The Safety of Telerehabilitation: Systematic Review
Notice bibliographique
Résumé
Background: Telerehabilitation involves the delivery of rehabilitation services over a distance through communication technologies. In contrast to traditional in-person rehabilitation, telerehabilitation can help overcome barriers including geographic distance and facility use. There is evidence to suggest that telerehabilitation can lead to increased patient engagement and adherence to treatment plans. However, limited research exists on the association of telerehabilitation with adverse events, potentially hindering its broader adoption and use in health care. objectives: This systematic review of randomized controlled trials aims to summarize existing research on adverse events related to telerehabilitation delivery. Methods: This review was conducted according to the methodological framework outlined by the Joanna Briggs Institute. Studies were identified from MEDLINE ALL, Embase, APA PsycINFO, CENTRAL, and CINAHL. Included studies were randomized controlled trials published between 2013 and 2023, written in English, and had no geographic or delivery mode restrictions. Data extraction used the TIDieR (Template for Intervention Description and Replication) framework, along with authors, publication year, sample size, specific telerehabilitation modes, and the incidence, type, severity, and relatedness of reported adverse events. Methodological quality was assessed using the Cochrane risk of bias tool, and the certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation tool. Results: Search results identified 9022 references, of which 37 randomized controlled trials met the criteria for inclusion. There were a total of 3166 participants, with a mean age of 57.4 (SD 11.3) years, and 1023 (32.3%) being female participants. Various delivery modes were used, with videoconferencing emerging as the most frequently used method. A total of 201 adverse events were recorded during 65,352 sessions (0.31% or 3.1 per 1000 sessions). These events were predominantly physical (eg, falls and palpitations), nonserious or mild, and not directly attributed to the telerehabilitation intervention. Additionally, 34 (92%) of included studies implemented various safety practices including vital sign monitoring, safety checklists, and scheduled check-ins with study personnel. Conclusions: This review demonstrates that telerehabilitation exhibits a generally safe profile as an alternative to in-person rehabilitation, with most reported adverse events being rare, nonserious or mild, and unrelated to telerehabilitation protocols. However, more extensive research with detailed reporting on adverse event characteristics is needed. Moreover, future research should evaluate the effectiveness of different safety practices and their association with adverse events. An enhanced understanding of potential risks in telerehabilitation can foster broader adoption while ensuring its safe implementation among health care providers and patients.
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 | 0,023 | 0,128 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,010 | 0,009 |
| Bibliométrie | 0,010 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».