Implementation science and stigma reduction interventions in low- and middle-income countries: a systematic review
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Notice bibliographique
Résumé
BACKGROUND: Interventions to alleviate stigma are demonstrating effectiveness across a range of conditions, though few move beyond the pilot phase, especially in low- and middle-income countries (LMICs). Implementation science offers tools to study complex interventions, understand barriers to implementation, and generate evidence of affordability, scalability, and sustainability. Such evidence could be used to convince policy-makers and donors to invest in implementation. However, the utility of implementation research depends on its rigor and replicability. Our objectives were to systematically review implementation studies of health-related stigma reduction interventions in LMICs and critically assess the reporting of implementation outcomes and intervention descriptions. METHODS: PubMed, CINAHL, PsycINFO, and EMBASE were searched for evaluations of stigma reduction interventions in LMICs reporting at least one implementation outcome. Study- and intervention-level characteristics were abstracted. The quality of reporting of implementation outcomes was assessed using a five-item rubric, and the comprehensiveness of intervention description and specification was assessed using the 12-item Template for Intervention Description and Replication (TIDieR). RESULTS: A total of 35 eligible studies published between 2003 and 2017 were identified; of these, 20 (57%) used qualitative methods, 32 (91%) were type 1 hybrid effectiveness-implementation studies, and 29 (83%) were evaluations of once-off or pilot implementations. No studies adopted a formal theoretical framework for implementation research. Acceptability (20, 57%) and feasibility (14, 40%) were the most frequently reported implementation outcomes. The quality of reporting of implementation outcomes was low. The 35 studies evaluated 29 different interventions, of which 18 (62%) were implemented across sub-Saharan Africa, 20 (69%) focused on stigma related to HIV/AIDS, and 28 (97%) used information or education to reduce stigma. Intervention specification and description was uneven. CONCLUSION: Implementation science could support the dissemination of stigma reduction interventions in LMICs, though usage to date has been limited. Theoretical frameworks and validated measures have not been used, key implementation outcomes like cost and sustainability have rarely been assessed, and intervention processes have not been presented in detail. Adapted frameworks, new measures, and increased LMIC-based implementation research capacity could promote the rigor of future stigma implementation research, helping the field deliver on the promise of stigma reduction interventions worldwide.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,021 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle