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Record W4411583153 · doi:10.17161/gjcpp.v16i1.21679

A qualitative insight on stereotypes and prejudices toward mental disorders in Burkina Faso: the interaction of shame and fear as underlying influences of stigma

2025· article· en· W4411583153 on OpenAlexaff
Émilie Pigeon-Gagné, Thomas Delaware-Saias, Maurice Yaogo, Ghayda Hassan, Djeneba Ouedraoogo

Bibliographic record

VenueGlobal Journal of Community Psychology Practice · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsUniversité TÉLUQ
Fundersnot available
KeywordsShameStigma (botany)PsychologySocial psychologyQualitative researchSociologySocial sciencePsychiatry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.225
GPT teacher head0.609
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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