User Perception of a Smartphone App to Promote Physical Activity Through Active Transportation: Inductive Qualitative Content Analysis Within the Smart City Active Mobile Phone Intervention (SCAMPI) Study
Notice bibliographique
Résumé
BACKGROUND: Physical inactivity is globally recognized as a major risk factor for morbidity, particularly the incidence of noncommunicable diseases. Increasing physical activity (PA) is therefore a public health priority. Engaging in active transportation (AT) is a viable approach for promoting daily PA levels. Mobile health interventions enable the promotion of AT to a larger population. The Smart City Active Mobile Phone Intervention (SCAMPI) study was a randomized controlled trial designed to evaluate the ability of a behavior change program delivered via a smartphone app to motivate participants to increase their PA by engaging in AT. OBJECTIVE: This qualitative study aims to examine the acceptance and user experience of the app promoting AT that was used in the SCAMPI trial (the TRavelVU Plus app). METHODS: A total of 17 residents of Stockholm County (13 women; age range 25-61 years) who completed the 3-month app-based behavioral change program (delivered through the TRavelVU Plus app) in the SCAMPI randomized controlled trial during 2018 agreed to participate in a semistructured telephone-based interview. These participants were well representative of the whole intervention group (n=127) in terms of baseline characteristics such as age, sex, and area of residence. The interviews were audiorecorded, transcribed verbatim, and analyzed using an inductive qualitative content analysis. RESULTS: The content analysis revealed 2 themes and 4 subcategories. The first theme, "main motivators: monitoring and messages," highlighted that monitoring AT and being able to set weekly goals using the app were the primary motivators reported by study participants. The second theme, "acceptable but modifiable," reflects that the app was well accepted and effectively encouraged many participants to use more AT. Nevertheless, there were functions in the app that require modification. For example, while the semiautomated travel tracking feature was appreciated, participants found it time-consuming and unreliable at times. CONCLUSIONS: This study contributes novel insight into adults' experiences of using a mobile app to promote the use of AT. The results showed that the app was well accepted and that self-monitoring and goal setting were the main motivators to engage in more AT. The semiautomated tracking of AT was appreciated; however, it was also reported to be energy- and time-consuming when it failed to work. Thus, this feature should be improved going forward. TRIAL REGISTRATION: ClinicalTrials.gov NCT03086837; https://clinicaltrials.gov/ct2/show/NCT03086837. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12889-018-5658-4.
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 | 0,011 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».