Promoting Dairy Consumption Among Families: Development and User Experience Study of a Web-Based Nutrition Intervention
Bibliographic record
Abstract
Background: Insufficient adherence to dietary guidelines underscores the need for effective interventions promoting healthy eating, including dairy consumption, among Canadian families. Research suggests that web-based interventions grounded in user research and behavior change theories can effectively support dietary improvements. However, few theory-driven digital interventions specifically target dairy consumption in families. Objective: This study aims to describe the development of a web-based nutrition intervention, Dairyathlon, designed to promote dairy consumption among families using the IDEAS (Ideate, Design, Assess, and Share) framework. In addition, it evaluates user experience (UX) with the web-based platform. Methods: Following the IDEAS framework, family perspectives and beliefs regarding dairy consumption were explored through ethnographic research and interviews. Behavior change techniques, based on the theory of planned behavior, were integrated to enhance attitudes and perceived behavioral control toward dairy intake. These techniques underwent iterative design, prototype testing, and refinement. UX was assessed with the AttrakDiff questionnaire, comparing families using Dairyathlon to those using the Canadian Food Guide (CFG). Children and parents completed the questionnaire after the presentation of the platform (PRE) and following 8 weeks of use (POST). AttrakDiff evaluates pragmatic quality (PQ), hedonic stimulation (HSQ), hedonic identity (HIQ), and attractiveness dimension (ATT) on a scale from -3 to +3, with >1 considered optimal, 0-1 acceptable, and < 0 suboptimal. Results: Between April 2019 and August 2020, Dairyathlon was developed to enhance families' attitudes and perceived control over dairy consumption, adhering to the IDEAS framework. Users' experience assessments were conducted among 29 families and showed significantly higher scores for Dairyathlon compared to the reference platform (CFG) at both pre- and postassessments (P<.001). Although both platforms were initially rated as optimal, UX ratings decreased after use: PRE (1.7, SD 0.6) to POST (1.4, SD 0.8) in the Dairyathlon group (mean difference of 0.4, 95% CI 0.2-0.7; P=.002), and (1.4, SD 0.6) to (0.9, SD 0.6) in the CFG group (mean difference = 0.6, 95% CI 0.5-0.6; P<.001). After using Dairyathlon, children (n=45) rated all UX dimensions as optimal, with scores of PQ (1.4, SD 1.0), HSQ (1.6, SD 1.0), HIQ (1.4, SD 1.1), and ATT (1.7, SD 0.9). Parents (n=50) also rated most dimensions as optimal, with scores of 1.2 (SD 1.0) for PQ, 1.4 (SD 0.8) for HIQ, and 1.6 (SD 0.8) for ATT. However, the HSQ dimension received a slightly lower rating of 0.9 (SD 0.8), indicating a need for improvement in adult stimulation. Conclusions: This study highlights the effectiveness of the IDEAS framework in developing a web-based intervention to promote dairy consumption. The Dairyathlon platform's UX was rated as optimal, especially for visual attractiveness, though the stimulation dimension requires improvement for adults. Future research will evaluate its impact on dairy consumption, diet quality, and family health status.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".