Features of Structured, One-to-One Videoconference Interventions That Actively Engage People in the Management of Their Chronic Conditions: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: A dramatic increase in the use of videoconferencing occurred as a response to the COVID-19 pandemic, including delivery of chronic disease management programs. With this increase, clients' openness to and confidence in receiving any type of telehealth care has dramatically improved. However, the rapidity of the response was accomplished with little time to learn from existing knowledge and research. OBJECTIVE: The purpose of this scoping review was to identify features, barriers, and facilitators of synchronous videoconference interventions that actively engage clients in the management of chronic conditions. METHODS: Using scoping review methodology, MEDLINE, CINAHL, and 6 other databases were searched from 2003 onward. The included studies reported on structured, one-on-one, synchronous videoconferencing interventions that actively engaged adults in the management of their chronic conditions at home. Studies reporting assessment or routine care were excluded. Extracted text data were analyzed using thematic analysis and published taxonomies. RESULTS: The 33 included articles reported on 25 distinct programs. Most programs targeted people with neurological conditions (10/25, 40%) or cancer (7/25, 28%). Analysis using the Taxonomy of Every Day Self-Management Strategies and the Behavior Change Technique Taxonomy version 1 identified common program content and behavior change strategies. However, distinct differences were evident based on whether program objectives were to improve physical activity or function (7/25, 28%) or mental health (7/25, 28%). Incorporating healthy behaviors was addressed in all programs designed to improve physical activity or function, whereas only 14% (1/7) of the programs targeting mental health covered content about healthy lifestyles. Managing emotional distress and social interaction were commonly discussed in programs with objectives of improving mental health (6/25, 24% and 4/25, 16%, respectively) but not in programs aiming at physical function (2/25, 8% and 0%, respectively). In total, 13 types of behavior change strategies were identified in the 25 programs. The top 3 types of strategies applied in programs intent on improving physical activity or function were feedback and monitoring, goals and planning, and social support, in contrast to shaping knowledge, regulation, and identity in programs with the goal of improving mental health. The findings suggest that chronic condition interventions continue to neglect evidence that exercise and strong relationships improve both physical and mental health. Videoconference interventions were seen as feasible and acceptable to clients. Challenges were mostly technology related: clients' comfort, technology literacy, access to hardware and the internet, and technical breakdowns and issues. Only 15% (5/33) of the studies explicitly described compliance with health information or privacy protection regulations. CONCLUSIONS: Videoconferencing is a feasible and acceptable delivery format to engage clients in managing their conditions at home. Future program development could reduce siloed approaches by adding less used content and behavior change strategies. Addressing client privacy and technology issues should be priorities.
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 | 0,018 | 0,084 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,005 |
| Bibliométrie | 0,020 | 0,024 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 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) | 0,004 | 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 ».