JMIR Aging最新文献

Background: Cognitive impairment and dementia pose a significant challenge to the aging population, impacting the well-being, quality of life, and autonomy of affected individuals. As the population ages, this will place enormous strain on health care and economic systems. While computerized cognitive training programs have demonstrated some promise in addressing cognitive decline, adherence to these interventions can be challenging.

Objective: The objective of this study is to improve the accuracy of predicting adherence lapses to ultimately develop tailored adherence support systems to promote engagement with cognitive training among older adults.

Methods: Data from 2 previously conducted cognitive training intervention studies were used to forecast adherence levels among older participants. Deep convolutional neural networks were used to leverage their feature learning capabilities and predict adherence patterns based on past behavior. Domain adaptation (DA) was used to address the challenge of limited training data for each participant, by using data from other participants with similar playing patterns. Time series data were converted into image format using Gramian angular fields, to facilitate clustering of participants during DA. To the best of our knowledge, this is the first effort to use DA techniques to predict older adults' daily adherence to cognitive training programs.

Results: Our results demonstrated the promise and potential of deep neural networks and DA for predicting adherence lapses. In all 3 studies, using 2 independent datasets, DA consistently produced the best accuracy values.

Conclusions: Our findings highlight that deep learning and DA techniques can aid in the development of adherence support systems for computerized cognitive training, as well as for other interventions aimed at improving health, cognition, and well-being. These techniques can improve engagement and maximize the benefits of such interventions, ultimately enhancing the quality of life of individuals at risk for cognitive impairments. This research informs the development of more effective interventions, benefiting individuals and society by improving conditions associated with aging.

Background: Current clinical guidelines for the management of type 2 diabetes mellitus (T2DM) in older adults recommend the use of antihyperglycemic medications, monitoring of blood glucose levels, regular exercise, and a healthy diet to improve glycemic control and reduce associated comorbidities. However, adherence to traditional exercise programs is poor (<35%). Common barriers to adherence include fear of hypoglycemia and the need for blood glucose level monitoring before exercise. Digital health strategies offer great promise for managing T2DM as they facilitate patient-practitioner communication, support self-management, and improve access to health care services for underserved populations. We have developed a novel web-based software program allowing practitioners to create tailored interventions and deliver them to patients via digital voice assistants (DVAs) in their own homes.

Objective: We aim to evaluate the feasibility of a 12-week, home-based, personalized lifestyle intervention delivered and monitored by DVAs for older adults with obesity and T2DM.

Methods: In total, 50 older adults with obesity aged 50-75 years with oral hypoglycemic agent-treated T2DM were randomized to the intervention (DVA, n=25) or a control group (n=25). Participants allocated to the DVA group were prescribed a home-based muscle strengthening exercise program (~20- to 30-min sessions) and healthy eating intervention, delivered via DVAs (Alexa Echo Show 8; Amazon) using newly developed software ("Buddy Link"; Great Australian Pty Ltd). Control group participants received generalized physical activity information via email. Outcomes were feasibility, DVA usability (System Usability Scale), and objectively assessed physical activity and sedentary time (wrist-worn accelerometers).

Results: In total, 45 (90%) out of 50 participants completed this study. Mean adherence to prescribed exercise was 85% (SD 43%) with no intervention-related adverse events. System usability was rated above average (70.4, SD 16.9 out of 100). Compared with controls, the DVA group significantly decreased sedentary time (mean difference -67, SD 23; 95% CI -113 to -21 min/d), which was represented by a medium to large effect size (d=-0.6).

Conclusions: A home-based lifestyle intervention delivered and monitored by health professionals using DVAs was feasible for reducing sedentary behavior and increasing moderate-intensity activity in older adults with obesity and T2DM.

Trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12621000307808; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381364&isReview=true.

Background: Despite positive results for the use of assistive technologies (ATs) in dementia, the uptake of ATs lags behind. It is considered important to assess determinants of successful or unsuccessful implementation of ATs.

Objective: We explored factors that influence the implementation of ATs for community-dwelling people with dementia, with the aim to better understand potentially effective implementation strategies.

Methods: A cross-sectional survey for researchers was developed and disseminated, exploring factors that influence either successful or unsuccessful implementation of ATs for dementia. The survey consisted of closed and open questions.

Results: The response rate was 10% (21/206); the 21 respondents who completed the survey were from 8 countries. Determinants of implementation were described for 21 ATs, of which 12 were successfully and 9 were unsuccessfully implemented. Various types of ATs were included, such as online platforms, sensors, or physical aids. The main determinants of implementation success were related to the AT itself, contextual factors, research activities, and implementation strategies. There was a lack of research data on some ethical issues and cost-effectiveness.

Conclusions: This study provided insight into some main barriers to and facilitators of implementation of ATs in dementia related to the AT itself, context, research-related activities, and applied implementation strategies. Lessons were formulated for various stakeholders to improve the implementation effectiveness of ATs in dementia.

Background: Maintaining exercise is essential for healthy aging but difficult to sustain. EngAGE is a socially motivated exercise program delivered over a voice-activated device that targets older adult-care partner dyads.

Objective: This 10-week pilot study aimed to assess EngAGE feasibility and use, obtain user experience feedback, and estimate potential impact on function.

Methods: In total, 10 older adults aged ≥65 years were recruited from an independent living residence together with their self-identified care partners. EngAGE delivered National Institute on Aging Go4Life exercises to older adults daily, while care partners received progress reports and prompts to send encouraging messages that were read aloud by the device to the older adult. Older adults' use was tracked, and physical function was assessed at baseline and follow-up. Follow-up focus group data provided qualitative feedback.

Results: On average, participants completed 393.7 individual exercises over the 10-week intervention period or 39.4 exercises/wk (range 48-492, median 431, IQR 384-481, SD 112.4) without injury and used EngAGE on an average of 41 of 70 days or 4.1 d/wk (range 7-66, median 51, IQR 23-56, and SD 21.2 days). Mean grip strength increased nonsignificantly by 1.3 kg (preintervention mean 26.3 kg, SD 11.0; postintervention mean 27.6 kg, SD 11.6; P=.34), and 4 of 10 participants improved by a minimal clinically important difference (MCID) of 2.5 kg. Further, the time for 5-repeated chair stands significantly reduced by 2.3 seconds (preintervention mean 12, SD 3.6 s; postintervention mean 9.7, SD 2.7 s; P=.02), and 3 of 9 participants improved by an MCID of -2.3 seconds. Furthermore, 3-meter usual walk performance was brisk at baseline (mean 2.1, SD 0.4 s) and decreased by 0.1 seconds (postintervention 2, SD 0.4 s; P=.13), although 5 of 9 participants improved by a MCID of 0.05 m/s. Qualitative results showed perceived benefits, favored program features, and areas for improvement.

Conclusions: We present a pilot study of a new voice-activated device application customized to older adult users that may serve as a guide to other technology development for older adults. Our pilot study served to further refine the application and to inform a larger trial testing EngAGE's impact on functional outcomes, a necessary step for developing evidence-based technology tools.

Background: Chronic noncancer pain (CNCP) is a major health issue among the older population, affecting multiple aspects of individual functioning. Recently, the use of eHealth solutions has been proposed in supporting chronic pain self-management even among older adults, although some barriers have emerged. Few qualitative studies, with none conducted in Mediterranean countries, have explored older people's experiences and perceptions regarding the types of strategies used to cope with chronic pain and eHealth tools for chronic pain management.

Objective: This study's objectives were to explore the perspectives and experiences of older adults regarding the coping strategies used to manage chronic pain, the use of digital technologies in everyday life, and the potentiality and barriers in using those technologies for health and pain management.

Methods: A multimethod approach (ie, self-report questionnaires and a semistructured interview) has been adopted targeting older adults (ie, those who are aged 65 to 80 years and presenting different types of CNCP) who are attending a pain therapy center in Italy. Qualitative answers were analyzed using thematic analysis.

Results: Overall, participants reported using a variety of pain coping strategies; however, they showed an attitude of resignation to their CNCP condition. Nearly 70% (12/18) of the interviewees referred to using digital technologies for purposes related to health and pain management, mostly involving very basic management activities. The participants' opinions on the useful functions that need to be incorporated in eHealth tools for chronic pain management have been categorized into four themes: (1) specific pain self-management skills, (2) support in organizing various health-related aspects, (3) sharing experiences with others, and (4) increasing pain-related personal knowledge. Conversely, the following potential barriers to adopting eHealth tools emerged: (1) computer illiteracy, (2) negative effects or risks, (3) impersonal interaction, and (4) physical limitations.

Conclusions: The use of eHealth solutions still seems low, often being accompanied by a perceived lack of digital skills or attitude among a sample of older adults from Italy with CNCP. Before introducing innovative eHealth solutions, it would be of primary importance to take action to enhance, on the one hand, self-efficacy in pain management and, on the other, the digital literacy level among older people.

Background: Older adults discharged from the emergency department (ED) face elevated risk of falls and functional decline. Smartphones might enable remote monitoring of mobility after ED discharge, yet their application in this context remains underexplored.

Objective: This study aimed to assess the feasibility of having older adults provide weekly accelerometer data from an instrumented Timed Up-and-Go (TUG) test over an 11-week period after ED discharge.

Methods: This single-center, prospective, observational, cohort study recruited patients aged 60 years and older from an academic ED. Participants downloaded the GaitMate app to their iPhones that recorded accelerometer data during 11 weekly at-home TUG tests. We measured adherence to TUG test completion, quality of transmitted accelerometer data, and participants' perceptions of the app's usability and safety.

Results: Of the 617 approached patients, 149 (24.1%) consented to participate, and of these 149 participants, 9 (6%) dropped out. Overall, participants completed 55.6% (912/1639) of TUG tests. Data quality was optimal in 31.1% (508/1639) of TUG tests. At 3-month follow-up, 83.2% (99/119) of respondents found the app easy to use, and 95% (114/120) felt safe performing the tasks at home. Barriers to adherence included the need for assistance, technical issues with the app, and forgetfulness.

Conclusions: The study demonstrates moderate adherence yet high usability and safety for the use of smartphone TUG tests to monitor mobility among older adults after ED discharge. Incomplete TUG test data were common, reflecting challenges in the collection of high-quality longitudinal mobility data in older adults. Identified barriers highlight the need for improvements in user engagement and technology design.

Background: In our aging population, primary care is under pressure to remain accessible to all. Effective use of digital health care could potentially lower general practitioners' (GPs) workload. Some general practices are already implementing a digital health platform as a primary method to contact their patients. However, it is unknown how older people experience this novel way to communicate with their GP.

Objective: The aim of this study was to study the experiences of patients aged 65 years and older in general practices who use digital health as a primary communication tool. The secondary aims were to identify barriers and facilitators for the use of digital health care and whether a practice focus on digital health influences older patients' choice to enlist.

Methods: We invited all patients aged 65 years and older at 2 general practices in Amsterdam that work with a novel digital health platform. We used purposive sampling to select a heterogeneous group of patients in terms of age, sex, level of education, digital literacy, and experiences with the digital app of their general practice. We conducted 18 semistructured interviews from May through July 2023. All interviews were audio-recorded, transcribed, coded, and thematically analyzed.

Results: We generated three themes: (1) experiences of older people with digital health care in general practice, (2) impact of individual factors on digital health experiences, and (3) reasons for choosing a digitally oriented general practice. Participants reported both positive and negative experiences. The main perceived advantages of the digital health platform were increased accessibility, direct GP contact without an intermediary, and saving time through asynchronous communication. The disadvantages mentioned were log-in difficulties and problems with the automated explanatory questionnaire. Individual factors such as age, digital literacy, and expectations of general practice care seemed to impact people's experiences and could act as barriers or facilitators for using digital health. Reasons for older patients to enlist at a general practice were mainly practical. The digital orientation of the practice hardly played a role in this choice.

Conclusions: Older patients in general practice see benefits to using a digital health platform that offers 2-way chat-based communication between the patient and GP. We found that individual factors such as skills, norms and values, attitudes toward digitalization, and expectations of general practice care impacted older patients' experiences with digital health care. For many older participants, the digital profile of the general practice did not play a role in their choice to enlist. Further improvement of digital health platforms will be necessary to ensure digital health for all in general practice.

Background: Long-term care (LTC) homes face the challenges of increasing care needs of residents and a shortage of health care providers. Literature suggests that artificial intelligence (AI)-enabled robots may solve such challenges and support person-centered care. There is a dearth of literature exploring the perspectives of health care providers, which are crucial to implementing AI-enabled robots.

Objective: This scoping review aims to explore this scant body of literature to answer two questions: (1) what barriers do health care providers perceive in adopting AI-enabled robots in LTC homes? (2) What strategies can be taken to overcome these barriers to the adoption of AI-enabled robots in LTC homes?

Methods: We are a team consisting of 3 researchers, 2 health care providers, 2 research trainees, and 1 older adult partner with diverse disciplines in nursing, social work, engineering, and medicine. Referring to the Joanna Briggs Institute methodology, our team searched databases (CINAHL, MEDLINE, PsycINFO, Web of Science, ProQuest, and Google Scholar) for peer-reviewed and gray literature, screened the literature, and extracted the data. We analyzed the data as a team. We compared our findings with the Person-Centered Practice Framework and Consolidated Framework for Implementation Research to further our understanding of the findings.

Results: This review includes 33 articles that met the inclusion criteria. We identified three barriers to AI-enabled robot adoption: (1) perceived technical complexity and limitation; (2) negative impact, doubted usefulness, and ethical concerns; and (3) resource limitations. Strategies to mitigate these barriers were also explored: (1) accommodate the various needs of residents and health care providers, (2) increase the understanding of the benefits of using robots, (3) review and overcome the safety issues, and (4) boost interest in the use of robots and provide training.

Conclusions: Previous literature suggested using AI-enabled robots to resolve the challenges of increasing care needs and staff shortages in LTC. Yet, our findings show that health care providers might not use robots because of different considerations. The implication is that the voices of health care providers need to be included in using robots.

International registered report identifier (irrid): RR2-doi:10.1136/bmjopen-2023-075278.

Background: During the COVID-19 pandemic, there was a rapid adoption of telehealth care services as a public health strategy to maintain access to essential health care. In Australia, there has been increasing optimism for the expansion of telehealth services. However, little is known about the patterns and determinants of telehealth adoption among older adults, with concerns that an expansion of telehealth services may only be of benefit to those who already have better access to health care.

Objective: Leveraging data collected by The Sax Institute's 45 and Up COVID Insights study between November 2020 and April 2022, the objective of this study was to identify and describe the sociodemographic and health-related determinants of telehealth adoption and use among a cohort of older Australians. We hypothesized that health-related factors would be key determinants of telehealth adoption for Australians aged ≥65 years during the COVID-19 pandemic.

Methods: A repeated cross-sectional design was used. The relationships between telehealth use (classified as low, moderate, or high) and selected sociodemographic and health-related characteristics were assessed using logistic regression techniques. Variable selection and findings were situated within the Technology Acceptance Model, the Unified Theory of Acceptance, and the Use of Technology theoretical frameworks.

Results: Of the 21,830 participants aged ≥65 years, the proportion who indicated adopting telehealth ranged from 50.77% (11,082/21,830) at survey 1 in 2020 to 39.4% (7401/18,782) at survey 5 in 2022. High levels of telehealth use were associated with being female, aged <85 years, living in a major city, cohabiting with others, and being from the most socioeconomically disadvantaged areas (deciles 1-3). Individuals with a disability, chronic disease, multimorbidity, and lower perceived quality of life and those experiencing missed or delayed care were significantly more likely to use telehealth across all levels (P<.001). A temporal association was observed, whereby participants who engaged with telehealth services before or early in the pandemic (as assessed in survey 1) were more likely to continue telehealth use when assessed in survey 5 in 2022 (P<.001).

Conclusions: This research contributes to the broader understanding of telehealth adoption and use among older adults. As telehealth models of care expand, there is an opportunity to tailor these services to the needs of older adults, particularly those living with chronic diseases and multimorbidity, by using targeted strategies that overcome barriers to accessing specialized health care services.

Background: Assistive technology is becoming increasingly accessible and affordable for supporting people with dementia and their care partners living at home, with strong potential for technology-based prompting to assist with initiation and tracking of complex, multistep activities of daily living. However, there is limited direct comparison of different prompt features to guide optimal technology design.

Objective: Across 3 experiments, we investigated the features of tablet-based prompts that best support people with dementia to complete activities of daily living at home, measuring prompt effectiveness and gaining feedback from people with dementia and their care partners about their experiences.

Methods: Across experiments, we developed a specialized iPad app to enable data collection with people with dementia at home over an extended experimental period. In experiment 1, we varied the prompts in a 3 (visual type: text instruction, iconic image, and photographic image) × 3 (audio type: no sound, symbolic sound, and verbal instruction) experimental design using repeated measures across multiple testing sessions involving single-step activities. In experiment 2, we tested the most effective prompt breakdown for complex multistep tasks comparing 3 conditions (1-prompt, 3-prompt, and 7-prompt conditions). In experiment 3, we compared initiation and maintenance alerts that involved either an auditory tone or an auditory tone combined with a verbal instruction. Throughout, we asked people with dementia and their care partners to reflect on the usefulness of prompting technology in their everyday lives and what could be developed to better meet their needs.

Results: First, our results showed that audible verbal instructions were more useful for task completion than either tone-based or visual prompts. Second, a more granular breakdown of tasks was generally more useful and increased independent use, but this varied across individuals. Third, while a voice or text maintenance alert enabled people with dementia to persist with a multistep task for longer when it was more frequent, task initiation still frequently required support from a care partner.

Conclusions: These findings can help inform developers of assistive technology about the design features that promote the usefulness of home prompting systems for people with dementia as well as the preferences and insights of people with dementia and their care partners regarding assistive technology design.