IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i15p7894-d601465.html
   My bibliography  Save this article

Socioeconomic Status, Mental Health, and Workplace Determinants among Working Adults in Hong Kong: A Latent Class Analysis

Author

Listed:
  • Alan C. Y. Tong

    (Department of Psychology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong
    Joint first authors.)

  • Emily W. S. Tsoi

    (Department of Psychology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong
    Joint first authors.)

  • Winnie W. S. Mak

    (Department of Psychology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong)

Abstract

This study provides insights on mental health correlates and work stress patterns in a representative sample of working adults in Hong Kong using an intersectional perspective. Using data from a cross-sectional, population-based telephone survey of 1007 working adults in Hong Kong, latent class analysis was conducted to identify socioeconomic classes within the sample. Three latent classes were identified, and they differed significantly in all the SES variables. Results suggested mental health to be the lowest in Class 1, the lowest income group. The three classes did not differ from their perceived level of job demand and control in work-related stress. Predictably, the highest income group perceived the lowest level of effort-reward imbalance. The lowest paid class was also reported perceiving the lowest level of relational justice. Different barriers to mental health services were also identified. Finally, cultural implications associated with work stress patterns, research, and practice implications are discussed. This study provides an empirical foundation for future studies to investigate patterns of job stress and mental health needs in a diverse population of working adults, with a particular focus on addressing the intersectional profiles of working adults and their needs in mental health services.

Suggested Citation

  • Alan C. Y. Tong & Emily W. S. Tsoi & Winnie W. S. Mak, 2021. "Socioeconomic Status, Mental Health, and Workplace Determinants among Working Adults in Hong Kong: A Latent Class Analysis," IJERPH, MDPI, vol. 18(15), pages 1-18, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:15:p:7894-:d:601465
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/15/7894/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/15/7894/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Teris Cheung & Paul S.F. Yip, 2015. "Depression, Anxiety and Symptoms of Stress among Hong Kong Nurses: A Cross-sectional Study," IJERPH, MDPI, vol. 12(9), pages 1-29, September.
    2. Kanami Tsuno & Norito Kawakami & Akizumi Tsutsumi & Akihito Shimazu & Akiomi Inoue & Yuko Odagiri & Toru Yoshikawa & Takashi Haratani & Teruichi Shimomitsu & Ichiro Kawachi, 2015. "Socioeconomic Determinants of Bullying in the Workplace: A National Representative Sample in Japan," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-15, March.
    3. Oakes, J. Michael & Rossi, Peter H., 2003. "The measurement of SES in health research: current practice and steps toward a new approach," Social Science & Medicine, Elsevier, vol. 56(4), pages 769-784, February.
    4. Rosenfield, Sarah, 2012. "Triple jeopardy? Mental health at the intersection of gender, race, and class," Social Science & Medicine, Elsevier, vol. 74(11), pages 1791-1801.
    5. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    6. Fernando R. Feijó & Débora D. Gräf & Neil Pearce & Anaclaudia G. Fassa, 2019. "Risk Factors for Workplace Bullying: A Systematic Review," IJERPH, MDPI, vol. 16(11), pages 1-25, May.
    7. Chiu, Catherine C H & Ting, Kwok-fai & Tso, Geoffrey K F & Cai, He, 1998. "A Comparison of Occupational Values between Capitalist Hong Kong and Socialist Guangzhou," Economic Development and Cultural Change, University of Chicago Press, vol. 46(4), pages 749-770, July.
    8. Stanley Sclove, 1987. "Application of model-selection criteria to some problems in multivariate analysis," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 333-343, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daniel McNeish & Jeffrey R. Harring, 2017. "The Effect of Model Misspecification on Growth Mixture Model Class Enumeration," Journal of Classification, Springer;The Classification Society, vol. 34(2), pages 223-248, July.
    2. Po-Hsien Huang, 2017. "Asymptotics of AIC, BIC, and RMSEA for Model Selection in Structural Equation Modeling," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 407-426, June.
    3. Morgan, Grant B. & Hodge, Kari J. & Baggett, Aaron R., 2016. "Latent profile analysis with nonnormal mixtures: A Monte Carlo examination of model selection using fit indices," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 146-161.
    4. Qi Chen & Wen Luo & Gregory J. Palardy & Ryan Glaman & Amber McEnturff, 2017. "The Efficacy of Common Fit Indices for Enumerating Classes in Growth Mixture Models When Nested Data Structure Is Ignored," SAGE Open, , vol. 7(1), pages 21582440177, March.
    5. Roy Levy & Gregory R. Hancock, 2011. "An Extended Model Comparison Framework for Covariance and Mean Structure Models, Accommodating Multiple Groups and Latent Mixtures," Sociological Methods & Research, , vol. 40(2), pages 256-278, May.
    6. Riser, Quentin H. & Rouse, Heather L. & Dorius, Cassandra J., 2023. "Association between early income variation around poverty thresholds, income trajectories, and birth, child, and family characteristics," Children and Youth Services Review, Elsevier, vol. 145(C).
    7. Liam Mahedy & Flora Todaro-Luck & Brendan Bunting & Samuel Murphy & Karen Kirby, 2013. "Risk factors for psychological distress in Northern Ireland," International Journal of Social Psychiatry, , vol. 59(7), pages 646-654, November.
    8. Fabrice Gilles & Sabina Issehnane & Florent Sari, 2022. "Using short-term jobs as a way to find a regular job. What kind of role for local context?," TEPP Working Paper 2022-07, TEPP.
    9. Eunjung Ko & Yun-Jung Choi, 2020. "Debriefing Model for Psychological Safety in Nursing Simulations: A Qualitative Study," IJERPH, MDPI, vol. 17(8), pages 1-12, April.
    10. repec:hal:spmain:info:hdl:2441/dambferfb7dfprc9m052g20qh is not listed on IDEAS
    11. Paulo M. D. C. Parente & Richard J. Smith, 2021. "Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
    12. Cornelia Lawson, 2013. "Academic Inventions Outside the University: Investigating Patent Ownership in the UK," Industry and Innovation, Taylor & Francis Journals, vol. 20(5), pages 385-398, July.
    13. Vipin Arora & Shuping Shi, 2016. "Nonlinearities and tests of asset price bubbles," Empirical Economics, Springer, vol. 50(4), pages 1421-1433, June.
    14. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    15. Da Fonseca José & Grasselli Martino & Ielpo Florian, 2014. "Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 1-37, May.
    16. Gülüm Özer & İdil Işık & Jordi Escartín, 2024. "Is There Somebody Looking out for Me? A Qualitative Analysis of Bullying Experiences of Individuals Diagnosed with Bipolar Disorder," IJERPH, MDPI, vol. 21(2), pages 1-22, January.
    17. Hansen, Lars Peter & Heaton, John & Luttmer, Erzo G J, 1995. "Econometric Evaluation of Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 237-274.
    18. Das, Marcel & van Soest, Arthur, 1999. "A panel data model for subjective information on household income growth," Journal of Economic Behavior & Organization, Elsevier, vol. 40(4), pages 409-426, December.
    19. Gillespie, Colin S., 2015. "Fitting Heavy Tailed Distributions: The poweRlaw Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i02).
    20. Luis Garicano & Thomas N. Hubbard, 2016. "The Returns to Knowledge Hierarchies," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 32(4), pages 653-684.
    21. Jiwon Lee & Midam An & Yongku Kim & Jung-In Seo, 2021. "Optimal Allocation for Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(18), pages 1-10, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:15:p:7894-:d:601465. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.