Factors associated with non-adherence to clinic visits among patients with severe mental illness enrolled in the SMILE study in Uganda

Background: Non-adherence to clinic visits among patients with severe mental illness (SMI) presents challenges to patient management, treatment outcomes, and research in resource-limited settings. This study investigated the factors associated with non-adherence to clinic visits in Uganda, using appointment attendance as a proxy for clinic adherence.

Methods: This cohort study took place at Butabika National Referral Mental Hospital and Masaka Regional Referral Hospital from January to March 2018. A total of 1,201 participants with confirmed diagnoses of SMI were systematically sampled from over 3,000 outpatients. Data on socio-demographic, psychosocial, psychiatric, and behavioural factors were collected, with adherence defined as attending scheduled visits at 3, 6, 9, and 12 months post-enrolment. Descriptive statistics, bivariate, and multivariate logistic regression analyses were employed to identify significant predictors of non-adherence.

Results: The overall prevalence of non-adherence to clinic visits was 20% (95% CI: 17.8 − 22.3%), with males showing higher rates (22.9%) compared to females (17.6%). Factors significantly associated with increased non-adherence included younger age, being treated at Butabika National Referral Mental Hospital, and alcohol use. Conversely, higher social support was linked to improved adherence. Among psychiatric variables, patients with major depressive disorder and severe psychiatric symptoms were more likely to miss appointments.

Conclusions: The study highlights the multifaceted nature of non-adherence in patients with SMI, emphasizing the need for targeted interventions addressing socio-demographic, psychosocial, and clinical factors. Enhancing social support, managing psychiatric symptoms, and reducing substance use are critical strategies for improving adherence rates, which could, in turn, lead to better health outcomes and resource optimization in mental health services.