STROBE · Observational Studies

The STROBE checklist: all 22 items.

Q: How many items are in the STROBE checklist?

STROBE has 22 items, covering the title and abstract (item 1), introduction (items 2–3), methods (items 4–12), results (items 13–17), discussion (items 18–21), and funding (item 22). Eighteen items are common to all observational designs; the other four — items 6, 12, 14, and 15 — are design-specific.

Q: Which STROBE checklist applies to my study — cohort, case-control, or cross-sectional?

All three share the same 22-item structure and differ only on items 6, 12, 14, and 15. Use the cohort version if you followed groups forward from exposure to outcome; the case-control version if you started from the outcome (cases vs. controls) and looked back at exposure; and the cross-sectional version if exposure and outcome were measured at a single time point.

Q: Is a completed STROBE checklist required for publication?

Many biomedical journals require or request a completed STROBE checklist at submission for observational studies, and reviewers increasingly expect STROBE-consistent reporting. It's a reporting standard rather than a regulatory mandate — check your target journal's author instructions for the specific requirement.

Q: What's the difference between STROBE and CONSORT, PRISMA, or STARD?

STROBE covers observational studies, where investigators observe rather than assign exposures. CONSORT is for randomized controlled trials, PRISMA for systematic reviews and meta-analyses, and STARD for diagnostic accuracy studies. If participants were randomized to an intervention, use CONSORT; if you synthesized prior studies, use PRISMA.

Q: Where can I get the official STROBE checklist?

The official checklists and the Explanation & Elaboration paper (which gives the rationale and worked examples for every item) are available from the STROBE Initiative (strobe-statement.org) and the EQUATOR Network. You can also download a free annotated version of all 22 items on this page.

STROBE is the reporting standard for cohort, case-control, and cross-sectional studies — every observational design where investigators do not assign exposures. Twenty-two items cover what reviewers want to see, with a small number of design-specific entries layered on top. This is a complete walkthrough.

Last updated: June 17, 2026

Check Your Manuscript Learn About AI Peer Review

The guideline

What STROBE is.

STROBE — Strengthening the Reporting of Observational Studies in Epidemiology — is the international reporting guideline for observational research. It exists because observational study reports historically omitted the items most needed to assess internal validity: how participants were selected, how exposures and outcomes were measured, what confounders were considered, and how missing data and bias sources were handled. Twenty-two items address these, organized into the same six manuscript sections every reader scans in order.

STROBE is maintained by the STROBE Initiative, listed under the EQUATOR Network. The STROBE Statement — the current, widely adopted version — is the 22-item core checklist with the original Explanation and Elaboration document. Most major biomedical journals require STROBE compliance for observational studies, and many ask for a completed checklist at submission.

STROBE applies to any study where investigators observe — rather than assign — exposures. If you randomized participants to interventions, you need CONSORT instead. If you synthesized evidence from prior studies, you need PRISMA.

The variants

Three design-specific checklists.

The 22 STROBE items are largely shared across designs, but cohort, case-control, and cross-sectional studies each have a dedicated checklist that emphasizes the items that matter most for that design. PeerReviewAI selects the correct variant from the manuscript automatically.

STROBE Cohort

For cohort studies — prospective or retrospective. Defines exposed and unexposed groups at baseline and follows them forward to outcome. STROBE places extra weight on follow-up time, loss to follow-up, and how exposure was operationalized at baseline.

STROBE Case-Control

For case-control studies. Cases must be defined precisely; controls must represent the source population that generated the cases. STROBE places extra weight on case definition, control selection, matching criteria, and ensuring exposure ascertainment is identical for cases and controls.

STROBE Cross-Sectional

For cross-sectional studies — exposure and outcome assessed at one time point. STROBE places extra weight on the inability to establish temporality, on selection of the source population, and on how exposure and outcome were measured at the same visit.

What differs by design.

Item	Cohort	Case-control	Cross-sectional
6 · Participants	How the exposed and unexposed groups were selected; methods of follow-up. Matched designs: matching criteria and numbers.	How cases were ascertained and controls selected, with the rationale. Matched designs: matching criteria and controls per case.	Eligibility and the sources and methods of participant selection.
12(d) · Statistical methods	Explain how loss to follow-up was addressed.	Explain how matching of cases and controls was addressed.	Describe analytical methods that account for the sampling strategy.
14 · Descriptive data	Characteristics + missing-data counts, plus a summary of follow-up time.	Characteristics + missing-data counts.	Characteristics + missing-data counts.
15 · Outcome data	Numbers of outcome events or summary measures over time.	Numbers in each exposure category, or summary measures of exposure.	Numbers of outcome events or summary measures.

The checklist

STROBE, section by section.

The 22 items are organized into title and abstract, introduction, methods, results, discussion, and funding. These are the topics each item asks you to cover — what is required, and why reviewers care.

Download the 22-item checklist (PDF)

Title and abstract

Identify the study's design with a commonly used term — cohort, case-control, or cross-sectional — in the title or abstract, and give an informative, balanced abstract of what was done and found. Burying the design in the methods, or summarizing the rationale only after the results, fails this item.

Background / rationale

Explain the scientific background and rationale for the investigation: the gap in existing evidence the study addresses and why it matters.

Objectives

State specific objectives, including any pre-specified hypotheses. Objectives stated only after the results are summarized do not satisfy this item.

Study design

Present the key elements of the study design early in the paper, so reviewers do not have to infer it from the analysis.

Setting

Describe the setting, locations, and relevant dates — periods of recruitment, exposure, follow-up, and data collection. A study that doesn't specify when participants were enrolled, when exposure was measured, or how long follow-up lasted can't be evaluated for temporality or generalizability.

ParticipantsDesign-specific

Give the eligibility criteria and the sources and methods of participant selection. This differs by design: cohort studies describe how the exposed and unexposed groups were selected and the methods of follow-up (and, for matched designs, the matching criteria and the number of exposed and unexposed); case-control studies describe how cases were ascertained and how controls were selected, with the rationale for that choice (and, for matched designs, the matching criteria and the number of controls per case); cross-sectional studies describe the eligibility criteria and the sources and methods used to select participants. Vague selection ("patients seen in our clinic") is a flagged item.

Variables

Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers, with diagnostic criteria where applicable. A study that examines "smoking" without defining what counts — pack-years, current versus former, intensity, recency — can't be reproduced or compared across the literature.

Data sources / measurement

For each variable of interest, give the sources of data and the details of how it was assessed (measured), and describe the comparability of assessment methods if there is more than one group. Self-reported, registry-linked, lab-measured, and clinically adjudicated data carry very different validity profiles. (Report separately for cases and controls, or for exposed and unexposed groups.)

Bias

Describe the efforts made to address potential sources of bias. Name the specific bias sources the design is exposed to — selection, information, recall, ascertainment, immortal-time, healthy-worker — and what was done about each. "Limitations are discussed in the discussion" does not satisfy this item.

Study size

Explain how the study size was arrived at. Reviewers expect a power calculation for a primary analysis where the size was chosen prospectively, or a precision-based rationale for studies built on secondary data.

Quantitative variables

Explain how quantitative variables were handled in the analyses, and describe which groupings were chosen and why. Categorizing a continuous exposure into deciles without justification, or choosing cut-points after seeing the data, raises concerns about multiplicity and post-hoc analysis.

Statistical methodsDesign-specific

Describe all statistical methods, including those used to control for confounding; the methods used to examine subgroups and interactions; how missing data were addressed; and any sensitivity analyses. One sub-item is design-specific: cohort studies explain how loss to follow-up was addressed, case-control studies explain how matching of cases and controls was addressed, and cross-sectional studies describe analytical methods that account for the sampling strategy. This is the most commonly under-reported section in observational manuscripts.

Participants (results)

Report the numbers of individuals at each stage — potentially eligible, examined for eligibility, confirmed eligible, included, completing follow-up, and analyzed — and give reasons for non-participation at each stage. A flow diagram is not formally required but is strongly preferred by reviewers. (Report separately for cases/controls or exposed/unexposed as applicable.)

Descriptive dataDesign-specific

Give the characteristics of study participants (demographic, clinical, social) and information on exposures and potential confounders, and indicate the number of participants with missing data for each variable of interest. Cohort studies additionally summarize follow-up time (for example, average and total). Missing-data counts per variable are easy to omit and are frequently flagged.

Outcome dataDesign-specific

What to report depends on the design: cohort studies report the numbers of outcome events or summary measures over time; case-control studies report the numbers in each exposure category, or summary measures of exposure; cross-sectional studies report the numbers of outcome events or summary measures.

Main results

Give unadjusted estimates and, where applicable, confounder-adjusted estimates and their precision (such as 95% confidence intervals), making clear which confounders were adjusted for and why. Report category boundaries when continuous variables were categorized, and where relevant translate relative risk into absolute risk for a meaningful time period.

Other analyses

Report other analyses performed — subgroups and interactions, and sensitivity analyses. Pre-specified and exploratory analyses must be distinguished. Subgroup findings reported without interaction tests, or sensitivity analyses chosen to support the main result, are common overreaches.

Key results

Summarize the key results with reference to the study objectives.

Limitations

Discuss the limitations of the study, taking into account sources of potential bias or imprecision, and discuss both the direction and the magnitude of any potential bias. STROBE asks authors to name the likely direction of bias — not merely to acknowledge that bias exists.

Interpretation

Give a cautious overall interpretation of the results, considering the objectives, limitations, the multiplicity of analyses, results from similar studies, and other relevant evidence.

Generalisability

Discuss the generalizability (external validity) of the results. A finding in a single-center clinic population doesn't transfer to a national registry sample without justification, and STROBE asks authors to make the transferability case explicitly.

Funding

Give the source of funding and the role of the funders for the present study and, where applicable, for the original study on which the present article is based. Underspecified funder roles — especially in industry-sponsored secondary analyses — are flagged.

The contrast

Adequate vs. inadequate reporting.

Three of the STROBE items most consistently missed in submitted observational manuscripts. Each shows the version that fails review next to the version that passes — with the reasoning a reviewer would use.

Exposure definition and ascertainment

Inadequate

"We compared smokers and non-smokers for risk of lung cancer."

Adequate

"Smoking status was defined at baseline as: current smoker (≥1 cigarette/day for ≥6 months and smoking at the time of enrollment), former smoker (any history of regular smoking but no smoking in the 6 months before enrollment), or never smoker (lifetime <100 cigarettes). Status was self-reported via a structured questionnaire and validated by serum cotinine in a 10% random subsample (95% agreement). Cumulative exposure was calculated in pack-years."

Why it mattersSTROBE Item 7 (variables) and Item 8 (data sources/measurement) together require this level of detail. The inadequate version makes misclassification a near-certainty — "smokers" could mean anything from one cigarette ever to two packs a day. The adequate version operationalizes the exposure, names the measurement instrument, and reports a validation check.

Confounding control

Inadequate

"We adjusted for age, sex, and other relevant variables in a multivariable model."

Adequate

"The primary analysis adjusted for pre-specified confounders identified a priori from a directed acyclic graph: age (continuous), sex, baseline BMI, smoking status, alcohol intake, physical activity, baseline blood pressure, baseline LDL cholesterol, and socioeconomic status (deprivation index). Variables were chosen as confounders if they were associated with both exposure and outcome based on prior literature and the DAG; mediators on the causal pathway were excluded. A sensitivity analysis additionally adjusted for [variable], which approached significance in univariate analysis but was not pre-specified."

Why it mattersSTROBE Item 12 (statistical methods) requires confounding control to be specified, not gestured at. "Other relevant variables" is uninterpretable and signals data-driven model selection. The adequate version pre-specifies confounders, names the framework (DAG), and separates pre-specified from post-hoc adjustment — which is exactly what a careful observational analysis looks like.

Participant flow and missing data

Inadequate

"We included 2,400 patients in the analysis."

Adequate

"Of 3,150 individuals potentially eligible from the source registry, 2,610 met all eligibility criteria (excluded: 312 with prior outcome, 158 with missing baseline exposure data, 70 lost to baseline visit). Of these, 2,400 were included in the primary analysis (loss to follow-up: 210, 8.0%; reasons reported in Supplementary Figure S1). Missing data on individual covariates ranged from 0% to 6.8%; multiple imputation under a missing-at-random assumption was used for the primary analysis (20 imputations, MICE), with complete-case analysis reported as a sensitivity check."

Why it mattersSTROBE Item 13 (participants) and Item 14 (descriptive data) together require this. The inadequate version skips from "source" to "analyzed" with no accountability for the 750 who dropped out at each stage. The adequate version makes participation transparent and pre-specifies missing-data handling — which is the difference between a study reviewers trust and one they do not.

The check

How PeerReviewAI evaluates STROBE compliance.

STROBE compliance is checked on every observational manuscript submitted to AI Peer Review — including the lowest tier. No add-on required.

Auto-detected observational design

Upload your manuscript and cohort, case-control, or cross-sectional design is identified automatically. The matching STROBE variant is used as the reporting checklist — you do not have to choose it.

Item-by-item qualitative assessment

Each STROBE item is evaluated against your manuscript text. The output is a qualitative judgment per item — adequate, incomplete, or missing. Items most often under-reported in observational research (variable definitions, confounder handling, bias sources, missing data) get explicit attention.

Specific, locatable feedback

For every item flagged as incomplete or missing, the feedback says what STROBE requires, what your manuscript currently states, and what is missing. You can act on it directly without cross-referencing the official Explanation and Elaboration document.

Included in every tier

STROBE compliance checking is part of Essentials ($2.99), Peer Review ($29), and Author Review ($79). The deeper tiers add Major/Minor Issue analysis and (for Author Review) a compliance audit against your target journal's author instructions.

Related guidelines

If your study is not observational.

STROBE · checked on every observational study

Check your study against STROBE.

Check Your Manuscript Learn About AI Peer Review

FAQ

Questions, answered.

Don't see yours? Email us — we read every one.

How many items are in the STROBE checklist?+

Which STROBE checklist applies to my study — cohort, case-control, or cross-sectional?+

Is a completed STROBE checklist required for publication?+

What's the difference between STROBE and CONSORT, PRISMA, or STARD?+

Where can I get the official STROBE checklist?+