Implications for Training on Smartphone Medication Reminder App Use by Adults With Chronic Conditions: Pilot Study Applying the Technology Acceptance Model
Notice bibliographique
Résumé
BACKGROUND: The majority of middle-aged to older patients with chronic conditions report forgetting to take medications as prescribed. The promotion of patients' smartphone medication reminder app (SMRA) use shows promise as a feasible and cost-effective way to support their medication adherence. Providing training on SMRA use, guided by the technology acceptance model (TAM), could be a promising intervention to promote patients' app use. OBJECTIVE: The aim of this pilot study was to (1) assess the feasibility of an SMRA training session designed to increase patients' intention to use the app through targeting perceived usefulness of app, perceived ease of app use, and positive subjective norm regarding app use and (2) understand the ways to improve the design and implementation of the training session in a hospital setting. METHODS: A two-group design was employed. A total of 11 patients older than 40 years (median=58, SD=9.55) and taking 3 or more prescribed medications took part in the study on one of two different dates as participants in either the training group (n=5) or nontraining group (n=6). The training group received an approximately 2-hour intervention training session designed to target TAM variables regarding one popular SMRA, the Medisafe app. The nontraining group received an approximately 2-hour control training session where the participants individually explored Medisafe app features. Each training session was concluded with a one-time survey and a one-time focus group. RESULTS: Mann-Whitney U tests revealed that the level of perceived ease of use (P=.13) and the level of intention to use an SMRA (P=.33) were higher in the training group (median=7.00, median=6.67, respectively) than in the nontraining group (median=6.25, median=5.83). However, the level of perceived usefulness (U=4.50, Z=-1.99, P=.05) and the level of positive subjective norm (P=.25) were lower in the training group (median=6.50, median=4.29) than in the nontraining group (median=6.92, median=4.50). Focus groups revealed the following participants' perceptions of SMRA use in the real-world setting that the intervention training session would need to emphasize in targeting perceived usefulness and positive subjective norm: (1) the participants would find an SMRA to be useful if they thought the app could help address specific struggles in medication adherence in their lives and (2) the participants think that their family members (or health care providers) might view positively the participants' SMRA use in primary care settings (or during routine medical checkups). CONCLUSIONS: Intervention training session, guided by TAM, appeared feasible in targeting patients' perceived ease of use and, thereby, increasing intention to use an SMRA. Emphasizing the real-world utility of SMRA, the training session could better target patients' perceived usefulness and positive subjective norm that are also important in increasing their intention to use the app.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,014 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».