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Demand–Resource Profiles and Job Satisfaction in the Healthcare Sector: A Person-Centered Examination Using Bayesian Informative Hypothesis Testing

Author

Listed:
  • Ivan Marzocchi

    (Department of Psychology, Sapienza—University of Rome, 00185 Rome, Italy)

  • Valerio Ghezzi

    (Department of Psychology, Sapienza—University of Rome, 00185 Rome, Italy)

  • Cristina Di Tecco

    (Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian Workers’ Compensation Authority (INAIL), Monte Porzio Catone, 00078 Rome, Italy)

  • Matteo Ronchetti

    (Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian Workers’ Compensation Authority (INAIL), Monte Porzio Catone, 00078 Rome, Italy)

  • Valeria Ciampa

    (Department of Psychology, Sapienza—University of Rome, 00185 Rome, Italy)

  • Ilaria Olivo

    (Department of Psychology, Sapienza—University of Rome, 00185 Rome, Italy)

  • Claudio Barbaranelli

    (Department of Psychology, Sapienza—University of Rome, 00185 Rome, Italy)

Abstract

Work characteristics may independently and jointly affect well-being, so that whether job demands deplete or energize employees depends on the resources available in the job. However, contradictory results on their joint effects have emerged so far in the literature. We argue that these inconsistencies can be partially explained by two arguments in the contemporary literature in the field. First, most studies in the job design domain are based on classic variable-centered methodologies which, although informative, are not well suited to investigate complex patterns of interactions among multiple variables. Second, these studies have mainly focused on generic work characteristics (e.g., workload, control, support), and are lacking in occupational specificity. Thus, to overcome these limitations, in the current research we include generic and occupation-specific work characteristics and adopt a person-centered approach to (a) identify different patterns of interactions of job demands and resources in a sample of healthcare employees, and (b) determine the degree to which these patterns are associated with employee well-being. We involved a sample of 1513 Italian healthcare providers and collected data on key job demands (workload, emotional dissonance, patient demands and physical demands) and resources (control, management support and peers’ support). We focused on job satisfaction as a broad indicator of well-being. Latent profile analysis revealed four profiles of job demands and resources: high strain–isolated, resourceless, resourceful and active job on the ward. The results of Bayesian informative hypothesis testing showed the highest support for the hypothesis stating that healthcare employees belonging to the active job on the ward profile (medium–high demands, high resources) were the most satisfied. Conversely, employees belonging to the high strain–isolated profile (high demands, low resources) and the resourceless profile (medium–low demands, low resources) were the least satisfied. Overall, our study confirms the key role played by job resources in determining well-being in high-risk sectors, demonstrating that job satisfaction can develop both in challenging and less demanding situations. On a practical level, mapping the complexity of the healthcare psychosocial work environment has important implications, allowing for a better assessment process of employee well-being and helping to identify the most effective and fitting interventions.

Suggested Citation

  • Ivan Marzocchi & Valerio Ghezzi & Cristina Di Tecco & Matteo Ronchetti & Valeria Ciampa & Ilaria Olivo & Claudio Barbaranelli, 2023. "Demand–Resource Profiles and Job Satisfaction in the Healthcare Sector: A Person-Centered Examination Using Bayesian Informative Hypothesis Testing," IJERPH, MDPI, vol. 20(2), pages 1-21, January.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:967-:d:1025809
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    References listed on IDEAS

    as
    1. Paula Franklin & Anna Gkiouleka, 2021. "A Scoping Review of Psychosocial Risks to Health Workers during the Covid-19 Pandemic," IJERPH, MDPI, vol. 18(5), pages 1-20, March.
    2. Igor Portoghese & Maura Galletta & Michael P. Leiter & Gabriele Finco & Ernesto d’Aloja & Marcello Campagna, 2020. "Job Demand-Control-Support Latent Profiles and Their Relationships with Interpersonal Stressors, Job Burnout, and Intrinsic Work Motivation," IJERPH, MDPI, vol. 17(24), pages 1-21, December.
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    4. Moeller, Julia & Ivcevic, Zorana & White, Arielle E. & Menges, Jochen & Brackett, Marc A., 2018. "Highly Engaged but Burned Out: Intra-Individual Profiles in the US Workforce," OSF Preprints h6qnf, Center for Open Science.
    5. Franck Biétry & John P. J.P Meyer & Jordane Creusier & Alexandre J. S. Morin, 2016. "Multiple-Group Analysis of Similarity in Latent Profile Solutions," Post-Print hal-01884085, HAL.
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