PLoS ONE (Jan 2019)

Quickscan assesses risk factors of long-term sickness absence: A cross-sectional (factorial) construct validation study.

  • Kaat Goorts,
  • Sofie Vandenbroeck,
  • Tinne Vander Elst,
  • Dorina Rusu,
  • Marc Du Bois,
  • Saskia Decuman,
  • Lode Godderis

DOI
https://doi.org/10.1371/journal.pone.0210359
Journal volume & issue
Vol. 14, no. 1
p. e0210359

Abstract

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ObjectivesThe number of sick-listed employees has increased dramatically worldwide. Therefore, many countries aim to stimulate early and sustainable return to work opportunities to obtain better health outcomes and lower costs for disability pensions. To effectively orientate resources to patients with a high risk of not resuming work spontaneously, it is necessary to screen patients early in their sickness absence process. In this study, we validate "Quickscan", a new instrument to assess return-to-work needs and to predict risks of long-term sick leave.MethodsAs part of the Quickscan validation process, we tested and compared the reliability and construct validity of the questionnaire in two different populations. First, we conducted a cross-sectional study in which the screening instrument was sent to sick-listed individuals in healthcare insurance. In a second cross-sectional study, sick-listed workers who consulted the occupational health physician for return-to-work assessment were asked to fill out the questionnaire. We compared both samples for descriptive statistics: frequencies, means and standard deviations. Reliability of the scales was calculated using Cronbach's alpha. Confirmatory factor analysis was performed to evaluate the construct (factorial) validity of the studied scales using software package AMOS 24.ResultsThe screening tool was shown to be an instrument with reliable scales (except for the perfectionism and health perception patient scale) in both populations. The construct validity was satisfactory: we found that the hypothesized measurement models with the theoretical factors fitted the data well in both populations. In the first sample, the model improved for scales concerning stressful life events and showed worse fit for person-related factors. Work-related factors and functioning factors both showed similar fit indices across samples. We found small differences in descriptive statistics, which we could explain by the differences in characteristics of both populations.ConclusionsWe can conclude that the instrument has considerable potential to function as a screening tool for disability management and follow-up of sick-leave, provided that some adaptations and validation tests are executed.