Evidence map›Paper›PMID 42151719›Full record

ArticleJournal of occupational rehabilitation2026

Predictors of Mental Health-Related Sick Leave at Referral to Clinical Psychology: A Population-Based Study Using Electronic Health Records.

César González-Blanch, Sandra Martínez-Gómez, Saioa Pérez-García-Abad, Jose Ruiz-Gutiérrez, María Del Mar Miras-Aguilar, Carmen Ramos-Barrón, Emilio Pariente-Rodrigo, Lourdes Piñán-Setién, Noelia Otero-Cabanillas, María Isabel Priede

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Article in Journal of occupational rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

César González-BlanchMental Health Unit, University Hospital Marqués de Valdecilla-IDIVAL, Santander, Spain. cesar.gonzalezblanch@scsalud.es.ORCID http://orcid.org/0000-0002-3181-4731
Sandra Martínez-GómezPrimary Care, Cantabrian Healthcare Service, Santander, Spain.ORCID http://orcid.org/0000-0002-6393-2695
Saioa Pérez-García-AbadTudela Mental Health Center, Navarre Health Service-Osasunbidea, Pamplona, Spain.ORCID http://orcid.org/0009-0008-8410-2720
Jose Ruiz-GutiérrezMental Health Unit, University Hospital Infanta Leonor, Madrid, Spain.ORCID http://orcid.org/0000-0002-8143-7049
María Del Mar Miras-AguilarMental Health Unit, University Hospital Infanta Leonor, Madrid, Spain.ORCID http://orcid.org/0009-0001-5084-2877
Carmen Ramos-BarrónPrimary Care, Cantabrian Healthcare Service, Santander, Spain.
Emilio Pariente-RodrigoPrimary Care, Cantabrian Healthcare Service, Santander, Spain.ORCID http://orcid.org/0000-0003-0035-3298
Lourdes Piñán-SetiénPrimary Care, Cantabrian Healthcare Service, Santander, Spain.
Noelia Otero-CabanillasPrimary Care, Cantabrian Healthcare Service, Santander, Spain.
María Isabel PriedePrimary Care, Cantabrian Healthcare Service, Santander, Spain.

Funding

Health Research Institute Valdecilla (IDIVAL) PRIMVAL 22/02
6 · The paper itself

Abstract

purposeTo examine factors associated with sick leave status at referral to clinical psychology and its duration using electronic health records (EHRs).

methodsA population-based observational study was conducted with 2,765 patients referred from primary care to mental health units in a regional public healthcare system in Spain in 2021. Sociodemographic and clinical variables were analysed, and a subsample of 400 patients provided additional data on healthcare use and prior sick leave. Logistic regression and generalized linear models were applied.

resultsAt referral, 22.1% of patients were on sick leave (median = 181 d). In analyses based on the full sample, psychopharmacological treatment and being in a relationship were associated with higher odds, whereas female sex was associated with lower odds. In the subsample including prior history variables, prior sick leave emerged as the strongest predictor of both status and duration.

conclusionsRoutine clinical variables have limited predictive value, whereas prior sick leave episodes are a key and readily available indicator of risk for prolonged sick leave. Incorporating standardized clinical and work-related measures into EHRs may facilitate early identification of individuals at risk of prolonged sick leave and permanent work disability.

Indexed as

Common mental disordersElectronic health recordsPrimary careSick leaveWork disability

Identifiers

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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.