case study on depression in psychology

Mental Health Case Study: Understanding Depression through a Real-life Example

Through the lens of a gripping real-life case study, we delve into the depths of depression, unraveling its complexities and shedding light on the power of understanding mental health through individual experiences. Mental health case studies serve as invaluable tools in our quest to comprehend the intricate workings of the human mind and the various conditions that can affect it. By examining real-life examples, we gain profound insights into the lived experiences of individuals grappling with mental health challenges, allowing us to develop more effective strategies for diagnosis, treatment, and support.

The Importance of Case Studies in Understanding Mental Health

Case studies play a crucial role in the field of mental health research and practice. They provide a unique window into the personal narratives of individuals facing mental health challenges, offering a level of detail and context that is often missing from broader statistical analyses. By focusing on specific cases, researchers and clinicians can gain a deeper understanding of the complex interplay between biological, psychological, and social factors that contribute to mental health conditions.

One of the primary benefits of using real-life examples in mental health case studies is the ability to humanize the experience of mental illness. These narratives help to break down stigma and misconceptions surrounding mental health conditions, fostering empathy and understanding among both professionals and the general public. By sharing the stories of individuals who have faced and overcome mental health challenges, case studies can also provide hope and inspiration to those currently struggling with similar issues.

Depression, in particular, is a common mental health condition that affects millions of people worldwide. Disability Function Report Example Answers for Depression and Bipolar: A Comprehensive Guide offers valuable insights into how depression can impact daily functioning and the importance of accurate reporting in disability assessments. By examining depression through the lens of a case study, we can gain a more nuanced understanding of its manifestations, challenges, and potential treatment approaches.

Understanding Depression

Before delving into our case study, it’s essential to establish a clear understanding of depression and its impact on individuals and society. Depression is a complex mental health disorder characterized by persistent feelings of sadness, hopelessness, and loss of interest in activities. It can affect a person’s thoughts, emotions, behaviors, and overall well-being.

Some common symptoms of depression include:

– Persistent sad, anxious, or “empty” mood – Feelings of hopelessness or pessimism – Irritability – Loss of interest or pleasure in hobbies and activities – Decreased energy or fatigue – Difficulty concentrating, remembering, or making decisions – Sleep disturbances (insomnia or oversleeping) – Appetite and weight changes – Physical aches or pains without clear physical causes – Thoughts of death or suicide

The prevalence of depression worldwide is staggering. According to the World Health Organization, more than 264 million people of all ages suffer from depression globally. It is a leading cause of disability and contributes significantly to the overall global burden of disease. The impact of depression extends far beyond the individual, affecting families, communities, and economies.

Depression can have profound consequences on an individual’s quality of life, relationships, and ability to function in daily activities. It can lead to decreased productivity at work or school, strained personal relationships, and increased risk of other health problems. The economic burden of depression is also substantial, with costs associated with healthcare, lost productivity, and disability.

The Significance of Case Studies in Mental Health Research

Case studies serve as powerful tools in mental health research, offering unique insights that complement broader statistical analyses and controlled experiments. They allow researchers and clinicians to explore the nuances of individual experiences, providing a rich tapestry of information that can inform our understanding of mental health conditions and guide the development of more effective treatment strategies.

One of the key advantages of case studies is their ability to capture the complexity of mental health conditions. Unlike standardized questionnaires or diagnostic criteria, case studies can reveal the intricate interplay between biological, psychological, and social factors that contribute to an individual’s mental health. This holistic approach is particularly valuable in understanding conditions like depression, which often have multifaceted causes and manifestations.

Case studies also play a crucial role in the development of treatment strategies. By examining the detailed accounts of individuals who have undergone various interventions, researchers and clinicians can identify patterns of effectiveness and potential barriers to treatment. This information can then be used to refine existing approaches or develop new, more targeted interventions.

Moreover, case studies contribute to the advancement of mental health research by generating hypotheses and identifying areas for further investigation. They can highlight unique aspects of a condition or treatment that may not be apparent in larger-scale studies, prompting researchers to explore new avenues of inquiry.

Examining a Real-life Case Study of Depression

To illustrate the power of case studies in understanding depression, let’s examine the story of Sarah, a 32-year-old marketing executive who sought help for persistent feelings of sadness and loss of interest in her once-beloved activities. Sarah’s case provides a compelling example of how depression can manifest in high-functioning individuals and the challenges they face in seeking and receiving appropriate treatment.

Background: Sarah had always been an ambitious and driven individual, excelling in her career and maintaining an active social life. However, over the past year, she began to experience a gradual decline in her mood and energy levels. Initially, she attributed these changes to work stress and the demands of her busy lifestyle. As time went on, Sarah found herself increasingly isolated, withdrawing from friends and family, and struggling to find joy in activities she once loved.

Presentation of Symptoms: When Sarah finally sought help from a mental health professional, she presented with the following symptoms:

– Persistent feelings of sadness and emptiness – Loss of interest in hobbies and social activities – Difficulty concentrating at work – Insomnia and daytime fatigue – Unexplained physical aches and pains – Feelings of worthlessness and guilt – Occasional thoughts of death, though no active suicidal ideation

Initial Diagnosis: Based on Sarah’s symptoms and their duration, her therapist diagnosed her with Major Depressive Disorder (MDD). This diagnosis was supported by the presence of multiple core symptoms of depression that had persisted for more than two weeks and significantly impacted her daily functioning.

The Treatment Journey

Sarah’s case study provides an opportunity to explore the various treatment options available for depression and examine their effectiveness in a real-world context. Supporting a Caseworker’s Client Who Struggles with Depression offers valuable insights into the role of support systems in managing depression, which can complement professional treatment approaches.

Overview of Treatment Options: There are several evidence-based treatments available for depression, including:

1. Psychotherapy: Various forms of talk therapy, such as Cognitive Behavioral Therapy (CBT) and Interpersonal Therapy (IPT), can help individuals identify and change negative thought patterns and behaviors associated with depression.

2. Medication: Antidepressants, such as Selective Serotonin Reuptake Inhibitors (SSRIs), can help regulate brain chemistry and alleviate symptoms of depression.

3. Combination Therapy: Many individuals benefit from a combination of psychotherapy and medication.

4. Lifestyle Changes: Exercise, improved sleep habits, and stress reduction techniques can complement other treatments.

5. Alternative Therapies: Some individuals find relief through approaches like mindfulness meditation, acupuncture, or light therapy.

Treatment Plan for Sarah: After careful consideration of Sarah’s symptoms, preferences, and lifestyle, her treatment team developed a comprehensive plan that included:

1. Weekly Cognitive Behavioral Therapy sessions to address negative thought patterns and develop coping strategies.

2. Prescription of an SSRI antidepressant to help alleviate her symptoms.

3. Recommendations for lifestyle changes, including regular exercise and improved sleep hygiene.

4. Gradual reintroduction of social activities and hobbies to combat isolation.

Effectiveness of the Treatment Approach: Sarah’s response to treatment was monitored closely over the following months. Initially, she experienced some side effects from the medication, including mild nausea and headaches, which subsided after a few weeks. As she continued with therapy and medication, Sarah began to notice gradual improvements in her mood and energy levels.

The CBT sessions proved particularly helpful in challenging Sarah’s negative self-perceptions and developing more balanced thinking patterns. She learned to recognize and reframe her automatic negative thoughts, which had been contributing to her feelings of worthlessness and guilt.

The combination of medication and therapy allowed Sarah to regain the motivation to engage in physical exercise and social activities. As she reintegrated these positive habits into her life, she experienced further improvements in her mood and overall well-being.

The Outcome and Lessons Learned

Sarah’s journey through depression and treatment offers valuable insights into the complexities of mental health and the effectiveness of various interventions. Understanding the Link Between Sapolsky and Depression provides additional context on the biological underpinnings of depression, which can complement the insights gained from individual case studies.

Progress and Challenges: Over the course of six months, Sarah made significant progress in managing her depression. Her mood stabilized, and she regained interest in her work and social life. She reported feeling more energetic and optimistic about the future. However, her journey was not without challenges. Sarah experienced setbacks during particularly stressful periods at work and struggled with the stigma associated with taking medication for mental health.

One of the most significant challenges Sarah faced was learning to prioritize her mental health in a high-pressure work environment. She had to develop new boundaries and communication strategies to manage her workload effectively without compromising her well-being.

Key Lessons Learned: Sarah’s case study highlights several important lessons about depression and its treatment:

1. Early intervention is crucial: Sarah’s initial reluctance to seek help led to a prolongation of her symptoms. Recognizing and addressing mental health concerns early can prevent the condition from worsening.

2. Treatment is often multifaceted: The combination of medication, therapy, and lifestyle changes proved most effective for Sarah, underscoring the importance of a comprehensive treatment approach.

3. Recovery is a process: Sarah’s improvement was gradual and non-linear, with setbacks along the way. This emphasizes the need for patience and persistence in mental health treatment.

4. Social support is vital: Reintegrating social activities and maintaining connections with friends and family played a crucial role in Sarah’s recovery.

5. Workplace mental health awareness is essential: Sarah’s experience highlights the need for greater understanding and support for mental health issues in professional settings.

6. Stigma remains a significant barrier: Despite her progress, Sarah struggled with feelings of shame and fear of judgment related to her depression diagnosis and treatment.

Sarah’s case study provides a vivid illustration of the complexities of depression and the power of comprehensive, individualized treatment approaches. By examining her journey, we gain valuable insights into the lived experience of depression, the challenges of seeking and maintaining treatment, and the potential for recovery.

The significance of case studies in understanding and treating mental health conditions cannot be overstated. They offer a level of detail and nuance that complements broader research methodologies, providing clinicians and researchers with invaluable insights into the diverse manifestations of mental health disorders and the effectiveness of various interventions.

As we continue to explore mental health through case studies, it’s important to recognize the diversity of experiences within conditions like depression. Personal Bipolar Psychosis Stories: Understanding Bipolar Disorder Through Real Experiences offers insights into another complex mental health condition, illustrating the range of experiences individuals may face.

Furthermore, it’s crucial to consider how mental health issues are portrayed in popular culture, as these representations can shape public perceptions. Understanding Mental Disorders in Winnie the Pooh: Exploring the Depiction of Depression provides an interesting perspective on how mental health themes can be embedded in seemingly lighthearted stories.

The field of mental health research and treatment continues to evolve, driven by the insights gained from individual experiences and comprehensive studies. By combining the rich, detailed narratives provided by case studies with broader research methodologies, we can develop more effective, personalized approaches to mental health care. As we move forward, it is essential to continue exploring and sharing these stories, fostering greater understanding, empathy, and support for those facing mental health challenges.

References:

1. World Health Organization. (2021). Depression. Retrieved from https://www.who.int/news-room/fact-sheets/detail/depression

2. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

3. Beck, A. T., & Alford, B. A. (2009). Depression: Causes and treatment. University of Pennsylvania Press.

4. Cuijpers, P., Quero, S., Dowrick, C., & Arroll, B. (2019). Psychological treatment of depression in primary care: Recent developments. Current Psychiatry Reports, 21(12), 129.

5. Malhi, G. S., & Mann, J. J. (2018). Depression. The Lancet, 392(10161), 2299-2312.

6. Otte, C., Gold, S. M., Penninx, B. W., Pariante, C. M., Etkin, A., Fava, M., … & Schatzberg, A. F. (2016). Major depressive disorder. Nature Reviews Disease Primers, 2(1), 1-20.

7. Sapolsky, R. M. (2004). Why zebras don’t get ulcers: The acclaimed guide to stress, stress-related diseases, and coping. Holt paperbacks.

8. Yin, R. K. (2017). Case study research and applications: Design and methods. Sage publications.

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4 Treatment of Depression

• Published: February 2013
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Chapter 4 covers the treatment of depression, and discusses popular myths regarding depression, its frequency, characteristics and diagnosis, and includes case studies, assessment, case conceptualization, intervention development and course of treatment, problems that may arise in therapy, ethical considerations, common mistakes in the course of treatment, relapse prevention, and cultural factors.

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Leanne: A Case Study in Major Depressive Disorder, Recurrent

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Biological, Psychological, and Social Determinants of Depression: A Review of Recent Literature

Olivia remes.

1 Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK

João Francisco Mendes

2 NOVA Medical School, Universidade NOVA de Lisboa, 1099-085 Lisbon, Portugal; ku.ca.mac@94cfj

Peter Templeton

3 IfM Engage Limited, Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK; ku.ca.mac@32twp

4 The William Templeton Foundation for Young People’s Mental Health (YPMH), Cambridge CB2 0AH, UK

Associated Data

Depression is one of the leading causes of disability, and, if left unmanaged, it can increase the risk for suicide. The evidence base on the determinants of depression is fragmented, which makes the interpretation of the results across studies difficult. The objective of this study is to conduct a thorough synthesis of the literature assessing the biological, psychological, and social determinants of depression in order to piece together the puzzle of the key factors that are related to this condition. Titles and abstracts published between 2017 and 2020 were identified in PubMed, as well as Medline, Scopus, and PsycInfo. Key words relating to biological, social, and psychological determinants as well as depression were applied to the databases, and the screening and data charting of the documents took place. We included 470 documents in this literature review. The findings showed that there are a plethora of risk and protective factors (relating to biological, psychological, and social determinants) that are related to depression; these determinants are interlinked and influence depression outcomes through a web of causation. In this paper, we describe and present the vast, fragmented, and complex literature related to this topic. This review may be used to guide practice, public health efforts, policy, and research related to mental health and, specifically, depression.

1. Introduction

Depression is one of the most common mental health issues, with an estimated prevalence of 5% among adults [ 1 , 2 ]. Symptoms may include anhedonia, feelings of worthlessness, concentration and sleep difficulties, and suicidal ideation. According to the World Health Organization, depression is a leading cause of disability; research shows that it is a burdensome condition with a negative impact on educational trajectories, work performance, and other areas of life [ 1 , 3 ]. Depression can start early in the lifecourse and, if it remains unmanaged, may increase the risk for substance abuse, chronic conditions, such as cardiovascular disease, and premature mortality [ 4 , 5 , 6 , 7 , 8 ].

Treatment for depression exists, such as pharmacotherapy, cognitive behavioural therapy, and other modalities. A meta-analysis of randomized, placebo-controlled trials of patients shows that 56–60% of people respond well to active treatment with antidepressants (selective serotonin reuptake inhibitors, tricyclic antidepressants) [ 9 ]. However, pharmacotherapy may be associated with problems, such as side-effects, relapse issues, a potential duration of weeks until the medication starts working, and possible limited efficacy in mild cases [ 10 , 11 , 12 , 13 , 14 ]. Psychotherapy is also available, but access barriers can make it difficult for a number of people to get the necessary help.

Studies on depression have increased significantly over the past few decades. However, the literature remains fragmented and the interpretation of heterogeneous findings across studies and between fields is difficult. The cross-pollination of ideas between disciplines, such as genetics, neurology, immunology, and psychology, is limited. Reviews on the determinants of depression have been conducted, but they either focus exclusively on a particular set of determinants (ex. genetic risk factors [ 15 ]) or population sub-group (ex. children and adolescents [ 16 ]) or focus on characteristics measured predominantly at the individual level (ex. focus on social support, history of depression [ 17 ]) without taking the wider context (ex. area-level variables) into account. An integrated approach paying attention to key determinants from the biological, psychological, and social spheres, as well as key themes, such as the lifecourse perspective, enables clinicians and public health authorities to develop tailored, person-centred approaches.

The primary aim of this literature review: to address the aforementioned challenges, we have synthesized recent research on the biological, psychological, and social determinants of depression and we have reviewed research from fields including genetics, immunology, neurology, psychology, public health, and epidemiology, among others.

The subsidiary aim: we have paid special attention to important themes, including the lifecourse perspective and interactions between determinants, to guide further efforts by public health and medical professionals.

This literature review can be used as an evidence base by those in public health and the clinical setting and can be used to inform targeted interventions.

2. Materials and Methods

We conducted a review of the literature on the biological, psychological, and social determinants of depression in the last 4 years. We decided to focus on these determinants after discussions with academics (from the Manchester Metropolitan University, University of Cardiff, University of Colorado, Boulder, University of Cork, University of Leuven, University of Texas), charity representatives, and people with lived experience at workshops held by the University of Cambridge in 2020. In several aspects, we attempted to conduct this review according to PRISMA guidelines [ 18 ].

The inclusion and exclusion criteria are the following:

• - We included documents, such as primary studies, literature reviews, systematic reviews, meta-analyses, reports, and commentaries on the determinants of depression. The determinants refer to variables that appear to be linked to the development of depression, such as physiological factors (e.g., the nervous system, genetics), but also factors that are further away or more distal to the condition. Determinants may be risk or protective factors, and individual- or wider-area-level variables.
• - We focused on major depressive disorder, treatment-resistant depression, dysthymia, depressive symptoms, poststroke depression, perinatal depression, as well as depressive-like behaviour (common in animal studies), among others.
• - We included papers regardless of the measurement methods of depression.
• - We included papers that focused on human and/or rodent research.
• - This review focused on articles written in the English language.
• - Documents published between 2017–2020 were captured to provide an understanding of the latest research on this topic.
• - Studies that assessed depression as a comorbidity or secondary to another disorder.
• - Studies that did not focus on rodent and/or human research.
• - Studies that focused on the treatment of depression. We made this decision, because this is an in-depth topic that would warrant a separate stand-alone review.
• Next, we searched PubMed (2017–2020) using keywords related to depression and determinants. Appendix A contains the search strategy used. We also conducted focused searches in Medline, Scopus, and PsycInfo (2017–2020).
• Once the documents were identified through the databases, the inclusion and exclusion criteria were applied to the titles and abstracts. Screening of documents was conducted by O.R., and a subsample was screened by J.M.; any discrepancies were resolved through a communication process.
• The full texts of documents were retrieved, and the inclusion and exclusion criteria were again applied. A subsample of documents underwent double screening by two authors (O.R., J.M.); again, any discrepancies were resolved through communication.
• a. A data charting form was created to capture the data elements of interest, including the authors, titles, determinants (biological, psychological, social), and the type of depression assessed by the research (e.g., major depression, depressive symptoms, depressive behaviour).
• b. The data charting form was piloted on a subset of documents, and refinements to it were made. The data charting form was created with the data elements described above and tested in 20 studies to determine whether refinements in the wording or language were needed.
• c. Data charting was conducted on the documents.
• d. Narrative analysis was conducted on the data charting table to identify key themes. When a particular finding was noted more than once, it was logged as a potential theme, with a review of these notes yielding key themes that appeared on multiple occasions. When key themes were identified, one researcher (O.R.) reviewed each document pertaining to that theme and derived concepts (key determinants and related outcomes). This process (a subsample) was verified by a second author (J.M.), and the two authors resolved any discrepancies through communication. Key themes were also checked as to whether they were of major significance to public mental health and at the forefront of public health discourse according to consultations we held with stakeholders from the Manchester Metropolitan University, University of Cardiff, University of Colorado, Boulder, University of Cork, University of Leuven, University of Texas, charity representatives, and people with lived experience at workshops held by the University of Cambridge in 2020.

We condensed the extensive information gleaned through our review into short summaries (with key points boxes for ease of understanding and interpretation of the data).

Through the searches, 6335 documents, such as primary studies, literature reviews, systematic reviews, meta-analyses, reports, and commentaries, were identified. After applying the inclusion and exclusion criteria, 470 papers were included in this review ( Supplementary Table S1 ). We focused on aspects related to biological, psychological, and social determinants of depression (examples of determinants and related outcomes are provided under each of the following sections.

3.1. Biological Factors

The following aspects will be discussed in this section: physical health conditions; then specific biological factors, including genetics; the microbiome; inflammatory factors; stress and hypothalamic–pituitary–adrenal (HPA) axis dysfunction, and the kynurenine pathway. Finally, aspects related to cognition will also be discussed in the context of depression.

3.1.1. Physical Health Conditions

Studies on physical health conditions—key points:

• The presence of a physical health condition can increase the risk for depression
• Psychological evaluation in physically sick populations is needed
• There is large heterogeneity in study design and measurement; this makes the comparison of findings between and across studies difficult

A number of studies examined the links between the outcome of depression and physical health-related factors, such as bladder outlet obstruction, cerebral atrophy, cataract, stroke, epilepsy, body mass index and obesity, diabetes, urinary tract infection, forms of cancer, inflammatory bowel disorder, glaucoma, acne, urea accumulation, cerebral small vessel disease, traumatic brain injury, and disability in multiple sclerosis [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 ]. For example, bladder outlet obstruction has been linked to inflammation and depressive behaviour in rodent research [ 24 ]. The presence of head and neck cancer also seemed to be related to an increased risk for depressive disorder [ 45 ]. Gestational diabetes mellitus has been linked to depressive symptoms in the postpartum period (but no association has been found with depression in the third pregnancy trimester) [ 50 ], and a plethora of other such examples of relationships between depression and physical conditions exist. As such, the assessment of psychopathology and the provision of support are necessary in individuals of ill health [ 45 ]. Despite the large evidence base on physical health-related factors, differences in study methodology and design, the lack of standardization when it comes to the measurement of various physical health conditions and depression, and heterogeneity in the study populations makes it difficult to compare studies [ 50 ].

The next subsections discuss specific biological factors, including genetics; the microbiome; inflammatory factors; stress and hypothalamic–pituitary–adrenal (HPA) axis dysfunction, and the kynurenine pathway; and aspects related to cognition.

3.1.2. Genetics

Studies on genetics—key points:

There were associations between genetic factors and depression; for example:

• The brain-derived neurotrophic factor (BDNF) plays an important role in depression
• Links exist between major histocompatibility complex region genes, as well as various gene polymorphisms and depression
• Single nucleotide polymorphisms (SNPs) of genes involved in the tryptophan catabolites pathway are of interest in relation to depression

A number of genetic-related factors, genomic regions, polymorphisms, and other related aspects have been examined with respect to depression [ 61 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 ]. The influence of BDNF in relation to depression has been amply studied [ 117 , 118 , 141 , 142 , 143 ]. Research has shown associations between depression and BDNF (as well as candidate SNPs of the BDNF gene, polymorphisms of the BDNF gene, and the interaction of these polymorphisms with other determinants, such as stress) [ 129 , 144 , 145 ]. Specific findings have been reported: for example, a study reported a link between the BDNF rs6265 allele (A) and major depressive disorder [ 117 ].

Other research focused on major histocompatibility complex region genes, endocannabinoid receptor gene polymorphisms, as well as tissue-specific genes and gene co-expression networks and their links to depression [ 99 , 110 , 112 ]. The SNPs of genes involved in the tryptophan catabolites pathway have also been of interest when studying the pathogenesis of depression.

The results from genetics studies are compelling; however, the findings remain mixed. One study indicated no support for depression candidate gene findings [ 122 ]. Another study found no association between specific polymorphisms and major depressive disorder [ 132 ]. As such, further research using larger samples is needed to corroborate the statistically significant associations reported in the literature.

3.1.3. Microbiome

Studies on the microbiome—key points:

• The gut bacteria and the brain communicate via both direct and indirect pathways called the gut-microbiota-brain axis (the bidirectional communication networks between the central nervous system and the gastrointestinal tract; this axis plays an important role in maintaining homeostasis).
• A disordered microbiome can lead to inflammation, which can then lead to depression
• There are possible links between the gut microbiome, host liver metabolism, brain inflammation, and depression

The common themes of this review have focused on the microbiome/microbiota or gut metabolome [ 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 ], the microbiota-gut-brain axis, and related factors [ 152 , 162 , 163 , 164 , 165 , 166 , 167 ]. When there is an imbalance in the intestinal bacteria, this can interfere with emotional regulation and contribute to harmful inflammatory processes and mood disorders [ 148 , 151 , 153 , 155 , 157 ]. Rodent research has shown that there may be a bidirectional association between the gut microbiota and depression: a disordered gut microbiota can play a role in the onset of this mental health problem, but, at the same time, the existence of stress and depression may also lead to a lower level of richness and diversity in the microbiome [ 158 ].

Research has also attempted to disentangle the links between the gut microbiome, host liver metabolism, brain inflammation, and depression, as well as the role of the ratio of lactobacillus to clostridium [ 152 ]. The literature has also examined the links between medication, such as antibiotics, and mood and behaviour, with the findings showing that antibiotics may be related to depression [ 159 , 168 ]. The links between the microbiome and depression are complex, and further studies are needed to determine the underpinning causal mechanisms.

3.1.4. Inflammation

Studies on inflammation—key points:

• Pro-inflammatory cytokines are linked to depression
• Pro-inflammatory cytokines, such as the tumour necrosis factor (TNF)-alpha, may play an important role
• Different methods of measurement are used, making the comparison of findings across studies difficult

Inflammation has been a theme in this literature review [ 60 , 161 , 164 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 ]. The findings show that raised levels of inflammation (because of factors such as pro-inflammatory cytokines) have been associated with depression [ 60 , 161 , 174 , 175 , 178 ]. For example, pro-inflammatory cytokines, such as tumour necrosis factor (TNF)-alpha, have been linked to depression [ 185 ]. Various determinants, such as early life stress, have also been linked to systemic inflammation, and this can increase the risk for depression [ 186 ].

Nevertheless, not everyone with elevated inflammation develops depression; therefore, this is just one route out of many linked to pathogenesis. Despite the compelling evidence reported with respect to inflammation, it is difficult to compare the findings across studies because of different methods used to assess depression and its risk factors.

3.1.5. Stress and HPA Axis Dysfunction

Studies on stress and HPA axis dysfunction—key points:

• Stress is linked to the release of proinflammatory factors
• The dysregulation of the HPA axis is linked to depression
• Determinants are interlinked in a complex web of causation

Stress was studied in various forms in rodent populations and humans [ 144 , 145 , 155 , 174 , 176 , 180 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , 193 , 194 , 195 , 196 , 197 , 198 , 199 , 200 , 201 , 202 , 203 , 204 , 205 , 206 , 207 , 208 , 209 , 210 , 211 ].

Although this section has some overlap with others (as is to be expected because all of these determinants and body systems are interlinked), a number of studies have focused on the impact of stress on mental health. Stress has been mentioned in the literature as a risk factor of poor mental health and has emerged as an important determinant of depression. The effects of this variable are wide-ranging, and a short discussion is warranted.

Stress has been linked to the release of inflammatory factors, as well as the development of depression [ 204 ]. When the stress is high or lasts for a long period of time, this may negatively impact the brain. Chronic stress can impact the dendrites and synapses of various neurons, and may be implicated in the pathway leading to major depressive disorder [ 114 ]. As a review by Uchida et al. indicates, stress may be associated with the “dysregulation of neuronal and synaptic plasticity” [ 114 ]. Even in rodent studies, stress has a negative impact: chronic and unpredictable stress (and other forms of tension or stress) have been linked to unusual behaviour and depression symptoms [ 114 ].

The depression process and related brain changes, however, have also been linked to the hyperactivity or dysregulation of the HPA axis [ 127 , 130 , 131 , 182 , 212 ]. One review indicates that a potential underpinning mechanism of depression relates to “HPA axis abnormalities involved in chronic stress” [ 213 ]. There is a complex relationship between the HPA axis, glucocorticoid receptors, epigenetic mechanisms, and psychiatric sequelae [ 130 , 212 ].

In terms of the relationship between the HPA axis and stress and their influence on depression, the diathesis–stress model offers an explanation: it could be that early stress plays a role in the hyperactivation of the HPA axis, thus creating a predisposition “towards a maladaptive reaction to stress”. When this predisposition then meets an acute stressor, depression may ensue; thus, in line with the diathesis–stress model, a pre-existing vulnerability and stressor can create fertile ground for a mood disorder [ 213 ]. An integrated review by Dean and Keshavan [ 213 ] suggests that HPA axis hyperactivity is, in turn, related to other determinants, such as early deprivation and insecure early attachment; this again shows the complex web of causation between the different determinants.

3.1.6. Kynurenine Pathway

Studies on the kynurenine pathway—key points:

• The kynurenine pathway is linked to depression
• Indolamine 2,3-dioxegenase (IDO) polymorphisms are linked to postpartum depression

The kynurenine pathway was another theme that emerged in this review [ 120 , 178 , 181 , 184 , 214 , 215 , 216 , 217 , 218 , 219 , 220 , 221 ]. The kynurenine pathway has been implicated not only in general depressed mood (inflammation-induced depression) [ 184 , 214 , 219 ] but also postpartum depression [ 120 ]. When the kynurenine metabolism pathway is activated, this results in metabolites, which are neurotoxic.

A review by Jeon et al. notes a link between the impairment of the kynurenine pathway and inflammation-induced depression (triggered by treatment for various physical diseases, such as malignancy). The authors note that this could represent an important opportunity for immunopharmacology [ 214 ]. Another review by Danzer et al. suggests links between the inflammation-induced activation of indolamine 2,3-dioxegenase (the enzyme that converts tryptophan to kynurenine), the kynurenine metabolism pathway, and depression, and also remarks about the “opportunities for treatment of inflammation-induced depression” [ 184 ].

3.1.7. Cognition

Studies on cognition and the brain—key points:

• Cognitive decline and cognitive deficits are linked to increased depression risk
• Cognitive reserve is important in the disability/depression relationship
• Family history of cognitive impairment is linked to depression

A number of studies have focused on the theme of cognition and the brain. The results show that factors, such as low cognitive ability/function, cognitive vulnerability, cognitive impairment or deficits, subjective cognitive decline, regression of dendritic branching and hippocampal atrophy/death of hippocampal cells, impaired neuroplasticity, and neurogenesis-related aspects, have been linked to depression [ 131 , 212 , 222 , 223 , 224 , 225 , 226 , 227 , 228 , 229 , 230 , 231 , 232 , 233 , 234 , 235 , 236 , 237 , 238 , 239 ]. The cognitive reserve appears to act as a moderator and can magnify the impact of certain determinants on poor mental health. For example, in a study in which participants with multiple sclerosis also had low cognitive reserve, disability was shown to increase the risk for depression [ 63 ]. Cognitive deficits can be both causal and resultant in depression. A study on individuals attending outpatient stroke clinics showed that lower scores in cognition were related to depression; thus, cognitive impairment appears to be associated with depressive symptomatology [ 226 ]. Further, Halahakoon et al. [ 222 ] note a meta-analysis [ 240 ] that shows that a family history of cognitive impairment (in first degree relatives) is also linked to depression.

In addition to cognitive deficits, low-level cognitive ability [ 231 ] and cognitive vulnerability [ 232 ] have also been linked to depression. While cognitive impairment may be implicated in the pathogenesis of depressive symptoms [ 222 ], negative information processing biases are also important; according to the ‘cognitive neuropsychological’ model of depression, negative affective biases play a central part in the development of depression [ 222 , 241 ]. Nevertheless, the evidence on this topic is mixed and further work is needed to determine the underpinning mechanisms between these states.

3.2. Psychological Factors

Studies on psychological factors—key points:

• There are many affective risk factors linked to depression
• Determinants of depression include negative self-concept, sensitivity to rejection, neuroticism, rumination, negative emotionality, and others

A number of studies have been undertaken on the psychological factors linked to depression (including mastery, self-esteem, optimism, negative self-image, current or past mental health conditions, and various other aspects, including neuroticism, brooding, conflict, negative thinking, insight, cognitive fusion, emotional clarity, rumination, dysfunctional attitudes, interpretation bias, and attachment style) [ 66 , 128 , 140 , 205 , 210 , 228 , 235 , 242 , 243 , 244 , 245 , 246 , 247 , 248 , 249 , 250 , 251 , 252 , 253 , 254 , 255 , 256 , 257 , 258 , 259 , 260 , 261 , 262 , 263 , 264 , 265 , 266 , 267 , 268 , 269 , 270 , 271 , 272 , 273 , 274 , 275 , 276 , 277 , 278 , 279 , 280 , 281 , 282 , 283 , 284 , 285 , 286 , 287 , 288 , 289 , 290 ]. Determinants related to this condition include low self-esteem and shame, among other factors [ 269 , 270 , 275 , 278 ]. Several emotional states and traits, such as neuroticism [ 235 , 260 , 271 , 278 ], negative self-concept (with self-perceptions of worthlessness and uselessness), and negative interpretation or attention biases have been linked to depression [ 261 , 271 , 282 , 283 , 286 ]. Moreover, low emotional clarity has been associated with depression [ 267 ]. When it comes to the severity of the disorder, it appears that meta-emotions (“emotions that occur in response to other emotions (e.g., guilt about anger)” [ 268 ]) have a role to play in depression [ 268 ].

A determinant that has received much attention in mental health research concerns rumination. Rumination has been presented as a mediator but also as a risk factor for depression [ 57 , 210 , 259 ]. When studied as a risk factor, it appears that the relationship of rumination with depression is mediated by variables that include limited problem-solving ability and insufficient social support [ 259 ]. However, rumination also appears to act as a mediator: for example, this variable (particularly brooding rumination) lies on the causal pathway between poor attention control and depression [ 265 ]. This shows that determinants may present in several forms: as moderators or mediators, risk factors or outcomes, and this is why disentangling the relationships between the various factors linked to depression is a complex task.

The psychological determinants are commonly researched variables in the mental health literature. A wide range of factors have been linked to depression, such as the aforementioned determinants, but also: (low) optimism levels, maladaptive coping (such as avoidance), body image issues, and maladaptive perfectionism, among others [ 269 , 270 , 272 , 273 , 275 , 276 , 279 , 285 , 286 ]. Various mechanisms have been proposed to explain the way these determinants increase the risk for depression. One of the underpinning mechanisms linking the determinants and depression concerns coping. For example, positive fantasy engagement, cognitive biases, or personality dispositions may lead to emotion-focused coping, such as brooding, and subsequently increase the risk for depression [ 272 , 284 , 287 ]. Knowing the causal mechanisms linking the determinants to outcomes provides insight for the development of targeted interventions.

3.3. Social Determinants

Studies on social determinants—key points:

• Social determinants are the conditions in the environments where people are born, live, learn, work, play, etc.; these influence (mental) health [ 291 ]
• There are many social determinants linked to depression, such as sociodemographics, social support, adverse childhood experiences
• Determinants can be at the individual, social network, community, and societal levels

Studies also focused on the social determinants of (mental) health; these are the conditions in which people are born, live, learn, work, play, and age, and have a significant influence on wellbeing [ 291 ]. Factors such as age, social or socioeconomic status, social support, financial strain and deprivation, food insecurity, education, employment status, living arrangements, marital status, race, childhood conflict and bullying, violent crime exposure, abuse, discrimination, (self)-stigma, ethnicity and migrant status, working conditions, adverse or significant life events, illiteracy or health literacy, environmental events, job strain, and the built environment have been linked to depression, among others [ 52 , 133 , 235 , 236 , 239 , 252 , 269 , 280 , 292 , 293 , 294 , 295 , 296 , 297 , 298 , 299 , 300 , 301 , 302 , 303 , 304 , 305 , 306 , 307 , 308 , 309 , 310 , 311 , 312 , 313 , 314 , 315 , 316 , 317 , 318 , 319 , 320 , 321 , 322 , 323 , 324 , 325 , 326 , 327 , 328 , 329 , 330 , 331 , 332 , 333 , 334 , 335 , 336 , 337 , 338 , 339 , 340 , 341 , 342 , 343 , 344 , 345 , 346 , 347 , 348 , 349 , 350 , 351 , 352 , 353 , 354 , 355 , 356 , 357 , 358 , 359 , 360 , 361 , 362 , 363 , 364 , 365 , 366 , 367 , 368 , 369 , 370 , 371 ]. Social support and cohesion, as well as structural social capital, have also been identified as determinants [ 140 , 228 , 239 , 269 , 293 , 372 , 373 , 374 , 375 , 376 , 377 , 378 , 379 ]. In a study, part of the findings showed that low levels of education have been shown to be linked to post-stroke depression (but not severe or clinical depression outcomes) [ 299 ]. A study within a systematic review indicated that having only primary education was associated with a higher risk of depression compared to having secondary or higher education (although another study contrasted this finding) [ 296 ]. Various studies on socioeconomic status-related factors have been undertaken [ 239 , 297 ]; the research has shown that a low level of education is linked to depression [ 297 ]. Low income is also related to depressive disorders [ 312 ]. By contrast, high levels of education and income are protective [ 335 ].

A group of determinants touched upon by several studies included adverse childhood or early life experiences: ex. conflict with parents, early exposure to traumatic life events, bullying and childhood trauma were found to increase the risk of depression (ex. through pathways, such as inflammation, interaction effects, or cognitive biases) [ 161 , 182 , 258 , 358 , 362 , 380 ].

Gender-related factors were also found to play an important role with respect to mental health [ 235 , 381 , 382 , 383 , 384 , 385 ]. Gender inequalities can start early on in the lifecourse, and women were found to be twice as likely to have depression as men. Gender-related factors were linked to cognitive biases, resilience and vulnerabilities [ 362 , 384 ].

Determinants can impact mental health outcomes through underpinning mechanisms. For example, harmful determinants can influence the uptake of risk behaviours. Risk behaviours, such as sedentary behaviour, substance abuse and smoking/nicotine exposure, have been linked to depression [ 226 , 335 , 355 , 385 , 386 , 387 , 388 , 389 , 390 , 391 , 392 , 393 , 394 , 395 , 396 , 397 , 398 , 399 , 400 , 401 ]. Harmful determinants can also have an impact on diet. Indeed, dietary aspects and diet components (ex. vitamin D, folate, selenium intake, iron, vitamin B12, vitamin K, fiber intake, zinc) as well as diet-related inflammatory potential have been linked to depression outcomes [ 161 , 208 , 236 , 312 , 396 , 402 , 403 , 404 , 405 , 406 , 407 , 408 , 409 , 410 , 411 , 412 , 413 , 414 , 415 , 416 , 417 , 418 , 419 , 420 , 421 , 422 , 423 , 424 , 425 , 426 , 427 , 428 ]. A poor diet has been linked to depression through mechanisms such as inflammation [ 428 ].

Again, it is difficult to constrict diet to the ‘social determinants of health’ category as it also relates to inflammation (biological determinants) and could even stand alone as its own category. Nevertheless, all of these factors are interlinked and influence one another in a complex web of causation, as mentioned elsewhere in the paper.

Supplementary Figure S1 contains a representation of key determinants acting at various levels: the individual, social network, community, and societal levels. The determinants have an influence on risk behaviours, and this, in turn, can affect the mood (i.e., depression), body processes (ex. can increase inflammation), and may negatively influence brain structure and function.

3.4. Others

Studies on ‘other’ determinants—key points:

• A number of factors are related to depression
• These may not be as easily categorized as the other determinants in this paper

A number of factors arose in this review that were related to depression; it was difficult to place these under a specific heading above, so this ‘other’ category was created. A number of these could be sorted under the ‘social determinants of depression’ category. For example, being exposed to deprivation, hardship, or adversity may increase the risk for air pollution exposure and nighttime shift work, among others, and the latter determinants have been found to increase the risk for depression. Air pollution could also be regarded as an ecologic-level (environmental) determinant of mental health.

Nevertheless, we have decided to leave these factors in a separate category (because their categorization may not be as immediately clear-cut as others), and these factors include: low-level light [ 429 ], weight cycling [ 430 ], water contaminants [ 431 ], trade [ 432 ], air pollution [ 433 , 434 ], program-level variables (ex. feedback and learning experience) [ 435 ], TV viewing [ 436 ], falls [ 437 ], various other biological factors [ 116 , 136 , 141 , 151 , 164 , 182 , 363 , 364 , 438 , 439 , 440 , 441 , 442 , 443 , 444 , 445 , 446 , 447 , 448 , 449 , 450 , 451 , 452 , 453 , 454 , 455 , 456 , 457 , 458 , 459 , 460 , 461 , 462 , 463 , 464 , 465 , 466 , 467 , 468 , 469 ], mobile phone use [ 470 ], ultrasound chronic exposure [ 471 ], nighttime shift work [ 472 ], work accidents [ 473 ], therapy enrollment [ 226 ], and exposure to light at night [ 474 ].

4. Cross-Cutting Themes

4.1. lifecourse perspective.

Studies on the lifecourse perspective—key points:

• Early life has an importance on mental health
• Stress has been linked to depression
• In old age, the decline in social capital is important

Trajectories and life events are important when it comes to the lifecourse perspective. Research has touched on the influence of prenatal or early life stress on an individual’s mental health trajectory [ 164 , 199 , 475 ]. Severe stress that occurs in the form of early-life trauma has also been associated with depressive symptoms [ 362 , 380 ]. It may be that some individuals exposed to trauma develop thoughts of personal failure, which then serve as a catalyst of depression [ 380 ].

At the other end of the life trajectory—old age—specific determinants have been linked to an increased risk for depression. Older people are at a heightened risk of losing their social networks, and structural social capital has been identified as important in relation to depression in old age [ 293 ].

4.2. Gene–Environment Interactions

Studies on gene–environment interactions—key points:

• The environment and genetics interact to increase the risk of depression
• The etiology of depression is multifactorial
• Adolescence is a time of vulnerability

A number of studies have touched on gene–environment interactions [ 72 , 77 , 82 , 119 , 381 , 476 , 477 , 478 , 479 , 480 , 481 ]. The interactions between genetic factors and determinants, such as negative life events (ex. relationship and social difficulties, serious illness, unemployment and financial crises) and stressors (ex. death of spouse, minor violations of law, neighbourhood socioeconomic status) have been studied in relation to depression [ 82 , 135 , 298 , 449 , 481 ]. A study reported an interaction of significant life events with functional variation in the serotonin-transporter-linked polymorphic region (5-HTTLPR) allele type (in the context of multiple sclerosis) and linked this to depression [ 361 ], while another reported an interaction between stress and 5-HTTLPR in relation to depression [ 480 ]. Other research reported that the genetic variation of HPA-axis genes has moderating effects on the relationship between stressors and depression [ 198 ]. Another study showed that early-life stress interacts with gene variants to increase the risk for depression [ 77 ].

Adolescence is a time of vulnerability [ 111 , 480 ]. Perceived parental support has been found to interact with genes (GABRR1, GABRR2), and this appears to be associated with depressive symptoms in adolescence [ 480 ]. It is important to pay special attention to critical periods in the lifecourse so that adequate support is provided to those who are most vulnerable.

The etiology of depression is multifactorial, and it is worthwhile to examine the interaction between multiple factors, such as epigenetic, genetic, and environmental factors, in order to truly understand this mental health condition. Finally, taking into account critical periods of life when assessing gene–environment interactions is important for developing targeted interventions.

5. Discussion

Depression is one of the most common mental health conditions, and, if left untreated, it can increase the risk for substance abuse, anxiety disorders, and suicide. In the past 20 years, a large number of studies on the risk and protective factors of depression have been undertaken in various fields, such as genetics, neurology, immunology, and epidemiology. However, there are limitations associated with the extant evidence base. The previous syntheses on depression are limited in scope and focus exclusively on social or biological factors, population sub-groups, or examine depression as a comorbidity (rather than an independent disorder). The research on the determinants and causal pathways of depression is fragmentated and heterogeneous, and this has not helped to stimulate progress when it comes to the prevention and intervention of this condition—specifically unravelling the complexity of the determinants related to this condition and thus refining the prevention and intervention methods.

The scope of this paper was to bring together the heterogeneous, vast, and fragmented literature on depression and paint a picture of the key factors that contribute to this condition. The findings from this review show that there are important themes when it comes to the determinants of depression, such as: the microbiome, dysregulation of the HPA axis, inflammatory reactions, the kynurenine pathway, as well as psychological and social factors. It may be that physical factors are proximal determinants of depression, which, in turn, are acted on by more distal social factors, such as deprivation, environmental events, and social capital.

The Marmot Report [ 291 ], the World Health Organization [ 482 ], and Compton et al. [ 483 ] highlight that the most disadvantaged segments of society are suffering (the socioeconomic context is important), and this inequality in resources has translated to inequality in mental health outcomes [ 483 ]. To tackle the issue of egalitarianism and restore equality in the health between the groups, the social determinants need to be addressed [ 483 ]. A wide range of determinants of mental health have been identified in the literature: age, gender, ethnicity, family upbringing and early attachment patterns, social support, access to food, water and proper nutrition, and community factors. People spiral downwards because of individual- and societal-level circumstances; therefore, these circumstances along with the interactions between the determinants need to be considered.

Another important theme in the mental health literature is the lifecourse perspective. This shows that the timing of events has significance when it comes to mental health. Early life is a critical period during the lifespan at which cognitive processes develop. Exposure to harmful determinants, such as stress, during this period can place an individual on a trajectory of depression in adulthood or later life. When an individual is exposed to harmful determinants during critical periods and is also genetically predisposed to depression, the risk for the disorder can be compounded. This is why aspects such as the lifecourse perspective and gene–environment interactions need to be taken into account. Insight into this can also help to refine targeted interventions.

A number of interventions for depression have been developed or recommended, addressing, for example, the physical factors described here and lifestyle modifications. Interventions targeting various factors, such as education and socioeconomic status, are needed to help prevent and reduce the burden of depression. Further research on the efficacy of various interventions is needed. Additional studies are also needed on each of the themes described in this paper, for example: the biological factors related to postpartum depression [ 134 ], and further work is needed on depression outcomes, such as chronic, recurrent depression [ 452 ]. Previous literature has shown that chronic stress (associated with depression) is also linked to glucocorticoid receptor resistance, as well as problems with the regulation of the inflammatory response [ 484 ]. Further work is needed on this and the underpinning mechanisms between the determinants and outcomes. This review highlighted the myriad ways of measuring depression and its determinants [ 66 , 85 , 281 , 298 , 451 , 485 ]. Thus, the standardization of the measurements of the outcomes (ex. a gold standard for measuring depression) and determinants is essential; this can facilitate comparisons of findings across studies.

5.1. Strengths

This paper has important strengths. It brings together the wide literature on depression and helps to bridge disciplines in relation to one of the most common mental health problems. We identified, selected, and extracted data from studies, and provided concise summaries.

5.2. Limitations

The limitations of the review include missing potentially important studies; however, this is a weakness that cannot be avoided by literature reviews. Nevertheless, the aim of the review was not to identify each study that has been conducted on the risk and protective factors of depression (which a single review is unable to capture) but rather to gain insight into the breadth of literature on this topic, highlight key biological, psychological, and social determinants, and shed light on important themes, such as the lifecourse perspective and gene–environment interactions.

6. Conclusions

We have reviewed the determinants of depression and recognize that there are a multitude of risk and protective factors at the individual and wider ecologic levels. These determinants are interlinked and influence one another. We have attempted to describe the wide literature on this topic, and we have brought to light major factors that are of public mental health significance. This review may be used as an evidence base by those in public health, clinical practice, and research.

This paper discusses key areas in depression research; however, an exhaustive discussion of all the risk factors and determinants linked to depression and their mechanisms is not possible in one journal article—which, by its very nature, a single paper cannot do. We have brought to light overarching factors linked to depression and a workable conceptual framework that may guide clinical and public health practice; however, we encourage other researchers to continue to expand on this timely and relevant work—particularly as depression is a top priority on the policy agenda now.

Acknowledgments

Thank you to Isla Kuhn for the help with the Medline, Scopus, and PsycInfo database searches.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/brainsci11121633/s1 , Figure S1: Conceptual framework: Determinants of depression, Table S1: Data charting—A selection of determinants from the literature.

Appendix A.1. Search Strategy

Search: ((((((((((((((((“Gene-Environment Interaction”[Majr]) OR (“Genetics”[Mesh])) OR (“Genome-Wide Association Study”[Majr])) OR (“Microbiota”[Mesh] OR “Gastrointestinal Microbiome”[Mesh])) OR (“Neurogenic Inflammation”[Mesh])) OR (“genetic determinant”)) OR (“gut-brain-axis”)) OR (“Kynurenine”[Majr])) OR (“Cognition”[Mesh])) OR (“Neuronal Plasticity”[Majr])) OR (“Neurogenesis”[Mesh])) OR (“Genes”[Mesh])) OR (“Neurology”[Majr])) OR (“Social Determinants of Health”[Majr])) OR (“Glucocorticoids”[Mesh])) OR (“Tryptophan”[Mesh])) AND (“Depression”[Mesh] OR “Depressive Disorder”[Mesh]) Filters: from 2017—2020.

Ovid MEDLINE(R) and Epub Ahead of Print, In-Process, In-Data-Review & Other Non-Indexed Citations, Daily and Versions(R)

• exp *Depression/
• exp *Depressive Disorder/
• exp *”Social Determinants of Health”/
• exp *Tryptophan/
• exp *Glucocorticoids/
• exp *Neurology/
• exp *Genes/
• exp *Neurogenesis/
• exp *Neuronal Plasticity/
• exp *Kynurenine/
• exp *Genetics/
• exp *Neurogenic Inflammation/
• exp *Gastrointestinal Microbiome/
• exp *Genome-Wide Association Study/
• exp *Gene-Environment Interaction/
• exp *Depression/et [Etiology]
• exp *Depressive Disorder/et
• or/4-16   637368
• limit 22 to yr = “2017–Current”
• “cause* of depression”.mp.
• “cause* of depression”.ti.
• (cause adj3 (depression or depressive)).ti.
• (caus* adj3 (depression or depressive)).ti.

Appendix A.2. PsycInfo

(TITLE ( depression OR “ Depressive Disorder ”) AND TITLE (“ Social Determinants of Health ” OR tryptophan OR glucocorticoids OR neurology OR genes OR neurogenesis OR “ Neuronal Plasticity ” OR kynurenine OR genetics OR “ Neurogenic Inflammation ” OR “ Gastrointestinal Microbiome ” OR “ Genome-Wide Association Study ” OR “ Gene-Environment Interaction ” OR aetiology OR etiology )) OR TITLE ( cause* W/3 ( depression OR depressive )).

Author Contributions

O.R. was responsible for the design of the study and methodology undertaken. Despite P.T.’s involvement in YPMH, he had no role in the design of the study; P.T. was responsible for the conceptualization of the study. Validation was conducted by O.R. and J.F.M. Formal analysis (data charting) was undertaken by O.R. O.R. and P.T. were involved in the investigation, resource acquisition, and data presentation. The original draft preparation was undertaken by O.R. The writing was conducted by O.R., with review and editing by P.T. and J.F.M. Funding acquisition was undertaken by O.R. and P.T. All authors have read and agreed to the published version of the manuscript.

This research was funded by The William Templeton Foundation for Young People’s Mental Health, Cambridge Philosophical Society, and the Aviva Foundation.

Conflicts of Interest

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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

Understanding Depression and Managing It Effectively

Depression needs a personalized, holistic approach for effective management..

Posted August 14, 2024 | Reviewed by Davia Sills

• What Is Depression?
• Take our Depression Test
• Find a therapist to overcome depression
• Depression is a multi-faceted condition affecting every aspect of life, requiring personalized treatment.
• Depression's causes can be biological, psychological, and social; it is not merely a chemical imbalance.
• Medications can manage symptoms but are not a standalone solution for treating depression.
• Psychotherapy is crucial in developing coping strategies and understanding individual triggers for depression.

"Whatever you lack, you must borrow from yourself." — Cato

The term “ depression ” has evolved significantly over time, reflecting the changing ways in which society understands and describes this complex condition. From the ancient concept of “black bile” in Hippocratic medicine to the existential “pain of existence” and the romantic “spleen,” depression has long been a topic of interest not only to doctors and psychologists but also to intellectuals and religious figures.

In modern times, depression is often labeled as the “disorder of the century,” a term that captures the widespread and varied nature of this “obscure illness.” This article delves into the many faces of depression, emphasizing that it is not just a single mood but a multifaceted condition requiring a comprehensive approach to treatment.

The Multifaceted Nature of Depression

Depression is not a one-size-fits-all condition. Its manifestations can range from mild to severe, and it can be a temporary phase or a long-term condition integrated into a person’s way of life. Understanding depression requires recognizing that each person’s experience is different, and thus, their treatment needs will differ as well (Yapko, 2018).

The evolution of the term “depression” highlights its complexity. Historically, depression has been associated with various emotional states and conditions, and modern psychiatry now groups the causes of depression into three primary domains: biological, psychological, and social. Biological factors include neurochemistry, genetic predispositions, and the effects of certain diseases or medications (Yapko, 2018). Psychological factors encompass a person’s individual history, trauma exposure, and coping mechanisms. Social factors involve the relationships people maintain, the culture they grow up in, and the family dynamics they experience (Yapko, 2018).

This bio-psycho-social model illustrates that depression is not merely a chemical imbalance in the brain—a misconception perpetuated by the pharmaceutical industry since the advent of antidepressants like Prozac in the late 1980s (Lacasse & Leo, 2005). Although these medications can be beneficial for managing certain symptoms, they do not address the underlying causes of depression, such as poor coping skills, lack of a support network, or unresolved trauma (Yapko, 2018).

The Limitations of Antidepressants

While antidepressants can help alleviate some symptoms of depression, they are not a cure-all. The social use of the term “depression” has led to its frequent abuse and, unfortunately, its misuse in describing a wide range of moods and conditions.

This over-simplification often leads to an overreliance on medications, which cannot teach essential life skills such as problem-solving, building healthy relationships, or managing stress . Overreliance on medication without addressing these broader issues often leads to undertreatment, which can exacerbate the condition in the long run (Deacon & Abramowitz, 2005).

Furthermore, the narrative that depression is solely due to a chemical imbalance has been largely discredited by recent research. The simplistic view that a pill can “fix” depression ignores the complexity of the condition and can lead to disappointment and relapse . Effective treatment must, therefore, be holistic, incorporating therapy to build life skills and foster a deeper understanding of oneself and one’s risk factors (Moncrieff et al., 2022).

The Role of Therapy in Managing Depression

Psychotherapy plays a crucial role in helping individuals with their perceptions and relationships that give rise to depression. A skilled therapist can help identify the unique vulnerabilities, behaviors, and contexts that exacerbate and maintain depression in each person. This personalized approach allows individuals to develop coping strategies that are tailored to their specific needs and circumstances (Yapko, 2018).

The goal of therapy is not to “cure” depression but to transform the person’s perception of themselves and their relationship with their reality. It also equips individuals with the tools they need to manage their moods and themselves on an ongoing basis. This includes learning to recognize depressive patterns, developing better problem-solving skills, and creating a better social and relational environment (Gibson, 2024; Beck, 1979).

Supporting a Loved One with Depression

For those in a relationship with someone who is depressed, it is important to find a balance between being supportive and avoiding enabling self-defeating behaviors to continue. It’s crucial to encourage the depressed individual to seek help and engage in activities that can lift their mood, even if they initially resist. However, it’s equally important for the partner to take care of their well-being and not allow depression to dominate their life (Yapko, 2018).

Supporting a loved one with depression also involves setting boundaries . It’s essential to communicate that while the feelings of the depressed person are valid, they do not justify harmful behaviors or the neglect of their own needs or those of the relationship (Coyne, 1976). This understanding is part of the broader context in which depression, as a term and a condition, is often misused or misunderstood.

The Importance of Action

One of the most effective ways to counteract depression is through positive action. While depression often leads to passivity and a feeling of helplessness, taking small steps toward engaging with life and disrupting the current defeatist perception can create a positive feedback loop that improves mood and builds momentum. This could be as simple as taking a walk, engaging in a hobby, or socializing with friends (Jacobson et al., 1996), basically not surrendering to the problem (Gibson, 2024).

However, these actions must be taken with the right support and preparation. A person with depression may need to develop certain skills before they can successfully engage in these activities without feeling overwhelmed. This is where therapy and the support of loved ones play a critical role (Gibson, 2024).

Depression, as a term and a condition, has evolved significantly over the centuries, reflecting its complex and multi-dimensional nature. While medication can help alleviate some symptoms, it is not a standalone solution. Therapy, support from loved ones, and a proactive approach to building life skills and coping mechanisms are essential for managing depression effectively (Beck, 1979; Gibson, 2024).

For those supporting a loved one with depression, it’s important to be both supportive and self-caring, encouraging positive action without allowing the depression to dictate the terms of the relationship. With the right approach, it is possible to manage depression and lead a fulfilling life despite the challenges it presents (Yapko, 2018).

Beck, A. T. (1979). Cognitive therapy and emotional disorders . Penguin.

Coyne, J. C. (1976). Depression and the response of others. Journal of Abnormal Psychology, 85 (2), 186–193.

Deacon, B. J., & Abramowitz, J. S. (2005). The short-term efficacy of psychological treatments for depression: A meta-analysis. Clinical Psychology Review, 25 (4), 401–419.

Gibson, P. (2024). When The Bubble Bursts. A New Approach to Treating Depression. Strategic Science Books.

Jacobson, N. S., Martell, C. R., & Dimidjian, S. (2001). Behavioural activation treatment for depression: Returning to contextual roots. Clinical Psychology: Science and Practice, 8 (3), 255–270.

Lacasse, J. R., & Leo, J. (2005). Serotonin and depression: A disconnect between the advertisements and the scientific literature. PLoS Medicine, 2 (12), e392.

Moncrieff, J., Cooper, R. E., Stockmann, T., Amendola, S., Hengartner, M. P., & Horowitz, M. A. (2022). The serotonin theory of depression: A systematic umbrella review of the evidence. Molecular Psychiatry, 27 (6), 2402–2414.

Yapko, M. D. (2018). Keys to unlocking depression: An integrated approach to healing . Yapko Publications.

Padraic Gibson, D.Psych, is a Consultant Clinical Psychotherapist and is the Clinical Director of The OCD Clinic®, and director of Training and Organization Consultation at The Coaching Clinic®, Dublin. He is senior research associate at Dublin City University.

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Sticking up for yourself is no easy task. But there are concrete skills you can use to hone your assertiveness and advocate for yourself.

• Emotional Intelligence
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Everyone experiences sadness at times. But depression is something more. Depression is extreme sadness or despair that lasts more than days. It interferes with the activities of daily life and can cause physical symptoms such as pain, weight loss or gain, sleeping pattern disruptions, or lack of energy.

People with depression may also experience an inability to concentrate, feelings of worthlessness or excessive guilt, and recurrent thoughts of death or suicide.

Depression is the most common mental disorder. Fortunately, depression is treatable. A combination of therapy and antidepressant medication can help ensure recovery.

Adapted from the Encyclopedia of Psychology

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• Introduction
• Conclusions
• Article Information

a After completing the prescreening questionnaire, people were deemed ineligible if they were currently using antidepressant medication (n = 157); lived outside reasonable commuting distance (n = 161); did not meet criteria for the magnetic resonance imaging scans (n = 99); had a first- or second-degree relative with a diagnosis of schizophrenia spectrum, bipolar I or II, or other psychotic disorder ( = 77); had a recent history of substance use disorder (n = 50); opted out of in-person screening (n = 38); were not in a current depressive episode (n = 37); were more than 25% beyond the upper or lower range of recommended body weight (n = 32); had a medically significant suicide attempt (n = 30); had lifetime hallucinogen use that exceeded the exclusion threshold (n = 30); if major depressive disorder (MDD) was not primary psychiatric diagnosis (n = 18); if they had a medical exclusion (n = 11); had exclusionary use of nonserotonergic psychoactive medication (n = 11); or failed to respond to electroconvulsive therapy during current depressive episode (n = 4). Forty-five people were ineligible for other reasons.

b People were deemed ineligible during in-person screening if they had a psychiatric condition judged to be incompatible with establishment of rapport or safe exposure to psilocybin (n = 17); did not have confirmed DSM-5 diagnosis of MDD (n = 7); had a recent history of moderate to severe substance use disorder (n = 5); were at high risk for suicidality (n = 3); disagreed with study procedures (n = 3); had a baseline GRID Hamilton Depression Rating Scale score lower than the eligibility threshold of 17 (n = 2); had cardiovascular conditions (n = 2); had lifetime hallucinogen use that exceeded the exclusion threshold (n = 2); were currently taking serotonergic medication (n = 1); or were more than 25% beyond the upper and lower range of recommended body weight (n = 1).

c Dropped out of the study due to anticipatory anxiety about the upcoming first psilocybin session.

d Dropped out of study due to sleep difficulties. Sleep difficulties were also reported at screening, and it was not clear whether sleep difficulties were exacerbated by the intervention.

e Participant showed a marked reduction in depression symptoms immediately following the first psilocybin session and chose not to proceed with the intervention.

GRID-HAMD indicates GRID Hamilton Depression Rating Scale.

Data points are presented as mean (SD). In the immediate treatment group (n = 13), weeks 5 and 8 correspond to weeks 1 and 4 after the psilocybin session 2. In the delayed treatment group (n = 11), weeks 5 and 8 are prepsilocybin assessments obtained during the delay period. Effect sizes (Cohen d with 95% CI) and P values reflect the results of a 2-sample t test between the 2 groups at week 5 (Cohen d  = 2.5; 95% CI, 1.4-3.5; P  < .001) and week 8 (Cohen d  = 2.6; 95% CI, 1.5-3.7; P  < .001).

The mean (SD) GRID-HAMD score was 22.8 (3.9) at baseline, 8.7 (7.6) at week 1, and 8.9 (7.4) at week 4. Effect sizes (Cohen d with 95% CI) and P values reflect the results of a paired sample t test that compared scores between baseline and week 1 (Cohen d  = 2.3; 95% CI, 1.5-3.1; P  < .001) and week 4 postsession-2 follow-up (Cohen d  = 2.3; 95% CI, 1.5-3.1; P  < .001).

Trial protocol

eTable 1. Repeated Measures ANOVAs Comparing Depression, Anxiety, and Suicidal Ideation Outcomes at Each Timepoint by Treatment Condition

eTable 2. t Tests Comparing Depression, Anxiety, and Suicidal Ideation Outcomes at Each Timepoint by Condition

eTable 3. Repeated Measures ANOVAs and Effect Sizes for Depression, Anxiety, and Suicidal Ideation Outcomes Across Overall Sample

eTable 4. Ratings of Personal Meaning, Spiritual Significance, Psychological Challenge, and Psychological Insight During Each of Two Psilocybin Sessions

eTable 5. Mean Proportion (and Standard Deviation) of Total Possible Score on the Mystical and Challenging Experiences Questionnaires During Each of Two Psilocybin Sessions; Proportion of Participants Who Had a Complete Mystical Experience in Each Session

eTable 6. Monitor Ratings of Peak Psilocybin Effects During Each of Two Psilocybin Sessions

eTable 7. Mean of the Peak Heart Rate and Blood Pressure Across Participants During Each of Two Psilocybin Sessions. Data Regarding Number of Participants Requiring Increased Rate of Monitoring

eTable 8. Adverse Emotional and Physical Effects During Psilocybin Sessions

eTable 9. Adverse Effects Reported the Day After Sessions 1 and 2 That Were Rated by Staff as Possibly or Probably Related to Psilocybin

eTable 10. Initiation of Antidepressant Medication, Psychotherapy, or Psilocybin Reported 4 weeks After Session 2

eFigure 1. Decrease in Depression Scores on the Quick Inventory of Depression Symptoms (QIDS-SR) from Baseline to 1-day Post Psilocybin Session 1 and Through the 4-week Follow-up

eFigure 2. Comparison of Depression Scores on the Quick Inventory of Depression Symptoms (QIDS-SR) by Treatment Condition

eFigure 3. Comparison of Depression Scores on the Beck Depression Inventory – II (BDI-II) by Treatment Condition

eFigure 4. Comparison of Depression Scores on the Patient Health Questionnaire – 9 Item (PHQ-9) by Treatment Condition

eFigure 5. Comparison of Anxiety Scores on the Hamilton Anxiety Scale (HAM-A) by Treatment Condition (Immediate vs Delayed). Effect Size Calculation Using Cohen’s d Statistic

eFigure 6. Comparison of Anxiety Scores on the State-Trait Anxiety Inventory – State Subscale (STAI-State) by Treatment Condition

eFigure 7. Comparison of Anxiety Scores on the State-Trait Anxiety Inventory – Trait Subscale (STAI-Trait) by Treatment Condition

eFigure 8. Comparison of Anxiety Scores on the State-Trait Anxiety Inventory – Total Scale (STAI-Total) by Treatment Condition

eFigure 9. Comparison of Suicidal Ideation Scores on the Columbia Suicide Severity Rating Scale (CSSRS) by Treatment Condition

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• JAMA Network Journals’ Articles of the Year 2021 JAMA Medical News & Perspectives December 28, 2021 This Medical News article is our fifth-annual roundup of the top-viewed articles from each of the JAMA Network Journals. Jennifer Abbasi
• Psilocybin-Assisted Supportive Psychotherapy in the Treatment of Major Depression—Quo Vadis? JAMA Psychiatry Editorial May 1, 2021 Charles F. Reynolds III, MD
• Errors in a Response Rate and in Effect Sizes in Study of Psilocybin-Assisted Therapy for Major Depressive Disorder JAMA Psychiatry Comment & Response May 1, 2021 Alan K. Davis, PhD; Roland R. Griffiths, PhD
• Errors in Response Rate, Effect Sizes, and Confidence Intervals JAMA Psychiatry Correction May 1, 2021

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Davis AK , Barrett FS , May DG, et al. Effects of Psilocybin-Assisted Therapy on Major Depressive Disorder : A Randomized Clinical Trial . JAMA Psychiatry. 2021;78(5):481–489. doi:10.1001/jamapsychiatry.2020.3285

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Effects of Psilocybin-Assisted Therapy on Major Depressive Disorder : A Randomized Clinical Trial

• 1 Center for Psychedelic and Consciousness Research, Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
• 2 College of Social Work, The Ohio State University, Columbus
• 3 Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, Maryland
• Editorial Psilocybin-Assisted Supportive Psychotherapy in the Treatment of Major Depression—Quo Vadis? Charles F. Reynolds III, MD JAMA Psychiatry
• Medical News & Perspectives JAMA Network Journals’ Articles of the Year 2021 Jennifer Abbasi JAMA
• Comment & Response Errors in a Response Rate and in Effect Sizes in Study of Psilocybin-Assisted Therapy for Major Depressive Disorder Alan K. Davis, PhD; Roland R. Griffiths, PhD JAMA Psychiatry
• Correction Errors in Response Rate, Effect Sizes, and Confidence Intervals JAMA Psychiatry

Question   Is psilocybin-assisted therapy efficacious among patients with major depressive disorder?

Findings   In this randomized clinical trial of 24 participants with major depressive disorder, participants who received immediate psilocybin-assisted therapy compared with delayed treatment showed improvement in blinded clinician rater–assessed depression severity and in self-reported secondary outcomes through the 1-month follow-up.

Meaning   This randomized clinical trial found that psilocybin-assisted therapy was efficacious in producing large, rapid, and sustained antidepressant effects in patients with major depressive disorder.

Importance   Major depressive disorder (MDD) is a substantial public health burden, but current treatments have limited effectiveness and adherence. Recent evidence suggests that 1 or 2 administrations of psilocybin with psychological support produces antidepressant effects in patients with cancer and in those with treatment-resistant depression.

Objective   To investigate the effect of psilocybin therapy in patients with MDD.

Design, Setting, and Participants   This randomized, waiting list–controlled clinical trial was conducted at the Center for Psychedelic and Consciousness Research at Johns Hopkins Bayview Medical Center in Baltimore, Maryland. Adults aged 21 to 75 years with an MDD diagnosis, not currently using antidepressant medications, and without histories of psychotic disorder, serious suicide attempt, or hospitalization were eligible to participate. Enrollment occurred between August 2017 and April 2019, and the 4-week primary outcome assessments were completed in July 2019. A total of 27 participants were randomized to an immediate treatment condition group (n = 15) or delayed treatment condition group (waiting list control condition; n = 12). Data analysis was conducted from July 1, 2019, to July 31, 2020, and included participants who completed the intervention (evaluable population).

Interventions   Two psilocybin sessions (session 1: 20 mg/70 kg; session 2: 30 mg/70 kg) were given (administered in opaque gelatin capsules with approximately 100 mL of water) in the context of supportive psychotherapy (approximately 11 hours). Participants were randomized to begin treatment immediately or after an 8-week delay.

Main Outcomes and Measures   The primary outcome, depression severity was assessed with the GRID-Hamilton Depression Rating Scale (GRID-HAMD) scores at baseline (score of ≥17 required for enrollment) and weeks 5 and 8 after enrollment for the delayed treatment group, which corresponded to weeks 1 and 4 after the intervention for the immediate treatment group. Secondary outcomes included the Quick Inventory of Depressive Symptomatology-Self Rated (QIDS-SR).

Results   Of the randomized participants, 24 of 27 (89%) completed the intervention and the week 1 and week 4 postsession assessments. This population had a mean (SD) age of 39.8 (12.2) years, was composed of 16 women (67%), and had a mean (SD) baseline GRID-HAMD score of 22.8 (3.9). The mean (SD) GRID-HAMD scores at weeks 1 and 4 (8.0 [7.1] and 8.5 [5.7]) in the immediate treatment group were statistically significantly lower than the scores at the comparable time points of weeks 5 and 8 (23.8 [5.4] and 23.5 [6.0]) in the delayed treatment group. The effect sizes were large at week 5 (Cohen d  = 2.5; 95% CI, 1.4-3.5; P  < .001) and week 8 (Cohen d  = 2.6; 95% CI, 1.5-3.7; P  < .001). The QIDS-SR documented a rapid decrease in mean (SD) depression score from baseline to day 1 after session 1 (16.7 [3.5] vs 6.3 [4.4]; Cohen d  = 2.6; 95% CI, 1.8-3.5; P  < .001), which remained statistically significantly reduced through the week 4 follow-up (6.0 [5.7]; Cohen d  = 2.3; 95% CI, 1.5-3.0; P  < .001). In the overall sample, 17 participants (71%) at week 1 and 17 (71%) at week 4 had a clinically significant response to the intervention (≥50% reduction in GRID-HAMD score), and 14 participants (58%) at week 1 and 13 participants (54%) at week 4 were in remission (≤7 GRID-HAMD score).

Conclusions and Relevance   Findings suggest that psilocybin with therapy is efficacious in treating MDD, thus extending the results of previous studies of this intervention in patients with cancer and depression and of a nonrandomized study in patients with treatment-resistant depression.

Trial Registration   ClinicalTrials.gov Identifier: NCT03181529

Major depressive disorder (MDD) is a substantial public health concern, affecting more than 300 million individuals worldwide. Depression is the number one cause of disability, 1 and the relative risk of all-cause mortality for those with depression is 1.7 times greater than the risk for the general public. 2 In the United States, approximately 10% of the adult population has been diagnosed with MDD in the past 12 months, 3 and the yearly economic burden of MDD is estimated to be $210 billion. 4

Although effective pharmacotherapies for depression are available, these drugs have limited efficacy, produce adverse effects, and are associated with patient adherence problems. 5 Although many patients with depression showed reduced or remitted symptoms after treatment with existing pharmacotherapies, 6 approximately 30% to 50% of patients did not respond fully and as many as 10% to 30% of patients were considered treatment-resistant, resulting in average effects that were only modestly larger than the effects of placebo. 7 , 8

Most of the current pharmacotherapies for MDD, including the widely used selective serotonin reuptake inhibitors, increase levels of brain monoamine neurotransmitters such as serotonin and norepinephrine (typically by blocking reuptake). 6 A growing body of evidence suggests that newer ketamine-like medications exert therapeutic efficacy in MDD through effects on glutamate neurotransmission. 9 , 10 Ketamine hydrochloride, a nonselective N -methyl- d -aspartate receptor antagonist, is the most well-researched of these newer medications. Several studies have demonstrated the efficacy of a single ketamine infusion in rapidly (within hours) reducing depression symptoms and, when effective, lasting from a few days to about 2 weeks. 10 , 11 However, ketamine has high abuse liability, and its administration involves moderate physiological risk that requires medical monitoring. 12

Quiz Ref ID The combined serotonergic and glutamatergic action of psilocybin 13 - 15 (a classic hallucinogen) and the preliminary evidence of the antidepressant effects of psilocybin-assisted therapy (among patients with life-threatening cancer or patients with treatment-resistant depression) 16 - 18 indicate the potential of psilocybin-assisted therapy as a novel antidepressant intervention. 19 Moreover, psilocybin has lower addiction liability and toxic effects compared with ketamine 20 - 22 and is generally not associated with long-term perceptual, cognitive, or neurological dysfunction. 23

The substantial negative public health impact of MDD underscores the importance of conducting more research into drugs with rapid and sustained antidepressant effects. Current pharmacotherapies for depression have variable efficacy and unwanted adverse effects. Novel antidepressants with rapid and sustained effects on mood and cognition could represent a breakthrough in the treatment of depression and may potentially improve or save lives. Therefore, the primary objective of this randomized clinical trial was to investigate the effect of psilocybin therapy in patients with MDD.

This randomized, waiting list–controlled clinical trial was conducted at the Center for Psychedelic and Consciousness Research in Baltimore, Maryland. The Johns Hopkins Medicine Institutional Review Board approved this trial (the protocol is included in Supplement 1 ). Written informed consent was obtained from all participants.

This trial of psilocybin therapy included participants with moderate or severe MDD episodes, as assessed with the Structured Clinical Interview for DSM-5 (SCID-5) 24 and the GRID-Hamilton Depression Rating Scale (GRID-HAMD; a score of ≥17 was required for enrollment). 25 , 26 Eligible candidates were aged 21 to 75 years who self-reported no current pharmacotherapy for depression at trial screening. To avoid the confounding effects and potential interactions of concurrent antidepressant use, candidates were required to refrain from using antidepressants (eg, selective serotonin reuptake inhibitors) for at least 5 half-lives before the screening and up to 4 months after enrollment (through the completion of the primary outcome assessment). However, the decision to taper off and/or continuing not to take their medications during the study was made by the individuals and their prescribing physicians and not by study personnel. Additional eligibility requirements included being medically stable with no uncontrolled cardiovascular conditions; having no personal or family history (first or second degree) of psychotic or bipolar disorders; and, for women, being nonpregnant, being non-nursing, and agreeing to use contraception. Individuals with a moderate or severe alcohol or other drug use disorder (including nicotine) in the past year, as defined by Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) ( DSM-5 ) criteria, were excluded, as were individuals with substantial lifetime use (>10 total) or recent use (past 6 months) of ketamine or classic hallucinogens, such as psilocybin-containing mushrooms or lysergic acid diethylamide (eMethods in Supplement 2 ).

Participants were enrolled between August 2017 and April 2019, and the 4-week primary outcome assessments were completed in July 2019. Recruitment was carried out through flyers, print advertisements, internet forums, social media, and the study website. Of the 870 individuals screened by telephone or electronic screening survey, 70 went on to undergo in-person medical and psychological screening, 43 were disqualified, and 27 qualified and were enrolled in the study. After screening, baseline assessments, and enrollment, 27 participants were randomized to either the immediate treatment group or the delayed treatment group (ie, the waiting list control condition). The use of a delayed treatment control was chosen to differentiate the psilocybin intervention from spontaneous symptom improvement. The delay interval was 8 weeks, after which participants in the delayed treatment group underwent all study assessments and entered the study intervention period. Randomization to the immediate treatment and delayed treatment groups occurred after screening and baseline assessments ( Figure 1 ). Participants were randomized using urn randomization, 27 balancing for sex, age, depression severity at screening (assessed using the GRID-HAMD), and level of treatment resistance (assessed using the Maudsley Staging Method). 28 One of us (F.S.B.), who was not involved in participant screening or enrollment, performed urn randomization using the randPack library, version 1.32.0, 29 in the R Statistical Software package (R Foundation for Statistical Computing). 30

Participants received no monetary compensation for undergoing the intervention. However, participants received a total of $200 for completing 2 magnetic resonance imaging sessions.

Quiz Ref ID The intervention period was 8 weeks and involved at least 18 in-person visits, including 2 daylong psilocybin administration sessions ( Figure 2 ). Consistent with previous studies using psilocybin, 16 , 31 the visit schedule included preparatory meetings (8 hours in total) with 2 session facilitators before the first psilocybin session as well as follow-up meetings after psilocybin sessions (2-3 hours in total) (eMethods in Supplement 2 ). Session facilitators were study staff with varying educational levels (ie, bachelor’s, master’s, doctorate, and medical degrees) and professional disciplines (eg, social work, psychology, and psychiatry). After the preparation meetings, 2 psilocybin administration sessions were conducted a mean of 1.6 weeks apart (no statistically significant differences were found between conditions; eResults in Supplement 2 ). The psilocybin dose was moderately high (20 mg/70 kg) in session 1 and was high (30 mg/70 kg) in session 2. Procedures for psilocybin administration and the conduct of the sessions were similar to procedures used in previous and ongoing studies with psilocybin (eMethods in Supplement 2 ) at the Center for Psychedelic and Consciousness Research. 16 , 32 , 33

Psilocybin was administered in opaque gelatin capsules with approximately 100 mL water. Both facilitators were present in the room and available to respond to participants’ physical and emotional needs during the day-long session, with the exception of short breaks taken by 1 facilitator at a time. During the session, participants were instructed to lie on a couch in a living room–like environment, and facilitators encouraged participants to focus their attention inward and stay with any experience that arose. To enhance inward reflection, music was played (the playlist is provided in the eMethods in Supplement 2 ), and participants were instructed to wear eyeshades and headphones.

For safety during the 8-week delay period of the delayed treatment group, participants were monitored weekly by in-person assessment or brief telephone calls. In weeks 5 and 8, participants attended an in-person visit and underwent the GRID-HAMD assessment and other study measures. In other weeks of the delay period, participants received telephone calls that included a brief check-in and assessment for self-reported suicidal ideation or behavior and depression symptoms. All assessments during the delay period were administered by study staff who were not lead facilitators. At the end of the delay period, all participants in the delayed treatment group completed the same intervention as the participants in the immediate treatment group.

Screening evaluation included a preliminary questionnaire administered via telephone or an online survey as well as an in-person medical history and physical examination, electrocardiogram, routine medical blood and urinalysis laboratory tests, and structured assessments (eg, SCID-5, SCID-5 Screening Personality Questionnaire, SCID-5 Personality Disorders, and Personality Assessment Inventory). 24 , 34 - 36

Quiz Ref ID The primary outcome measure was the GRID-HAMD, 37 a version of the 17-item Hamilton Depression Rating Scale that has high reliability and validity. 26 The GRID-HAMD was administered by blinded clinician raters via telephone at baseline and at postrandomization weeks 5 and 8 for participants in the delayed treatment group and at the weeks 1 and 4 follow-up visits after the second psilocybin session for participants in both the immediate treatment and delayed treatment groups. The primary between-group end point comparison was at weeks 5 and 8 between the immediate treatment and delayed treatment groups ( Figure 2 ). The primary within-group end point comparison was between baseline and weeks 1 and 4 postsession 2 follow-up visits in both groups.

Severity of depression was assessed using the total GRID-HAMD score (0-7: no depression; 8-16: mild depression; 17-23: moderate depression; ≥24: severe depression). 38 A clinically significant response was defined as 50% or greater decrease from baseline; symptom remission was defined as a score of 7 or lower. The GRID-HAMD assessment was audiorecorded to examine interrater reliability (eMethods in Supplement 2 ). Interrater reliability for all depression assessments (through postsession week 4) was 85%. Rapid and sustained antidepressant effects were examined at baseline; at day 1 and week 1 of postsession-1 follow-up; and at day 1, week 1, and week 4 postsession-2 follow-up using the Quick Inventory of Depressive Symptomatology–Self-Report (QIDS-SR; score range: 0-27, with higher scores indicating very severe depression). 39

Descriptions of secondary outcome measures and timing of assessment are provided in the eMethods in Supplement 2 . Secondary outcome measures for depressive symptoms were the Beck Depression Inventory II (score range: 0-63, with higher scores indicating severe depression) 40 and the 9-item Patient Health Questionnaire (score range: 0-27, with higher scores indicating severe depression). 41 The Columbia-Suicide Severity Rating Scale (severity of ideation subscale score range: 0-5, with higher scores indicating presence of ideation with at least some intent to die) 42 , 43 was completed at every visit to assess for potentially worsening suicidal ideation throughout the trial. Anxiety symptoms were measured using the clinician-administered Hamilton Anxiety Rating Scale (score range: 0-56, with higher scores indicating severe anxiety) 44 and the State-Trait Anxiety Index (score range: 0-80, with higher scores indicating greater anxiety). 45 Blood pressure and heart rate were examined before and during the psilocybin sessions.

Data analysis was conducted on participants who completed the intervention (evaluable population). A previous study of psilocybin 16 found a large effect of a high psilocybin dose (compared with a low dose) on reducing GRID-HAMD scores (Cohen d  = 1.30). Assuming a similar large effect size with 24 participants, nearly 100% power was calculated to detect a statistically significant effect of psilocybin on change in depressive symptoms.

No primary outcome data were missing. Descriptive statistics for demographic and background characteristics for all study variables were calculated and compared between study conditions using a 2-sample t test for continuous variables and a χ 2 test for all remaining variables. A repeated-measures analysis of variance with time (baseline, week 5, and week 8) and condition (immediate treatment and delayed treatment) as factors was used to examine changes in the primary depression outcome (GRID-HAMD score).

Follow-up planned comparisons included independent samples t tests to compare week 1 with week 4 GRID-HAMD scores in the immediate treatment condition group (corresponding to the week 5 and week 8 time points in the delayed treatment condition group). Within-participant (n = 24) treatment effect was examined using t tests comparing GRID-HAMD scores at baseline with scores at week 1 and week 4 postsession-2 follow-up. Rapid and sustained antidepressant effects were examined using t tests comparing QIDS-SR scores between baseline and day 1 postsession-1 and between baseline and week 4 postsession-2 follow-up. Effect sizes for the independent samples t tests were calculated using the Cohen d statistic, and effect sizes for the repeated-measures analysis of variance were calculated using the partial eta squared (η p 2 ) statistic. Further primary outcomes included a descriptive analysis of the percentage of participants who met the criterion for clinically significant response and remission in the sample.

All statistical tests used a P  < .05 to determine statistical significance. Data analysis was conducted from July 1, 2019, to July 31, 2020, using SPSS, version 25 (IBM). 46 Data analysis plans for secondary outcomes are reported in the eMethods in Supplement 2 .

A total of 27 participants were randomized, of whom 24 (89%) completed the intervention as well as the postsession assessments at weeks 1 and 4; specifically, 13 were randomized to the immediate treatment group and 11 to the delayed treatment group ( Figure 1 ). The Table shows the demographic characteristics for the 24 participants, among whom were 16 women (67%) and 8 men (33%), with a mean (SD) age of 39.8 (12.2) years and a mean (SD) baseline GRID-HAMD score of 22.8 (3.9). An examination of the differences in stratification variables as a function of the treatment condition indicated no statistically significant differences between conditions (mean [SD] months in current major depressive episode: immediate treatment, 25.9 [22.4]; delayed treatment, 22.6 [22.5]; P  = .39) ( Table ).

A statistically significant time by condition interaction effect on GRID-HAMD was found (η p 2  = 0.57; 90% CI, 0.38-0.66; P  < .001) ( Figure 3 ).

Follow-up independent samples t tests revealed significantly lower depression scores in the immediate treatment condition at weeks 1 and 4 postsession-2 follow-up compared with the corresponding time points (weeks 5 and 8) in the delayed treatment condition before psilocybin treatment. In the immediate treatment group, the mean (SD) GRID-HAMD scores were 22.9 (3.6) at baseline, 8.0 (7.1) at week 5, and 8.5 (5.7) at week 8. In the delayed treatment group, the mean (SD) GRID-HAMD scores were 22.5 (4.4) at baseline, 23.8 (5.4) at week 5, and 23.5 (6.0) at week 8. The effect sizes were large at week 5 (Cohen d  = 2.5; 95% CI, 1.4-3.5; P  < .001) and at week 8 (Cohen d  = 2.6; 95% CI, 1.5-3.7; P  < .001) (eTables 1-3 and eResults in Supplement 2 ).

Quiz Ref ID After the psilocybin session, 17 participants (71%) at week 1 and 17 participants (71%) at week 4 had a clinically significant response to the intervention (≥50% reduction in GRID-HAMD score), and 14 participants (58%) at week 1 and 13 participants (54%) at week 4 met the criteria for remission of depression (≤7 GRID-HAMD score). Within-participant t tests showed statistically significant decreases in GRID-HAMD scores among participants from baseline to week 1 (Cohen d  = 2.3; 95% CI, 1.5-3.1; P  < .001) and week 4 (Cohen d  = 2.3; 95% CI, 1.5-3.1; P  < .001) ( Figure 4 ). The QIDS-SR measure of depression, which was assessed more frequently, showed a rapid, large decrease in mean (SD) depression score among participants from baseline to day 1 after psilocybin session 1 (16.7 [3.5] vs 6.3 [4.4]; Cohen d  = 2.6; 95% CI, 1.8-3.5; P  < .001). This substantial decrease remained through week 4 after session 2 (6.0 [5.7]; Cohen d  = 2.3; 95% CI, 1.5-3.0; P  < .001) (eFigure 1 in Supplement 2 ).

All secondary depression and anxiety outcomes showed a similar pattern of results as the primary depression outcomes, with statistically significant differences between conditions and across both conditions after entry into the active intervention period (eTables 1 to 3 and eFigures 1 to 8 in Supplement 2 ). For example, statistically significant treatment condition effects were found on self-reported depression (Beck Depression Inventory II and Patient Health Questionnaire–9) and clinician-administered anxiety (Hamilton Anxiety Rating Scale) measures. Overall, suicidal ideation was low and trended lower after enrollment in both groups (eFigure 9 in Supplement 2 ).

Participant and facilitator rated intensity of acute psilocybin effects are provided in eTables 4-6 in Supplement 2 . There were no serious adverse events in this trial. A transient increase in blood pressure that exceeded the protocol criteria for more frequent assessment (ie, diastolic blood pressure >100 mm Hg) occurred during 1 session, but no medical intervention was needed, and the blood pressure level remained within predetermined safety parameters and resolved spontaneously during the session (eTable 7 in Supplement 2 ). Other nonserious adverse effects, which occurred during the psilocybin administration, that were reported by participants after completing at least one-half of the psilocybin sessions included challenging emotional (eg, fear and sadness) and physical (eg, feeling body shake or tremble) experiences (eTable 8 in Supplement 2 ). Mild to moderate transient headache was reported during 16 of 48 sessions (33%) and after the subjective psilocybin effects had subsided after 14 of 48 sessions (29%). Other adverse events are reported in eTables 8 and 9 in Supplement 2 , and initiation of antidepressants or psychotherapy is reported in eTable 10 in Supplement 2 .

This randomized clinical trial documented the substantial rapid and enduring antidepressant effects of psilocybin-assisted therapy among patients with MDD. Although the rapid antidepressant effects of psilocybin are similar to those reported with ketamine, 10 , 11 the therapeutic effects are different: ketamine effects typically last for a few days to 2 weeks, whereas the current study showed that clinically significant antidepressant response to psilocybin therapy persisted for at least 4 weeks, with 71% of the participants continuing to show a clinically significant response (≥50% reduction in GRID-HAMD score) at week 4 of follow-up. Furthermore, psilocybin was found to have low potential for addiction 22 and a minimal adverse event profile, 22 , 23 suggesting therapeutic advantages with less risk for associated problems than ketamine. 12 The present findings in patients with MDD are consistent with results of studies that reported on the effectiveness of psilocybin-assisted therapy in producing antidepressant effects among patients with cancer who had psychological distress 16 , 17 , 47 and a small open-label study of patients with treatment-resistant depression. 18

The mounting evidence of the use of psilocybin as an adjunct to treatment of a variety of psychiatric conditions (eg, depression, 16 - 18 tobacco use disorder, 48 and alcohol use disorder 49 ) suggests a transdiagnostic mechanism of action. In several studies in patients 16 - 18 , 49 - 51 and in healthy volunteers, 32 , 52 the intensity of mystical-type experiences reported after psilocybin sessions was associated with favorable outcomes. Furthermore, cross-sectional studies have suggested that mystical-type and psychologically insightful experiences during a psychedelic session predict positive therapeutic effects. 53 - 55 Consistent with these previous studies, the current trial showed that psilocybin-occasioned mystical-type, personally meaningful, and insightful experiences were associated with decreases in depression at 4 weeks (eResults in Supplement 2 ). Furthermore, a recent report suggested that psilocybin may decrease negative affect and the neural correlates of negative affect, 56 which may be a mechanism underlying transdiagnostic efficacy. Taken together, these findings suggest that further studies into psychological and neural mechanisms across different psychiatric conditions are warranted.

The present trial showed that psilocybin administered in the context of supportive psychotherapy (approximately 11 hours) produced large, rapid, and sustained antidepressant effects. The effect sizes reported in this study were approximately 2.5 times greater than the effect sizes found in psychotherapy 57 and more than 4 times greater than the effect sizes found in psychopharmacological depression treatment studies. 58 These findings are consistent with literature that showed that combined pharmacotherapy and psychotherapy were more efficacious in the treatment of MDD than either intervention alone. 59 - 61 Furthermore, given that psilocybin was associated with nonserious adverse effects that were frequently reported as mild-to-moderate headache and challenging emotions that were limited to the time of sessions (eTables 8 and 9 in Supplement 2 ), this intervention may be more acceptable to patients than widely prescribed antidepressant medications that confer substantially more problematic effects (eg, suicidal ideation, decrease in sexual drive, and weight gain). The effectiveness of psilocybin therapy after a single or only a few administrations represents another substantial advantage over commonly used antidepressants that require daily administration.

This study has some strengths. It had a randomized design and used GRID-HAMD as the primary outcome measure that was assessed by blinded clinician raters. The delayed treatment condition controlled for the possible effects of having been accepted into the trial and for the passage of time between screening and initial follow-up assessments. However, the delayed treatment condition did not control for other aspects of psilocybin administration, such as preparation and rapport building, postsession integration meetings, or expectancy effects. Although placebo and active treatment controlled designs are widely used in therapeutic trials, 62 they too have limitations owing to the highly discriminable effects of psilocybin.

Quiz Ref ID This study has some other limitations. It had a short-term follow-up, a small sample that was predominantly composed of White non-Hispanic participants, and included participants with low risk of suicide and moderately severe depression. Further research with larger and more diverse samples, longer-term follow-up, and a placebo control is needed to better ascertain the safety (eg, abuse potential of psilocybin, suicide risk, and emergence of psychosis) and efficacy of this intervention among patients with MDD. Another limitation is the psychotherapy approach 31 that involved session facilitators from a variety of professional disciplines (eg, social work, psychology, psychiatry) and session facilitators without formal clinical training (eg, research assistants and clinical trainees). The type of psychotherapy offered and the characteristics of therapists should be explored in future studies.

Results of this randomized clinical trial demonstrated the efficacy of psilocybin-assisted therapy in producing large, rapid, and sustained antidepressant effects among patients with MDD. These data expand the findings of previous studies involving patients with cancer and depression as well as patients with treatment-resistant depression by suggesting that psilocybin may be effective in the much larger population of MDD. Further studies are needed with active treatment or placebo controls and in larger and more diverse populations.

Accepted for Publication: July 31, 2020.

Published Online: November 4, 2020. doi:10.1001/jamapsychiatry.2020.3285

Correction: This article was corrected on February 10, 2021, to fix errors in the Abstract Results and Results section.

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2020 Davis AK et al. JAMA Psychiatry .

Corresponding Authors: Alan K. Davis, PhD ( [email protected] ), and Roland R. Griffiths, PhD ( [email protected] ), Center for Psychedelic and Consciousness Research, Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 5510 Nathan Shock Drive, Baltimore, MD 21224.

Author Contributions: Drs Davis and Griffiths 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: Davis, Barrett, May, Cosimano, Johnson, Griffiths.

Acquisition, analysis, or interpretation of data: Davis, Barrett, May, Sepeda, Johnson, Finan, Griffiths.

Drafting of the manuscript: Davis, Barrett, May, Cosimano, Sepeda, Griffiths.

Critical revision of the manuscript for important intellectual content: Davis, Barrett, May, Sepeda, Johnson, Finan, Griffiths.

Statistical analysis: Davis, Griffiths.

Obtained funding: Barrett, Griffiths.

Administrative, technical, or material support: Davis, Barrett, May, Cosimano, Sepeda, Finan, Griffiths.

Supervision: Davis, Barrett, May, Cosimano, Johnson, Griffiths.

Conflict of Interest Disclosures: Dr Davis reported being a board member at Source Research Foundation. Dr Johnson reported receiving grants from Heffter Research Institute outside the submitted work and personal fees as a consultant and/or advisory board member from Beckley Psychedelics Ltd, Entheogen Biomedical Corp, Field Trip Psychedelics Inc, Mind Medicine Inc, and Otsuka Pharmaceutical Development & Commercialization Inc. Dr Griffiths reported being a board member at Heffter Research Institute and receiving grants from Heffter Research Institute outside the submitted work. No other disclosures were reported.

Funding/Support: This study was funded in part by a crowd-sourced funding campaign organized by Tim Ferriss; a grant from the Riverstyx Foundation; and grants from Tim Ferriss, Matt Mullenweg, Craig Nerenberg, Blake Mycoskie, and the Steven and Alexandra Cohen Foundation. Drs Davis and May were supported by postdoctoral training grant T32DA07209 from NIDA. Dr Finan was supported by grant K23DA035915 from NIDA. Drs Griffiths and Johnson were partially supported by grant R01DA03889 from NIDA. The Center for Psychedelic and Consciousness Research is funded by the Steven and Alexandra Cohen Foundation and has received support from Tim Ferriss, Matt Mullenweg, Craig Nerenberg, and Blake Mycoskie.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: Annie Umbricht, MD, and Eric Strain, MD, provided medical oversight during the study sessions. Jessiy Salwen, PhD, and Mary Bailes, LCPC, served as blinded clinician raters. Natalie Gukasyan, MD; Laura Doyle, BA; John Clifton, BS; Kasey Cox, MS; and Rhiannon Mayhugh, PhD, facilitated the intervention sessions. These individuals, from Johns Hopkins University, received no additional compensation, outside of their usual salary, for their contributions.

Data Sharing Statement: See Supplement 3 .

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