Division Ageing and Social Change (ASC), Linköping University, Kungsgatan 40, 601 74, Norrköping, Sweden.
Aging Research Center (ARC), Karolinska Institutet & Stockholm University, Gävlegatan 16, 113 30, Stockholm, Sweden.
BMC Public Health. 2019 Nov 8;19(1):1487. doi: 10.1186/s12889-019-7830-x.
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.
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 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.
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.
欧洲各国的医疗服务正日益数字化。然而，在评估数字健康技术的研究中，有些人参与的可能性低于其他人，例如年龄较大、教育程度较低和数字技能较差的人。这种源于目标人群未招募和自我选择的研究参与度低的情况，可能会导致老年人被排除在新的数字健康技术之外。我们旨在引入、讨论和测试一种衡量数字健康研究中非参与度的工具，特别是自我选择的过程。
我们基于对相关文献的回顾，设计了一种用于分析自我选择的工具——NPART 调查问卷，涵盖了五个主题领域：社会经济因素、自我评估的健康和主观总体生活质量、社会参与、时间资源以及数字技能和技术使用。该工具在瑞典的 70 名老年研究参与者中进行了试点，这些参与者是在一项试验研究的招募过程中被招募的。
结果表明，与拒绝者相比，参与者的平均年龄稍小、受教育程度更高，并且报告记忆力更好、社会参与度更高、对数字技术的熟悉度和使用度更高。总体而言，该调查问卷能够根据相关文献，在研究参与者和拒绝者之间区分出关键方面。
NPART 调查问卷可用于描述数字健康研究中的非参与度，特别是自我选择的过程。它有助于确定代表性不足的群体及其需求。从这种调查中生成的数据与医院登记的未招募数据相结合，可以实施改进的抽样策略，例如有针对性地招募代表性不足的群体，以及对来自有偏见样本的结果进行事后调整，例如加权程序。
