Body Image and Emotional Status in Patients with Acquired Brain Injury
Bibliographic record
Abstract
Emotional experiences can lead to a real or distorted self-representation. After brain damage, altered self-perception of one's own body image is frequent. This study evaluates the relationship of mood disorders and lesion sites on body image in a cohort of ABI patients. A total of 46 patients (26 men, 20 women) without severe physical impairments were found eligible for this study. Patients underwent Beck's Depression Inventory and the Hamilton Rating Scale for Anxiety to assess mood disorders, whereas the Body Image Scale and Human Figure Drawing were used to evaluate body dissatisfaction and implicit body image. The Montreal Cognitive Assessment was used to assess patients' cognitive condition. We found a moderate correlation between depression and body image (r = 0.48), as well as between anxiety and body image (r = 0.52), and the regression model also reported the right lesion site as a predictive variable for body image score. In addition, the regression model built by Human Figure Drawing scores showed anxiety, cognitive functioning, and a marital status of single to be significant predictors. The study confirmed that participants with acquired brain injury have deficits in body representation associated with mood disorders, regardless of the side of the lesions. A neuropsychological intervention could be useful for these patients to improve their cognitive performance and learn to manage emotional dysfunction in order to increase their self-perception of body image and improve their quality of life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".