Establishing partnerships with people with lived experience of mental illness for stigma reduction in low- and middle-income settings
Bibliographic record
Abstract
Social contact refers to the facilitation of connection and interactions between people with and without mental health conditions. It can be achieved, for example, through people sharing their lived experience of mental health conditions, which is an effective strategy for stigma reduction. Meaningful involvement of people with lived experience (PWLE) in leading and co-leading anti-stigma interventions can/may promote autonomy and resilience. Our paper aimed to explore how PWLE have been involved in research and anti-stigma interventions to improve effective means of involving PWLE in stigma reduction activities in LMICs. A qualitative collective case study design was adopted. Case studies from four LMICs (China, Ethiopia, India and Nepal) are summarized, briefly reflecting on the background of the work, alongside anticipated and experienced challenges, strategies to overcome these, and recommendations for future work. We found that the involvement of PWLEs in stigma reduction is commonly a new concept in LMIC. Experienced and anticipated challenges were similar, such as identifying suitable persons to engage in the work and sustaining their involvement. Such an approach can be difficult because PWLE might be apprehensive about the negative consequences of disclosure. In many case studies, we found that long-standing professional connectedness, continued encouragement, information sharing, debriefing and support helped the participants' involvement. We recommend that confidentiality of the individual, cultural norms and family concerns be prioritized and respected during the implementation. Taking into account socio-cultural contextual factors, it is possible to directly involve PWLEs in social contact-based anti-stigma interventions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".