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Record W4321217273 · doi:10.1186/s12966-022-01377-y

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

2023· article· en· W4321217273 on OpenAlexafffund
Julie Brimblecombe, Bethany Miles, Emma Chappell, Khia De Silva, Megan Ferguson, Catherine L. Mah, Anthony Gunther, Thomas P. Wycherley, Anna Peeters, Leia Minaker, Emma McMahon

Bibliographic record

VenueInternational Journal of Behavioral Nutrition and Physical Activity · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of WaterlooUniversity of TorontoDalhousie University
FundersMedical Research CouncilNational Health and Medical Research CouncilCanada Research Chairs
KeywordsImplementation researchThematic analysisPsychological interventionIntervention (counseling)Qualitative researchGeneral partnershipQualitative propertyStrategy implementationChecklistMedicineMarketingPsychologyBusinessNursingComputer scienceSociology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.772
GPT teacher head0.752
Teacher spread0.020 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations27
Published2023
Admission routes2
Has abstractyes

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