The Global Impact of COVID‐19 Control Measures on People With Dementia Living at Home and Their Carers: A Systematic Review of Quantitative and Qualitative Research Across 27 Countries
Notice bibliographique
Résumé
BACKGROUND: COVID-19 control measures have had a unique impact on people with dementia (PWD) and their carers living at home. Yet, uncertainty exists regarding the global impact of such measures and whether differences exist between countries and global regions. We aimed to synthesize evidence on this topic. METHODS: We searched Medline, PsycINFO, EMBASE, Web of Science, CINAHL, Latin American and Caribbean Health Literature (LILACS), Scientific Electronic Library Online (SciELO), and EM Premium from the start of the pandemic to July 2022. At least two researchers independently screened citations and performed quality assessment following recommended criteria for critical appraisal according to study methodology. We analyzed data by country and region and synthesized results descriptively. RESULTS: Sixty-nine studies met inclusion criteria (74% quantitative and 26% qualitative; 22% included PWD, 44% carers of PWD, and 4% dyads), with a total of 209,738 participants. Most studies were conducted in Europe (59%), followed by Asia and North America (15% each), South America (7%), and Oceania (1%). Two studies presented data from multiple regions (3%). The quality of the studies varied, with the majority (62%) being of moderate quality. Across the study populations and global regions, COVID-19 control measures had implications for PWD and carers' access to health services, physical and mental health and daily routine, cognition, behavior, with accompanying social and economic costs. The impact on mental health for PWD and on loneliness and well-being for carers were the two most frequently studied outcomes. CONCLUSION: People with dementia and their carers represent a heterogeneous group of people across countries and communities; despite that, the impacts of COVID-19 control measures on PWD and their carers were broadly consistent across regions. Our evidence synthesis highlights the critical need for decision-makers to account for the needs of PWD and their carers when designing and implementing public health measures. OTHER: This work was funded by the JPND Call for Expert Working Groups: The Impact of COVID-19 on Neurodegenerative Diseases in partnership with the CIHR-Institute of Aging and the Public Health Agency (CIHR #02342-000). PROSPERO CRD42024554701.
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 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 | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».