Evidence map›Paper›PMID 42554106›Full record

ArticlePain research & management2026

Prevalence and Ergonomic Risk Factors for Musculoskeletal Pain Among Clinical Nurses in Türkiye: A Cross-Sectional Study.

Habip Balsak, Askeri Türken

Abstract read
In one paragraph

Article in Pain research & management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Habip BalsakDepartment of Midwifery, Faculty of Health Sciences, Batman University, Batman, Türkiye, batman.edu.tr.ORCID https://orcid.org/0000-0002-2074-6884
Askeri TürkenDepartment of Physical Medicine and Rehabilitation, Gazi Yaşargil Training and Research Hospital, University of Health Sciences, Diyarbakır, Türkiye, akdeniz.edu.tr.ORCID https://orcid.org/0000-0003-0638-8918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMusculoskeletal pain (MSP) is among the most common occupational health problems for nurses. The purpose of this study was to evaluate the prevalence and severity of work-related MSP in clinical nurses.

methodsThis cross-sectional and descriptive study was conducted with individuals who had been working as clinical nurses for at least 6 months. The study included 312 clinical nurses who were directly involved in patient care and met the eligibility criteria. Clinical nurses were assessed with the Ergonomic Risks Questionnaire (Ergo-Nurse), and work-related MSP was assessed with the Cornell Musculoskeletal Disorder Questionnaire (CMDQ). Spearman correlation, independent samples t-test, and hierarchical regression analysis were used to determine the relevant factors.

resultsWork-related MSP is a major health problem in clinical nurses, with MSP severity ranging from low lumbar > back > neck. Hierarchical regression analysis showed that biomechanical factors were the most important ergonomic factor associated with work-related MSP in clinical nurses (R

conclusionsBiomechanical ergonomic risks and female sex were the main factors associated with work-related MSP among clinical nurses. These findings highlight the need for targeted ergonomic interventions, safe patient-handling practices, workload regulation, and institutional strategies to reduce musculoskeletal strain in clinical nursing settings.

Indexed as

ErgonomicsMusculoskeletal PainNursesOccupational DiseasesAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsSurveys and QuestionnairesWorking ConditionsYoung Adultclinical nurseergonomicmusculoskeletal painoccupational healthworkplace

Identifiers

PMID42554106
PMCPMC13439509

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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.