Bias Assessor (risk-of-bias, lightweight)

Goal: make evidence quality explicit in a way that is quick, consistent, and auditable.

Inputs

• papers/extraction_table.csv

Outputs

• Updated papers/extraction_table.csv

Recommended fields

Use a simple 3-level scale (all lowercase): low | unclear | high .

Suggested columns to add (if missing):

• rob_selection

• rob_measurement

• rob_confounding

• rob_reporting

• rob_overall

• rob_notes

Workflow

• Read papers/extraction_table.csv and identify the set of included studies.

• If RoB columns are missing, add them (keep names stable once introduced).

• For each study, fill each RoB domain:

• low : design/reporting plausibly controls the bias

• unclear : not enough information to judge

• high : clear risk (e.g., missing controls, ambiguous measurement, selective reporting)

• Set rob_overall conservatively:

• high if any domain is high

• unclear if no high but at least one unclear

• low only if all domains are low

• Add 1–3 short notes in rob_notes that justify the rating.

Definition of Done

• Every included paper row has all RoB columns filled.

• Values are strictly from low|unclear|high (no free-form scale drift).

• Notes are short and specific (what was missing / what was strong).

Troubleshooting

Issue: the table has mixed or inconsistent RoB column names

Fix:

• Normalize to the recommended column names and keep a single set across all rows.

Issue: the paper lacks enough methodological detail

Fix:

• Prefer unclear with a concrete note (“no details on X”) rather than guessing.