Older Veterans’ Experiences of a Multicomponent Telehealth Program: Qualitative Program Evaluation Study
Notice bibliographique
Résumé
BACKGROUND: There are 8.8 million American veterans aged >65 years. Older veterans often have multiple health conditions that increase their risk of social isolation and loneliness, disability, adverse health events (eg, hospitalization and death), mental illness, and heavy health care use. This population also exhibits low levels of physical function and daily physical activity, which are factors that can negatively influence health. Importantly, these are modifiable risk factors that are amenable to physical therapy intervention. We used a working model based on the dynamic biopsychosocial framework and social cognitive theory to conceptualize the multifactorial needs of older veterans with multiple health conditions and develop a novel, 4-component telehealth program to address their complex needs. OBJECTIVE: This study aims to describe veterans' experiences of a multicomponent telehealth program and identify opportunities for quality and process improvement. We conducted qualitative interviews with telehealth program participants to collect their feedback on this novel program; explore their experience of program components; and document perceived outcomes and the impact on their daily life, relationships, and quality of life. METHODS: As part of a multimethod program evaluation, semistructured interviews were conducted with key informants who completed ≥8 weeks of the 12-week multicomponent telehealth program for veterans aged ≥50 years with at least 3 medical comorbidities. Interviews were audio recorded and transcribed. Data were analyzed by a team of 2 coders using a directed content analysis approach and Dedoose software was used to assist with data analysis. RESULTS: Of the 21 individuals enrolled in the program, 15 (71%) met the inclusion criteria for interviews. All 15 individuals completed 1-hour interviews. A total of 6 main conceptual domains were identified: technology, social networks, therapeutic relationship, patient attributes, access, and feasibility. Themes associated with each domain detail participant experiences of the telehealth program. Key informants also provided feedback related to different components of the program, leading to adaptations for the biobehavioral intervention, group sessions (transition from individual to group sessions and group session dynamics), and technology supports. CONCLUSIONS: Findings from this program evaluation identified quality and process improvements, which were made before rigorously testing the intervention in a larger population through a randomized controlled trial. The findings may inform adaptations of similar programs in different contexts. Further research is needed to develop a deeper understanding of how program components influence social health and longer-term behavior change.
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 | 0,017 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».