Evidence map›Paper›PMID 40408509›Full record

ArticlePloS one2025

Determinants of general health perception among individuals with chronic low back pain overtime: structural equation modeling.

Owis Eilayyan, Line Enjalbert-Auneau, Sara Ahmed

Abstract read
In one paragraph

Article in PloS one, 2025. 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. 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

3 authors.

Owis EilayyanPhysical Therapy Department, Faculty of Allied Medical Sciences, Al-Ahliyya Amman University, Amman, Jordan.ORCID 0000-0001-6191-8745
Line Enjalbert-AuneauSchool of Physical & Occupational Therapy, McGill University, Montreal, Quebec, Canada.
Sara AhmedSchool of Physical & Occupational Therapy, McGill University, Montreal, Quebec, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLow back pain (LBP) is a public health problem. General health perception is the best predictor of healthcare utilization and mortality. Identifying predictors of health perception helps understand how people with LBP live, implement the appropriate treatment, and improve the quality of care.

objectiveThis study aimed to estimate the relationships between pain intensity, psychological distress, self-efficacy, functional ability, and healthcare utilization among individuals with chronic LBP over a period of six-months and to estimate the impact of these relationships on general health perception.

methodsThis is a secondary analysis of data from a longitudinal study that assessed the health outcomes of individuals with chronic LBP. Structural equation modeling (SEM), based on health frameworks, was used to estimate the predictors of health perception among people with LBP at baseline and 6-months.

results314 individuals with LBP were included in the analysis. The final SEM model had good fit statistics and explained 48% of health perception variance at 6-months. The model showed that health perception was significantly affected by pain intensity (β = 0.29, β = 0.21), psychological distress (β = 0.51, β = 0.44) and self-efficacy (β = 0.4, β = 0.36) cross-sectionally and overtime, respectively.

conclusionDifferent health outcomes could affect the health perception among people with low back pain. This requires holistic approaches to treatment, involving self-management and cognitive behavioral therapy, as well as improved self-efficacy to improve their health.

Indexed as

Chronic PainLow Back PainAdultFemaleHumansLatent Class AnalysisLongitudinal StudiesMaleMiddle AgedPain MeasurementPatient Acceptance of Health CarePsychological DistressSelf Efficacy

Identifiers

PMID40408509
PMCPMC12101730

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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.