Alexithymia Prevalence, Characterization, and Associations With Emotional Functioning and Life Satisfaction: A Traumatic Brain Injury Model System Study
Bibliographic record
Abstract
OBJECTIVES: Alexithymia an emotional processing deficit that interferes with a person's ability to recognize, express, and differentiate emotional states. Study objectives were to (1) determine rates of elevated alexithymia among people with moderate-to-severe traumatic brain injury (TBI) 1-year post-injury, (2) identify demographic and injury-related variables associated with high versus low-average levels of alexithymia, and (3) examine associations among alexithymia with other aspects of emotional functioning and life satisfaction. SETTING: Data were collected during follow-up interviews across four TBI Model System (TBIMS) centers. PARTICIPANTS: The sample consisted of 196 participants with moderate-to-severe TBI enrolled in the TBIMS. They were predominately male (77%), White (69%), and had no history of pre-injury mental health treatment (66.3%). DESIGN: Cross-sectional survey data were obtained at study enrollment and 1-year post-injury. MAIN MEASURES: Toronto Alexithymia Scale-20 (TAS-20) as well as measures of anger, aggression, hostility, emotional dysregulation, post-traumatic stress, anxiety, depression, resilience and life satisfaction. Sociodemographic information, behavioral health history and injury-related variables were also included. RESULTS: High levels of alexithymia (TAS-20 score > 1.5 standard deviation above the normative mean) were observed for 14.3%. Compared to individuals with low/average levels of alexithymia, the high alexithymia group tended to have lower levels of education. At 1-year follow-up, high TAS-20 scores were strongly associated with emotional dysregulation and post-traumatic stress; moderately associated with anger, hostility, depression, anxiety, lower resilience and lower satisfaction with life; and weakly associated with aggression. CONCLUSION: These findings provide further evidence that alexithymia is associated with poor emotional functioning and life satisfaction after TBI. Longitudinal studies are needed to determine if alexithymia is a risk factor that precipitates and predicts worse emotional outcomes in the TBI population. This line of work is important for informing treatment targets that could prevent or reduce of psychological distress after TBI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".