1. Randomised study of the effects of sense of entitlement and conflict of interest contrarianism on researcher decision-making to work with the alcohol industry
- Author
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Jim McCambridge, Kypros Kypri, Jan R. Boehnke, Lisa Bero, and Marcus Bendtsen
- Subjects
Conflict of interest ,Contrarianism ,Entitlement ,Industry funding ,Alcohol industry ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background It is well established that the tobacco industry used research funding as a deliberate tactic to subvert science. There has been little wider attention to how researchers think about accepting industry funding. We developed, then tested, hypotheses about two psychological constructs, namely, entitlement and conflict of interest contrarianism (CoI-C) among alcohol researchers who had previously received industry funding. Methods A mixed-methods pilot study involved construct and instrument development, followed by an online survey and nested 3-arm randomised trial. We randomly allocated alcohol industry funding recipients to one of three conditions. In two experimental conditions we asked participants questions to remind them (and thus increase the salience) of their sense of entitlement or CoI-C. We compared these groups with a control group who did not receive any reminder. The outcome was a composite measure of openness to working with the alcohol industry. Results 133 researchers were randomised of whom 79 completed the experiment. The posterior distribution over effect estimates revealed that there was a 94.8% probability that reminding researchers of their CoI-C led them to self-report being more receptive to industry funding, whereas the probability was 68.1% that reminding them of their sense of entitlement did so. Biomedical researchers reported being more open to working with industry than did psychosocial researchers. Conclusion Holding contrarian views on conflict of interest could make researchers more open to working with industry. This study shows how it is possible to study researcher decision-making using quantitative experimental methods.
- Published
- 2024
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