Interventions incorporating physical and cognitive elements to reduce falls risk in cognitively impaired older adults
Notice bibliographique
Résumé
BACKGROUND: Cognitive impairment is a risk factor for falls. Older adults with cognitive impairment (such as dementia) have an increased risk of falling compared with age-matched individuals without a cognitive impairment. To reduce falls in this population, interventions could theoretically target and train both physical and cognitive abilities. Combining and addressing cognitive components in falls rehabilitation is a novel and emerging area of healthcare. OBJECTIVES: The objective of this review was to identify the effectiveness of combined cognitive and physical interventions on the risk of falls in cognitively impaired older adults. INCLUSION CRITERIA TYPES OF PARTICIPANTS: Older persons who were 65 years or older and identified as having a cognitive impairment either through diagnosis or assessment of global cognition. TYPES OF INTERVENTION(S): Multifactorial or multiple interventions where physical and cognitive elements were combined was compared against standard care or a single element intervention. TYPES OF STUDIES: Randomized controlled trials (RCTs), controlled clinical trials and experimental studies in which randomization was used. OUTCOMES: Outcomes related to falls, including falls rate, specific falls risk measures (i.e. Physiological Profile Assessment) or related clinical outcome measures (i.e. Timed Up and Go test, Tinetti and gait speed). SEARCH STRATEGY: A three-step search strategy was utilized in this review, including search of electronic databases: CENTRAL, JBISRIR, MEDLINE, EMBASE, AMED, CINAHL and PsychINFO. Initial keywords used were dementia, cognitive impairment, memory loss, exercise, rehabilitation and accidental falls. Grey literature (Google Scholar) and trials registers (Current Controlled Trials) searches were also completed. METHODOLOGICAL QUALITY: The methodological quality of included studies was assessed using Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) software. DATA EXTRACTION: Data was extracted from articles included in the review using the standardized data extraction tool from JBI-MAStARI. DATA SYNTHESIS: A quantitative meta-analysis was performed where possible. Otherwise, data synthesis was in the form of narrative review. Sub-group analysis according to level of cognitive impairment was completed where possible. RESULTS: Eight RCTs were included in this review; they evaluated the effectiveness of multicomponent exercise programs, including physical and cognitive activities, music-based group exercise and mind-body tai chi on falls related outcomes. Most of the studies were of good quality with an average quality score of 7.5. Four studies reported effectiveness based on the number of falls, half of which reported a significant difference between the groups, but pooling of results into meta-analysis was not possible because of differences in reporting of the outcome. Falls related outcomes that were combined in meta-analysis included balance (Berg balance scale), functional mobility (Timed Up and Go) and gait speed (m/s). There was a statistically significant improvement in balance and gait speed following the intervention; however, the studies were too heterogeneous to be included in the analysis from the functional mobility results. CONCLUSION: Overall, multicomponent interventions incorporating both physical and cognitive components demonstrated positive effects on balance, functional mobility and gait speed when compared with a control and had significantly better effect on balance and gait speed within mild cognitive impairment populations.
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 | 0,003 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,007 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».