A randomized controlled trial of analogue pharmacogenomic testing feedback for psychotropic medications

• প্রধান লেখক: John Young (Author), Aileen Jimenez (Author), Madeline Pruett (Author), Laken Hancock (Author), McCall Schruff (Author)
• বিন্যাস: গ্রন্থ
• প্রকাশিত: Elsevier, 2023-12-01T00:00:00Z.
• বিষয়গুলি: article
• অনলাইন ব্যবহার করুন: Connect to this object online.
• Notes: 2772-6282; 10.1016/j.pecinn.2022.100119
• Keywords: Pharmacogenomic testing; Medical decision-making; Psychotropics; Patient interaction; Clinical feedback; Public aspects of medicine; RA1-1270
• Source: PEC Innovation, Vol 2, Iss , Pp 100119- (2023)

Objective: To examine the impact of various presentations of pharmacogenomic testing results using a published, color-coded decision support tool (DST) format as a standard stimulus to list possible medications. Methods: Participants were randomly assigned to groups and asked to decide which psychotropic medication they would prefer if depressed. Three of the groups varied the color-coded category of fluoxetine and received a statement indicating that this was the most prescribed drug for depression. A fourth control condition omitted base rate information. Participants also provided detail about their decision-making processes through a qualitative interview. Results: Comparison of the first three groups indicated that significantly more participants selected medications from the highest category of likely effectiveness when fluoxetine appeared in this list. Comparison of the control group to its relevant analogue suggested no significant differences in selection strategy. Qualitative interview responses indicated participant comfort with genetic testing despite awareness of having very limited understanding of these techniques and their implications. Conclusions: Both DST color-coding and base rates were influential in driving drug selection decisions, despite most participants indicating they did not understand this information. Innovation: Efforts to standardize pharmacogenomic stimuli may lead to advances in methods of studying quantifiable healthcare decisions. Attention to the context for presenting test results may also be a useful source of understanding patient responses, particularly regarding complex tests that are likely to be interpreted heuristically.