Qualitative Rigor & COREQ
Audit rigor strategies against COREQ
Qualitative Rigor & COREQ
Audit rigor strategies against COREQ
Showcase
Description
Based on your qualitative study design, it writes a Methods section according to the Lincoln & Guba trustworthiness criteria, then transparently identifies which items are missing or weakly reported according to the COREQ checklist. Who it’s for: researchers seeking robust reporting before journal submission and graduate students writing theses.
Recommended by
Shuting@YouMind
Why we love this skill
Grounds qualitative study trustworthiness in Lincoln & Guba’s criteria while rigorously auditing all 32 COREQ items. It highlights missing reporting, avoids invented strategies, and emphasizes researcher positionality.
Related Skills
View all
ResearchSTROBE/CONSORT Section Writer
Produces complete Methods + Results sections according to the reporting standard appropriate for your study design (STROBE for observational studies and CONSORT for randomized controlled trials). It then transparently audits which checklist items are missing or weakly reported and provides suggestions for completing them. Suitable for researchers seeking robust reporting before journal submission and graduate students writing a thesis.
ResearchResearch Topic & Gap Finder
Suggests original, feasible research topics and gaps based on your interests and knowledge of the existing literature. For each, it provides a draft research question and a feasibility note. Who it's for: Graduate students and researchers looking for a thesis or paper topic.
ResearchStats Report + Reviewer Reply
Generates a complete Findings section from your descriptive and inferential statistics outputs, including assumption tests. If it detects violations of normality or homogeneity of variance, it recommends a nonparametric alternative test rather than hiding the issue. It also anticipates at least four objections commonly raised by journal reviewers (for example, "assumption tests were not reported," "effect sizes were not provided," or "no multiple-comparison correction was applied") and provides a defense sentence for each. Suitable for: researchers working with quantitative research methods who want stronger statistical reporting before journal submission.
Information
- Version
- v2
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto