QUALITY OF SLEEP AND ITS RELATIONSHIP WITH DEPRESSIVE SYMPTOMATOLOGY AND SUICIDALITY IN BIPOLAR DEPRESSION
DOI:
https://doi.org/10.22159/ijcpr.2026v18i1.8051Keywords:
Bipolar depression, Sleep quality, Suicidality, PSQI, Hamilton depression rating scaleAbstract
Objective: To evaluate the relationship between sleep quality, depressive symptomatology, and suicidality among patients with bipolar depression.
Methods: This hospital-based, cross-sectional observational study was conducted in the Department of Psychiatry, Burdwan Medical College and Hospital, West Bengal. Fifty participants fulfilling ICD-11 diagnostic criteria for bipolar affective disorder in the depressive phase were enrolled using simple random sampling. Standardized instruments were applied like Sleep Quality Scale (SQS) to assess subjective sleep parameters, Beck Depression Inventory (BDI) to quantify depressive severity, and Columbia–Suicide Severity Rating Scale (C-SSRS) to evaluate suicidality. Statistical analysis was performed using SPSS version 20.0, employing Pearson’s and Spearman’s correlation coefficients, with significance set at p<0.05.
Results: Participants demonstrated moderate sleep impairment (mean SQS score = 4.9±1.2) and significant depressive symptoms. A strong positive correlation was observed between SQS and BDI scores (r = 0.846, p<0.001), indicating that poorer sleep quality was associated with greater depressive severity. Sleep quality also correlated moderately with suicidal ideation (r = 0.49, p = 0.01) and suicidal behavior (r = 0.54, p = 0.01), underscoring the independent contribution of sleep disturbance to suicidality.
Conclusion: Sleep dysfunction constitutes a pivotal element in the psychopathology of bipolar depression, strongly influencing both mood intensity and suicidal risk. Integrating systematic sleep evaluation and targeted interventions such as circadian rhythm regulation and behavioral sleep therapy into routine management may enhance clinical outcomes and mitigate suicidal vulnerability in bipolar depressive patients.
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