Gender-specific economic interventions for women's mental health and well-being in South Asia: a systematic review.

Soc Psychiatry Psychiatr EpidemiolMar 5, 2026 (epub)

Jaya Katiyar, Roxanne Keynejad

✦ AI-curated · Sources linked

In 30 seconds

This systematic review assessed quantitative studies of economic interventions and women’s common mental disorder (CMD) outcomes or well-being in South Asia. Eight eligible studies from Afghanistan, Bangladesh and India examined microfinance, employment, conditional cash transfers, self-help groups and economic empowerment programmes. Approximately 60% reported statistically significant associations between receiving an intervention and improved CMD symptoms or well-being. The authors judged the evidence limited, with moderate risk of bias and heterogeneous study designs, and noted limited attention to gendered risks in settings with strong patriarchal norms.

Key findings

  • Eight studies evaluated five intervention types across Afghanistan (n = 1), Bangladesh (n = 2) and India (n = 5).
  • Approximately 60% of studies reported statistically significant associations with improved CMD symptoms or well-being.
  • Risk of bias was moderate, and study designs were heterogeneous.
  • Attention to gendered risks in countries with strong patriarchal norms was limited.

Why it matters

Economic disadvantage is identified as a modifiable risk factor for CMDs, and the review suggests that some economic interventions may coincide with better mental health or well-being among women. However, the evidence base is small and geographically concentrated, and potential gendered harms have received limited attention. Evaluating both benefits and risks is important when considering such programmes.

What to keep in mind

Only eight studies were eligible; designs were heterogeneous, risk of bias was moderate, and geographical representation was limited. Attention to gendered risks was also limited.

Source

Published in Soc Psychiatry Psychiatr Epidemiol. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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