aceA Machine Learning-Guided Lyric Analysis Peer Support Intervention (LAPSI) for Psychological Distress in South African Women: Protocol for an Exploratory Sequential Mixed Methods Study
Background Psychological distress disproportionately affects women in South Africa and is shaped by complex structural, socioeconomic, and psychosocial determinants, particularly within the context of HIV. Despite policy commitments to integrate mental health services into existing health systems, current interventions are limited in their capacity to address these intersecting determinants and are frequently insufficiently targeted, contextually responsive, or inclusive. Data-driven strategies that identify sub…
Machine learning risk profiling with SHAP interpretability was used to design a culturally grounded peer support intervention, which was delivered to 30 women in two provinces; effectiveness is not yet known.
The quantitative assessment is a single-arm pre-post design without a comparison group, and analyses were still ongoing, so effects on distress cannot yet be established.
Evidence
- Peer-reviewedJMIR Research Protocols2026-10-21
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Truvace Impact Record TRV-2026-2235, v1: “A Machine Learning-Guided Lyric Analysis Peer Support Intervention (LAPSI) for Psychological Distress in South African Women: Protocol for an Exploratory Sequential Mixed Methods Study.” Truvace, 2026-10-24. /record/TRV-2026-2235 (accessed at citation time). sha256 95824696a1ec325c…
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