| Element | Description | Example |
|---|---|---|
| P | Population of Interest: Who is the target group you are studying? | US adults |
| I | Intervention: What is the main action, treatment, or variable you're looking at? | Effect of having rheumatoid arthritis |
| C | Comparison: Are you comparing the intervention against a control group or usual care? | People without rheumatoid arthritis |
| O | Outcome of Interest: What specifically do you want to measure? | Rate of cardiovascular diseases |
| T | Time Frame: Over what time period will your study take place? | 1999–2018 |
Concepts (Q)
According to Thabane et al., there is a structured approach to do this, primarily using the PICOT and FINER frameworks.
Thabane et al. (2009)
PICOT Framework
The PICOT framework helps to structure a specific and clear research question by focusing on five key elements:
Research Question: “In US adults, does having rheumatoid arthritis, compared to those without rheumatoid arthritis, affect the rate of cardiovascular diseases during 1999–2018?” based on Hossain et al. (2022): DOI: 10.1016/j.annepidem.2022.03.005
FINER Criteria
Once we have formulated your research question with the help of the PICOT elements, we should evaluate it using the FINER criteria:
| Element | Description |
|---|---|
| F | Feasible: Is it possible to conduct this research with available resources? |
| I | Interesting: Is the research question intriguing to the scientific community? |
| N | Novel: Is the question original and not already thoroughly researched? |
| E | Ethical: Is the research ethically sound? |
| R | Relevant: Is the research currently needed or will it fill a gap in existing knowledge? |
The key takeaway is: Use the PICOT and FINER frameworks to guide you in framing a compelling, ethical, and achievable research question.
SAP
A Statistical Analysis Plan (SAP), also referred to as a Data Analysis Plan (DAP) or Reporting Analysis Plan (RAP), is an integral part of research, particularly in randomized controlled trials (RCTs) (Kahan et al. 2020), but also in observational studies (Hiemstra et al. 2019). Here are a few reasons why it is beneficial to pre-plan the SAP for an observational study:
- Pre-planning an SAP helps define the specific analytical strategies and methods that will be used to answer the research questions. It outlines the techniques for handling data, including
- the treatment of missing data, outliers,
- the use of statistical tests, and
- confounding adjustment techniques.
- By detailing the analysis plan before the data is examined, researchers ensure transparency and reduce the risk of data dredging or p-hacking.
- Confounding is a more pronounced issue in observational studies. Strategies for addressing confounding need to be more elaborate and explicit in observational studies.
Refer to the ‘Scientific Writing for Health Research’ book chapter for more details and examples for PICOT, FINER and Statistical Analysis Plan (SAP).
Note
We include 2 types of tutorials that emphasize the critical steps of data preparation and analysis tailored to specific research questions, cosidering the PICOT framework. They underscore the importance of refining and cleaning datasets to ensure their suitability for rigorous analytical procedures. The analyses, while rooted in distinct methodologies, converge on the common goal of deriving meaningful insights and ensuring the integrity and validity of the results obtained from the processed analytical data.
Data preparation: Merging, reformatting and recategorizing essential variables to create a dataset suitable for analysis, aligning it with the study’s objectives.
Video Lessons
PICOT and FINER
What is included in this Video Lesson:
- References 0:53
- How to get an idea about a Research Question? 1:05
- Why the question need to be good? 2:41
- A framework for defining a research question 5:17
- Think hard about the ‘Outcome’ 14:40
- Is this research doable? 17:57
- Overall Roadmap 19:57
- Other Reference (optional) 21:27
The timestamps are also included in the YouTube video description.
SAP
What is included in this Video Lesson:
- SAP 0:03
- SAP example from a RCT 1:31
- SAP example from an observational study 4:40
- Code book 15:35
The timestamps are also included in the YouTube video description.
Video Lesson Slides
Links
References
Hiemstra, Bart, Frederik Keus, Jørn Wetterslev, Christian Gluud, and Iwan CC van der Horst. 2019. “DEBATE-Statistical Analysis Plans for Observational Studies.” BMC Medical Research Methodology 19 (1): 1–10.
Hossain, Md Belal, Jacek A Kopec, Mohammad Atiquzzaman, and Mohammad Ehsanul Karim. 2022. “The Association Between Rheumatoid Arthritis and Cardiovascular Disease Among Adults in the United States During 1999–2018, and Age-Related Effect Modification in Relative and Absolute Scales.” Annals of Epidemiology 71: 23–30.
Kahan, Brennan C, Tahania Ahmad, Gordon Forbes, and Suzie Cro. 2020. “Public Availability and Adherence to Prespecified Statistical Analysis Approaches Was Low in Published Randomized Trials.” Journal of Clinical Epidemiology 128: 29–34.
Thabane, Lehana, Tara Thomas, Chenglin Ye, and James Paul. 2009. “Posing the Research Question: Not so Simple.” Canadian Journal of Anesthesia/Journal Canadien d’anesthésie 56 (1): 71–79.