Enrichment of the Canadian Partnership for Tomorrow’s Health Study: Protocol for Administering Multiple Online Dietary and Movement Behavior Assessment Tools in a Longitudinal Cohort Study
Notice bibliographique
Résumé
BACKGROUND: Suboptimal diet quality and physical inactivity are key risk factors for chronic disease and disability in Canada. However, the lack of high-quality population-level data hinders the development of evidence-based strategies to support improvements in diet quality, movement behaviors (physical inactivity, activity, and sleep), and health. The lack of data is also a barrier to developing capacity in diet and physical activity assessment and epidemiology in Canada. OBJECTIVE: This protocol describes the development of the largest known repository of dietary intake and movement behavior data in Canada by drawing upon an existing longitudinal cohort study, the Canadian Partnership for Tomorrow's Health (CanPath). In the short-term, the data will be used to examine associations between system factors (eg, retail food environments) and dietary intake. In the longer-term, data will be available to pursue a range of research questions, including longitudinal associations between diet, movement behavior, and health outcomes. METHODS: Participants in CanPath (>330,000 adults) who can complete online questionnaires are eligible and will be asked to complete a baseline web-based questionnaire including questions on demographic characteristics and screeners capturing dietary intake and movement behaviors. Subsequently, participants will be invited to complete an online 24-hour dietary recall using the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24-Canada-2018) and an online 24-hour activity recall using Activities Completed Over Time in 24 Hours (ACT24). Repeat recalls will be administered 1-2 weeks later. A subset of participants will be invited to complete 2 additional ASA24-Canada-2018 and Activities Completed Over Time in 24 Hours recalls 6 months later. One year after baseline, participants will be invited to complete past-year diet and movement behavior questionnaires. In Québec, dietary intake and movement behavior data are from 3000 CanPath participants enrolled in the NutriQuébec study. Participant addresses will be linked to geospatial data on the food, built, and social environment. RESULTS: Data collection began in 2025. As of manuscript acceptance (November 4, 2025), 3171 participants had been recruited. Data processing and cleaning will be completed in 2027, and analyses will occur in 2028. It is anticipated that dietary intake and movement behavior data will be available for up to 100,000 adults. CONCLUSIONS: This protocol outlines the collection of detailed data on dietary intake and movement behavior in a large cohort spanning all provinces in Canada. In addition to allowing examination of a range of research questions related to diet, movement behavior, and health, the combination of assessment tools will support methodological research, including expanding analytical strategies to mitigate the effects of error in dietary and movement behavior data. This effort will also build capacity in the collection, processing, and harmonization of dietary and movement behavior data among cohorts and provide a training ground for emerging researchers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/71680.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,032 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,003 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,011 | 0,002 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,055 | 0,010 |
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 ».