Promoting Dairy Consumption Among Families: Development and User Experience Study of a Web-Based Nutrition Intervention
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».