Skip to main content
Log in

Challenge and Hindrance Stressors and Work Outcomes: the Moderating Role of Day-Level Affect

  • Original Paper
  • Published:
Journal of Business and Psychology Aims and scope Submit manuscript

Abstract

Our research examined the role of challenge and hindrance stressors, as well as the interactive effects of these stressors with positive and negative affect, in predicting work engagement and exhaustion using experience sampling methodology. In Study 1, university staff completed measures of challenge and hindrance stressors, positive and negative affect, work engagement, and exhaustion before the end of the workday over 5 working days. Results from multilevel regression indicated that challenge stressors were positively related to work engagement but not exhaustion, while hindrance stressors were unrelated to both work engagement and exhaustion. Additionally, positive affect moderated the association between challenge stressors and both work engagement and exhaustion. We partially replicated and extended these findings in our second sample of Amazon’s Mechanical Turk workers, who completed measures of affect in the mornings before starting work and stressors, work engagement, and exhaustion in the evenings before leaving work, over a period of 10 working days. Results suggested that challenge stressors were positively related to work engagement and exhaustion, while hindrance stressors were positively related to exhaustion and negatively related to work engagement. Similar to our results in Study 1, we found that positive affect interacted with challenge stressors in predicting each work outcome. Furthermore, positive affect moderated the hindrance stressor-work outcomes relationship. Lastly, negative affect moderated the association between challenge stressors and exhaustion. The findings of this study can be used to design interventions that enhance employee motivation and engagement in the presence of challenge and hindrance stressors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. We ran these analyses with and without controlling for state of recovery. When controlling for state of recovery, positive affect did not significantly predict workday exhaustion when simultaneously assessed with negative affect and challenge stressors. All other findings remained the same.

References

  • Aiken, L. S., West, S. G., & Reno, R. R. (1991). Multiple regression: Testing and interpreting interactions. Sage.

  • Allen, T. D., French, K. A., Braun, M. T., & Fletcher, K. (2019). The passage of time in work-family research: Toward a more dynamic perspective. Journal of Vocational Behavior, 110, 245–257.

    Article  Google Scholar 

  • Bakker, A. B., & Demerouti, E. (2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22, 309–328.

    Article  Google Scholar 

  • Balk, Y. A., de Jonge, J., Geurts, S. A., & Oerlemans, W. G. (2019). Antecedents and consequences of perceived autonomy support in elite sport: a diary study linking coaches’ off-job recovery and athletes’ performance satisfaction. Psychology of Sport and Exercise, 44, 26–34.

    Article  Google Scholar 

  • Bindl, U. K., Parker, S. K., Totterdell, P., & Hagger-Johnson, G. (2012). Fuel of the self-starter: How mood relates to proactive goal regulation. Journal of Applied Psychology, 97, 134–150.

    Article  Google Scholar 

  • Binnewies, C., & Wörnlein, S. C. (2011). What makes a creative day? A diary study on the interplay between affect, job stressors, and job control. Journal of Organizational Behavior, 32, 589–607.

    Article  Google Scholar 

  • Bliese, P. (2016). Multilevel: Multilevel Functions [Software].

  • Bliese, P. D., Schepker, D. J., Essman, S. M., & Ployhart, R. E. (2020). Bridging methodological divides between macro-and microresearch: Endogeneity and methods for panel data. Journal of Management, 46, 70–99.

    Article  Google Scholar 

  • Boswell, W. R., Olson-Buchanan, J. B., & LePine, M. A. (2004). Relations between stress and work outcomes: The role of felt challenge, job control, and psychological strain. Journal of Vocational Behavior, 64, 165–181.

    Article  Google Scholar 

  • Breevaart, K., & Bakker, A. B. (2018). Daily job demands and employee work engagement: The role of daily transformational leadership behavior. Journal of Occupational Health Psychology, 23, 338–349.

    Article  PubMed  Google Scholar 

  • Buhrmester, M. D., Talaifar, S., & Gosling, S. D. (2018). An evaluation of Amazon’s Mechanical Turk, its rapid rise, and its effective use. Perspectives on Psychological Science, 13, 149–154.

    Article  PubMed  Google Scholar 

  • Casler, K., Bickel, L., & Hackett, E. (2013). Separate but equal? A comparison of participants and data gathered via Amazon’s MTurk, social media, and face-to-face behavioral testing. Computers in Human Behavior, 29, 2156–2160.

    Article  Google Scholar 

  • Cavanaugh, M. A., Boswell, W. R., Roehling, M. V., & Boudreau, J. W. (2000). An empirical examination of self-reported work stress among US managers. Journal of Applied Psychology, 85, 65–74.

    Article  Google Scholar 

  • Crane, M. F., & Searle, B. J. (2016). Building resilience through exposure to stressors: The effects of challenges versus hindrances. Journal of Occupational Health Psychology, 21, 468–479.

    Article  PubMed  Google Scholar 

  • Crawford, E. R., LePine, J. A., & Rich, B. L. (2010). Linking job demands and resources to employee engagement and burnout: A theoretical extension and meta-analytic test. Journal of Applied Psychology, 95, 834–848.

    Article  Google Scholar 

  • Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86, 499–512.

    Article  Google Scholar 

  • DeShon, R. P., Ployhart, R. E., & Sacco, J. M. (1998). The estimation of reliability in longitudinal models. International Journal of Behavioral Development, 22, 493–515.

    Article  Google Scholar 

  • Edwards, B. D., Franco-Watkins, A. M., Cullen, K. L., Howell, J. W., & Acuff, R. E., Jr. (2014). Unifying the challenge-hindrance and sociocognitive models of stress. International Journal of Stress Management, 21, 162–185.

    Article  Google Scholar 

  • Feuerhahn, N., Sonnentag, S., & Woll, A. (2014). Exercise after work, psychological mediators, and affect: A day-level study. European Journal of Work and Organizational Psychology, 23, 62–79.

    Article  Google Scholar 

  • Folkman, S., & Lazarus, R. S. (1985). If it changes it must be a process: Study of emotion and coping during three stages of a college examination. Journal of Personality and Social Psychology, 48, 150–170.

    Article  PubMed  Google Scholar 

  • Ford, M. T., Matthews, R. A., Wooldridge, J. D., Mishra, V., Kakar, U. M., & Strahan, S. R. (2014). How do occupational stressor-strain effects vary with time? A review and meta-analysis of the relevance of time lags in longitudinal studies. Work & Stress, 28, 9–30.

    Article  Google Scholar 

  • Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American Psychologist, 56(3), 218–226.

    Article  Google Scholar 

  • Frijda, N. H. (1987). Emotion, cognitive structure, and action tendency. Cognition and Emotion, 1, 115–143.

    Article  Google Scholar 

  • Heinisch, D. A., & Jex, S. M. (1997). Negative affectivity and gender as moderators of the relationship between work-related stressors and depressed mood at work. Work & Stress, 11, 46–57.

    Article  Google Scholar 

  • Huelsman, T. J., Nemanick, R. C., Jr., & Munz, D. C. (1998). Scales to measure four dimensions of dispositional mood: Positive energy, tiredness, negative activation, and relaxation. Educational and Psychological Measurement, 58, 804–819.

    Article  Google Scholar 

  • Isen, A. M., & Shalker, T. E. (1982). The effect of feeling state on evaluation of positive, neutral, and negative stimuli: When you “accentuate the positive,” do you “eliminate the negative”? Social psychology Quarterly, 58–63.

  • Jayawickreme, E., Tsukayama, E., & Kashdan, T. B. (2017). Examining the effect of affect on life satisfaction judgments: A within-person perspective. Journal of Research in Personality, 68, 32–37.

    Article  Google Scholar 

  • Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer publishing company.

  • LePine, J. A., Podsakoff, N. P., & LePine, M. A. (2005). A meta-analytic test of the challenge stressor–hindrance stressor framework: An explanation for inconsistent relationships among stressors and performance. Academy of Management Journal, 48, 764–775.

    Article  Google Scholar 

  • Lin, W., Ma, J., Wang, L., & Wang, M. (2015). A double-edged sword: The moderating role of conscientiousness in the relationships between work stressors, psychological strain, and job performance. Journal of Organizational Behavior, 36, 94–111.

    Article  Google Scholar 

  • Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002). To parcel or not to parcel: Exploring the question, weighing the merits. Structural Equation Modeling, 9(2), 151–173.

    Article  Google Scholar 

  • Liu, C., Liu, Y., Mills, M. J., & Fan, J. (2013). Job stressors, job performance, job dedication, and the moderating effect of conscientiousness: A mixed-method approach. International Journal of Stress Management, 20, 336–363.

    Article  Google Scholar 

  • Malinowski, P., & Lim, H. J. (2015). Mindfulness at work: Positive affect, hope, and optimism mediate the relationship between dispositional mindfulness, work engagement, and well-being. Mindfulness, 6, 1250–1262.

    Article  Google Scholar 

  • Mazzola, J. J., & Disselhorst, R. (2019). Should we be “challenging” employees? A critical review and meta-analysis of the challenge-hindrance model of stress. Journal of Organizational Behavior, 40(8), 949–961.

    Article  Google Scholar 

  • McCormick, B. W., Reeves, C. J., Downes, P. E., Li, N., & Ilies, R. (2020). Scientific contributions of within-person research in management: Making the juice worth the squeeze. Journal of Management, 46(2), 321–350.

  • Michel, J. S., O’Neill, S. K., Hartman, P., & Lorys, A. (2018). Amazon’s Mechanical Turk as a viable source for organizational and occupational health research. Occupational Health Science, 2, 83–98.

    Article  Google Scholar 

  • Min, H., Kim, H. J., & Lee, S. B. (2015). Extending the challenge–hindrance stressor framework: The role of psychological capital. International Journal of Hospitality Management, 50, 105–114.

    Article  Google Scholar 

  • Paolacci, G., & Chandler, J. (2014). Inside the Turk: Understanding Mechanical Turk as a participant pool. Current Directions in Psychological Science, 23, 184–188.

    Article  Google Scholar 

  • Ployhart, R. E., Holtz, B. C., & Bliese, P. D. (2002). Longitudinal data analysis: Applications of random coefficient modeling to leadership research. The Leadership Quarterly, 13, 455–486.

    Article  Google Scholar 

  • Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569.

    Article  PubMed  Google Scholar 

  • Reis, D., Arndt, C., Lischetzke, T., & Hoppe, A. (2016). State work engagement and state affect: Similar yet distinct concepts. Journal of Vocational Behavior, 93, 1–10.

    Article  Google Scholar 

  • Rodell, J. B., & Judge, T. A. (2009). Can “good” stressors spark “bad” behaviors? The mediating role of emotions in links of challenge and hindrance stressors with citizenship and counterproductive behaviors. Journal of Applied Psychology, 94, 1438–1451.

    Article  Google Scholar 

  • Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161–1178.

    Article  Google Scholar 

  • Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110, 145–172.

    Article  PubMed  Google Scholar 

  • Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). Utrecht Work Engagement Scale-9.

  • Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology, 45, 513–523.

    Article  Google Scholar 

  • Searle, B. J., & Lee, L. (2015). Proactive coping as a personal resource in the expanded job demands–resources model. International Journal of Stress Management, 22, 46–69.

    Article  Google Scholar 

  • Selye, H. (1982). History and present status of the stress concept. In L. Goldberger & S. Breznitz (Eds.), Handbook of stress (pp. 7–17). New York: Free Press.

  • Shirom, A., & Melamed, S. (2006). A comparison of the construct validity of two burnout measures in two groups of professionals. International Journal of Stress Management, 13, 176–200.

    Article  Google Scholar 

  • Shockley, K. M., Ispas, D., Rossi, M. E., & Levine, E. L. (2012). A meta-analytic investigation of the relationship between state affect, discrete emotions, and job performance. Human Performance, 25, 377–411.

    Article  Google Scholar 

  • Sonnentag, S. (2015). Dynamics of well-being. Annual Review of Organizational Psychology and Organizational Behavior, 2, 261–293.

    Article  Google Scholar 

  • Tadić, M., Bakker, A. B., & Oerlemans, W. G. (2015). Challenge versus hindrance job demands and well-being: A diary study on the moderating role of job resources. Journal of Occupational and Organizational Psychology, 8, 702–725.

    Article  Google Scholar 

  • Thayer, R. E. (1989). The biopsychology of mood and arousal. Oxford University Press.

  • Totterdell, P., Wall, T., Holman, D., Diamond, H., & Epitropaki, O. (2004). Affect networks: A structural analysis of the relationship between work ties and job-related affect. Journal of Applied Psychology, 89, 854–867.

    Article  Google Scholar 

  • Van den Broeck, A., De Cuyper, N., De Witte, H., & Vansteenkiste, M. (2010). Not all job demands are equal: Differentiating job hindrances and job challenges in the Job Demands-Resources model. European Journal of Work and Organizational Psychology, 19, 735–759.

    Article  Google Scholar 

  • Van den Heuvel, M., Demerouti, E., & Peeters, M. C. (2015). The job crafting intervention: Effects on job resources, self-efficacy, and affective well-being. Journal of Occupational and Organizational Psychology, 88, 511–532.

    Article  Google Scholar 

  • Wallace, J. C., Edwards, B. D., Arnold, T., Frazier, M. L., & Finch, D. M. (2009). Work stressors, role-based performance, and the moderating influence of organizational support. Journal of Applied Psychology, 94, 254–262.

    Article  Google Scholar 

  • Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.

    Article  PubMed  Google Scholar 

  • Webster, J. R., Beehr, T. A., & Christiansen, N. D. (2010). Toward a better understanding of the effects of hindrance and challenge stressors on work behavior. Journal of Vocational Behavior, 76, 68–77.

    Article  Google Scholar 

  • Webster, J. R., Beehr, T. A., & Love, K. (2011). Extending the challenge-hindrance model of occupational stress: The role of appraisal. Journal of Vocational Behavior, 79, 505–516.

    Article  Google Scholar 

  • Weiss, H. M., & Cropanzano, R. (1996). Affective events theory: A theoretical discussion of the structure, causes and consequences of affective experiences at work. Research in Organizational Behavior, 18, 1–74.

    Google Scholar 

  • Wyer, R. S., Jr., & Carlston, D. E. (1979). Social cognition, inference, and attribution. Psychology Press.

  • Yuan, Z., Li, Y., & Lin, J. (2014). Linking challenge and hindrance stress to safety performance: The moderating effect of core self-evaluation. Personality and Individual Differences, 68, 154–159.

    Article  Google Scholar 

  • Zellars, K. L., Hochwarter, W. A., Perrewe, P. L., Hoffman, N., & Ford, E. W. (2004). Experiencing job burnout: The roles of positive and negative traits and states. Journal of Applied Social Psychology, 34, 887–911.

    Article  Google Scholar 

  • Zhang, Y., LePine, J. A., Buckman, B. B., & Wei, F. (2014). It’s not fair … Or is it? The role of justice and leadership in explaining work stressor-job performance relationships. Academy of Management Journal, 57, 675–697.

    Article  Google Scholar 

  • Zhou, Z. E., Yan, Y., Che, X. X., & Meier, L. L. (2015). Effect of workplace incivility on end-of-work negative affect: Examining individual and organizational moderators in a daily diary study. Journal of Occupational Health Psychology, 20, 117–130.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gargi Sawhney.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 15 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sawhney, G., Michel, J.S. Challenge and Hindrance Stressors and Work Outcomes: the Moderating Role of Day-Level Affect. J Bus Psychol 37, 389–405 (2022). https://doi.org/10.1007/s10869-021-09752-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10869-021-09752-5

Keywords

Navigation