Proceedings of the 4th Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2017: implementation mechanisms: what makes implementation work and why? part 2
Notice bibliographique
Résumé
BackgroundIn 2016, the Department for Family and Community Services in New South Wales, Australia selected Multisystemic Therapy -Emerging Adults (MST-EA) as a potentially suitable intervention for clients in a leaving care program with high and complex support needs emerging from challenging behaviour, mental health problems, involvement with the criminal justice system, intellectual disabilities, and alcohol and other drug use.MST-EA was originally developed in the U.S. for young people aged 17 -21 with a serious mental health condition and involvement in the justice system [1].The program is an adaptation of standard MST [2] and had not been tested with a population with intellectual disabilities before.In the Australian MST-EA trial, its potential to be effective for people aged 16 -26 with a mild to moderate disability and at high risk for poor outcomes was explored.The first year of MST-EA implementation took place in a complex policy environment that was dominated by one of the most comprehensive social reforms in Australiathe introduction of the National Disability Insurance Scheme (NDIS).Its national roll-out began in July 2016.The NDIS follows a market-style system where government funding will no longer go directly to disability service providers, but instead to the client, who can choose the providers they want.This reform created substantial barriers to the implementation of MST-EA in New South Wales. Materials and MethodsBased on the Consolidated Framework for Implementation Research [3], a semi-structured questionnaire was developed for use with 15 key stakeholders to the MST-EA Implementation.It was administered with clinicians, managers, partner organisations, consultants and program developers to explore the perceived barriers that contributed most substantially to the lack of success in adapting, transferring and implementing this evidence-based program to the Australian context. ResultsData are currently being collected.Data collection will finish in May, and data analysis commence in June.Data will undergo thematic analysis guided by the Consolidated Framework for Implementation Research (CFIR).Of particular interest will be to understand in what way respondents suggest addressing the challenges that were perceived as substantial barriers to MST-EA adaptation, transport and implementation. ConclusionsToo few examples of challenged implementation projects are being documented, analysed and utilised for learning.Our understanding of complex policy contexts and how to manage them during implementation requires further development.The Australian MST-EA trial mirrors an implementation experience that is shared by many other projects initiated by government or non-government organisations and providers.It should be used to inform future implementation practice and decision-making.
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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 | 0,017 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,005 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,005 |
| Science ouverte | 0,001 | 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 ».