Arianna Poli, Ingemar Kåreholt, Susanne Kelfve, Katarina Berg, Andreas Motel-Klingebiel
{"title":"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。","authors":"Arianna Poli, Ingemar Kåreholt, Susanne Kelfve, Katarina Berg, Andreas Motel-Klingebiel","doi":"10.1093/gerona/glae265","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":94243,"journal":{"name":"The journals of gerontology. Series A, Biological sciences and medical sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Non-Participation in a Digital Health Intervention Study Among Older Adults: Uneven Involvement, Biased Outcomes and the Effect of Weighting.\",\"authors\":\"Arianna Poli, Ingemar Kåreholt, Susanne Kelfve, Katarina Berg, Andreas Motel-Klingebiel\",\"doi\":\"10.1093/gerona/glae265\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":94243,\"journal\":{\"name\":\"The journals of gerontology. Series A, Biological sciences and medical sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The journals of gerontology. 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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.