Classifying mental disorders through clinicians' subjective approach based on three-way decisions.

Area of Science:

• Psychiatry and Psychology
• Computational Linguistics
• Decision Theory

Background:

• Current psychiatric diagnostic manuals face limitations in accurately diagnosing complex cases and individuals from minority cultures due to culture-bound data.
• Atypical symptom presentation in minority patients can be missed by standard diagnostic approaches, leading to potential misdiagnosis.

Purpose of the Study:

• To propose a unified, complementary diagnostic model for mental disorders that incorporates clinician subjectivity and data-driven analysis.
• To enhance the accuracy and cultural sensitivity of psychiatric diagnoses.

Main Methods:

• Development of a unified model based on the three-way decisions (3WD) framework, incorporating a clinician's subjective approach (CSA).
• The model integrates qualitative analysis, quantitative analysis, and evaluation-based analysis of patient symptoms.
• A comparative classification of diseases into three categories with varying importance levels using a three-way evaluation-based model.

Main Results:

• The model generates a classification list and numerical weights reflecting malady severity based on clinician assumptions.
• It provides a three-way classification of diseases, aiding in comprehension and communication of diagnostic results.
• The proposed method allows for the integration of patient behavioral symptoms with existing manual-based diagnostic processes.

Conclusions:

• The proposed model offers a complementary diagnostic instrument to improve the accuracy of mental disorder diagnosis.
• It enables clinicians to better account for individual patient data and subjective clinical judgment.
• This approach aims to reduce misdiagnosis, particularly for complex cases and culturally diverse patient populations.