September 10, 2025HealthcareOpen Access

The Relationship Between Smartphone and Game Addiction, Leisure Time Management, and the Enjoyment of Physical Activity: A Comparison of Regression Analysis and Machine Learning Models

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Authors

SNSevinç NAMLIErzurum Technical University BÇBekir ÇarBandırma Onyedi Eylül University AKAhmet KurtoğluBandırma Onyedi Eylül University

Discussion

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Implication

Findings revealed machine learning models better predict smartphone and gaming addiction in adolescents, highlighting the roles of leisure time management and physical activity enjoyment.

Key Points

Higher leisure time management scores are linked to lower smartphone addiction, indicating a potential intervention point.
The hybrid GBM + RF model achieved the highest prediction accuracy for smartphone addiction, showing MAE of 0.095.
Machine learning models outperformed classical regression methods in explaining complex relationships between addiction and related factors.
Gaming addiction was significantly related to leisure time management but not to the enjoyment of physical activity.

Cite This Study

NAMLI et al. (2025) studied this question.

synapsesocial.com/papers/68c2409bb210217d6479bd7f https://doi.org/10.3390/healthcare13151805

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Implication

Findings revealed machine learning models better predict smartphone and gaming addiction in adolescents, highlighting the roles of leisure time management and physical activity enjoyment.

The Relationship Between Smartphone and Game Addiction, Leisure Time Management, and the Enjoyment of Physical Activity: A Comparison of Regression Analysis and Machine Learning Models

Discussion

Member takes

Implication

Key Points

Cite This Study

The Relationship Between Smartphone and Game Addiction, Leisure Time Management, and the Enjoyment of Physical Activity: A Comparison of Regression Analysis and Machine Learning Models

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider