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Prediction of (Non)Participation of Older People in Digital Health Research: Exergame Intervention Study.

ABSTRACT: BACKGROUND:The use of digital technologies is increasing in health care. However, studies evaluating digital health technologies can be characterized by selective nonparticipation of older people, although older people represent one of the main user groups of health care. OBJECTIVE:We examined whether and how participation in an exergame intervention study was associated with age, gender, and heart failure (HF) symptom severity. METHODS:A subset of data from the HF-Wii study was used. The data came from patients with HF in institutional settings in Germany, Italy, the Netherlands, and Sweden. Selective nonparticipation was examined as resulting from two processes: (non)recruitment and self-selection. Baseline information on age, gender, and New York Heart Association Functional Classification of 1632 patients with HF were the predictor variables. These patients were screened for HF-Wii study participation. Reasons for nonparticipation were evaluated. RESULTS:Of the 1632 screened patients, 71% did not participate. The nonrecruitment rate was 21%, and based on the eligible sample, the refusal rate was 61%. Higher age was associated with lower probability of participation; it increased both the probabilities of not being recruited and declining to participate. More severe symptoms increased the likelihood of nonrecruitment. Gender had no effect. The most common reasons for nonrecruitment and self-selection were related to physical limitations and lack of time, respectively. CONCLUSIONS:Results indicate that selective nonparticipation takes place in digital health research and that it is associated with age and symptom severity. Gender effects cannot be proven. Such systematic selection can lead to biased research results that inappropriately inform research, policy, and practice. TRIAL REGISTRATION:ClinicalTrial.gov NCT01785121, https://clinicaltrials.gov/ct2/show/NCT01785121.

SUBMITTER: Poli A

PROVIDER: S-EPMC7305561 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Prediction of (Non)Participation of Older People in Digital Health Research: Exergame Intervention Study.

Poli Arianna A Kelfve Susanne S Klompstra Leonie L Strömberg Anna A Jaarsma Tiny T Motel-Klingebiel Andreas A

Journal of medical Internet research 20200605 6

<h4>Background</h4>The use of digital technologies is increasing in health care. However, studies evaluating digital health technologies can be characterized by selective nonparticipation of older people, although older people represent one of the main user groups of health care.<h4>Objective</h4>We examined whether and how participation in an exergame intervention study was associated with age, gender, and heart failure (HF) symptom severity.<h4>Methods</h4>A subset of data from the HF-Wii stud ...[more]

PMID: 32501275

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Project description:BACKGROUND:Healthcare services are being increasingly digitalised in European countries. However, in studies evaluating digital health technology, some people are less likely to participate than others, e.g. those who are older, those with a lower level of education and those with poorer digital skills. Such non-participation in research - deriving from the processes of non-recruitment of targeted individuals and self-selection - can be a driver of old-age exclusion from new digital health technologies. We aim to introduce, discuss and test an instrument to measure non-participation in digital health studies, in particular, the process of self-selection. METHODS:Based on a review of the relevant literature, we designed an instrument - the NPART survey questionnaire - for the analysis of self-selection, covering five thematic areas: socioeconomic factors, self-rated health and subjective overall quality of life, social participation, time resources, and digital skills and use of technology. The instrument was piloted on 70 older study persons in Sweden, approached during the recruitment process for a trial study. RESULTS:Results indicated that participants, as compared to decliners, were on average slightly younger and more educated, and reported better memory, higher social participation, and higher familiarity with and greater use of digital technologies. Overall, the survey questionnaire was able to discriminate between participants and decliners on the key aspects investigated, along the lines of the relevant literature. CONCLUSIONS:The NPART survey questionnaire can be applied to characterise non-participation in digital health research, in particular, the process of self-selection. It helps to identify underrepresented groups and their needs. Data generated from such an investigation, combined with hospital registry data on non-recruitment, allows for the implementation of improved sampling strategies, e.g. focused recruitment of underrepresented groups, and for the post hoc adjustment of results generated from biased samples, e.g. weighting procedures.

Project description:BackgroundSocial participation is an indicator of successful ageing and important determinant of health outcomes. As more studies have been conducted on social participation of older people, a comprehensive and quantitative analysis of the current literature will contribute to a better understanding of the main and novel issues and improve existing geriatric care services in this domain. However, limited bibliometric analysis was employed in this research field. Therefore, we conducted this study to investigate the research trend and quantitatively and comprehensively characterise the landscapes of publications on social participation of older people via bibliometric analysis methods.MethodsData were obtained from the Web of Science Core Collection in January 2020. CiteSpace 5.5.R2 and VOSviewer software packages were used to generate knowledge maps and analyse the publication outputs, countries/regions, institutions, journals, research hot spots and research frontiers.ResultsA total of 7,029 publications between 2000 and 2019 were retrieved, and the publication number per year continues to increase. The United States held a leading position in this research field, and Duke University was the most productive institution. Co-cited reference cluster analysis and keyword co-occurrence analysis showed that research hot spots contained factors of healthy ageing, quality of life, psychological problems and health status, especially dementia, function (including cognitive function) and frailty. Burst detection of keywords revealed that social participation, social support, instrumental activity, frailty and loneliness have been new research frontiers since 2015.ConclusionsBy analysing publications over the past 20 years, we found publication trends and characteristics in this field. These findings will hopefully provide new insight into the scientific landscapes and further directions in the study of social participation of older people.Implications for practiceSocial participation is strongly associated with physical and psychological problems and the well-being of older people. Related professionals, such as social workers, psychologists, nurses and many other health care practitioners, should raise widespread awareness and concern over research hot spots and frontiers on this topic to promote research knowledge translation and adoption into the practice of caring for older people.

Project description:BackgroundBy 2050, worldwide dementia prevalence is expected to triple. Affordable, scalable interventions are required to support protective behaviours such as physical activity, cognitive training and healthy eating. This paper outlines the theory-, evidence- and person-based development of 'Active Brains': a multi-domain digital behaviour change intervention to reduce cognitive decline amongst older adults.MethodsDuring the initial planning phase, scoping reviews, consultation with PPI contributors and expert co-investigators and behavioural analysis collated and recorded evidence that was triangulated to inform provisional 'guiding principles' and an intervention logic model. The following optimisation phase involved qualitative think aloud and semi-structured interviews with 52 older adults with higher and lower cognitive performance scores. Data were analysed thematically and informed changes and additions to guiding principles, the behavioural analysis and the logic model which, in turn, informed changes to intervention content.ResultsScoping reviews and qualitative interviews suggested that the same intervention content may be suitable for individuals with higher and lower cognitive performance. Qualitative findings revealed that maintaining independence and enjoyment motivated engagement in intervention-targeted behaviours, whereas managing ill health was a potential barrier. Social support for engaging in such activities could provide motivation, but was not desirable for all. These findings informed development of intervention content and functionality that appeared highly acceptable amongst a sample of target users.ConclusionsA digitally delivered intervention with minimal support appears acceptable and potentially engaging to older adults with higher and lower levels of cognitive performance. As well as informing our own intervention development, insights obtained through this process may be useful for others working with, and developing interventions for, older adults and/or those with cognitive impairment.

Project description:BACKGROUND:Health behaviours (physical activity, maintenance of a healthy diet and not smoking) are known to be beneficial to the health and well-being of chronically ill people. With China's ageing population and increased prevalence of people with chronic diseases, the improvement of unhealthy behaviours in this population has become crucial. Although recent studies have highlighted the importance of social participation for health and quality of life (QoL) among older people, no study to date has included social participation along with more traditional health behaviours. Therefore, this study aimed to identify associations of multiple health behaviours (social participation, physical activity, maintenance of a healthy diet and not smoking) with health and QoL outcomes (including cognitive and physical function) among chronically ill older adults in China. METHODS:For this nationally representative cross-sectional study, wave 1 data from the World Health Organization's Study on global AGEing and adult health (China) were examined. In total, 6629 community-dwelling older adults (mean age, 64.9?years) with at least one chronic disease were included. Multivariate linear regression analyses were used to evaluate associations of health behaviours with health and QoL outcomes while controlling for background characteristics. RESULTS:Greater social participation was associated with better QoL [??=?0.127, standard error (SE)?=?0.002, p?<?0.001], cognitive function (??=?0.154, SE?=?0.033, p?<?0.001) and physical function (??=?-?0.102, SE?=?0.008, p?<?0.001). Physical activity was associated with better QoL (??=?0.091, SE?=?0.015, p?<?0.001) and physical function (??=?-?0.155, SE?=?0.062, p?<?0.001). Sufficient fruit and vegetable consumption was associated with better QoL (??=?0.087, SE?=?0.015, p?<?0.001). CONCLUSIONS:Our findings suggest that social participation is an important health behaviour for quality of life and cognitive function among chronically ill older people in China. Health promotion programmes should expand their focus to include social participation as a health behaviour, in addition to physical activity, maintenance of a healthy diet and not smoking.

Dataset Information

Prediction of (Non)Participation of Older People in Digital Health Research: Exergame Intervention Study.

Publications

Prediction of (Non)Participation of Older People in Digital Health Research: Exergame Intervention Study.

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