Multidimensional assessment of challenging behaviors in advanced stages of dementia in nursing homes-The insideDEM framework

Characterizing Walking Behaviors in Aged Residential Care Using Accelerometry, With Comparison Across Care Levels, Cognitive Status, and Physical Function: Cross-Sectional Study

Background

Walking is important for maintaining physical and mental well-being in aged residential care (ARC). Walking behaviors are not well characterized in ARC due to inconsistencies in assessment methods and metrics as well as limited research regarding the impact of care environment, cognition, or physical function on these behaviors. It is recommended that walking behaviors in ARC are assessed using validated digital methods that can capture low volumes of walking activity.

Objective

This study aims to characterize and compare accelerometry-derived walking behaviors in ARC residents across different care levels, cognitive abilities, and physical capacities.

Methods

A total of 306 ARC residents were recruited from the Staying UpRight randomized controlled trial from 3 care levels: rest home (n=164), hospital (n=117), and dementia care (n=25). Participants' cognitive status was classified as mild (n=87), moderate (n=128), or severe impairment (n=61); physical function was classified as high-moderate (n=74) and low-very low (n=222) using the Montreal Cognitive Assessment and the Short Physical Performance Battery cutoff scores, respectively. To assess walking, participants wore an accelerometer (Axivity AX3; dimensions: 23×32.5×7.6 mm; weight: 11 g; sampling rate: 100 Hz; range: ±8 g; and memory: 512 MB) on their lower back for 7 days. Outcomes included volume (ie, daily time spent walking, steps, and bouts), pattern (ie, mean walking bout duration and alpha), and variability (of bout length) of walking. Analysis of covariance was used to assess differences in walking behaviors between groups categorized by level of care, cognition, or physical function while controlling for age and sex. Tukey honest significant difference tests for multiple comparisons were used to determine where significant differences occurred. The effect sizes of group differences were calculated using Hedges g (0.2-0.4: small, 0.5-0.7: medium, and 0.8: large).

Results

Dementia care residents showed greater volumes of walking (P<.001; Hedges g=1.0-2.0), with longer (P<.001; Hedges g=0.7-0.8), more variable (P=.008 vs hospital; P<.001 vs rest home; Hedges g=0.6-0.9) bouts compared to other care levels with a lower alpha score (vs hospital: P<.001; Hedges g=0.9, vs rest home: P=.004; Hedges g=0.8). Residents with severe cognitive impairment took longer (P<.001; Hedges g=0.5-0.6), more variable (P<.001; Hedges g=0.4-0.6) bouts, compared to those with mild and moderate cognitive impairment. Residents with low-very low physical function had lower walking volumes (total walk time and bouts per day: P<.001; steps per day: P=.005; Hedges g=0.4-0.5) and higher variability (P=.04; Hedges g=0.2) compared to those with high-moderate capacity.

Conclusions

ARC residents across different levels of care, cognition, and physical function demonstrate different walking behaviors. However, ARC residents often present with varying levels of both cognitive and physical abilities, reflecting their complex multimorbid nature, which should be considered in further work. This work has demonstrated the importance of considering a nuanced framework of digital outcomes relating to volume, pattern, and variability of walking behaviors among ARC residents.

Evaluation on service quality in institutional pensions based on a novel hierarchical DEMATEL method for PLTSs

In recent years, to address the continued aging of China’s population, the Chinese government has focused on the issue of pensions through a series of pension policies. The traditional system of institutional pensions is facing serious challenges, with a variety of novel pension modes placing them under enormous pressure. Furthermore, the development of institutional pensions has been restricted by many factors, such as long construction cycles and high fees, meaning that this traditional system no longer meets the pension needs of the elderly. Improving the service quality of institutional pensions is inevitable for future progress. Thus, identifying the key factors that influence the service quality of institutional pensions, and understanding the relationships between these factors, is hugely significant. Furthermore, traditional decision-making trial and evaluation laboratory (DEMATEL) method can not solve this problem because the number of factors is too large. To address these issues, we establish an evaluation system for Chinese pension institutions, and propose a hierarchical DEMATEL model based on probabilistic linguistic term sets (PLTSs), which can help decision makers to find the key factors influencing service quality in institutional pensions and deal with the evaluation problem with a large number of criteria. The proposed hierarchical DEMATEL model based on PLTSs fully reflects experts’ preferences and evaluation information, and is able to identify the directions in which China’s pension institutions should improve their quality of service. In addition, we use the best-worst method (BWM) to calculate the importance values of each subsystem, which makes the cause-effect relationship between subsystems more reasonable than the traditional DEMATEL method. Finally, we apply our method to evaluate nursing homes in Zhenjiang, Jiangsu province and propose some managerial implications.

Comparison of behaviors characteristic of autism spectrum disorder behaviors and behavioral and psychiatric symptoms of dementia

BACKGROUND

Similarities exist in behavioral expression of autism spectrum disorder (ASD) and Alzheimer's disease and related dementias (ADRD). The purpose of this study was to assess presence of behavioral and psychiatric symptoms of dementia (BPSD) and ASD-like behaviors in adults with ADRD.

METHODS

Using a cross-sectional design, data from University of Kentucky Alzheimer's Disease Center participant cohort were used. Hierarchical linear regression was used to assess (1) the relationship between ASD-like behaviors (measured by the Gilliam Autism Rating Scale-Second Edition, GARS-2) and BPSD measured by the Neuropsychiatric Inventory (NPI), and (2) the relationship between ASD-like behaviors and dementia severity (measured by the Clinical Dementia Rating [CDR] sum of boxes), when controlling for BPSD.

RESULTS

Complete data were available for 142 participants. Using α of 0.05, analyses identified ASD behaviors were significantly associated with BPSD severity ratings (r = 0.47; p < 0.001) and dementia severity (r = 0.46; p < 0.001). GARS-2 explained 6.1% (p < 0.001) of variance in CDR sum of boxes when controlling for NPI and other covariates.

DISCUSSION

There is significant overlap in behaviors characteristic of ASD and BPSD as assessed by the NPI and GARS-2, despite the use of these instruments in disparate developmental vs. aging settings. ASD behaviors appear to not be solely present in early childhood as a manifestation of ASD but are also present in older adults with neurodegenerative cognitive impairment. Such associations warrant additional research into causation, assessment, and behavioral interventions to further enable new therapeutic approaches targeting ASD behaviors across the lifespan.

Dementia and COVID-19: A Case Report and Literature Review on Pain Management

The coronavirus disease 2019 (COVID-19) pandemic imposes an unprecedented lifestyle, dominated by social isolation. In this frame, the population to pay the highest price is represented by demented patients. This group faces the highest risk of mortality, in case of severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection, and they experience rapid cognitive deterioration, due to lockdown measures that prevent their disease monitoring. This complex landscape mirrors an enhancement of neuropsychiatric symptoms (NPSs), with agitation, delirium and reduced motor performances, particularly in non-communicative patients. Due to the consistent link between agitation and pain in these patients, the use of antipsychotics, increasing the risk of death during COVID-19, can be avoided or reduced through an adequate pain treatment. The most suitable pain assessment scale, also feasible for e-health implementation, is the Mobilization-Observation-Behaviour-Intensity-Dementia (MOBID-2) pain scale, currently under validation in the Italian real-world context. Here, we report the case of an 85-year-old woman suffering from mild cognitive impairment, subjected to off-label treatment with atypical antipsychotics, in the context of undertreated pain, who died during the pandemic from an extensive brain hemorrhage. This underscores the need for appropriate assessment and treatment of pain in demented patients.

Agitation Detection in People Living with Dementia using Multimodal Sensors

People Living with Dementia (PLwD) often exhibit behavioral and psychological symptoms of dementia; with agitation being one of the most prevalent symptoms. Agitated behaviour in PLwD indicates distress and confusion and increases the risk to injury to both the patients and the caregivers. In this paper, we present the use of wearable devices to detect agitation in PLwD. We hypothesize that combining multi-modal sensor data can help in building better classifiers to identify agitation in PLwD in comparison to a single sensor. We present a unique study to collect motion and physiological data from PLwD. This multi-modal sensor data is subsequently used to build predictive models to detect agitation in PLwD. The results on Random Forest for 28 days of data from PLwD show a strong evidence to support our hypothesis and highlight the importance of using multi-modal sensor data for detecting agitation events amongst them.

Automated sensor-based detection of challenging behaviors in advanced stages of dementia in nursing homes

INTRODUCTION

Sensor-based assessment of challenging behaviors in dementia may be useful to support caregivers. Here, we investigated accelerometry as tool for identification and prediction of challenging behaviors.

METHODS

We set up a complex data recording study in two nursing homes with 17 persons in advanced stages of dementia. Study included four-week observation of behaviors. In parallel, subjects wore sensors 24 h/7 d. Participants underwent neuropsychological assessment including MiniMental State Examination and Cohen-Mansfield Agitation Inventory.

RESULTS

We calculated the accelerometric motion score (AMS) from accelerometers. The AMS was associated with several types of agitated behaviors and could predict subject's Cohen-Mansfield Agitation Inventory values. Beyond the mechanistic association between AMS and behavior on the group level, the AMS provided an added value for prediction of behaviors on an individual level.

DISCUSSION

We confirm that accelerometry can provide relevant information about challenging behaviors. We extended previous studies by differentiating various types of agitated behaviors and applying long-term measurements in a real-world setting.

Rastreio cognitivo em estruturas residenciais para pessoas idosas no Concelho de Miranda do Corvo, Portugal

Resumo Com o objetivo de efetuar o rastreio do perfil cognitivo dos residentes em Estruturas Para Idosos no Concelho de Miranda do Corvo, avaliaram-se 174 participantes recorrendo ao Mini-Mental State Examination (MMSE) (n=96) e ao diagnóstico de demência reportado nos prontuários dos pacientes (n=78). Verificou-se, através do MMSE, que 41,7% dos inquiridos apresentavam pontuações sugestivas de déficit cognitivo. Adicionando a este resultado o diagnóstico de demência reportado nos prontuários dos pacientes, a percentagem subiu para 67,8% (n=118). A comparação dos nossos resultados com os obtidos a nível nacional revelou que essa percentagem foi significativamente superior (p<0,001). A escolaridade foi um fator preditivo da pontuação do MMSE (p=0,001). Conclui-se que a elevada prevalência de suspeita de déficit cognitivo e de demência revelada no nosso estudo deve remeter para a reflexão sobre a adequação dos cuidados prestados e sobre a ausência/escassez de programas de estimulação cognitiva nas estruturas residenciais para idosos. Nesse sentido, torna-se imperativo implementar avaliação cognitiva regular e instituir programas de intervenção que promovam a conservação e melhoria do funcionamento cognitivo em pessoas idosas institucionalizadas de zonas desfavorecidas.

A Tablet App- and Sensor-Based Assistive Technology Intervention for Informal Caregivers to Manage the Challenging Behavior of People With Dementia (the insideDEM Study): Protocol for a Feasibility Study

Background

Despite the enormous number of assistive technologies (ATs) in dementia care, the management of challenging behavior (CB) of persons with dementia (PwD) by informal caregivers in home care is widely disregarded. The first-line strategy to manage CB is to support the understanding of the underlying causes of CB to formulate individualized nonpharmacological interventions. App- and sensor-based approaches combining multimodal sensors (actimetry and other modalities) and caregiver information are innovative ways to support the understanding of CB for family caregivers.

Objective

The main aim of this study is to describe the design of a feasibility study consisting of an outcome and a process evaluation of a newly developed app- and sensor-based intervention to manage CB of PwD for family caregivers at home.

Methods

In this feasibility study, we perform an outcome and a process evaluation with a pre-post descriptive design over an 8-week intervention period. The Medical Research Council framework guides the design of this feasibility study. The data on 20 dyads (primary caregiver and PwD) are gathered through standardized questionnaires, protocols, and log files as well as semistructured qualitative interviews. The outcome measures (neuropsychiatric inventory and Cohen-Mansfield agitation inventory) are analyzed by using descriptive statistics and statistical tests relevant to the individual assessments (eg, chi-square test and Wilcoxon signed-rank test). For the analysis of the process data, the Unified Theory of Acceptance and Use of Technology is used. Log files are analyzed by using descriptive statistics, protocols are analyzed by using documentary analysis, and semistructured interviews are analyzed deductively using content analysis.

Results

The newly developed app- and sensor-based AT has been developed and was evaluated until July in 2018. The recruitment of dyads started in September 2017 and was concluded in March 2018. The data collection was completed at the end of July 2018.

Conclusions

This study presents the protocol of the first feasibility study to encompass an outcome and process evaluation to assess a complex app- and sensor-based AT combining multimodal actimetry sensors for informal caregivers to manage CB. The feasibility study will provide in-depth information about the study procedure and on how to optimize the design of the intervention and its delivery.

International Registered Report Identifier (IRRID)

DERR1-10.2196/11630

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials.

Mapping Movement: Applying Motion Measurement Technologies to the Psychiatric Care of Older Adults

PURPOSE OF REVIEW

Recent advances in technology have changed the landscape of treatment for adults with mental illness. This review highlights technological innovations that may improve care for older adults with mental illness and neurocognitive disorders through the measurement and assessment of physical motion. These technologies include wearable sensors (such as smart watches and Fitbits), passive motion sensors, and smart home models that incorporate both active and passive motion technologies.

RECENT FINDINGS

Clinicians have evaluated motion measurement technologies in older adults with depression, dementia, anxiety, and schizophrenia. Results from studies in dementia populations suggest that motion measurement technologies can assist clinicians in diagnosing dementia earlier through the evaluation of gait, balance, and postural kinematics. Motion detection technologies can also be used to identify mood episodes at an earlier stage by detecting subtle behavioral changes. Clinicians may use the objective data provided by technologies such as accelerometers to identify illnesses earlier, which may inform treatment decisions. The data may be used as a suitable surrogate marker for detecting depression in older adults, predicting the likelihood of falls, or quantifying physical activity in older adults with chronic mental illnesses or anxiety. Motion-based technologies also have the potential to detect physical activity for older adults residing in nursing homes. Wearable technologies are generally well tolerated in older adults, although the use of new technology and electronic health data could involve privacy and security concerns among this vulnerable population.