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STROBE guidelines checklist observational studies 2025
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STROBE statement observational epidemiology reporting guidelines
Here is a full overview of the STROBE Guidelines (Strengthening the Reporting of Observational Studies in Epidemiology):
What is STROBE?
STROBE is a reporting guideline - not a study design tool or quality assessment instrument - developed in 2004 by epidemiologists, methodologists, statisticians, and journal editors, and first published in 2007 (von Elm et al., BMJ 2007, PMID: 17947786). It applies to the three main observational designs:
- Cohort studies
- Case-control studies
- Cross-sectional studies
The 22-Item STROBE Checklist
Title & Abstract
| Item | Requirement |
|---|---|
| 1 | Indicate the study design with a commonly used term in the title or abstract; provide an informative, balanced summary of what was done and found |
Introduction
| Item | Requirement |
|---|---|
| 2 | Background/rationale - Explain the scientific background and rationale for the investigation |
| 3 | Objectives - State specific objectives, including any pre-specified hypotheses |
Methods
| Item | Requirement |
|---|---|
| 4 | Study design - Present key elements of study design early in the paper |
| 5 | Setting - Describe the setting, locations, and relevant dates (recruitment, exposure, follow-up, data collection) |
| 6* | Participants - Eligibility criteria and sources/methods of participant selection (design-specific) |
| 7 | Variables - Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers; give diagnostic criteria if applicable |
| 8 | Data sources/measurement - For each variable, describe sources of data and methods of assessment; if >1 group, describe comparability of methods |
| 9 | Bias - Describe any efforts to address potential sources of bias |
| 10 | Study size - Explain how the study size was determined |
| 11 | Quantitative variables - Explain how quantitative variables were handled in analyses; if applicable, describe grouping rationale |
| 12* | Statistical methods - Describe all statistical methods, including those used to control for confounding; methods for missing data; sensitivity analyses (design-specific elements) |
Results
| Item | Requirement |
|---|---|
| 13* | Participants - Report numbers at each stage (eligible, excluded, analysed); reasons for non-participation; consider flow diagram |
| 14* | Descriptive data - Characteristics of participants, information on exposures and potential confounders |
| 15* | Outcome data - Report numbers of outcome events or summary measures (design-specific) |
| 16 | Main results - Report unadjusted and adjusted estimates with precision (confidence intervals); report category boundaries if continuous variables were categorized |
| 17 | Other analyses - Report other analyses done (sensitivity, subgroups, interactions) |
Discussion
| Item | Requirement |
|---|---|
| 18 | Key results - Summarise key results with reference to study objectives |
| 19 | Limitations - Discuss limitations, sources of potential bias/imprecision, and both direction and magnitude of potential bias |
| 20 | Interpretation - Give a cautious overall interpretation considering objectives, limitations, multiplicity of analyses, and other relevant evidence |
| 21 | Generalisability - Discuss the generalisability (external validity) of the study results |
Other Information
| Item | Requirement |
|---|---|
| 22 | Funding - Give the source of funding and the role of funders |
* Items 6, 12, 14, and 15 have design-specific versions for cohort, case-control, and cross-sectional studies.
Design-Specific Notes
Item 6 - Participants:
- Cohort: Eligibility criteria, sources/methods of selection, methods of follow-up
- Case-control: Eligibility criteria, sources/methods of case ascertainment and control selection; rationale for choice of cases and controls
- Cross-sectional: Eligibility criteria, sources/methods of selection
Item 12 - Statistical methods (extra elements):
- Cohort: How loss to follow-up was addressed
- Case-control: How matching of cases and controls was accounted for
- Cross-sectional: Sampling strategy if applicable
STROBE Extensions (Specialist Adaptations)
Several extensions exist for specific contexts:
| Extension | Target |
|---|---|
| STROBE-NI | Neonatal infections |
| STROBE-Vet | Veterinary epidemiology |
| STROBE-ME | Molecular epidemiology |
| STROBE-MCCS | Matched case-control studies |
| RECORD | Routinely collected health data |
| STROBE-Equity | Health equity reporting (published BMJ 2025 - adds 10 equity-specific items) |
| STROBE-D | Drowning research (under development as of 2025) |
Key Points for Use
- Not a quality tool - STROBE guides reporting, not study quality assessment. Do not use it to score study quality.
- Not prescriptive for design - It tells you what to report, not how to conduct your study.
- Downloadable checklists - Separate checklists for each of the three designs are available at strobe-statement.org and via the EQUATOR Network.
- Companion E&E document - A detailed Explanation and Elaboration (E&E) document accompanies the main statement and provides rationale and examples for each item.
- Journal adoption - Over 100 journals endorse or require STROBE compliance at submission.
The original STROBE statement is: von Elm E et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 2007;335:806. PMID: 17947786
Create a STROBE checklist template I can use for my manuscript
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Your STROBE checklist is ready:
STROBE CaseControl Checklist
PDF Document · PDF
Here's what's included in the template:
- All 22 STROBE items with full recommendation text, tailored for a case-control study
- Design-specific items (6, 12, 13, 14, 15) are marked with a blue dot and contain the exact case-control wording
- Manuscript info fields at the top - fill in your title, author(s), journal, and date
- "Page(s) in MS" column - fill in the page numbers where each item appears in your manuscript before submission
- "Notes / Comments" column - space to flag items you still need to address
- Section groupings (Title & Abstract, Introduction, Methods, Results, Discussion, Other Information) with colour-coded headers
- Full citation and link to strobe-statement.org in the footer
To use it: open the PDF, print it or annotate it digitally, and work through each item before submitting.
make critical appraisal as per strobe guidlines
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Your critical appraisal report is ready:
STROBE CriticalAppraisal DiabetesTB
PDF Document · PDF
Summary of findings across all 22 STROBE items
| Judgement | Count |
|---|---|
| ✅ MET | 8 / 22 |
| 🟡 PARTIAL | 11 / 22 |
| ❌ NOT MET | 3 / 22 |
The 4 most important methodological gaps found
1. Wrong regression model for matched data (Item 12)
The study used 1:1 age/sex matching but then applied unconditional logistic regression. Matched case-control designs require conditional logistic regression - using unconditional regression can produce biased OR estimates for the matched variables.
2. No participant flow diagram (Item 13)
The total sampling frame size, number of ineligible cases, and number of controls approached-then-refused are never reported. It is impossible to assess selection bias or recruitment adequacy.
3. Ambiguous diabetes exposure definition (Item 7)
Diabetes was classified as "known case" (self-report/prior diagnosis). FBG was measured for all participants but never used to reclassify participants or detect undiagnosed diabetes. This leaves exposure misclassification unquantified.
4. Missing data not reported anywhere (Item 12c)
No variable in Tables 1-3 shows any missing data counts or imputation strategy - this is essential for transparent observational research reporting.
What was done well
- Study design clearly stated throughout (Item 1, 4, 5)
- Sample size calculation fully described with software, alpha, power, and cited proportions (Item 10)
- Multivariable regression table with full ORs and 95% CIs (Item 16)
- Funding and conflicts of interest disclosed (Item 22)
- Background and rationale well-supported with WHO data and prior literature (Item 2)
Create a summary table showing which adjustments would improve reporting compliance
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Your improvement table is ready:
STROBE ImprovementTable DiabetesTB
PDF Document · PDF
What the table contains
The table covers all 16 items needing improvement, organised into three groups:
Group A — NOT MET items (2 items)
| Item | Gap | Fix |
|---|---|---|
| 13 | No flow diagram, no non-response data | Add CONSORT-style flow diagram as Figure 1 |
| 17 | No subgroup/sensitivity analyses | Add sex-stratified ORs, DM×tobacco interaction, rural exclusion sensitivity run |
Group B — PARTIAL items (11 items)
Key fixes include: redefining diabetes using FBG ≥126 mg/dL (Item 7), switching to conditional logistic regression for matched data (Item 12), adding crude OR column to Table 1 (Item 16), reporting missing data per variable (Items 12, 14), and adding detection bias discussion (Items 9, 19).
Group C — MET items with minor enhancements (3 items)
Small additions to abstract CIs, biological mechanism sentence, and funder role statement.
The revision roadmap at the bottom of the PDF breaks the fixes into 3 steps:
- Step 1 (HIGH priority) - Must do before resubmission: flow diagram, FBG-based diabetes reclassification, conditional logistic regression, detection bias discussion
- Step 2 (MEDIUM priority) - Strongly recommended: TB case definition, glucometer QC, crude ORs, sensitivity analysis
- Step 3 (LOW priority) - Best practice polish: abstract CIs, mechanism text, generalisability clarification, funder role
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