Pub Date : 2023-01-01DOI: 10.20517/chatmed.2023.002
Jaclyn N Escudero, Jasmin A Tiro, Diana S M Buist, Hongyuan Gao, Tara Beatty, John Lin, Diana L Miglioretti, Rachel L Winer
Aim: Financial incentives improve response to electronic health surveys, yet little is known about how unconditional incentives (guaranteed regardless of survey completion), conditional incentives, and various combinations of incentives influence response rates. We compared electronic health survey completion with two different financial incentive structures.
Methods: We invited women aged 30-64 years enrolled in a U.S. healthcare system and overdue for Pap screening to complete a web-based survey after receiving a mailed human papillomavirus (HPV) self-sampling kit in a pragmatic trial. HPV kit returners (n = 272) and non-returners (n = 1,083) were allocated to one of two different incentive structures: (1) Unconditional: $5 pre-incentive only (n = 653); (2) Combined: $2 pre-incentive plus $10 post-incentive conditional on completion (n = 702). Chi-square tests evaluated whether survey completion differed by incentive structure within kit return groups or was modified by kit return status. For each incentive-by-kit status group, the cost-per-survey response was calculated as: ([number invited*pre-incentive amount] + [number responses*post-incentive amount]) / number responses.
Results: Overall, survey response was higher in kit returners vs. kit non-returners (42.6% vs. 11.0%, P < 0.01), and survey response was higher in the combined (20.1%) vs. unconditional (14.4%) incentive group (P = 0.01). Kit return status did not modify the association between incentive type and survey response (P = 0.52). Among respondents, time to survey completion did not differ by incentive type among either kit returners or non-returners. Among returners, the cost-per-survey response was similar between groups ($13.57 unconditional; $14.15 combined); among non-returners, the cost was greater in the unconditional ($57.78) versus the combined ($25.22) group.
Conclusion: A combined incentive can be cost-effective for increasing survey response in health services research, particularly in hard-to-reach populations.
{"title":"Impact of different financial incentive structures on a web-based health survey: do timing and amount matter?","authors":"Jaclyn N Escudero, Jasmin A Tiro, Diana S M Buist, Hongyuan Gao, Tara Beatty, John Lin, Diana L Miglioretti, Rachel L Winer","doi":"10.20517/chatmed.2023.002","DOIUrl":"https://doi.org/10.20517/chatmed.2023.002","url":null,"abstract":"<p><strong>Aim: </strong>Financial incentives improve response to electronic health surveys, yet little is known about how unconditional incentives (guaranteed regardless of survey completion), conditional incentives, and various combinations of incentives influence response rates. We compared electronic health survey completion with two different financial incentive structures.</p><p><strong>Methods: </strong>We invited women aged 30-64 years enrolled in a U.S. healthcare system and overdue for Pap screening to complete a web-based survey after receiving a mailed human papillomavirus (HPV) self-sampling kit in a pragmatic trial. HPV kit returners (<i>n</i> = 272) and non-returners (<i>n</i> = 1,083) were allocated to one of two different incentive structures: (1) Unconditional: $5 pre-incentive only (<i>n</i> = 653); (2) Combined: $2 pre-incentive plus $10 post-incentive conditional on completion (<i>n</i> = 702). Chi-square tests evaluated whether survey completion differed by incentive structure within kit return groups or was modified by kit return status. For each incentive-by-kit status group, the cost-per-survey response was calculated as: ([number invited*pre-incentive amount] + [number responses*post-incentive amount]) / number responses.</p><p><strong>Results: </strong>Overall, survey response was higher in kit returners vs. kit non-returners (42.6% <i>vs.</i> 11.0%, <i>P</i> < 0.01), and survey response was higher in the combined (20.1%) <i>vs.</i> unconditional (14.4%) incentive group (<i>P</i> = 0.01). Kit return status did not modify the association between incentive type and survey response (<i>P</i> = 0.52). Among respondents, time to survey completion did not differ by incentive type among either kit returners or non-returners. Among returners, the cost-per-survey response was similar between groups ($13.57 unconditional; $14.15 combined); among non-returners, the cost was greater in the unconditional ($57.78) versus the combined ($25.22) group.</p><p><strong>Conclusion: </strong>A combined incentive can be cost-effective for increasing survey response in health services research, particularly in hard-to-reach populations.</p>","PeriodicalId":72693,"journal":{"name":"Connected health and telemedicine","volume":"2 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462406/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10467184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Electrooculography-based Human-Computer Interaction (EOG-HCI) is an emerging field. Research in this domain aims to capture eye movement patterns by measuring the corneal-retinal potential difference. This enables translating eye movements into commands, facilitating human-computer interaction through eye movements. This paper reviews articles published from 2002 to 2022 in the EOG-HCI domain, aiming to provide a comprehensive analysis of the current developments and challenges in this field. It includes a detailed and systematic analysis of EOG signal electrode arrangement, hardware design for EOG signal acquisition, commonly used features, and algorithms. Representative studies in each section are presented to help readers quickly grasp the common technologies in this field. Furthermore, the paper emphasizes the analysis of interaction design within the EOG-HCI domain, categorizing different interaction task types and modalities to provide insights into prevalent interaction research. The focus of current research in the field is revealed by examining commonly used evaluation metrics. Lastly, a user-centered EOG-HCI research model is proposed to visually present the current research status in the EOG-HCI field from the perspective of users. Additionally, we highlight the challenges and opportunities in this field.
{"title":"Review of electrooculography-based human-computer interaction: recent technologies, challenges and future trends","authors":"Linkai Tao, Hao Huang, Chen Chen, Loe Feijs, Jun Hu, Wei Chen","doi":"10.20517/chatmed.2023.05","DOIUrl":"https://doi.org/10.20517/chatmed.2023.05","url":null,"abstract":"Electrooculography-based Human-Computer Interaction (EOG-HCI) is an emerging field. Research in this domain aims to capture eye movement patterns by measuring the corneal-retinal potential difference. This enables translating eye movements into commands, facilitating human-computer interaction through eye movements. This paper reviews articles published from 2002 to 2022 in the EOG-HCI domain, aiming to provide a comprehensive analysis of the current developments and challenges in this field. It includes a detailed and systematic analysis of EOG signal electrode arrangement, hardware design for EOG signal acquisition, commonly used features, and algorithms. Representative studies in each section are presented to help readers quickly grasp the common technologies in this field. Furthermore, the paper emphasizes the analysis of interaction design within the EOG-HCI domain, categorizing different interaction task types and modalities to provide insights into prevalent interaction research. The focus of current research in the field is revealed by examining commonly used evaluation metrics. Lastly, a user-centered EOG-HCI research model is proposed to visually present the current research status in the EOG-HCI field from the perspective of users. Additionally, we highlight the challenges and opportunities in this field.","PeriodicalId":72693,"journal":{"name":"Connected health and telemedicine","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134884429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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