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Emergency Medical Services (EMS) in Israel was called on to vaccinate the most vulnerable population—the elderly in assisted living facilities and their caregivers. Two parameters led the operation: (1) maximum use of the scarce COVID-19 vaccine, and (2) minimizing the time it took to reach this entire population. We present the process of vaccinating 126 245 people in two weeks at 756 locations countrywide, focusing on the planning and logistics of this operation. Resilience, flexible logistics, and dedicated personnel provided an efficient public health operation.

Funding Information: This work was supported by the Päivikki and Sakari Sohlberg Founda-tion and the Björkqvist Fund. The work was done in the framework of the Gerontology Research Center (GEREC) and the Centre of Excellence in Research on Ageing and Care (CoE AgeCare). We would like to thank all the people living and working in and visiting the ALF for giving us a window into their everyday life in the facility. We especially wish to thank staff members for helping us arrange the group discussion and interviews and all the residents who took part in them. Funding Information: This work was supported by the Päivikki and Sakari Sohlberg Foundation and the Björkqvist Fund. The work was done in the framework of the Gerontology Research Center (GEREC) and the Centre of Excellence in Research on Ageing and Care (CoE AgeCare). We would like to thank all the people living and working in and visiting the ALF for giving us a window into their everyday life in the facility. We especially wish to thank staff members for helping us arrange the group discussion and interviews and all the residents who took part in them. Publisher Copyright: © The Authors. Assisted living facilities are presented as the older person’s home but, at the same time, defined by institutional and communal characteristics. Using Goffman’s (1974/1986) concept of frame, we aim to find out how home, institution and community frames define social roles and shape social relationships and interaction in assisted living facilities. Directed content analysis was used to analyse the data consisting of observations, one group discussion and ten individual interviews with residents in an assisted living facility. We found that the home frame was characterised by meaningfulness, spontaneousness and informality of social relationships and interaction, whereas the institution frame by indifference and formality of them. Acknowledging and tolerating other people was not only central in the community frame but also dissociating oneself from some people. Frames can shed light on how different interpretations of the multifaceted social environment of assisted living affect homeliness of the facility and well-being of the residents.

OBJECTIVES Maximizing quality of life (QoL) is the ultimate goal of long-term dementia care. However, routine QoL measurement is rare in nursing home (NH) and assisted living (AL) facilities. Routine QoL measurement might lead to improvements in resident QoL. Our objective was to assess the feasibility of using DEMQOL-CH, completed by long-term care staff in video calls with researchers, to assess health-related quality of life (HrQoL) of NH and AL residents with dementia or other cognitive impairment. DESIGN Cross-sectional study. SETTING AND PARTICIPANTS We included a convenience sample of 5 NHs and 5 AL facilities in the Canadian province of Alberta. Forty-two care staff who had worked in the facility for ≥3 months completed DEMQOL-CH assessments of 183 residents who had lived in the facility for 3 months or more and were aged ≥65 years. Sixteen residents were assessed independently by 2 care staff to assess inter-rater reliability. METHODS We assessed HrQoL in people with dementia or other cognitive impairment using DEMQOL-CH, and assessed time to complete, inter-rater reliability, internal consistency reliability, and care staff ratings of feasibility of completing the DEMQOL-CH. RESULTS Average time to complete DEMQOL-CH was

One of the most difficult components of stroke therapy is regaining hand mobility. This research describes a preliminary approach to robot-assisted hand motion therapy. Our objectives were twofold: First, we used machine learning approaches to determine and describe hand motion patterns in healthy people. Surface electrodes were used to collect electromyographic (EMG) data from the forearm’s flexion and extension muscles. The time and frequency characteristics were used as parameters in machine learning algorithms to recognize seven hand gestures and track rehabilitation progress. Eight EMG sensors were used to capture each contraction of the arm muscles during one of the seven actions. Feature selection was performed using the Pareto front. Our system was able to reconstruct the kinematics of hand/finger movement and simulate the behaviour of every motion pattern. Analysis has revealed that gesture categories substantially overlap in the feature space. The correlation of the computed joint trajectories based on EMG and the monitored hand movement was 0.96 on average. Moreover, statistical research conducted on various machine learning setups revealed a 92% accuracy in measuring the precision of finger motion patterns.

Purpose This paper aims to provide an evidence assessment and narrative synthesis of literature regarding the key characteristics of older people living in service-integrated housing (SIH) facilities and their “accommodation journey”. Design/methodology/approach A rapid evidence assessment was conducted: 22 research publications met the inclusion criteria and were analysed using narrative synthesis. Findings The quality of studies in this area is low, but consistency across components of the results of studies included in the review is apparent. Results suggest key characteristics of older people that drive moves into SIH are a decline in health, increased dependency, increased health service use and carer burden. Suggested key characteristics of SIH residents are high levels of health problems, dependency and health service use, but high self-reported health and well-being. Results indicate that the key driver for older people leaving SIH is a lack of workforce competency to manage further declines in health and dependency status. Research limitations/implications Current policy may not realise or account for the complex health and care needs of SIH residents. Investment into integrated care, robust community health services and workforce development to facilitate a comprehensive assessment approach may be required to support residents to remain in SIH and live well. Further longitudinal studies are required to map the progression of SIH residents’ health status in detail over time to provide an understanding of preventative and enablement support, development of care pathways and workforce planning and development requirements. Originality/value This evidence assessment is the first to consider the accommodation journey of older people residing in SIH.

This phenomenological study involved individual, unstructured interviews with older adults. Eleven participants were recruited from independent living, assisted living, and community center setting...

Background: Community-based residential settings (e.g., assisted living facilities and retirement communities), are increasing, where vulnerable older adults are living as they age and die. Despite prevalent serious illness, functional impairment, and dementia among residents, the mix and types of built-in services available are not known. Objective: To classify older adults in community-based residential settings by the types of services available and examine associations between service availability and hospice use and location of death. Design: Pooled cross-sectional analysis. Setting: Medicare Current Beneficiary Survey data (2002–2018). Subjects: U.S. adults 65 years of age and older, who lived in a community-based residential setting and died between 2002 and 2018 (N = 1006). Measurements: Availability (yes/no) of nursing care, medication assistance, meals, laundry, cleaning, transportation, and recreation. Results: Our sample resided in assisted living facilities (32.0%), retirement communities (29.0%), senior citizen housing (13.7%), continuing care facilities (13.5%), and other (11.8%). Four classes of individuals with distinct combinations of available services were identified: 48.2% lived in a residence with all measured services available; 29.1% had availability of all services, except nursing care and medication assistance; 12.6% had availability of only recreation and transportation services; and 10.1% had minimal/no service availability. Of the 51.8% of older adults residing in settings without clinical services, more than half died at home and fewer than half died with hospice. Conclusions: The majority of older adults who die in community-based residential settings do not have access to built-in clinical services. Palliative care training for staff in these settings may be warranted, given variable rates of hospice use and high rates of home death.

Our goal was to learn about monitoring and enforcement of state assisted living (AL) regulations. Using survey responses provided in 2019 from administrative agents across 48 states, we described state agency structures, accounted for operational processes concerning monitoring and enforcement, and documented data collecting and public reporting efforts. In half of the states, oversight of AL was dispersed across three or more agencies, and administrative support varied in terms of staffing and budget allocations. Operations also varied. While most agents could deploy a range of monitoring and enforcement tools, less than half compiled data concerning inspections, violations, and penalties. Less than 10 states shared such information in a manner that was easily accessible to the public. Future research should determine how these varied administrative structures and processes deter or contribute to AL communities’ efforts to implement regulations designed to promote quality of life and provide for the safety of residents.

Background: Older adults living in assisted living facilities (ALFs) are at risk for physical and mental health decline that precipitates nursing home placement. There is a need for an exercise program that improves the quality of life (QOL) for older adults living in the ALFs. This study’s primary purpose was to investigate the feasibility of an Enriched tai chi (ETC) intervention program on improving the QOL of older adults living in an ALF. Method: A convenience sample of six older adults living in the same ALF attended the ETC program for 16 consecutive sessions two times per week for 8 weeks. A pre-test and post-test one-group design was used. The 36-Item Short Form Survey and the Beck depression inventory were used to measure QOL and mood at baseline, the 4th week, and the 8th week of the study. Results: Wilcoxon sign rank test on pre and postintervention SF-36 scores were significant (p < .05). Pre-test and post-test intervention changes in mood were significantly improved (BDI; p < .05). Conclusion: These findings suggest the ETC program may be a feasible intervention to improve the QOL of older adults in ALFs, warranting the need for further research.

Dissertação de mestrado em Engenharia Informática, A área de eHealth/Assisted Living tem vindo a crescer com a necessidade de melhorar a qualidade de vida de pessoas que precisam de acompanhamento médico permanente (e.g., doença crónica) ou ocasional (e.g., pós-operatório, pandemia), de forma presencial ou à distância. No entanto, a tendência é manter as pessoas em casa o máximo tempo possível e não nas instituições, evitando o perigo de contaminação, precavendo a rutura dos serviços de saúde, e garantindo simultaneamente maior conforto e bem-estar ao utente. Contudo, estas pessoas precisam de ser acompanhadas e ter acesso a serviços de saúde de qualidade, tal como se estivessem nas instituições. Os serviços de telemedicina e telemonitorização servem este propósito, permitindo a cuidadores formais e/ou informais estar em contacto com os seus doentes, acompanhá-los remotamente em tempo real e prevenir situações de maior risco, agindo rapidamente em casos de urgência. No âmbito específico da telemonitorização, esta pode ser clínica e/ou não clínica, mais focada no controlo de sinais vitais ou apenas no acompanhamento da pessoa com base noutro tipo de informação pessoal (e.g., atividade, sono, localização), respetivamente. No caso particular desta dissertação, o objetivo é desenhar, especificar e implementar um serviço que ofereça conforto e segurança usando essencialmente informação não clínica e assegure o acompanhamento remoto de pessoas de idade avançada que vivam ou passem muito tempo sozinhas. A necessidade de criação de uma ferramenta deste tipo deve-se ao facto de, cada vez mais, se pretender apostar na prevenção e segurança das pessoas, sobretudo das pessoas de idade que se encontram em situações de alguma fragilidade (e.g., por doença, por isolamento), mas simultaneamente tentar passar um sentimento de companhia, mesmo à distância, procurando preservar ao máximo a sua autonomia. Neste contexto, o projeto pretende explorar cenários mistos de telemonitorização, através de informação proveniente de sensores ligados à casa edispositivos wearables, criando o conceito de Confort@Home, ou seja, um conceito de saúde e bem-estar centrado na pessoa, na sua casa e no ambiente circundante. A oferta de serviços a considerar incluirá in formação de localização dentro e fora de casa, dados adicionais provenientes de dispositivos a selecionar e notificações/alertas; na lógica da aplicação serão definidas as situações e condições que espelhem os possíveis riscos e falta de segurança do idoso, e enviados alertas para o seu cuidador/familiar, de forma a facilitar a vida de ambos no dia-a-dia. Como demonstração do conceito, será desenvolvida uma das vertentes do Confort@Home que se materializa numa aplicação Web fornecida em ambiente cloud que permita a cuidadores informais monitorizar os seus familiares/dependentes com base na sua localização., The area of eHealth/Assisted Living has been growing with the need to improve the quality of life of people who need permanent (e.g., chronic disease) or occasional (e.g., post-operative, pandemic) medical monitoring, in person or remotely. However, the trend is to keep people at home for as long as possible, rather than in institutions, avoiding the danger of contamination, preventing the breakdown of health services, and at the same time ensuring greater comfort and well-being for the user. Nevertheless, these people need to be accompanied and have access to quality health services, just as if they were in the institutions. Telemedicine and telemonitoring services serve this purpose, allowing formal and/or informal caregivers to stay in touch with their patients, to monitor them remotely in real time, and to prevent higher risk situations by acting quickly in cases of emergency. In the specific scope of telemonitoring, this monitoring may be clinical and/or non-clinical, i.e., more focused on monitoring vital signs or only on monitoring the person based on other types of personal information (e.g., activity, sleep, location), respectively. In the particular case of this dissertation, the goal is to design, specify and implement a service that offers comfort and security using essentially non-clinical information and ensures remote monitoring of elderly people who live or spend a lot of time alone. The need to create a tool of this type is due to the fact that, increasingly, we want to focus on the prevention and safety of people, especially the elderly who are in situations of some fragility (e.g., due to illness, isolation), but simultaneously trying to pass on a sense of companionship, even at a distance, trying to preserve their autonomy as much as possible. In this context, the project aims to explore mixed telemonitoring scenarios, through information from sensors connected to the house and wearable devices, creating the concept of Confort@Home, that is, a concept of health and well-being centered on the person, their home and the surrounding environment. The service offering to be considered will include location information inside and outside the home, additional data from devices to be selected, and notifications/alerts; in the application logic, situations and conditions that mirror possible risks and lack of safety of the elderly person will be defined, and alerts will be sent to the caregiver/family member, in order to facilitate the life of both on a daily basis. As a demonstration of the concept, one of the aspects of the Confort@Home will be developed, materialized in an web application provided in an cloud environment that will allow informal caregivers to monitor their relatives/dependents based on their location.

Ambient Assisted Living (AAL) applications are related to the use of technology to improve wellbeing and independence of older adults. These applications commonly are supported by Internet of Things technologies and require communication between devices and people in a scenario characterized by mobility and heterogeneity of devices and data. Besides the communication between devices and people, AAL applications also have strict requirements related to security, usability, and management. Named Data networking (NDN) is a content-centric approach created to address the current and future network requirements. NDN architecture allows the adoption of new services intrinsic to the network and decouples the content from its location. This elementary change in network structure allows solving many problems and challenges faced by AAL applications. In our work, we intend to enumerate the main requirements of AAL applications, identify limitations of current networking architectures and protocols (e.g., SDN) and evaluate how future Internet architectures, such as NDN, can address open issues to boost the adoption of AAL applications.

The growing share of the population over the age of 65 is putting pressure on the social health insurance system, especially on institutions that provide long-term care services for the elderly or to people who suffer from chronic diseases or mental disabilities. This pressure can be reduced through the assisted living of the patients, based on an intelligent system for monitoring vital signs and home automation. In this regard, since 2008, the European Commission has financed the development of medical products and services through the ambient assisted living (AAL) program—Ageing Well in the Digital World. The SmartCare Project, which integrates the proposed Computer Vision solution, follows the European strategy on AAL. This paper presents an indoor human activity recognition (HAR) system based on scene understanding. The system consists of a ZED 2 stereo camera and a NVIDIA Jetson AGX processing unit. The recognition of human activity is carried out in two stages: all humans and objects in the frame are detected using a neural network, then the results are fed to a second network for the detection of interactions between humans and objects. The activity score is determined based on the human–object interaction (HOI) detections.

This research paper reviews the methodologies used to monitor and enable the elderly population to live a safe lifestyle. The four different methodologies reviewed primarily revolve around the concept of Ambient Intelligence and behavior monitoring where-in the elderly person’s activities of daily living are monitored and deviations are analyzed as possible emergencies. Most of the methodologies were found to have good success rates and confidence levels and areas of improvements were also determined. A survey was also initiated to about 60 participants from different geographies and demographics to know about the awareness and acceptance of such technologies. While awareness will need to be built up, most respondents were in favor of self-reliance for elderly people. An opinion of an expert working in the field of elderly care was also taken and it corroborated the findings from literature review and survey results that the method of assisted living using sensor based ambient intelligence will gain prevalence to provide well-being of elderly people.

This qualitative study aims at identifying the motivations and barriers that seniors and family members consider while relocating to an assisted living facility in Portugal. Moreover, this study identifies the various factors as well as the antecedents that can be grouped under push, pull motivations and intervening barriers. The data of the present study was collected by performing 18 semistructured interviews of seniors ageing at home, and in a facility, as well as with family members. The data was transcribed and coded thematically. The findings validate the role of family members in the decision-making process of relocation to an assisted living facility, which is directly influenced by senior’s (physical and financial) dependence on their family members. This study further indicates that, health conditions, family dependency, poor social well-being, dysfunctional houses, negative experiences of external assistance at home are the push factors considered while relocating to an assisted living facility in Portugal, whereas housing and location, socio-psychological barriers, services and amenities, and price to quality and price to location are the pull factors. With respect to barriers, family, economic, and facility are the important primary barriers, whereas sociocultural and psychological barriers is considered to be a secondary barrier; considering that this barrier was identified having senior homes (i.e., Lars) in mind. This paper intends to develop a comprehensive model that points out relevant aspects of senior relocation to an assisted living facility which can further be explored and validated by quantitative analysis. O objectivo do estudo qualitativo é identificar as motivações e barreiras que os idosos e os membros da família encontram ao considerar a relocalização para uma instalação de vida assistida em Portugal. Este documento vai mais longe para identificar os vários factores, juntamente com os antecedentes que podem ser agrupados sob as motivações que aproximam ou afastam as barreiras de intervenção. Os dados do estudo seguinte foram recolhidos através da realização de um total de 18 entrevistas semiestruturadas de idosos bem como dos seus familiares. Os dados foram transcritos e codificados tematicamente. Os resultados deste estudo validam o papel dos membros da família no processo de tomada de decisão de mudança para uma instalação de vida assistida e este papel é directamente proporcional à dependência (física e financeira) dos seniores em relação aos seus familiares. Este estudo indica ainda que as condições de saúde, dependência familiar, bem-estar social deficiente, casas disfuncionais, experiências negativas de assistência externa em casa, e habitação e localização, sócio-psicologia, serviços e comodidades e preço para a qualidade e preço para a localização são, respectivamente, factores impulsionadores e atractivos, considerados durante a mudança para uma instalação de vida assistida em Portugal. No que diz respeito às barreiras, as instalações familiares, económicas, são as barreiras primárias importantes, enquanto que as sócioculturais e psicológicas ainda podem ser consideradas como uma barreira, mas não dada a mesma ponderação que a anterior, considerando o facto de esta barreira ter sido apontada tendo em mente as casas de idosos. Este estudo tem como intenção desenvolver um modelo compreensivel que aponte aspectos relevantes da relocalização de idosos para uma instalação de vida assistida que possa ser mais explorado e validado através de uma análise quantitativa.

Over the past decade, WiFi CSI-based device-free sensing technology has shown great potential in smart homes, assisted living, and many other applications. While model-based device-free sensing approaches analyze and recognize human behaviors by constructing mathematical relationships among WiFi devices, environment, human position/posture, and received channel state information, they have attracted great attention because of the interpretable physical meaning and the ability to guide the WiFi-based sensing system design. In this paper, we retrospect two general-purpose sensing models, i.e., the Fresnel zone model and CSI-ratio model, and demonstrate how these two models are leveraged to extract insightful properties and support a variety of device-free sensing applications.

Assisted living provides housing and long-term care services to more than 811,000 older adults in the United States daily and is regulated by the states. This article describes changes in the speci...

Care interactions are essential to understand and respond to resident needs in assisted living (AL). The factors that influence care interactions in AL have not been directly examined. In this study, we explored the factors associated with the quality of care interactions in AL. It was hypothesized that resident functional status, agitation, depression, and resistiveness to care as well as facility size and ownership would be significantly associated with the quality of care interactions in AL after controlling for resident demographics (age, gender, marital status), comorbidities, and cognition. To test the hypothesis, we utilized baseline data including 379 residents from the second and third cohorts recruited in a randomized trial titled ‘Dissemination and Implementation of Function Focused Care for Assisted Living Using the Evidence Integration Triangle’. Regression analysis was performed using a stepwise method. The care interactions were mostly positive (mean=6.3; range = 0-7). Resident agitation and facility ownership were significantly associated with care interactions and accounted for 8.2% of the variance. Increased resident agitation was associated with negative or neutral interaction while for-profit ownership was associated with positive interactions. To promote positive care interactions, staff should be educated about strategies to minimize resident agitation (e.g., calm posture and respectful listening) and encouraged to engage with residents using resident-centered care and communication approach. Findings also suggest the need to work towards optimizing care interactions in nonprofit stings. Future research could further explore the impact of facility-level factors (e.g., staffing ratios, staff longevity, and job satisfaction) on care interactions.

One of the most important lifestyle risk factors for many chronic conditions in the older age, low physical activity has shown to have significant impact on the sustainability of national welfare in many developed countries. Technology-based assisted living solutions can effectively be used to enable older adults to optimise their health-related quality of life, as well as to promote an active and healthy longevity. This paper describes vINCI—an interdisciplinary research project to actively support assisted living for older adults via state-of-the-art assistive technologies—which seamlessly deploys an ambient intelligence environment to integrate wearable devices, networking, software, and personalised services. It entails clinical validation and feedback at home and residential care facilities via a cloud microservices platform. Underpinned by blockchain technologies, multiple wearable devices, apps, and cameras securely capture the anonymised facets of different life events, whilst machine learning models create individualised user profiles to analyse any decrease in the perceived health-related quality of life typically associated with old age. Two controlled pilots are being conducted with 80 participants at older adult facilities in Romania and Cyprus. By incorporating clinical validation and feedback from specialised practitioners, the vINCI technologies enable older adults not only to self-evaluate their physical activity level, but also to change their behaviours and lifestyle in the long-term.

Objective COVID-19 disproportionately impacts residents in long-term care facilities. Our objective was to quantify the presence and magnitude of antibody response in vaccinated, older adult residents at assisted living, personal care, and independent living communities. Design A cross-sectional quality improvement study was conducted March 15 – April 1, 2021 in the greater Pittsburgh region. Setting and Population: Participants were older adult residents at assisted living, personal care, and independent living communities, who received mRNA-based COVID-19 vaccine. Conditions that impair immune responses were exclusionary criteria. Methods Sera were collected to measure IgG anti-SARS-CoV-2 antibody level with reflex to total anti-SARS-CoV-2 immunoglobulin levels, and blinded evaluation of SARS-CoV-2 pseudovirus neutralization titers. Descriptive statistics, Pearson correlation coefficients, and multiple linear regression analysis evaluated relationships between factors potentially associated with antibody levels. Spearman correlations were calculated between antibody levels and neutralization titers. Results All participants (N = 70) had received two rounds of vaccination and were found to have antibodies with wide variation in relative levels. Antibody levels trended lower in males, advanced age, current use of steroids, and longer length of time from vaccination. Pseudovirus neutralization titer levels were strongly correlated (P < .001) with Beckman Coulter antibody levels (D614 G NT50, rs = 0.91; B.1.1.7 [UK] NT50, rs = 0.91). Conclusions and Implications Higher functioning, healthier, residential older adults mounted detectable antibody responses when vaccinated with mRNA-based COVID-19 vaccines. Data suggests some degree of immunity is present during the immediate period following vaccination. However, protective effects remain to be determined in larger studies as clinical protection is afforded by ongoing adaptive immunity, which is known to be decreased in older adults. This study provides important preliminary results on level of population risk in older adult residents at assisted living, personal care, and independent living communities to inform reopening strategies, but are not likely to be translatable for residents in nursing homes.

Background and Objectives Assisted living (AL) constitutes an important sector of residential long-term care, yet there has been limited research about the impact of the coronavirus disease 2019 (COVID-19) pandemic in this setting. This qualitative study sought to understand the impact of the early stages of the pandemic (February–August 2020) from AL administrators’ perspectives. Research Design and Methods Semistructured phone interviews were conducted with 40 AL administrators in Oregon. A stratified sampling method emphasizing rurality, profit status, Medicaid acceptance, and memory care designation was used to maximize variation in perspectives. We asked 8 questions aimed at understanding the impact of the COVID-19 pandemic on their roles and AL residents and their families, as well as AL operations, such as staffing and resource procurement. Audio-recorded interviews were transcribed and analyzed using an iterative thematic analysis. Results We identified 3 themes that characterize AL administrators’ response to COVID-19: emotion and burnout management, information management, and crisis management. Based on their experiences, administrators made suggestions for managing future crises. Discussion and Implications Our findings demonstrate the slow-burning but devastating impact of the COVID-19 pandemic in AL communities similar to recent findings in nursing homes. Coupled with the limited resources, perceived external pressures, and the ongoing pandemic, many administrators were managing but not thriving in these domains. AL as a care setting, and the role of administrators, requires more scholarly and policy attention, especially regarding emergency preparedness and response.

Common Bond Communities (CBC) is a nonprofit organization that provides housing for low-income individuals and families. CBC utilized the Live Well at Home-Rapid Screen (LWAH-RS) to identify the risks for nursing home admission or assisted living entry among housing residents aged 60 or above. Drawing data from 842 assessments, we studied how well the LWAH-RS predicted moves to nursing homes or assisted living settings. Cox regression models showed that the LWAH-RS did predict which residents would move to a care setting. Every 1-point higher in the LWAH-RS assessment score was associated with a 38% higher risk of moving to a higher-level care facility due to health issues. Given this demonstrated predictive validity in a real-world setting, we suggest more systematic approaches for housing practitioners to combat low assessment completion rates and unclear protocols for actions based on the scores.

Background Using Ambient Assisted Living sensors to detect acute stress could help people mitigate the harmful effects of everyday stressful situations. This would help both the healthy and those affected more by sudden stressors, e.g., people with diabetes or heart conditions. The study aimed to develop a method for providing reliable stress detection based on heart rate variability features extracted from portable devices. Methods Features extracted from portable electrocardiogram sensor recordings were used for training various classification algorithms for stress detection purposes. Data were recorded in a clinical trial with 7 participants and two stressors, the Trier Social Stress Test and the Stroop colour word test, both validated by standardised questionnaires. Different heart rate variability feature sets (all, time-domain and non-linear only, frequency-domain only) were tested to investigate how classification performance is affected, in addition to various time window length setups and participant-wise training sessions. The accuracy and F1 score of the trained models were compared and analysed. Results The best results were achieved with models using time-domain and non-linear heart rate variability features with 5-min-long overlapping time windows, yielding 96.31% accuracy and 96.26% F1 score. Shorter overlapping windows had slightly lower performance, with 91.62–94.55% accuracy and 91.77–94.55% F1 score ranges. Non-overlapping window configurations were less effective, with both accuracy and F1 score below 88%. For participant-wise learning, average F1 scores of 99.47%, 98.93% and 96.1% were achieved for feature sets using all, time-domain and non-linear, and frequency-domain features, respectively. Conclusion The tested stress detector models based on heart rate variability data recorded by a single electrocardiogram sensor performed just as well as those published in the literature working with multiple sensors, or even better. This suggests that once portable devices such as smartwatches provide reliable hear rate variability recordings, efficient stress detection can be achieved without the need for additional physiological measurements.

Rehabilitation robots are becoming an important means of assisted living for the elderly, and the appearance of rehabilitation robots directly affects the willingness of the elderly to interact with the robots. Much of the current research on robot appearance preferences relies solely on subjective evaluations, which are relatively cheap, but do not reach deep into the brain to get an accurate grasp of how humans respond to robot appearance. Using electroencephalogram signal and questionnaire survey, we studied the preference of the elderly for abstract and figurative robots. The experimental materials are derived from the pictures of 10 robots in the market. The electroencephalogram signal are collected by BrainVision Recorder and processed by BrainVision Analyzer, as well as SPSS statistical analysis. Experiment shows that the peak of figurative robot pictures is higher and the fluctuation is more intense from 350 ms to 600 ms in the central region and the right half of parietal region. While the peak of abstract robot pictures is higher and the fluctuation is more intense in the prefrontal region, and the difference between abstract robot and figurative robot is not obvious in the occipital region. Based on the electroencephalogram signal and experimental results, it provides the possibility for objective preference evaluation of the elderly to the robot designed features.

An aging population is increasingly prevalent in both developed and developing countries, raising a series of social challenges and economic burdens. In particular, more elderly people are staying alone at home than are living with people who can take care of them. Therefore, assisted living (AL) and health-care monitoring (HM) can be critical issues in this era of human-centered artificial intelligence (AI). In this context, we aim to provide an encompassing review summarizing the state-of-the-art works combining AI and the Internet of Things (IoT) to help the elderly live easier and better. We systematically and comprehensively compare paradigms in terms of methodologies and application scenarios. The pros and cons among these technologies are discussed in detail. Then, we summarize current achievements and indicate their limitations. Finally, perspectives on highly promising future work are presented.

Protocol for integrative review

Adolescent asylum seekers have been an independent, yet understudied group in the German Youth welfare service since 2016. Due to the separation from their familiar surroundings, young people must establish new connections with their peers in supervised living groups. However, little is known about this special group in the youth welfare system as there are only a few studies covering the situation of adolescent asylum seekers in residential groups. In our study, we apply a mixed‐methods approach to analyse the self‐understanding of adolescent asylum seekers, social comparisons between the perceived own group and outside group and link them with data on the emergence of friendship ties among adolescent asylum seekers. Analytically, we describe institutional factors and narratives (qualitative focus) and access structural mechanisms (demographics, network organization principles) via network regression models (quantitative focus). Our results indicate a strong influence of a high level of upstreamness in the network in the tie creation and less influence from factors like age and religion. Following this, our study provides first indications about patterns of connection and separation in this niche group.

Recognition of the human activities in videos has gathered numerous demands in various applications of computer vision like Ambient Assisted Living, intelligent surveillance, Human-Computer interaction. One of the most pioneering techniques for Human Detection in Video Surveillance based on deep learning and this project mainly focuses on various approaches based on that. This paper provides an idea of solution to use video surveillance more effectively, by detecting any humans present and notifying the concerned people. The deep learning model, preferred for fast computation, Convolution Neural Network is used by stacking 3 blocks of layers on fully connected layers. This provided an identification of humans and naïve approach to eliminate inanimate human like objects such as mannequins.

Objectives Social relationships are important for older adults’ well-being, including those who live in assisted living (AL) communities. This study explores coresident networks within an AL community and identifies factors associated with residents’ social ties. Methods Acquaintance and companionship networks within the community are described using cross-sectional survey data (N = 38). We use inferential network statistical methods to estimate parameters for factors associated with residents’ acquaintance and companionship ties. Results Residents reported an average of 10 acquaintances and almost 4 companionships with other residents in the sample. The likelihood a resident had an acquaintance was associated with higher levels of cognitive functioning (p < .05), higher levels of physical limitations (p < .01), living in the AL community for a longer time (p < .01), and less frequent contact with outside family and friends (p < .05). Acquaintances were more likely between residents who moved in around the same time as each other (p < .01), lived on the same floor (p < .001), or had similar levels of physical limitations (p < .05). Companionships were more likely to be reported by male residents (p < .05) and residents with higher levels of cognitive functioning (p < .05) or depressive symptoms (p < .05). Longtime residents were more popular as companions (p < .01). Companionships were more likely between residents who lived on the same floor (p < .001) or were similar in age (p < .01). Discussion This research contributes to the literature of older adults’ nonkin social relationships by providing detailed descriptions of the acquaintance and companionship networks within an AL community, quantifying correlates of residents’ social ties, and distinguishing between acquaintances and companions.

Ingrid Goudriaan,1,2 Leonieke C van Boekel,1 Marjolein EA Verbiest,1 Joost van Hoof,3,4 Katrien G Luijkx1 1Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, the Netherlands; 2Innovation and Quality, BrabantZorg, Oss, the Netherlands; 3Chair of Urban Ageing, Faculty of Social Work & Education, The Hague University of Applied Sciences, The Hague, the Netherlands; 4Institute of Spatial Management, Faculty of Environmental Engineering and Geodesy, Wrocław University of Environmental and Life Sciences, Wrocław, PolandCorrespondence: Ingrid GoudriaanTranzo, Tilburg University, PO Box 90153, Tilburg, 5000 LE, the NetherlandsTel +31 (0) 612 692 435Email ingrid.goudriaan@xs4all.nlAbstract: Light therapy for older persons with dementia is often administered with light boxes, even though indoor ambient light may more comfortably support the diverse lighting needs of this population. Our objective is to investigate the influence of indoor daylight and lighting on the health of older adults with dementia living in long-term care facilities. A systematic literature search was performed within PubMed, CINAHL, PsycINFO, Web of Science and Scopus databases. The included articles (n=37) were published from 1991 to 2020. These articles researched the influence of existing and changed indoor light conditions on health and resulted in seven categories of health outcomes. Although no conclusive evidence was found to support the ability of indoor light to decrease challenging behaviors or improve circadian rhythms, findings of two studies indicate that exposure to (very) cool light of moderate intensity diminished agitation. Promising effects of indoor light were to reduce depressive symptoms and facilitate spatial orientation. Furthermore, there were indications that indoor light improved one’s quality of life. Despite interventions with dynamic lighting having yielded little evidence of its efficacy, its potential has been insufficiently researched among this study population. This review provides a clear and comprehensive description of the impact of diverse indoor light conditions on the health of older adults with dementia living in long-term care facilities. Variation was seen in terms of research methods, (the description of) light conditions, and participants’ characteristics (types and severity of dementia), thus confounding the reliability of the findings. The authors recommend further research to corroborate the beneficial effects of indoor light on depression and to clarify its role in supporting everyday activities of this population. An implication for practice in long-term care facilities is raising the awareness of the increased lighting needs of aged residents.Keywords: lighting, Alzheimer’s disease, assisted living, nursing homes, indoor daylight, light therapy

Objective Little is known about the prevalence of serious mental illness (SMI) in assisted living (AL) communities in the United States. Trends in the prevalence of SMI in AL communities were examined over time and in relationship to characteristics such as dual eligibility and health conditions. Within- and between-state variability of SMI in AL was also examined. Design Samples of Medicare beneficiaries who lived in the 48 contiguous states were created: individuals who resided in the community, in a nursing home (NH), and in an AL community on December 31st of each year (2007–2017). We conducted univariate analysis to display the trends in SMI over time in AL compared with NHs and the community. To demonstrate intrastate variability, we examined the prevalence of SMI for each state. We described within-nation and within-state variability using a Lorenz curve and GINI coefficients, respectively. Results The prevalence of SMI in AL increased by 54%, rising from 7.4% in 2007 to 11.4% in 2017. Residents with SMI were more likely to be dually eligible for Medicare and Medicaid than residents without SMI. The prevalence of SMI in AL ranged from to 3.2% in Wyoming to 33.1% in New York. Approximately 10% of AL communities had over half of the sample's AL residents with SMI. Conclusion Given the increased proportion of residents with SMI in AL, research is needed into the mental health and social care needs of this population. Analysis is needed to uncover reasons for variations among states.

Demographically, the proportion of elderly people in the population is increasing worldwide. The proportion of elderly people (aged over 60) has been rising and in 2015 the proportion was reported to be 12.3% and is expected to reach 16.5% of the world population in the year 2030. Additionally, elderly people are more vulnerable to many diseases and heart failure persists as the most common cause of mortality. However, while acknowledging this threat, elderly people have a longer life expectancy and live more independently in the environment of their choice. To meet this challenge, smart devices are considered a solution to monitor heart rates of elderly people and detect any abnormal activity that may require action to be taken. In order to assess how this solution could be implemented, the aim of this paper was to compare the accuracy of heart rate readings by conducting experiments on five different models of smart devices: (A) Vivosmart, (B) Philips, (C) Pulsimeter, (D) Fitbit-Surge, and (E) Chest Strap. A comparison of the results demonstrated that the Smart watch devices detect heart rates more accurately when compared to Chest Straps and the Pulsoximeter, with a variation of $$\pm$$ 10%. The results of this paper suggest that replacing current devices (such as chest strap and finger device) with Smart watches as a primary solution for heart rate monitoring to support healthcare and for Ambient Assisted Living (AAL) would significantly reduce cost incurred by physically visiting elderly individuals on a daily, weekly or even monthly basis.

Older people express a preference for home and community-based care over skilled nursing, realizing that preference, however, is dependent upon having those options available. The present exploratory study uses publicly available data to understand if the geographic availability of long-term care options-skilled nursing, assisted living, home health, and homemaker/companion services-are equally distributed by demographics in Florida. Regression analyses showed that the percent 65 and older and the percent in poverty in a county were not related to long-term care availability or quality. Findings indicate that Hispanic older people have less access to nursing home beds, greater access to home health and homemaker/companion agencies, and tend to live in counties with a greater number of assisted living facility (ALF) deficiencies while Black older people have greater access to homemaker services. Rural counties had lower rates of home health and homemaker/companion agencies and fewer ALF deficiencies. The 65 and older population would benefit from the increased availability of long-term care options near the communities in which they live.

Older adults residing in long term care (LTC) settings commonly experience apathy, a neuropsychiatric condition with adverse consequences of increased morbidity and mortality. Activities that combine social, physical and cognitive stimuli are most effective in engaging older adults with apathy but are time consuming and require significant staff resources. We present the results from an initial pilot field study of our socially assistive robotic (SAR) system, Ro-Tri, capable of multi-modal interventions to foster social interaction between pairs of older adults. Seven paired participants attended two sessions a week for three weeks. Sessions consisted of robot-mediated triadic interactions with three types of activities repeated once over the 3 weeks. Ro-Tri gathered quantitative interaction data, head pose, vocal sound, and physiological signals to automatically evaluate older adults’ activity and social engagement. Ro-Tri functioned smoothly without any technical issues. Older adults had > 90% attendance and 100% completion rate and remained engaged with the system throughout the study duration. Participants’ visual attention toward the SAR system and their partners increased 7.2% and 4.7%, respectively, with their interaction effort showing an increase of 2.9%. Older adults and LTC staff had positive perceptions with the system. These initial results demonstrate Ro-Tri’s ability to engage older adults, encourage social human-to-human interaction, and assess the changes using quantitative metrics. Future studies will determine SAR’s impact on apathy in LTC older adults.

Objectives: This project examined administrator processes, barriers, and facilitators for conducting advance care planning in assisted living. Method: Data from qualitative interviews with 27 administrators from seven diverse assisted living communities in the metropolitan Atlanta area were linked with descriptive and administrative data collected from each site and analyzed using thematic analysis. Results: Although administrators generally contended with a lack of staff training and stakeholders’ reluctance to discuss advance care planning and end-of-life care, important facilitators of advance care planning in some assisted living communities included periodic follow-up discussions of residents’ wishes and successfully educating consumers about the importance of planning. Three study communities whose administrators discussed planning with residents and informal caregivers during regular care plan meetings had more advance care planning documents on file. Discussion: These findings demonstrate the potential for nonmedical organizations, such as assisted living, to successfully promote advance care planning among their members.

Assisted living has become more widely used by dual-eligible Medicare beneficiaries as states try to rebalance their long-term services and supports away from institutional (nursing home) care. In an analysis of 2014 Medicare data for 506,193 adults who live in large (25+ beds) assisted living communities, we found wide variability among states in the share of assisted living residents who were dual-eligible, ranging from 6% in New Hampshire to over 40% in New York. This variation is strongly correlated with the Medicaid support for assisted living care: In states with a Medicaid state plan option covering services in assisted living or both a state plan and waiver, the percent of assisted living residents with dual-eligibility was more than 10 percentage points higher than in states with neither a state plan nor waiver. Findings provide a basis for understanding the role of Medicaid financing in access to assisted living for duals.

Dear Editor, We commend Mauldin et al. (2020) for their recent article titled “Supports and gaps in federal policy for addressing racial and ethnic disparities among long-term care facility residen...

BACKGROUND/OBJECTIVES: Care-partner support affects outcomes among assisted living (AL) residents. Yet, little is known about care-partner support and its effects on hospitalization during post-acute care transitions. This study examined the variation in care-partner support and its impact on hospitalizations among AL residents receiving Medicare home health (HH) services. DESIGN: Analysis of national data from the Outcome and Assessment Information Set, Medicare claims, Area Health Resources File and the Social Deprivation Index File. SETTING: AL facilities and Medicare HH agencies in the U.S. PARTICIPANTS: 741,926 Medicare HH admissions of AL residents in 2017. MEASUREMENTS: Care-partner support during the HH admission was measured based on the type and frequency of assistance from AL staff in seven domains (i.e., activities of daily living [ADL], instrumental ADLs [IADL], medication administration, treatment, medical equipment, home safety, and transportation). Care-partner support in each domain was measured as “assistance not needed” (reference group), “Care-partner currently provides assistance”, “care-partner need additional training / support to provide assistance” (i.e., inadequate care-partner support), and “care-partner unavailable / unlikely to provide assistance” (i.e., unavailable care-partner support). Outcome was time-to-hospitalization during the HH admission. RESULTS: Among the 741,926 Medicare HH admissions of AL residents, inadequate care-partner support was identified for all 7 domains that ranged from 13.1% (for transportation) to 49.8% (for treatment), and care-partner support was unavailable from 0.9% (for transportation) to 11.0% (for treatment). In Cox proportional hazard models adjusted for patient covariates and geography, compared with “assistance not needed”, having inadequate and unavailable care-partner support was related to increased risk of hospitalization by 8.9% (treatment [Hazard Ratio / HR =1.089, p

Microservice-based systems promote agility and rapid business development. Some features, such as fast time-to-market, scalability and optimal response times, have encouraged stakeholders to get more involved in the development and implementation of microservices architectures in order to translate their business vision into the implementation of the architecture. Although some techniques allow the inclusion of the stakeholders’ perspective in the design of microservice architectures, few proposals consider such perspectives in the selection and evaluation of technologies that implement microservice architectures. Indeed, the qualities that characterize microservice-based systems strongly depend on the suitable selection of technologies, such as application frameworks and platforms. This article proposes a collaborative technique that includes stakeholders and software architects in the selection and evaluation of application frameworks and platforms to implement microservice-based systems. We evaluated the technique in an industrial case of design and implementation of an Ambient-Assisted Living (AAL) system, which combines microservice architecture and Internet-of-Medical-Things (IoMT) sensors. The case results indicate that the proposed technique supported stakeholders in the pragmatic evaluation of alternative technological solutions. Additionally, it allowed the implementation of an AAL system that satisfies the quality specifications of stakeholders and end-users. This initial study suggests that actively including stakeholders in the implementation of microservice-based systems allows architects to make design decisions that better consider stakeholders viewpoints as well as managing their expectations.

The detection of Generalized Tonic Clonic Seizures (GTCS) and Falls is of utmost importance due to the increase in prevalence of epilepsy and Sudden Death in Epileptic Patients during CoVID-19 pandemic, and prevention of serious injuries in Fall risk groups such as elderly requiring continuous monitoring for disease management and assisted living etc. Monitoring of Activities of Daily Living (ADLs) can assist in the detection of symptoms and onset of neurological disorders such as Alzheimer’s, stroke, and epileptic seizures. With a host of embedded sensors, improved memory, enhanced processing capabilities and availability to masses, smartphones can be used for Human Activity Recognition (HAR) through continuous monitoring of ADLs. This paper presents a tri-axial accelerometer-based approach to detect and classify activities performed by individuals by applying machine learning algorithms including RF, J48, NB, LMT and SVM to movement data. Movement data is collected in real-time from the embedded accelerometer of a smartphone worn by individual on upper-left arm in unconstraint environment. It is pre-processed using time and frequency domain analysis and spatial domain features are computed. Supervised machine learning techniques are applied to classify ADLs into five classes based on the intensity of movements: Stationary, Light Ambulatory, Intense Ambulatory, GTCS and Falls. We also used training data from MyNeuroHealth dataset collected from 23 individuals including epilepsy patients. Based on gathered results, Random Forest outperforms other classifiers with classification accuracy of 99.6% for stationary, 81.5% for light ambulatory, 99.8% for intense ambulatory and GTCS, and 97.2% for Falls corresponding to training data of 14000 samples. To date, activity classification in our system has been implemented on cloud instead of mobile phone application as subjects are using smartphones with dissimilar software and hardware specifications for assisted living applications.

The significant increase in the number of individuals with chronic ailments (including the elderly and disabled) has dictated an urgent need for an innovative model for healthcare systems. The evolved model will be more personalized and less reliant on traditional brick-and-mortar healthcare institutions such as hospitals, nursing homes, and long-term healthcare centers. The smart healthcare system is a topic of recently growing interest and has become increasingly required due to major developments in modern technologies, especially in artificial intelligence (AI) and machine learning (ML). This paper is aimed to discuss the current state-of-the-art smart healthcare systems highlighting major areas like wearable and smartphone devices for health monitoring, machine learning for disease diagnosis, and the assistive frameworks, including social robots developed for the ambient assisted living environment. Additionally, the paper demonstrates software integration architectures that are very significant to create smart healthcare systems, integrating seamlessly the benefit of data analytics and other tools of AI. The explained developed systems focus on several facets: the contribution of each developed framework, the detailed working procedure, the performance as outcomes, and the comparative merits and limitations. The current research challenges with potential future directions are addressed to highlight the drawbacks of existing systems and the possible methods to introduce novel frameworks, respectively. This review aims at providing comprehensive insights into the recent developments of smart healthcare systems to equip experts to contribute to the field.

In a world with an increasingly aging population, design researchers and practitioners can play an essential role in shaping better future societies, by designing environments, tools, and services that positively influence older adults’ everyday experiences. The World Health Organization (WHO) has proposed a framework called Healthy Ageing, which can be adopted as the basis for designing for an aging society. There are, however, many challenges in achieving this goal. This article addresses one of these challenges identified by WHO, which is overcoming ageism as a form of discrimination based on age. In contrast with most other types of discrimination, ageism is not always easy to detect and overcome because of its generally implicit nature. This paper investigates adopting storytelling as a method for detecting implicit ageism and proposes a co-design process that utilizes this method to better address older adults’ needs and requirements. The use of this method is discussed through two example case studies aimed at improving the design of assistive services and technologies for aging people. The findings from these case studies indicate that the proposed method can help co-design teams better identify possible implicit ageist biases and, by doing so, try to overcome them in the design process.

Life expectancy has increased, so the number of people in need of intensive care and attention is also growing. Falls are a major problem for older adult health, mainly because of the consequences they entail. Falls are indeed the second leading cause of unintentional death in the world. The impact on privacy, the cost, low performance, or the need to wear uncomfortable devices are the main causes for the lack of widespread solutions for fall detection and prevention. This work present a solution focused on bedtime that addresses all these causes. Bed exit is one of the most critical moments, especially when the person suffers from a cognitive impairment or has mobility problems. For this reason, this work proposes a system that monitors the position in bed in order to identify risk situations as soon as possible. This system is also combined with an automatic fall detection system. Both systems work together, in real time, offering a comprehensive solution to automatic fall detection and prevention, which is low cost and guarantees user privacy. The proposed system was experimentally validated with young adults. Results show that falls can be detected, in real time, with an accuracy of 93.51%, sensitivity of 92.04% and specificity of 95.45%. Furthermore, risk situations, such as transiting from lying on the bed to sitting on the bed side, are recognized with a 96.60% accuracy, and those where the user exits the bed are recognized with a 100% accuracy., La esperanza de vida ha aumentado, por lo que también crece el número de personas que necesitan cuidados y atención intensivos. Las caídas son un problema importante para la salud de los adultos mayores, principalmente por las consecuencias que conllevan. Las caídas son, de hecho, la segunda causa principal de muerte no intencional en el mundo. El impacto en la privacidad, el coste, el bajo rendimiento o la necesidad de llevar dispositivos incómodos son las principales causas de la falta de soluciones generalizadas para la detección y prevención de caídas. Este trabajo presenta una solución centrada en la hora de dormir que aborda todas estas causas. La salida de la cama es uno de los momentos más críticos, especialmente cuando la persona sufre un deterioro cognitivo o tiene problemas de movilidad. Por ello, este trabajo propone un sistema que monitorice la posición en la cama con el fin de identificar situaciones de riesgo lo antes posible. Este sistema también se combina con un sistema automático de detección de caídas. Ambos sistemas trabajan en conjunto, en tiempo real, ofreciendo una solución integral para la detección y prevención automática de caídas, que es de bajo costo y garantiza la privacidad del usuario. El sistema propuesto fue validado experimentalmente con adultos jóvenes. Los resultados muestran que las caídas se pueden detectar, en tiempo real, con una precisión del 93,51 %, una sensibilidad del 92,04 % y una especificidad del 95,45 %. Además, las situaciones de riesgo, como pasar de estar tumbado en la cama a sentarse al lado de la cama, se reconocen con un 96,60 % de precisión, y aquellas en las que el usuario sale de la cama se reconocen con un 100 % de precisión. El sistema propuesto fue validado experimentalmente con adultos jóvenes. Los resultados muestran que las caídas se pueden detectar, en tiempo real, con una precisión del 93,51 %, una sensibilidad del 92,04 % y una especificidad del 95,45 %. Además, las situaciones de riesgo, como pasar de estar tumbado en la cama a sentarse al lado de la cama, se reconocen con un 96,60 % de precisión, y aquellas en las que el usuario sale de la cama se reconocen con un 100 % de precisión. El sistema propuesto fue validado experimentalmente con adultos jóvenes. Los resultados muestran que las caídas se pueden detectar, en tiempo real, con una precisión del 93,51 %, una sensibilidad del 92,04 % y una especificidad del 95,45 %. Además, las situaciones de riesgo, como pasar de estar tumbado en la cama a sentarse al lado de la cama, se reconocen con un 96,60 % de precisión, y aquellas en las que el usuario sale de la cama se reconocen con un 100 % de precisión

Background: Several benefits of working in a self-organizing team, such as higher job satisfaction and better en-gagement to work have been demonstrated in previous studies.Objective: To examine whether those employees working in a self-organizing team have higher job satisfaction and lower turnover intentions compared to those in non-self-organized teams. Further, to test whether psycho-social factors defined by the Job Demand-Control model would function as mediators.Design: A cross-sectional survey study.Setting(s): Home care and assisted living facilities (with 24-h assistance).Participants: Licensed practical nurses (N = 377), registered nurses, therapists and managers (N = 183), and other employees (N = 31) in services for older people.Methods: A survey for employees working in services for older people and who were either in the self-organized teams or in the non-self-organized teams. Data was analyzed using linear regression and mediation analyses.Results: Those employees who worked in a self-organizing team were more satisfied with their job and had lower turnover intentions compared to those in a non-self-organizing team (mean [SD] 3.9 [1.0] vs. 3.7 [1.0], p = 0.006 and 2.2 [1.2] vs. 2.5 [1.3], p = 0.006, respectively). Moreover, job demands and job strain partially mediated the effect of self-organizing teamwork on job satisfaction (Average causal mediation effect [95%CI] 0.09 [0.02-0.15] and 0.10 [0.03-0.18], respectively), as well as on turnover intentions (Average causal mediation effect [95%CI] -0.08 [-0.15 to -0.01] and -0.20 [-0.18 to-0.03], respectively).Conclusions: In the context of older people care services, working in self-organizing teams may enhance employee wellbeing by lowering job demands and job strain, but not by improving job control. Based on the findings of this study, self-organization seems beneficial, however, it requires real autonomy for the teams and team building.Tweetable abstract: Self-organizing teamwork increases job satisfaction and decreases turnover intentions via lower job demands and strain in older people care.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

OBJECTIVES: Admission to assisted living (AL) is on the rise in the United States, and adjustment to this new environment can be challenging for older adults. To date, few studies have explored the ways in which older adults may be able to ease the transition to AL by minimizing relocation-related losses. Consequently, we explored the potential for the components of the framework Selective Optimization with Compensation (SOC) to facilitate successful adjustment to AL. METHOD: Ninety-one recently-relocated residents of eight assisted living facilities in Alabama and Maryland were interviewed about their transition and adjustment to AL. Using the SOC framework as an analytical lens, directed content analysis identified emergent themes. RESULTS: Fifty-six participants were identified as using SOC-based strategies. Five major themes emerged: Relationships with Others, Health and Wellness, Normalcy, Entertainment, and Growth and Meaning. The theme of Health and Wellness was reported by nearly half of SOC users. Fifty-five percent reported at least one instance of elective selection, 51.8% reported loss-based selection, 48.2% reported optimization, and 41.1% reported compensation. CONCLUSION: These findings offer insight into strategies that may facilitate successful adaptation to AL and other long-term care settings. This represents an important first step in identifying ways older adults might cope with the different forms of loss and role adjustment that accompany the move from a private residence to assisted living.