Testing job typologies and identifying at-risk subpopulations using factor mixture models

J Occup Health Psychol. 2017 Oct;22(4):503-517. doi: 10.1037/ocp0000038. Epub 2016 Apr 25.

Abstract

Research in occupational health psychology has tended to focus on the effects of single job characteristics or various job characteristics combined into 1 factor. However, such a variable-centered approach does not account for the clustering of job attributes among groups of employees. We addressed this issue by using a person-centered approach to (a) investigate the occurrence of different empirical constellations of perceived job stressors and resources and (b) validate the meaningfulness of profiles by analyzing their association with employee well-being and performance. We applied factor mixture modeling to identify profiles in 4 large samples consisting of employees in Switzerland (Studies 1 and 2) and the United States (Studies 3 and 4). We identified 2 profiles that spanned the 4 samples, with 1 reflecting a combination of relatively low stressors and high resources (P1) and the other relatively high stressors and low resources (P3). The profiles differed mainly in terms of their organizational and social aspects. Employees in P1 reported significantly higher mean levels of job satisfaction, performance, and general health, and lower means in exhaustion compared with P3. Additional analyses showed differential relationships between job attributes and outcomes depending on profile membership. These findings may benefit organizational interventions as they show that perceived work stressors and resources more strongly influence satisfaction and well-being in particular profiles. (PsycINFO Database Record

Publication types

  • Comparative Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Employment / psychology
  • Fatigue / psychology
  • Female
  • Health Status
  • Humans
  • Job Satisfaction*
  • Male
  • Middle Aged
  • Occupational Stress / psychology*
  • Personal Satisfaction*
  • Principal Component Analysis
  • Risk Factors
  • Social Support*
  • Surveys and Questionnaires
  • Work / psychology
  • Work Performance*
  • Young Adult