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Record W7053234739

Transitions in Mood Among Residents of Canadian Long-Term Care Facilities: The Effects of COVID-19 Individual Risk Factors and Regional Characteristics

2024· dissertation· en· W7053234739 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2024
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessPsychosocialMental healthMoodVulnerability (computing)Social isolationHealth careCoping (psychology)
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.205
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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