Impact of Cognitive Behavioral Therapy (CBT) on Depression Severity in Patients with Chronic Illness: A Randomized Controlled Trial - Saboor, Saleha; Shuja, Naveed; Shuja, Arslan (Biological and Clinical Sciences Research Journal, 2025)
Depression is a frequent comorbidity among chronic disease patients (i.e., diabetes, cardiovascular disease, and chronic kidney disease). It hurts treatment compliance, quality of life, and prognosis. Cognitive Behavioral Therapy (CBT) is an evidence-based psychotherapeutic modality, and very little research has investigated its effects on depression among chronically ill populations in South Asia. Objective: The study aimed to compare the effectiveness of CBT in the reduction of depression severity in patients with a chronic illness with that of standard medical care treatment on its own. Methods: A randomized controlled trial was performed at Tertiary care hospitals in Lahore, Pakistan, between January 2024 and January 2025. We recruited and randomly assigned 120 chronically ill patients with moderate-to-severe depression (HDRS score ≥18) to an intervention group of 12 sessions of CBT per week on top of standard care (n = 60) or a control group (n=60) receiving standard medical care only. The Hamilton Depression Rating Scale (HDRS) was used to determine the severity of depression at baseline, 6 weeks, and 12 weeks. The data analysis was performed using repeated-measures ANOVA. Results: There was no difference in baseline demographic and clinical characteristics. At 6 weeks, there was a significantly larger decrease in HDRS scores in the intervention group than in the controls (16.8 ± 2.7 vs. 20.9 ± 3.0, p < 0.001). The results of the HDRS at 12 weeks further declined to 11.2 ± 2.3 in the intervention arm, as opposed to 19.1 ± 2.6 in the control arm (p < 0.001). Conclusion: CBT also had a significant impact in terms of depression severity and secondary outcomes, including treatment adherence and quality of life. CBT may have overall advantages in terms of its integration into chronic disease management algorithms, especially in healthcare facilities with limited resources.