UCL Discovery Stage
UCL home » Library Services » Electronic resources » UCL Discovery Stage

Predicting long-term sickness absence with employee questionnaires and administrative records: a prospective cohort study of hospital employees

Nyberg, ST; Elovainio, M; Pentti, J; Frank, P; Ervasti, J; Härmä, M; Koskinen, A; ... Kivimäki, M; + view all (2023) Predicting long-term sickness absence with employee questionnaires and administrative records: a prospective cohort study of hospital employees. Scandinavian Journal of Work, Environment and Health , 49 (8) pp. 610-620. 10.5271/sjweh.4124. Green open access

[thumbnail of 610_620_Nyberg.pdf]
Preview
PDF
610_620_Nyberg.pdf - Published Version

Download (892kB) | Preview

Abstract

Objective: This study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers. Methods This prospective cohort study comprised 3197 shift-working hospital employees (mean age 44.5 years, 88.0% women) who responded to a brief 8-item questionnaire on work disability risk factors and were linked to 28 variables on their working hour and workplace characteristics obtained from administrative registries at study baseline. The primary outcome was the first sickness absence lasting ≥90 days during a 4-year follow-up. Results The C-index of 0.73 [95% confidence interval (CI) 0.70–0.77] for a questionnaire-only based prediction model, 0.71 (95% CI 0.67–0.75) for an administrative records-only model, and 0.79 (95% CI 0.76–0.82) for a model combining variables from both data sources indicated good discriminatory ability. For a 5%-estimated risk as a threshold for positive test results, the detection rates were 76%, 74%, and 75% and the false positive rates were 40%, 45% and 34% for the three models. For a 20%-risk threshold, the corresponding detection rates were 14%, 8%, and 27% and the false positive rates were 2%, 2%, and 4%. To detect one true positive case with these models, the number of false positive cases accompanied varied between 7 and 10 using the 5%-estimated risk, and between 2 and 3 using the 20%-estimated risk cut-off. The pattern of results was similar using 30-day sickness absence as the outcome. Conclusions The best predictive performance was reached with a model including both questionnaire responses and administrative records. Prediction was almost as accurate with models using only variables from one of these data sources. Further research is needed to examine the generalizability of these findings.

Type: Article
Title: Predicting long-term sickness absence with employee questionnaires and administrative records: a prospective cohort study of hospital employees
Location: Finland
Open access status: An open access version is available from UCL Discovery
DOI: 10.5271/sjweh.4124
Publisher version: https://doi.org/10.5271/sjweh.4124
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: Humans, Female, Adult, Male, Prospective Studies, Surveys and Questionnaires, Personnel, Hospital, Workplace, Sick Leave, Absenteeism, Hospitals
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry > Mental Health of Older People
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10181796
Downloads since deposit
380Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item