Examining the relationship between brain activation and proxies of disease severity using quantile regression in individuals at risk of Alzheimer's disease.

Previous studies have reported a pattern of hyperactivation in the pre-dementia phase of Alzheimer's disease (AD), followed by hypoactivation in later stages of the disease. This pattern was modeled as an inverse U-shape function between activation and markers of disease severity. In this study, we used quantile regression to model the association between task-related brain activation in AD signature regions and three markers of disease severity (hippocampal volume, cortical thickness, and associative memory). This approach offers distinct advantages over standard regression models as it analyzes the relationship between brain activation and disease severity across various levels of brain activation. Participants were 54 older adults with subjective cognitive decline+ (SCD+) or mild cognitive impairment (MCI) from the CIMA-Q cohort. The analysis revealed an inverse U-shape quadratic function depicting the relationship between disease severity markers and the activation of the left superior parietal region, while a linear relationship was observed for activation of the hippocampal and temporal regions. Quantile differences were observed for temporal and parietal activation, with more pronounced effects observed in the higher quantiles of activation. When comparing quantiles, we found that higher quantile of activation featured a greater number of individuals with SCD+ compared to mild cognitive impairment (MCI). Results are globally consistent with the presence of an inverse-U shape function of activation in relation to disease severity. They study also underscores the utility of employing quantile regression modeling as the modeling approach revealed the presence of non-homogeneous effects across various quantiles.

Development, psychometric evaluation, and factor analysis of an instrument measuring quality of life in autistic preschoolers.

INTRODUCTION: Early interventions for autistic children should target their quality of life (QoL) but require adapted measures. The association of a child's temperament and parental characteristics with the QoL of autistic children remains unknown. METHODS: We constructed an autism module based on a thematic analysis, a Delphi survey with experts, and a pre-test with parents to be completed alongside the proxy version of the PedsQL 4.0. We explored compliance, responsiveness, internal consistency, convergent validity, and factor structure with 157 parents of autistic preschool children. We examined the association between child and parental characteristics with the QoL of autistic children using correlation analysis, principal component analysis, hierarchical ascending classification, and linear regression. Sociodemographic information was collected via multiple choice questions, autism severity via Autism Diagnostic Observation Schedule (ADOS) scores, and parental acceptance and child's temperament via the Acceptance and Action Questionnaire and the Emotionality, Activity, and Sociability. RESULTS: An autism module comprised of 27 items emerged. Psychometric evaluation resulted in a 24-item autism module with good internal consistency and significant convergent validity. ADOS total score was not significantly related to QoL, contrary to children's sleep issues, children's emotionality, and parental acceptance. CONCLUSIONS: The autism module is a reliable QoL proxy measure for autistic preschool children. Results suggest parental interventions targeting children's QoL.

Insomnia symptoms among older adults during the first year of the COVID-19 pandemic: A longitudinal study.

OBJECTIVE: To identify sociodemographic, psychological, and health factors related to trajectories of insomnia symptoms in older adults during the COVID-19 pandemic. METHODS: From May 2020 to May 2021, 644 older adults (mean age = 78.73, SD = 5.60) completed telephone-administered self-reported measures (ie, Insomnia Severity Index, consensus sleep diaries, UCLA Loneliness Scale, Kessler Psychological Distress Scale, Post-Traumatic Checklist, perceived health threat, and International Physical Activity Questionnaire) and provided sociodemographic data at 4 timepoints. Using the Insomnia Severity Index score at each timepoint, group-based trajectory modeling was conducted to identify groups with distinct insomnia trajectories. RESULTS: On average, there was no significant change in insomnia symptoms over time. Three groups with distinct sleep trajectories were identified: clinical (11.8%), subthreshold (25.3%), and good sleepers (62.9%). Older adults who were younger, male, had elevated psychological distress and posttraumatic stress disorder symptoms, perceived more SARS-CoV-2 health threat, spent more time in bed, and had shorter sleep duration during the first wave of the pandemic were more likely to belong to the clinical than to the good sleepers group. Those who were younger, female, had elevated psychological distress and PTSD symptoms, greater loneliness, spent more time in bed, and had reduced sleep duration during the first wave were more likely to belong to the subthreshold than to the good sleepers group. CONCLUSIONS: Over 1 in 3 older adults experienced persistent subthreshold or clinically significant insomnia symptoms. Both sleep-related behaviors as well as general and COVID-19-related psychological factors were associated with insomnia trajectories.

Trajectories of psychological distress during the COVID-19 pandemic among community-dwelling older adults in Quebec: A longitudinal study.

OBJECTIVE: The COVID-19 pandemic and its associated public health measures may increase the risk for psychological distress among vulnerable older adults. This longitudinal study aimed to identify predictors of psychological distress trajectories among community-dwelling older adults in Quebec, Canada. METHODS: The study spanned four time points across 13 months and three waves of the COVID-19 pandemic. The sample included 645 community-dwelling older adults ages 60 years and older in Quebec. Participants completed telephone-based interviews that included the Kessler 6-item Psychological Distress Scale (K6) to assess psychological distress at each time point as well as information on socioeconomic, medical, psychological and COVID-19 related factors. Group-based trajectory modelling was used to identify distinct trajectories of psychological distress across time. RESULTS: Three group-based trajectories of psychological distress were identified: the resilient (50.5%), reactive (34.9%), and elevated distress groups (14.6%). Individuals with mobility issues, insomnia symptoms, COVID-19 related acute stress, general health anxiety, increased loneliness symptoms, and those unable to use technology to see others were more likely to be in the reactive and elevated groups than the resilient group. Those with past mental health problems had uniquely increased odds of being in the reactive group compared to the resilient group. Individuals living in poverty and those who reported taking psychotropic medication had increased odds of being in the elevated distress group compared to the resilient group. CONCLUSION: These findings characterized distinct trajectories of psychological distress in older adults and identified risk factors for elevated distress levels.

Group-based trajectories and predictors of adherence to physical distancing during the COVID-19 pandemic.

Objective: This study sought to identify psychosocial predictors of trajectories of adherence to physical distancing alongside changes in public health measures during the COVID-19 pandemic. Design: A three-time point longitudinal survey during the first two waves of the COVID-19 pandemic. Methods: Participants (N = 1003) completed self-report measures of adherence to physical distancing over an 8-month period at the start (T1) and end (T2) of the first wave of the pandemic, and the start of the second wave of the pandemic (T3). Participants also completed measures of their health beliefs related to the self and others, social norms, emotional distress, and sociodemographic characteristics. Results: Using group-based trajectory modeling, four trajectories of adherence to physical distancing emerged: a high-adherence trajectory, a slow-declining trajectory, a fluctuating trajectory, and a fast-declining trajectory. The most important psychosocial predictors of poorer adherence trajectories included perceptions of lower self-efficacy and higher barriers to adherence, as well as lower prosocial attitudes towards physical distancing. Conclusion: Public health messages targeting these factors may be most relevant to promote sustained adherence to physical distancing over time in the context of a pandemic.