Lessons from a theory of change-driven evaluation of a global mental health funding portfolio
Notice bibliographique
Résumé
BACKGROUND: Given the underinvestment in global mental health to-date, it is important to consider how best to maximize the impact of existing investments. Theory of Change (ToC) is increasingly attracting the interest of funders seeking to evaluate their own impact. This is one of four papers investigating Grand Challenges Canada's (GCC's) first global mental health research funding portfolio (2012-2016) using a ToC-driven approach. METHODS: A portfolio-level ToC map was developed through a collaborative process involving GCC grantees and other key stakeholders. Proposed ToC indicators were harmonised with GCC's pre-existing Results-based Management and Accountability Framework to produce a "Core Metrics Framework" of 23 indicators linked to 17 outcomes of the ToC map. For each indicator relevant to their project, the grantee was asked to set a target prior to the start of implementation, then report results at six-month intervals. We used the latest available dataset from all 56 projects in GCC's global mental health funding portfolio to produce a descriptive analysis of projects' characteristics and outcomes related to delivery. RESULTS: 12,999 people were trained to provide services, the majority of whom were lay or other non-specialist health workers. Most projects exceeded their training targets for capacity-building, except for those training lay health workers. Of the 321,933 people screened by GCC-funded projects, 162,915 received treatment. Most projects focused on more than one disorder and exceeded all their targets for screening, diagnosis and treatment. Fewer people than intended were screened for common mental disorders and epilepsy (60% and 54%, respectively), but many more were diagnosed and treated than originally proposed (148% and 174%, respectively). In contrast, the three projects that focused on perinatal depression exceeded screening and diagnosis targets, but only treated 43% of their intended target. CONCLUSIONS: Under- or over-achievement of targets may reflect operational challenges such as high staff turnover, or challenges in setting appropriate targets, for example due to insufficient epidemiological evidence. Differences in delivery outcomes when disaggregated by disorder suggest that these challenges are not universal. We caution implementers, funders and evaluators from taking a one-size-fits all approach and make several recommendations for how to facilitate more in-depth, multi-method evaluation of impact using portfolio-level ToC.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».