Use of a Technology-Based Fall Prevention Program With Visual Feedback in the Setting of Early Geriatric Rehabilitation: Controlled and Nonrandomized Study
Notice bibliographique
Résumé
Background: The Otago program (OP) is evidence-based and focuses on fall prevention in older people. The feasibility and usability of a short-term digital program modeled after the principles of the OP in the setting of early geriatric rehabilitation (EGR) are unclear. Objective: This study investigated the feasibility and usability of an additional technology-based fall prevention program (FPP) in the setting of EGR. Methods: We performed a feasibility study in the setting of EGR. A sample of 30 patients (mobility at least by walker; mini-mental status test score >17) was recruited between March and June 2024 and compared with a retrospective cohort (n=30, former EGR patients). All patients in the intervention group (IG) received a supervised, OP-modified FPP thrice/week for 20 minutes using a technology-based platform called "Pixformance." The device is a digital trainer and enables real-time corrections. The primary end point was the feasibility (given when 80% of the IG participated in 6 trainings within 2 weeks). Secondary outcomes were usability (patients' and facilitators' perspective; ≥75%), risk of falls (Berg Balance Scale), mobility (Timed Up and Go Test), functional independence (Functional Independence Measure), and activities of daily living (Barthel Index). Several further exploratory end points were analyzed including anxiety and depression (Four-Item Patient Health Questionnaire; PH-Q4). Data were accessed at entry to EGR and after 2 weeks prior to discharge. To analyze the pre-posttest results, the dependent Student t test and the Wilcoxon test were applied. A mixed ANOVA with repeated measurements was used for statistical analyses of time-, group-, and interaction-related changes. Results: A cohort of 60 patients (mean 80.2, SD 6.1 y; 58% females, 35/60) was analyzed. The main indication for EGR was stroke (9/60, 15%). Patients were recruited into a prospective IG (n=30) and a retrospective control group (n=30). Of the 30 patients in the prospective IG, 11 patients (37%) completed 6 training sessions within 2 weeks. Reasons why participants did not complete 6 training sessions were diagnostic appointments (33%), pain/discomfort (33%), or fatigue (17%). EGR patients rated FPP usability at 84% and facilitators at 65% out of 100%. Pre-posttest analysis of the standard assessments showed a significant interaction in Berg Balance Scale (<.01). In both groups, a significant improvement over time was found in the Timed Up and Go Test (<.01), Barthel Index (<.01), and Functional Independence Measure (<.01). Likewise, in the IG, the PH-Q4 score (.02) improved. Conclusions: While the technology-based FPP in the EGR setting was generally well-accepted by patients, with high usability ratings, its feasibility was limited. Only 37% of participants completed the required additional training sessions. Further studies should test the technology-based FPP as an integrated part of the EGR complex therapy concept. Our findings suggest potential benefits of incorporating technology-based FPPs in EGR, but further refinement is needed to enhance participation and feasibility.
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 | 0,009 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».