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Prediction of (Non)Participation of Older People in Digital Health Research: Exergame Intervention Study [Elektronisk resurs]

Poli, Arianna, 1987- (författare)
Kelfve, Susanne (författare)
Klompstra, Leonie (författare)
Strömberg, Anna (författare)
Jaarsma, Tiny (författare)
Motel-Klingebiel, Andreas (författare)
Linköpings universitet Institutionen för kultur och samhälle (utgivare)
Linköpings universitet Filosofiska fakulteten (utgivare)
Linköpings universitet Institutionen för kultur och samhälle (utgivare)
Linköpings universitet Institutionen för hälsa, medicin och vård (utgivare)
Linköpings universitet Medicinska fakulteten (utgivare)
Region Östergötland Hjärt- och Medicincentrum (utgivare)
Publicerad: JMIR PUBLICATIONS, INC, 2020
Engelska.
Ingår i: Journal of Medical Internet Research. - 1438-8871. ; 22:6
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  • 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 nonrecmitment 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. 

Ämnesord

Medical and Health Sciences  (ssif)
Health Sciences  (ssif)
Public Health, Global Health, Social Medicine and Epidemiology  (ssif)
Medicin och hälsovetenskap  (ssif)
Hälsovetenskap  (ssif)
Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi  (ssif)

Genre

government publication  (marcgt)

Indexterm och SAB-rubrik

technology; exclusion; recruitment; self-selection; nonparticipation
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