Effect of a relative pricing intervention and active merchandising on snack purchases: interrupted time series analysis of a hospital retailer-led strategy
Bibliographic record
Abstract
Abstract Background Pricing policies have been shown to be an effective lever for promoting healthier dietary choices in consumer food environments. It is not yet well understood how pricing can be used to encourage healthier substitute purchases. The aim of the study was to assess the effect of a retailer-led relative pricing intervention on weekly purchases of targeted snack foods and beverages. Methods This was an ecological analysis in a real-world large tertiary hospital consumer food environment setting in urban Canada, comprised of four retail outlets: two large cafeterias, one smaller cafeteria, and one grab-and-go café. An interrupted time series analysis was designed to evaluate the effect of Snacking Made Simple, a retailer-led relative pricing intervention applied to 10 popular snack foods and beverages (n = 87 weeks, 66 weeks baseline and 21 weeks intervention, April 2018 to December 2019), on weekly purchase differences between healthier and less healthy targeted items, adjusted for weekly sales volume. Five healthier items were price discounted, alongside a price increase for five less healthy items. The intervention was actively merchandised in keeping with behaviour change theory. Results Weekly purchases of targeted snacks became healthier during the intervention period (β = 21.41, p = 0.0024). This followed a baseline period during which weekly purchases of less healthy targeted snacks had outpaced over time those of healthier targeted snacks (β = -11.02, p = 3.68E-14). We estimated that, all else being equal, a hypothetical 9.43 additional weeks of the intervention would be required to transition to net-healthier targeted snack purchases in this environment. The effects of the intervention varied by retail outlet, and the outcome appears driven by specific food items; further, examining merchandising implementation, we posited whether direct versus indirect substitution may have affected purchasing outcomes. Conclusions Relative pricing may be a promising way to incentivize healthier substitute purchasing in the consumer food environment. Added attention to merchandising strategy as well as value-add factors within food categories and their effects on price salience may be an important factor in effective intervention design.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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 source (direct Gemma or distilled Codex), 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".