ArticleSpine2016
Structural Equation Model of Disability in Low Back Pain.
Article in Spine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Re-Examining the Dimensionality of a Disability Assessment Tool Using Exploratory Structural Equation Modeling (ESEM): A Preliminary Study in Low Back Pain.Journal of clinical medicine · 2025Article
- Study on the Associations of Individual and Work-Related Factors with Low Back Pain among Manufacturing Workers Based on Logistic Regression and Structural Equation Model.International journal of environmental research and public health · 2021Article
- Article
- Model Simulations Challenge Reductionist Research Approaches to Studying Chronic Low Back Pain.The Journal of orthopaedic and sports physical therapy · 2019Article
- Postural Responses to a Suddenly Released Pulling Force in Older Adults with Chronic Low Back Pain: An Experimental Study.PloS one · 2016Article
- Functional disability in patients with low back pain: the mediator role of suffering and beliefs about pain control in patients receiving physical and chiropractic treatment.Brazilian journal of physical therapyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
STUDY
designThe effects of participant characteristics along with descriptions of pain and psychological involvement, such as fear avoidance, were assessed using structural equation modeling (SEM) to identify relationships between these factors and disability as a result of low back pain (LBP).
objectiveThe aim of this study was to evaluate the relationship between factors related to pain description, participants' characteristics, psychological involvement, and disability through SEM. SUMMARY OF BACKGROUND DATA: LBP is a complex multifactorial condition that can lead to disability. Understanding which factors contribute to disability and how those factors interact is important for predicting and minimizing disability in patients with LBP.
methodsWe analyzed data from 156 participants (63% female) with LBP. A stepwise SEM was built with patient characteristics, pain intensity, depression, anxiety, and fear avoidance to predict disability in LBP.
resultsParticipants were 23-84 years (49.7 ± 15.1 yrs) of age and experienced 0.03 to 300 months duration (25.5 ± 36.4 months) of current LBP. The final model explained 62% of the variance in disability and included female gender, full-time employment, depression, and fear avoidance beliefs as significant predictors. Full-time employment was the only significant predictor that reduced disability; all other significant predictors increased disability in the model.
conclusionUnderstanding the relationship between these predictors and disability provides a foundation for predicting and managing disability for individual patients who suffer from LBP. LEVEL OF EVIDENCE: 3.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.