Structural model of determinants of medication adherence in elderly individuals with tuberculosis in Iran

"Medication adherence" is essential for the successful treatment of tuberculosis. Numerous studies have indicated a higher probability of non-adherence to medication among elderly individuals with tuberculosis. As the elderly population continued to grow, non-adherence to medication in this group could lead to the failure of achieving the goal of tuberculosis eradication and make them a significant source of tuberculosis infection transmission in the community. Recognizing the significance of medication adherence in elderly individuals with tuberculosis, this study aims to developing and testing a structural model of determinants of medication adherence in elderly individuals with tuberculosis in Iran.

The present study is part of a PhD dissertation that utilized a mixed methods approach and a sequential exploratory method. The qualitative portion of the study focused on factors influencing medication adherence in elderly individuals with tuberculosis. Subsequently, experts in the fields of tuberculosis and elderly health identified influential variables using the Delphi method. Valid and reliable questionnaires were then administered to 305 elderly individuals with tuberculosis and their family caregivers to measure these selected variables. A structural model was employed to examine the relationship between concepts and predict medication adherence variance.

44.92% of elderly individuals with tuberculosis had low medication adherence, 27.54% had moderate medication adherence, and 27.54% had complete medication adherence. According to the results of the sequential logistic regression test (simultaneous type), the variables studied predicted medication adherence behavior to a very acceptable level. The coefficient of determination values ​​obtained from the three statistics McFadden (0.603), Nagel kerke (0.888), and Cox and Snell (0.849) indicated the high explanatory power of the model by the predictor variables. The findings from the structural equation model showed that the category of personal factors (such as reminders to take medication on time, patient addiction, extroverted personality, depression, motivation to adhere to tuberculosis medication, presence of concomitant disease, importance of medication adherence from the patient's perspective, and side effects of tuberculosis medications) directly and significantly predict medication adherence. Additionally, the categories of interpersonal factors (including indicators of caregiver general health, caregiver care pressure, caregiver income adequacy, patient marital status, patient education, patient trust in the physician, and appropriate behavior of the treatment team from the perspective of patients) and extra-organizational factors (including indicators of social support, quality of life, rejection by others, and the patient's willingness to disclose the disease) also significantly and indirectly (through the category of personal factors) predict medication adherence in elderly individuals with tuberculosis. The total effect of personal factors in predicting medication adherence was estimated to be 62%, which was higher than other categories.

The findings of the current study demonstrate that medication adherence in elderly individuals with tuberculosis is a complex and multidimensional phenomenon. The relationship between the components of the model suggests that a comprehensive understanding of all concepts within the model is necessary to effectively plan and implement interventions aimed at improving medication adherence in this population. Additionally, the structural equation model revealed that the personal factor category had the greatest impact on predicting medication adherence compared to other categories. This suggests that elderly individuals with tuberculosis play a crucial role in medication adherence. The structural model presented in this study can serve as a valuable tool for researchers, policymakers, and healthcare providers to inform future studies, interventions, and policy decisions related to tuberculosis control.