IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i6p3293-d768584.html
   My bibliography  Save this article

Efficacy of the Virtual Reality Intervention VR FestLab on Alcohol Refusal Self-Efficacy: A Cluster-Randomized Controlled Trial

Author

Listed:
  • Julie Dalgaard Guldager

    (Unit for Health Promotion Research, Department of Public Health, University of Southern Denmark, Degnevej 14, DK6705 Esbjerg, Denmark
    Department of Physiotherapy, University College South Denmark, Degnevej 16, DK6705 Esbjerg, Denmark)

  • Satayesh Lavasani Kjær

    (Unit for Health Promotion Research, Department of Public Health, University of Southern Denmark, Degnevej 14, DK6705 Esbjerg, Denmark)

  • Ulrike Grittner

    (Institute of Biometry and Clinical Epidemiology, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany)

  • Christiane Stock

    (Unit for Health Promotion Research, Department of Public Health, University of Southern Denmark, Degnevej 14, DK6705 Esbjerg, Denmark
    Institute for Health and Nursing Science, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany)

Abstract

It is currently unknown whether a virtual social environment can support young people in building their skills to overcome peer pressure when offered alcohol. This study evaluated the efficacy of the newly developed virtual reality simulation game VR FestLab on the refusal self-efficacy regarding social pressures to drink of Danish male and female students aged 15–18. VR FestLab features a party setting where adolescents can “steer” their own party experience. Eleven schools were included in a cluster-randomized controlled trial and allocated to either the intervention ( n = 181) or the active control group ( n = 191). Students in intervention schools played VR FestLab , while those in the control group played the VR game Oculus Quest—First Steps . The primary outcome measure was the social pressure subscale of the drinking refusal self-efficacy scale (DRSEQ-RA). The intervention effects were measured immediately after the intervention/control session (T1) and after a 6-week follow-up (T2). Data were examined using linear mixed regression models. Our study did not demonstrate a significant effect of drinking refusal self-efficacy at T1. For all secondary outcomes, we observed no substantial differences between the intervention and control groups. This study provides new insights into the feasibility and effectiveness of an innovative virtual reality alcohol prevention tool. VR FestLab can be an innovative and promising contribution to complement existing school-based alcohol prevention, but more research is needed to improve its effectiveness.

Suggested Citation

  • Julie Dalgaard Guldager & Satayesh Lavasani Kjær & Ulrike Grittner & Christiane Stock, 2022. "Efficacy of the Virtual Reality Intervention VR FestLab on Alcohol Refusal Self-Efficacy: A Cluster-Randomized Controlled Trial," IJERPH, MDPI, vol. 19(6), pages 1-18, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:6:p:3293-:d:768584
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/6/3293/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/6/3293/
    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. Lotte Vallentin-Holbech & Julie Dalgaard Guldager & Timo Dietrich & Sharyn Rundle-Thiele & Gunver Majgaard & Patricia Lyk & Christiane Stock, 2020. "Co-Creating a Virtual Alcohol Prevention Simulation with Young People," IJERPH, MDPI, vol. 17(3), pages 1-12, February.
    3. Viechtbauer, Wolfgang, 2010. "Conducting Meta-Analyses in R with the metafor Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i03).
    4. Julie Dalgaard Guldager & Satayesh Lavasani Kjær & Patricia Lyk & Timo Dietrich & Sharyn Rundle-Thiele & Gunver Majgaard & Christiane Stock, 2020. "User Experiences with a Virtual Alcohol Prevention Simulation for Danish Adolescents," IJERPH, MDPI, vol. 17(19), pages 1-14, September.
    5. Rundle-Thiele, Sharyn & Schuster, Lisa & Dietrich, Timo & Russell-Bennett, Rebekah & Drennan, Judy & Leo, Cheryl & Connor, Jason P., 2015. "Maintaining or changing a drinking behavior? GOKA's short-term outcomes," Journal of Business Research, Elsevier, vol. 68(10), pages 2155-2163.
    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. José Jesús Gázquez Linares & Ana Belén Barragán Martín & María del Mar Molero Jurado & María del Mar Simón Márquez & María del Carmen Pérez-Fuentes & África Martos Martínez & Rosa María Del Pino Salva, 2023. "Perception of Parental Attitudes and Self-Efficacy in Refusing Alcohol Drinking and Smoking by Spanish Adolescents: A Cross-Sectional Study," IJERPH, MDPI, vol. 20(1), pages 1-17, January.
    2. Christina Prediger & Robert Hrynyschyn & Iasmina Iepan & Christiane Stock, 2022. "Adolescents’ Perceptions of Gender Aspects in a Virtual-Reality-Based Alcohol-Prevention Tool: A Focus Group Study," IJERPH, MDPI, vol. 19(9), pages 1-17, April.

    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. Zhidiankui Xu & Yu Wu & Yixi Bao & Jiawei Li & Zhengzhong Zhou, 2023. "Using Co-Design to Explore New Trends in Future Kitchen Designs: An Exploratory Workshop Study of College Students in China," IJERPH, MDPI, vol. 20(2), pages 1-22, January.
    2. Christina Prediger & Robert Hrynyschyn & Iasmina Iepan & Christiane Stock, 2022. "Adolescents’ Perceptions of Gender Aspects in a Virtual-Reality-Based Alcohol-Prevention Tool: A Focus Group Study," IJERPH, MDPI, vol. 19(9), pages 1-17, April.
    3. Long, Emily & Gardani, Maria & McCann, Mark & Sweeting, Helen & Tranmer, Mark & Moore, Laurence, 2020. "Mental health disorders and adolescent peer relationships," Social Science & Medicine, Elsevier, vol. 253(C).
    4. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    5. Whitney S Beck & Ed K Hall, 2018. "Confounding factors in algal phosphorus limitation experiments," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-19, October.
    6. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    7. Xindong Xue & W. Robert Reed & Robbie C.M. van Aert, 2022. "Social Capital and Economic Growth: A Meta-Analysis," Working Papers in Economics 22/20, University of Canterbury, Department of Economics and Finance.
    8. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    9. Bart Verkuil & Serpil Atasayi & Marc L Molendijk, 2015. "Workplace Bullying and Mental Health: A Meta-Analysis on Cross-Sectional and Longitudinal Data," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-16, August.
    10. Francesca Pilotto & Ingolf Kühn & Rita Adrian & Renate Alber & Audrey Alignier & Christopher Andrews & Jaana Bäck & Luc Barbaro & Deborah Beaumont & Natalie Beenaerts & Sue Benham & David S. Boukal & , 2020. "Meta-analysis of multidecadal biodiversity trends in Europe," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    11. repec:cup:judgdm:v:15:y:2020:i:6:p:972-988 is not listed on IDEAS
    12. Jonas Schmidt & Tammo H. A. Bijmolt, 2020. "Accurately measuring willingness to pay for consumer goods: a meta-analysis of the hypothetical bias," Journal of the Academy of Marketing Science, Springer, vol. 48(3), pages 499-518, May.
    13. 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.
    14. Liangyuan Hu & Lihua Li, 2022. "Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series," IJERPH, MDPI, vol. 19(23), pages 1-13, December.
    15. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    16. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    17. Eunsil Seok & Akhgar Ghassabian & Yuyan Wang & Mengling Liu, 2024. "Statistical Methods for Modeling Exposure Variables Subject to Limit of Detection," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 435-458, July.
    18. Mario Herberz & Tobias Brosch & Ulf J. J. Hahnel, 2020. "Kilo what? Default units increase value sensitivity in joint evaluations of energy efficiency," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(6), pages 972-988, November.
    19. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
    20. Georges Steffgen & Philipp E. Sischka & Martha Fernandez de Henestrosa, 2020. "The Quality of Work Index and the Quality of Employment Index: A Multidimensional Approach of Job Quality and Its Links to Well-Being at Work," IJERPH, MDPI, vol. 17(21), pages 1-31, October.
    21. 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.

    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:6:p:3293-:d:768584. 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.