Xun Wang1, Wufang Zhang1, Ning Ma1, Lili Guan1, Samuel F Law1, Xin Yu1, Hong Ma1. 1. With the exception of Dr. Law, who is affiliated with the Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada, the authors are affiliated with Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, People's Republic of China (e-mail: yuxin@bjmu.edu.cn ).
Abstract
OBJECTIVE: Nonadherence to antipsychotic medication is a major health concern. Identification of risk factors associated with nonadherence is a useful initial step toward designing an effective intervention. This study compared the characteristics of medication-adherent and -nonadherent outpatients with schizophrenia in a Chinese community setting. METHODS: In a naturalistic, multicenter, and cross-sectional design, 601 outpatients with schizophrenia served by the National Continuing Management and Intervention Program for Psychoses (the "686 program") were surveyed from June 2013 to January 2014 in four Chinese cities. On the basis of self-reported behavior, the patients were divided into medication-adherent and -nonadherent groups. Logistic regression analyses were performed to identify potential risk factors associated with nonadherence. RESULTS: The analyses included 554 patients, 20% of whom were considered to be nonadherent. Compared with the adherent group, the nonadherent group had a longer period of untreated psychosis (odds ratio [OR]=1.09), lower body mass index (OR=.94), higher rate of rural residency (OR=2.01), and lower monthly household income per capita (OR=.94/100 renminbi) (p<.05 by hierarchical analysis). Other characteristics (age, gender, occupation, education, marital status, living with family, age at initial presentation of symptoms, duration of illness, and type of antipsychotic medication) did not differ significantly between the groups. CONCLUSIONS: Medication-adherent and -nonadherent groups differed significantly in some social and treatment characteristics. These findings may be useful in informing the development of strategies for reducing medication nonadherence.
OBJECTIVE: Nonadherence to antipsychotic medication is a major health concern. Identification of risk factors associated with nonadherence is a useful initial step toward designing an effective intervention. This study compared the characteristics of medication-adherent and -nonadherent outpatients with schizophrenia in a Chinese community setting. METHODS: In a naturalistic, multicenter, and cross-sectional design, 601 outpatients with schizophrenia served by the National Continuing Management and Intervention Program for Psychoses (the "686 program") were surveyed from June 2013 to January 2014 in four Chinese cities. On the basis of self-reported behavior, the patients were divided into medication-adherent and -nonadherent groups. Logistic regression analyses were performed to identify potential risk factors associated with nonadherence. RESULTS: The analyses included 554 patients, 20% of whom were considered to be nonadherent. Compared with the adherent group, the nonadherent group had a longer period of untreated psychosis (odds ratio [OR]=1.09), lower body mass index (OR=.94), higher rate of rural residency (OR=2.01), and lower monthly household income per capita (OR=.94/100 renminbi) (p<.05 by hierarchical analysis). Other characteristics (age, gender, occupation, education, marital status, living with family, age at initial presentation of symptoms, duration of illness, and type of antipsychotic medication) did not differ significantly between the groups. CONCLUSIONS: Medication-adherent and -nonadherent groups differed significantly in some social and treatment characteristics. These findings may be useful in informing the development of strategies for reducing medication nonadherence.
Authors: Wei Yu; Jie Tong; Xirong Sun; Fazhan Chen; Jie Zhang; Yu Pei; Tingting Zhang; Jiechun Zhang; Binggen Zhu Journal: Int J Environ Res Public Health Date: 2021-04-29 Impact factor: 3.390