Impact of Platform Design and Usability on Adherence and Retention: Randomized Web- and Mobile-Based Longitudinal Study
Notice bibliographique
Résumé
Background: Low retention and adherence increase clinical trial costs and timelines. Burdens associated with participating in a clinical trial contribute to early study termination. Electronic patient-reported outcome (ePRO) tools reduce participant burden by allowing remote participation, and facilitate communication between researchers and participants. The Datacubed Health (DCH) mobile app is unique among ePRO platforms in its application of behavioral science principles (reward, motivation, identity, etc) in clinical trials to promote engagement, adherence, and retention. Objective: We evaluated the impact of platform design and usability on adherence and retention with a longitudinal study involving repeated patient-facing study instruments. We expected participants assigned to complete instruments in the DCH mobile app to stay in this study longer (increased retention) and complete more surveys while in this study (increased adherence) due to the enhanced motivational elements unique to the participant experience in the DCH app group, and this group's overall lower burden of participation. Methods: A total of 284 adult participants completed 24 weekly surveys via 1 of 4 modalities (DCH app vs DCH website vs third-party website vs paper) in a web-based and mobile longitudinal study. Participants were recruited from open access websites (eg, Craigslist or Facebook [Meta]), and a closed web-based user group. All participation occurred remotely. Study staff deliberately limited communications with participants to directly assess the main effects of survey administration modality; enrollment and study administration were largely automated. Participants assigned to the DCH app group experienced behavioral science-driven motivational elements related to reward and identity formation throughout their study journey. There was no homolog to this feature in any other tested platform. Participants assigned to the DCH app group accessed study measures using passcodes or smartphone biometrics (face or touch ID). Participants in the DCH website group logged into a website using a username and password. Participants in the third-party website group accessed web-based surveys via personalized emailed links with no need for password authentication. Paper arm participants received paper surveys in the mail. Results: Mode of survey administration (DCH app vs DCH website vs third-party website vs paper) predicted study retention (F9,255=4.22, P<.001) and adherence (F9,162=5.5, P<.001). The DCH app group had greater retention than the paper arm (t=-3.80, P<.001), and comparable retention to the DCH website group. The DCH app group had greater adherence than all other arms (DCH web: t=-2.42, P=.02; third-party web: t=-3.56, P<.001; and paper arm: t=-4.53, P<.001). Conclusions: Using an ePRO platform in a longitudinal study increased retention and adherence in comparison to paper instruments. Incorporating behavioral science design in an ePRO platform resulted in further increase in adherence in a longitudinal study.
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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 | 0,009 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».