. LARCs change the default so that users can “set it and forget it” without losing sleep over concerns about getting pregnant.

Many women are taking notice. The share of women using LARCs increased sevenfold between 2002 and 2018. LARCs are now the third most common contraceptive method used by women after sterilization and the pill. Early evidence suggests more women and men are seeking out effective contraception including LARCs in response to the overturning of Roe v. Wade.

Beyond the increased use of LARCs, the first-ever over-the-counter birth control pill hit the shelves of major drug stores earlier this year. That is important because nearly one-third of women using the pill say they have missed taking their dosage because they were unable to get their next supply in time.

But what more could be done?

Primary care physicians should screen all women of reproductive age for their pregnancy intentions to encourage patients who don’t want to get pregnant to focus on the risks of sex and their contraceptive options for reducing them. We also need to ensure all healthcare providers, not just doctors, are trained in the use of LARCs, have them on hand, and can provide same day insertion. Where these approaches have been tried, unintended pregnancy and abortion rates have both declined dramatically .

In addition, more funding for Title X is needed. One rigorous study has shown that eliminating cost sharing for low-income patients seeking birth control would significantly reduce unintended pregnancies and abortions and save more than one billion dollars in Medicaid expenses in the first year alone.

The overturning of Roe v. Wade was a Pandora’s box that unleashed an invigorated assault on women’s fundamental freedoms. As the onslaught intensifies, defenders of women’s reproductive autonomy must fight back to fortify the first and strongest line of defense in protecting a woman’s right to choose if and when to seek a pregnancy.

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Exploring Readiness for Birth Control in Improving Women Health Status: Factors Influencing the Adoption of Modern Contraceptives Methods for Family Planning Practices

Adnan muhammad shah.

1 Department of Computing Engineering, Gachon University, Seoul 13120, Korea; [email protected]

2 Department of Management Sciences, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad 44320, Pakistan

3 Charles E. Schmidt College of Science, Florida Atlantic University, Boca Raton, FL 33431, USA

KangYoon Lee

Javaria nisa mir.

4 Faculty of Management Science, Riphah International University, Rawalpindi 46000, Pakistan; moc.liamg@110rimairevaj

Associated Data

The data used to support the findings of this study are available from the corresponding author upon request.

Background: Pakistan is the world’s sixth most populated country, with a population of approximately 208 million people. Despite this, just 25% of legitimate couples say they have used modern contraceptive methods. A large body of literature has indicated that sexual satisfaction is a complex and multifaceted concept, since it involves physical and cultural components. The purpose of this study is to investigate the impact of influencing factors in terms of contraceptive self-efficacy (CSE), contraceptive knowledge, and spousal communication on the adoption of modern contraceptive methods for family planning (FP) under the moderating role of perceived barriers. Methods: Data were collected using an adopted questionnaire issued to married women of reproductive age belonging to the Rawalpindi and Neelum Valley regions in Pakistan. The sample consisted of 250 married women of reproductive age. SPSS was used to analyze the respondents’ feedback. Results: The findings draw public attention towards CSE, contraceptive knowledge, and spousal communication, because these factors can increase the usage of modern methods for FP among couples, leading to a reduction in unwanted pregnancies and associated risks. Regarding the significant moderation effect of perceived barriers, if individuals (women) are highly motivated (CSE) to overcome perceived barriers by convincing their husbands to use contraceptives, the probability to adopt modern contraceptive methods for FP practices is increased. Conclusions: Policymakers should formulate strategies for the involvement of males by designing male-oriented FP program interventions and incorporating male FP workers to reduce communication barriers between couples. Future research should address several other important variables, such as the desire for additional child, myths/misconceptions, fear of side effects, and partner/friend discouragement, which also affect the adoption of modern contraceptive methods for FP practices.

1. Background

Pakistan is the world’s sixth most populated country, with a population of 208 million people at the time of writing [ 1 ]. The Pakistani government is concerned about population growth because it is related to economic and social consequences of unrestrained expansion [ 2 , 3 ]. Failure to control the rate of reproduction and rapid population expansion has negative consequences for development indices such as education, poverty, and life expectancy, especially for mother and child health [ 4 ]. Beginning in the 1960s, the country became a pioneer in the field of family planning (FP) among developing countries. Fifty years later, the program is still struggling to increase the use of modern contraceptives. The current contraceptive prevalence rate in Pakistan is 34%, compared to 62% in India and 56% in Bangladesh [ 5 , 6 ]. For years, the low and stagnant prevalence of contraception in Pakistan has been a source of academic debate [ 7 ]. Much has been written about Pakistan’s sluggish adoption of modern contraception methods, highlighting cultural hurdles, inconsistent political support, and service delivery failures [ 7 , 8 ]. The majority of the research has focused on service delivery problems, with the assumption that increasing contraceptive provision would improve contraceptive use [ 8 , 9 , 10 , 11 ].

The gradual increase in contraceptive rates in Pakistan compared to other nations in the region has been a hotly debated topic among demographers and other academics, with many speculating that inconsistencies in political support and a lackluster FP policy are to blame [ 11 , 12 ]. Researchers recommend that communication between couples should be encouraged because it increases the adoption of FP practices [ 13 , 14 , 15 ]. A recent study indicated that there is a need for modern contraceptive prevalence in Pakistan, which requires an increased uptake of contraceptives (National Institute of Population Studies (NIPS)) [ 16 ]. Pakistan has been facing the issue of FP for decades [ 17 ]. About 17% of married women in Pakistan have modern contraceptive prevalence for FP, and this rate is higher among rural areas. The demand for FP has reduced over the last 5 years, currently at 52% whilst it was 55% in 2012–2013. Pakistan has a 34% contraceptive prevalence rate, and the use of modern contraceptive methods has not increased since 2013 [ 16 ]. The literature shows that knowledge on contraceptives has profound effects on the FP practices [ 18 ]. Due to a lack of appropriate knowledge about contraceptive methods, women cannot get desired results [ 19 ].

Women’s self-efficacy and knowledge about the appropriate use and the side effects of contraceptive methods, a couple’s communication, and combined decisions are positive predictors of contraceptive use [ 20 ]. Women’s education and power to make decisions are significantly associated with the use of contraceptives [ 21 ]. Previous literature has indicated low contraceptive use in Pakistan, and there is an urgent need to explore factors which can help to improve FP practices and modern contraceptive prevalence necessary for FP practices [ 22 ]. Contraceptive self-efficacy (CSE), contraceptive knowledge, and spousal communication are found to be associated with FP practices [ 23 ]. Self-efficacy theory suggests that an individual’s belief in his own competence to perfectly perform any behavior is affected by several moderators and barriers, either personal or social [ 24 ]. Therefore, researchers have suggested that while assessing self-efficacy, the impact of perceived barriers on health behavior estimation must be examined [ 25 ]. Researchers have also reported several reasons for why improving contraceptive knowledge might improve contraceptive use [ 26 ]. Spousal communication is the determinant of FP practices, but there is need to assess this connection in the context of developing countries [ 13 ]. Because a lack of communication and counselling is affecting couples’ and women’s decision-making ability regarding fertility preferences [ 14 ], the current study attempts to assess the impact of these variables on women’s perceptions regarding the adoption of modern contraceptive methods for FP practices.

Numerous economists and researchers continue to doubt Pakistan’s ability to significantly boost the adoption of modern FP practices because of religious norms, social liberalism, and preferences for large family systems. Therefore, several gaps are observed in the policies and structure of programs related to FP practices in Pakistan [ 8 , 11 ] and other developing regions [ 27 , 28 ]. The unavailability of contraceptives, especially in rural areas, users’ dissatisfaction, low service quality, lack of proper guidance concerning the methods selected, religious factors, and a lack of knowledge, funding, and collaboration between public and private sector facilities providing FP services have been quoted as barriers that cause a low prevalence of contraceptive measures [ 10 , 17 ]. Since the context of this study is Pakistan, it is worth noting that FP in Pakistan is entirely female-oriented [ 29 ]. Programs that target only a single sex tend to fail to achieve its targets [ 13 ]. Therefore, all these issues need to be investigated, because they are affecting population control activities in the country. The theoretical foundation of this study is based on a combined health belief model, social cognitive theory, and the theory of planned behavior. In this regard, this study attempts to examine different predictors in the adoption of modern contraceptive methods for FP practices. This study will provide a thorough understanding of these factors, which will be helpful for the control of fertility.

The current study aims to explore the impact of spousal communication, contraceptive knowledge, and CSE on the adoption of modern contraceptive methods for FP practices in a developing country context, such as Pakistan. In addition, the moderating role of perceived barriers is, for the first time, theorized and tested to determine the relationship between contraceptive knowledge, spousal communication, CSE, and the adoption of modern contraceptive methods for FP practices. The findings of the current study would be helpful for policymakers in implementing and revising policies to further improve FP programs.

The rest of the sections in the current study are arranged as follows: Section 2 presents a literature review and hypotheses; Section 3 covers the proposed methodology, including sample and data collection, the measurement of variables, common method bias, and control variables; Section 4 explains the data analysis and results; finally, Section 5 discusses the results of the study, sheds light on practical implications, and recommends a direction for future research.

2. Literature Review

2.1. contraceptive self-efficacy (cse) and family planning (fp) practices.

Levinson, as cited in [ 30 ], defined CSE as “it is the strength of a young woman’s conviction that she should and could exercise control within sexual and contraceptive situations to prevent an unintended pregnancy, if that is what she desires” (p. 9). Following the self-efficacy theory, the concept of CSE was developed to measure women’s self-efficacy and its impact on their reproductive health. The extant literature indicates that women with higher self-efficacy are more independent in the selection and practice of modern contraceptive methods [ 31 , 32 ]. CSE is important because it stimulates individual behavior related to the use of modern contraceptives, therefore helping to prevent major public health issues by prompting the use of modern contraceptives [ 31 ]. Contraceptive acceptance is higher among females with higher CSE [ 33 , 34 , 35 ]. CSE enables women to manage all resistance related to FP practices [ 25 ]. Findings from previous research also reveal that CSE increases contraceptive adherence [ 20 ]. The above explanations suggest that CSE is a strong predictor of the use of modern contraceptive for FP practices. Therefore, it can be hypothesized that:

Contraceptive self-efficacy has a positive impact on the adoption of modern contraceptive methods for FP practices .

2.2. Contraceptive Knowledge and Family Planning (FP) Practices

Contraceptive knowledge was defined by Nsubuga et al. [ 36 ] as “the state of awareness of contraceptive methods, any specific types and the source of contraceptive”. Contraceptive knowledge enables women to easily access FP services [ 37 ]. It is reported that counselling increases contraceptive awareness, which modifies people’s attitudes towards the use of contraceptives [ 38 ]. Efficient contraceptive knowledge helps in changing people’s perceptions and decisions about FP [ 39 ]. Researchers have also found that educated women are more aware of contraceptive methods and FP practices, which ultimately increases the use of contraceptives among females [ 40 ]. It is also reported that females with good contraceptive knowledge practiced different methods effectively [ 41 ]. In contrast, individuals with a lack of contraceptive knowledge will discontinue contraceptive use due to its side effects or method failures [ 42 ]. According to a recent survey, 3/4th of the overall urban population is aware of FP practices, but a low level of awareness among rural population was reported [ 16 ]. Well-aware and knowledgeable individuals regarding different contraceptive methods have a tendency to solve different FP issues [ 43 , 44 , 45 ], such as intercourse and the method not changing the woman’s menstrual periods [ 46 ], intrauterine device and implant [ 47 ], and female sterilization [ 48 ].

Contraceptive knowledge in terms of awareness about the available contraceptive methods helps people in choosing the best and effective contraceptives practices, and also changes people’s fertility preferences [ 49 ]. It has been noted that people who are aware of implants and breastfeeding as contraceptive methods were more interested in the adoption of modern contraceptive methods for FP practices [ 50 ]. Studies in the context of a developing country, such as Pakistan, highlighted the gap between contraceptive knowledge and FP practice [ 17 , 51 ]. This gap is because of a lack of knowledge about the benefits and availability, as well as misinformation, of modern contraceptive methods for FP practices. Major sources delivering contraceptive knowledge include healthcare centers, friends, family, and media [ 52 ]. Therefore, based on the available literature, it can be hypothesized that:

Contraceptive knowledge has a positive impact on the adoption of modern contraceptive methods for FP practices.

2.3. Spousal Communication and Family Planning (FP) Practices

Backman, as cited in [ 53 ], stated that “spousal communication in the marital dyad is generally defined as the frequency of discussion between spouses, as reported by one or both partners” (p. 5). Communication between spouses plays an important role in the continuous adoption of modern contraceptive methods for FP practices. Partner communication appeared as a topic of interest regarding FP practices. In this regard, researchers found a positive association between spousal communication and FP practices [ 54 , 55 , 56 ]. Another study reported husbands as key decision makers for getting access to health and FP services. A husband’s education level is significantly associated with the current use of contraceptives. The location of service providers, the quality of services, women’s age, and financial status also determine the use of contraceptives [ 4 ].

FALAH (Family Advancement for Life and Health) is already working on male involvement in FP programs. An analysis of program outcomes found that engaging Pakistani men in FP practices to support and encourage their wives to use FP services and introducing male contraceptive methods can increase the utilization and acceptance of FP practices among the population [ 57 ]. Similarly, Khan et al. [ 58 ] stated that husband approval is a strong predictor of the use of contraceptives. Spousal communication helps in coping with psychological barriers and reduces emotional strains that discourage the use of contraceptives [ 59 ]. It helps couples in decision making concerning an appropriate family size, and enhances positive intentions towards modern contraceptive methods for FP practices. Thus, it can be hypothesized that:

Spousal communication has a positive impact on the adoption of modern contraceptive methods for FP practices.

2.4. Moderating Role of Perceived Barriers

Glasgow [ 60 ] defined perceived barriers as “A person’s estimation of the level of challenge of social, personal, environmental, and economic obstacles to a specified behavior” (p. 1). In the literature, the concept of perceived barriers has been extensively used with the health belief model (HBM). Perceived barriers have been used in many theories, including HBM, social cognitive theory, and social-ecological theory [ 60 ]. The integrated impact of multiple barriers hamper women from accessing reproductive health services. The restricted mobility of women by family [ 42 ] and a lack of communication between couples are factors that hamper women from using contraceptives [ 61 ]. Additionally, barriers restrain women’s ability to practice contraceptive methods. Most of the time, women that desire to limit their fertility by using contraceptives are influenced by religious and cultural hindrances [ 11 , 62 ]. They have to face great resistance from social barriers comparative to financial issues [ 63 , 64 ].

Women’s perceptions about contraceptive use, fear of their husbands’ negative response, and FP practices are perceived as an unacceptable act by society; therefore, culture limits the use of contraceptives among women [ 65 ]. Another study conducted by researchers in Pakistan declared that reasons for not using contraceptives include a desire for a baby boy (19%), fear of a health risk (29%), and lack of partner support and consideration of them as un-Islamic (14%); similar findings were found in other studies [ 66 , 67 ]. Interpersonal violence [ 68 ], cost, shyness, desire for a baby boy and a large family size [ 69 ], fear of sin, sterility [ 70 ], misinterpretation, husband and in-laws disapproval, prevailing myths, and social norms are all factors that contribute to the low intention of adopting of FP practices [ 66 , 71 ].

Fear of privacy breach, stigmatization, and FP service providers’ attitudes negatively affect the adoption of modern FP practices among women, despite them having knowledge about contraceptive use [ 72 , 73 ]. Spousal communication increases FP practices, but in-laws’ pressure, low parity, and administrative issues weaken this relationship [ 74 ]. Men’s disinterest and lack of knowledge about contraceptives, female financially dependency, and physical violence discourage women to communicate with their husbands about FP practices, which ultimately causes the low prevalence or lack of use of contraceptive methods [ 75 ]. Despite having information about several available FP methods, a low use of contraceptives has been noted among couples of rural areas due to misconceptions about risks associated with contraceptive methods [ 76 ]. Family environments also define women’s behavior towards FP practices [ 77 ]. A woman’s autonomy to make decisions about any aspect of her life is strongly influenced by the stratified family structure [ 78 ]. All these barriers contribute towards modern contraceptive prevalence for FP practices, in which women do not want to conceive for a period of time but still do not use any contraceptives [ 79 ]. Based on the above literature, it is argued whether perceived barriers act as moderator in the relationship between CSE, contraceptive knowledge, spousal communication, and FP practices or not. Therefore, it can be hypothesized that:

Perceived barriers moderate the relationship between contraceptive self-efficacy and the adoption of modern contraceptive methods for FP practices.

Perceived barriers moderate the relationship between contraceptive knowledge and the adoption of modern contraceptive methods for FP practices.

Perceived barriers moderate the relationship between spousal communication and the adoption of modern contraceptive methods for FP practices .

The research model of the study is presented in Figure 1 .

Research model.

3. Methodology

3.1. sample and data collection.

Women of reproductive age are the main target of FP practices in Pakistan due to higher needs for the use of contraceptives at this age. The adoption of modern contraceptive methods for FP is a key variable in current research. Using a convenience sampling technique, data were collected from married women of reproductive age from the Rawalpindi and Neelum Valley regions in Pakistan through distributed questionnaires. Convenience sampling has the advantages of being inexpensive, efficient, and easy to use. We selected the aforementioned sampling locations because both these regions are highly prevalent in terms of FP practices. Additionally, the travel restrictions implemented during the COVID-19 outbreak made it difficult for the authors to visit other areas for data collection. We decided to collect data using both self-administered questionnaires and social circles from these areas to distribute our questionnaire to the relevant samples. A cover letter was attached, declaring the purpose of the research and asking participants at the time they join the study for relevant and historical information on spousal communication and decision making regarding FP practices. A screening question was also placed at the beginning of the survey to clearly ask whether respondents belonged to these regions and they knew the contraceptive methods used in FP practices. Confidentiality, anonymity, and voluntary participation were also ensured.

A total number of 340 questionnaires were distributed. The authors believe that the sampling size was appropriate due to the COVID-19 restrictions and respondents’ hesitation to respond to specific questions because of cultural and religious beliefs [ 11 ]. Out of the 292 questionnaires that were returned 42 were not useable, making the valid response rate 73.5%. The contraceptive prevalence rate in our sample was 41.28%.

As shown in Table 1 , the majority of the women participants were literate (86.8%), most were non-working (63.6%), the majority of the women were in the age range of 24 to 35 years (78.3%), and the majority of the women got married in the age range of 18–25 years (72%). Most of the participants were residents of a rural area (70%), and most were Muslim (95.6%). The majority of the participants’ husbands were literate (95.2%) and working (97.2%). Of the respondents, 48% of them had a maximum of two–three children and (25%) had four or more children. Of the women, 92% of them reported having a good health status and 72.4% reported that their husbands were the head of the household. Of the respondents, 62.3% responded that their husbands were highly involvement in decision making regarding pregnancy, while 64.8% responded that they have spousal communication regarding FP and birth spacing.

Socio-demographic characteristics of respondents.

3.2. Measurements

All the study variables were measured on a 5-point Likert scale. All constructs were measured on a Likert scale ranging from strongly disagree = 1 to strongly agree = 5.

Constructs such as contraceptive self-efficacy (CSE) were measured using a 7-item scale developed by Prata et al. [ 80 ]. One sample item which was measured was “I can use a modern contraceptive method to prevent pregnancy”. Contraceptive knowledge (CK) was measured by using a 7-item scale developed by Lincoln et al. [ 81 ]. One sample item which was measured was “I am aware that health education is important for women who want to use contraception”. Spousal communication (SC) was measured using a 5-item scale developed by Wegs et al. [ 82 ]. One sample item which was measured was “I and my spouse discuss things that happened during the day”. Modern FP practices were measured using a 7-item scale developed by Lincoln, Mohammadnezhad, and Khan [ 81 ]. One sample item which was measured was “I often use one of the contraceptives to prevent unplanned pregnancy”. Perceived barriers (PB) were measured using a 14-item scale developed by Sen et al. [ 83 ]. One sample item which was measured was “Contraceptive measures are too expensive for me”. The details of all constructs and their corresponding items are presented in Appendix A , Table A1 . According to the criteria defined by Fornell and Larcker [ 84 ], the composite reliability values for all constructs were above the threshold (i.e., 0.70).

3.3. Common Method Bias

A common bias test was performed by taking into account Harman’s single factor [ 85 ]. Five constructs with their corresponding non-removed items were tested using an exploratory factor analysis by Harman’s single-factor test and analyzed with an unrotated factor solution. It was shown that there is no question about the common method bias in the current research data due to no emerging factor being reported, and 41.451% (less than 50%) variance was documented for the first factor, as suggested by Podsakoff, MacKenzie, Lee, and Podsakoff [ 85 ].

3.4. Control Variables

A one-way ANOVA was performed to control the variation in the adoption of modern contraceptive methods for FP practices on the basis of demographic variables used in the study. Results obtained from one-way ANOVA (see Table 2 ) indicated no significant differences in the adoption of contraceptive methods for FP practices (dependent variable) across qualification (F = 0.880, p > 0.05), profession (F = 3.371, p > 0.05), age at time of marriage (F = 2.881, p > 0.05), religion (F = 1.495, p > 0.05), health status (F = 1.267, p > 0.05), husband’s qualification (F = 1.496, p > 0.05), husband’s profession (F = 0.897, p > 0.05), and head of household (F = 0.399, p > 0.05).

One-way ANOVA.

At the same time, the one-way ANOVA indicated significant differences in FP across region (F = 19.089, p < 0.05), area of residence (F = 19.089, p < 0.05), current age (F = 2.682, p < 0.05), and number of children (F = 7.984, p < 0.05). Subsequently, factors identified as significant were entered as control variables in step 1 of a regression analysis for a single dependent variable.

Means, standard deviations, scale reliabilities ( bold diagonal entries ) , and correlation matrices are presented in Table 3 . Reliabilities for all constructs were greater than the cutoff value (i.e., α ≥ 0.7), which indicates acceptable reliability [ 86 ]. The results also revealed that all the absolute values of the correlation coefficients and the VIF statistics for each individual variable are less than 0.5 and 10, respectively [ 86 ]. Hence, multicollinearity is not a serious problem in the study, and the results are reliable. Table 3 also indicates that CSE is significantly positively correlated with modern FP practices (r = 0.48, p < 0.01) providing support for proposed hypothesis 1. Contraceptive knowledge is significantly positively correlated with modern FP practices (r = 0.34, p < 0.01), which provides support for proposed hypothesis 2. Modern FP practices are significantly positively correlated with spousal communication (r = 0.22, p < 0.01), which provides support for proposed hypothesis 3. Perceived barriers are not correlated with modern FP practices (r = 0.092, p = ns). Control variables, such as area of residence, region, current age, and number of children are positively correlated with modern FP practices.

Means, standard deviations, correlations, and reliabilities.

Notes: n = 250; alpha reliabilities are given in parentheses. p < 0.05. S.D = standard deviation, CSE = contraceptive self-efficacy, CK = contraceptive knowledge, SC = spousal communication, PB = perceived barriers, Qual = qualification, Prof. = profession, AoR = area of residence, Reg. = region, CA = current age, ATM = age at time of marriage, Relig. = religion, HQ = husband’s qualification, HP = husband’s profession, NC = No. of children, HS = health status, and HH = head of household. **, correlation is significant at the 0.01 level; *, correlation is significant at the 0.05 level. ns = correlation is not significant.

A multiple regression analysis was run to check the relationship between variables in the proposed model of this study. Table 4 shows the results of the regression analysis for the controls, direct effects, and moderating variable. The findings reveal that control variables, such as area of residence (β = 0.126, p < 0.01), region (β = 0.256, p < 0.05), current age (β = 0.325, p < 0.01), and number of children (β = 0.258, p < 0.05) significantly influence modern FP practices. The results show a significant positive impact of CSE on the adoption of modern contraceptive methods for FP practices (β = 0.551, p < 0.001). Thus, hypothesis 1 is accepted. The regression analysis shows that there is a significant positive impact of contraceptive knowledge on the adoption of modern contraceptive methods for FP practices as (β = 0.226, p < 0.01); thus, hypothesis 2 is accepted. In addition, the results indicate that spousal communication has a significant positive impact on the adoption of modern contraceptive methods for FP practices as (β = 0.184, p < 0.01), thus leading towards the acceptance of hypothesis 3. Analysis shows that perceived barriers have no significant direct effect on the adoption of modern contraceptive methods for FP practices as (β = 0.049, p = ns).

Hierarchical moderated regression analysis.

Notes: ***, p < 0.001; **, p < 0.01; and *, p < 0.05. CSE = contraceptive self-efficacy, CK = contraceptive knowledge, SC = spousal communication, and PB = perceived barriers. ns = not significant.

Hypotheses 4, 5, and 6 were tested using moderated regression analysis. Where control variables were entered in step 1, independent and moderator variables were entered in step 2, and interaction terms were entered in step 3. Results show that in the third step after incorporating for interaction terms, such as contraceptive self-efficacy×perceived barriers, the results (β = 0.168, p < 0.05) lead to the rejection of hypothesis 4, that higher perceived barriers weaken the relationship between contraceptive self-efficacy and the adoption of modern contraceptive methods for FP practices in such a way that the relationship is weaker when the perceived barrier is high.

Result shows that FP practices in women with high CSE will be higher even in the presence of high perceived barriers. In addition, regression analysis shows that by incorporating interaction terms in the model for contraceptive knowledge×perceived barriers (β = −0.020, p = ns) and for spousal communication×perceived barriers (β = 0.037, p = ns) in the model, hypotheses 5 and 6 are not accepted. These results indicate that perceived barriers are not moderating the relationship between contraceptive knowledge and the adoption of modern contraceptive methods for FP practices or that between spousal communication and the adoption of modern contraceptive methods for FP practices.

The interaction effect in Figure 2 shows that the relationship between CSE and the adoption of modern FP practices was stronger in the presence of high perceived barriers (in dashed red line) than in the presence of low perceived barriers (in solid blue line); thus, hypothesis 4 is rejected.

Interactive effect of contraceptive self-efficacy and perceived barriers on FP practices. CSE = contraceptive self-efficacy; PB = perceived barriers.

5. Discussion

The purpose of this study was to investigate the causal effect of different factors (i.e., CSE, contraceptive knowledge, and spousal communication) that influence the adoption of modern contraceptive methods for FP practices. Additionally, the moderating role of perceived barriers was also examined in the relationships between aforementioned constructs [ 31 , 32 ]. The findings were in support of previous studies conducted by scholars [ 20 , 25 ], where similar findings were reported.

Contraceptive knowledge as awareness was found to have a significant positive impact on the adoption of modern contraceptive methods for FP practices. These findings were in line with previous studies findings [ 37 , 40 ]. This is because contraceptive knowledge among women encourages them to adopt modern methods for FP services and choose suitable method for practice. A good level of contraceptive knowledge improves the modern contraceptive prevalence. Contraceptive knowledge modifies people’s perceptions about FP practices [ 39 ]. Furthermore, the majority respondents were literate, so they valued contraceptive knowledge as an important factor for FP practices. Thus, it is quite logical to infer that the adoption of modern contraceptive methods for FP in Pakistan can be enhanced by increasing comprehensive knowledge about contraceptive measures among women.

Similarly, spousal communication also has a positive impact on the adoption of modern contraceptive methods for FP practices. Spousal communication is an effective way to involve males in FP practices and support women’s decisions about fertility preferences. Partner support and encouragement is a key determinant of FP practices [ 87 ]. The current findings were in line with previous studies [ 54 , 55 , 56 , 88 ]. As discussed in the literature, good spousal communication and encouragement by their partners allows women to make decisions about desired family size, usability, selection, and awareness of all available FP methods, which results in a reduction in contraceptive discontinuation and their low prevalence. This situation usually happens because of public dissatisfaction and a fear of opposition. Introducing male-oriented FP methods could help in increasing the uptake of FP practices by couples.

The results of moderated regression analysis show that the relationship between CSE and the adoption of modern contraceptive methods for FP practices is moderated by perceived barriers. Since the perceived barriers were used as moderators between the relationship of CSE and modern FP practices for the first time, the findings of the current study are supported by evidence from previous studies [ 20 , 25 , 61 ], where they declared that women with higher CSE are motivated and can convince men to use contraceptives. The adoption of any health behavior is dependent on individuals’ intentions to adopt that specific behavior. If an individual has strong intentions to practice or adopt a specific health behavior as well as the self-efficacy to overcome his/her perceived obstacles, the probability to adopt a specific health behavior increases [ 89 , 90 ]. As in the current study, participants reported higher CSE; therefore, the presence of barriers cannot reduce their intentions to practice modern FP methods.

The results of the interactive effect of perceived barriers and contraceptive knowledge show that perceived barriers do not moderate the relationship between contraceptive knowledge and the adoption of modern FP practices, which contradicts a proposed hypothesis. This result is in accordance with the common-sense model [ 91 ]. The model explains that human behavior is determined by the process of learning. Before adopting any health behavior, an individual assesses its pros and cons through cognition. For example, if individuals have to get treatment for a disease they will think about its cost, prognosis, and benefits, and then make decisions about action. Comprehensive knowledge about threats associated with health behavior reduces fear and leads to the adoption of that behavior [ 92 ]. As the participants of this study reported a higher level of contraceptive knowledge, it can thus be concluded, based on the previous literature, that high contraceptive knowledge among women helps them to make informed choices, overcome fears, and motivate them towards adopting modern FP practices.

The results of the interactive effect between perceived barriers and spousal communication were not significant, which shows that perceived barriers were not moderating the relationship between spousal communication and the adoption of modern FP practices. Since the literature shows that spousal communication about using contraceptives and involving the male partner in decision making about fertility preferences directly influences efforts for limiting fertility, they help women in overcoming perceived barriers as the fear of opposition is being shared by both partners [ 93 ]. Evidence from previous studies [ 94 , 95 ] also reveals that dynamics of spousal communication have a positive effect on contraceptive behavior; thus, these result are in line with the findings of the current study. Spousal discussion boosts modern FP use and consequently reduces fertility and maternal mortality rate.

5.1. Practical Implications

The findings provide several implications for practice. It is recommended that policymakers should incorporate modern contraceptive FP program models as a strategy to enhance the contraceptive prevalence rate. Special consideration should be given to spousal communication, and couples should be encouraged to discuss the adoption of modern contraceptive methods for FP practices. Awareness campaigns should be launched that highlight the benefits of spousal discussion about ideal family size, societal pressures, complications related to closely spaced deliveries, unsafe abortion, the risks of maternal and child mortality, malnutrition among children, and modern FP practices. Policymakers should also formulate policies for male involvement in modern FP programs across the country by introducing improved male-oriented methods and incorporating male FP workers to reduce communication barriers and shyness (as shown by a program that has been launched by FALAH in Pakistan and reported positive outcomes) [ 57 ]. FP program stakeholders should focus on promoting contraceptive knowledge among women to promote the adoption of modern contraceptive methods for FP practices.

Understanding different factors in the adoption of modern FP practices is necessary in formulating more suitable policies for public health [ 8 , 96 ]. As the use of FP is high in educated and urbanized people, there is a need to focus on slums and rural areas with a low literacy rate as well as how their perceptions about ideal family size change [ 88 ]. As the findings indicated that improving contraceptive knowledge leads towards FP practices, this study provides baseline information to policymakers towards the value of gaining comprehensive knowledge to increase the use of FP [ 97 ]. This study also draws public attention towards spousal discussion because it can increase the usage of modern methods for FP among couples, leading to a reduction in unwanted pregnancies and associated risks. In addition, our findings highlight the need for proper fund allocation as well as the provision of training and refresher courses for female health workers [ 98 ]. Furthermore, counselling intervention should be introduced to involve in-laws in programs to reduce barriers toward the adoption of modern methods for FP practices [ 99 , 100 ]. This study attempts to assist the Pakistani government in reaching its national development goals of enhancing maternal and reproductive health through the increased use of modern contraceptives.

5.2. Limitations and Directions for Future Research

This paper has several limitations. First, the findings of current study were predisposing to recall bias as data were self-reported by respondents rather than dyads, etc. Future studies should ensure that the way questions are worded does not influence the answers of participants due to the possible risk of recall bias. Second, as the majority of the respondents belonged to the Rawalpindi and Neelum Valley regions, the findings may not be generalizable due to the smaller sample size and convenience sampling technique using a specific targeted group, which lack external validity. Future studies should run the analysis using a larger dataset. Third, the current study is limited and not able to measure several other important variables (i.e., the desire for an additional child, myths/misconceptions, fear of side effects, and partner/friend discouragement) which also affect the use of contraceptives. Future researchers are required to conduct studies on the approval of modern FP practices by couples and their association with contraceptive knowledge and barriers in acquiring contraceptive knowledge. Fourth, since the current study employed a statistical method due to the authors’ limitations in using advanced statistical tools, future studies may use PLS-SEM as an advanced statistical tool, which seems much more appropriate, especially when analyzing possible moderation. Finally, for formulating comprehensive strategies about couple counselling to overcome the knowledge and practice gap and to dispel misconceptions about contraceptives, researchers should conduct qualitative studies on spousal communication and contraceptive knowledge.

6. Conclusions

To conclude, the empirical analysis supported three hypotheses proposed in this study. The results indicated that CSE, contraceptive knowledge, and spousal communication positively impact the adoption of modern contraceptive methods for FP practices. In particular, the higher CSE in women motivates them to adopt modern contraceptive methods for FP practices. It also encourages women to overcome all the barriers, which limit their access to FP services. CSE helps women to understand the importance of FP practices that are important in maintaining the gap between child births. It supports women in decision making about fertility preferences, which helps them to recover their health from previous pregnancies and provide better care to their children.

Constructs along with their corresponding items.

Contraceptive Methods (A): Pill, IUCD, condom, periodic abstinence, withdrawal, female sterilization, male sterilization, implants.

Author Contributions

Conceptualization, J.N.M.; methodology, J.N.M.; software, J.N.M.; validation, A.M.S. and K.L.; formal analysis, J.N.M.; investigation, J.N.M.; resources, A.M.S.; data curation, J.N.M. and A.M.S.; writing—original draft preparation, J.N.M. and A.M.S.; writing—review and editing, A.M.S.; visualization, K.L.; supervision, K.L.; project administration, K.L.; funding acquisition, K.L. All authors have read and agreed to the published version of the manuscript.

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2021-2017-0-01630), and the work (No. 2020-0-01907, Development of Smart Signage Technology for Automatic Classification of Untact Examination and Patient Status Based on AI) was supervised by the IITP (Institute for Information and Communications Technology Promotion).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Faculty of Management Sciences, Riphah International University, Islamabad, Pakistan (FMS/RSL/ERC/107 on 11 August 2020).

Informed Consent Statement

Not applicable.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

91 Birth control Essay Topic Ideas & Examples

🏆 best birth control topic ideas & essay examples, 📌 simple & easy birth control essay titles, 👍 good essay topics on birth control, ❓ research questions about birth control.

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• Open access
• Published: 29 July 2024

Predicting hospital length of stay using machine learning on a large open health dataset

• Raunak Jain 1 ,
• Mrityunjai Singh 1 ,
• A. Ravishankar Rao 2 &
• Rahul Garg 1  

BMC Health Services Research volume  24 , Article number:  860 ( 2024 ) Cite this article

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Governments worldwide are facing growing pressure to increase transparency, as citizens demand greater insight into decision-making processes and public spending. An example is the release of open healthcare data to researchers, as healthcare is one of the top economic sectors. Significant information systems development and computational experimentation are required to extract meaning and value from these datasets. We use a large open health dataset provided by the New York State Statewide Planning and Research Cooperative System (SPARCS) containing 2.3 million de-identified patient records. One of the fields in these records is a patient’s length of stay (LoS) in a hospital, which is crucial in estimating healthcare costs and planning hospital capacity for future needs. Hence it would be very beneficial for hospitals to be able to predict the LoS early. The area of machine learning offers a potential solution, which is the focus of the current paper.

We investigated multiple machine learning techniques including feature engineering, regression, and classification trees to predict the length of stay (LoS) of all the hospital procedures currently available in the dataset. Whereas many researchers focus on LoS prediction for a specific disease, a unique feature of our model is its ability to simultaneously handle 285 diagnosis codes from the Clinical Classification System (CCS). We focused on the interpretability and explainability of input features and the resulting models. We developed separate models for newborns and non-newborns.

The study yields promising results, demonstrating the effectiveness of machine learning in predicting LoS. The best R 2 scores achieved are noteworthy: 0.82 for newborns using linear regression and 0.43 for non-newborns using catboost regression. Focusing on cardiovascular disease refines the predictive capability, achieving an improved R 2 score of 0.62. The models not only demonstrate high performance but also provide understandable insights. For instance, birth-weight is employed for predicting LoS in newborns, while diagnostic-related group classification proves valuable for non-newborns.

Our study showcases the practical utility of machine learning models in predicting LoS during patient admittance. The emphasis on interpretability ensures that the models can be easily comprehended and replicated by other researchers. Healthcare stakeholders, including providers, administrators, and patients, stand to benefit significantly. The findings offer valuable insights for cost estimation and capacity planning, contributing to the overall enhancement of healthcare management and delivery.

Peer Review reports

Introduction

Democratic governments worldwide are placing an increasing importance on transparency, as this leads to better governance, market efficiency, improvement, and acceptance of government policies. This is highlighted by reports from the Organization for Economic Co-operation and Development (OECD) an international organization whose mission it is to shape policies that foster prosperity, equality, opportunity and well-being for all [ 1 ]. Openness and transparency have been recognized as pillars for democracy, and also for fostering sustainable development goals [ 2 ], which is a major focus of the United Nations ( https://sustainabledevelopment.un.org/sdg16 ).

An important government function is to provide for the healthcare needs of its citizens. The U.S. spends about $3.6 trillion a year on healthcare, which represents 18% of its GDP [ 3 ]. Other developed nations spend around 10% of their GDP on healthcare. The percentage of GDP spent on healthcare is rising as populations age. Consequently, research on healthcare expenditure and patient outcomes is crucial to maintain viable national economies. It is advantageous for nations to combine investigations by the private sector, government sector, non-profit agencies, and universities to find the best solutions. A promising path is to make health data open, which allows investigators from all sectors to participate and contribute their expertise. Though there are obvious patient privacy concerns, open health data has been made available by organizations such as New York State Statewide Planning and Research Cooperative System (SPARCS) [ 4 ].

Once the data is made available, it needs to be suitably processed to extract meaning and insights that will help healthcare providers and patients. We favor the creation and use of an open-source analytics system so that the entire research community can benefit from the effort [ 5 , 6 , 7 ]. As a concrete demonstration of the utility of our system and approach, we revealed that there is a growing incidence of mental health issues amongst adolescents in specific counties in New York State [ 8 ]. This has resulted in targeted interventions to address these problems in these communities [ 8 ]. Knowing where the problems lie allows policymakers and funding agencies to direct resources where needed.

Healthcare in the U.S. is largely provided through private insurance companies and it is difficult for patients to reliably understand what their expected healthcare costs are [ 9 , 10 ]. It is ironic that consumers can readily find prices of electronics items, books, clothes etc. online, but cannot find information about healthcare as easily. The availability of healthcare information including costs, incidence of diseases, and the expected length of stay for different procedures will allow consumers and patients to make better and more informed choices. For instance, in the U.S., patients can budget pre-tax contributions to health savings accounts, or decide when to opt for an elective surgery based on the expected duration of that procedure.

To achieve this capability, it is essential to have the underlying data and models that interpret the data. Our goal in this paper is twofold: (a) to demonstrate how to design an analytics system that works with open health data and (b) to apply it to a problem of interest to both healthcare providers and patients. Significant advances have been made recently in the fields of data mining, machine-learning and artificial intelligence, with growing applications in healthcare [ 11 ]. To make our work concrete, we use our machine-learning system to predict the length of stay (LoS) in hospitals given the patient information in the open healthcare data released by New York State SPARCS [ 4 ].

The LoS is an important variable in determining healthcare costs, as costs directly increase for longer stays. The analysis by Jones [ 12 ] shows that the trends in LoS, hospital bed capacity and population growth have to be carefully analyzed for capacity planning and to ensure that adequate healthcare can be provided in the future. With certain health conditions such as cardiovascular disease, the hospital LoS is expected to increase due to the aging of the population in many countries worldwide [ 13 ]. During the COVID-19 pandemic, hospital bed capacity became a critical issue [ 14 ], and many regions in the world experienced a shortage of healthcare resources. Hence it is desirable to have models that can predict the LoS for a variety of diseases from available patient data.

The LoS is usually unknown at the time a patient is admitted. Hence, the objective of our research is to investigate whether we can predict the patient LoS from variables collected at the time of admission. By building a predictive model through machine learning techniques, we demonstrate that it is possible to predict the LoS from data that includes the Clinical Classifications Software (CCS) diagnosis code, severity of illness, and the need for surgery. We investigate several analytics techniques including feature selection, feature encoding, feature engineering, model selection, and model training in order to thoroughly explore the choices that affect eventual model performance. By using a linear regression model, we obtain an R 2 value of 0.42 when we predict the LoS from a set of 23 patient features. The success of our model will be beneficial to healthcare providers and policymakers for capacity planning purposes and to understand how to control healthcare costs. Patients and consumers can also use our model to estimate the LoS for procedures they are undergoing or for planning elective surgeries.

Stone et al. [ 15 ] present a survey of techniques used to predict the LoS, which include statistical and arithmetic methods, intelligent data mining approaches and operations-research based methods. Lequertier et al. [ 16 ] surveyed methods for LoS prediction.

The main gap in the literature is that most methods focus on analyzing trends in the LoS or predicting the LoS only for specific conditions or restrict their analysis to data from specific hospitals. For instance, Sridhar et al. [ 17 ] created a model to predict the LoS for joint replacements in rural hospitals in the state of Montana by using a training set with 127 patients and a test set with 31 patients. In contrast, we have developed our model to predict the LoS for 285 different CCS diagnosis codes, over a set of 2.3 million patients over all hospitals in New York state. The CCS diagnosis code refers to the code used by the Clinical Classifications Software system, which encompasses 285 possible diagnosis and procedure categories [ 18 ]. Since the CCS diagnosis codes are too numerous to list, we give a few examples that we analyzed, including but not limited to abdominal hernia, acute myocardial infarction, acute renal failure, behavioral disorders, bladder cancer, Hodgkins disease, multiple sclerosis, multiple myeloma, schizophrenia, septicemia, and varicose veins. To the best of our knowledge, we are not aware of models that predict the LoS on such a variety of diagnosis codes, with a patient sample greater than 2 million records, and with freely available open data. Hence, our investigation is unique from this point of view.

Sotodeh et al. [ 19 ] developed a Markov model to predict the LoS in intensive care unit patients. Ma et al. [ 20 ] used decision tree methods to predict LoS in 11,206 patients with respiratory disease.

Burn et. al. examined trends in the LoS for patients undergoing hip-replacement and knee-replacement in the U.K. [ 21 ]. Their study demonstrated a steady decline in the LoS from 1997–2012. The purpose of their study was to determine factors that contributed to this decline, and they identified improved surgical techniques such as fast-track arthroplasty. However, they did not develop any machine-learning models to predict the LoS.

Hachesu et al. examined the LoS for cardiac disease patients [ 22 ] and found that blood pressure is an important predictor of LoS. Garcia et al. determined factors influencing the LoS for undergoing treatment for hip fracture [ 23 ]. B. Vekaria et al. analyzed the variability of LoS for COVID-19 patients [ 24 ]. Arjannikov et al. [ 25 ] used positive-unlabeled learning to develop a predictive model for LoS.

Gupta et al. [ 26 ] conducted a meta-analysis of previously published papers on the role of nutrition on the LoS of cancer patients, and found that nutrition status is especially important in predicting LoS for gastronintestinal cancer. Similarly, Almashrafi et al. [ 27 ] performed a meta-analysis of existing literature on cardiac patients and reviewed factors affecting their LoS. However, they did not develop quantitative models in their work. Kalgotra et al. [ 28 ] use recurrent neural networks to build a prediction model for LoS.

Daghistani et al. [ 13 ] developed a machine learning model to predict length of stay for cardiac patients. They used a database of 16,414 patient records and predicted the length of stay into three classes, consisting of short LoS (< 3 days), intermediate LoS ( 3–5 days) and long LoS (> 5 days). They used detailed patient information, including blood test results, blood pressure, and patient history including smoking habits. Such detailed information is not available in the much larger SPARCS dataset that we utilized in our study.

Awad et al. [ 29 ] provide a comprehensive review of various techniques to predict the LoS. Though simple statistical methods have been used in the past, they make assumptions that the LoS is normally distributed, whereas the LoS has an exponential distribution [ 29 ]. Consequently, it is preferable to use techniques that do not make assumptions about the distribution of the data. Candidate techniques include regression, classification and regression trees, random forests, and neural networks. Rather than using statistical parametric techniques that fit parameters to specific statistical distributions, we favor data-driven techniques that apply machine-learning.

In 2020, during the height of the COVID-19 pandemic, the Lancet, a premier medical journal drew widespread rebuke [ 30 , 31 , 32 ] for publishing a paper based on questionable data. Many medical journals published expressions of concern [ 33 , 34 ]. The Lancet itself retracted the questionable paper [ 35 ], which is available at [ 36 ] with the stamp “retracted” placed on all pages. One possible solution to prevent such incidents from occurring is for top medical journals to require authors to make their data available for verification by the scientific community. Patient privacy concerns can be mitigated by de-identifying the records made available, as is already done by the New York State SPARCS effort [ 4 ]. Our methodology and analytics system design will become more relevant in the future, as there is a desire to prevent a repetition of the Lancet debacle. Even before the Lancet incident, there was declining trust amongst the public related to medicine and healthcare policy [ 37 ]. This situation continues today, with multiple factors at play, including biased news reporting in mainstream media [ 38 ]. A desirable solution is to make these fields more transparent, by releasing data to the public and explaining the various decisions in terms that the public can understand. The research in this paper demonstrates how such a solution can be developed.

Requirements

We describe the following three requirements of an ideal system for processing open healthcare data

Utilize open-source platforms to permit easy replicability and reproducibility.

Create interpretable and explainable models.

Demonstrate an understanding of how the input features determine the outcomes of interest.

The first requirement captures the need for research to be easily reproduced by peers in the field. There is growing concern that scientific results are becoming hard for researchers to reproduce [ 39 , 40 , 41 ]. This undermines the validity of the research and ultimately hurts the fields. Baker termed this the “reproducibility crisis”, and performed an analysis of the top factors that lead to irreproducibility of research [ 39 ]. Two of the top factors consist of the unavailability of raw data and code.

The second requirement addresses the need for the machine-learning models to produce explanations of their results. Though deep-learning models are popular today, they have been criticized for functioning as black-boxes, and the precise working of the model is hard to discern. In the field of healthcare, it is more desirable to have models that can be explained easily [ 42 ]. Unless healthcare providers understand how a model works, they will be reluctant to apply it in their practice. For instance, Reyes et al. determined that interpretable Artificial Intelligence systems can be better verified, trusted, and adopted in radiology practice [ 43 ].

The third requirement shows that it is important for relevant patient features to be captured that can be related to the outcomes of interest, such as LoS, total cost, mortality rate etc. Furthermore, healthcare providers should be able to understand the influence of these features on the performance of the model [ 44 ]. This is especially critical when feature engineering methods are used to combine existing features and create new features.

In the subsequent sections, we present our design for a healthcare analytics system that satisfies these requirements. We apply this methodology to the specific problem of predicting the LoS.

We have designed the overall system architecture as shown in Fig.  1 . This system is built to handle any open data source. We have shown the New York SPARCS as one of the data sources for the sake of specificity. Our framework can be applied to data from multiple sources such as the Center for Medicare and Medicaid Services (CMS in the U.S.) as shown in our previous work [ 6 ]. We chose a Python-based framework that utilizes Pandas [ 45 ] and Scikit learn [ 46 ]. Python is currently the most popular programming language for engineering and system design applications [ 47 ].

Shows the system architecture. We use Python-based open-source tools such as Pandas and Scikit-Learn to implement the system

In Fig.  2 , we provide a detailed overview of the necessary processing stages. The specific algorithms used in each stage are described in the following sections.

Shows the processing stages in our analytics pipeline

Recent research has shown that it is highly desirable for machine learning models used in the healthcare domain to be explainable to healthcare providers and professionals [ 48 ]. Hence, we focused on the interpretability and explainability of input features in our dataset and the models we chose to explore. We restricted our investigation to models that are explainable, including regression models, multinomial logistic regression, random forests, and decision trees. We also developed separate models for newborns and non-newborns.

Brief description of the dataset

During our investigation, we utilized open-health data provided by the New York State SPARCS system. The data we accessed was from the year 2016, which was the most recent year available at the time. This data was provided in the form of a CSV file, containing 2,343,429 rows and 34 columns. Each row contains de-identified in-patient discharge information. The dataset columns contained various types of information. They included geographic descriptors related to the hospital where care was provided, demographic descriptors such as patient race, ethnicity, and age, medical descriptors such as the CCS diagnosis code, APR DRG code, severity of illness, and length of stay. Additionally, payment descriptors were present, which included information about the type of insurance, total charges, and total cost of the procedure.

Detailed descriptions of all the elements in the data can be found in [ 49 ]. The CCS diagnosis code has been described earlier. The term “DRG” stands for Diagnostic Related Group [ 49 ], which is used by the Center for Medicare and Medicaid services in the U.S. for reimbursement purposes [ 50 ].

The data includes all patients who underwent inpatient procedures at all New York State Hospitals [ 51 ]. The payment for the care can come from multiple sources: Department of Corrections, Federal/State/Local/Veterans Administration, Managed Care, Medicare, Medicaid, Miscellaneous, Private Health Insurance, and Self-Pay. The dataset sourced from the New York State SPARCS system, encompassing a wider patient population beyond Medicare/Medicaid, holds greater value compared to datasets exclusively composed of Medicare/Medicaid patients. For instance, Gilmore et al. analyzed only Medicare patients [ 52 ].

We examine the distribution of the LoS in the dataset, as shown in Fig.  3 . We note that the providers of the data have truncated the length of stay to 120 days. This explains the peak we see at the tail of the distribution.

Distribution of the length of stay in the dataset

Data pre-processing and cleaning

We identified 36,280 samples, comprising 1.55% of the data where there were missing values. These were discarded for further analysis. We removed samples which have Type of Admission = ‘Unknown’ (0.02% samples). So, the final data set has 2,306,668 samples. ‘Payment Typology 2’, and ‘Payment Typology 3’, have missing values (> = 50% samples), which were replaced by a ‘None’ string.

We note that approximately 10% of the dataset consists of rows representing newborns. We treat this group as a separate category. We found that the ‘Birth Weight’ feature had a zero value for non-newborn samples. Accordingly, to better use the ‘Birth Weight’ feature, we partitioned the data into two classes: newborns and non-newborns. This results in two classes of models, one for newborns and the second for all other patients. We removed the ‘Birth Weight’ feature in the input for the non-newborn samples as its value was zero for those samples.

The column ‘Total Costs’ (and in a similar way, ‘Total Charges’) are usually proportional to the LoS, and it would not be fair to use these variables to predict the LoS. Hence, we removed this column. We found that the columns 'Discharge Year', 'Abortion Edit Indicator'' are redundant for LoS prediction models, and we removed them. We also removed the columns ‘CCS Diagnosis Description’, ‘CCS Procedure Description’, ‘APR DRG Description’, ‘APR MDC Description’, and ‘APR Severity of Illness Description’ as we were given their corresponding numerical codes as features.

Since the focus of this paper is on the prediction of the LoS, we analyzed the distribution of LoS values in the dataset.

We developed regression models using all the LoS values, from 1–120. We also developed classification models where we discretized the LoS into specific bins. Since the distribution of LoS values is not uniform, and is heavily clustered around smaller values, we discretized the LoS into a small number of bins, e.g. 6 to 8 bins.

We utilized 10% of the data as a holdout test-set, which was not seen during the training phase. For the remaining 90% of the data, we used tenfold cross-validation in order to train the model and determine the best parameters to use.

Feature encoding

Many variables in the dataset are categorical, e.g., the variable “APR Severity of Illness Description” has the values in the set [Major, Minor, Moderate, Extreme]. We used distribution-dependent target encoding techniques and one-hot techniques to improve the model performance [ 53 ]. We replaced categorical data with the product of mean LoS and median LoS for a category value. The categorical feature can then better capture the dependence distribution of LoS with the value of the categorical feature.

For the linear regression model [ 54 ], we sampled a set of 6 categorical features, [‘Type of Admission’, ‘Patient Disposition’, ‘APR Severity of Illness Code’, ‘APR Medical Surgical Description’, ‘APR MDC Code’] which we target encoded with the mean of the LoS and the median of the LoS. We then one-hot encoded every feature (all features are categorical) and for each such one-hot encoded feature, created a new feature for each of the features in the sampled set, by replacing the ones in the one-hot encoded feature with the value of the corresponding feature in the sampled set. For example, we one-hot encoded ‘Operating Certificate Number’, and for samples where ‘Operating Certificate Number’ was 3, we created 6 features, each where samples having the value 3 were assigned the target encoded values of the sampled set features, and the other samples were assigned zero. We used such techniques to exploit the linear relation between LoS and each feature.

According to the sklearn documentation [ 55 ], a random forest regressor is “a meta estimator that fits a number of decision tree regressors on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting”. The random forest regressor leverages ensemble learning based on many randomized decision trees to make accurate and robust predictions for regression problems. The averaging of many trees protects against single trees overfitting the training data.

The random forest classifier is also an ensemble learning technique and uses many randomized decision trees to make predictions for classification problems. The 'wisdom of crowds' concept suggests that the decision made by a larger group of people is typically better than an individual. The random forest classifier uses this intuition, and allows each decision tree to make a prediction. Finally, the most popular predicted class is chosen as the overall classification.

For the Random Forest Regressor [ 56 , 57 ] and Random Forest Classifier [ 58 ], we only used a similar distribution dependent target encoding as a random forest classifier/ regressor is unsuitable for sparse one-hot encoded columns.

Multinomial logistic regression is a type of regression analysis that predicts the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables. It allows for more than two discrete outcomes, extending binomial logistic regression for binary classification to models with multiple class membership. For the multinomial logistic regression model [ 59 ], we used only one-hot encoding, and not target encoding, as the target value was categorical.

Finally, we experimented with combinations of target encoding and one-hot encoding. We can either use target encoding, or one-hot encoding, or both. When both encodings are employed, the dimensionality of the data increases to accommodate the one-hot encoded features. For each combination of encodings, we also experimented with different regression models including linear regression and random forest regression.

Feature importance, selection, and feature engineering

We experimented with different feature selection methods. Since the focus of our work is on developing interpretable and explainable models, we used SHAP analysis to determine relevant features.

We examine the importance of different features in the dataset. We used the SHAP value (Shapley Additive Explanations), a popular measure for feature importance [ 60 ]. Intuitively, the SHAP value measures the difference in model predictions when a feature is used versus omitted. It is captured by the following formula.

where \({{\varnothing }}_{i}\) is the SHAP value of feature \(i\) , \(p\) is the prediction by the model, n is the number of features and S is any set of features that does not include the feature \(i\) . The specific model we used for the prediction was the random forest regressor where we target-encoded all features with the product of the mean and the median of the LoS, since most of the features were categorical.

Classification models

One approach to the problem is to bin the LoS into different classes, and train a classifier to predict which class an input sample falls in. We binned the LoS into roughly balanced classes as follows: 1 day, 2 days, 3 days, 4–6 days, > 6 days. This strategy is based on the distribution of the LoS as shown earlier in Figs.  3 and  4 .

A density plot of the distribution of the length of stay. The area under the curve is 1. We used a kernel density estimation with a Gaussian kernel [ 61 ] to generate the plot

We used three different classification models, comprising the following:

Multinomial Logistic Regression

Random Forest Classifier

CatBoost classifier [ 62 ].

We used a Multinomial Logistic Regression model [ 59 ] trained and tested using tenfold cross validation to classify the LoS into one of the bins. The multinomial logistic regression model is capable of providing explainable results, which is part of the requirements. We used the feature engineering techniques described in the previous section.

We used a Random Forest Classifier model trained and tested using tenfold cross validation to classify the LoS into one of the bins. We used a maximum depth of 10 so as to get explainable insights into the model.

Finally, we used a CatBoost Classifier model trained and tested using tenfold cross validation to classify the LoS into one of the bins.

Regression models

We used three different regression models with the feature engineering techniques mentioned above ( Feature encoding section). These comprise:

Linear regression

Catboost regression

Random forest regression

The linear regression was implemented using the nn.Linear() function in the open source library PyTorch [ 63 ]. We used the ‘Adam’ optimization algorithm [ 64 ] in mini-batch settings to train the model weights for linear regression.

We investigated CatBoost regression in order to create models with minimal feature sets, whereby models with a low number of input features would provide adequate results. Accordingly, we trained a CatBoost Regressor [ 65 ] in order to determine the relationship between combinations of features and the prediction accuracy as determined by the R 2 correlation score.

The random forest regression was implemented using the function RandomForestRegressor() in scikit learn [ 55 ].

Model performance measures

For the regression models, we used the following metrics to compare the model performance.

The R 2 score and the p -value. We use a significance level of α = 0.05 (5 %) for our statistical tests.  If the p -value is small, i.e. less than α = 0.05, then the R 2 score is statistically significant.

For classifier models, we used the following metrics to compare the model performance.

True positive rate, false negative rate, and F1 score [ 66 ].

We computed the Brier score using Brier’s original calculation in his paper [ 67 ]. In this formulation, for R classes the Brier score B can vary between 0 and R, with 0 being the best score possible.

where \({\widehat{y}}_{i,c}\) is the class probability as per the model and \({I}_{i,c}=1\) if the i th sample belongs to class c and \({I}_{i,c}=0\) if it does not belong to class c .

We used the Delong test [ 68 ] to compare the AUC for different classifiers.

These metrics will allow other researchers to replicate our study and provide benchmarks for future improvements.

In this section we present the results of applying the techniques in the Methods section.

Descriptive statistics

We provide descriptive statistics that help the reader understand the distributions of the variables of interest.

Table 1 summarizes basic statistical properties of the LoS variable.

Figure  5 shows the distribution of the LoS variable for newborns.

This figure depicts the distribution of the LoS variable for newborns

Table 2 shows the top 20 APR DRG descriptions based on their frequency of occurrence in the dataset.

Figure  6 shows the distribution of the LoS variable for the top 20 most frequently occurring APR DRG descriptions shown in Table  2 .

A 3-d plot showing the distribution of the LoS for the top-20 most frequently occuring APR DRG descriptions. The x-axis (horizontal) depicts the LoS, the y-axis shows the APR DRG codes and the z-axis shows the density or frequency of occurrence of the LoS

We experimented with different encoding schemes for the categorical variables and for each encoding we examined different regression techniques. Our results are shown in Table 3 . We experimented with the three encoding schemes shown in the first column. The last row in the table shows a combination of one-hot encoding and target encoding, where the number of columns in the dataset are increased to accommodate one-hot encoded feature values for categorical variables.

Feature importance, selection and feature engineering

We obtained the SHAP plots using a Random Forest Regressor trained with target-encoded features.

Figures  7  and 8 show the SHAP values plots obtained for the features in the newborn partition of the dataset. We find that the features, “APR DRG Code”, “APR Severity of Illness Code”, “Patient Disposition”, “CCS Procedure Code”, are very useful in predicting the LoS. For instance, high feature values for “APR Severity of Illness Code”, which are encoded by red dots have higher SHAP values than the blue dots, which correspond to low feature values.

SHAP Value plot for newborns

1-D SHAP plot, in order of decreasing feature importance: top to bottom (for non-newborns)

A similar interpretation can be applied to the features in the non-newborn partition of the dataset. We note that “Operating Certificate Number” is among the top-10 most important features in both the newborn and non-newborn partitions. This finding is discussed in the Discussion section.

From Fig.  9 , we observe that as the severity of illness code increases from 1–4, there is a corresponding increase in the SHAP values.

A 2-D plot showing the relationship between SHAP values for one feature, “APR Severity of Illness Code”, and the feature values themselves (non-newborns)

To further understand the relationship between the APR Severity of Illness code and the LoS, we created the plot in Fig.  10 . This shows that the most frequently occurring APR Severity of Illness code is 1 (Minor), and that the most frequently occurring LoS is 2 days. We provide this 2-D projection of the overall distribution of the multi-dimensional data as a way of understanding the relationship between the input features and the target variable, LoS.

A density plot showing the relationship between APR Severity of Illness Code and the LoS. The color scale on the right determines the interpretation of colors in the plot. We used a kernel density estimation with a Gaussian kernel [ 61 ] to generate the plot

Similarly, Fig.  11 shows the relationship between the birth weight and the length of stay. The most common length of stay is two days.

A density plot showing the distribution of the birth weight values (in grams) versus the LoS. The colorbar on the right shows the interpretation of color values shown in the plot. We used a kernel density estimation with a Gaussian kernel [ 61 ] to generate the plot

Classification

We obtained a classification accuracy of 46.98% using Multinomial Logistic Regression with tenfold cross-validation in the 5-class classification task for non-newborn cases. The confusion matrix in Fig.  12 shows that the highest density of correctly classified samples is in or close to the diagonal region. The regions where out model fails occurs between adjacent classes as can be inferred from the given confusion matrix.

Confusion matrix for classification of non-newborns. The number inside each square along the diagonal represents the number of correctly classified samples. The color is coded so lighter colors represent lower numbers

For the newborn cases, we obtained a classification accuracy of 60.08% using Random Forest Classification model with tenfold cross-validation in the 5-class classification task. The confusion matrix in Fig.  13 shows that the majority of data samples lie in or close to the diagonal region. The regions where our model does not do well occurs between adjacent classes as can be inferred from the given confusion matrix,

Confusion matrix for classification of newborns. The number inside each square along the diagonal represents the number of correctly classified samples. The color is coded so lighter colors represent lower numbers

The density plot in Fig.  14 shows the relationship between the actual LoS and the predicted LoS. For a LoS of 2 days, the centroid of the predicted LoS cluster is between 2 and 3 days.

Shows the density plot of the predicted length of stay versus actual length of stay for the classifier model for non-newborns. We used a kernel density estimation with a Gaussian kernel [ 61 ] to generate the plot

A quantitative depiction of our model errors is shown in Fig.  15 . The values in Fig.  15 are interpreted as follows. Referring to the column for LoS = 2, the top row shows that 51% of the predicted LoS values for an actual stay of 2 days is also 2 days (zero error), and that 23% of the predicted values for LoS equal to 2 days have an error of 1 day and so on. The relatively high values in the top row indicates that the model is performing well, with an error of less than 1 day. There are relatively few instances of errors between 2 and 3 days (typically less than 10% of the values show up in this row). The only exception is for the class corresponding to LoS great than 8 days. The truncation of the data to produce this class results in larger model errors specifically for this class.

Shows the distribution of correctly predicted LoS values for each class used in our model. Along the columns, we depict the different classes used in the model, consisting of LoS equal to 1, 2, 3 …8, and more than 8. Each row depicts different errors made in the prediction. For instance, the top row depicts an error of less than or equal to one day between the actual LoS and the predicted Los. The second row from the top depicts an error which is greater than 1 and less than or equal 2 days. And so on for the other rows, for non-newborns

Figures  16 and 17 show the scatter plots for the linear regression models. The exact line represents a line with slope 1, and a perfect model would be one that produced all points lying on this line.

Scatter plot showing an instance of a linear regression fit to the data (newborns). The R 2 score is 0.82. The blue line represents an exact fit, where the predicted LoS equals the actual LoS (slope of the line is 1)

Scatter plot for linear regression. (non-newborns). The R 2 score is 0.42. The blue line represents an exact fit, where the predicted LoS equals the actual LoS (slope of the line is 1)

Figure  18 shows a density plot depicting the relationship between the predicted length of stay and the actual length of stay.

Shows the density plot of the predicted length of stay versus actual length of stay for the classifier model for non-newborns. We used a kernel density estimation with a Gaussian kernel [ 40 ] to generate the plot. The best fit regression line to our predictions is shown in green, whereas the blue line represents the ideal fit (line of slope 1, where actual LoS and predicted LoS are equal)

Most of the existing literature on LoS stay prediction is based on data for specific disease conditions such as cancer or cardiac disease. Hence, in order to understand which CCS diagnosis codes produce good model fits, we produced the plot in Fig.  19 .

This figure shows the three CCS diagnosis codes that produced the top three R 2 scores using linear regression. These are 101, 100 and 109. The three CCS Diagnosis codes that produced the lowest R 2 scores are 159, 657, and 659

We provide the following descriptions in Tables  4  and 5 for the 3 CCS Diagnosis Codes in Fig.  19 with the top R 2 Scores using linear regression.

Similarly, the following table shows the 3 CCS Diagnosis Codes in Fig.  19 for the lowest R 2 Scores using linear regression.

Models with minimal feature sets

We trained a CatBoost Regressor [ 65 ] on the complete dataset in order to determine the relationship between combinations of features and the prediction accuracy as determined by the R 2 correlation score. This is shown in Fig.  20

The labels for each row on the left show combinations of different input features. A CatBoost regression model was developed using the selected combination of features. The R 2 correlation scores for each model is shown in the bar graph

We can infer from Fig.  20 that only four features (‘'APR MDC Code', 'APR Severity of Illness Code', 'APR DRG Code', 'Patient Disposition') are sufficient for the model to reach very close to its maximum performance. We obtain similar concurring results when using other regression models for the same experiment.

Classification trees

We used a random forest tree approach to generate the trees in Figs.  21 and 22 .

A random forest tree that represents a best-fit model to the data for newborns. With 4 levels of the decision tree, the R 2 score is 0.65

A random forest tree using only a tree of depth 3 that represents a best-fit model to the data for non-newborns. The R 2 score is 0.28. We can generate trees with greater depth that better fit the data, but we have shown only a depth of 3 for the sake of readability in the printed version of this paper. Otherwise, the tree would be too large to be legible on this page. The main point in this figure is to showcase the ease of interpretation of the working of the model through rules

We used tenfold cross validation to determine the regression scores. The results are summarized in Tables  6 and 7 .

We computed the multi-class classifier metrics for logistic regression, using one-hot encoding for non-newborns. The results are presented in Table  8 . The first row represents the accuracy of the classifier when Class 0 is compared against the rest of the classes. A similar interpretation applies to the other rows in the table, ie one-versus-rest. The macro average gives the balanced recall and precision, and the resulting F1 score. The weighted average gives a support (number of samples) weighted average of the individual class metric. The overall accuracy is computed by dividing the total number of accurate predictions, which is 49,686 out of a total number of 105,932 samples, which yields a value of 0.47.

For the category of non-newborns, Fig.  23  provides a graphical plot that visualizes the ROC curves for the different multiclass classifiers we developed.

This figure applies to data concerning non-newborns. We show the multiclass ROC curves for the performance of the catboost classifier for the different classes shown. The area under the ROC curve is 0.7844

In Table  9 we compare the performance of our multiclass classifier using logistic regression developed on 2016 SPARCS data against 2017 SPARCS data.

In order to compare the performance of the different classifiers, we computed the AUC measures reported in Table  10 . Figure 24 visualizes the data in Table 10 and Fig. 25 visualizes the data in Table 11 . In Tables 12 and 13 we report the results of computing the Delong test for non-newborns and newborns respectively. In Tables 14 and 15 we report the results of computing the Brier scores for non-new borns and newborns respectively.

A bar chart that depicts the data in Table  10 for non-newborns

A bar chart that depicts the data in Table  11

Model parameters

In Table  16 we present the parameter and hyperparameter values used in the different models.

Additional results shown in the Appendix/Supplementary material

Due to space restrictions, we show additional results in the Appendix/Supplementary Material. These results are in tabular form and describe the R 2 scores for different segmentations of the variables in the dataset, e.g. according to age group, severity of illness code, etc.

The most significant result we obtain is shown in Figs.  21 and 22 , which provides an interpretable working of the decision trees using random forest modeling. Figure  21 for newborns shows that the birth weight features prominently in the decision tree, occurring at the root node. Low birth weights are represented on the left side of the tree and are typically associated with longer hospital stays. Higher birth weights occur on the right side of the tree, and the node in the bottom row with 189,574 samples shows that the most frequently occurring predicted stay is 2.66 days. Figure  22 for non-newborns shows that the features of “APR DRG Code”, “APR Severity of Illness Code” and “Patient Disposition” are the most important top-level features to predict the LoS. This provides a relatively simple rule-based model, which can be easily interpreted by healthcare providers as well as patients. For instance, the right-most branch of the tree classifies the input data into a relatively high LoS (46 days) when the branch conditions APR DRG Code is greater than 813.55 and the APR Severity of Illness Code is less than 91.

The results in Fig.  19 and Table  4 show that if we restrict our model to specific CCS Diagnosis descriptions such as “coronary atherosclerosis and other heart disease”, we obtain a good R 2 Score of 0.62. The objective of our work is not to cherry-pick CCS Diagnosis codes that produce good results, but rather to develop a single model for the entire SPARCS dataset to obtain a birds-eye perspective. For future work, we can explicitly build separate models for each CCS Diagnosis code, and that could have relevance to specific medical specialties, such as cardiovascular care.

Similarly, the results in Fig.  19 and Table  5 show that there are CCS Diagnosis codes corresponding to schizophrenia and mood disorders that produce a poor model fit. Factors that contribute to this include the type of data in the SPARCS dataset, where information about patient vitals, medications, or a patient’s income level is not provided, and the inherent variability in treating schizophrenia and mood disorders. Baeza et al. [ 69 ] identified several variables that affect the LoS in psychiatric patients, which include psychiatric admissions in the previous years, psychiatric rating scale scores, history of attempted suicide, and not having sufficient income. Such variables are not provided in the SPARCS dataset. Hence a policy implication is to collect and make such data available, perhaps as a separate dataset focused on mental health issues, which have proven challenging to treat.

Figures  16 and 17 show that a better regression fit is obtained when a specific CCS Diagnosis code is used to build the model, such as “Newborn” in Fig.  16 . To put these results in context, we note that it is difficult to obtain a high R 2 value for healthcare datasets in general, and especially for large numbers of patient samples that span multiple hospitals. For instance, Bertsimas [ 70 ] reported an R 2 value of 0.2 and Kshirsagar [ 71 ] reported an R 2 value of 0.33 for similar types of prediction problems as studied in this paper.

Further details for a segmentation of R 2 scores by the different variable categories are shown in the Appendix/Supplementary Material section. For instance, the table corresponding to Age Groups shows that there is close agreement between the mean of the predicted LoS from our model and the actual LoS. Furthermore, the mean LoS increases steadily from 4.8 days for Age group 0–17 to 6.4 days for ages 70 or older. A discussion of these tables is outside the scope of this paper. However, they are being provided to help other researchers form hypotheses for further investigations or to find supporting evidence for ongoing research.

Table 3 shows that the best encoding scheme is to combine target encoding with one-hot encoding and then apply linear regression. This produces an R 2 score of 0.42 for the non-newborn data, which is the best fit we could obtain. This table also shows that significant improvements can be obtained by exploring the search space which consists of different strategies of feature encoding and regression methods. There is no theoretical framework which determines the optimum choice, and the best method is to conduct an experimental search. An important contribution of the current paper is to explore this search space so that other researchers can use and build upon our methodology.

The distribution of errors in Fig.  15 shows that the truncation we employed at a LoS of 8 days produces artifacts in the prediction model as all stays of greater than 8 days are lumped into one class. Nevertheless, the distribution of LoS values in Fig.  4 shows that a relatively small number of data samples have LoS greater than 8 days. In the future, we will investigate different truncation levels, and this is outside the scope of the current paper. By using our methodology, the truncation level can also be tuned by practitioners in the field, including hospital administrators and other researchers.

Our results in Fig.  7 show that certain features are not useful in predicting the LoS. The SHAP plot shows that features such as race, gender, and ethnicity are not useful in predicting the LoS. It would have been interesting if this were not the case, as that implies that there is systemic bias based on race, gender or ethnicity. For instance, a person with a given race may have a smaller LoS based on their demographic identity. This would be unacceptable in the medical field. It is satisfying to see that a large and detailed healthcare dataset does not show evidence of bias.

To place this finding in context, racial bias is an important area of research in the U.S., especially in fields such as criminology and access to financial services such as loans. In the U.S., it is well known that there is a disproportional imprisonment of black and Hispanic males [ 72 ]. Researchers working on criminal justice have determined that there is racial bias in the process of sentencing and granting parole, with blacks being adversely affected [ 73 ]. This bias is reinforced through any algorithms that are trained on the underlying data. There is evidence that banks discriminate against applicants for loans based on their race or gender [ 74 ].

This does not appear to be the case in our analysis of the SPARCS data. Though we did not specifically investigate the issue of racial bias in the LoS, the feature analysis we conducted automatically provides relevant answers. Other researchers including those in the U.K [ 21 ] have also determined that gender does not have an effect on LoS or costs. Hence the results in the current paper are consistent with the findings of other researchers in other countries working on entirely different datasets.

From Table  6 we see that in the case of data concerning non-newborns, the catboost regression performs the best, with an R 2 score of 0.432. The p -value is less than 0.01, indicating that the correlation between the actual and predicted values of LoS through catboost regression is statistically significant. Similarly, the p -values for linear regression and random forest regression indicate that these models produce predictions that are statistically significant, i.e. they did not occur by random chance.

From Table  7 that refers to data from newborns, the linear regression performs the best, with an R 2 score of 0.82. The p -value is less than 0.01, indicating that the correlation between the actual and predicted values of LoS through linear regression is statistically significant. Similarly, the p -values for random forest regression and catboost regression indicate that these models produce predictions that are statistically significant.

We examine the performance of classifiers on non-newborn data, as shown in Tables  10 and 12 . The Delong test conducted in Table  12 shows that there is a statistically significant difference between the AUCs of the pairwise comparisons of the models. Hence, we conclude that the catboost classifier performs the best with an average AUC of 0.7844. We also note that there is a marginal improvement in performance when we use the catboost classifier instead of the random forest classifier. Both the catboost classifier and the random forest classifier perform better than logistic regression. We conclude that the best performing model for non-newborns is the catboost classifier, followed by the random forest classifier, and then logistic regression.

In the case of newborn data, we examine the performance of the classifiers as shown in Tables  11 and 13 . From Table 13 , we note that the p -values in all the rows are less than 0.05, except for the binary class “one vs. rest for class 3”, random forests vs. catboost. Hence, for this particular comparison between the random forest classifier and the catboost classifier for “one vs. rest for class 3”, we cannot conclude that there is a statistically significant difference between the performance of these two classifiers. From Table  11 we observe that the AUCs of these two classifiers are very similar. We also note that only about 10% of the dataset consists of newborn cases.

From Table  14 we note that the Brier score for the catboost classifier is the lowest. A lower Brier score indicates better performance. According to the Brier scores for the non-newborn data, the catboost classifier performs the best, followed by the random forest classifier and then logistic regression. Table 15 shows that for newborns, the random forest classifier performs the best, followed by the catboost classifier and logistic regression. The performance of the random forest classifier and catboost classifier are very similar.

From a practical perspective, it may make sense to use a catboost classifier on both newborn and non-newborn data as it simplifies the processing pipeline. The ultimate decision rests with the administrators and implementers of these decision systems in the hospital environment.

Burn et al. observe [ 21 ] that though the U.S. has reported similar declines in LoS as in the U.K, the overall costs of joint replacement have risen. The U.K. government created policies to encourage the formation of specialist centers for joint replacement, which have resulted in reduction in the LoS as well as delivering cost reductions. The results and analysis presented in our current paper can help educate patients and healthcare consumers about trends in healthcare costs and how they can be reduced. An informed and educated electorate can press their elected representatives to make changes to the healthcare system to benefit the populace.

Hachesu et al. examined the LoS for cardiac disease patients [ 22 ] where they used data from around 5000 patients and considered 35 input variables to build a predictive model. They found that the LoS was longer in patients with high blood pressure. In contrast, our method uses data from 2.5 million patients and considers multiple disease conditions simultaneously. We also do not have access to patient vitals such as blood pressure measurements, due to the limitation of the existing New York State SPARCS data.

Garcia et al. [ 23 ] conducted a study of elderly patients (age greater than 60) to understand factors governing the LoS for hip fracture treatment. They used 660 patient records and determined that the most significant variable was the American Society of Anesthesiologists (ASA) classification system. The ASA score ranges from 1–5 and captures the anesthesiologist’s impression of a patient’s health and comorbidities at the time of surgery. Garcia et al. showed a monotonically increasing relationship between the ASA score and the LoS. However, they did not build a specific predictive model. Their work shows that it is possible to find single variables with significant information content in order to estimate the LoS. The New York SPARCS dataset that we used does not contain the ASA score. Hence a policy implication of our research is to alert the healthcare authorities include such variables such as the ASA score where relevant in the datasets released in the future. The additional storage required is very small (one additional byte per patient record).

Arjannikov et al. [ 25 ] developed predictive models by binarizing the data into two categories, e.g. LoS <  = 2 days or LoS > 2 days. In our work, we did not employ such a discretization. In contrast, we used continuous regression techniques as well as classification into more than two bins. It is preferable to stay as close to the actual data as possible.

Almashrafi et al. [ 27 ] and Cots et al. [ 75 ] observed that larger hospitals tended to have longer LoS for patients undergoing cardiac surgery. Though we did not specifically examine cardiac surgery outcomes, our feature analysis indicated that the hospital operating certificate number had lower relevance than other features such as DRG codes. Nevertheless, the SHAP plots in Fig.  7 and Fig.  8 show that the hospital operating certificate number occurs within the top 10 features in order of SHAP values. We will investigate this relationship in more detail in future research, as it requires determining the size of the hospital from the operating certificate number and creating an appropriate machine-learning model. The Appendix contains results that show certain operating certificate numbers that produce a good model fit to the data.

A major focus of our research is on building interpretable and explainable models. Based on the principle of parsimony, it is preferable to utilize models which involve fewer features. This will provide simpler explanations to healthcare professionals as well as patients. We have shown through Fig.  20 that a model with five features performs just as well as a model with seven features. These features also make intuitive sense and the model’s operation can be understood by both patients and healthcare providers.

Patients in the U.S. increasingly have to pay for medical procedures out-of-pocket as insurance payments do not cover all the expenses, leading to unexpectedly large bills [ 76 ]. Many patients also do not possess health insurance in the U.S., with the consequence that they get charged the highest [ 77 ]. Kullgreen et.al. observe that patients in the U.S. need to be discerning healthcare consumers [ 78 ], as they can optimize the value they receive from out-of-pocket spending. In addition to estimating the cost of medical procedures, patients will also benefit from estimating the expected duration for a procedure such as joint replacement. This will allow them to budget adequate time for their medical procedures. Patients and consumers will benefit from obtaining estimates from an unbiased open data source such as New York State SPARCS and the use of our model.

Other researchers have developed specific LoS models for particular health conditions, such as cardiac disease [ 22 ], hip replacement [ 21 ], cancer [ 26 ], or COVID-19 [ 24 ]. In addition, researchers typically assume a prior statistical distribution for the outcomes, such a Weibull distribution [ 24 ]. However, we have not made any assumptions of specific prior statistical distributions, nor have we restricted our analysis to specific diseases. Consequently, our model and techniques should be more widely applicable, especially in the face of rapidly changing disease trajectories worldwide.

Our study is based exclusively on freely available open health data. Consequently, we cannot control the granularity of the data and must use the data as-is. We are unable to obtain more detailed patient information such as their physiological variables such as blood pressure, heartrate variability etc. at the time of admittance and during their stay. Hospitals, healthcare providers, and insurers have access to this data. However, there is no mandate for them to make this available to researchers outside their own organizations. Sometimes they sell de-identified data to interested parties such as pharmaceutical companies [ 79 ]. Due to the high costs involved in purchasing this data, researchers worldwide, especially in developing countries are at a disadvantage in developing AI algorithms for healthcare.

There is growing recognition that medical researchers need to standardize data formats and tools used for their analysis, and share them openly. One such effort is the organization for Observational Health Data Sciences and Informatics (OHDSI) as described in [ 80 ].

Twitter has demonstrated an interesting path forward, where a small percentage of its data was made available freely to all users for non-commercial purposes through an API [ 81 ]. Recently, Twitter has made a larger proportion of its data available to qualified academic researchers [ 82 ]. In the future, the profit motives of companies need to be balanced with considerations for the greater public good. An advantage of using the Twitter model is that it spurs more academic research and allows universities to train students and the workforce of the future on real-world and relevant datasets.

In the U.S., a new law went into effect in January 2021 requiring hospitals to make pricing data available publicly. The premise is that having this data would provide better transparency into the working of the healthcare system in the U.S. and lead to cost efficiencies. However, most hospitals are not in compliance with this law [ 83 ]. Concerted efforts by government officials as well as pressure by the public will be necessary to achieve compliance. If the eventual release of such data is not accompanied by a corresponding interest shown by academicians, healthcare researchers, policymakers, and the public it is likely that the very premise of the utility of this data will be called into question. Furthermore, merely dumping large quantities of data into the public domain is unlikely to benefit anyone. Hence research efforts such as the one presented in this paper will be valuable in demonstrating the utility of this data to all stakeholders.

Our machine-learning pipeline can easily be applied to new data that will be released periodically by New York SPARCS, and also to hospital pricing data [ 83 ]. Due to our open-source methodology, other researchers can easily extend our work and apply it to extract meaning from open health data. This improves reproducibility, which is an essential aspect of science. We will make our code available on Github to interested researchers for non-commercial purposes.

Limitations of our models

Our models are restricted to the data available through New York State SPARCS, which does not provide detailed information about patient vitals. More detailed physiological data is available through the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) framework [ 84 ], though for a smaller number of patients. We plan to extend our methodology to handle such data in the future. Another limitation of our study is that it does not account for patient co-morbidities. This arises from the de-identification process used to release the SPARCS data, where patient information is removed. Hence we are unable to analyze multiple hospital admissions for a given patient, possibly for different conditions. The main advantage of our approach is that it uses large-scale population data (2.3 million patients) but at a coarse level of granularity, where physiological data is not available. Nevertheless, our approach provides a high-level view of the operation of the healthcare system, which provides valuable insights.

There is growing interest in using data analytics to increase government transparency and inform policymaking. It is expected that the meaning and insights gained from such evidence-based analysis will translate to better policies and optimal usage of the available infrastructure. This requires cooperation between computer scientists, domain experts, and policy makers. Open healthcare data is especially valuable in this context due to its economic significance. This paper presents an open-source analytics system to conduct evidence-based analysis on openly available healthcare data.

The goal is to develop interpretable machine learning models that identify key drivers and make accurate predictions related to healthcare costs and utilization. Such models can provide actionable insights to guide healthcare administrators and policy makers. A specific illustration is provided via a robust machine learning pipeline that predicts hospital length of stay across 285 disease categories based on 2.3 million de-identified patient records. The length of stay is directly related to costs.

We focused on the interpretability and explainability of input features and the resulting models. Hence, we developed separate models for newborns and non-newborns, given differences in input features. The best performing model for non-newborn data was catboost regression, which used linear regression and achieved an R 2 score of 0.43. The best performing model for newborns and non-newborns respectively was linear regression, which achieved an R 2 score of 0.82. Key newborn predictors included birth weight, while non-newborn models relied heavily on the diagnostic related group classification. This demonstrates model interpretability, which is important for adoption. There is an opportunity to further improve performance for specific diseases. If we restrict our analysis to cardiovascular disease, we obtain an improved R 2 score of 0.62.

The presented approach has several desirable qualities. Firstly, transparency and reproducibility are enabled through the open-source methodology. Secondly, the model generalizability facilitates insights across numerous disease states. Thirdly, the technical framework can easily integrate new data while allowing modular extensions by the research community. Lastly, the evidence generated can readily inform multiple key stakeholders including healthcare administrators planning capacity, policy makers optimizing delivery, and patients making medical decisions.

Availability of data and materials

Data is publicly available at the website mentioned in the paper, https://www.health.ny.gov/statistics/sparcs/

There is an “About Us” tab in the website which contains all the contact details. The authors have nothing to do with this website as it is maintained by New York State.

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We are grateful to the New York State SPARCS program for making the data available freely to the public. We greatly appreciate the feedback provided by the anonymous reviewers which helped in improving the quality of this manuscript.

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Jain, R., Singh, M., Rao, A.R. et al. Predicting hospital length of stay using machine learning on a large open health dataset. BMC Health Serv Res 24 , 860 (2024). https://doi.org/10.1186/s12913-024-11238-y

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Received : 19 June 2023

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DOI : https://doi.org/10.1186/s12913-024-11238-y

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