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As if it weren’t hard enough already: Breaking down hiring discrimination following burnout

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  • Sterkens, Philippe
  • Baert, Stijn
  • Rooman, Claudia
  • Derous, Eva
Abstract
Hiring discrimination towards (former) burnout patients has been extensively documented in the literature. To tackle this problem, it is important to understand the underlying mechanisms of such unequal hiring opportunities. Therefore, we conducted a vignette experiment with 425 genuine recruiters and jointly tested the potential stigma against job candidates with a history of burnout that were mentioned earlier in the literature. We found candidates revealing a history of burnout elicit perceptions of requiring work adaptations, likely having more unpleasant collaborations with others as well as diminished health, autonomy, ability to work under pressure, leadership capacity, manageability, and learning ability, when compared to candidates with a comparable gap in working history due to physical injury. Led by perceptions of a reduced ability to work under pressure, the tested perceptions jointly explained over 90 % of the effect of revealing burnout on the probability of being invited to a job interview. In addition, the negative effect on interview probability of revealing burnout was stronger when the job vacancy required higher stress tolerance. In contrast, the negative impact of revealing burnout on interview probability appeared weaker when recruiters were women and when recruiters had previously had personal encounters with burnout.

Suggested Citation

  • Sterkens, Philippe & Baert, Stijn & Rooman, Claudia & Derous, Eva, 2021. "As if it weren’t hard enough already: Breaking down hiring discrimination following burnout," Economics & Human Biology, Elsevier, vol. 43(C).
    • Handle: RePEc:eee:ehbiol:v:43:y:2021:i:c:s1570677x21000745
    DOI: 10.1016/j.ehb.2021.101050
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    1. Baert, Stijn & De Visschere, Sarah & Schoors, Koen & Vandenberghe, Désirée & Omey, Eddy, 2016. "First depressed, then discriminated against?," Social Science & Medicine, Elsevier, vol. 170(C), pages 247-254.
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    3. Van Belle, Eva & Caers, Ralf & Cuypers, Laure & De Couck, Marijke & Neyt, Brecht & Van Borm, Hannah & Baert, Stijn, 2020. "What do student jobs on graduate CVs signal to employers?," Economics of Education Review, Elsevier, vol. 75(C).
    4. Jones, Andrew M. & Rice, Nigel & Zantomio, Francesca, 2020. "Acute health shocks and labour market outcomes: Evidence from the post crash era," Economics & Human Biology, Elsevier, vol. 36(C).
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    6. Ilyana Kuziemko & Michael I. Norton & Emmanuel Saez & Stefanie Stantcheva, 2015. "How Elastic Are Preferences for Redistribution? Evidence from Randomized Survey Experiments," American Economic Review, American Economic Association, vol. 105(4), pages 1478-1508, April.
    7. Van Borm, Hannah & Burn, Ian & Baert, Stijn, 2021. "What Does a Job Candidate's Age Signal to Employers?," Labour Economics, Elsevier, vol. 71(C).
    8. Marianne Bertrand & Dolly Chugh & Sendhil Mullainathan, 2005. "Implicit Discrimination," American Economic Review, American Economic Association, vol. 95(2), pages 94-98, May.
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    Cited by:

    1. Moens, Eline & Verhofstadt, Elsy & Van Ootegem, Luc & Baert, Stijn, 2023. "So, Dear Applicant, Do You Mean Working from Home or Shirking from Home?," IZA Discussion Papers 16560, Institute of Labor Economics (IZA).
    2. Sterkens, Philippe & Baert, Stijn & Rooman, Claudia & Derous, Eva, 2021. "Why Making Promotion After a Burnout Is Like Boiling the Ocean," GLO Discussion Paper Series 871, Global Labor Organization (GLO).
    3. Philippe Sterkens & Adelina Sharipova & Stijn Baert, 2024. "Disclosing the ‘Big C’: what does cancer survivorship signal to employers?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(4), pages 671-688, June.

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    More about this item

    Keywords

    Hiring discrimination; Burnout; Statistical discrimination; Taste-based discrimination;
    All these keywords.

    JEL classification:

    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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