Examining Worsening Positive Symptoms During the COVID-19 Pandemic in Older Adult Home Care Clients in Ontario
Notice bibliographique
Résumé
Background: In response to the COVID-19 pandemic, lockdown restrictions were implemented to minimize the spread of infection. Older adults over the age of 60 account for majority of COVID-19-related deaths, hospitalizations, and intensive care admissions (Government of Canada, 2023). Thus, since the beginning of the pandemic, older adults were a vulnerable cohort with a high-risk of mortality. \nOlder adults with a mental disorder may be even more vulnerable to worsening physical health and mortality, as well as may experience greater psychological distress or a relapse in symptoms of their diagnosis due to social isolation and loneliness experienced during the pandemic. Research highlighting the pandemic effects on the general population of older adult psychological health have had mixed results. It is not well understood how the pandemic has affected positive symptoms of older adults with mental disorders. Objectives: The goal of part I of this paper was to identify and synthesize existing literature focusing on older adults with mental disorders, their experience throughout the COVID-19 pandemic, and the outcomes that have been researched in this realm. The goal of part II of this paper was to explore the changes of positive symptoms prior to and during the COVID-19 pandemic on older adults experiencing mental disorders in Ontario, and to examine risk factors that make them prone to experiencing worsening positive symptoms. Methods: Part I consisted of a rapid review and critical appraisal of the current research on older adults with mental disorders and COVID-19. Five electronic databases (PubMed, MEDLINE, Scopus, CINAHL, and PsycINFO) were searched. Part II entailed secondary data analysis using Ontario interRAI HC collected between September 1, 2018, to August 31, 2022. The sample was divided into four subsamples, “Pre-COVID,” “COVID Year 1,” “COVID Year 2,” and “COVID Year 3,” to conduct bivariate analyses. Bivariate analyses guided the development of three binary logistic regression models that were selected with modified stepwise selection. The final multivariate model determined predictors of worsening positive symptoms at time two for the total sample. Two additional models explored stratified logistic regression models of anti-psychotic use. Results: 40 studies were included in part I of this study. The results revealed that majority of existing research has been conducted from older adults with depression, in the first year of the pandemic, where the outcome was mood symptoms effected by social isolation in a variety of study settings. In part II of this study, risk of worsening positive symptoms was found to be associated with several variables. Variations in risk factor was present in main effects from the final model through LHIN region, higher MAPLe & CHESS scores, financial trade-offs, exercise, medication adherence, and difficulty sleeping, indicating that these factors had considerable associations with worsening positive symptoms prior to, and during the pandemic. Delirium and anti-psychotic use remained consistent prior to and during the pandemic in the COVID interactions. Older adults aged 64-75 with a diagnosis of schizophrenia had a AOR of 9.99 (reference = 18-64 and no mental illness). Variations of these risk factors were also found in the stratified logistic regression models of anti-psychotic use. Conclusion: Existing literature points to the pandemic leading to adverse health outcomes for older adults with mental disorders. Age-related risk factors and mental disorders were found to be of notable concern for worsening of positive symptoms, however, these factors may not have been exacerbated due to the COVID-19 pandemic. Future research is still needed to unpack this further.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».