How Health Professionals Conceptualize and Represent Placebo Treatment in Clinical Trials and How Their Patients Understand It: Impact on Validity of Informed Consent

<div><p>Context</p><p>Previous studies suggested that many patients, who have given their informed consent to participate in randomized controlled trials (RCT), have somewhat limited understanding of what a placebo treatment is. We hypothesized that the relationship between patients and their health professionals plays a central role in this understanding.</p><p>Methods</p><p>We interviewed 12 patients included in RCTs (nine suffering from Parkinson’s disease and three from Huntington’s disease) and 18 health professionals involved with RCTs (eight principal investigators, four associated physicians and six clinical research associates). Semi-structured interviews were conducted after the RCTs had ended but before the treatment allocation was revealed.</p><p>Results</p><p>Only two patients clearly understood the aim of placebo-controlled RCTs. Only one principal investigator said she asks all her patients whether they agree to participate in RCTs. The seven others said they only ask patients who seem more likely to be compliant. Their selection criteria included docility and personality traits associated in other studies with enhanced placebo responses. According to 13 of the 18 health professionals, their relationship with patients may influence the amplitude of the placebo response. All but one clinical research associates added that the placebo response could result from a “maternal” type of care. All principal investigators said they have a strong influence on their patient's decision to participate. Finally, when interviewees were asked to narrate a memory of a medically unexplained healing, in eight of 11 physicians' narratives the beneficiary was a child while in 10 of 12 patients' narratives it was an adult.</p><p>Conclusion</p><p>Our observations suggest that the interrelationship between health professionals and patients involved in RCTs could be compared to that between parents and children. Therefore, adherence to formal rules regarding informed consent does not ensure a balanced relationship between patients and health professionals.</p></div

Opinion of principal investigators about patients' inclusion in RCTs.

<p>Opinion of principal investigators about patients' inclusion in RCTs.</p

Conceptualization of the placebo response.

<p>Conceptualization of the placebo response.</p

List of questions asked to interviewees.

<p>List of questions asked to interviewees.</p

Interviewees.

<p>Interviewees.</p

General influence of PI and CRA on placebo response.

<p>General influence of PI and CRA on placebo response.</p

Specific influence of APs on treatment response of their patients.

<p>Specific influence of APs on treatment response of their patients.</p

Analysis of personal memories of unexplained healings.

<p>Analysis of personal memories of unexplained healings.</p

Figures S1-S12. Flow charts for inclusion of studies from Low statistical power in biomedical science: a review of three human research domains

Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric and somatic diseases, excluding treatment studies, in order to estimate the average statistical power across these domains. Taking the effect size indicated by a meta-analysis as the best estimate of the likely true effect size, and assuming a threshold for declaring statistical significance of 5%, we found that approximately 50% of studies have statistical power in the 0–10% or 11–20% range, well below the minimum of 80% that is often considered conventional. Studies with low statistical power appear to be common in the biomedical sciences, at least in the specific subject areas captured by our search strategy. However, we also observe evidence that this depends in part on research methodology, with candidate gene studies showing very low average power and studies using cognitive/behavioural measures showing high average power. This warrants further investigation

Table S2. Characteristics of included studies from Low statistical power in biomedical science: a review of three human research domains

Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric and somatic diseases, excluding treatment studies, in order to estimate the average statistical power across these domains. Taking the effect size indicated by a meta-analysis as the best estimate of the likely true effect size, and assuming a threshold for declaring statistical significance of 5%, we found that approximately 50% of studies have statistical power in the 0–10% or 11–20% range, well below the minimum of 80% that is often considered conventional. Studies with low statistical power appear to be common in the biomedical sciences, at least in the specific subject areas captured by our search strategy. However, we also observe evidence that this depends in part on research methodology, with candidate gene studies showing very low average power and studies using cognitive/behavioural measures showing high average power. This warrants further investigation