IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i2p890-d724438.html
   My bibliography  Save this article

Ultrashort Version of the Utrecht Work Engagement Scale (UWES-3): A Psychometric Assessment

Author

Listed:
  • César Merino-Soto

    (Instituto de Investigación en Psicología, Universidad de San Martin de Porres, Lima 15024, Peru)

  • Milagros Lozano-Huamán

    (Escuela de Psicología, Universidad de San Ignacio de Loyola, Lima 15024, Peru)

  • Sadith Lima-Mendoza

    (Escuela de Psicología, Universidad de San Ignacio de Loyola, Lima 15024, Peru)

  • Gustavo Calderón de la Cruz

    (Instituto de Investigación en Psicología, Universidad de San Martin de Porres, Lima 15024, Peru)

  • Arturo Juárez-García

    (Centro de Investigación Transdisciplinar en Psicología, Universidad Autónoma del Estado de Morelos, Cuernavaca 62350, Mexico)

  • Filiberto Toledano-Toledano

    (Unidad de Investigación en Medicina Basada en Evidencias, Hospital Infantil de México Federico Gómez, Mexico City 06720, Mexico
    Unidad de Investigación Sociomédica, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico)

Abstract

The objective was to determine the validity of the UWES-3, an ultrashort measure of work engagement lacking evidence in Hispanic populations. In total, 200 workers with heterogeneous positions and careers from Metropolitan Lima were enrolled via nonprobabilistic sampling. The UWES-3 and measures of external variables (work accidents, stress overload, and others) were used. Data were collected through a web platform. Items were analysed, nonparametric response theory methods (Mokken scale analysis and Ramsay curves) were applied to the items, and ordinal and linear regression were used to determine the relationships with external variables. The items had statistically similar distributional properties and monotonic associations with external variables but with fewer functional response options. The UWES-3 complied with the monotonic homogeneity model and invariant ordering of items; the scaling of the items, score (greater than 0.80), and reliability (0.94) were high. With the effects of age and sex controlled, the UWES-3 significantly predicted minor accidents at work and job satisfaction and revealed effects of stress overload and perceived efficacy. The theoretical implications of the UWES-3 as a brief unidimensional measure integrating the three original dimensions of the instrument and the practical implications of its use for research and professional practice are discussed.

Suggested Citation

  • César Merino-Soto & Milagros Lozano-Huamán & Sadith Lima-Mendoza & Gustavo Calderón de la Cruz & Arturo Juárez-García & Filiberto Toledano-Toledano, 2022. "Ultrashort Version of the Utrecht Work Engagement Scale (UWES-3): A Psychometric Assessment," IJERPH, MDPI, vol. 19(2), pages 1-14, January.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:2:p:890-:d:724438
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/2/890/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/2/890/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    2. Achim Elfering & Simone Grebner, 2010. "A Smile is Just a Smile: But Only for Men. Sex Differences in Meaning of Faces Scales," Journal of Happiness Studies, Springer, vol. 11(2), pages 179-191, April.
    3. Klaas Sijtsma & Ivo Molenaar, 1987. "Reliability of test scores in nonparametric item response theory," Psychometrika, Springer;The Psychometric Society, vol. 52(1), pages 79-97, March.
    4. J. Ramsay, 1991. "Kernel smoothing approaches to nonparametric item characteristic curve estimation," Psychometrika, Springer;The Psychometric Society, vol. 56(4), pages 611-630, December.
    5. 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).
    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. Gabriela Topa & Mercedes Aranda-Carmena, 2022. "It Is Better for Younger Workers: The Gain Cycle between Job Crafting and Work Engagement," IJERPH, MDPI, vol. 19(21), pages 1-12, November.

    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. Henry Santa-Cruz-Espinoza & Gina Chávez-Ventura & Julio Domínguez-Vergara & César Merino-Soto, 2023. "Internal Structure of the Work–Family Conflict Questionnaire (WFCQ) in Teacher Teleworking," IJERPH, MDPI, vol. 20(2), pages 1-16, January.
    2. 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.
    3. 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).
    4. Markus Pauly & Maria Umlauft & Ali Ünlü, 2018. "Resampling-Based Inference Methods for Comparing Two Coefficients Alpha," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 203-222, March.
    5. Jeffrey Douglas, 2001. "Asymptotic identifiability of nonparametric item response models," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 531-540, December.
    6. 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.
    7. Michael Brusco & J Dennis Cradit & Douglas Steinley, 2021. "A comparison of 71 binary similarity coefficients: The effect of base rates," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-19, April.
    8. Daniel L. Oberski, 2016. "A Review of Latent Variable Modeling With R," Journal of Educational and Behavioral Statistics, , vol. 41(2), pages 226-233, April.
    9. Paas, Leonard J., 1998. "Mokken scaling characteristic sets and acquisition patterns of durable- and financial products," Journal of Economic Psychology, Elsevier, vol. 19(3), pages 353-376, June.
    10. Benjamin Williams, 2019. "Identification of a nonseparable model under endogeneity using binary proxies for unobserved heterogeneity," Quantitative Economics, Econometric Society, vol. 10(2), pages 527-563, May.
    11. Jesper Tijmstra & Herbert Hoijtink & Klaas Sijtsma, 2015. "Evaluating Manifest Monotonicity Using Bayes Factors," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 880-896, December.
    12. Javier Revuelta, 2004. "Analysis of distractor difficulty in multiple-choice items," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 217-234, June.
    13. 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.
    14. Leah M. Feuerstahler, 2019. "Metric Transformations and the Filtered Monotonic Polynomial Item Response Model," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 105-123, March.
    15. Alessandro Chiarotto & Annette Bishop & Nadine E Foster & Kirsty Duncan & Ebenezer Afolabi & Raymond W Ostelo & Muirne C S Paap, 2018. "Item response theory evaluation of the biomedical scale of the Pain Attitudes and Beliefs Scale," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-17, September.
    16. J. Ramsay, 1995. "A similarity-based smoothing approach to nondimensional item analysis," Psychometrika, Springer;The Psychometric Society, vol. 60(3), pages 323-339, September.
    17. Simon Foster & Meichun Mohler-Kuo, 2020. "The proportion of non-depressed subjects in a study sample strongly affects the results of psychometric analyses of depression symptoms," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-13, July.
    18. Chanjin Zheng & Shaoyang Guo & Justin L Kern, 2021. "Fast Bayesian Estimation for the Four-Parameter Logistic Model (4PLM)," SAGE Open, , vol. 11(4), pages 21582440211, October.
    19. Christian Genest & Johanna G. Nešlehová, 2014. "A Conversation with James O. Ramsay," International Statistical Review, International Statistical Institute, vol. 82(2), pages 161-183, August.
    20. 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.

    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:2:p:890-:d:724438. 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.