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A Qualitative Evaluation of the Ontario School Food and Beverage Policy using an Implementation Framework: Lessons Learned

2016· article· en· W2490987418 on OpenAlexaffabout
Renata Valaitis, Rhona M. Hanning, Taryn Orava

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsQualitative researchBusinessProcess managementPolitical scienceEnvironmental planningSociologyEnvironmental scienceSocial science

Abstract

fetched live from OpenAlex

Introduction With obesity rates rising in Canada, schools have been identified as an ideal setting for health promotion interventions. In 2011, Ontario's School Food and Beverage Policy (P/PM 150) was mandated by the Ministry of Education for all schools in the province to try and improve the diets and food behaviours of youth. Policies have been introduced in a number of jurisdictions internationally, but what is not known are the best ways to implement them. Purpose The purpose of this research was to i) describe the school food context in one Ontario Region, ii) examine, from the perspectives of multiple stakeholders, the process of P/PM 150 implementation including perceived challenges/successes with policy implementation and its impacts; iii) analyze the results in relation to the constructs of Damschroder's Consolidated Framework for Implementation Research (CFIR). Methods A qualitative interpretive study was conducted to capture perceptions of stakeholders (students, parents, school stakeholders and food service providers) in one large, diverse region in Ontario, Canada. This qualitative study consisted of 5 food service provider interviews, 15 school stakeholder interviews, 5 elementary school parent focus groups, and 11 student focus groups. Two surveys were conducted that provided responses to open‐ended questions from 46 secondary school parent surveys, and 1,251 Grade 6–10 students. Focus group and open ended survey data were analyzed using NVivo 10 qualitative analysis software. Results Results reported on stakeholder perceptions of: i) school food, ii) school food behaviours, iii) factors that influence school food behaviours (including individual, social, macro‐level factors), iv) and the multiple environments (school, home, community) that influence food behaviours. Policy‐specific results provided stakeholders’ knowledge and opinions of P/PM 150, the process of policy implementation, factors influencing policy implementation (including successes and challenges) as well as the perceived outcomes and impacts of the policy on school food environments and student food behaviours. All results were analyzed using Damschroder's CFIR to better understand how the domains and constructs described in the framework related to school food policy implementation in this Region. Factors influencing policy implementation will be presented. These closely aligned with the constructs described in CFIR. Two additional constructs were identified that were not reflected in the framework: ‘implementation climate outside the school’ and ‘adaptability of the inner setting’. Study results indicated that these were significant factors influencing implementation in Peel Region schools. Therefore, these factors should be a considered in further revisions of the framework, in particular where it is being used to support policy implementation. Conclusion Implementation of a new school food policy, P/PM 150, was found to be complex with many factors influencing its successful uptake by school stakeholders. While participants discussed many challenges and negative outcomes and impacts resulting from P/PM 150, positive impacts on school food and food behaviours were also reported. Those planning to implement school food policies in the future need to consider comprehensive approaches that address potential influencing factors and environments outside of the school that impact student food behaviours. Support or Funding Information Funding: CIHR‐Danone Institute Doctoral Research Award & Peel Public Health

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.784

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0170.010
Scholarly communication0.0040.002
Open science0.0040.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.189
GPT teacher head0.470
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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