Liar! Liar! Identifying eligibility fraud by applicants in digital health research

Glazer, Jillian V.; MacDonnell, Kirsten; Frederick, Christina; Ingersoll, Karen S.; Ritterband, Lee M.

doi:10.1016/j.invent.2021.100401

Cited by 37 publications

(40 citation statements)

References 21 publications

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“…However, it is important to consider that successful recruitment strategies do not necessarily translate into high participant retention. This could be due, in part, to unrepresentative samples that enroll in a study to collect financial incentives and then dropout [ 86 , 87 ]. Studies may be highly effective if they place equal importance on their recruitment and retention strategies, while applying sample validation approaches to ensure the representativeness of their study sample.…”

Section: Discussionmentioning

confidence: 99%

“…• Adapt incentives and nudges provided to participants based on their motivation profile: offer different incentives or nudges at each key step of the study procedure. Monetary incentives may contribute to higher study enrollment [48,53,[55][56][57]70,78], after sample validation [86,87], whereas nudges in the form of assistance during onboarding [48,55] and the provision of reminders [50,53,55,60,64,73] or a participant community (eg, through citizen science [2]) could contribute to higher retention. As technology replaces in-person interactions, the procedures set in place should be user-friendly [50,53,[55][56][57]65,66] and enable participants to build personal relationships, with either study participants or study investigators [116].…”

Section: Future Directions For Remote Digital Health Study Planningmentioning

confidence: 99%

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Enrollment and Retention of Participants in Remote Digital Health Studies: Scoping Review and Framework Proposal

Daniore¹,

Nittas²,

Wyl³

2022

J Med Internet Res

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Background Digital technologies are increasingly used in health research to collect real-world data from wider populations. A new wave of digital health studies relies primarily on digital technologies to conduct research entirely remotely. Remote digital health studies hold promise to significant cost and time advantages over traditional, in-person studies. However, such studies have been reported to typically suffer from participant attrition, the sources for which are still largely understudied. Objective To contribute to future remote digital health study planning, we present a conceptual framework and hypotheses for study enrollment and completion. The framework introduces 3 participation criteria that impact remote digital health study outcomes: (1) participant motivation profile and incentives or nudges, (2) participant task complexity, and (3) scientific requirements. The goal of this study is to inform the planning and implementation of remote digital health studies from a person-centered perspective. Methods We conducted a scoping review to collect information on participation in remote digital health studies, focusing on methodological aspects that impact participant enrollment and retention. Comprehensive searches were conducted on the PubMed, CINAHL, and Web of Science databases, and additional sources were included in our study from citation searching. We included digital health studies that were fully conducted remotely, included information on at least one of the framework criteria during recruitment, onboarding or retention phases of the studies, and included study enrollment or completion outcomes. Qualitative analyses were performed to synthesize the findings from the included studies. Results We report qualitative findings from 37 included studies that reveal high values of achieved median participant enrollment based on target sample size calculations, 128% (IQR 100%-234%), and median study completion, 48% (IQR 35%-76%). Increased median study completion is observed for studies that provided incentives or nudges to extrinsically motivated participants (62%, IQR 43%-78%). Reducing task complexity for participants in the absence of incentives or nudges did not improve median study enrollment (103%, IQR 102%-370%) or completion (43%, IQR 22%-60%) in observational studies, in comparison to interventional studies that provided more incentives or nudges (median study completion rate of 55%, IQR 38%-79%). Furthermore, there were inconsistencies in measures of completion across the assessed remote digital health studies, where only around half of the studies with completion measures (14/27, 52%) were based on participant retention throughout the study period. Conclusions Few studies reported on participatory factors and study outcomes in a consistent manner, which may have limited the evidence base for our study. Our assessment may also have suffered from publication bias or unrepresentative study samples due to an observed preference for participants with digital literacy skills in digital health studies. Nevertheless, we find that future remote digital health study planning can benefit from targeting specific participant profiles, providing incentives and nudges, and reducing study complexity to improve study outcomes.

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Section: Discussionmentioning

confidence: 99%

Section: Future Directions For Remote Digital Health Study Planningmentioning

confidence: 99%

Enrollment and Retention of Participants in Remote Digital Health Studies: Scoping Review and Framework Proposal

Daniore¹,

Nittas²,

Wyl³

2022

J Med Internet Res

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“…In addition to the measurement limitations, the recruited study sample was primarily highly-educated, of high socioeconomic status, and non-Hispanic white, limiting generalizability. A strength of our study includes the use of online recruitment methods (Glazer et al, 2021 ) to identify a sample generalizable to older individuals who are likely to be interested in using an Internet intervention – and our accrual of 311 participants within 1 year suggests that there is considerable interest.…”

Section: Discussionmentioning

confidence: 99%

Effects of an internet-delivered insomnia intervention for older adults: A secondary analysis on symptoms of depression and anxiety

et al. 2022

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Objective To test whether an Internet-delivered cognitive behavioral therapy for insomnia (CBT-I) program for older adults attenuates symptoms of depression and anxiety. Methods Adults aged ≥ 55 with insomnia were randomized to SHUTi-OASIS (Sleep Healthy Using the Internet for Older Adult Sufferers of Insomnia and Sleeplessness; N = 207) or Patient Education (PE; N = 104). Depression and anxiety were assessed (HADS-D and HADS-A, respectively) at baseline, post-assessment, and 6- and 12-month follow-ups. Results Multilevel modeling of HADS-D showed a condition by time interaction ( F [3,779] = 3.23, p = .02): SHUTi-OASIS participants reported lower symptoms than PE at post-assessment. There was no such interaction effect for HADS-A ( F [3,779] = 2.12, p = .10). Generalized linear modeling showed no moderation of effects by baseline symptom severity. Conclusions Participants randomized to Internet-delivered CBT-I showed stable depression and anxiety across time, while control participants’ depressive symptoms briefly increased. CBT-I may help prevent development or worsening of psychological distress among older adults with insomnia. TRIAL REGISTRATION [Registered at ClinicalTrials.gov; identifier removed for anonymity]

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“…Raw data were “cleaned” using standard practices including humanistic and heuristic approaches that involve inclusion of survey completion time, originating IP address, assessment of correlated variables and plausible associations, and attention-check item response, to reduce the likelihood of including fraudulent or duplicate responses [ 26 ]. Analysis is underway and has consisted of three phases: 1) exploratory factor analyses to ensure scale items load to their intended scales, including calculation and reporting of psychometric properties, 2) univariate descriptive analyses, including calculating means, standard deviations and scale and item distributions and weighing sample analyses appropriately to represent population estimates for the three geographic regions and 3) bivariate and multivariate models to examine relationships between variables.…”

Section: Methodsmentioning

confidence: 99%

Community engaged research to measure the impact of COVID-19 on vulnerable community member’s well-being and health

Barwise

Egginton

Pacheco-Spann

et al. 2022

Wien Klin Wochenschr

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Summary Background The COVID-19 pandemic has exacerbated existing income inequality and health disparities in the United States (US). The objective of this study was to conduct timely, community-engaged research to understand the disproportionate impact of the COVID-19 pandemic on historically under-resourced communities with the goal of improving health equity. The initiative focused on priorities identified by Community Health Needs Assessments (CHNA) conducted every 3 years per Federal funding requirements. These were access to healthcare, maternal/child health, obesity/food insecurity/physical activity, and mental health/addiction. Methods In the first three quarters of 2021, we developed and employed mixed methods in three simultaneous phases of data collection. In phase 1, we used purposive sampling to identify key informants from multiple stakeholder groups and conducted semi-structured interviews. In phase 2, we held focus groups with community members from historically marginalized demographics. In phase 3, we developed a survey using validated scales and distributed it to diverse communities residing in the geographic areas of our healthcare system across four states. Conclusion Healthcare systems may use the methodology outlined in this paper to conduct responsive community engagement during periods of instability and/or crisis and to address health equity issues. The results can inform sustainable approaches to collaborate with communities to build resilience and prepare for future crises.

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Liar! Liar! Identifying eligibility fraud by applicants in digital health research

Cited by 37 publications

References 21 publications

Enrollment and Retention of Participants in Remote Digital Health Studies: Scoping Review and Framework Proposal

Enrollment and Retention of Participants in Remote Digital Health Studies: Scoping Review and Framework Proposal

Effects of an internet-delivered insomnia intervention for older adults: A secondary analysis on symptoms of depression and anxiety

Community engaged research to measure the impact of COVID-19 on vulnerable community member’s well-being and health

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