IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0217015.html
   My bibliography  Save this article

Prevalence of intimate partner violence against women in Sweden and Spain: A psychometric study of the ‘Nordic paradox’

Author

Listed:
  • Enrique Gracia
  • Manuel Martín-Fernández
  • Marisol Lila
  • Juan Merlo
  • Anna-Karin Ivert

Abstract

The high prevalence of intimate partner violence against women (IPVAW) in countries with high levels of gender equality has been defined as the “Nordic paradox”. In this study we compared physical and sexual IPVAW prevalence data in two countries exemplifying the Nordic paradox: Sweden (N = 1483) and Spain (N = 1447). Data was drawn from the European Union Agency for Fundamental Rights Survey on violence against women. To ascertain whether differences between these two countries reflect true differences in IPVAW prevalence, and to rule out the possibility of measurement bias, we conducted a set of analyses to ensure measurement equivalence, a precondition for appropriate and valid cross-cultural comparisons. Results showed that in both countries items were measuring two separate constructs, physical and sexual IPVAW, and that these factors had high internal consistency and adequate validity. Measurement equivalence analyses (i.e., differential item functioning, and multigroup confirmatory factor analysis) supported the comparability of data across countries. Latent means comparisons between the Spanish and the Swedish samples showed that scores on both the physical and sexual IPVAW factors were significantly higher in Sweden than in Spain. The effect sizes of these differences were large: 89.1% of the Swedish sample had higher values in the physical IPVAW factor than the Spanish average, and this percentage was 99.4% for the sexual IPVAW factor as compared to the Spanish average. In terms of probability of superiority, there was an 80.7% and 96.1% probability that a Swedish woman would score higher than a Spanish woman in the physical and the sexual IPVAW factors, respectively. Our results showed that the higher prevalence of physical and sexual IPVAW in Sweden than in Spain reflects actual differences and are not the result of measurement bias, supporting the idea of the Nordic paradox.

Suggested Citation

  • Enrique Gracia & Manuel Martín-Fernández & Marisol Lila & Juan Merlo & Anna-Karin Ivert, 2019. "Prevalence of intimate partner violence against women in Sweden and Spain: A psychometric study of the ‘Nordic paradox’," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-17, May.
  • Handle: RePEc:plo:pone00:0217015
    DOI: 10.1371/journal.pone.0217015
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217015
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0217015&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0217015?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
    ---><---

    References listed on IDEAS

    as
    1. Choi, Seung W. & Gibbons, Laura E. & Crane, Paul K., 2011. "lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(i08).
    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. Gonthier, Corentin & Grégoire, Jacques, 2022. "Flynn effects are biased by differential item functioning over time: A test using overlapping items in Wechsler scales," Intelligence, Elsevier, vol. 95(C).
    2. Cervantes, Víctor H., 2017. "DFIT: An R Package for Raju's Differential Functioning of Items and Tests Framework," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i05).
    3. Wenling Liu & Ziping Xu & Tianan Yang, 2018. "Health Effects of Air Pollution in China," IJERPH, MDPI, vol. 15(7), pages 1-15, July.
    4. Kai Liu & Longfei Zhang & Dongbo Tu & Yan Cai, 2022. "Developing an Item Bank of Computerized Adaptive Testing for Eating Disorders in Chinese University Students," SAGE Open, , vol. 12(4), pages 21582440221, December.
    5. Jeanne A. Teresi & Katja Ocepek-Welikson & John A. Toner & Marjorie Kleinman & Mildred Ramirez & Joseph P. Eimicke & Barry J. Gurland & Albert Siu, 2017. "Methodological Issues in Measuring Subjective Well-Being and Quality-of-Life: Applications to Assessment of Affect in Older, Chronically and Cognitively Impaired, Ethnically Diverse Groups Using the F," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 12(2), pages 251-288, June.
    6. Marissa A. Gogniat & Violeta J. Rodriguez & Maria Granros & Kharine R. Jean & Talia L. Robinson & L. Stephen Miller, 2022. "Differential Item Functioning: An Examination of the NEO-FFI by Sex in Older Adults," SAGE Open, , vol. 12(1), pages 21582440221, March.
    7. Christopher B. Forrest & Ulrike Ravens-Sieberer & Janine Devine & Brandon D. Becker & Rachel E. Teneralli & JeanHee Moon & Adam C. Carle & Carole A. Tucker & Katherine B. Bevans, 2018. "Development and Evaluation of the PROMIS® Pediatric Positive Affect Item Bank, Child-Report and Parent-Proxy Editions," Journal of Happiness Studies, Springer, vol. 19(3), pages 699-718, March.
    8. Ke-Hai Yuan & Hongyun Liu & Yuting Han, 2021. "Differential Item Functioning Analysis Without A Priori Information on Anchor Items: QQ Plots and Graphical Test," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 345-377, June.
    9. Torbjørn Torsheim & Franco Cavallo & Kate Ann Levin & Christina Schnohr & Joanna Mazur & Birgit Niclasen & Candace Currie, 2016. "Psychometric Validation of the Revised Family Affluence Scale: a Latent Variable Approach," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 9(3), pages 771-784, September.
    10. Carla Sabariego & Cornelia Oberhauser & Aleksandra Posarac & Jerome Bickenbach & Nenad Kostanjsek & Somnath Chatterji & Alana Officer & Michaela Coenen & Lay Chhan & Alarcos Cieza, 2015. "Measuring Disability: Comparing the Impact of Two Data Collection Approaches on Disability Rates," IJERPH, MDPI, vol. 12(9), pages 1-23, August.
    11. Benjamin D. Schalet & Sangdon Lim & David Cella & Seung W. Choi, 2021. "Linking Scores with Patient-Reported Health Outcome Instruments:A VALIDATION STUDY AND COMPARISON OF THREE LINKING METHODS," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 717-746, September.
    12. Sati Bozkurt & Gizem B. Ekitli & Christopher L. Thomas & Jerrell C. Cassady, 2017. "Validation of the Turkish Version of the Cognitive Test Anxiety Scale–Revised," SAGE Open, , vol. 7(1), pages 21582440166, January.
    13. Martin Jelínek & Petr Květon & Iva Burešová & Helena Klimusová, 2021. "Measuring depression in adolescence: Evaluation of a hierarchical factor model of the Children’s Depression Inventory and measurement invariance across boys and girls," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-17, April.
    14. Rikkert M. van der Lans & Ridwan Maulana & Michelle Helms-Lorenz & Carmen-María Fernández-García & Seyeoung Chun & Thelma de Jager & Yulia Irnidayanti & Mercedes Inda-Caro & Okhwa Lee & Thys Coetze, 2021. "Student Perceptions of Teaching Quality in Five Countries: A Partial Credit Model Approach to Assess Measurement Invariance," SAGE Open, , vol. 11(3), pages 21582440211, August.
    15. Jeanne A. Teresi & Chun Wang & Marjorie Kleinman & Richard N. Jones & David J. Weiss, 2021. "Differential Item Functioning Analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Measures: Methods, Challenges, Advances, and Future Directions," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 674-711, September.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0217015. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.