Download Your Doctor: Implementation of a Digitally Mediated Personal Physician Presence to Enhance Patient Engagement With a Health-Promoting Internet Application
Notice bibliographique
Résumé
BACKGROUND: Brief interventions delivered in primary health care are effective in reducing excessive drinking; online behavior-changing technique interventions may be helpful. Physicians may actively encourage the use of such interventions by helping patients access selected websites (a process known as "facilitated access"). Although the therapeutic working alliance plays a significant role in the achievement of positive outcomes in face-to-face psychotherapy and its development has been shown to be feasible online, little research has been done on its impact on brief interventions. Strengthening patients' perception of their physician's endorsement of a website could facilitate the development of an effective alliance between the patient and the app. OBJECTIVE: We describe the implementation of a digitally mediated personal physician presence to enhance patient engagement with an alcohol-reduction website as part of the experimental online intervention in a noninferiority randomized controlled trial. We also report the feedback of the users on the module. METHODS: The Download Your Doctor module was created to simulate the personal physician presence for an alcohol-reduction website that was developed for the EFAR-FVG trial conducted in the Italian region of Friuli-Venezia-Giulia. The module was designed to enhance therapeutic alliance and thus improve outcomes in the intervention group (facilitated access to the website). Participating general and family practitioners could customize messages and visual elements and upload a personal photo, signature, and video recordings. To assess the perceptions and attitudes of the physicians, a semistructured interview was carried out 3 months after the start of the trial. Participating patients were invited to respond to a short online questionnaire 12 months following recruitment to investigate their evaluation of their online experiences. RESULTS: Nearly three-quarters (23/32, 72%) of the physicians interviewed chose to customize the contents of the interaction with their patients using the provided features and acknowledged the ease of use of the online tools. The majority of physicians (21/32, 57%) customized at least the introductory photo and video. Barriers to usage among those who did not customize the contents were time restrictions, privacy concerns, difficulties in using the tools, and considering the approach not useful. Over half (341/620, 55.0%) of participating patients completed the optional questionnaire. Many of them (240/341, 70.4%) recalled having noticed the personalized elements of their physicians, and the majority of those (208/240, 86.7%) reacted positively, considering the personalization to be of either high or the highest importance. CONCLUSIONS: The use of a digitally mediated personal physician presence online was both feasible and welcomed by both patients and physicians. Training of the physicians seems to be a key factor in addressing perceived barriers to usage. Further research is recommended to study the mechanisms behind this approach and its impact. TRIAL REGISTRATION: Clinicaltrials.gov NCT 01638338; https://clinicaltrials.gov/ct2/show/NCT01638338 (Archived by WebCite at http://www.webcitation.org/6f0JLZMtq).
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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 | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 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 ».