IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i14p7394-d592143.html
   My bibliography  Save this article

Analysis of Parenting Attitude Types and Influencing Factors of Korean Parents by Using Latent Transition Analysis

Author

Listed:
  • Hanna Lee

    (Department of Nursing, Gangneung-Wonju National University, Wonju-si 26403, Korea)

  • Jeong-Won Han

    (College of Nursing Science, Kyung Hee University, Seoul 02447, Korea)

Abstract

This study aimed to classify the latent class of parenting attitude for parents with preschool children and school-age children, identify the pattern of transition in the type of parenting attitude over time, and determine the influencing factors associated with the transition. A total of 1462 households were the subjects of this longitudinal study that used latent profile analysis, latent transition analysis, and logistic regression analysis. The parenting attitude in the preschool year was classified into a model of three latent classes of ‘parent uninvolved’, ‘maternal authoritative and paternal authoritarian’, and ‘maternal authoritarian and paternal authoritative’, and the parenting attitude in the school year was classified into a model of four latent classes of ‘parent weak uninvolved’, ‘parent strong uninvolved’, parent authoritative’, and ‘maternal authoritarian and paternal authoritative.’ All latent class subjects with preschool children showed an attitude transition to maternal authoritarian and paternal authoritative when their children were in school years. It was confirmed that a mother’s depression and father’s parenting stress were the most influential factors in the parenting attitude transition. This study lay in identifying the patterns of parenting attitude and the transition in attitude according to the developmental stage of children.

Suggested Citation

  • Hanna Lee & Jeong-Won Han, 2021. "Analysis of Parenting Attitude Types and Influencing Factors of Korean Parents by Using Latent Transition Analysis," IJERPH, MDPI, vol. 18(14), pages 1-13, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7394-:d:592143
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/14/7394/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/14/7394/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    2. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Geniş, Çiğdem & Ayaz-Alkaya, Sultan, 2023. "Digital game addiction, social anxiety, and parental attitudes in adolescents: A cross-sectional study," Children and Youth Services Review, Elsevier, vol. 149(C).

    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. 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.
    2. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    3. Schreier, Alayna & Stenersen, Madeline R. & Strambler, Michael J. & Marshall, Tim & Bracey, Jeana & Kaufman, Joy S., 2023. "Needs of caregivers of youth enrolled in a statewide system of care: A latent class analysis," Children and Youth Services Review, Elsevier, vol. 147(C).
    4. Isabelle Archambault & Véronique Dupéré, 2017. "Joint trajectories of behavioral, affective, and cognitive engagement in elementary school," The Journal of Educational Research, Taylor & Francis Journals, vol. 110(2), pages 188-198, March.
    5. T. Paul de Cock & Mark Shevlin, 2014. "Parental Bonding," SAGE Open, , vol. 4(3), pages 21582440145, August.
    6. Yi-Jhen Wu & Yi-Hsin Chen & Sarah M. Kiefer & Claus H. Carstensen, 2021. "Learning Strategies as Moderators Between Motivation and Mathematics Performance in East Asian Students: Latent Class Analysis," SAGE Open, , vol. 11(4), pages 21582440211, November.
    7. William Magee & Sébastien St-Arnaud, 2012. "Models of the Joint Structure of Domain-Related and Global Distress: Implications for the Reconciliation of Quality of Life and Mental Health Perspectives," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 105(1), pages 161-185, January.
    8. repec:jss:jstsof:06:i02 is not listed on IDEAS
    9. Moira Mckniff & Stephanie M. Simone & Tania Giovannetti, 2023. "Age, Loneliness, and Social Media Use in Adults during COVID-19: A Latent Profile Analysis," IJERPH, MDPI, vol. 20(11), pages 1-12, May.
    10. Yang, Chih-Chien, 2006. "Evaluating latent class analysis models in qualitative phenotype identification," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1090-1104, February.
    11. Thorhildur Halldorsdottir & Maria G Fraire & Deborah A. G. Drabick & Thomas H. Ollendick, 2023. "Co-Occurring Conduct Problems and Anxiety: Implications for the Functioning and Treatment of Youth with Oppositional Defiant Disorder," IJERPH, MDPI, vol. 20(4), pages 1-12, February.
    12. Sarah Butter & Jamie Murphy & Mark Shevlin & James Houston, 2017. "Social isolation and psychosis-like experiences: a UK general population analysis," Psychosis, Taylor & Francis Journals, vol. 9(4), pages 291-300, October.
    13. Jennifer M. Boldero & Richard C. Bell & Susan M. Moore, 2010. "Do gambling activity patterns predict gambling problems? A latent class analysis of gambling forms among Australian youth," International Gambling Studies, Taylor & Francis Journals, vol. 10(2), pages 151-163, August.
    14. Yongsung Lee & Giovanni Circella & Patricia L. Mokhtarian & Subhrajit Guhathakurta, 2020. "Are millennials more multimodal? A latent-class cluster analysis with attitudes and preferences among millennial and Generation X commuters in California," Transportation, Springer, vol. 47(5), pages 2505-2528, October.
    15. Caili Liu & Yong Wei & Yu Ling & E. Scott Huebner & Yifang Zeng & Qin Yang, 2020. "Identifying Trajectories of Chinese High School Students’ Depressive Symptoms: an Application of Latent Growth Mixture Modeling," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 15(3), pages 775-789, July.
    16. Dayton, C. Mitchell, 2001. "SUBSET: Best Subsets using Information Criteria," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 6(i02).
    17. Seamus Fleming & Mark Shevlin & Jamie Murphy & Stephen Joseph, 2014. "Psychosis within dimensional and categorical models of mental illness," Psychosis, Taylor & Francis Journals, vol. 6(1), pages 4-15, January.
    18. D. M. Hutchinson & J. A. Macdonald & W. T. Hallam & R. K. Leung & J. W. Toumbourou & R. McGee & G. Tooley & S. A. Hemphill & H. Skouteris & C. A. Olsson, 2016. "Care Orientation in the Teens as a Predictor of Young Adult Psychosocial Adjustment," Journal of Happiness Studies, Springer, vol. 17(5), pages 2051-2076, October.
    19. Thao Thi Phuong Nguyen & Ha Ngoc Do & Thao Bich Thi Vu & Khanh Long Vu & Hiep Duy Nguyen & Dung Tuan Nguyen & Hoang Minh Do & Nga Thi Thu Nguyen & Ly Thi Bac La & Linh Phuong Doan & Tham Thi Nguyen & , 2023. "Association of Individual and Neighborhood Characteristics to Problematic Internet Use among Youths and Adolescents: Evidence from Vietnam," IJERPH, MDPI, vol. 20(3), pages 1-14, January.
    20. Ssu-Kuang Chen & Sunny Lin, 2014. "The Latent Profiles of Life Domain Importance and Satisfaction in a Quality of Life Scale," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 116(2), pages 429-445, April.
    21. 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.

    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:14:p:7394-:d:592143. 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.