Volume 14, Issue 4 (Autumn 2026)
Pract Clin Psychol 2026, 14(4): 377-386 |
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Ali S, Azadi F. Assessing the Contribution of Biological (Chronotype and Sleep) and Motivational Factors to Bipolar Disorder Symptom Severity. Pract Clin Psychol 2026; 14 (4) :377-386
URL: http://jpcp.uswr.ac.ir/article-1-1138-en.html
URL: http://jpcp.uswr.ac.ir/article-1-1138-en.html
1- Department of Psychology, Naser Khosrow Institute of Higher Education, Saveh, Iran. , samiraali.135061@gmail.com
2- Department of Psychology, Naser Khosrow Institute of Higher Education, Saveh, Iran.
2- Department of Psychology, Naser Khosrow Institute of Higher Education, Saveh, Iran.
Abstract: (487 Views)
Objective: Bipolar disorder (BD) is characterized by mood fluctuations between the poles of mania and depression. Identifying predictors of these fluctuations can improve diagnosis and treatment. The present study aimed to examine the role of behavioral brain systems (behavioral activation system [BAS]/ behavioral inhibition system [BIS]), chronotype, and sleep disturbance in predicting mood fluctuations during both manic and depressive phases in individuals with bipolar I disorder (male and female).
Methods: The study used a purposive, correlational design and involved systematic monitoring of participants over 3 months. The study population consisted of all individuals diagnosed with bipolar I disorder at the Razi Psychiatric Educational and Treatment Center, Tehran City, Iran, in 2025. A convenience sample of 150 participants was selected (commencing the study with patients hospitalized in the acute manic phase). Data collection tools included the Horne-Östberg morningness-eveningness questionnaire (MEQ; 1976), the Carver and White BIS/BAS scales (1994) as baseline measures, the patient health questionnaire for assessing depressive symptom severity, and the Altman self-rating mania scale (ASRM) for assessing mania/hypomania symptom severity over 3 months. Data were analyzed using SPSS software, and hierarchical regression analysis was employed to determine the variance explained by motivational and biological variables.
Results: The results indicated that predictive mechanisms function differently across the two phases of the disorder. In the manic phase, BAS was the strongest predictor (β=0.467, P<0.001), and the model explained 35.8% of the variance in the third month (R2=0.358). Conversely, in the depressive phase, BIS variables (β=0.328, P<0.001) and sleep disturbance (β=0.377, P<0.001) played a key role in prediction; notably, in the first month, the inclusion of sleep quality led to a significant change in the coefficient of determination (ΔR2=0.089, P<0.001).
Conclusion: The findings suggest that in the depressive phase, biological variables (sleep) play a more prominent role than motivational variables. The results demonstrated that the pathophysiology of mania (BAS-dependent) and depression (BIS- and circadian rhythm-dependent) follows distinct pathways. These results emphasize the necessity of personalizing therapeutic interventions based on the phase of the disorder, prioritizing reward system management in mania and biological rhythm regulation in depression.
Methods: The study used a purposive, correlational design and involved systematic monitoring of participants over 3 months. The study population consisted of all individuals diagnosed with bipolar I disorder at the Razi Psychiatric Educational and Treatment Center, Tehran City, Iran, in 2025. A convenience sample of 150 participants was selected (commencing the study with patients hospitalized in the acute manic phase). Data collection tools included the Horne-Östberg morningness-eveningness questionnaire (MEQ; 1976), the Carver and White BIS/BAS scales (1994) as baseline measures, the patient health questionnaire for assessing depressive symptom severity, and the Altman self-rating mania scale (ASRM) for assessing mania/hypomania symptom severity over 3 months. Data were analyzed using SPSS software, and hierarchical regression analysis was employed to determine the variance explained by motivational and biological variables.
Results: The results indicated that predictive mechanisms function differently across the two phases of the disorder. In the manic phase, BAS was the strongest predictor (β=0.467, P<0.001), and the model explained 35.8% of the variance in the third month (R2=0.358). Conversely, in the depressive phase, BIS variables (β=0.328, P<0.001) and sleep disturbance (β=0.377, P<0.001) played a key role in prediction; notably, in the first month, the inclusion of sleep quality led to a significant change in the coefficient of determination (ΔR2=0.089, P<0.001).
Conclusion: The findings suggest that in the depressive phase, biological variables (sleep) play a more prominent role than motivational variables. The results demonstrated that the pathophysiology of mania (BAS-dependent) and depression (BIS- and circadian rhythm-dependent) follows distinct pathways. These results emphasize the necessity of personalizing therapeutic interventions based on the phase of the disorder, prioritizing reward system management in mania and biological rhythm regulation in depression.
Keywords: Bipolar disorder (BD), Behavioral brain system, Behavioral activation system (BAS), Behavioral inhibition system (BIS), Chronotype, Sleep disturbance, Mania, Depression
Type of Study: Original Research Article |
Subject:
Psychiatry
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