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#

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

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

3. 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)

4. 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

5. 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.