Financial Incentives for Physical Activity and Heart Health (FIPAHH): exploring the usability and feasibility of an eight-week financial incentive and physical activity mHealth intervention
Notice bibliographique
Résumé
Background: Hypertension is the leading modifiable risk factor for cardiovascular disease and mortality. Physical activity (PA) is critical for hypertension prevention, however scalable PA solutions are warranted. Previous studies have shown the potential of mHealth lifestyle interventions to be an effective and scalable strategy to improve PA outcomes, however, engagement and PA adherence remain a challenge. Financial incentives have the potential to overcome these challenges, by providing immediate behaviour reinforcement, but the effectiveness of a pay-per-minute (PPM) versus a modified social impact bond (SIB) financial incentive framework is unknown. Objective: The objective of Study 1 was to co-create and determine the usability of Healthy Hearts, an eight-week mHealth financial incentive hypertension education program. The objectives of Study 2 were to determine the feasibility (recruitment, engagement, and acceptability) and evaluate the preliminary efficacy of eight-week financial incentive PA interventions of PPM and SIB relative to control. Methods: In Studies 1 and 2, adults aged 40-65 who were not meeting the Canadian PA Guidelines were recruited online. Study 1: The IDEAS framework was used to guide the development of Healthy Hearts. The development process consisted of intervention planning, development, and usability testing. For usability testing, participants completed online questionnaires and I conducted semi-structured interviews to assess Healthy Hearts and gather feedback to further enhance the user experience. Descriptive analyses were used to evaluate the online questionnaire data and thematic analysis was conducted for semi-structured interviews analysis. Study 2: An eight-week feasibility study was conducted to explore the feasibility of a financial incentive PA intervention using the Healthy Hearts program. Study recruitment, retention and acceptability were evaluated following the intervention. Changes in PA outcomes (MVPA, daily steps), BP, and PA motivation were evaluated between PPM, SIB, and control groups using linear regressions. Results: Study 1: Six participants were recruited to gather feedback to enhance the content, layout, and design of the Healthy Hearts program to prepare the program to be employed in Study 2. Study 2: 55 participants were recruited and randomized to the PPM (n=19), SIB (n=18), or control (n=18) groups. Recruitment, engagement, and acceptability were successful, with a recruitment rate of 77%, a 65% engagement rate, and overall positive feedback on the acceptability of the program. Relative to control at four weeks, the PPM and SIB arms increased their MVPA with medium effect (η2p= 0.06 and η2p=0.08, respectively). At eight weeks, relative to the control arm, the SIB arm increased their MVPA with medium effect (η2p=0.07) and no effect was noted between the PPM and control arm. There were small effects in PA outcomes, BP, and PA motivation. Conclusion: Study 1: The necessity for co-creating physical activity interventions was emphasized in the process of creating Healthy Hearts. Through the creation and usability testing of this program, valuable feedback was collected and integrated from the participants, thus preparing the program for Study 2. Study 2: Per the high recruitment, engagement, and acceptability results, after minor changes are made, this study recommends a full-scale randomized control trial after appropriate power calculations.
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 | 0,024 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».