Acceptability of Telehealth as the Default Modality for Multiple Sclerosis Care in Switzerland: Cross-Sectional Study
Notice bibliographique
Résumé
Background: Telehealth can improve access to care for people living with multiple sclerosis (MS), but information on its acceptance is limited in Switzerland. Objective: This study aimed to determine the proportion of people living with MS willing to accept telehealth as a new default and the factors associated with their acceptance. Methods: We conducted a cross-sectional analysis using survey data from the Swiss Multiple Sclerosis Registry. We defined "telehealth as a default" as a health care model where remote consultations (telephone and/or video calls) are the primary mode of interaction between patients and their physicians, with in-person visits based on clinical necessity. Multivariable logistic regression was performed to evaluate the association between telehealth acceptance and sociodemographic and health-related factors. Telehealth acceptance was described in relation to 3 survey variables that mirrored key constructs from the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework. The variables were digital communication preferences, internet use for health provider searches, and experience with telemedicine. Results: Among 427 respondents, 15.5% (66/427) reported a willingness to accept telehealth as their default. In this group, only 21.2% (14/66) had experience using telemedicine. A descriptive analysis of our 3 NASSS-derived key constructs showed that among the 78.5% (335/427) respondents who generally agreed to digital access to health data, only 17.0% (57/335) accepted telehealth as a default. Notably, 30.7% (129/427) of participants stated a wish for support for using devices or the internet. Among those 129 individuals, 17.1% (22/129) were willing to accept telehealth as a default. Of the 89 people with prior telehealth experience, 15.7% (14/89) were willing to accept telehealth. In multivariable analysis, digital communication with health care providers (adjusted odds ratio [aOR] 14.56, 95% CI 6.18-39.04; P<.001), current internet use for health care provider search (aOR 7.78, 95% CI 1.34-45.32; P=.021), and a secondary progressive MS diagnosis (aOR 0.22, 95% CI 0.05-0.72; P=.021) were independently associated with accepting telehealth as a default. Conclusions: Our findings suggest a low acceptance of telehealth as a default among people living with MS in Switzerland. While our 3 postulated NASSS-derived key constructs were not associated with telehealth acceptance, we noted additional behavioral factors, including previous digital communication with health care providers and using the internet to search for health care provider information, which were associated with telehealth acceptance. Moreover, advanced disease states like secondary progressive MS were negatively associated with telehealth acceptance. Thus, telehealth as a default will be most acceptable in people living with MS who already use the internet for their health, and those with less severe disease. Future research should explore provider perspectives and evaluate long-term strategies for the acceptance of telehealth in MS care.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».