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Diseases that resolve spontaneously can increase the belief that ineffective treatments work

Blanco, Fernando; Matute, Helena

SOCIAL SCIENCE & MEDICINE
2020
VL / 255 - BP / - EP /
abstract
Rationale: Self-limited diseases resolve spontaneously without treatment or intervention. From the patient's viewpoint, this means experiencing an improvement of the symptoms with increasing probability over time. Previous studies suggest that the observation of this pattern could foster illusory beliefs of effectiveness, even if the treatment is completely ineffective. Therefore, self-limited diseases could provide an opportunity for pseudotherapies to appear as if they were effective. Objective: In three computer-based experiments, we investigate how the beliefs of effectiveness of a pseudotherapy form and change when the disease disappears gradually regardless of the intervention. Methods: Participants played the role of patients suffering from a fictitious disease, who were being treated with a fictitious medicine. The medicine was completely ineffective, because symptom occurrence was uncorrelated to medicine intake. However, in one of the groups the trials were arranged so that symptoms were less likely to appear at the end of the session, mimicking the experience of a self-limited disease. Except for this difference, both groups received similar information concerning treatment effectiveness. Results: In Experiments 1 and 2, when the disease disappeared progressively during the session, the completely ineffective medicine was judged as more effective than when the same information was presented in a random fashion. Experiment 3 extended this finding to a new situation in which symptom improvement was also observed before the treatment started. Conclusions: We conclude that self-limited diseases can produce strong overestimations of effectiveness for treatments that actually produce no effect. This has practical implications for preventative and primary health services. The data and materials that support these experiments are freely available at the Open Science Framework (https://osf.io/xt3z9/). https://bit.ly/2FMPrMi.

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