Opening Minds: The Mental Health Commission of Canada’s Anti-Stigma Initiative: Key Ingredients of Anti-Stigma Programs for Health Care Providers: A Data Synthesis of Evaluative Studies
Notice bibliographique
Résumé
As part of its OM Anti-Stigma Initiative, the MHCC partnered with organizations and investigators conducting anti-stigma interventions targeting various health care provider groups in Canada, with the purpose of evaluating program outcomes.1 Using existing evidence on the value of social contact2–5 as an initial point of departure, OM partnered with programs using some form of social contact or contact-based education in the delivery of their program. Typically, social contact-based approaches emphasize the inclusion of planned exchanges between people with lived experience of mental illness and the target audience as a part of the program curriculum.5 In many cases, target audiences hear personal stories from, and (or) interact with, people who have recovered or are successfully managing a mental illness. While all programs evaluated by OM included some form of social contact, the extent and nature of the contact varied from program to program, as did many other characteristics, including program length, educational emphasis, program context and delivery features, and target audience (for example, practicing professionals, compared with students). Online eTable 1 contains a description of the various partner programs, their targeted audiences, and their main program elements. To enhance the comparability of the various studies, OM developed and adopted a common outcome scale, the OMS-HC,6,7 and had data-sharing arrangements with its partners. Two RCTs were first conducted to confirm the general effectiveness of the contact-based approach. Both trials returned positive results.8,9 Subsequently, with efficacy confirmed, the goal became the identification of characteristics associated with maximal effectiveness. Most of the evaluative studies used a before-and-after study comparison to evaluate effectiveness, and data collected in this way became the main source of data for assessing program characteristics or key ingredients associated with the best outcomes. With 22 total pre–post data sets from a diverse set of studies (but all using the OMS-HC), it became necessary to identify a systematic approach to quantifying the outcomes associated with each potential key ingredient. Analysis of individual study results had not identified individual characteristics (such as age, sex, or whether a person had a friend or close relative with a mental illness) as being significant determinants of outcome.1,8,9 For this reason, we chose a strategy based on contrasting study-level characteristics using methods commonly employed in meta-analysis, including meta-regression. These techniques can accommodate heterogeneity across studies and provide a method of weighting the contributions of larger and smaller studies when generating pooled effect estimates. Implementation of the overall strategy required a multi-phased, mixed-methods approach. First, a qualitative study was required to identify potentially important program characteristics and to accurately classify each intervention according to those characteristics. Next, the aforementioned quantitative strategies were used to evaluate the impact of these characteristics on outcomes. In our paper, we report the comparative evaluation of anti-stigma interventions affiliated with OM, including the elements of these programs found to be associated with the most favourable outcomes. Clinical Implications Anti-stigma interventions incorporating social contact are effective in a broad range of health care providers and trainees. Programs that include a recovery emphasis, personal testimony from a trained speaker who has lived experience of mental illness, that employ multiple forms of social contact, that teach skills involving what to say and what to do, that employ myth-busting, and that use an enthusiastic facilitator perform significantly better than programs that include only some of these ingredients. A recovery emphasis and having multiple forms of social contact are especially critical for maximizing outcomes. Limitations The studies evaluated here consisted of before-and-after comparisons and were usually uncontrolled. Considerable heterogeneity was observed even after modelling for intervention ingredients. Other important determinants of outcomes remain to be identified. Most of these evaluations were short-term, leaving unanswered questions about the long-term effects of anti-stigma interventions.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,087 | 0,183 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,005 |
| Bibliométrie | 0,012 | 0,017 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,007 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».