Title

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

Authors

Poli, A.1

Kelfve, S.1,2

Motel-Klingebiel, A.1

Klompstra, L.3

Strömberg, A.3,4

Jaarsma, T.3,5

Author Affiliations

¹Division Ageing and Social Change, Department of Culture and Society, Linköping University
²Aging Research Center, Karolinska Institutet, Stockholm University
³Department of Health, Medicine and Caring Science, Linköping University
⁴Department of Cardiology, Linköping University
⁵Julius Centre, University Medical Center

Publication Information

JMIR Publications Inc.

Date of Publication

2020

Series/Report no.

Internet Research, 22(6), e17884.

Key words

technology; exclusion; recruitment; self-selection; nonparticipation

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.

주요 내용

이 논문의 목적은 디지털 건강 연구에서 노인의 (비)참여를 예측하는 것이 무엇인지 밝히는 것이다. 여기서 참여는 연구 참여자로서, 디지털 헬스 연구에 참여하는 것으로 정의하고, 비참여는 디지털 헬스 연구에 참여하지 않는 것으로 정의한다. 이를 연구하기 위해 심부전(HF) 환자를 대상으로 Exergame 기술을 평가하는 분석을 수행하였다.

ISSN

14388871

DOI

10.2196/17884