A Novel Approach to Assess Weekly Self-efficacy for Meeting Personalized Physical Activity Goals Via a Cellphone: 12-Week Longitudinal Study
Notice bibliographique
Résumé
BACKGROUND: Despite the health benefits of engaging in regular physical activity (PA), the majority of American adults do not meet the PA guidelines for aerobic and muscle-strengthening activities. Self-efficacy, the belief that one can execute specific actions, has been suggested to be a strong determinant of PA behaviors. With the increasing availability of digital technologies, collecting longitudinal real-time self-efficacy and PA data has become feasible. However, evidence in longitudinal real-time assessment of self-efficacy in relation to objectively measured PA is scarce. OBJECTIVE: This study aimed to examine a novel approach to measure individuals' real-time weekly self-efficacy in response to their personalized PA goals and performance over the 12-week intervention period in community-dwelling women who were not meeting PA guidelines. METHODS: In this secondary data analysis, 140 women who received a 12-week PA intervention were asked to report their real-time weekly self-efficacy via a study mobile app. PA (daily step counts) was measured by an accelerometer every day for 12 weeks. Participants rated their self-efficacy on meeting PA goals (ranging from "not confident" to "very confident") at the end of each week via a mobile app. We used a logistic mixed model to examine the association between weekly self-efficacy and weekly step goal success, controlling for age, BMI, self-reported White race, having a college education or higher, being married, and being employed. RESULTS: The mean age was 52.7 (SD 11.5, range 25-68) years. Descriptive analyses showed the dynamics of real-time weekly self-efficacy on meeting PA goals and weekly step goal success. The majority (74.4%) of participants reported being confident in the first week, whereas less than half of them (46.4%) reported confidence in the final week of the intervention. Participants who met weekly step goals were 4.41 times more likely to be confident about achieving the following week's step goals than those who did not meet weekly step goals (adjusted odds ratio 4.41; 95% CI 2.59-7.50; P<.001). Additional analysis revealed that participants who were confident about meeting the following week's step goals were 2.07 times more likely to meet their weekly step goals in the following week (adjusted odds ratio 2.07; 95% CI 1.16-3.70; P=.01). The significant bidirectional association between real-time self-efficacy and weekly step goal success was confirmed in a series of sensitivity analyses. CONCLUSIONS: This study demonstrates the potential utility of a novel approach to examine self-efficacy in real time for analysis of self-efficacy in conjunction with objectively measured PA. Discovering the dynamic patterns and changes in weekly self-efficacy on meeting PA goals may aid in designing a personalized PA intervention. Evaluation of this novel approach in an RCT is warranted.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».