Pre-procedural nursing home length of stay and outcomes of transcatheter aortic valve replacement.

BACKGROUND: Older adults with severe aortic stenosis (AS) may receive care in a nursing home (NH) prior to undergoing transcatheter aortic valve replacement (TAVR). NH level of care can be used to stabilize medical conditions, to provide rehabilitation services, or for long-term care services. Our primary objective is to determine whether NH utilization pre-TAVR can be used to stratify patients at risk for higher mortality and poor disposition outcomes at 30 and 365 days post-TAVR. METHODS: We conducted a retrospective cohort study among Medicare beneficiaries who spent ≥1 day in an NH 6 months before TAVR (2011-2019). The intensity of NH utilization was categorized as low users (1-30 days), medium users (31-89 days), long-stay NH residents (≥ 100 days, with no more than a 10-day gap in care), and high post-acute rehabilitation patients (≥90 days, with more than a 10-day gap in care). The probabilities of death and disposition were estimated using multinomial logistic regression, adjusting for age, sex, and race. RESULTS: Among 15,581 patients, 9908 (63.6%) were low users, 4312 (27.7%) were medium users, 663 (4.3%) were high post-acute care rehab users, and 698 (4.4%) were long-stay NH residents before TAVR. High post-acute care rehabilitation patients were more likely to have dementia, weight loss, falls, and extensive dependence of activities of daily living (ADLs) as compared with low NH users. Mortality was the greatest in high post-acute care rehab users: 5.5% at 30 days, and 36.4% at 365 days. In contrast, low NH users had similar mortality rates compared with long-stay NH residents: 4.8% versus 4.8% at 30 days, and 24.9% versus 27.0% at 365 days. CONCLUSION: Frequent bouts of post-acute rehabilitation before TAVR were associated with adverse outcomes, yet this metric may be helpful to determine which patients with severe AS could benefit from palliative and geriatric services.

Recognition of Daily Activities in Adults With Wearable Inertial Sensors: Deep Learning Methods Study.

BACKGROUND: Activities of daily living (ADL) are essential for independence and personal well-being, reflecting an individual's functional status. Impairment in executing these tasks can limit autonomy and negatively affect quality of life. The assessment of physical function during ADL is crucial for the prevention and rehabilitation of movement limitations. Still, its traditional evaluation based on subjective observation has limitations in precision and objectivity. OBJECTIVE: The primary objective of this study is to use innovative technology, specifically wearable inertial sensors combined with artificial intelligence techniques, to objectively and accurately evaluate human performance in ADL. It is proposed to overcome the limitations of traditional methods by implementing systems that allow dynamic and noninvasive monitoring of movements during daily activities. The approach seeks to provide an effective tool for the early detection of dysfunctions and the personalization of treatment and rehabilitation plans, thus promoting an improvement in the quality of life of individuals. METHODS: To monitor movements, wearable inertial sensors were developed, which include accelerometers and triaxial gyroscopes. The developed sensors were used to create a proprietary database with 6 movements related to the shoulder and 3 related to the back. We registered 53,165 activity records in the database (consisting of accelerometer and gyroscope measurements), which were reduced to 52,600 after processing to remove null or abnormal values. Finally, 4 deep learning (DL) models were created by combining various processing layers to explore different approaches in ADL recognition. RESULTS: The results revealed high performance of the 4 proposed models, with levels of accuracy, precision, recall, and F1-score ranging between 95% and 97% for all classes and an average loss of 0.10. These results indicate the great capacity of the models to accurately identify a variety of activities, with a good balance between precision and recall. Both the convolutional and bidirectional approaches achieved slightly superior results, although the bidirectional model reached convergence in a smaller number of epochs. CONCLUSIONS: The DL models implemented have demonstrated solid performance, indicating an effective ability to identify and classify various daily activities related to the shoulder and lumbar region. These results were achieved with minimal sensorization-being noninvasive and practically imperceptible to the user-which does not affect their daily routine and promotes acceptance and adherence to continuous monitoring, thus improving the reliability of the data collected. This research has the potential to have a significant impact on the clinical evaluation and rehabilitation of patients with movement limitations, by providing an objective and advanced tool to detect key movement patterns and joint dysfunctions.

Automated Detection of In-Home Activities with Ultra-Wideband Sensors.

As Canada's population of older adults rises, the need for aging-in-place solutions is growing due to the declining quality of long-term-care homes and long wait times. While the current standards include questionnaire-based assessments for monitoring activities of daily living (ADLs), there is an urgent need for advanced indoor localization technologies that ensure privacy. This study explores the use of Ultra-Wideband (UWB) technology for activity recognition in a mock condo in the Glenrose Rehabilitation Hospital. UWB systems with built-in Inertial Measurement Unit (IMU) sensors were tested, using anchors set up across the condo and a tag worn by patients. We tested various UWB setups, changed the number of anchors, and varied the tag placement (on the wrist or chest). Wrist-worn tags consistently outperformed chest-worn tags, and the nine-anchor configuration yielded the highest accuracy. Machine learning models were developed to classify activities based on UWB and IMU data. Models that included positional data significantly outperformed those that did not. The Random Forest model with a 4 s data window achieved an accuracy of 94%, compared to 79.2% when positional data were excluded. These findings demonstrate that incorporating positional data with IMU sensors is a promising method for effective remote patient monitoring.

Sex differences in unmet needs between male and female older veterans.

Aging Veterans face complex needs across multiple domains. However, the needs of older female Veterans and the degree to which unmet needs differ by sex are unknown. We analyzed responses to the HERO CARE survey from 7,955 Veterans aged 55 years and older (weighted N = 490,148), 93.9% males and 6.1% females. We evaluated needs and unmet needs across the following domains: activities of daily living (ADLs), instrumental ADLs (IADLs), health management, and social. We calculated weighted estimates and compared sex differences using age-adjusted prevalence ratios. On average, female Veterans were younger, more were Non-Hispanic Black and unmarried. Females and males reported a similar prevalence of problems across all domains. However, compared to males, female Veterans had a lesser prevalence of missed appointments due to transportation (aPR 0.49; 95% CI: 0.26-0.92), housework unmet needs (aPR: 0.44; 95% CI: 0.20-0.97), and medication management unmet needs (aPR: 0.33; 95% CI: 0.11-0.95) but a higher prevalence of healthcare communication unmet needs (aPR: 2.40; 95% CI: 1.13-5.05) and monitoring health conditions unmet needs (aPR: 2.13, 95% CI: 1.08-4.20). Female Veterans' common experience of unmet needs in communicating with their healthcare teams could result in care that is less aligned with their preferences or needs. As the number of older female Veterans grows, these data and additional work to understand sex-specific unmet needs and ways to address them are essential to providing high-quality care for female Veterans.

Subjective Aging and Basic Activities of Daily Living: Moderation by Health Care Access and Mediation by Health Care Resources.

Subjective aging in older adults is associated with a decline in basic activities of daily living (bADL), although this is less well studied with increasing age cohorts by their healthcare resources (HCR) and healthcare access (HCA) controlling for sociodemographics. We aimed to address this gap in knowledge by analyzing the National Health and Aging Trends round 11 data set on 3303 older adults aged 70 to above 90, comprising 42% male and 58% female by age cohort (middle-old -70-79, n = 1409; older-old -80-89, n = 1432, oldest-old- 90 plus, n = 462). Results of mediation-moderation analysis show the subjective aging whole model comprising subjective cognitive decline, HCR, HCA, and sociodemographic to predict a decline in bADL with increasing age to be higher among the older-old age (80-89) compared to the middle-old age (70-79) or oldest-old (90 years +) cohorts. These findings suggest a "doughnut" effect by which the older-old age cohort of 80-89 may be coping less well with their bADL, while the oldest-old may have adapted to functional loss in their everyday living and/or comprises adults who may have passed a mortality selection despite a more significant burden of comorbidity.

Food Security and Health Outcomes following Gray Divorce.

The study evaluates the immediate and long-term consequences of gray divorce (i.e., marital dissolution after age 50) for the food security, depression, and disability of older Americans. Staggered Difference-in-Difference models were fitted to a nationally representative longitudinal sample of adults aged ≥ 50 years from the Health and Retirement Study, 1998-2018. Food insecurity and disability increase in the year of gray divorce and remain significantly elevated for up to six years or more following the event, consistent with the chronic strain model of gray divorce. Gray divorce has particularly adverse consequences for the food security of older women, while no gender differences were observed for disability. Increasing trends in gray divorce have important negative implications for food security and health of older Americans, particularly women, who appear to be less prepared to financially withstand a marital collapse in older age. Targeted policies to provide nutrition assistance and support in reemployment might be necessary to reduce the burden of food insecurity in the wake of gray divorce among women.

A Semantic Framework to Detect Problems in Activities of Daily Living Monitored through Smart Home Sensors.

Activities of daily living (ADLs) are fundamental routine tasks that the majority of physically and mentally healthy people can independently execute. In this paper, we present a semantic framework for detecting problems in ADLs execution, monitored through smart home sensors. In the context of this work, we conducted a pilot study, gathering raw data from various sensors and devices installed in a smart home environment. The proposed framework combines multiple Semantic Web technologies (i.e., ontology, RDF, triplestore) to handle and transform these raw data into meaningful representations, forming a knowledge graph. Subsequently, SPARQL queries are used to define and construct explicit rules to detect problematic behaviors in ADL execution, a procedure that leads to generating new implicit knowledge. Finally, all available results are visualized in a clinician dashboard. The proposed framework can monitor the deterioration of ADLs performance for people across the dementia spectrum by offering a comprehensive way for clinicians to describe problematic behaviors in the everyday life of an individual.

Identifying Functional Status Impairment in People Living With Dementia Through Natural Language Processing of Clinical Documents: Cross-Sectional Study.

BACKGROUND: Assessment of activities of daily living (ADLs) and instrumental ADLs (iADLs) is key to determining the severity of dementia and care needs among older adults. However, such information is often only documented in free-text clinical notes within the electronic health record and can be challenging to find. OBJECTIVE: This study aims to develop and validate machine learning models to determine the status of ADL and iADL impairments based on clinical notes. METHODS: This cross-sectional study leveraged electronic health record clinical notes from Mass General Brigham's Research Patient Data Repository linked with Medicare fee-for-service claims data from 2007 to 2017 to identify individuals aged 65 years or older with at least 1 diagnosis of dementia. Notes for encounters both 180 days before and after the first date of dementia diagnosis were randomly sampled. Models were trained and validated using note sentences filtered by expert-curated keywords (filtered cohort) and further evaluated using unfiltered sentences (unfiltered cohort). The model's performance was compared using area under the receiver operating characteristic curve and area under the precision-recall curve (AUPRC). RESULTS: The study included 10,000 key-term-filtered sentences representing 441 people (n=283, 64.2% women; mean age 82.7, SD 7.9 years) and 1000 unfiltered sentences representing 80 people (n=56, 70% women; mean age 82.8, SD 7.5 years). Area under the receiver operating characteristic curve was high for the best-performing ADL and iADL models on both cohorts (>0.97). For ADL impairment identification, the random forest model achieved the best AUPRC (0.89, 95% CI 0.86-0.91) on the filtered cohort; the support vector machine model achieved the highest AUPRC (0.82, 95% CI 0.75-0.89) for the unfiltered cohort. For iADL impairment, the Bio+Clinical bidirectional encoder representations from transformers (BERT) model had the highest AUPRC (filtered: 0.76, 95% CI 0.68-0.82; unfiltered: 0.58, 95% CI 0.001-1.0). Compared with a keyword-search approach on the unfiltered cohort, machine learning reduced false-positive rates from 4.5% to 0.2% for ADL and 1.8% to 0.1% for iADL. CONCLUSIONS: In this study, we demonstrated the ability of machine learning models to accurately identify ADL and iADL impairment based on free-text clinical notes, which could be useful in determining the severity of dementia.

The beneficial effects of transitional care for patients with stroke: A meta-analysis.

INTRODUCTION: Transitional care interventions have emerged as a promising method of ensuring treatment continuity and health care coordination when patients are discharged from hospital to home. However, few studies have investigated the frequency and duration of interventions and the effects of interventions on physical function. Therefore, this study aimed to determine the efficacy of transitional care for patients with stroke. METHODS: Six databases and the grey literature were searched to obtain relevant articles from October 1, 2022 to March 10, 2023. The primary outcomes studied were motor performance, walking speed, activities of daily living (ADLs) and caregiver burden following hospital-to-home transitional care. The quality of the studies was assessed with Cochrane risk of bias version 2. The quality and sensitivity of the evidence were assessed to ensure rigour of the findings. Meta-analyses were performed using stata 17.0. RESULTS: A total of 2966 patients were identified from 23 studies. Transitional care improved post-stroke motor performance, walking speed and ADLs, and reduced caregiver burden. CONCLUSION: The findings suggest that provision of transitional care model implementation in patients with stroke is important because it reduces disability in stroke patients and helps to decrease caregivers' burden. IMPACT: The findings of the study emphasize the importance of transitional care programmes for stroke patients after they are discharged from the hospital and returned to their homes. To meet the needs of patients, all levels of health professionals including nurses should be aware of the discharge process and care plan.

Marital dissatisfaction and functional performance in older adults: Heterogeneity in the association by educational level.

RATIONALE: The marital relationship is an important source of the well-being of older adults. Despite existing literature on marital dissatisfaction and adverse health outcomes, little is known about whether marital dissatisfaction is associated with functional performance in older adults. OBJECTIVE: Drawing on stress process model and health behavior model, this study examined the longitudinal association between marital dissatisfaction and older adults' functional performance. Furthermore, we sought to investigate whether this association varies based on educational level. METHODS: Using seven waves (12 years) of the Korean Longitudinal Study of Ageing (KLoSA) from 2006 to 2019, this study estimated fixed effects models to account for unobserved individual-level confounders. Objectively measured hand grip strength and subjective assessments of vision, hearing, masticatory functions, as well as limitations in activities of daily living (ADLs) and instrumental activities of daily living (IADLs) were used to evaluate functional performance. An interaction model was used to determine whether educational level moderates the association. RESULTS: Fixed effects estimates revealed that marital dissatisfaction is negatively associated with grip strength, as well as masticatory, vision, and hearing functions, while also showing a positive association with limitations in ADLs and IADLs. The results of this study provided evidence on heterogeneity in the association by educational level. The associations between marital dissatisfaction and functional performance, including grip strength, mastication, and hearing, were driven primarily by those with older adults with a higher level of education. CONCLUSION: The findings of this study suggest that marital dissatisfaction is a robust predictor of functional performance in older adults. Efforts to address marital dissatisfaction has the potential to improve functional performance, particularly for older adults with higher levels of education.

Evaluating computed bony range of motion (BROM) by registering in-vitro cadaver-based functional range of motion (FROM) to a hip motion simulation.

BACKGROUND: While modern hip replacement planning relies on hip motion simulation (HMS), it lacks the capability to include soft-tissues and ligaments restraints on computed bony range of motion (BROM), often leading to an overestimation of the in-vivo functional range of motion (FROM). Furthermore, there is a lack of literature on BROM assessment in relation to FROM. Therefore, the study aimed to assess computed BROM using in-vitro cadaver-derived FROM measurements, registered to a CT-based in-house HMS, and to further investigate the effect of functional and anatomical hip joint centres (FHJC and AHJC) on BROM. METHOD: Seven limiting and three non-limiting circumducted passive FROM of four cadaver hips were measured using optical coordinate measuring machine with reference spheres (RSs) affixed to the pelvis and the femur, following CT-scan of the specimen. The RSs' centres were used to register the measured FROM in HMS, enabling its virtual recreation to compute corresponding BROM by detecting nearest bony impingement. FHJC, estimated from non-limiting FROM, was compared with AHJC to examine their positional differences and effect on BROM. RESULTS: Differences in BROM and FROM were minimal in deep flexion (3.0° ± 4.1°) and maximum internal rotation (IR) at deep flexion (3.0° ± 2.9°), but substantially greater in extension (53.2° ± 9.5°). Bony impingement was observed during flexion, and IR at deep flexion for two hips. The average positional difference between FHJC and AHJC was 3.1 ± 1.2 mm, resulting in BROM differences of 1°-13° across four motions. CONCLUSIONS: The study provided greater insight into the applicability and reliability of computed BROM in pre-surgical planning.

Effects of declines in personal mastery on self-perceived mobility, physical function, cognitive function, and depressive symptoms: a 6-year follow-up study from the Social Environment and Biomarkers of Aging Study.

OBJECTIVES: As the psychosocial competence, personal mastery helps individuals to cope with stressful life events, and this study aims to examine impacts of declines in personal mastery on healthy aging among community-dwelling middle-aged and older adults using a nationally representative cohort. METHODS: Data from 648 study participants in the Social Environment and Biomarkers of Aging Study (SEBAS) were retrieved for analysis. All participants were divided into four groups based on their baseline and changes of personal mastery (measured by the Pearlin mastery score) during the 6-year follow-up. Multivariate logistic regression models were adopted to examine associations between declines in personal mastery and indicators for healthy aging (declines in self-perceived mobility, physical function (activities of daily living (ADLs) and instrumental activities of daily living (IADLs)), cognitive function and depressive symptoms). RESULTS: After adjustments for demographics and comorbidities, those with declines in personal mastery were associated with greater risks of declines in self-perceived mobility (adjusted odds ratio (aOR) 1.50 [95% confidence interval 1.01-2.22], p < 0.05). Although the point estimate in the unadjusted models indicated similar associations between declines in personal mastery and declines in ADLs, IADLs, cognitive function or depressive symptoms, these outcomes did not reach statistical significance in the adjusted model. CONCLUSIONS: Declines in personal mastery were negatively associated with indicators related to healthy aging (particularly locomotion) in a 6-year follow-up. Further investigations are needed to explore the effects of preventing declines in personal mastery in promoting healthy aging over time.

Unmet needs for care for activities of daily living among older adults with functional disabilities in Vietnam.

Background: Given its low-middle-income status, Vietnam is experiencing a rapidly aging population. Along with this demographic trend, the care needs of older adults, particularly those with functional disabilities, have become an emerging policy issue. Purpose: This study examined the prevalence of unmet needs for care in activities of daily living (ADLs) among Vietnamese older adults with functional disabilities. Methods: We used data from the Population Change and Family Planning Survey (PCS) in 2021, which was a nationally representative survey. Cross-tabulations and logistic regressions were applied to identify older adults' individual and household factors associated with their unmet care needs. Results: Overall, 4.80% of older adults with at least one functional disability needing care to perform one or more ADLs suffered from unmet needs, of whom 2.32% did not receive any care and 3.05% received insufficient assistance. Logistic regression results revealed that age, sex, place of residence, ethnicity, marital status, education levels, and self-rated health were significantly associated with unmet needs. The higher risk of having unmet needs is associated with those in middle age (70-79), men, rural residents, ethnic minorities, currently unmarried people, those with less than a primary educational level, and those with normal or poor self-rated health. Conclusion: Attention should be paid to vulnerable older adults, such as those living in rural areas with poor health status, in order to reduce their unmet needs for ADL assistance.

Is the Health of Older Americans With a GED Equivalent to Their Peers With a High School Diploma?

The aim of this study was to identify differences in the prevalence and odds of cognitive impairment, hearing impairment, vision impairment, limitations in activities of daily living (ADLs), and ambulation limitations among three groups of older American adults: high school dropouts, General Educational Development (GED) recipients, and high school graduates. This study used secondary analysis of the nationally representative 2017 American Community Survey. The sample included 20,489 GED recipients, 154,892 high school graduates, and 49,912 high school dropouts. Our findings indicate that there is a gradient in health outcomes among older Americans, with the highest prevalence and odds of cognitive impairment, hearing impairment, vision impairment, ADL limitations, and ambulation limitations among high school dropouts, followed by GED recipients, and the lowest among high school graduates. Although GED recipients have better health outcomes than high school dropouts, there is still a significant disparity in health status between GED recipients and high school graduates.

Activities of daily living in heart failure patients and healthy subjects: when the cardiopulmonary assessment goes beyond traditional exercise test protocols.

Heart failure (HF) patients traditionally report dyspnoea as their main symptom. Although the cardiopulmonary exercise test (CPET) and 6 min walking test are the standardized tools in assessing functional capacity, neither cycle ergometers nor treadmill maximal efforts do fully represent the actual HF patients' everyday activities [activities of daily living (ADLs)] (i.e. climbing the stairs). New-generation portable metabolimeters allow the clinician to measure task-related oxygen intake (VO2) in different scenarios and exercise protocols. In the last years, we have made considerable progress in understanding the ventilatory and metabolic behaviours of HF patients and healthy subjects during tasks aimed to reproduce ADLs. In this paper, we describe the most recent findings in the field, with special attention to the relationship between the metabolic variables obtained during ADLs and CPET parameters (i.e. peak VO2), demonstrating, for example, how exercises traditionally thought to be undemanding, such as a walk, instead represent supramaximal efforts, particularly for subjects with advanced HF and/or artificial heart (left ventricular assist devices) wearers.

This article summarizes the most recent evidence on the cardiometabolic behaviours of a full spectrum of heart failure (HF) patients of different severity during their daily life activities (i.e. walking, making a bed, and taking the stairs).Heart failure patients experience symptoms (mostly dyspnoea) during daily activities that sometimes represent maximal or supramaximal exercises for them, particularly for the most severe patients.Measuring metabolic parameters (O2 intake, ventilation, and CO2 production) through appropriate devices during these activities provides a better understanding of the pathophysiological mechanisms underlying HF patients' symptoms and their adaptation. This can lead to the detection of new parameters that can become novel patient-centred prognostic markers or therapeutic targets for drugs and rehabilitation treatments.

Translation and psychometric evaluation of the Persian version of Knee Outcome Survey-Activities of Daily Living Scale (KOS-ADLS).

BACKGROUND: The present study aimed to translate and validate the Knee Outcome Survey-Activities of Daily Living Scale (KOS-ADLS) in Iran. METHODS: Following standard forward and backward translation procedure, content and face validity were tested by specialists and a sample of 32 patients. Then, in a cross sectional study, a sample of patients with knee disorders, recruited through simple sampling, completed the KOS-ADLS and the Short-Form Health Survey (SF-36) in their first visit to physiotherapy clinics in Tehran. Regarding construct validity, the Spearman's correlation (rs) and one-way ANOVA were employed to evaluate the correlations between the Persian KOS-ADLS and SF-36 subscales (convergent validity) and known groups comparison, respectively. Test-retest reliability and internal consistency were evaluated by intraclass correlation coefficient (ICC) and the Cronbach's α coefficient. RESULTS: In total 101 patients were included in the study. The mean age of patients was 42.39 (SD = 9.2). The finding indicated that the KOS-ADLS had strong correlations with SF-36 physical functioning, bodily pain subscales, and also physical component summary while it had lower correlations with other subscales of the SF-36 as expected. The KOS-ADLS was able to differentiate between the subgroups of patients who differed in BMI. The acceptable level of intraclass correlation coefficient (ICC = 0.91) and Cronbach's α coefficient (α = 0.91) was obtained for the Persian KOS-ADLS. Also no floor and ceiling effects were observed for the questionnaire. CONCLUSIONS: The Persian version of KOS-ADLS was found to be a reliable and valid outcome measure for assessing daily living activities in patients who suffer from knee pathological conditions.

Racial, Ethnic, Nativity, and Educational Disparities in Cognitive Impairment and Activity Limitations in the United States, 1998-2016.

Despite extensive research on cognitive impairment and limitations in basic activities of daily living, no study has investigated the burden of their co-occurrence (co-impairment). Using the Health and Retirement Study data and incidence-based multistate models, we study the population burden of co-impairment using three key indicators: mean age at onset, lifetime risk, and health expectancy. We examine patterns by gender, race, ethnicity, nativity, education, and their interactions for U.S. residents aged 50-100. Furthermore, we analyze what fractions of racial, ethnic, and nativity disparities in co-impairment are attributable to inequalities in educational attainment. Results reveal that an estimated 56% of women and 41% of men aged 50 will experience co-impairment in their remaining life expectancy. Men experience an earlier onset of co-impairment than women (74 vs. 77 years), and women live longer in co-impairment than men (3.4 vs. 1.9 years). Individuals who are Black, Latinx, and lower educated, especially those experiencing intersecting disadvantages, have substantially higher lifetime risk of co-impairment, earlier co-impairment onset, and longer life in co-impairment than their counterparts. Up to 75% of racial, ethnic, and nativity disparity is attributable to inequality in educational attainment. This study provides novel insights into the burden of co-impairment and offers evidence of dramatic disparities in the older U.S. population.

Eyes on privacy: acceptance of video-based AAL impacted by activities being filmed.

Introduction: The use of video-based ambient assisted living (AAL) technologies represents an innovative approach to supporting older adults living as independently and autonomously as possible in their homes. These visual devices have the potential to increase security, perceived safety, and relief for families and caregivers by detecting, among others, emergencies or serious health situations. Despite these potentials and advantages, using video-based technologies for monitoring different activities in everyday life evokes concerns about privacy intrusion and data security. For a sustainable design and adoption of such technical innovations, a detailed analysis of future users' acceptance, including perceived benefits and barriers is required and possible effects and privacy needs of different activities being filmed should be taken into account. Methods: Therefore, the present study investigated the acceptance and benefit-barrier-perception of using video-based AAL technologies for different activities of daily living based on a scenario-based online survey (N = 146). Results: In the first step, the results identified distinct evaluation patterns for 25 activities of daily living with very high (e.g., changing clothes, showering) and very low privacy needs (e.g., gardening, eating, and drinking). In a second step, three exemplary activity types were compared regarding acceptance, perceived benefits, and barriers. The acceptance and the perceived benefits of using video-based AAL technologies revealed to be higher in household and social activities compared to intimate activities. The strongest barrier perception was found for intimate activities and mainly regarded privacy concerns. Discussion: The results can be used to derive design and information recommendations for the conception, development, and communication of video-based AAL technologies in order to meet the requirements and needs of future users.

The Effect of Cognitive Task Complexity on Healthy Gait in the Walking Corsi Test.

Dual-task activities are essential within everyday life, requiring visual-spatial memory (VSM) and mobility skills. Navigational memory is an important component of VSM needed to carry out everyday activities, but this is often not included in traditional tests such as the Corsi block tapping test (CBT). The Walking Corsi Test (WalCT) allows both VSM and navigational memory to be tested together, as well as allowing measures of gait to be collected, thus providing a more complete understanding of dual-task function. The aim of this study was to investigate the effect of an increasingly complex cognitive task on gait in a healthy adult population, using the WalCT and body-worn inertial measurement unit (IMU) sensors. Participants completed both the CBT and WalCT, where they were asked to replicate increasingly complex sequences until they were no longer able to carry this out correctly. IMU sensors were worn on the shins throughout the WalCT to assess changes in gait as task complexity increased. Results showed that there were significant differences in several gait parameters between completing a relatively simple cognitive task and completing a complex task. The type of memory used also appeared to have an impact on some gait variables. This indicates that even within a healthy population, gait is affected by cognitive task complexity, which may limit function in everyday dual-task activities.

Multimorbidity patterns in older persons and their association with self-reported quality of life and limitations in activities of daily living.

BACKGROUND: As populations age, multimorbidity (the presence of two or more chronic morbidities) is increasingly more common. These evolving demographics demand further research into the identification of morbidity patterns in different settings as well as the longitudinal effects of these patterns. METHODS: Prospectively collected data on 12,755 older persons aged 65+ years were derived from The Older Persons and Informal Caregivers Survey Minimum DataSet (TOPICS-MDS, www.topics-mds.eu). Latent class analyses were performed to identify unobserved relationship patterns between morbidities in older persons. Using linear mixed models, the average difference in health-related quality of life (EQ-5D) and general quality of life scores (Cantril's Self Anchoring Ladder) as well as limitations in Activities of Daily Living and Instrumental Activities of Daily Living (ADL/IADL) were examined over a 12-month period. RESULTS: Five multimorbidity patterns were identified: sensory (n = 3882), cardio-metabolic (n = 2627), mental health (n = 920), osteo-articular (n = 4486), and system decline (n = 840). Relative to older persons in the sensory group, multimorbidity patterns did not have a strong effect on health-related quality of life, general quality of life or ADL/IADLs over a one-year period. CONCLUSIONS: The observed multimorbidity patterns are similar to others based on different methodologies and study populations. When examining the effect of such patterns on quality of life, the EQ-5D and Cantril's Ladder may be insufficient outcome measures. Further investigations into the prognostic value of morbidity patterns would be of benefit.