Evidence map›Paper›PMID 32107267›Full record

ArticleBMJ open2020

Identifying return to work trajectories among employees on sick leave due to mental health problems using latent class transition analysis.

Maitta Spronken, Evelien P M Brouwers, Jeroen K Vermunt, Iris Arends, Wido G M Oerlemans, Jac J L van der Klink, Margot C W Joosen

Abstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Observational
  12. Article
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

7 authors.

Maitta SpronkenTranzo Scientific Center for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands maittaspronken@gmail.com.ORCID 0000-0002-4390-9586
Evelien P M BrouwersTranzo Scientific Center for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.
Jeroen K VermuntDepartment of Methodology and Statistics, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.
Iris ArendsDepartment of Health Sciences, Community and Occupational Medicine, University Medical Center Groningen, Groningen, The Netherlands.
Wido G M OerlemansResearch and Business Development, HumanTotalCare, Utrecht, The Netherlands.
Jac J L van der KlinkTranzo Scientific Center for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.
Margot C W JoosenTranzo Scientific Center for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo develop effective return to work (RTW) interventions for employees on sick leave due to mental health problems (MHPs), a better understanding of individual variation in the RTW process is needed. We investigated which RTW trajectories can be identified among employees with MHPs in terms of RTW duration and relapse occurrence during the RTW process. Additionally, we examined how different RTW trajectories can be described in terms of personal and work characteristics.

methodsLongitudinal sickness absence registry data were collected retrospectively from the largest Dutch occupational health service. Quantitative RTW information as well as personal and work characteristics were extracted. In total, 9517 employees with a sickness absence due to MHPs were included in the analyses (62 938 data points; RTW durations from 29 to 730 days).

resultsA latent class transition analysis revealed five distinct RTW trajectories, namely (1) fast RTW with little chance of relapse, (2) slow RTW with little chance of relapse, (3) fast RTW with considerable chance of relapse, (4) slow RTW with considerable chance of relapse and (5) very fast RTW with very small chance of relapse. Differences between employees in the slower and faster trajectories were observed regarding gender, age, type of MHP, organisation sector and organisation size but not regarding part-time work.

conclusionsRTW trajectories among employees with MHPs showed large individual variability and differed on personal and work characteristics. Knowledge on different RTW trajectories and their characteristics contributes to the development of personalised RTW treatments, tailored to specific individuals and organisations.

Indexed as

Mental DisordersMental HealthReturn to WorkWorkplaceAdultFemaleHumansIndividualityMaleNetherlandsOccupational Health ServicesPsychology, IndustrialRecurrenceSick Leavelatent class transition analysismental health problemsreturn to worksick leavetrajectories

Identifiers

PMID32107267
PMCPMC7202700

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.