Using the STROSA checklist in BMF studies

Ni Putu Wulan Purnama Sari
Faculty of Nursing, Widya Mandala Surabaya Catholic University, East Java, Indonesia

March 5, 2026

The STROSA checklist (Strengthening the Reporting of Observational Studies in Secondary Data Analysis) [1] was developed to improve transparency, rigor, and reproducibility in studies that rely on existing datasets, like BMF studies [2].

The STROSA checklist was developed as an extension of the STROBE statement (used for observational studies) to address the unique aspects of secondary data analyses. Compared to STROBE, seven new STROSA-specific items are highlighted: legal aspects, data flow, study protocol, unit of analysis, internal validations, advantages of secondary data use, and role of data owners. Other items were adapted from STROBE to ensure consistency across observational and secondary data reporting. Finally, the STROSA checklist includes 29 items related to the title/abstract, introduction, methods, results, discussion, and additional information sections of articles.



The STROSA Checklist

Unlike primary data collection, secondary data analysis involves working with information that has already been gathered for other purposes, such as administrative records, health surveys, or registries. Because of this, BMF scholars must be especially clear about how they handle data limitations, biases, and methodological choices. By filling in each section of the STROSA, BMF scholars can demonstrate methodological rigor and allow readers to critically assess the validity of findings. Filling in the STROSA checklist requires systematically addressing each reporting item. Researchers should:

1. Identify the dataset: Clearly state the source, scope, and time frame of the secondary data used.
2. Describe study design and population: Explain inclusion/exclusion criteria, sampling methods, and representativeness.
3. Detail variables and measures: Define exposures, outcomes, and covariates, including how they were operationalized from the dataset.
4. Explain data handling: Document cleaning, linkage, imputation, and transformations.
5. Report statistical methods: Specify models, adjustments, and sensitivity analyses.
6. Address limitations: Discuss missing data, measurement error, and potential biases inherent in secondary sources.
7. Ensure transparency: Provide access details (if possible) and clarify ethical considerations around data use.

Why STROSA compliance is essential for BMF studies lies in the unique challenges of working with pre-existing datasets. Unlike primary studies, BMF scholars cannot control how data were collected, which introduces risks of bias, misclassification, and incomplete information. The STROSA checklist ensures that:

• Transparency: Readers understand the dataset’s origin, strengths, and weaknesses.
• Reproducibility: Other researchers can replicate or build upon the analysis.
• Credibility: Journals and policymakers can trust the findings, knowing that methodological limitations were openly addressed.
• Ethical responsibility: Proper reporting safeguards against misuse or misinterpretation of sensitive data.

In short, the STROSA checklist is not just a bureaucratic requirement—it is a tool that strengthens the scientific integrity of BMF studies. By adhering to it, BMF scholars uphold standards of clarity, accountability, and reliability, ensuring that secondary data contributes meaningfully to evidence-based practice [3].

References

[1] Swart E, Schmitt J (2014) Standardized Reporting of secondary data analyses (STROSA)-Vorschlag für Ein berichtsformat für Sekundärdatenanalysen. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, 108(8-9), 511-516. https://doi.org/10.1016/j.zefq.2014.08.022

[2] Vuong QH, Nguyen MH, La VP (2022) The mindsponge and BMF analytics for innovative thinking in social sciences and humanities. Walter de Gruyter GmbH.

[3] Vuong QH, Nguyen MH (2025) Developing Bayesian probabilistic reasoning capacity in HSS disciplines: Qualitative evaluation on bayesvl and BMF analytics for ECRs. https://doi.org/10.48550/arXiv.2601.06038