A Survey on Use of Machine Learning for Employee Wellness

Authors

  • Chetan Thote  Department of Computer Engineering, Zeal College of Engineering & Research, Pune, Maharashtra, India
  • Prof. Jareena Shaikh  Department of Computer Engineering, Zeal College of Engineering & Research, Pune, Maharashtra, India

Keywords:

Machine Learning,Mental health,Survey.

Abstract

The Pandemic times that we are living in has forced many changes into the lifestyle and preferences of our lives. Mental health is the most talked about topic in recent times with cases of employee burnout happening frequently. And because of such burnouts at workplace Employee churn rate is also high in such cases. In this paper, survey of the work done in the field of machine learning to predict stress, anxiety and depression is presented. The survey paper is providing analysis and extensive review of the work presented around the topic by more than 10 papers in last decade. This survey paper discusses different approaches taken by various researchers around the topic, it also talks about machine learning algorithms used by these researchers to create machine learning model.

References

  1. https://www.who.int/teams/mental-health-and- substance-use/promotion-prevention/mental-health- in-the-workplace
  2. Neha Prerna Tiggaa, Shruti Garga, Anu Priya, ”Predicting Anxiety, Depression and Stress in Modern Life using Machine Learning Algorithms ” ICCIDS 2019
  3. Arkaprabha Sau, Ishita Bhakta (2018) "Screening of anxiety and depression among seafarers using machine learning technology" Informatics in Medicine Unlocked, Volume 16, 2019, Pages 100228.
  4. A. Sethy, Dr. Ajit Kumar Raut , ”Employee attrition rate prediction using machine learning approach”, Turkish Journal of Physiotherapy and Rehabilitation; 32(3)
  5. Isaac Teoh Yi Zhe & Pantea Keikhosrokiani. “Knowledge workers mental workload prediction using optimised ELANFIS”, Applied Intelligence volume 51, pages2406–2430 (2021)
  6. Tyshchenko, Y. (2018)"Depression and anxiety detection from blog posts data."Nature Precis. Sci., Inst. Comput. Sci., Univ. Tartu, Tartu,Estonia.
  7. Shear MK, Vander Bilt J, Rucci P, Endicott J, Lydiard B, Otto MW, Pollack MH, Chandler L, Williams J, Ali A, Frank DM. Reliability and validity of a structured interview guide for the Hamilton Anxiety Rating Scale (SIGH-A). Depress Anxiety 2001 Jan 1;13(4):166–78.
  8. Williams JB. A structured interview guide for the Hamilton Depression Rating Scale. Arch Gen Psychiatr 1988 Aug 1;45(8):742–7.
  9. Pankaj Ajit, Rohit Punnoose , ” Prediction of Employee Turnover in Organizations using Machine Learning Algorithms ”, International Journal of Advanced Research in Artificial Intelligence, 2016
  10. Oei, T. P., Sawang, S., Goh, Y. W., Mukhtar, F. (2013) “Using the depression anxiety stress scale 21 (DASS-21) across cultures.” International Journal of Psychology 48 (6): 1018-1029.
  11. S. Jahan, “Human Resources Information System : A Theoretical Perspective”, Journal of Human Resource and Sustainability Studies, 2014.
  12. E. K. Kalokerinos, J. D. Henry and C. von Hippel, “Stereotype threat among older employees: Relationship with job attitudes and turnover intentions”, Psychology and aging, 2013.
  13. Li, L., Zhang, X. (2010) "Study of data mining algorithm based on decision tree." International Conference On Computer Design and Applications IEEE 1: V1-155.
  14. Paul, A., Mukherjee, D. P., Das, P., Gangopadhyay, A., Chintha, A. R., Kundu, S. (2018) "Improved random forest for classification."IEEE Transactions on Image Processing
  15. Marjorie Laura Kane-Sellers , ”To explore various personal, as well as work variables impacting employee voluntary turnover ” 2009
  16. S. J. Delany and P. Cunningham, “k-Nearest neighbour classifiers”, Multiple Classifier Systems, 1- 17, 2007.
  17. A. Liaw and M. Wiener, “Classification and regression by randomForest”, R news, 2002.
  18. L. Breiman, Random forests. Machine Learning, 2001.
  19. V. Vapnik and C. Cortes, Support-vector networks. Machine learning, 1995.

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Published

2022-05-30

Issue

Section

Research Articles

How to Cite

[1]
Chetan Thote, Prof. Jareena Shaikh "A Survey on Use of Machine Learning for Employee Wellness" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 9, Issue 3, pp.589-593, May-June-2022.