Abstract
BackgroundHealthcare 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.MethodsBased 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.ResultsResults 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.ConclusionsThe 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.
Highlights
Healthcare services are being increasingly digitalised in European countries
Following the two phases of data collection, comparisons between non-recruited, decliners and participants are conducted. Such an investigation based on hospital and survey data serves as a key basis for implementing improved sampling strategies, for example focused recruitment aiming at reaching specific underrepresented groups [54], and/ or for conducting post hoc adjustments of the research outcomes, for example weighting outcomes according to the information on non-participation [55]
We focused on predictors for individual decisions to participate in digital health research, resulting in five thematic areas: socioeconomic factors, subjective health and subjective overall quality of life, social participation, time resources, and use of technology and digital skills
Summary
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 oldage exclusion from new digital health technologies. Discuss and test an instrument to measure non-participation in digital health studies, in particular, the process of self-selection. The overall aim of the present paper is to introduce, discuss and test an instrument to measure nonparticipation in digital health studies. We consider its use and applicability and knowledge generated by it
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