Exploring active ageing in a community-based living environment: an ethnographic study in the Western Norway context.

Background: Age-friendly environments intend to promote active ageing by facilitating social, mental, and physical participation. This could potentially delay the onset of chronic complex conditions, enabling people to live longer independently at home, and prevent loneliness. This study investigates a community-based living environment in Norway called Helgetun and aims to explore how it can facilitate active ageing. Method: We chose an ethnographic approach consisting of observation, informal conversations, and in-depth semi-structured interviews with 15 residents (11 female, 4 male, ages 62-84). We analysed the data using reflexive thematic analysis. Result: We developed three themes on facilitating active ageing in this living environment: maintaining self-identity, experiencing growth and development, and feeling a sense of belonging. These themes were related to physical activity levels, social engagement, and overall satisfaction with the living environment. Maintaining self-identity concerned getting a new role in life as well as access to meaningful activities. Experiencing growth and development involved being exposed to new activities, learning new skills, and experiencing mastery. Lastly, feeling a sense of belonging meant feeling safe and part of a group, as well as receiving social support and help. This feeling of social connectedness and safety was reflected in their experience with the COVID-19 pandemic, in which most felt relatively unaffected, suggesting that this way of living could increase reliance among this age group. Conclusion: Having a flexible structure, adapting to the core needs and individual resources of the residents, can facilitate active ageing in community-based living environments. Our findings contribute to the growing evidence that these environments increase social and physical engagement, whilst reducing social isolation and loneliness. These findings may be particularly relevant in a Norwegian context-where older adults are less dependent on family for care-and are meant as grounding points for policymakers to reflect upon designing future senior living.

Feedback System Analysis of a Multicomponent Intervention on Dyads of Home-Dwelling Persons With Dementia and Their Caregivers: Results From the LIVE@Home.Path Trial.

Background and Objectives: Proper symptom management, informal caregiver support, and service innovation are required to reduce dementia care burden. The objective of this study is to investigate the effect of the multicomponent LIVE (Learning, Innovation, Volunteering, Empowerment) intervention on caregiver experience of the self-perceived care situation, coordinator performance, and informal care time. Research Design and Methods: We conducted a 24-month multicomponent, stepped-wedge randomized control trial including dyads of people ≥65 years with mild-to-moderate dementia with minimum weekly contact with their informal caregivers in Norway. The intervention was implemented by municipal coordinators over a 6-month period. This study investigates the first 6-month period (September 2019-March 2020) of the trial, due to the coronavirus disease 2019 (COVID-19) pandemic. Primary outcomes are changes in provision of informal care time assessed by Resource Utilization in Dementia Care (RUD) and informal caregiver experience assessed by the Clinical Global Impression of Change (CGIC). We use logistic regression and feedback system analysis to assess the reach of the multicomponent intervention. Results: A total of 280 dyads were included at baseline, mean age of the person with dementia was 81.8 years, and 62.5% were female. After 6 months, the feedback system analysis reveals that the caregivers randomized to the intervention period reported improved caregiver situation (CGIG-T: intervention 0.63 (SD 2.4) vs control -0.43 (SD 1.7), p < .01), even though informal care time for activities of daily living was not reduced (p = .31). Informal caregivers registered a positive change for the Learning, Innovation, and Empowerment components, while no change was found for Volunteer support. Discussion and Implications: Findings illustrate the usefulness of dementia care coordinators that provide regular follow-up. We also show that complex intervention studies benefit from applying feedback system analysis. Meeting the needs of persons with dementia and their caregivers is a complex process that requires coordinated input from health services and user communities. Clinical Trial Registration Number: NCT04043364.

The Difficulties of Managing Pain in People Living with Frailty: The Potential for Digital Phenotyping.

Pain and frailty are closely linked. Chronic pain is a risk factor for frailty, and frailty is a risk factor for pain. People living with frailty also commonly have cognitive impairment, which can make assessment of pain and monitoring of pain management even more difficult. Pain may be sub-optimally treated in people living with frailty, people living with cognitive impairment and those with both these factors. Reasons for sub-optimal treatment in these groups are pharmacological (increased drug side effects, drug-drug interactions, polypharmacy), non-pharmacological (erroneous beliefs about pain, ageism, bidirectional communication challenges), logistical (difficulty in accessing primary care practitioners and unaffordable cost of drugs), and, particularly in cognitive impairment, related to communication difficulties. Thorough assessment and characterisation of pain, related sensations, and their functional, emotional, and behavioural consequences ("phenotyping") may help to enhance the assessment of pain, particularly in people with frailty and cognitive impairment, as this may help to identify who is most likely to respond to certain types of treatment. This paper discusses the potential role of "digital phenotyping" in the assessment and management of pain in people with frailty. Digital phenotyping is concerned with observable characteristics in digital form, such as those obtained from sensing-capable devices, and may provide novel and more informative data than existing clinical approaches regarding how pain manifests and how treatment strategies affect it. The processing of extensive digital and usual data may require powerful algorithms, but processing these data could lead to a better understanding of who is most likely to benefit from specific and targeted treatments.

Oral symptoms in dying nursing home patients. Results from the prospective REDIC study.

BACKGROUND: The mouth is a central organ for communication and fluid intake, also for dying nursing home patients. This study describes the prevalence and severity of oral symptoms from nursing home admission until the day of perceived dying and the day of death. METHODS: A prospective, longitudinal cohort study including 696 patients who were admitted to 47 Norwegian nursing homes in 35 municipalities. During the first year of their stay, 189 died (27%), of whom 82 participants were assessed on the day they were perceived as dying and 134 on the day of death. Mouth care, nutrition, and bedsores were assessed with the Residents' Assessment Instrument for nursing homes (RAI-NH) and palliative care (RAI-PC). Pain intensity was assessed with the Mobilization-Observation-Behaviour-Intensity-Dementia-2 Pain Scale (MOBID-2). RESULTS: The proportion of patients with ≥ 6 oral symptoms increased from 16% when perceived as dying to 20% on the day of death (P = 0.001). On the day of death, xerostomia (66%), dysphagia (59%), and mastication problems (50%) were the most frequently observed oral symptoms. Only 16% received mouth care every hour and 12% were in pain during this procedure. Compared to people without dementia, those with a diagnosis of dementia at admission (N = 112, 86%) had xerostomia and mastication problems more frequently (50% vs. 73%; 32% vs. 56% (P = 0.038), respectively) on the day of death. CONCLUSIONS: The high extent of oral symptoms such as xerostomia, dysphagia, and mastication problems underline the need for systematic assessment and improved oral palliative care for dying nursing home patients with dementia. TRIAL REGISTRATION: Clinicaltrials.gov NCT01920100 08/08/2013. First submission to BMC oral 15/03/2023.

Digital phenotyping by wearable-driven artificial intelligence in older adults and people with Parkinson's disease: Protocol of the mixed method, cyclic ActiveAgeing study.

BACKGROUND: Active ageing is described as the process of optimizing health, empowerment, and security to enhance the quality of life in the rapidly growing population of older adults. Meanwhile, multimorbidity and neurological disorders, such as Parkinson's disease (PD), lead to global public health and resource limitations. We introduce a novel user-centered paradigm of ageing based on wearable-driven artificial intelligence (AI) that may harness the autonomy and independence that accompany functional limitation or disability, and possibly elevate life expectancy in older adults and people with PD. METHODS: ActiveAgeing is a 4-year, multicentre, mixed method, cyclic study that combines digital phenotyping via commercial devices (Empatica E4, Fitbit Sense, and Oura Ring) with traditional evaluation (clinical assessment scales, in-depth interviews, and clinical consultations) and includes four types of participants: (1) people with PD and (2) their informal caregiver; (3) healthy older adults from the Helgetun living environment in Norway, and (4) people on the Helgetun waiting list. For the first study, each group will be represented by N = 15 participants to test the data acquisition and to determine the sample size for the second study. To suggest lifestyle changes, modules for human expert-based advice, machine-generated advice, and self-generated advice from accessible data visualization will be designed. Quantitative analysis of physiological data will rely on digital signal processing (DSP) and AI techniques. The clinical assessment scales are the Unified Parkinson's Disease Rating Scale (UPDRS), Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory (GAI), Apathy Evaluation Scale (AES), and the REM Sleep Behaviour Disorder Screening Questionnaire (RBDSQ). A qualitative inquiry will be carried out with individual and focus group interviews and analysed using a hermeneutic approach including narrative and thematic analysis techniques. DISCUSSION: We hypothesise that digital phenotyping is feasible to explore the ageing process from clinical and lifestyle perspectives including older adults and people with PD. Data is used for clinical decision-making by symptom tracking, predicting symptom evolution, and discovering new outcome measures for clinical trials.

Understanding Pain and Agitation Through System Analysis Algorithms in People With Dementia. A Novel Explorative Approach by the DIGI.PAIN Study.

Background: Many people with dementia (PwD) live and die with undiagnosed and untreated pain and are no longer able to report their suffering. Several pain assessment tools have been developed, tested, and implemented in clinical practice, but nursing home patients are reported to be still in pain. Clinicians and research groups worldwide are seeking novel approaches to encode the prediction, prevalence, and associations to pain in PwD. Participants: The data in this analysis are acquired from the COSMOS study, a cluster-randomized controlled trial (2014 to 2015), aimed to improve the quality of life in nursing home patients (N = 723) through the implementation of a multicomponent intervention. We utilize baseline data of PwD (N = 219) with complete datasets of pain and agitation. Method: Systems analysis explores the relationship between pain and agitation using the Mobilization-Observation-Behavior-Intensity-Dementia (MOBID-2) Pain Scale, Cohen-Mansfield Agitation Inventory (CMAI), and Neuropsychiatric Inventory-Nursing Home version (NPI-NH). For each patient, the individualized continuous time trajectory, and rates of change of pain and agitation are estimated. We determine the relationship between these rates by analyzing them across the entire group. Results: We found that the new analysis method can generate individualized estimations for pain and agitation evolution for PwD, as well as their relationship. For 189 of 219 PwD, results show that whenever pain increases or decreases, agitation does too, with the same rate. The method also identifies PwD for whom pain or agitation remains constant while the other varies over time, and patients for whom agitation and pain do not change together. The algorithm is scalable to other variables and compatible with wearable devices and digital sensors. Conclusion: We presented a new approach to clinical data analysis using systems concepts and algorithms. We found that it is possible to quantify and visualize relationships between variables with a precision only dependent on the precision of measurements. This method should be further validated, but incipient results show great potential, especially for wearable-generated continuous data.

A software tool for modeling and simulation of numerical P systems.

UNLABELLED: A P system represents a distributed and parallel bio-inspired computing model in which basic data structures are multi-sets or strings. Numerical P systems have been recently introduced and they use numerical variables and local programs (or evolution rules), usually in a deterministic way. They may find interesting applications in areas such as computational biology, process control or robotics. The first simulator of numerical P systems (SNUPS) has been designed, implemented and made available to the scientific community by the authors of this paper. SNUPS allows a wide range of applications, from modeling and simulation of ordinary differential equations, to the use of membrane systems as computational blocks of cognitive architectures, and as controllers for autonomous mobile robots. This paper describes the functioning of a numerical P system and presents an overview of SNUPS capabilities together with an illustrative example. AVAILABILITY: SNUPS is freely available to researchers as a standalone application and may be downloaded from a dedicated website, http://snups.ics.pub.ro/, which includes an user manual and sample membrane structures.