실천공학교육논문지 (Journal of Practical Engineering Education)

  • 제16권4호
  • /
  • Pages.577-585
  • /
  • 2024
  • /
  • 2288-405X(pISSN)
  • /
  • 2288-4068(eISSN)
한국실천공학교육학회 (Korean Institute for Pratical Engineering Education)
권호 표지
DOI QR코드

DOI QR Code

The Relationship Between GPS-Based Physical Activity Patterns and Depression

  • Kwang Ho Seok (School of AI Drone, Global Cyber University) ;
  • Sung Man Bae (Department of Psychology and Psychotherapy, Dankook University)
  • 투고 : 2024.08.02
  • 심사 : 2024.08.16
  • 발행 : 2024.08.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This study analyzed the relationship between GPS-based physical activity patterns and mental health using Kaggle Student Life data. Data were collected over a 10-week period from 48 students at Dartmouth College through Android smartphones and included GPS, dark, and phone lock data, and measures such as the Patient Health Questionnaire-9 (PHQ-9), Loneliness Scale, the Positive and Negative Affect Schedule (PANAS), and Perceived Stress Scale. Using latitude and longitude data obtained from GPS measurements, various physical activity indicators were calculated, including the total distance traveled, average distance traveled, average distance traveled in the morning, average distance traveled in the afternoon, average distance traveled in the evening, and average distance traveled in the middle of the night. Pearson's correlation analysis was performed to explore the relationship between GPS-based physical activity patterns and mental health. The study results indicated a significant negative correlation between the average distance traveled in the afternoon and PHQ-9 scores. Results indicated that the higher the afternoon activity, the lower the depressive symptoms. There was a positive correlation be-tween the PANAS-Pos score and the average distance traveled in the evening, indicating that positive emotions tended to increase as evening activities increased. This finding suggests a relationship between physical activity at specific times and mental health.

키워드

과제정보

Funding: This research was funded by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea grant number [NRF-2022S1A5A2A03050428]. Institutional Review Board Statement: The study was approved by the Institutional Review Board of Dankook University (IRB no. 2023-08-015).

참고문헌

  1. G. S. Yang and H. Y. Hong, "The effects of insecure attachment on depression in early adulthood: The mediating effects of mentalization and distress tolerance," Korea Journal of Counseling, vol. 23, no. 2, pp. 147-166, 2022.
  2. S. H. Kim and E. H. Lee, "The effect of internalized shame on depression in early adulthood: The mediation effect of emotional regulation," The Journal of Learner Centered Curriculum and Instruction (JLCCI), vol. 23, no. 14, pp. 15-26, 2023.
  3. S. M. Bae, "The association between adverse childhood and adulthood experiences, social isolation, loneliness, and depression among young adults in South Korea," International Journal of Environmental Research and Public Health, vol. 20, no. 19, 6900, 2023.
  4. X. Li, W. Guo, W. Tang, Q. Lv, Y. Zhang, H. Yu, Q. Wang, W. Deng, L. Zhao, X. Ma, Y. Meng, M. Li, H. Wang, T. Chen, Y. Liu, Z. Tang, X. Du, A. J. Greenshaw, and T. Li, "The interactions between childhood adversities and recent stress were associated with early-adulthood depression among Chinese undergraduate students," Depression and Anxiety, vol. 38, issue. 9, pp. 961-971, 2021.
  5. S. M. Vargas, C. Wang, M. Rubenson, N. Jafarzadeh, and S. J. Huey, "Depression, perceived burdensomeness, thwarted belongingness, and suicide risk trajectories among emerging adults during the early Covid-19 pandemic," Journal of Social and Clinical Psychology, vol. 42, no. 5, pp. 487-510, 2023.
  6. J. Shin and S. M. Bae, "A systematic review of location data for depression prediction," International Journal of Environmental Research and Public Health, vol. 20, issue 11, 5984, 2023.
  7. P. Ayranci, C. Bandera, N. Phan, R. Jin, D. Li, and D. Kenne, "Distinguishing the effect of time spent at home during cOVID-19 pandemic on the mental health of urban and suburban college students using cell phone geolocation," International Journal of Environmental Research and Public Health, vol. 19, issue 12, 7513, 2022.
  8. M. Boukhechba, A. R. Daros, K. Fua, P. I. Chow, B. A. Teachman, and L. E. Barnes, "DemonicSalmon: Monitoring mental health and social interactions of college students using smartphones," Smart Health, vol. 9, pp. 192-203, 2018.
  9. J. J. Chow, J. M. Thom, M. A. Wewege, R. E. Ward, and B. J. Parmenter, "Accuracy of step count measured by physical activity monitors: The effect of gait speed and anatomical placement site," Gait & Posture, vol. 57, pp. 199-203, 2017.
  10. J. C. Hong, H. C. Juan, and W. C. Hung, "The role of family intimacy in playing collaborative e-sports with a Switch de-vice to predict the experience of flow and anxiety during COVID-19 lockdown," Computers in Human Behavior, vol. 132, 107244, 2022.
  11. K. O. Asare, I. Moshe, Y. Terhorst, J. Vega, S. Hosio, H. Baumeister, L. P. Raback, and D. Ferreira, "Mood ratings and digital biomarkers from smartphone and wearable data differentiates and predicts depression status: A longitudinal data analysis," Pervasive and Mobile Computing, vol. 83, 101621, 2022.
  12. D. Ben-Zeev, E. A. Scherer, R. Wang, H. Xie, and A. T. Campbell, "Next-generation psychiatric assessment: Using smartphone sensors to monitor behavior and mental health," Psychiatric Rehabilitation Journal, vol. 38, no. 3, pp. 218-226, 2015.
  13. P. Laiou, D. A. Kaliukhovich, A. A. Folarin, Y. Ranjan, Z. Rashid, P. Conde, C. Stewart, S. Sun, Y. Zhang, F. Matcham, A. Ivan, G. Lavelle, S. Siddi, F. Lamers, B. W. Penninx, J. M. Haro, P. Annas, N. Cummins, S. Vairavan, N. V. Manyakov, V. A. Narayan, R. J. Dobson, M. Hotopf, and R. C., "The association between home stay and symptom severity in major depressive disorder: preliminary findings from a multicenter observational study using geolocation data from smartphones," JMIR mHealth and uHealth, vol. 10, no. 1, e28095, 2022.
  14. R. Wang, F. Chen, Z. Chen, T. Li, G. Harari, S. Tignor, X. Zhou, D. B. Zeev, and A. T. Campbell, "StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones," In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 3-14, 2014.
  15. K. L. Szuhany, M. Malgaroli, and G. A. Bonanno, "Physical activity may buffer against depression and promote resilience after major life stressors," Mental Health and Physical Activity, vol. 24, 100505, 2023.
  16. M. Hallgren, M. Kraepelien, N. Lindefors, Z. Zeebari, V. Kaldo, and Y. Forsell, "Physical exercise and internet-based cognitive-behavioural therapy in the treatment of depression: randomised controlled trial," The British Journal of Psychiatry, vol. 207, no. 3, pp. 227-234, 2015.
  17. Kaggle StudentLife. Available online: (https://www.kaggle.com/datasets/dartweichen/studentlife?datasetId=942862&sortBy=dateRun&tab=profile).
  18. K. Kroenke, R. L. Spitzer, and J. B. Williams, "The phq9 validity of a brief depression severity measure," Journal of General Internal Medicine, vol. 16, no. 9, pp. 606-613, 2001.
  19. D. W. Russell, "UCLA loneliness scale (version 3): Reliability, validity, and factor structure," Journal of Personality Assessment, vol. 66, issue 1, pp. 20-40, 1996.
  20. S. Cohen, T. Kamarck, and R. Mermelstein, "A global measure of perceived stress," Journal of Health and Social Behavior, vol. 24, no. 4, pp. 385-396, 1983.
  21. D. Watson, L. A. Clark, and A. Tellegen, "Development and validation of brief measures of positive and negative affect: the panas scales," Journal of Personality and Social Psychology, vol. 54, no. 6, pp. 1063-1070, 1988.