老年人不参与数字健康干预研究:不均衡的参与、有偏差的结果以及加权的影响。

Arianna Poli, Ingemar Kåreholt, Susanne Kelfve, Katarina Berg, Andreas Motel-Klingebiel
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引用次数: 0

摘要

背景:根据年龄、性别、健康状况和数字技能等因素,老年人参与数字健康研究的情况并不均衡。然而,人们对老年人参与数字健康研究的不均衡性对研究成果的影响知之甚少。本研究有助于填补这一知识空白,确定老年人参与数字健康研究的不均衡性对研究成果的影响,并对此进行修正:方法:从瑞典一项针对日间手术患者术后监测的数字健康干预中获取数据。根据有关干预措施的招募过程和研究结果的实地信息,本研究(1)在 281 个 50 岁或以上的样本中使用两种标准的非加权程序测试干预效果,然后(2)使用有关参与者、非参与者及其各自参与干预研究的概率的信息,对每一步选择和研究组成员的干预效果进行加权:结果发现,由于接受干预的群体比例过高,干预效果被高估了。在对参与偏差进行调整后,没有发现干预效果:选择性地让老年人参与数字健康研究会使研究结果产生偏差,并可能导致干预效果被高估。通过加权法,研究人员可以纠正和描述选择性参与对研究结果的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-Participation in a Digital Health Intervention Study Among Older Adults: Uneven Involvement, Biased Outcomes and the Effect of Weighting.

Background: The involvement of older adults in research on digital health is uneven with respect to e.g. age, gender, health status, and digital skills. However, little is known regarding the impact of the uneven involvement of older adults in digital health research on researched outcomes. This study helps to fill this knowledge gap and identifies the effects of uneven involvement of older adults in digital health research on researched outcomes, and also develops a correction for this.

Methods: Data are retrieved from a digital health intervention for postoperative monitoring of people who underwent day surgery in Sweden. Based on field information on the recruitment process and researched outcomes for the intervention, this study (1) tested intervention effects by using two standard unweighted procedures in a sample of 281 individuals aged 50 years or older, and then (2) used the information on participants, non-participants and their respective probabilities to be involved in the intervention study to perform a weighting of the intervention effects for each step of selection and for the study group membership.

Results: The intervention effects were found to be overestimated due to overrepresentation of groups which gained from receiving the intervention. No intervention effects were found after adjustment for participation bias.

Conclusions: Selective participation of older adults in digital health research biases research outcomes and can lead to overestimation of intervention effects. Weighting allows researchers to correct and describe the impact of selective participation on researched outcomes.

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