Transitions in Mood Among Residents of Canadian Long-Term Care Facilities: The Effects of COVID-19 Individual Risk Factors and Regional Characteristics
Notice bibliographique
Résumé
Long-term care home residents are among the most vulnerable populations due to their advanced age. Their health and well-being can be influenced by physical and psychosocial factors, the surrounding physical environment, and practice patterns that make them more susceptible to increased morbidity, disability, and mortality. \nMental health disorders are particularly common among residents of long-term care (LTC) homes affecting between 27% and 40% of all LTC residents in Canada. The COVID-19 pandemic had a substantial impact on the physical and mental health and well-being of residents of long-term care (LTC) homes. The increased vulnerability of older adults combined with essential preventive and infection control measures led to a challenging environment in these care facilities. The COVID-19 pandemic highlighted and magnified pre-existing challenges in the LTC system, emphasizing the importance of comprehensive strategies to safeguard the mental health of LTC residents. \nStudy 1 is a scoping review that investigates the effect of isolation and loneliness on the mood of long-term care (LTC) home residents, both before and during the COVID-19 pandemic. It provides an overview of existing literature to understand the effects of family and friends’ visits or loneliness and of COVID-19 restrictions on residents’ mood. The review shows a diversity of findings highlighting the complexity of factors influencing residents' mood during a global health crisis such as that of COVID-19. It suggests a need for a nuanced understanding of the interplay between social interactions, pandemic-induced restrictions, and individual coping mechanisms. It also highlights the need to use a standardized measure for depressive symptoms globally to prevent biases and inconsistencies that might arise from research based on different measures. \nStudy 2 is a longitudinal study evaluating the effect of COVID-19 pandemic on incident mood disturbance among Canadian long-term care home residents. It also examines the effects of COVID-19 in stratified models using resident and facility-level variables. This study shows that a variety of factors contributed to an increase in mental health challenges during the initial waves of the pandemic including, but not limited to, the potential effects of lockdown procedures. Our findings highlight the importance of implementing broad-based multidimensional interventions to ensure the mental well-being of all individuals during outbreaks. \nStudy 3 is a pan-Canadian retrospective longitudinal analysis of residents in long-term care homes. It examines the complex transition between the different mood states and absorbing states out of LTC settings using a one-step multistate Markov transition analysis. Study 2 reports incident mood disturbance among Canadian long-term care home residents; however, it does not address the multidirectional changes or the absorbing states that act as competing risks. This study can inform decisions on programs that can enhance the mood of long-term care residents by examining predictors of worsening or improving mood as well as factors predicting transition to the absorbing states. \nStudy 4 expands on our knowledge from study 3 by treating COVID-19 as a covariate to examine the effects of COVID-19 on transitions between the transient mood states and the absorbing states in comparison to the pre-pandemic period. A one-step multistate Markov transition analysis was used in a pan-Canadian retrospective longitudinal analysis. The findings suggest further knowledge on the effects of COVID-19 on mood and inform decisions on the effective programs that can improve mood during periods of outbreaks. \nThe importance of this thesis lies in its comprehensive examination of the multifaceted complex interplay between social interactions, pandemic-related measures, as well as individual and facility-level variables pre-pandemic and during the COVID-19 pandemic. The included studies provide important insights for developing targeted interventions to support positive mood of LTC residents. In conclusion, this thesis not only advances our understanding of the mental health implications for LTC residents but also informs the development of evidence-based strategies to mitigate the adverse effects of isolation and pandemic-related stressors on this vulnerable population.
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 | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,006 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».