2. American women
Question: | How often do British university students use Facebook each week? |
Variable: | Weekly Facebook usage |
Group: | British university students |
Question: | How often do male and female British university students upload photos and comment on other users' photos on Facebook each week? |
Variable: | 1. Weekly photo uploads on Facebook 2. Weekly comments on other users? photos on Facebook |
Group: | 1. Male, British university students 2. Female, British university students |
Question: | What are the most important factors that influence the career choices of Australian university students? |
Variable: | Factors influencing career choices |
Group: | Australian university students |
In each of these example descriptive research questions, we are quantifying the variables we are interested in. However, the units that we used to quantify these variables will differ depending on what is being measured. For example, in the questions above, we are interested in frequencies (also known as counts ), such as the number of calories, photos uploaded, or comments on other users? photos. In the case of the final question, What are the most important factors that influence the career choices of Australian university students? , we are interested in the number of times each factor (e.g., salary and benefits, career prospects, physical working conditions, etc.) was ranked on a scale of 1 to 10 (with 1 = least important and 10 = most important). We may then choose to examine this data by presenting the frequencies , as well as using a measure of central tendency and a measure of spread [see the section on Data Analysis to learn more about these and other statistical tests].
However, it is also common when using descriptive research questions to measure percentages and proportions , so we have included some example descriptive research questions below that illustrate this.
Question: | What percentage of American men and women exceed their daily calorific allowance? |
Variable: | Daily calorific intake |
Group: | 1. American men 2. American women |
Question: | What proportion of British male and female university students use the top 5 social networks? |
Variable: | Use of top 5 social networks (i.e. Facebook, MySpace, Twitter, LinkedIn, and Classmates) |
Group: | 1. Male, British university students 2. Female, British university students |
In terms of the first descriptive research question about daily calorific intake , we are not necessarily interested in frequencies , or using a measure of central tendency or measure of spread , but instead want understand what percentage of American men and women exceed their daily calorific allowance . In this respect, this descriptive research question differs from the earlier question that asked: How many calories do American men and women consume per day? Whilst this question simply wants to measure the total number of calories (i.e., the How many calories part that starts the question); in this case, the question aims to measure excess ; that is, what percentage of these two groups (i.e., American men and American women) exceed their daily calorific allowance, which is different for males (around 2500 calories per day) and females (around 2000 calories per day).
If you are performing a piece of descriptive , quantitative research for your dissertation, you are likely to need to set quite a number of descriptive research questions . However, if you are using an experimental or quasi-experimental research design , or a more involved relationship-based research design , you are more likely to use just one or two descriptive research questions as a means to providing background to the topic you are studying, helping to give additional context for comparative research questions and/or relationship-based research questions that follow.
Comparative research questions aim to examine the differences between two or more groups on one or more dependent variables (although often just a single dependent variable). Such questions typically start by asking "What is the difference in?" a particular dependent variable (e.g., daily calorific intake) between two or more groups (e.g., American men and American women). Examples of comparative research questions include:
Question: | What is the difference in the daily calorific intake of American men and women? |
Dependent variable: | Daily calorific intake |
Groups: | 1. American men 2. American women |
Question: | What is the difference in the weekly photo uploads on Facebook between British male and female university students? |
Dependent variable: | Weekly photo uploads on Facebook |
Groups: | 1. Male, British university students 2. Female, British university students |
Question: | What are the differences in usage behaviour on Facebook between British male and female university students? |
Dependent variable: | Usage behaviour on Facebook (e.g. logins, weekly photo uploads, status changes, commenting on other users' photos, app usage, etc.) |
Group: | 1. Male, British university students 2. Female, British university students |
Question: | What are the differences in perceptions towards Internet banking security between adolescents and pensioners? |
Dependent variable: | Perceptions towards Internet banking security |
Groups: | 1. Adolescents 2. Pensioners |
Question: | What are the differences in attitudes towards music piracy when pirated music is freely distributed or purchased? |
Dependent variable: | Attitudes towards music piracy |
Groups: | 1. Freely distributed pirated music 2. Purchased pirated music |
Groups reflect different categories of the independent variable you are measuring (e.g., American men and women = "gender"; Australian undergraduate and graduate students = "educational level"; pirated music that is freely distributed and pirated music that is purchased = "method of illegal music acquisition").
Comparative research questions also differ in terms of their relative complexity , by which we are referring to how many items/measures make up the dependent variable or how many dependent variables are investigated. Indeed, the examples highlight the difference between very simple comparative research questions where the dependent variable involves just a single measure/item (e.g., daily calorific intake) and potentially more complex questions where the dependent variable is made up of multiple items (e.g., Facebook usage behaviour including a wide range of items, such as logins, weekly photo uploads, status changes, etc.); or where each of these items should be written out as dependent variables.
Overall, whilst the dependent variable(s) highlight what you are interested in studying (e.g., attitudes towards music piracy, perceptions towards Internet banking security), comparative research questions are particularly appropriate if your dissertation aims to examine the differences between two or more groups (e.g., men and women, adolescents and pensioners, managers and non-managers, etc.).
Whilst we refer to this type of quantitative research question as a relationship-based research question, the word relationship should be treated simply as a useful way of describing the fact that these types of quantitative research question are interested in the causal relationships , associations , trends and/or interactions amongst two or more variables on one or more groups. We have to be careful when using the word relationship because in statistics, it refers to a particular type of research design, namely experimental research designs where it is possible to measure the cause and effect between two or more variables; that is, it is possible to say that variable A (e.g., study time) was responsible for an increase in variable B (e.g., exam scores). However, at the undergraduate and even master's level, dissertations rarely involve experimental research designs , but rather quasi-experimental and relationship-based research designs [see the section on Quantitative research designs ]. This means that you cannot often find causal relationships between variables, but only associations or trends .
However, when we write a relationship-based research question , we do not have to make this distinction between causal relationships, associations, trends and interactions (i.e., it is just something that you should keep in the back of your mind). Instead, we typically start a relationship-based quantitative research question, "What is the relationship?" , usually followed by the words, "between or amongst" , then list the independent variables (e.g., gender) and dependent variables (e.g., attitudes towards music piracy), "amongst or between" the group(s) you are focusing on. Examples of relationship-based research questions are:
Question: | What is the relationship between gender and attitudes towards music piracy amongst adolescents? |
Dependent variable: | Attitudes towards music piracy |
Independent variable: | Gender |
Group: | Adolescents |
Question: | What is the relationship between study time and exam scores amongst university students? |
Dependent variable: | Exam scores |
Independent variable: | Study time |
Group: | University students |
Question: | What is the relationship amongst career prospects, salary and benefits, and physical working conditions on job satisfaction between managers and non-managers? |
Dependent variable: | Job satisfaction |
Independent variable: | 1. Career prospects 2. Salary and benefits 3. Physical working conditions |
Group: | 1. Managers 2. Non-managers |
As the examples above highlight, relationship-based research questions are appropriate to set when we are interested in the relationship, association, trend, or interaction between one or more dependent (e.g., exam scores) and independent (e.g., study time) variables, whether on one or more groups (e.g., university students).
The quantitative research design that we select subsequently determines whether we look for relationships , associations , trends or interactions . To learn how to structure (i.e., write out) each of these three types of quantitative research question (i.e., descriptive, comparative, relationship-based research questions), see the article: How to structure quantitative research questions .
The “Golden Thread” Explained Simply (+ Examples)
By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022
The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.
The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.
Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.
The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.
Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.
Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .
True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:
“This research aims to explore employee experiences of digital transformation in retail HR.” “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”
As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.
The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.
The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.
Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.
For the digital transformation topic:
To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.
And for the student wellness topic:
To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.
As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.
Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).
The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.
Let’s look at some examples of research questions to make this more tangible.
Again, we’ll stick with the research aims and research objectives we mentioned previously.
For the digital transformation topic (which would be qualitative in nature):
How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?
And for the student wellness topic (which would be quantitative in nature):
Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?
You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.
So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.
Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.
Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .
In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.
As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.
This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...
Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.
Well appreciated. This has helped me greatly in doing my dissertation.
An so delighted with this wonderful information thank you a lot.
so impressive i have benefited a lot looking forward to learn more on research.
I am very happy to have carefully gone through this well researched article.
Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.
Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.
I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.
Thanks so much. This was really helpful.
I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up
i found this document so useful towards my study in research methods. thanks so much.
This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!
Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.
This is quite helpful. I like how the Golden thread has been explained and the needed alignment.
This is quite helpful. I really appreciate!
The article made it simple for researcher students to differentiate between three concepts.
Very innovative and educational in approach to conducting research.
I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.
A very helpful piece. thanks, I really appreciate it .
Very well explained, and it might be helpful to many people like me.
Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?
Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.
My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?
In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.
Exactly what I need in this research journey, I look forward to more of your coaching videos.
This helped a lot. Thanks so much for the effort put into explaining it.
What data source in writing dissertation/Thesis requires?
What is data source covers when writing dessertation/thesis
This is quite useful thanks
I’m excited and thankful. I got so much value which will help me progress in my thesis.
where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?
Very helpful and important tips on Aims, Objectives and Questions.
Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.
Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.
As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).
Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.
Well explained
The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.
A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.
I really found these tips helpful. Thank you very much Grad Coach.
I found this article helpful. Thanks for sharing this.
thank you so much, the explanation and examples are really helpful
This is a well researched and superbly written article for learners of research methods at all levels in the research topic from conceptualization to research findings and conclusions. I highly recommend this material to university graduate students. As an instructor of advanced research methods for PhD students, I have confirmed that I was giving the right guidelines for the degree they are undertaking.
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Quantitative methodology is the dominant research framework in the social sciences. it refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns . quantitative research gathers a range of numeric data. some of the numeric data is intrinsically quantitative (e.g. personal income), while in other cases the numeric structure is imposed (e.g. ‘on a scale from 1 to 10, how depressed did you feel last week’). the collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (e.g. averages, percentages), show relationships among the data (e.g. ‘students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (e.g. the usa has a higher gross domestic product than spain). quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research. qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies..
Coghlan, D., Brydon-Miller, M. (2014). The SAGE encyclopedia of action research (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406
What is the purpose of quantitative research?
The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people. Quantitative research is a way to learn about a particular group of people, known as a sample population. Using scientific inquiry, quantitative research relies on data that are observed or measured to examine questions about the sample population.
Allen, M. (2017). The SAGE encyclopedia of communication research methods (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc doi: 10.4135/9781483381411
How do I know if the study is a quantitative design? What type of quantitative study is it?
Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?
Studies do not always explicitly state what kind of research design is being used. You will need to know how to decipher which design type is used. The following video will help you determine the quantitative design type.
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This seven-hour course provides a comprehensive exploration of research methodologies, beginning with the foundational steps of the scientific method. Students will learn about hypotheses, experimental design, data collection, and the analysis of results. Emphasis is placed on defining variables accurately, distinguishing between independent, dependent, and controlled variables, and understanding their roles in research.
The course delves into major research designs, including experimental, correlational, and observational studies. Students will compare and contrast these designs, evaluating their strengths and weaknesses in various contexts. This comparison extends to the types of research questions scientists pose, highlighting how different designs are suited to different inquiries.
A critical component of the course is developing the ability to judge the quality of sources for literature reviews. Students will learn criteria for evaluating the credibility, relevance, and reliability of sources, ensuring that their understanding of the research literature is built on a solid foundation.
Reliability and validity are key concepts addressed in the course. Students will explore what it means for an observation to be reliable, focusing on consistency and repeatability. They will also compare and contrast different forms of validity, such as internal, external, construct, and criterion validity, and how these apply to various research designs.
The course concepts are thoroughly couched in examples drawn from the psychological research literature. By the end of the course, students will be equipped with the skills to design robust research studies, critically evaluate sources, and understand the nuances of reliability and validity in scientific research. This knowledge will be essential for conducting high-quality research and contributing to the scientific community.
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Research design, research methods and statistical analysis are critical elements of scientific discovery. Understanding the characteristics of quantitative study design, quantitative data collection and quantitative data analysis is a cornerstone of doctoral studies. Here students will explore research design, research methods and data analysis using the foundational skills of quantitative analysis. Doctoral candidates need fundamental skills using statistical software to analyze data. In this course students will use SPSS to analyze raw data. Finally, critical analysis is a cornerstone of doctoral studies. In this course students will critically analyze data presented in peer reviewed sources.
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The relationship between religiosity, spirituality and health has received increasing attention in the academic literature. Studies involving quantitative measurement of religiosity and/or spirituality (R/S) and health have reported many positive associations between these constructs. The quality of various measures, however, is very important in this field, given concerns that some measures of R/S have been contaminated with indicators of mental health. When this occurs, that is when R/S is defined and measured a priori, this subsequently guarantees a positive association between R/S and health (especially mental health). Such associations are called tautological, which involves correlating a construct with itself, thus producing associations that are uninterpretable and misleading. In this article, concerns about the measurement of R/S are discussed, examples of contaminated and potentially probelmatic measures of R/S are noted, and recommendations are made regarding uncontaminated measures of R/S that should be used in future studies of R/S and health.
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Defining “spirituality": Please note that it is not the intent nor within the scope of this review to consider the differences in meaning between "spirituality" and the actual practice of spiritual care or pastoral care. Please refer to Carey et al. ( 2024 , p. 2, and associated Footnote ) for a brief comparative discussion.
Ai, A. L., Wink, P., Paloutzian, R. F., & Harris, K. A. (Eds.). (2021). Assessing spirituality in a diverse world . Springer International Publishing.
Google Scholar
Al Zaben, F., Khalifa, D. A., Sehlo, M. G., Al Shohaib, S., Binzaqr, S. A., Badreg, A. M., & Koenig, H. G. (2015). Religious involvement and health in dialysis patients in Saudi Arabia. Journal of Religion and Health, 54 , 713–730. https://doi.org/10.1007/s10943-014-9962-8
Article PubMed Google Scholar
Al Zaben, F., Sehlo, M. G., Khalifa, D. A., & Koenig, H. G. (2015b). Test–retest reliability of the Muslim religiosity scale: Follow-up to “religious involvement and health among dialysis patients in Saudi Arabia.” Journal of Religion and Health, 54 , 1144–1147. https://doi.org/10.1007/s10943-015-0025-6
Artress, L. (1996). Walking a sacred path: Rediscovering the labyrinth as a spiritual practice . Penguin.
Carey, L. B., Koenig, H. G., Hill, T., Drummond, D., Gabbay, E., Cohen, J., Aiken, C., & Carey, J. R. (2024). Spirituality, mental health, and COVID-19. Journal of Religion and Health, 63 (1), 1–5. https://doi.org/10.1007/s10943-024-02000-z
Daaleman, T. P., & Frey, B. B. (2004). The spirituality index of well-being: A new instrument for health-related quality-of-life research. Annals of Family Medicine, 2 (5), 499–503. https://doi.org/10.1370/afm.89
Article PubMed PubMed Central Google Scholar
de BritoSena, M. A., Damiano, R. F., Lucchetti, G., & Peres, M. F. P. (2021). Defining spirituality in healthcare: A systematic review and conceptual framework. Frontiers in Psychology, 12 , 756080. https://doi.org/10.3389/fpsyg.2021.756080
Article Google Scholar
Drummond, D. A., & Carey, L. B. (2019). Assessing spiritual well-being in residential aged care: An exploratory review. Journal of Religion and Health, 58 , 372–390. https://doi.org/10.1007/s10943-018-0717-9
Exline, J. J., Pargament, K. I., Grubbs, J. B., & Yali, A. M. (2014). The religious and spiritual struggles scale: Development and initial validation. Psychology of Religion and Spirituality, 6 (3), 208. https://doi.org/10.1037/a0036465
Francis, L. J., Lewis, J. M., Philipchalk, R., Brown, L. B., & Lester, D. (1995). The internal consistency reliability and construct validity of the Francis Scale of Attitude toward Christianity (adult) among undergraduate students in the UK, USA, Australia and Canada. Personality and Individual Differences, 19 (6), 949–953. https://doi.org/10.1016/S0191-8869(95)00131-X
Francis, L. J., Santosh, Y. R., Robbins, M., & Vij, S. (2008). Assessing attitude toward Hinduism: The Santosh-Francis Scale. Mental Health, Religion and Culture, 11 (6), 609–621. https://doi.org/10.1080/13674670701846469
Garssen, B., & Visser, A. (2016). Spiritual wellbeing predicting depression: Is it relevant? Journal of Behavioral Medicine, 39 (2), 369–369. https://doi.org/10.1007/s10865-016-9719-9
Garssen, B., Visser, A., & de JagerMeezenbroek, E. (2016). Examining whether spirituality predicts subjective well-being: How to avoid tautology. Psychology of Religion and Spirituality, 8 (2), 141–148. https://doi.org/10.1037/rel0000025
Gomez, R., & Fisher, J. W. (2003). Domains of spiritual well-being and development and validation of the Spiritual Well-Being Questionnaire. Personality and Individual Differences, 35 (8), 1975–1991. https://doi.org/10.1016/S0191-8869(03)00045-X
Gomez, R., & Watson, S. (2023). A reevaluation of the factor structure, reliability, and validity of the Spiritual Well-Being Questionnaire (SWBQ). Journal of Religion and Health, 62 (3), 2112–2130. https://doi.org/10.1007/s10943-022-01619-0
Granqvist, P., & Hagekull, B. (2001). Seeking security in the new age: On attachment and emotional compensation. Journal for the Scientific Study of Religion, 40 (3), 527–545. https://doi.org/10.1111/0021-8294.0007
Hill, P. C., & Maltby, L. E. (2009). Measuring religiousness and spirituality: issues, existing measures, and the implications for education and wellbeing. In M. de Souza, L. J. Francis, J. O’Higgins-Norman, D. Scott (Eds.), International handbook of education for spirituality, care and wellbeing. International Handbooks of Religion and Education (vol 3). Springer.
Hill, P. C., & Hood, R. W., Jr. (1999). Measures of religiosity . Religious Education Press.
Hill, P. C., Hood, R. W., Jong, J., & Harris, K. A. (Eds.). (2024). Measures of religiosity and spirituality . Springer.
Hoge, D. R. (1972). A validated intrinsic religious motivation scale. Journal for the Scientific Study of Religion, 11 , 369–376. https://doi.org/10.2307/1384677
Idler, E. L., Musick, M. A., Ellison, C. G., George, L. K., Krause, N., Ory, M. G., et al. (2003). Measuring multiple dimensions of religion and spirituality for health research conceptual background and findings from the 1998 General Social Survey. Research on Aging, 25 (4), 327–365. https://doi.org/10.2307/1384677
JORH. (2021). Remembering 9/11, moral injury, COVID-19 and measuring religion, spirituality and health. Journal of Religion and Health , 60 (5). https://link.springer.com/journal/10943/volumes-and-issues/60-5 .
JORH. (2023). Care of the aged, women’s health, and measuring religion, spirituality and health. Journal of Religion and Health, 62 (5). https://link.springer.com/journal/10943/volumes-and-issues/62-5
JORH. (2024). Tribal healing, suicide, ethical issues, cancer and measuring religiosity and spirituality. Journal of Religion and Health , 63 (2). https://link.springer.com/journal/10943/volumes-and-issues/63-2
Koenig, H. G., Al-Zaben, F., Khalifa, D. A., & Al Shohaib, S. (2015). Measures of religiosity, Chapter 19. In B. J. Boyle, D. H. Saklofske, G. Mathews (Eds.), Measures of personality and social psychological constructs . Academic Press.
Koenig, H. G. (2008). Concerns about measuring “spirituality” in research. Journal of Nervous and Mental Disease, 196 (5), 349–355. https://doi.org/10.1097/NMD.0b013e31816ff796
Koenig, H. G. (2011). Spirituality and health research: Methods, measurement, statistics, and resources . Templeton Press.
Koenig, H. G., & Büssing, A. (2010). The Duke University Religion Index (DUREL): A five-item measure for use in epidemological studies. Religions, 1 (1), 78–85. https://doi.org/10.3390/rel1010078
Koenig, H. G., Cohen, H. J., Blazer, D. G., Pieper, C., Meador, K. G., Shelp, F., & DiPasquale, B. (1992). Religious coping and depression among elderly, hospitalized medically ill men. American Journal of Psychiatry, 149 (12), 1693–1700. https://doi.org/10.1176/ajp.149.12.1693
Article CAS PubMed Google Scholar
Koenig, H. G., Meador, K. G., & Parkerson, G. (1997). Religion index for psychiatric research. American Journal of Psychiatry, 154 (6), 885–886. https://doi.org/10.1176/ajp.154.6.885b
Koenig, H. G., Nelson, B., Shaw, S. F., Al Zaben, F., Wang, Z., & Saxena, S. (2014). Belief into Action scale: A brief but comprehensive measure of religious commitment. Open Journal of Psychiatry , 5 (01), 66.
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2024). Measurement (Chapter 2). In H. G. Koenig, T. J. VanderWeele, & J. R. Peteet (Eds.), Handbook of religion and health (3rd ed., pp. 15–29). Oxford University Press.
Chapter Google Scholar
Krause, N. (1999). Religious support. In Multidimensional measurement of religiousness/spirituality for use in health research : A report of the Fetzer Institute/National Institute on Aging Workshop Group (pp. 57–63). Fetzer Foundation.
Lesmana, C. B. J., Tiliopoulos, N., & Francis, L. J. (2011). The internal consistency reliability of the Santosh-Francis scale of attitude toward Hinduism among Balinese Hindus. International Journal of Hindu Studies, 15 (3), 293–301. https://doi.org/10.1007/s11407-011-9108-5
Levin, J. (2020). Religion and medicine: A history of the encounter between humanity’s two greatest institutions . Oxford University Press.
Book Google Scholar
Moreira-Almeida, A., & Koenig, H. G. (2006). Retaining the meaning of the words religiousness and spirituality: A commentary on the WHOQOL SRPB group’s “A cross-cultural study of spirituality, religion, and personal beliefs as components of quality of life” (62: 6, 2005, 1486–1497). Social Science and Medicine, 63 (4), 843–845. https://doi.org/10.1016/j.socscimed.2006.03.001
Paloutzian, R. F., & Ellison, C. W. (1982). Loneliness, spiritual well-being, and the quality of life. In L. A. Peplau & D. Perlman (Eds.), Loneliness: A sourcebook of current theory, research and therapy (pp. 224–236). John Wiley & Sons.
Pargament, K. I., Smith, B. W., Koenig, H. G., & Perez, L. (1998). Patterns of positive and negative religious coping with major life stressors. Journal for the Scientific Study of Religion . https://doi.org/10.2307/1388152
Peterman, A. H., Fitchett, G., Brady, M. J., Hernandez, L., & Cella, D. (2002). Measuring spiritual well-being in people with cancer: The functional assessment of chronic illness therapy—spiritual well-being scale (FACIT-Sp). Annals of Behavioral Medicine, 24 (1), 49–58. https://doi.org/10.2307/1388152
Phillips, R. E., Michelle Cheng, C., Oemig, C., Hietbrink, L., & Vonnegut, E. (2012). Validation of a Buddhist coping measure among primarily non-Asian Buddhists in the United States. Journal for the Scientific Study of Religion, 51 (1), 156–172. https://doi.org/10.1111/j.1468-5906.2012.01620.x
Piedmont, R. L. (1999). Does spirituality represent the sixth factor of personality? Spiritual transcendence and the five-factor model. Journal of Personality, 67 (6), 985–1013. https://doi.org/10.1111/1467-6494.00080
Piedmont, R. L. (2001). Spiritual transcendence and the scientific study of spirituality. Journal of Rehabilitation, 67 (1), 4–14.
Puchalski, C. M., Vitillo, R., Hull, S. K., & Reller, N. (2014). Improving the spiritual dimension of whole person care: Reaching national and international consensus. Journal of Palliative Medicine, 17 (6), 642–656. https://doi.org/10.1089/jpm.2014.9427
Rosmarin, D. H., Pargament, K. I., Krumrei, E. J., & Flannelly, K. J. (2009). Religious coping among Jews: Development and initial validation of the JCOPE. Journal of Clinical Psychology, 65 (7), 670–683. https://doi.org/10.1002/jclp.20574
Salander, P. (2006). Who needs the concept of ‘spirituality’? Psycho-Oncology, 15 (7), 647–649. https://onlinelibrary.wiley.com/doi/10.1002/pon.1060
Salander, P. (2012). The emperor’s new clothes: Spirituality. A concept based on questionable ontology and circular findings. Archive for the Psychology of Religion, 34 (1), 17–32. https://doi.org/10.1163/157361212X645241
Sheldrake, P. (2007). A brief history of spirituality . Blackwell Publishing.
Tsuang, M. T., & Simpson, J. C. (2008). Commentary on Koenig (2008): “Concerns about measuring ‘spirituality’ in research.” Journal of Nervous and Mental Disease, 196 (8), 647–649. https://doi.org/10.1097/NMD.0b013e31816ff796
Underwood, L. G., & Teresi, J. A. (2002). The daily spiritual experience scale. Annals of Behavioral Medicine, 24 (1), 22–33. https://doi.org/10.1207/S15324796ABM2401_04
WHOQoL SRPB Group. (2006). A cross-cultural study of spirituality, religion, and personal beliefs as components of quality of life. Social Science and Medicine, 62 (6), 1486–1497. https://doi.org/10.1016/j.socscimed.2005.08.001
Worthington, E. L., Jr., Wade, N. G., Hight, T. L., Ripley, J. S., McCullough, M. E., Berry, J. W., & O’Connor, L. (2003). The religious commitment inventory–10: Development, refinement, and validation of a brief scale for research and counseling. Journal of Counseling Psychology, 50 (1), 84. https://doi.org/10.1037/0022-0167.50.1.84
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Harold G. Koenig
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Department of Psychiatry, Shiraz University of Medical Sciences, Shiraz, Iran
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Lindsay B. Carey
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Institute for Ethics and Society, University of Notre Dame, Sydney, New South Wales, 2007, Australia
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