IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i19p12767-d934471.html
   My bibliography  Save this article

Factors Related to Perceived Stigma in Parents of Children and Adolescents in Outpatient Mental Healthcare

Author

Listed:
  • Halewijn M. Drent

    (Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of Groningen, 9723 HE Groningen, The Netherlands
    Accare Child Study Center, 9723 HE Groningen, The Netherlands)

  • Barbara van den Hoofdakker

    (Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of Groningen, 9723 HE Groningen, The Netherlands
    Accare Child Study Center, 9723 HE Groningen, The Netherlands)

  • Jan K. Buitelaar

    (Department of Cognitive Neuroscience, Radboud University Medical Center, Donders Institute for Brain Cognition and Behaviour, 6525 AJ Nijmegen, The Netherlands)

  • Pieter J. Hoekstra

    (Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of Groningen, 9723 HE Groningen, The Netherlands
    Accare Child Study Center, 9723 HE Groningen, The Netherlands)

  • Andrea Dietrich

    (Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of Groningen, 9723 HE Groningen, The Netherlands
    Accare Child Study Center, 9723 HE Groningen, The Netherlands)

Abstract

Little is known about factors contributing to perceived stigma in parents of children and adolescents with behavioral and emotional problems in outpatient mental healthcare. We aimed to identify the most relevant factors related to perceived parental stigma using least absolute shrinkage and selection operator (LASSO) regression including a broad range of factors across six domains: (1) child characteristics, (2) characteristics of the primary parent, (3) parenting and family characteristics, (4) treatment-related characteristics, (5) sociodemographic characteristics, and (6) social–environmental characteristics. We adapted the Parents’ Perceived Stigma of Service Seeking scale to measure perceived public stigma and affiliate stigma in 312 parents (87.8% mothers) during the first treatment year after referral to an outpatient child and adolescent clinic. We found that the six domains, including 45 individual factors, explained 34.0% of perceived public stigma and 19.7% of affiliate stigma. Child and social–environmental characteristics (social relations) explained the most deviance in public stigma, followed by parental factors. The strongest factors were more severe problems of the child (especially callous–unemotional traits and internalizing problems), mental healthcare use of the parent, and lower perceived parenting competence. The only relevant factor for affiliate stigma was lower perceived parenting competence. Our study points to the multifactorial nature of perceived stigma and supports that parents’ perceived public stigma is susceptible to social influences, while affiliate stigma relates to parents’ self-evaluation. Increasing parents’ perceived parenting competence may help mitigate perceived stigma. Future studies should explore how stigma relates to treatment outcomes.

Suggested Citation

  • Halewijn M. Drent & Barbara van den Hoofdakker & Jan K. Buitelaar & Pieter J. Hoekstra & Andrea Dietrich, 2022. "Factors Related to Perceived Stigma in Parents of Children and Adolescents in Outpatient Mental Healthcare," IJERPH, MDPI, vol. 19(19), pages 1-14, October.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12767-:d:934471
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/19/12767/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/19/12767/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Chih-Cheng Chang & Yu-Min Chen & Tai-Ling Liu & Ray C. Hsiao & Wen-Jiun Chou & Cheng-Fang Yen, 2020. "Affiliate Stigma and Related Factors in Family Caregivers of Children with Attention-Deficit/Hyperactivity Disorder," IJERPH, MDPI, vol. 17(2), pages 1-14, January.
    3. Chih-Cheng Chang & Yu-Min Chen & Ray C. Hsiao & Wen-Jiun Chou & Cheng-Fang Yen, 2021. "Affiliate Stigma in Caregivers of Children with Attention-Deficit/Hyperactivity Disorder: The Roles of Stress-Coping Orientations and Parental Child-Rearing Styles," IJERPH, MDPI, vol. 18(17), pages 1-11, August.
    4. Chavira, Denise A. & Bantados, Brenda & Rapp, Amy & Firpo-Perretti, Yudelki M. & Escovar, Emily & Dixon, Louise & Drahota, Amy & Palinkas, Lawrence A., 2017. "Parent-reported stigma and child anxiety: A mixed methods research study," Children and Youth Services Review, Elsevier, vol. 76(C), pages 237-242.
    5. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    6. Ganzeboom, H.B.G. & de Graaf, P.M. & Treiman, D.J. & de Leeuw, J., 1992. "A standard international socio-economic index of occupational status," WORC Paper 92.01.001/1, Tilburg University, Work and Organization Research Centre.
    7. Song, Jieun & Mailick, Marsha R. & Greenberg, Jan S., 2018. "Health of parents of individuals with developmental disorders or mental health problems: Impacts of stigma," Social Science & Medicine, Elsevier, vol. 217(C), pages 152-158.
    8. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    9. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    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. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    2. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    3. Kath, Christopher & Ziel, Florian, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Energy Economics, Elsevier, vol. 76(C), pages 411-423.
    4. Danhyang Lee & Jae Kwang Kim, 2022. "Semiparametric imputation using conditional Gaussian mixture models under item nonresponse," Biometrics, The International Biometric Society, vol. 78(1), pages 227-237, March.
    5. Tutz, Gerhard & Pößnecker, Wolfgang & Uhlmann, Lorenz, 2015. "Variable selection in general multinomial logit models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 207-222.
    6. Mkhadri, Abdallah & Ouhourane, Mohamed, 2013. "An extended variable inclusion and shrinkage algorithm for correlated variables," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 631-644.
    7. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    8. Immanuel Bayer & Philip Groth & Sebastian Schneckener, 2013. "Prediction Errors in Learning Drug Response from Gene Expression Data – Influence of Labeling, Sample Size, and Machine Learning Algorithm," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
    9. Mostafa Rezaei & Ivor Cribben & Michele Samorani, 2021. "A clustering-based feature selection method for automatically generated relational attributes," Annals of Operations Research, Springer, vol. 303(1), pages 233-263, August.
    10. Gustavo A. Alonso-Silverio & Víctor Francisco-García & Iris P. Guzmán-Guzmán & Elías Ventura-Molina & Antonio Alarcón-Paredes, 2021. "Toward Non-Invasive Estimation of Blood Glucose Concentration: A Comparative Performance," Mathematics, MDPI, vol. 9(20), pages 1-13, October.
    11. Karim Barigou & Stéphane Loisel & Yahia Salhi, 2020. "Parsimonious Predictive Mortality Modeling by Regularization and Cross-Validation with and without Covid-Type Effect," Risks, MDPI, vol. 9(1), pages 1-18, December.
    12. Gurgul Henryk & Machno Artur, 2017. "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Polish Statistical Association, vol. 18(1), pages 91-114, March.
    13. Michael Funke & Kadri Männasoo & Helery Tasane, 2023. "Regional Economic Impacts of the Øresund Cross-Border Fixed Link: Cui Bono?," CESifo Working Paper Series 10557, CESifo.
    14. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Post-Print halshs-00917797, HAL.
    15. Zichen Zhang & Ye Eun Bae & Jonathan R. Bradley & Lang Wu & Chong Wu, 2022. "SUMMIT: An integrative approach for better transcriptomic data imputation improves causal gene identification," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    16. Štefan Lyócsa & Petra Vašaničová & Branka Hadji Misheva & Marko Dávid Vateha, 2022. "Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    17. Peter Bühlmann & Jacopo Mandozzi, 2014. "High-dimensional variable screening and bias in subsequent inference, with an empirical comparison," Computational Statistics, Springer, vol. 29(3), pages 407-430, June.
    18. Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis Using Machine and Deep Learning Models," Risks, MDPI, vol. 6(2), pages 1-20, April.
    19. Capanu, Marinela & Giurcanu, Mihai & Begg, Colin B. & Gönen, Mithat, 2023. "Subsampling based variable selection for generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 184(C).
    20. Abhinav Kaushik & Diane Dunham & Xiaorui Han & Evan Do & Sandra Andorf & Sheena Gupta & Andrea Fernandes & Laurie Elizabeth Kost & Sayantani B. Sindher & Wong Yu & Mindy Tsai & Robert Tibshirani & Sco, 2022. "CD8+ T cell differentiation status correlates with the feasibility of sustained unresponsiveness following oral immunotherapy," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

    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:19:y:2022:i:19:p:12767-:d:934471. 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.