Background: Factors related to medication adherence in patients with schizophrenia have always been key to the treatment and rehabilitation of these patients. However, the treatment modes in different countries are not the same, and there is no research on the factors influencing medication adherence under different mental health service modes. Objectives: The purpose of this study was to explore medication adherence and its influencing factors in patients with schizophrenia in the Chinese institutional environment. Methods: We conducted a cross-sectional study of hospitalized persons living with schizophrenia from November 2018 to January 2019. A systematic sampling method was used to select 217 hospitalized persons living with schizophrenia. The Medication Adherence Rating Scale (MARS), Positive and Negative Syndrome Scale (PANSS), General Self-Efficacy Scale (GSES), Schizophrenia Quality of Life Scale (SQLS), and Scale of Social Skills for Psychiatric Inpatients (SSPI) were used to explore medication compliance and its influencing factors in the Chinese institutional environment. Results: The descriptive analysis and ANOVA showed that there were no significant differences in medication adherence when assessed by demographic characteristics such as sex, marital status, and education level (p > 0.05). A correlation analysis showed that there was no significant correlation between medication adherence and mental symptoms (p > 0.05) but that there was a positive correlation with self-efficacy, quality of life, and activities of daily living (p < 0.01). The linear regression analysis showed that self-efficacy, psychosocial factors, symptoms/side effects, and activities of daily living had significant effects on medication adherence (F = 30.210, p < 0.001). Conclusions: Our findings show that the self-efficacy, quality of life, and social function of patients with schizophrenia are important self-factors influencing medication adherence in the Chinese institutional environment.

Background: Due to drug efficacy, adverse reactions, and individual differences, clinicians face significant challenges in drug selection for the treatment of depression. However, the study on predicting antidepressant treatment response based on pharmacogenomics has not yet been determined. Methods: A total of 178 participants were recruited and randomly assigned to either pharmacogenomics-guided antidepressant treatment or regular antidepressant treatment. All participants completed pharmacogenomic sampling at baseline and underwent neuropsychological systemic assessments at baseline and at 4-week, 8-week, 16-week, and 32-week follow-ups. Results: Compared with the control group, the pharmacogenomics-guided group showed significant differences in the effect of DARS scores within 32 weeks (P_Bonferroni < 0.05), showing a significant time and group effect (p < 0.001; p = 0.007, respectively). In addition, the pharmacogenomic-guided group showed significant differences in ASEC scores within 32 weeks (P_Bonferroni < 0.05), showing a significant time effect, group effect, and group × time effect (p < 0.001; p = 0.018; p = 0.009, respectively). However, there was no significant difference in HAM-D₁₇, HAM-A, PDQ-D, and PSQI between the two groups within 32 weeks (P_Bonferroni > 0.05). Conclusions: Pharmacogenomics-guided antidepressant prescribing effectively alleviates anhedonia and reduces adverse effects in patients with first-episode depression, but there is no significant improvement in major psychopathological symptoms. These findings carry important implications for the early application of pharmacogenomic testing in primary care settings for depression.