Evidence map›Paper›PMID 37815247›Full record

ArticleScandinavian journal of work, environment & health2023

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

Solja T Nyberg, Marko Elovainio, Jaana Pentti, Philipp Frank, Jenni Ervasti, Mikko Härmä, Aki Koskinen, Laura Peutere, Annina Ropponen, Jussi Vahtera and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scandinavian journal of work, environment & health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. Towards the year 2049: The next 25 years of occupational health and safety research.Scandinavian journal of work, environment & health · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 5 institutions in 3 countries.

Solja T NybergUniversity of Helsinki, Clinicum, Faculty of Medicine, Tukholmankatu 8B, FI-00014 Helsingin yliopisto, Finland. solja.nyberg@helsinki.fi.
Marko Elovainio
Jaana Pentti
Philipp Frank
Jenni Ervasti
Mikko Härmä
Aki Koskinen
Laura Peutere
Annina Ropponen
Jussi Vahtera
Marianna Virtanen
Jaakko Airaksinen
G David Batty
Mika Kivimäki
Finnish Institute of Occupational Health · FIUniversity of Helsinki · FIFinnish Institute for Health and Welfare · FIKarolinska Institutet · SEUniversity College London · GB

Funding

Healthy transitions from mid-life to early older age: biomedical follow-up of 1958 Birth Cohort Study members at age 60R56AG052519 · NIA · UNIVERSITY COLLEGE LONDON · PI BATTY, DAVID, GOODMAN, ALISSA · 2016 to 2016
$500k
Medical Research Council MR/R024227/1NIA NIH HHS R56 AG052519
6 · The paper itself

Abstract

objectiveThis study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers.

methodsThis 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.

resultsThe 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.

conclusionsThe 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.

Indexed as

Personnel, HospitalWorkplaceAbsenteeismAdultFemaleHospitalsHumansMaleProspective StudiesSick LeaveSurveys and Questionnaires

Identifiers

PMID37815247
PMCPMC10882516
OpenAlexW4387473065

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.