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Samira Ali *1, Fatemeh Azadi2
1- Department of Psychology, Naser Khosrow Institute , Samiraali.1365061@gmail.com
2- Department of Psychology, Naser Khosrow Institute
2- Department of Psychology, Naser Khosrow Institute
Abstract: (76 Views)
Objective: Bipolar disorder is characterized by mood fluctuations between the poles of mania and depression. Identifying predictors of these fluctuations can contribute to improved diagnosis and treatment. The present study aimed to examine the role of behavioral brain systems (BAS/ BIS), chronotype, and sleep disturbance in predicting mood fluctuations during both manic and depressive phases in individuals with Bipolar I Disorder (male and female).
Method: The research design was applied in purpose and correlational in nature, involving systematic monitoring of participants over a three-month period. The study population consisted of all individuals diagnosed with Bipolar I Disorder at the Razi Psychiatric Educational and Treatment Center 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 (PHQ-9) for assessing depressive symptom severity, and the Altman Self-Rating Mania Scale (ASRM) for assessing mania/hypomania symptom y severity over the three-month period. Data were analyzed using SPSS software, and hierarchical regression analysis was employed to determine the variance explained by motivational and biological variables.
Result: The results indicated that predictive mechanisms function differently across the two phases of the disorder. In the manic phase, the Behavioral Activation System (BAS) was the strongest predictor (β=0.467, p<0.001), and in the third month, the model explained 35.8% of the variance (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, the role of biological variables (sleep) becomes more prominent than that of 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.
Method: The research design was applied in purpose and correlational in nature, involving systematic monitoring of participants over a three-month period. The study population consisted of all individuals diagnosed with Bipolar I Disorder at the Razi Psychiatric Educational and Treatment Center 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 (PHQ-9) for assessing depressive symptom severity, and the Altman Self-Rating Mania Scale (ASRM) for assessing mania/hypomania symptom y severity over the three-month period. Data were analyzed using SPSS software, and hierarchical regression analysis was employed to determine the variance explained by motivational and biological variables.
Result: The results indicated that predictive mechanisms function differently across the two phases of the disorder. In the manic phase, the Behavioral Activation System (BAS) was the strongest predictor (β=0.467, p<0.001), and in the third month, the model explained 35.8% of the variance (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, the role of biological variables (sleep) becomes more prominent than that of 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, Behavioral brain System (BAS/ BIS), Chronotype, Sleep disturbance, Mania, Depression.
Type of Study: Original Research Article |
Subject:
Psychiatry
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