Enhancing Psychological Well-Being Assessment Through Data Mining: A Case Study from Thailand

Area of Science:

• Educational Psychology
• Data Mining Applications
• Adolescent Mental Health

Background:

• Psychological well-being (PWB) is crucial for adolescent development.
• Existing PWB assessments may lack cultural relevance in diverse educational settings.
• Understanding factors influencing PWB in lower secondary students is essential for targeted interventions.

Purpose of the Study:

• To examine psychological well-being (PWB) in lower secondary students in Bangkok.
• To identify key factors influencing PWB using data mining techniques.
• To develop and validate a culturally adapted PWB questionnaire for the Thai context.

Main Methods:

• Utilized data mining techniques, specifically the JRip rule-based classification model within the Waikato Environment for Knowledge Analysis (WEKA) program.
• Collected data from 2543 lower secondary students in Bangkok's SESAO 1 and 2 during the 2023 academic year.
• Assessed PWB based on six components: autonomy, environmental mastery, personal growth, positive relationships, life purpose, and self-acceptance.

Main Results:

• Personal growth emerged as the most significant predictor of PWB classification performance.
• Positive relationships and life purpose were also identified as key influencing factors.
• The newly developed PWB questionnaire demonstrated high reliability and performance metrics (Accuracy: 90.18%, Precision: 69.00%, Recall: 90.90%, F-measure: 78.40%) using an 80:20 split.

Conclusions:

• Data mining effectively identifies critical factors impacting adolescent PWB in the Thai context.
• The validated, culturally relevant PWB questionnaire provides a valuable assessment tool for educators and researchers.
• Findings offer actionable insights for policymakers and educators to enhance student psychological well-being.