Let them eat (birthday) cake: reframing healthy eating in healthcare organizations
Bibliographic record
Abstract
Healthy eating is influenced by a myriad factors ranging from individual to societal. Healthcare organizations have recently adopted healthy eating policies to improve food environments; however, how such policies shape practice is still unknown. This qualitative study explores perspectives on continuous quality improvement (CQI) among healthcare staff and managers working in hospital foodservices post-implementation of a healthy eating policy aimed at improving food environments. We conducted semi-structured interviews with 12 foodservices staff at Nova Scotia Health. Participants varied in role (administrative, point-of-sale) and location (rural/urban). We analyzed findings using directed content analysis. Participants' approach to quality revealed a range of definitions of healthy eating, from health promotion efforts directed towards individual behavior change management to a broader emphasis on supportive food environments. This research also highlighted the complexity of the healthcare food environment in which health promotion was being implemented, a 'setting' as per the 'settings approach' to health promotion, but also revealing a 'setting within a setting': food environments within healthcare environments. These nested environments are alternatively more business or healthcare service-centric, within the larger healthcare environment. Healthcare practitioners' views on effective implementation of the policy also spanned many scales of healthy eating, informed by concepts within their core healthcare practice (dietetics: nutrients), the organization (historical nutrition contexts) and broader food culture (food trends and choice). This study has demonstrated that CQI for a healthier food environment within healthcare needs a broader focus to advance benchmarks for health promotion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".