Sleep disturbance is highly prevalent in people with osteoarthritis (OA) yet it is rarely considered in routine care. Emerging evidence suggests that sleep disturbance contributes to heightened musculoskeletal pain and poorer physical and emotional outcomes in those with OA. This narrative review synthesises current knowledge on the epidemiology and impact of sleep disturbances in OA, including their associations with and impact on fatigue, depressive symptoms, pain catastrophising, and negative mood. It examines the effects of core OA treatments such as exercise, diet and weight loss on sleep, as well as the potential for sleep-focused therapies such as cognitive behavioural therapy for insomnia to improve pain in OA populations. The review also considers how addressing sleep may offer a novel pathway to enhance clinical outcomes and identifies health professionals who may be well placed to deliver sleep care to individuals living with OA. Incorporating sleep into OA management presents an innovative, high-impact, and low-risk opportunity to improve patient outcomes.

Objective Explore physiotherapists’ experiences with Cognitive Behavioural Therapy for Insomnia (CBT-I) training to understand factors that may influence implementation and upscaling of CBT-I training for physiotherapists. Method Using a mixed-methods approach, data were collected through questionnaires and semi-structured interviews from twelve physiotherapists (3–27 years' experience) who completed a CBT-I training program consisting of online workshops and a pilot case. The Educational Course Assessment Toolkit (EDUCATOOL) evaluated reaction, learning, expected outcomes and behaviours in relation to the CBT-I training, and the Determinants of Implementation Behaviour Questionnaire (DIBQ), assessed barriers and enablers to the implementation of CBT-I. Interviews explored physiotherapists’ experiences of the training, guided by the theoretical framework of acceptability. Data were analysed thematically, with themes subsequently mapped to the Theoretical Domains Framework. Results The median EDUCATOOL overall score was 92.38 (IQR = 87.35–99.00) out of 100.87% of DIBQ items were rated favourably to their respective domains (>4 on 7-point Likert scale). Four themes were generated from the interviews. Physiotherapists reported confidence in their capability to deliver CBT-I, reflecting (1) readiness for implementation in their professional role. (2) Training delivery and design contributed positively to knowledge acquisition. (3) Experiential learning enhanced understanding and confidence. However, physiotherapists noted (4) barriers affecting the integration of CBT-I in physiotherapy practice, including stakeholder engagement, and feasibility considerations related to billing, and delivery. Conclusion Physiotherapists felt confident to deliver CBT-I following a training program. For successful upscaling, future initiatives must address identified systemic and practical barriers, including stakeholder engagement and delivery feasibility.

Longitudinal trajectories of sleep in subarachnoid hemorrhage (SAH) survivors are not well known. We identified subgroups of SAH survivors based on distinct trajectories of sleep during the first 6 months post-SAH and compared sociodemographic characteristics, clinical characteristics, inflammatory biomarkers (Toll-like receptor 4, tumor necrosis factor [TNF]-α, interleukin [IL]-1β, and IL-6), and symptom-related characteristics (depression/anxiety, fatigue, sleep quality, and cognition) among the subgroups. We conducted a 6-month longitudinal study of 40 SAH survivors (mean age = 56.0). Multi-trajectory latent class growth analysis identified salient patient groupings based on the trajectories of sleep parameters-sleep efficiency (SE), sleep onset latency (SOL), wake after sleep onset (WASO), and total sleep time (TST)-assessed using actigraphy at 2, 3, and 6 months. Two trajectory groups were identified: Group 1 (n = 24; "high SE/short SOL/short WASO/adequate TST") and Group 2 (n = 16; "low SE/long SOL/long WASO/insufficient TST"). The mean scores of all sleep parameters remained stable across months 2, 3, and 6 in both groups, except for SOL, which decreased in Group 2, but remained higher than that of Group 1. Individuals in Group 1 (vs. Group 2) were more likely to be female and had lower levels of TNF-α and IL-6 on days 3 and 4 post-SAH, respectively. Individuals in Group 1 (vs. Group 2) performed better on immediate memory, visuospatial/constructional ability, attention, and delayed memory tasks at 2 months. Distinct sleep trajectory groups were identified among SAH survivors; however, further studies with larger samples are needed to validate and better characterize these patterns.

People living with dementia frequently experience sleep disturbances, and their informal care partners are also at high risk of poor sleep. Few sleep interventions consider the unique sleep interplay and challenges within caregiver-care-recipient dyads. This study evaluated the feasibility and preliminary efficacy of co-designed multimodal intervention to address sleep disturbances in dyads of people living with dementia and their care partners in Australia and New Zealand. Dyads of people living with dementia and their care partner were recruited from the community via social media and Dementia Support services. Eligible dyads completed the Dementia, Sleep and Wellbeing Program, a co-designed, six-week online sleep intervention. The program included a mix of group-based and personalised sessions, which combined Cognitive Behavioural Therapy for Insomnia, mindfulness, activity, and light delivered by registered psychologists. Feasibility was evaluated by attrition, attendance, and satisfaction. Sleep was assessed using the Pittsburgh Sleep Quality Index, the Insomnia Severity Index, and the Sleep Disturbance Inventory. Psychological wellbeing was assessed via the Depression Anxiety Stress Scale-2. Feasibility outcomes were summarised using descriptive statistics, and sleep/mood outcomes were analysed using linear mixed models. Twenty-three dyads were assessed for the study. Four dyads withdrew before the intervention, and one dyad withdrew during intervention, resulting in 18 dyads who completed the study (Mage=67.34 years, SDage=10.76). Attendance rates were high, with seven care partners attending all sessions. Both people living with dementia and care partners reported high satisfaction with the intervention. For care partners, significant reductions were observed in insomnia severity (p=.006) and improvements in sleep quality (p=.042). Significant improvements in insomnia severity (p=.006), depression (p=.002) and stress symptoms (p=.006) were observed for people living with dementia. These findings provide support for a multimodal, dyadic approach to reducing sleep disturbances among community-dwelling people with dementia and their carer, demonstrating high engagement and satisfaction, and early indications of improved subjective sleep and wellbeing. These results highlight the potential efficacy of online interventions to address sleep issues in this population. Dementia Centre for Research Collaboration – Pilot Grant Scheme 2020 and the Turner Institute Sleep and Circadian Theme Consumer and Community Involvement Grant.

Physical function is likely bidirectionally associated with physical activity (PA), sedentary behavior (SB), and sleep. We examined trajectories of physical function as predictors of these behaviors in community-dwelling adults aged ≥65 y without dementia from the Adult Changes in Thought cohort. Exposures were trajectories of physical performance (short Performance-Based Physical Function [sPPF]) and self-reported activities of daily living (ADL) impairment. Outcomes were device-measured PA and SB and self-reported sleep. We fit linear mixed-effects models to define trajectory slopes and intercepts for each functional measure over the prior 10 years. We used multivariable linear regression to investigate the relationship between trajectory features and outcomes, using bootstrap confidence intervals. Participants (N = 905) were 77.6 (SD = 6.9) years old, 55% female, 91% white, and had a median sPPF score of 9 (IQR = [8, 11]) and median impairment of 1 ADL (IQR = [0, 2]) at the time of activity measurement (baseline). Steeper decreases in sPPF (0.3-unit, 25% of the range) were associated with fewer steps (−1180, 95% CI = [−2853, −185]) and less moderate-to-vigorous PA (−15.7 min/day [−35.6, −2.3]). Steeper increases in ADL impairment were associated with 35.0 min/day (4.3, 65.0) additional sitting time, longer mean sitting bout duration (3.5 min/bout [0.8, 6.2]), fewer steps (−1372 [−2223, −638]), less moderate-to-vigorous PA (−13 min/day [−22.6, −5.0]), and more time-in-bed (25.5 min/day [6.5, 43.5]). No associations were observed with light PA or sleep quality. Worsening physical function is associated with lower PA and higher SB, but not with light-intensity movement or sleep quality, supporting the bidirectional nature of the relationship between physical function and physical behaviors.

Sleep disturbance after subarachnoid hemorrhage (SAH) impacts recovery and rehabilitation. Longitudinal studies examining trajectories of sleep are needed to understand patients’ experiences of sleep over time. We aimed to identify subgroups of SAH survivors based on distinct trajectories of sleep during the first 6 months post-SAH and determine whether they vary according to sociodemographic and clinical characteristics, inflammatory biomarkers (Toll-like receptor 4, Tumor Necrosis Factor-Alpha [TNF-α], Interleukin [IL]-1 beta, and IL-6), and symptoms-related characteristics (depression/anxiety, fatigue, sleep quality, and cognition). We conducted a 6-month longitudinal study of 40 SAH survivors (average age: 56.9 years, 32.5% male). Multi-trajectory latent class growth analysis was used to identify salient patient groupings based on the trajectories of objective sleep parameters—sleep efficiency (SE), sleep onset latency (SOL), wake after sleep onset (WASO), and total sleep time (TST)—assessed using actigraphy at 2, 3, and 6 months. Sociodemographic, clinical, and symptom-related characteristics (at 2 months) and inflammatory biomarkers (at 2, 3, and 7 days and 2 months) were compared among trajectory groups using bivariate analyses. Statistical significance was set at p < 0.1. Two trajectory groups were identified: Group 1 (n = 24; “high SE/short SOL/short WASO/adequate TST”) and Group 2 (n = 16; “low SE/long SOL/long WASO/insufficient TST”). The mean scores of all sleep parameters remained stable across all three time points (2, 3, and 6 months) in both groups, except for SOL, which significantly decreased in Group 2, but remained higher than that of Group 1. Individuals in Group 1 (vs. Group 2) were more likely to be female and had lower plasma levels of TNF-α and IL-6 at days 3 and 7 post-SAH, respectively. Individuals in Group 1 (vs. Group 2) performed better in the following cognitive domains: immediate memory, visuospatial/constructional ability, attention, and delayed memory tasks at 2 months. Significant differences between the two trajectory groups were observed in gender proportion, TNF-α and IL-6 plasma levels, and cognitive domains. These findings may help healthcare providers identify patients at risk of developing sleep disturbances. Our study suggests inflammation as a plausible mechanism of sleep disturbances. Support: NIH/NINR K23NR017404

Cross-sectional studies suggest that chronic disease burden in older adults is associated with lower activity. However, preceding life-course patterns of morbidity accumulation may also influence current activity and have not been well characterized. Using a well-described sample of older adults, we estimated associations between current chronic disease burden and accelerometer-measured moderate-to-vigorous intensity movement measures, light-intensity movement measures, and sedentary behavior measures. Additionally, we examined historic morbidity patterns among those with current multimorbidity to provide additional understanding of these later life associations between current multimorbidity and activity. Analyses included N = 886 older adult study participants who wore activPAL and Actigraph accelerometers. We calculated Charlson Comorbidity Index (CCI; range 0–29) scores for participants at the time of device wear and estimated the association between current chronic disease burden (CCIcurrent) and each accelerometer-based activity metric using linear regression. Additionally, for participants categorized as having multimorbidity at time of device wear (CCIcurrent = 2+), we calculated CCI scores from age 55 through age at device wear. We plotted these to illustrate historic patterns of morbidity accumulation, and we compared activity metrics between participants with observed distal vs. recent onset of multimorbidity. A unit increment in CCIcurrent was associated with higher mean sitting bout duration (0.5 min, CI: [0.0,1.0], p = 0.039) and with both lower average daily step counts (-319 steps, CI: [-431,-208], p < 0.001) and lower average daily minutes of moderate-to-vigorous physical activity (MVPA; -3.8 min, CI: [-5.2,-2.4], p < 0.001). No associations were seen with standing, light-intensity physical activity, or other sitting measures. Among older adults with multimorbidity at time of device-wear, results suggested some evidence that participants whose apparent onset was more distal engaged in less MVPA (-12.1, CI: [-21.0, -3.2], p = 0.008) and had fewer daily steps (-1000, CI: [-1745, -254], p = 0.009) than participants whose apparent onset was more recent. Current chronic disease burden was associated with moderate-to-vigorous intensity movement measures and some patterns of prolonged sitting. Current multimorbidity is characterized by a preceding pattern of accumulation over the life-course. Attention to both current and historic trajectory of multimorbidity is important in investigations of MVPA and health.

Objectives Sleep disturbances are highly prevalent and have adverse health consequences for both people living with dementia and their carepartners. Despite this, they are under-addressed caregiving settings. This study aimed to explore these sleep disturbances and co-design a multimodal sleep intervention for people living with dementia and their carepartners. Methods We conducted two focus groups and five semi-structured interviews ( n = 4 people living with dementia, n = 6 carepartners). Active involvement of community advisors was sought throughout the design, development, and facilitation phases. Reflexive thematic analysis was used to explore sleep-related experiences and receive feedback to shape intervention development. Findings People living with dementia reported disruptions to sleep and circadian rhythms, including sleep disturbances and confusion between day and night. Multiple sleep challenges were encountered by carepartners including insomnia, hypervigilance, and daytime impairment. The proposed sleep intervention was received positively, with significant insights emphasising the need for a multimodal toolkit approach, adaptation of the intervention across different dementia stages, and a focus on tailoring the program to carepartners. Conclusion Sleep interventions for caregivers and care-recipients should target both sleep and daytime functioning to ensure holistic support. Participants were receptive towards time-friendly, online, multimodal sleep interventions that combine cognitive behaviour therapies, light therapy, mindfulness, and exercise elements.

BACKGROUND:Untreated sleep problems in both persons living with dementia (PLWD) and their family care partners (CP) impact their health and quality of life. This pilot study tested a sleep intervention program for both dyad members. METHODS:Thirty dyads were randomized to a 5-session Care2Sleep intervention (n = 15 dyads) or an information-only control group (n = 15 dyads) delivered in-person or by video-telehealth by trained sleep educators. Care2Sleep is a manual-based program, incorporating key components of cognitive behavioral therapy for insomnia, daily light exposure and walking, and problem-solving for dementia-related behaviors. Adherence with Care2Sleep recommendations was assessed. Sleep outcomes included actigraphy-measured sleep efficiency (SE) and total wake time (TWT) for dyads, and the Pittsburgh Sleep Quality Index (PSQI) for CP. Other outcomes for CP included the Zarit Burden Interview (ZBI) and positive aspects of caregiving (PAC). Outcomes were measured at baseline, posttreatment, and 3-month follow-up. A 2 (group) by 3 (time) mixed model analysis of variance tested treatment effects. RESULTS:Study feasibility was demonstrated, with 13 dyads completing all five sessions of Care2Sleep program and 14 completing the control condition. In the Care2Sleep group, the dyads adhered to recommended sleep schedules of 76% for bedtime and 72% for get-up time for PLWD, and 69% for bedtime and 67% for get-up time for CP. There were several nonsignificant trends in outcomes from baseline to 3-month follow-up between the two groups. For example, SE increased by 3.2% more for PLWD and 3.2% more for CP with Care2Sleep versus control. TWT decreased by 14 min more for PLWD and 12 min more for CP with Care2Sleep versus control at the 3-month follow-up. CP in Care2Sleep also showed improvement in the PSQI, ZBI, and PAC scores. CONCLUSIONS:A dyadic approach to sleep improvement is feasible. Larger trials are needed to test effects of this intervention for PLWD and their family CP. CLINICALTRIALS:gov: NCT03455569.

Background Changes in sleep, physical activity and mental health were observed in older adults during early stages of the COVID-19 pandemic. Here we describe effects of the COVID-19 pandemic on older adult mental health, wellbeing, and lifestyle behaviors and explore predictors of better mid-pandemic mental health and wellbeing. Methods Participants in the Adult Changes in Thought study completed measures of lifestyle behaviors (e.g., sleep, physical activity) and mental health and wellbeing both pre-pandemic during regular study visits and mid-pandemic via a one-time survey. We used paired t-tests to compare differences in these measures pre- vs. mid-pandemic. Using multivariate linear regression, we further explored demographic, health, and lifestyle predictors of pandemic depressive symptoms, social support, and fatigue. We additionally qualitatively coded free text data from the mid-pandemic survey for related comments. Results Participants (N = 896) reported significant changes in mental health and lifestyle behaviors at pre-pandemic vs. mid-pandemic measurements (p < 0.0001). Qualitative findings supported these behavioral and wellbeing changes. Being male, never smoking, and lower pre-pandemic computer time and sleep disturbance were significantly associated with lower pandemic depressive symptoms. Being partnered, female, never smoking, and lower pre-pandemic sleep disturbance were associated with higher pandemic social support. Pre-pandemic employment, more walking, less computer time, and less sleep disturbance were associated with less pandemic fatigue. Participant comments supported these quantitative findings, highlighting gender differences in pandemic mental health, changes in computer usage and physical activity during the pandemic, the value of spousal social support, and links between sleep disturbance and mental health and wellbeing. Qualitative findings also revealed additional factors, such as stresses from personal and family health situations and the country's concurrent political environment, that impacted mental health and wellbeing. Conclusions Several demographic, health, and lifestyle behaviors appeared to buffer the effects of the COVID-19 pandemic and may be key sources of resilience. Interventions and public health measures targeting men and unpartnered individuals could promote social support resilience, and intervening on modifiable behaviors like sleep quality, physical activity and sedentary activities like computer time may promote resilience to fatigue and depressive symptoms during future community stressor events. Further research into these relationships is warranted.

Background We examined whether trajectories of cognitive function over 10 years predict later-life physical activity (PA), sedentary time (ST), and sleep.Methods Participants were from the Adult Changes in Thought (ACT) cohort study. We included 611 ACT participants who wore accelerometers and had 3+ measures of cognition in the 10 years prior to accelerometer wear. The Cognitive Assessment Screening Instrument (CASI) measured cognition and was scored using item-response theory (IRT). activPAL and ActiGraph accelerometers worn over 7 days measured ST and PA outcomes. Self-reported time in bed and sleep quality measured sleep outcomes. Analyses used growth mixture modeling to classify CASI-IRT scores into latent groups and examine associations with PA, ST, and sleep including demographic and health covariates.Results Participants (Mean age = 80.3 (6.5) years, 90.3% White, 57.1% female, 29.3% had less than 16 years of education) fell into 3 latent trajectory groups: average stable CASI (56.1%), high stable CASI (34.0%), and declining CASI (9.8%). The declining group had 16 minutes less stepping time (95% confidence interval [95% CI]: 0.6, 31.4), 1 517 fewer steps per day (95% CI: 138, 2 896), and 16.3 minutes per day less moderate-to-vigorous PA (95% CI: 1.3, 31.3) compared to the average stable group. There were no associations between CASI trajectory and sedentary or sleep outcomes.Conclusions Declining cognition predicted lower PA providing some evidence of a reverse relationship between PA and cognition in older adults. However, this conclusion is limited by having outcomes at only one time point, a nonrepresentative sample, self-reported sleep outcomes, and using a global cognition measure.

Objective:Poor sleep is associated with increased inflammation, thereby increasing the risk of chronic diseases and mortality. However, the effects of behavioral sleep interventions on the upstream inflammatory system are unknown among family care partners (CP). The present study explored the role of a behavioral sleep intervention program on inflammatory gene expression. Methods:This was part of a randomized controlled trial of a sleep intervention for dementia care dyads with sleep problems. Thirty dyads were randomized to sleep intervention or control groups. Sleep outcomes for CP were assessed with 1 week of actigraphy and sleep diary, and the Pittsburgh Sleep Quality Index. Other information included CP demographics, body mass index, and intensity of caregiving tasks. All outcomes were collected at baseline, post-treatment, and 3-month follow-up. Results:Neither group showed any significant differential changes in gene expression from baseline to post-treatment or 3-month follow-up. A decrease in inflammatory gene expression was significantly associated with more nights of good sleep (i.e. nights without trouble falling or staying asleep at night). This finding remained significant after controlling for group (intervention/control), timepoint (baseline, post-treatment, and 3-month follow-up), and CP characteristics (e.g. age and ethnicity). Conclusions:Although better sleep was associated with decreased inflammatory gene expression, this study did not demonstrate any benefits of a behavioral sleep intervention over control, most likely due to a small sample. Studies with larger sample sizes are needed to test the specific aspects of disturbed sleep that relate to inflammatory biology among CP of persons living with dementia.

The 24-h activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach inherently captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We describe three popular approaches for modeling outcome associations with the 24HAC exposure. We apply these approaches to assess an association with a cognitive outcome in a cohort of older adults, discuss statistical challenges, and provide guidance on interpretation and selecting an appropriate approach. We compare the use of the isotemporal substitution model (ISM), compositional data analysis (CoDA), and latent profile analysis (LPA) to analyze 24HAC. We illustrate each method by exploring cross-sectional associations with cognition in 1,034 older adults (Mean age = 77; Age range = 65–100; 55.8% female; 90% White) who were part of the Adult Changes in Thought (ACT) Activity Monitoring (ACT-AM) sub-study. PA and SB were assessed with thigh-worn activPAL accelerometers for 7-days. For each method, we fit a multivariable regression model to examine the cross-sectional association between the 24HAC and Cognitive Abilities Screening Instrument item response theory (CASI-IRT) score, adjusting for baseline characteristics. We highlight differences in assumptions and the scientific questions addressable by each approach. ISM is easiest to apply and interpret; however, the typical ISM assumes a linear association. CoDA uses an isometric log-ratio transformation to directly model the compositional exposure but can be more challenging to apply and interpret. LPA can serve as an exploratory analysis tool to classify individuals into groups with similar time-use patterns. Inference on associations of latent profiles with health outcomes need to account for the uncertainty of the LPA classifications, which is often ignored. Analyses using the three methods did not suggest that less time spent on SB and more in PA was associated with better cognitive function. The three standard analytical approaches for 24HAC each have advantages and limitations, and selection of the most appropriate method should be guided by the scientific questions of interest and applicability of each model’s assumptions. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.

Abstract Evidence-based non-pharmacological community programs to improve care of older adults with dementia are growing. However, many programs have historically been tested in research studies that fail to reach medically underserved populations or communities with unique service needs. STAR-Caregivers (STAR-C, also known as STAR-Community Consultants) is an evidence-based psychosocial support and skill training program designed to teach family caregivers how to identify and increase pleasant events, improve communication, and use behavioral problem-solving skills to reduce the problems experienced by their family member with dementia while improving quality of life for both persons in the caregiver-care receiver dyad. Since its original randomized controlled trial in 2005, STAR-C has been translated in a variety of real-world settings, including in Area Agencies on Aging throughout Oregon and Washington state. This symposium describes three recent new translation efforts: (1) implementation of STAR-C as a virtual training program (STAR-VTF) for caregivers of persons with dementia who are part of the Kaiser Permanente Washington health care system; (2) cultural adaptation of STAR-VTF for Latino caregivers, and (3) incorporation of STAR-C into a largely rural community care setting in Illinois during the COVID-19 pandemic using Amazon Echo technology to conduct telehealth community dyad STAR-C sessions and connect clients to supplemental services. Each presenter will discuss the dementia care needs in their respective populations, the challenges encountered in translation of STAR-C to serve target caregiving dyads, and lessons learned regarding treatment effectiveness and program sustainability.