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To the Editor: Increased commercialization and competition in clinical research has led to difficulties in enrolling human subjects in a timely manner to satisfy sponsors.¹ As a result, clinical trials increasingly recruit participants outside the traditional clinic- or hospital-based settings. Investigators often advertise via radio or newspapers and promise payment for participation. These new approaches have the potential to recruit large numbers of participants to central locations and to allow faster subject accrual.

Methods
Family Health International has begun to use recent technological advances, such as interactive voice response systems (IRVSs) and the Internet, to explore the impact on data quality of more commercialized methods of recruiting subjects for clinical research. We initiated a randomized controlled trial of 2 approved barrier methods to further characterize their contraceptive effectiveness. Subjects were offered $150 for participating in the trial. To increase speed of recruitment, we advertised in 5 metropolitan newspapers and enrolled participants by telephone. The initial telephone call lasted about 30 minutes. Once patients were enrolled and randomized, we sent the study materials to the home addresses of the participants. During this 1-month study, participants were asked to call a toll-free IVRS daily and answer a few questions using the keypad of their telephone. We monitored these daily calls to evaluate participant compliance with the protocol and potential bogus participation.

Results
Of the first 25 participants randomized into the trial, our monitoring system identified 4 participants who consistently placed their IVRS calls from the same telephone number, usually only minutes apart. When our staff attempted to contact these 4 participants, they failed to respond and stopped participating in the trial. A fifth participant placed a single telephone call from the number used by the above-mentioned participants. Through an Internet search of an address database, we discovered that 2 additional participants had provided suspicious home addresses. These 2 participants ceased participating in the trial when our staff tried to contact them. A eighth participant provided an invalid address, and the study material was returned. Thus, 8 of 25 participants (32%; 95% confidence interval, 15%-54%) provided information that led to their exclusion from the trial.

Comment
Our small study detected big problems. We were forced to terminate the trial because of the unacceptably high exclusion rate. We caution researchers who embark on studies with remuneration of participants and no face-to-face contact that bogus participation may threaten data validity. We suspect that many trials, even those in which face-to-face contact does occur, enroll participants who knowingly provide invalid data. For example, we recently excluded a participant in a trial requiring exclusive use of male condoms because the site investigator discovered that the participant had been receiving prescriptions for oral contraceptives during the trial. While increasing attention is being placed on improving the quality of trials by reducing investigator fraud^2-3 and improving methodology,^4-5 bogus participation also needs to be scrutinized for its potential threat to the validity of clinical trials.

Markus J. Steiner, PhD; Amy E. Lovvorn, MPH; Kenneth F. Schulz, PhD
Family Health International
Research Triangle Park, NC

1. Department of Health and Human Services, Office of the Inspector General. Recruiting Human Subjects: Pressures in Industry-Sponsored Clinical Research (OEI-01-97-00195). Available at: http://www.hhs.gov/oig/oei/summaries/b459.pdf. Accessibility verified December 19, 2000. 2. Mayor S. New governance framework for NHS research aims to stop fraud. BMJ. 2000;321:725. FREE FULL TEXT 3. Weber W. European clinical research scandal investigators question self-regulation. Lancet. 2000;356:53. PUBMED 4. Schulz KF. Subverting randomization in controlled trials. JAMA. 1995;274:1456-1458. FREE FULL TEXT 5. Schulz KF, Chalmers I, Hayes RJ, Altman DG. Empirical evidence of bias: dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA. 1995;273:408-412. FREE FULL TEXT

Letters Section Editor: Stephen J. Lurie, MD, PhD, Senior Editor.

JAMA. 2001;285:293.

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