“In my before lifeâ€: Relationships, coping and post-traumatic growth in adolescent survivors of a traumatic brain injury
Bibliographic record
Abstract
OBJECTIVE: Explore the individual, adolescent phenomeno-logy of quality of life after traumatic brain injury. SUBJECTS/PATIENTS: Adolescent survivors of traumatic brain injury. METHODS: Qualitative interviews with 10 adolescents, mean age at assessment 17.09 years (SD 1.81). Mean time since injury 4.62 years (SD 2.89). Data were analysed using a primarily interpretative phenomenological analysis approach. RESULTS: Two major findings: (1) perceived quality of life was not automatically impacted by a traumatic brain injury, but when it was, the directionality of impact (positive, negative) varied depending on the life-domain; (2) changes in ability post-traumatic brain injury were attributed to the injury (more often cognitive and physical changes) or to a sense of normal maturation processes (72% and 28%, respectively). Attribution processing permeated themes of personal and social discrepancies, which also yielded themes of: altered family and relationships, roles, responsibilities, independence, coping and post-traumatic growth. All participants reported a happy life at the time of interview. CONCLUSION: The adolescents' appraisal of their identity from pre- to post-injury life was related to their current sense of well-being. Most notably was the sense of balance; participants addressed the negative and positive consequences of brain injury to qualify their sense of wellbeing.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".