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Method Guide
How to Use research-skills in a Medical Research Workflow
A practical guide to using research-skills for literature search, screening, evidence tables, methods checks, and manuscript planning.
Before using this in research
The goal is not to adopt another tool. The goal is to reduce verified research time without weakening the evidence trail.
Best for
Biomedical, clinical, public health, and academic researchers who need a structured way to organize literature searches, study screening, evidence extraction, methods review, and early manuscript outlines.
First step
Start by defining the research question, target population, intervention or exposure, comparator, outcomes, study types, and any date, language, or database limits before asking research-skills to help structure the workflow.
A safer workflow
1
Translate the research question into searchable concepts, keywords, synonyms, and controlled vocabulary terms, then draft database-specific search strategies for researcher review.
2Use predefined inclusion and exclusion criteria to organize title, abstract, and full-text screening, while documenting reasons for exclusion and keeping final eligibility decisions with the research team.
3Create an evidence table template covering study design, population, sample size, intervention or exposure, comparator, outcomes, effect estimates, limitations, and funding or conflict-of-interest information.
4Check whether the planned methods, reporting items, and manuscript structure align with the study type, journal requirements, and relevant reporting guidelines before drafting the introduction, methods, results, and discussion outline.
Research playbook
This section expands the summary into a working reference so you can compare it with the source page, brief a teammate, or turn it into a repeatable checklist.
What this page helps you decide
A practical guide to using research-skills for literature search, screening, evidence tables, methods checks, and manuscript planning. The practical decision is whether this workflow improves the research task while preserving traceability, source review, and a clear record of what changed between the first draft and the final claim.
Use this as a decision note rather than a generic recommendation. Start from the specific task, decide what evidence must be checked, and keep the final research claim tied to sources another person can inspect.
Who should use it first
Biomedical, clinical, public health, and academic researchers who need a structured way to organize literature searches, study screening, evidence extraction, methods review, and early manuscript outlines.
The first action is deliberately small: Start by defining the research question, target population, intervention or exposure, comparator, outcomes, study types, and any date, language, or database limits before asking research-skills to help structure the workflow. That small trial should produce a visible record of inputs, outputs, sources, decisions, and unresolved questions before the workflow is used on a manuscript, report, grant, or formal review.
Step-by-step working version
Step 1
Translate the research question into searchable concepts, keywords, synonyms, and controlled vocabulary terms, then draft database-specific search strategies for researcher review.
Record the source, decision, owner, and next check before moving on. This keeps the workflow auditable instead of becoming a one-off AI output.
Step 2
Use predefined inclusion and exclusion criteria to organize title, abstract, and full-text screening, while documenting reasons for exclusion and keeping final eligibility decisions with the research team.
Record the source, decision, owner, and next check before moving on. This keeps the workflow auditable instead of becoming a one-off AI output.
Step 3
Create an evidence table template covering study design, population, sample size, intervention or exposure, comparator, outcomes, effect estimates, limitations, and funding or conflict-of-interest information.
Record the source, decision, owner, and next check before moving on. This keeps the workflow auditable instead of becoming a one-off AI output.
Step 4
Check whether the planned methods, reporting items, and manuscript structure align with the study type, journal requirements, and relevant reporting guidelines before drafting the introduction, methods, results, and discussion outline.
Record the source, decision, owner, and next check before moving on. This keeps the workflow auditable instead of becoming a one-off AI output.
Before you rely on the output
Failure points to check
- Do not treat AI-generated search terms, screening suggestions, or summaries as final evidence; verify them against original databases and full-text articles.
- Avoid relying on research-skills for clinical, statistical, or methodological judgments that require domain expertise, protocol decisions, or senior researcher approval.
- Keep a transparent audit trail of search dates, databases, search strings, screening decisions, data extraction changes, and reviewer disagreements.
Evidence checklist
- Cross-check extracted data, effect sizes, sample characteristics, and outcome definitions against the original publication and supplementary materials.
- Assess risk of bias, study quality, and certainty of evidence using appropriate tools for the study design rather than generic summary judgments.
- Confirm that citations, claims, and manuscript statements are supported by the cited sources and do not overstate causality, generalizability, or clinical relevance.
Bottom line for How to Use research-skills in a Medical Research Workflow
A strong result is not the fastest output. It is the output that can be checked against the original source, repeated by another researcher, and revised without losing the reasoning trail.
Watch-outs
Do not treat AI-generated search terms, screening suggestions, or summaries as final evidence; verify them against original databases and full-text articles.
Avoid relying on research-skills for clinical, statistical, or methodological judgments that require domain expertise, protocol decisions, or senior researcher approval.
Keep a transparent audit trail of search dates, databases, search strings, screening decisions, data extraction changes, and reviewer disagreements.
Evidence checks
Cross-check extracted data, effect sizes, sample characteristics, and outcome definitions against the original publication and supplementary materials.
Assess risk of bias, study quality, and certainty of evidence using appropriate tools for the study design rather than generic summary judgments.
Confirm that citations, claims, and manuscript statements are supported by the cited sources and do not overstate causality, generalizability, or clinical relevance.
This English decision page is optimized for fast evaluation. The source detail page keeps the longer reference material, examples, and local context for deeper review.