IDEAS home Printed from https://ideas.repec.org/a/spr/chinre/v11y2018i4d10.1007_s12187-017-9472-9.html
   My bibliography  Save this article

Social Desirability Bias in Child-Report Social Well-Being: Evaluation of the Children’s Social Desirability Short Scale Using Item Response Theory and Examination of Its Impact on Self-Report Family and Peer Relationships

Author

Listed:
  • Anne-Linda Camerini

    (Università della Svizzera italiana)

  • Peter J. Schulz

    (Università della Svizzera italiana)

Abstract

Research on child well-being largely relies on children’s self-report data, potentially biased by social desirability (SD). In this study, we aim to (1) evaluate the psychometric properties of the Children’s Social Desirability Short (CSD-S) scale, and (2) examine if and, if so, how SD systematically biases child-report family and peer relationships as indicators of social well-being. In spring 2015, 843 elementary school children (aged 10) and their parents were surveyed on well-being indicators and SD measured with the 14-items Children’s Social Desirability Short (CSD-S) scale. The CSD-S was evaluated using nonparametric Item Response Theory (NIRT). Linear mixed-effects regression models based on multiple imputations of multilevel missing data were run to examine the role of SD in self-report social well-being in addition to socio-demographic characteristics, accounting for the nested structure of the data (students were sampled at class level). Applying NIRT, we identified a 13-items subset of the CSD-S with double monotonicity. Cronbach’s alpha was .82. When controlling for children’s socio-demographic characteristics, SD significantly positively predicted subjective evaluations of family relationships (B = 0.04, t(49272) = 7.45, p

Suggested Citation

  • Anne-Linda Camerini & Peter J. Schulz, 2018. "Social Desirability Bias in Child-Report Social Well-Being: Evaluation of the Children’s Social Desirability Short Scale Using Item Response Theory and Examination of Its Impact on Self-Report Family ," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 11(4), pages 1159-1174, August.
  • Handle: RePEc:spr:chinre:v:11:y:2018:i:4:d:10.1007_s12187-017-9472-9
    DOI: 10.1007/s12187-017-9472-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12187-017-9472-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12187-017-9472-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Klaas Sijtsma & Bas Hemker, 1998. "Nonparametric polytomous IRT models for invariant item ordering, with results for parametric models," Psychometrika, Springer;The Psychometric Society, vol. 63(2), pages 183-200, June.
    2. van der Ark, L. Andries, 2007. "Mokken Scale Analysis in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 20(i11).
    3. Ivar Krumpal, 2013. "Determinants of social desirability bias in sensitive surveys: a literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2025-2047, June.
    4. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    5. van Schuur, Wijbrandt H., 2003. "Mokken Scale Analysis: Between the Guttman Scale and Parametric Item Response Theory," Political Analysis, Cambridge University Press, vol. 11(2), pages 139-163, April.
    6. van der Ark, L. Andries, 2012. "New Developments in Mokken Scale Analysis in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i05).
    7. Elizabeth Pollard & Patrice Lee, 2003. "Child Well-being: A Systematic Review of the Literature," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 61(1), pages 59-78, January.
    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. Fastoso, Fernando & González-Jiménez, Héctor & Cometto, Teresa, 2021. "Mirror, mirror on my phone: Drivers and consequences of selfie editing," Journal of Business Research, Elsevier, vol. 133(C), pages 365-375.
    2. Stahlberg, Stephanie G. & Díaz-Cayeros, Alberto & Pizatella-Haswell, Rachel, 2022. "Supporting youth and families to prevent risky youth behavior and delinquency: An impact evaluation of a family counseling program in the Caribbean," Children and Youth Services Review, Elsevier, vol. 142(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. Dima, Alexandra L. & Stutterheim, Sarah E. & Lyimo, Ramsey & de Bruin, Marijn, 2014. "Advancing methodology in the study of HIV status disclosure: The importance of considering disclosure target and intent," Social Science & Medicine, Elsevier, vol. 108(C), pages 166-174.
    2. Jesper Tijmstra & Maria Bolsinova, 2019. "Bayes Factors for Evaluating Latent Monotonicity in Polytomous Item Response Theory Models," Psychometrika, Springer;The Psychometric Society, vol. 84(3), pages 846-869, September.
    3. Andersson-Hudson, Jessica & Rose, Jonathan & Humphrey, Mathew & Knight, Wil & O'Hara, Sarah, 2019. "The structure of attitudes towards shale gas extraction in the United Kingdom," Energy Policy, Elsevier, vol. 129(C), pages 693-697.
    4. Penny Bee & Chris Gibbons & Patrick Callaghan & Claire Fraser & Karina Lovell, 2016. "Evaluating and Quantifying User and Carer Involvement in Mental Health Care Planning (EQUIP): Co-Development of a New Patient-Reported Outcome Measure," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-14, March.
    5. Coromina, Lluís & Camprubí, Raquel, 2016. "Analysis of tourism information sources using a Mokken Scale perspective," Tourism Management, Elsevier, vol. 56(C), pages 75-84.
    6. Rudy Ligtvoet & L. Ark & Wicher Bergsma & Klaas Sijtsma, 2011. "Polytomous Latent Scales for the Investigation of the Ordering of Items," Psychometrika, Springer;The Psychometric Society, vol. 76(2), pages 200-216, April.
    7. César Merino-Soto & Gina Chávez-Ventura & Verónica López-Fernández & Guillermo M. Chans & Filiberto Toledano-Toledano, 2022. "Learning Self-Regulation Questionnaire (SRQ-L): Psychometric and Measurement Invariance Evidence in Peruvian Undergraduate Students," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    8. van der Ark, L. Andries, 2012. "New Developments in Mokken Scale Analysis in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i05).
    9. Bastiaan Bruinsma, 2020. "A comparison of measures to validate scales in voting advice applications," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(4), pages 1299-1316, August.
    10. Tyrone B. Pretorius & P. Paul Heppner & Anita Padmanabhanunni & Serena Ann Isaacs, 2023. "The PSI-20: Development of a Viable Short Form Alternative of the Problem Solving Inventory Using Item Response Theory," SAGE Open, , vol. 13(4), pages 21582440231, December.
    11. Wickelmaier, Florian & Strobl, Carolin & Zeileis, Achim, 2012. "Psychoco: Psychometric Computing in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i01).
    12. Martin Komarc & Ivana Harbichová & Lawrence M Scheier, 2020. "Psychometric validation of Czech version of the Sport Motivation Scale," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-20, January.
    13. Jules L. Ellis & Klaas Sijtsma, 2023. "A Test to Distinguish Monotone Homogeneity from Monotone Multifactor Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 387-412, June.
    14. Tendeiro, Jorge N. & Meijer, Rob R. & Niessen, A. Susan M., 2016. "PerFit: An R Package for Person-Fit Analysis in IRT," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i05).
    15. Michael Brusco & Hans-Friedrich Köhn & Douglas Steinley, 2015. "An Exact Method for Partitioning Dichotomous Items Within the Framework of the Monotone Homogeneity Model," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 949-967, December.
    16. Rita Saleh & Angela Bearth & Michael Siegrist, 2019. "“Chemophobia” Today: Consumers’ Knowledge and Perceptions of Chemicals," Risk Analysis, John Wiley & Sons, vol. 39(12), pages 2668-2682, December.
    17. Mirko Antino & Jesús M. Alvarado & Rodrigo A. Asún & Paul Bliese, 2020. "Rethinking the Exploration of Dichotomous Data: Mokken Scale Analysis Versus Factorial Analysis," Sociological Methods & Research, , vol. 49(4), pages 839-867, November.
    18. Mazza, Angelo & Punzo, Antonio & McGuire, Brian, 2014. "KernSmoothIRT: An R Package for Kernel Smoothing in Item Response Theory," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i06).
    19. Jules Ellis, 2014. "An Inequality for Correlations in Unidimensional Monotone Latent Variable Models for Binary Variables," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 303-316, April.
    20. repec:jss:jstsof:20:i11 is not listed on IDEAS
    21. Susan D Shenkin & Roger Watson & Ken Laidlaw & John M Starr & Ian J Deary, 2014. "The Attitudes to Ageing Questionnaire: Mokken Scaling Analysis," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-11, June.

    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:spr:chinre:v:11:y:2018:i:4:d:10.1007_s12187-017-9472-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.