IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i11p4079-d368564.html
   My bibliography  Save this article

A Latent Profile Analysis of Anxiety among Junior High School Students in Less Developed Rural Regions of China

Author

Listed:
  • Xiaotong Wen

    (School of Public Health, Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, China
    These authors contributed equally to this study.)

  • Yixiang Lin

    (School of Public Health, Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, China
    These authors contributed equally to this study.)

  • Yuchen Liu

    (Biology Department, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA)

  • Katie Starcevich

    (School of Community Science, University of Nevada, Reno, NV 89557, USA)

  • Fang Yuan

    (Office of Public Health Studies, the University of Hawaii at Mānoa, Honolulu, HI 96822, USA)

  • Xiuzhu Wang

    (Administration Office of Floating Population, Jiangxi Provincial Health Committee, Nanchang 330006, China)

  • Xiaoxu Xie

    (School of Public Health, Fujian Medical University, Fuzhou 350000, China)

  • Zhaokang Yuan

    (School of Public Health, Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, China)

Abstract

The purpose of this study is to understand the potential types of anxiety among middle school students by analyzing the current situation of middle school students’ anxiety and its influencing factor. This study used a multistage stratified cluster random sampling to investigate students in grades 9 to 12. Mplus 7.4 was used for latent profile analysis. A total of 900 junior high school students were investigated. The junior high school students were divided into three subgroups by latent profile analysis. A total of 223 junior high school students experienced severe anxiety, accounting for 24.78%. Multivariate logistic regression analysis revealed that males are more likely to develop moderate and severe anxiety. The development of severe anxiety (OR = 0.562, p < 0.05) is less likely for students in schools with adequate mental health support. Students who were confident with their academic performances were less likely to develop moderate anxiety (OR = 0.377, p < 0.05). Students with extreme academic pressure are more likely to develop moderate anxiety (OR = 6.523, p < 0.05) and severe anxiety (OR = 11.579, p < 0.05). It is recommended that mental health counseling be set up in schools and to provide professional counselors to prevent serious anxiety for students. This paper also demonstrates a need to reduce students’ academic pressure.

Suggested Citation

  • Xiaotong Wen & Yixiang Lin & Yuchen Liu & Katie Starcevich & Fang Yuan & Xiuzhu Wang & Xiaoxu Xie & Zhaokang Yuan, 2020. "A Latent Profile Analysis of Anxiety among Junior High School Students in Less Developed Rural Regions of China," IJERPH, MDPI, vol. 17(11), pages 1-14, June.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:11:p:4079-:d:368564
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/11/4079/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/11/4079/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gilles Celeux & Gilda Soromenho, 1996. "An entropy criterion for assessing the number of clusters in a mixture model," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 195-212, September.
    2. Jutta Lindert & Ondine Ehrenstein & Rachel Grashow & Gilad Gal & Elmar Braehler & Marc Weisskopf, 2014. "Sexual and physical abuse in childhood is associated with depression and anxiety over the life course: systematic review and meta-analysis," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 59(2), pages 359-372, April.
    3. Hongyu Guan & Huan Wang & Kang Du & Jin Zhao & Matthew Boswell & Yaojiang Shi & Yiwei Qian, 2018. "The Effect of Providing Free Eyeglasses on Children’s Mental Health Outcomes in China: A Cluster-Randomized Controlled Trial," IJERPH, MDPI, vol. 15(12), pages 1-15, December.
    4. Teris Cheung & Paul S.F. Yip, 2016. "Lifestyle and Depression among Hong Kong Nurses," IJERPH, MDPI, vol. 13(1), pages 1-12, January.
    5. Supa Pengpid & Karl Peltzer, 2019. "High Sedentary Behaviour and Low Physical Activity are Associated with Anxiety and Depression in Myanmar and Vietnam," IJERPH, MDPI, vol. 16(7), pages 1-8, April.
    6. 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. Mengya Xia & Caitlin M. Hudac, 2023. "Social Connection Constellations and Individual Well-Being Typologies: Using the Loglinear Modeling Approach with Latent Variables," Journal of Happiness Studies, Springer, vol. 24(6), pages 1991-2012, August.
    2. Laura Dal Corso & Alessandro De Carlo & Francesca Carluccio & Daiana Colledani & Alessandra Falco, 2020. "Employee burnout and positive dimensions of well-being: A latent workplace spirituality profile analysis," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-17, November.
    3. Meng Li & Sijia Xiang & Weixin Yao, 2016. "Robust estimation of the number of components for mixtures of linear regression models," Computational Statistics, Springer, vol. 31(4), pages 1539-1555, December.
    4. Nicolas Depraetere & Martina Vandebroek, 2014. "Order selection in finite mixtures of linear regressions," Statistical Papers, Springer, vol. 55(3), pages 871-911, August.
    5. Michael T. Baglivio & Kevin T. Wolff, 2021. "Adverse Childhood Experiences Distinguish Violent Juvenile Sexual Offenders’ Victim Typologies," IJERPH, MDPI, vol. 18(21), pages 1-14, October.
    6. Marianna Virtanen & Jussi Vahtera & Jenny Head & Rosemary Dray-Spira & Annaleena Okuloff & Adam G Tabak & Marcel Goldberg & Jenni Ervasti & Markus Jokela & Archana Singh-Manoux & Jaana Pentti & Marie , 2015. "Work Disability among Employees with Diabetes: Latent Class Analysis of Risk Factors in Three Prospective Cohort Studies," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    7. Danks, Nicholas P. & Sharma, Pratyush N. & Sarstedt, Marko, 2020. "Model selection uncertainty and multimodel inference in partial least squares structural equation modeling (PLS-SEM)," Journal of Business Research, Elsevier, vol. 113(C), pages 13-24.
    8. 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.
    9. Ana Zdravkovic & Abby L. Goldstein, 2023. "Optimists and Realists: A Latent Class Analysis of Students Graduating from High School during COVID-19 and Impacts on Affect and Well-Being," IJERPH, MDPI, vol. 20(3), pages 1-13, January.
    10. Julian Aichholzer & Sylvia Kritzinger & Carolina Plescia, 2021. "National identity profiles and support for the European Union," European Union Politics, , vol. 22(2), pages 293-315, June.
    11. 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.
    12. Palma, Marco A. & Ness, Meghan L. & Anderson, David P., 2015. "Buying More than Taste? A Latent Class Analysis of Health and Prestige Determinants of Healthy Food," 2015 Conference (59th), February 10-13, 2015, Rotorua, New Zealand 202566, Australian Agricultural and Resource Economics Society.
    13. Adrian Bruhin & Ernst Fehr & Daniel Schunk, 2019. "The many Faces of Human Sociality: Uncovering the Distribution and Stability of Social Preferences," Journal of the European Economic Association, European Economic Association, vol. 17(4), pages 1025-1069.
    14. Alan Crane & Kevin Crotty, 2020. "How Skilled Are Security Analysts?," Journal of Finance, American Finance Association, vol. 75(3), pages 1629-1675, June.
    15. Nicoleta Serban & Huijing Jiang, 2012. "Multilevel Functional Clustering Analysis," Biometrics, The International Biometric Society, vol. 68(3), pages 805-814, September.
    16. Jacky C. K. Ng & Joanne Y. H. Chong & Hilary K. Y. Ng, 2023. "The way I see the world, the way I envy others: a person-centered investigation of worldviews and the malicious and benign forms of envy among adolescents and adults," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    17. Gillian C. Williams & Karen A. Patte & Mark A. Ferro & Scott T. Leatherdale, 2021. "Associations between Longitudinal Patterns of Substance Use and Anxiety and Depression Symptoms among a Sample of Canadian Secondary School Students," IJERPH, MDPI, vol. 18(19), pages 1-14, October.
    18. Mélissa Lemoine & Gerhard Gmel & Simon Foster & Simon Marmet & Joseph Studer, 2020. "Multiple trajectories of alcohol use and the development of alcohol use disorder: Do Swiss men mature-out of problematic alcohol use during emerging adulthood?," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    19. Sarstedt, Marko & Salcher, André, 2007. "Modellselektion in Finite Mixture PLS-Modellen," Discussion Papers in Business Administration 1394, University of Munich, Munich School of Management.
    20. Lebret, Rémi & Iovleff, Serge & Langrognet, Florent & Biernacki, Christophe & Celeux, Gilles & Govaert, Gérard, 2015. "Rmixmod: The R Package of the Model-Based Unsupervised, Supervised, and Semi-Supervised Classification Mixmod Library," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i06).

    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:17:y:2020:i:11:p:4079-:d:368564. 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.