Implementation of a food retail intervention to reduce purchase of unhealthy food and beverages in remote Australia: mixed-method evaluation using the consolidated framework for implementation research
Notice bibliographique
Résumé
BACKGROUND: Adoption of health-enabling food retail interventions in food retail will require effective implementation strategies. To inform this, we applied an implementation framework to a novel real-world food retail intervention, the Healthy Stores 2020 strategy, to identify factors salient to intervention implementation from the perspective of the food retailer. METHODS: A convergent mixed-method design was used and data were interpreted using the Consolidated Framework for Implementation Research (CFIR). The study was conducted alongside a randomised controlled trial in partnership with the Arnhem Land Progress Aboriginal Corporation (ALPA). Adherence data were collected for the 20 consenting Healthy Stores 2020 study stores (ten intervention /ten control) in 19 communities in remote Northern Australia using photographic material and an adherence checklist. Retailer implementation experience data were collected through interviews with the primary Store Manager for each of the ten intervention stores at baseline, mid- and end-strategy. Deductive thematic analysis of interview data was conducted and informed by the CFIR. Intervention adherence scores derived for each store assisted interview data interpretation. RESULTS: Healthy Stores 2020 strategy was, for the most part, adhered to. Analysis of the 30 interviews revealed that implementation climate of the ALPA organisation, its readiness for implementation including a strong sense of social purpose, and the networks and communication between the Store Managers and other parts of ALPA, were CFIR inner and outer domains most frequently referred to as positive to strategy implementation. Store Managers were a 'make-or-break' touchstone of implementation success. The co-designed intervention and strategy characteristics and its perceived cost-benefit, combined with the inner and outer setting factors, galvanised the individual characteristics of Store Managers (e.g., optimism, adaptability and retail competency) to champion implementation. Where there was less perceived cost-benefit, Store Managers seemed less enthusiastic for the strategy. CONCLUSIONS: Factors critical to implementation (a strong sense of social purpose; structures and processes within and external to the food retail organisation and their alignment with intervention characteristics (low complexity, cost advantage); and Store Manager characteristics) can inform the design of implementation strategies for the adoption of this health-enabling food retail initiative in the remote setting. This research can help inform a shift in research focus to identify, develop and test implementation strategies for the wide adoption of health-enabling food retail initiatives into practice. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN 12,618,001,588,280.
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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 | 0,006 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,000 | 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 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 ».