ArticlePloS one2026
Predictors of Post-Traumatic Stress Symptoms after musculoskeletal trauma.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPost-traumatic stress symptoms (PTSS) are common following musculoskeletal trauma and are associated with poorer recovery, disability, and reduced quality of life. Although psychosocial and injury-related factors have been linked to PTSS, limited research has examined longitudinal predictors or the relationship between injury severity and PTSS progression in people hospitalised for musculoskeletal trauma.
objectivesTo identify predictors of PTSS at three and six months following musculoskeletal trauma and hospitalisation, and to examine the relationship between injury severity and PTSS severity over time.
methodsThis secondary analysis of a prospective cohort study included 125 adults admitted to a UK major trauma centre with acute musculoskeletal injuries. PTSS were assessed using the Impact of Event Scale-Revised (IES-R) at baseline, three, and six months, with scores ≥22 indicating elevated PTSS. Candidate predictors included socio-demographic, clinical, and trauma-related variables. Multivariate logistic regression identified predictors at three and six months. Multicollinearity was assessed using variance inflation factors and principal component analysis. Injury severity (mild, moderate, major) was examined using Kruskal-Wallis and Mann-Whitney U tests. Model discrimination and calibration were evaluated using AUC and Hosmer-Lemeshow tests.
resultsAt baseline, 97.6% of participants met the PTSS threshold, decreasing to 26.4% at three months and 17.6% at six months. This high baseline prevalence likely reflects the early post-injury assessment period and the use of a sensitive screening threshold. At three months, road traffic accidents (OR 3.71, 95% CI 2.60-6.85) and car accidents (OR 2.20, 95% CI 1.68-3.15) significantly increased PTSS risk compared to falls. Higher baseline anxiety (OR 0.53, 95% CI 0.33-0.86) and kinesiophobia (OR 0.58, 95% CI 0.39-0.86) were associated with reduced PTSS odds. At six months, higher chronic pain-related disability independently predicted lower PTSS risk (OR 0.89, 95% CI 0.82-0.97). Injury severity differed significantly at six months (p = 0.022) but not at three months (p = 0.172). The six-month model demonstrated excellent discrimination (AUC = 0.91) and good calibration (p = 0.70).
conclusionsPTSS following musculoskeletal trauma are influenced by trauma mechanism, psychological factors, and injury severity over time, supporting early risk stratification and targeted psychological intervention.
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.