Dataset Information

A research tool for measuring non-participation of older people in research on digital health.

ABSTRACT: 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.

SUBMITTER: Poli A

PROVIDER: S-EPMC6842243 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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A research tool for measuring non-participation of older people in research on digital health.

Poli Arianna A Kelfve Susanne S Motel-Klingebiel Andreas A

BMC public health 20191108 1

<h4>Background</h4>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 heal ...[more]

PMID: 31703655

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Project description:BACKGROUND:Lack of conceptual clarity and measurement methods have led to underdeveloped efforts to measure experience of participation in care by next of kin to older people in nursing homes. OBJECTIVE:We sought to assess the measurement properties of items aimed at operationalizing participation in care by next of kin, applied in nursing homes. METHODS:A total of 37 items operationalizing participation were administered via a questionnaire to 364 next of kin of older people in nursing homes. Measurement properties were tested with factor analysis and Rasch model analysis. RESULTS:The response rate to the questionnaire was 81% (n = 260). Missing responses per item varied between <0.5% and 10%. The 37 items were found to be two-dimensional, and 19 were deleted based on conceptual reasoning and Rasch model analysis. One dimension measured communication and trust (nine items, reliability 0.87) while the other measured collaboration in care (nine items, reliability 0.91). Items successfully operationalized a quantitative continuum from lower to higher degrees of participation, and were found to generally fit well with the Rasch model requirements, without disordered thresholds or differential item functioning. Total scores could be calculated based on the bifactor subscale structure (reliability 0.92). Older people (≥ 65 years) reported a higher degree of communication and trust and bifactor total scores than younger people (p < 0.05 in both cases). People with a specific contact person experienced a higher degree of participation in the two subscales and the bifactor total score (p < 0.05 in all three instances). CONCLUSION:Psychometric properties revealed satisfactory support for use, in nursing home settings, of the self-reported Next of Kin Participation in Care questionnaire, with a bifactor structure. Additional research is needed to evaluate the effectiveness of the scales' abilities to identify changes after intervention. TRIAL REGISTRATION:The KUPA project has Clinical Trials number NCT02708498.

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:BackgroundDigital technologies have the potential to contribute to health promotion and disease prevention in the aging world.ObjectiveThis study aims to identify digital technologies for health promotion and disease prevention that could be used independently by older people in nonclinical settings using a scoping review.MethodsThrough database (MEDLINE, PsycINFO, CINAHL, and SCOPUS; to March 3, 2022) and manual searches (to June 14, 2022), 90 primary studies and 8 systematic reviews were included in this scoping review. The eligibility was based on the PCC (Population, Concept, and Context) criteria: (1) people aged 50 years or older (population), (2) any digital (health) technology (eg, smartphone apps, websites, virtual reality; concept), and (3) health promotion and disease prevention in daily life in nonclinical and noninstitutional settings (context). Data items included study characteristics, PCC criteria, opportunities versus challenges, and evidence gaps. Data were synthesized using descriptive statistics or narratively described by identifying common themes.ResultsThe studies were published in 2005-2022 and originated predominantly from North America and Europe. Most primary studies were nonrandomized, reported quantitative data, and investigated effectiveness or feasibility (eg, acceptance or usability) of digital technologies in older people. The participants were aged 50 years to 99 years, predominantly female, affluent (ie, with high income, education, and digital competence), and intended to use or used digital technologies for a median of 3 months independently at home or in community settings. The digital technologies included mobile or nonmobile technologies or virtual reality. The studies used "modern devices" (eg, smartphones, wearables, or gaming consoles) or modern and "older devices" (eg, computers or mobile phones). The users interacted with digital technologies via websites, emails, text messages, apps, or virtual reality. Health targets of digital technologies were mobility, mental health, nutrition, or cognition. The opportunities versus challenges of digital technologies were (1) potential health benefits versus unclear or no benefits for some outcomes, (2) monitoring of health versus ethical issues with data collection and management, (3) implications for functioning in daily life (ie, potential to prolong independent living) versus unclear application for clinical management or care, (4) tailoring of technical properties and content toward older users versus general use, (5) importance of human support for feasibility versus other factors required to improve feasibility, (6) reduction of social isolation versus access to digital technologies, and (7) improvement in digital competence versus digital divide.ConclusionsVarious digital technologies were independently used by people aged 50 years or older for health promotion and disease prevention. Future studies should focus on (1) more diverse populations of older people, (2) new digital technologies, (3) other (clinical and care) settings, and (4) outcome evaluation to identify factors that could enhance any health benefits of digital technologies.International registered report identifier (irrid)RR2-10.2196/37729.

Project description:BackgroundHealth 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.MethodsFor 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.ResultsGreater social participation was associated with better QoL [β = 0.127, standard error (SE) = 0.002, p < 0.001], cognitive function (β = 0.154, SE = 0.033, p < 0.001) and physical function (β = - 0.102, SE = 0.008, p < 0.001). Physical activity was associated with better QoL (β = 0.091, SE = 0.015, p < 0.001) and physical function (β = - 0.155, SE = 0.062, p < 0.001). Sufficient fruit and vegetable consumption was associated with better QoL (β = 0.087, SE = 0.015, p < 0.001).ConclusionsOur 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

A research tool for measuring non-participation of older people in research on digital health.

Publications

A research tool for measuring non-participation of older people in research on digital health.

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