Peace of mind: A quasi-experimental, mixed-method evaluation of a community-based mental health intervention for persons affected by Neglected Tropical Diseases
Bibliographic record
Abstract
Evidence consistently shows high levels of mental distress amongst populations affected by skin NTDs. Self-help groups are thought to be a key intervention strategy to support affected persons. However, to date, self-help interventions have largely been concerned with physical improvements as opposed to psychological outcomes. This paper provides an evaluation of the impact of the 'Peace of Mind' intervention in Kasai Province, DRC. Peace of Mind was a community-based, peer-led mental health intervention, combining lay counselling, mutual support, self-care, and income generation activities within a self-help group model to address health, psychosocial and economic impacts of skin-NTDs. This mixed-methods study used a quasi-experimental difference-in-difference approach. A survey measured levels of depression, anxiety, and stigma before and after intervention. To facilitate data matching, machine learning was used to predict (based on age, sex, health zone and disability status) which participants in the baseline would have attended the self-help groups. In addition, qualitative and participatory methods including photovoice, in-depth interviews and key informant interviews were completed to elicit the experiences of group members and health staff. Our findings show that after 6 months of intervention this holistic approach was effective at reducing levels of depression (PHQ-9 score reduction ranging on average from -3.5 to -6.7 points, p < .05) and anxiety (GAD-7 score reduction from -2.0 to -3.3 points, p < .05) in persons affected by skin NTDs. However, the prevalence of depression (64%) and anxiety (52%) remained high with suicidal thoughts reported by 35% of respondents at endline. Whilst we found no impact on stigma scores, qualitative data indicated improvements to self-esteem and ability to take part in community life. To our knowledge, this is the first study in the DRC to evaluate the impact of a community-based, peer-led intervention on mental health outcomes of persons affected by skin-NTDs. Holistic self-help groups have the potential to serve as a key component of integrated NTD/mental health service provision at community-level. However, this should be accompanied by the integration of stigma-reduction strategies, the strengthening of primary health care capacities, and the establishment of mental health services at secondary and tertiary care levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".