Comprehensive Health Evaluation Model of Art Psychotherapy Using Genetic Algorithm

Area of Science:

• Psychology
• Art Therapy
• Mental Health

Background:

• Art therapy is increasingly recognized for its potential in mental health treatment.
• Understanding the specific psychological impacts of art therapy on college students is crucial.
• Previous research may not have fully elucidated the measurable effects of painting art therapy.

Purpose of the Study:

• To investigate the efficacy of painting art therapy as a psychotherapy intervention for college students.
• To identify specific psychological factors influenced by art therapy using a feature selection algorithm.
• To assess the impact of art psychology courses on emotional expression and mental well-being.

Main Methods:

• A feature selection algorithm based on a genetic algorithm was employed.
• College students participated in painting art therapy sessions as an educational intervention.
• Psychological assessments, including EPQ (Eysenck Personality Questionnaire) and measures of depression, social anxiety, and sadness, were conducted.

Main Results:

• Significant increases in EPQ extraversion factors (P < 0.01) were observed.
• Significant reductions in social avoidance and social anxiety (P < 0.05) were noted.
• A significant increase in the total score of sadness (P < 0.01) was found, with no significant changes in other EPQ factors, total depression score, or depression index (P > 0.05).

Conclusions:

• Painting art therapy effectively facilitates self-expression and emotional release in college students.
• Artistic elements contribute positively to mental health treatment, particularly in enhancing extraversion and mitigating social anxiety.
• The study highlights the therapeutic potential of art in addressing specific psychological challenges among students.