ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2026
Using confirmatory factor analysis to identify symptom clusters in individuals with acquired disabilities.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Profiles of Quality of Life Outcomes Observed in Rehabilitation Patients Using Latent Profile Analysis.Archives of physical medicine and rehabilitation · 2026Article
- Examining the factor structure of health-related quality of life in spinal cord injury using confirmatory factor analysis and multidimensional scaling.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
purposeAcquired disabilities, such as spinal cord injury, traumatic brain injury, limb loss (or other major limb injury/illness), or stroke, are typically accompanied by an array of physical and emotional symptoms and social challenges that interfere with recovery and affect quality of life (QOL). Despite advances in personalized medicine, interrelationships between symptoms remain unclear, and clinicians often treat individual symptoms in isolation. The objective of this study was to identify clusters of symptoms that occur across sudden-onset disability populations, with a long-term goal of identifying targets for clinical intervention.
methodsParticipants were 755 adults who sustained a spinal cord injury, traumatic brain injury, stroke, or sudden-onset limb-threatening injury/illness. Participants completed a battery of physical, emotional, and social patient reported outcomes measures and performance-based cognitive tests at baseline and after 14–18 months. Confirmatory factor analysis (CFA) of 26 indicator variables was used to reduce dimensions and identify clusters of symptoms.
resultsCFA results provide support for 10 factors: Cognition, Economic QOL, Negative Affect, Positive Affect, Psychological Adjustment, Physical Function, Independence, Sleep Impairment/Fatigue, Pain, and Social Health. Global model fit was acceptable: χ2 (255) = 875.0, RMSEA = 0.059, CFI = 0.948. The three emotional health clusters were highly correlated. The 10 factors demonstrated stability over time.
conclusionThese results can inform the development of composite scores and/or symptom indices to identify and compare broad areas of functioning and provide a method to detect specific areas of clinical concern. This improved understanding of symptom interrelationships may facilitate individualized care based on specific patient characteristics and, ultimately, lead to improved clinical outcomes for individuals with acquired disabilities.
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.