Background and aims: Many sustaining traumatic brain injury (TBI) suffer ongoing post-concussion symptoms (PCS). The Rivermead Post-Concussion Symptoms Questionnaire (RPQ) is widely used, although there is disagreement about its structure. This study compared the fit of published RPQ structures with a four-factor structure derived from a large adult sample with TBI in Tasmania.Method: 661 adults with TBI completed the RPQ at approximately one month post injury. Exploratory factor analysis (EFA), using the first half of the sample (n = 330), suggested a four-factor solution. This was compared with models reported in the literature with the second half of the sample (n = 331), using structural equation modelling. Trajectory of recovery across these factors was examined within subsamples at 1, 3, 6 and 12 months following TBI.Results: Inter-correlations between items were strongest for somatic, cognitive and emotional functioning items and the EFA identified a four-factor model. Fit was examined utilising bootstrapping for model comparison. The data at 1 month following TBI best fitted the four-factor model (CFI = .95, RMSEA = .060 (.049–.071) and factors had adequate internal consistency (r = .61–.89). This model appeared a good fit and clinically useful across time points to 12 months post injury.Conclusions: Data best fitted a four-factor model, identified using a rigorous statistical approach. Clinicians and clinical researchers may use this preferred model to provide more specific measurement of the severity of PCS. Future research could attempt replication within international samples.
P rimary Objectives: To examine the HADS structure in TBI, using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), and investigate the effects of TBI severity, Gender, and Age on factor scores. Methods and Procedures: HADS data from 186 TBI patients in a population study in Tasmania were subjected to EFA. HADS data from a second sample of 185 TBI participants in the same study underwent CFA. One-month follow-up data were used, allowing inclusion of severe TBI patients while still being early post-injury. Factor loadings were used to investigate the effects of demographic and clinical variables at 2 weeks post-injury. Results: While EFA suggested 2-factor (anxiety, depression) and 3-factor (anxiety, psychomotor, depression) structures provided adequate descriptions, CFA strongly supported the 3-factor model. Using this model, significant effects of TBI severity were noted on Psychomotor and Depression scores at 2 weeks post-injury. Males reported significantly fewer symptoms on all 3 factors, as did younger participants. Conclusions: CFA indicates that a 3-factor model provides the best fit for HADS data in TBI. One factor, Psychomotor, has been relatively neglected in the literature, and the current findings suggest its assessment and rehabilitation should receive more attention.
Overall LTFU increased from 22% at 1 month post-injury to 81% at 3-year follow-up. Most participants (52%) were employed at the time of their TBI, with 39% of TBIs being motor vehicle related. Lower LTFU at 2 and 3 years post-TBI was significantly associated with severe TBI. Within the mTBI sub-group significantly higher LTFU at 1 and 6 months after injury and at 2 and 3 years post-injury was associated with TBI from assault. Those sustaining mTBI from a fall or sport-related injury showed significantly lower LTFU at the 6-month, 12-month and 2-year follow-up points. The highest LTFU was noted for unemployed participants, with retired participants showing the lowest rate.
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