Development of a ParticipACTION App–Based Intervention for Improving Postsecondary Students’ 24-Hour Movement Guideline Behaviors: Protocol for the Application of Intervention Mapping
Notice bibliographique
Résumé
BACKGROUND: The Canadian 24-Hour Movement Guidelines for adults provide specific recommendations for levels of physical activity, sedentary behavior, and sleep (ie, the movement behaviors) required for optimal health. Performance of the movement behaviors is associated with improved mental well-being. However, most postsecondary students do not meet the movement behavior recommendations within the Canadian 24-Hour Movement Guidelines and experience increased stress and declining well-being, suggesting the need for an intervention targeting students' movement behaviors. OBJECTIVE: We aimed to develop and implement a theory-informed intervention intended to improve the movement behaviors and mental well-being of first-year postsecondary students. METHODS: The Intervention Mapping protocol was applied in the development and implementation of the intervention. Intervention Mapping entailed performing a needs assessment, determining the intervention outcomes, selecting theory- and evidence-based change methods and applications, preparing and producing intervention plans and materials, developing the implementation plan, and finally developing an evaluation plan. The Theoretical Domains Framework and the Behavior Change Wheel were also used in conjunction with the Intervention Mapping protocol to ensure a solid theoretical basis for the intervention. This protocol led to the development and implementation of a 6-week, theory-informed ParticipACTION app-based intervention aimed at helping first-year postsecondary students improve their movement behaviors and mental well-being. The developed app content provided students with information on each of the movement behaviors and behavioral strategies (ie, goal setting, action planning, monitoring, and coping planning). The use of Intervention Mapping allowed for the continuous involvement of various multidisciplinary partners and end users, ensuring that the intervention design and implementation was appropriate for the target audience. The feasibility, acceptability, and potential impact of the intervention will be examined in a subsequent proof-of-concept study at 2 Canadian university campuses. RESULTS: Participant recruitment occurred during September 2021, and the intervention was conducted from October to December 2021. The deadline for completion of the postintervention questionnaire by participants was mid-December 2021. The analysis of data examining the feasibility, acceptability, and potential impact of the intervention began in January 2022, with the publication of the proof-of-concept evaluation expected in 2023. CONCLUSIONS: Intervention Mapping with the Theoretical Domains Framework and Behavior Change Wheel was a useful approach to combine evidence and theoretical concepts to guide the design and implementation of a ParticipACTION app-based intervention targeting postsecondary students' movement behaviors and mental well-being. This process may serve as an example for other researchers developing multiple behavior change app-based interventions. Should the forthcoming evaluation demonstrate the intervention's acceptability, feasibility, and potential impact, the intervention may provide a scalable method of improving postsecondary students' movement behaviors and mental well-being. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/39977.
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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 | 0,024 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,059 | 0,009 |
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 ».