IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i8p4327-d539063.html
   My bibliography  Save this article

Ticket to Ride: A Longitudinal Journey to Health and Work-Attendance in the JD-R Model

Author

Listed:
  • Benedicte Langseth-Eide

    (Department of Psychology, UiT The Arctic University of Norway, 9019 Tromsø, Norway)

  • Joar Vittersø

    (Department of Psychology, UiT The Arctic University of Norway, 9019 Tromsø, Norway)

Abstract

The present study addresses one of the limitations of the JD-R model, namely, that analyses of the outcomes of the motivational process have largely focused on organizational outcomes and have neglected to investigate the associations between job resources, work engagement and health-related outcomes. Specifically, the aim of this paper is to show that health-related indicators may be outcomes of the motivational process in the job demands-resources (JD-R) model. We achieve this through a two-wave panel study with a two-year time lag. The results provide longitudinal evidence that two well-established job resources (i.e., social support and feedback) predicted work engagement, that work engagement was negatively related to sick leave and that this relation was mediated by subjective health. By showing that health-related indicators could also be outcomes of the motivational process in the JD-R model, we have strengthened the model.

Suggested Citation

  • Benedicte Langseth-Eide & Joar Vittersø, 2021. "Ticket to Ride: A Longitudinal Journey to Health and Work-Attendance in the JD-R Model," IJERPH, MDPI, vol. 18(8), pages 1-11, April.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:8:p:4327-:d:539063
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/8/4327/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/8/4327/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fylkesnes, Knut & Førde, Olav Helge, 1991. "The Tromsø study: Predictors of self-evaluated health--Has society adopted the expanded health concept?," Social Science & Medicine, Elsevier, vol. 32(2), pages 141-146, January.
    2. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
    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. Sven Resnjanskij & Jens Ruhose & Simon Wiederhold & Ludger Wößmann, 2021. "Mentoring verbessert die Arbeitsmarktchancen von stark benachteiligten Jugendlichen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 74(02), pages 31-38, February.
    2. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-dimensional econometrics and regularized GMM," CeMMAP working papers CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Dimitris Bertsimas & Agni Orfanoudaki & Rory B. Weiner, 2020. "Personalized treatment for coronary artery disease patients: a machine learning approach," Health Care Management Science, Springer, vol. 23(4), pages 482-506, December.
    4. Clément de Chaisemartin & Jaime Ramirez-Cuellar, 2024. "At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments?," American Economic Journal: Applied Economics, American Economic Association, vol. 16(1), pages 193-212, January.
    5. Clément de Chaisemartin & Luc Behaghel, 2020. "Estimating the Effect of Treatments Allocated by Randomized Waiting Lists," Econometrica, Econometric Society, vol. 88(4), pages 1453-1477, July.
    6. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    7. Bonesrønning, Hans & Finseraas, Henning & Hardoy, Ines & Iversen, Jon Marius Vaag & Nyhus, Ole Henning & Opheim, Vibeke & Salvanes, Kari Vea & Sandsør, Astrid Marie Jorde & Schøne, Pål, 2022. "Small-group instruction to improve student performance in mathematics in early grades: Results from a randomized field experiment," Journal of Public Economics, Elsevier, vol. 216(C).
    8. Peydró, José-Luis & Jiménez, Gabriel & Kenan, Huremovic & Moral-Benito, Enrique & Vega-Redondo, Fernando, 2020. "Production and financial networks in interplay: Crisis evidence from supplier-customer and credit registers," CEPR Discussion Papers 15277, C.E.P.R. Discussion Papers.
    9. Ruoxuan Xiong & Allison Koenecke & Michael Powell & Zhu Shen & Joshua T. Vogelstein & Susan Athey, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Papers 2107.11732, arXiv.org, revised Apr 2023.
    10. Marie Bjørneby & Annette Alstadsæter & Kjetil Telle, 2018. "Collusive tax evasion by employers and employees. Evidence from a randomized fi eld experiment in Norway," Discussion Papers 891, Statistics Norway, Research Department.
    11. Konrad Menzel, 2021. "Structural Sieves," Papers 2112.01377, arXiv.org, revised Apr 2022.
    12. 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.
    13. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2020. "Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis," Econometrica, Econometric Society, vol. 88(1), pages 265-296, January.
    14. Andrés Elberg & Pedro M. Gardete & Rosario Macera & Carlos Noton, 2019. "Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications," Quantitative Marketing and Economics (QME), Springer, vol. 17(1), pages 1-58, March.
    15. Suresh de Mel & David McKenzie & Christopher Woodruff, 2019. "Labor Drops: Experimental Evidence on the Return to Additional Labor in Microenterprises," American Economic Journal: Applied Economics, American Economic Association, vol. 11(1), pages 202-235, January.
    16. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    17. Chenchuan (Mark) Li & Ulrich K. Müller, 2021. "Linear regression with many controls of limited explanatory power," Quantitative Economics, Econometric Society, vol. 12(2), pages 405-442, May.
    18. Jeon, Sung-Hee & Pohl, R. Vincent, 2019. "Medical innovation, education, and labor market outcomes of cancer patients," Journal of Health Economics, Elsevier, vol. 68(C).
    19. Johnsen, Åshild A. & Kvaløy, Ola, 2021. "Conspiracy against the public - An experiment on collusion11“People of the same trade seldom meet together, even for merriment and diversion, but the conversation ends in a conspiracy against the publ," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).
    20. Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.

    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:18:y:2021:i:8:p:4327-:d:539063. 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.