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

**Authors:** Asamaporn Treearpornwong, Thiyaporn Kantathanawat, Mai Charoentham, Paitoon Pimdee, Aukkapong Sukkamart

PMC · DOI: 10.3390/ejihpe15040061 · European Journal of Investigation in Health, Psychology and Education · 2025-04-14

## TL;DR

This study uses data mining to assess psychological well-being in Thai secondary students, creating a culturally adapted questionnaire that shows strong accuracy.

## Contribution

The study introduces a new, culturally adapted psychological well-being questionnaire validated through data mining techniques in a Thai context.

## Key findings

- Personal growth was found to be the most predictive factor for psychological well-being in Thai students.
- The new PWB questionnaire achieved high accuracy (90.18%) and strong recall (90.90%) using a test set method.
- Data mining effectively identified key factors influencing adolescent psychological well-being in Bangkok.

## Abstract

This study examines the psychological well-being (PWB) of lower secondary school students in Bangkok’s Secondary Educational Service Area Offices (SESAO) 1 and 2, using data mining techniques to analyze key influencing factors and develop a culturally adapted PWB questionnaire. The research framework is based on six components: autonomy, environmental mastery, personal growth, positive relationships, life purpose, and self-acceptance. Data were collected from 2543 students in the 2023 academic year and analyzed using the Waikato Environment for Knowledge Analysis (WEKA) program and the JRip rule-based classification model. Results indicate that personal growth is the most predictive in the classification performance of PWB, followed by positive relationships and life purpose. A newly developed PWB questionnaire was tested for reliability, with the Supplied Test Set (80:20) method yielding strong performance metrics, including accuracy (90.18%), precision (69.00%), recall (90.90%), and F-measure (78.40%). This study demonstrates data mining’s effectiveness in identifying factors influencing adolescent PWB within the Thai context. The findings provide educators and policymakers with insights for fostering student well-being and contribute to research by offering a validated, culturally relevant assessment tool.

## Full-text entities

- **Diseases:** death (MESH:D003643), autism (MESH:D001321), depression (MESH:D003866), mental (MESH:D008607), mental health problems (MESH:D000076082), Health (OMIM:603663), COVID-19 (MESH:D000086382), anxiety (MESH:D001007), injury to (MESH:D014947), mental illness (MESH:D001523)
- **Species:** Homo sapiens (human, species) [taxon 9606]

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## Figures

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## References

74 references — full list in the complete paper: https://tomesphere.com/paper/PMC12025601/full.md

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Source: https://tomesphere.com/paper/PMC12025601