Supervised and Self-Directed Technology-Based Dual-Task Exercise Training Program for Older Adults With a History of Falls: Mixed Methods Feasibility Study
Notice bibliographique
Résumé
<sec> <title>BACKGROUND</title> Older adults who have fallen are at increased risk of future falls. Training cognitive and physical functions simultaneously, known as dual-task (DT) training, has been shown to improve mobility and reduce fall risks. With appropriate digital tools, such as smartphones and mobile applications (apps), it is possible to deliver DT training in unsupervised, home-based settings, thereby increasing accessibility beyond the clinical environment. </sec> <sec> <title>OBJECTIVE</title> This study evaluated the feasibility and acceptability of a technology-based DT training programme delivered through a blended model of supervised and self-directed sessions in older adults with a history of falls. Perspectives of healthcare professionals working in falls prevention services were also explored. </sec> <sec> <title>METHODS</title> A single-arm, non-randomised feasibility study was conducted with 45 community-dwelling adults aged ≥65 years with a history of falls. Participants were recruited through primary care practices, secondary care falls prevention services, and community outreach. The 24-week DT programme, which integrated balance and strength exercises with cognitive training using a mobile app, was delivered in two phases: (1) Phase 1 (12 weeks): weekly 50-minute physiotherapist-led group classes in the community, and two additional 50-minute self-directed sessions at home; and (2) Phase 2 (12 weeks): three weekly 50-minute self-directed sessions at home. Feasibility and acceptability were assessed through recruitment and retention rates, adherence, app usage, and self-reported satisfaction. Qualitative data were obtained from focus groups with 28 participants who completed the programme and 16 healthcare professionals. Quantitative data were analysed descriptively, and qualitative data thematically. </sec> <sec> <title>RESULTS</title> We recruited 45 of the target 50 participants with most participants (n = 41) recruited through community pathways; 4 were recruited via National Health Service (NHS) pathways. Adherence was 64%, with higher adherence during Phase 1 (81%) than Phase 2 (50%). App usage was high (95%), and self-reported programme satisfaction was moderate-to-high. Retention at 24 weeks was 76%, and no adverse events occurred. Qualitative findings supported the programme’s feasibility and acceptability, emphasising social connection and tailored exercises as key to adherence—especially in home-based sessions. Healthcare professionals identified community organisations and referral pathways as the most practical routes for implementation. </sec> <sec> <title>CONCLUSIONS</title> A blended, technology-based dual-task training programme is both feasible and acceptable for older adults at risk of falling and can be effectively delivered beyond clinical settings. Community-based recruitment outperformed NHS pathways, highlighting the value of community engagement. These findings support the feasibility and acceptability of a full-scale trial, with targeted refinements to recruitment, support structures and delivery to maximise scalability and impact. </sec> <sec> <title>CLINICALTRIAL</title> ISRCTN15123197 </sec> <sec> <title>INTERNATIONAL REGISTERED REPORT</title> RR2-10.1371/journal.pone.0314829 </sec>
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, pas un consensus.
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