Evidence map›Paper›PMID 40548528›Full record

Trial reportAnnals of behavioral medicine : a publication of the Society of Behavioral Medicine2025

Mitigating fraud in a fully decentralized clinical trial of a digital health intervention.

Jessie B Moore, Amy Chieng, Maddison C Pirner, Sarah Pajarito, Erin A Vogel, Molly A Bowdring, Lauren Bullard, Athena Robinson, Judith J Prochaska

Registry-linked trialAbstract readClinical Trial, Phase II
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Annals of behavioral medicine : a publication of the Society of Behavioral Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04925570 (Woebot for Substance Use Disorders Phase 2 RCT), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04925570 phase2completednot on this map

Woebot for Substance Use Disorders Phase 2 RCT: Digitally Delivered Intervention for Reducing Problematic Substance Use

TypeinterventionalSponsorWoebot HealthRan2022 to 2023Enrolled258ConditionsAlcohol Use Disorder (AUD), Substance Use DisordersArmsW-SUDs, Digitally-delivered Psychoeducation
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jessie B MooreStanford Prevention Research Center, Department of Medicine, School of Medicine, Stanford University, Palo Alto, CA, USA.ORCID 0000-0003-4657-0722
Amy ChiengStanford Prevention Research Center, Department of Medicine, School of Medicine, Stanford University, Palo Alto, CA, USA.ORCID 0000-0003-2739-7338
Maddison C PirnerWoebot Health, San Francisco, CA, USA.
Sarah PajaritoWoebot Health, San Francisco, CA, USA.
Erin A VogelTSET Health Promotion Research Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.ORCID 0000-0002-7193-8720
Molly A BowdringStanford Prevention Research Center, Department of Medicine, School of Medicine, Stanford University, Palo Alto, CA, USA.ORCID 0000-0001-5115-274X
Lauren BullardWoebot Health, San Francisco, CA, USA.ORCID 0000-0002-7368-2618
Athena RobinsonWoebot Health, San Francisco, CA, USA.ORCID 0000-0002-1393-1563
Judith J ProchaskaStanford Prevention Research Center, Department of Medicine, School of Medicine, Stanford University, Palo Alto, CA, USA.ORCID 0000-0001-7925-326X

Funding

CARDIOVASCULAR DISEASE PREVENTION TRAINING PROGRAMT32HL007034 · NHLBI · STANFORD UNIVERSITY · PI GARDNER, CHRISTOPHER D · 1985 to 2020
$8.7M
Identifying and Addressing the Effects of Social Media Use on Young Adults' E-Cigarette Use: A Solutions-Oriented ApproachK01DA055073 · NIDA · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI Erin Alyssa Vogel · 2023 to 2026
$764k
NHLBI NIH HHS T32 HL007034NIDA NIH HHS K01 DA055073NIDA NIH HHS K01DA055073NIDA NIH HHS R44D048712NIH HHS T32HL007034
6 · The paper itself

Abstract

backgroundDecentralized clinical trials (DCT), digital survey methodologies, and health monitoring technologies create the potential to reduce study participant burden as well as enhance sample diversity and enrollment pace. However, fraudulent participant activity poses a significant threat to study validity and data integrity. PURPOSE: This study quantifies fraudulent attempts at participation in a DCT of a mobile mental health intervention for problematic substance use and discusses methods to prevent and detect fraudulent activity.

methodsAdults residing in the US reporting problematic substance use were recruited for a fully remote DCT via 2 primary channels: social media advertisements and survey panels. The DCT offered incentives totaling up to $100 for completing assessments over the 12-week study. To prevent and detect fraudulent activity, the research team utilized VPN and proxy detection, checked for duplicate identifiers (e.g., emails, phone numbers, IP Addresses), and compared age and date of birth (DOB) responses across timepoints. Descriptive statistics and group comparisons across the 2 sources of recruitment methodology were utilized to quantify and characterize fraudulent activity.

resultsOf the 2,781 eligible screeners completed, 1,725 (62%) were determined to be fraudulent prior to randomization, detected most commonly by duplicate identifiers (65%) and/or VPN and proxy detection (47%). Of the 258 randomized participants, 51 (20%) were later determined to be fraudulent based upon age and/or DOB mismatch. Notable patterns in fraudulent activity (e.g., 42% of fraudulent screening respondents reported the exact age of 30 years; stylistic formatting of email address accounts) were identified. The fraudulent recruitment rate was higher for social media advertising (85%) than survey panels (26%).

conclusionsBoth social media and survey panel recruitment resulted in high levels of fraudulent activity in a DCT of a mobile mental health intervention. Researchers conducting DCTs and/or online surveys are urged to take several precautions and preventative measures to insulate against fraudulent activity including embedding identity verification procedures in consent processes. Researchers should consider making personal contact with a participant to verify identity as well as remain vigilant for fraudulent activity and its real-time dynamic potential.

trial registrationNCT04925570.

Indexed as

Clinical Trials as TopicFraudPatient SelectionSubstance-Related DisordersTelemedicineAdultDigital HealthFemaleHumansMaleMiddle AgedYoung Adultdata integritydecentralized clinical trialsfraudulent datafraudulent participant detectionmobile health intervention

Identifiers

PMID40548528
PMCPMC12205967

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.