Emotional intelligence and biological perception: A new approach to mental health ideological and political education
Abstract
In recent years, the combination of emotional intelligence (EI) and biological perception has emerged as a significant strategy in mental health, notably in ideological and political education. EI, which involves understanding and managing emotions, fosters self-awareness, empathy, and interpersonal relationships. The purpose was to explore a novel approach integrating EI with biological perception to enhance mental health and ideological and political education. The dynamics of EI and its effects on mental health are examined by analyzing patterns in biological data and emotional reactions using a machine learning (ML) algorithm. The research presents a novel Intelligent Sailfish Optimized Driven Categorical Boosting (ISO-CatBoost) to predict mental health based on emotional outcomes and biological signals. It uses biological data, behavioral reactions, and EI to predict mental health outcomes. The data was preprocessed using data cleaning and normalization from the obtained data. Fast Fourier Transform (FFT) was used to extract the data collection. The results demonstrate that the ISO-CatBoost model effectively predicts mental health outcomes by performance metrics such as accuracy (88.8%), precision (87.5%), recall (98.5%), F1-score (93.2%), and specificity (85.7%). This method advances customized mental health education by providing ways for more effective emotional resilience training within ideological and political frameworks.
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