Understanding Longitudinal Changes in The Performance of Activities of Daily Living in Long-Term Care Settings: Trajectories, Transition Patterns, Predictors and Associated Health Outcomes

Abstract: \nWith rapid global growth of the aging population and the associated “expansion of morbidity”, more people live to experience challenges with performing the usual daily living activities resulting in an increasing need for long-term care (LTC). Understanding the complexities of changes in physical function is essential for the planning and delivery of person-level care that would promote healthy aging and enhance quality of life. This thesis explores the diverse trajectories of change in functional level that occur among LTC. It examines the role of individual-level factors in these complex changes, with a view to identifying early markers of adverse trajectories and enablers of beneficial trajectories. The ultimate goal of this is to generate evidence that could be used for person-level care planning, health management, and policy development. The thesis is comprised of five empirical studies representing different steps toward the main goal. \nStudy 1 is a scoping review of existing literature for approaches used to examine longitudinal trajectories of change in physical function. It summarizes evidence of how trajectories of physical function have been modeled over the past 20 years, showing the most frequently applied methods and their outputs. This chapter presents an easy-to-use, concise summary of the existing functional change modeling approach, highlighting the benefits of each method and the situations where they would most likely be more appropriate. It contributes to our understanding of how physical function trajectory modeling evolved over the years and highlights current gaps in research. \nStudy 2 provides evidence based on generalized estimating equations to quantify the marginal effect of the COVID-19 pandemic on ADL performance in LTC settings in Canada. This chapter which has already been published with the title, “Functional Decline in Long-Term Care Homes in the First Wave of the COVID-19 Pandemic: A Population-based Longitudinal Study in Five Canadian Provinces”, provides an aggregate level comparative analysis of functional decline between the pandemic and pre-pandemic periods. It contributes to the literature on the actual “additional” functional decline that occurred during the pandemic, differentiating this effect from the decline that usually occurs among residents in the setting. \nStudy 3 presents an analysis of three-year longitudinal trajectories of functional decline in LTC settings using Group Based Trajectory Modelling (GBTM) technique, which is a form of latent class growth analysis. GBTM was identified through the scoping review in Study 1 to be the most appropriate method for answering the research question addressed in this chapter. Four distinct functional decline trajectory subgroups were identified with this modeling approach for the overall population and the sub-analytic samples are presented in the associated chapter. Predictors of trajectory group membership were determined as well using binary logistic regression. The study also highlights the value of identifying functional decline trajectory by showing that it predicts future health outcomes like mortality and resource utilization. Prior to this study, there has not been any characterization of the pattern and predictors of longitudinal trajectory of functional decline among LTC residents in Canada. This study therefore contributes new knowledge about the multiyear trajectory of functional change followed by residents upon entry into care homes. \nStudy 4 highlights the multifaceted and complex transition between the different ADL functional levels and transitions out of LTC settings. Study 2 of this thesis provides the aggregate analysis of functional changes associated with a widespread health crisis and, study 3 reports trajectory patterns. However, both do not address the complex dynamic multidirectional changes that occur among residents. This study fills this gap by using multistate Markov transition analysis to capture the complex multidirectional transition between different functional levels (including improvement, decline, and remaining unchanged), and transition out of the setting observed during each assessment. The novel contribution of this study is in expanding our knowledge about the transient and terminal transitions that occur concurrently between ADL functional levels and other health outcomes in LTC setting. \nLast, the 5th study further deepens our understanding of COVID-19’s effect on LTC settings. Multistate Markov transition analysis was used to produce evidence of the transitions between ADL functional levels and out of the LTC setting that occurred during COVID-19 pandemic compared to similar transitions in the pre-pandemic period. It advances our previous chapter on Functional Decline in Long-Term Care Homes in the First Wave of the COVID-19 Pandemic, by providing a disaggregated, multidirectional analysis. The study therefore improves existing knowledge by providing a more granular analysis of the complex effect of the COVID-19 pandemic on the physical function of LTC home residents. \nThrough evidence generated from this comprehensive series of studies, this thesis expands existing knowledge about changes in the performance of activities of daily living in LTC settings. It adds a nuanced understanding of the complex multidirectional transitions between ADL functional levels and transitions out of the setting. By examining both aggregated and disaggregated measures of functional status, the thesis provides various perspectives with evidence that would allow care providers, health administrators, and policymakers to make better decisions about care planning and service provision in LTC. Further, by generating evidence of ADL and other health outcome changes during the COVID-19 pandemic, the thesis contributes additional knowledge that would be useful in planning for future pandemics or similar widespread health crises. Future work should focus on utilizing this evidence to develop decision-support tools to inform personalized care planning, promote healthy aging and enhance the quality of life of older adults.

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