Pharmaceutical product withdrawal: Attributions of blame and its impact on trust

BackgroundSix major pharmaceutical products were withdrawn from the market from 2000 to 2006. Little evidence exists in understanding consumer reactions to such events and the influence the withdrawal has on its competitors.ObjectiveTo explore consumers' attribution of blame after pharmaceutical product market withdrawal (PPMW) and its effect on trust.MethodsSubjects were assigned randomly to 4 groups and provided a unique hypothetical PPMW scenario and asked to imagine themselves in the situation described. Each scenario represented a different “distance” from the PPMW (eg, whether subjects were asked to assume they were taking the withdrawn drug or a therapeutic substitute). Blame of and trust in several key professionals/groups were measured.ResultsCloser “distance” to the PPMW resulted in higher blame attributions for the Food and Drug Administration (FDA), pharmaceutical company (Pharma), and the physician. Although the pattern of trust scores did not differ based on “distance,” insurance companies and Pharma suffered from low trust, whereas pharmacists and physicians received higher trust ratings. Blaming appeared to be no different between consumers on a withdrawn product and those consumers on a product in the same therapeutic class (“substitute” product).ConclusionSubstitute products (drugs in the same therapeutic class) appear to be affected in the event of a PPMW, although drugs used to treat the same disease do not appear to be so affected. The difficult-to-explain findings with respect to trust may be accounted for by the fact that trust is more downstream than blame (based on the scenario presentations) and that trust is a complex construct with multiple antecedents. Although the bonds of interpersonal trust remain stronger than those of institutional trust, the likelihood of situational trust versus overall trust may complicate this picture of understanding trust. It may be possible that trust is impervious to this one negative instance versus many positive interactions.