Evidence map›Paper›PMID 22270230›Full record

ArticleJournal of occupational rehabilitation2012

Part-time sick leave as a treatment method for individuals with musculoskeletal disorders.

Daniela Andrén, Mikael Svensson

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Journal of occupational rehabilitation, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
9.0field-weighted citation impact, top 2% 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

17 citing papers in PubMed, 49 citations in OpenAlex.

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  12. Long-term sick leave and the impact of a graded return-to-work program: evidence from Germany.The European journal of health economics : HEPAC : health economics in prevention and care · 2016
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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

2 authors at 1 institution in 1 country.

Daniela AndrénSwedish Business School, Örebro University, Örebro, Sweden. daniela.andren@oru.se
Mikael Svensson
Örebro University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThere is increasing evidence that staying active is an important part of a recovery process for individuals on sick leave due to musculoskeletal disorders (MSDs). It has been suggested that using part-time sick-leave rather than full-time sick leave will enhance the possibility of full recovery to the workforce, and several countries actively favor this policy. The aim of this paper is to examine if it is beneficial for individuals on sick leave due to MSDs to be on part-time sick leave compared to full-time sick leave.

methodsA sample of 1,170 employees from the RFV-LS (register) database of the Social Insurance Agency of Sweden is used. The effect of being on part-time sick leave compared to full-time sick leave is estimated for the probability of returning to work with full recovery of lost work capacity. A two-stage recursive bivariate probit model is used to deal with the endogeneity problem.

resultsThe results indicate that employees assigned to part-time sick leave do recover to full work capacity with a higher probability than those assigned to full-time sick leave. The average treatment effect of part-time sick leave is 25 percentage points.

conclusionsConsidering that part-time sick leave may also be less expensive than assigning individuals to full-time sick leave, this would imply efficiency improvements from assigning individuals, when possible, to part-time sick leave.

Indexed as

Outcome Assessment, Health CareSick LeaveWork Capacity EvaluationAdolescentAdultAgedEmploymentFemaleHumansLogistic ModelsMaleMiddle AgedMusculoskeletal DiseasesRecovery of FunctionRegistriesRehabilitation, Vocational

Identifiers

PMID22270230
OpenAlexW2079898261

What OpenQuestion holds

Textmetadata
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.