A qualitative insight on stereotypes and prejudices toward mental disorders in Burkina Faso: the interaction of shame and fear as underlying influences of stigma
Bibliographic record
Abstract
Background: Worldwide, stigma is recognized as a barrier limiting access to psychiatric care. The scope of the stigma varies across cultural contexts and contributes to the social inequalities in health observed in many low- and middle-income countries. Aim and methods: In this paper, we explore the way mental disorders are stigmatized in Bobo-Dioulasso (Burkina Faso). We conducted 7 focus groups and 25 individual interviews with patients, family members, caregivers, and key informants. Interviews focused on stereotypes and attitudes toward individuals identified with mental disorders. Results: A set of stereotypes is socially conveyed about people with mental disorders. The perceptions that these individuals are fragile, useless, dangerous, marginal, and adopt strange behaviors are common. These stereotypes could be related to emotional reactions, such as sadness, compassion, indifference, fear, disgust, and shame that justify, in some cases, discrimination and unequal treatments. Discussion: This study suggests that affective reactions are crucial to understand stigma in Burkina Faso. The notion of shame seems to be rooted in a set of cultural norms and values, and fear seems to be related to structural stigma. Our results offer some insights for future anti-stigma programs in a context where resources are limited and where cultural characteristics must be considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".