학술논문

Attitudes on pharmacogenetic testing in psychiatric patients with treatment‐resistant depression
Document Type
article
Source
Depression and Anxiety. 37(9)
Subject
Pharmacology and Pharmaceutical Sciences
Biomedical and Clinical Sciences
Clinical Sciences
Patient Safety
Genetic Testing
Behavioral and Social Science
Mental Health
Genetics
Depression
Brain Disorders
Clinical Research
Mental health
Good Health and Well Being
Attitude
Depressive Disorder
Treatment-Resistant
Humans
Motivation
Pharmacogenomic Testing
attitude
depression
genetic testing
motivation
pharmacogenomic testing
risk
Veterans
Psychology
Psychiatry
Clinical sciences
Clinical and health psychology
Social and personality psychology
Language
Abstract
BackgroundNovel technologies make it possible to incorporate pharmacogenetic testing into the medical management of depression. However, previous studies indicate that there may be a subset of subjects who have concerns about genetic testing and may be psychologically vulnerable. If so, pharmacogenetic testing in depressed subjects could negatively impact their mental health and undermine treatment goals.MethodsIn this study, we developed a standardized instrument to assess motivations and attitudes around pharmacogenetic testing in a cohort of 170 depressed Veterans participating in a multi-center clinic trial.ResultsTesting reveals that subjects were largely positive about the use of genetic testing to guide pharmacological treatment and help plan their future. Most subjects showed only modest concerns about the impact on family, inability to cope with the results, and fear of discrimination. The severity of depression did not predict the concern expressed about negative outcomes. However, non-Caucasian subjects were more likely on average to endorse concerns about poor coping and fear of discrimination.ConclusionsThese data indicate that while the overall risk is modest, some patients with depression may face psychosocial challenges in the context of pharmacogenetic testing. Future work should identify factors that predict distress and aim to tailor test results to different populations.