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A research tool for measuring non-participation of older people in research on digital health
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI). Linköping University, Sweden.
Number of Authors: 32019 (English)In: BMC Public Health, ISSN 1471-2458, E-ISSN 1471-2458, Vol. 19, no 1, article id 1487Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2019. Vol. 19, no 1, article id 1487
Keywords [en]
Digital health, Old age inequality, Social exclusion, Digitalisation, Recruitment, Self-selection, Non-participation
National Category
Nursing Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
URN: urn:nbn:se:su:diva-176542DOI: 10.1186/s12889-019-7830-xISI: 000496430300001PubMedID: 31703655OAI: oai:DiVA.org:su-176542DiVA, id: diva2:1380086
Available from: 2019-12-18 Created: 2019-12-18 Last updated: 2019-12-18Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • Other style
More styles
Language
  • de-DE
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf