Critical Issues in Interviewing People with Traumatic Brain Injury
Bibliographic record
Abstract
People with cognitive impairments often cannot effectively recall and articulate experiences, feelings, and perceptions. Therefore, interviewing them can be fraught with pragmatic and methodological difficulties. Given this situation, the authors' experience in a study on the allocation of rehabilitative services to survivors of traumatic brain injury is discussed. Participants had physiological impairments affecting their ability to focus on interview questions. The authors discuss the unique challenges, including participants' recall of events, intolerance to stimuli, and image management and offer strategies for mitigating these concerns. The traditional view that reality is captured only in the subjective accounts of articulate people who can remember events in a precise and reflective manner is challenged.
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 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 | 0.301 | 0.399 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.039 | 0.061 |
| Scholarly communication | 0.027 | 0.020 |
| Open science | 0.009 | 0.019 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".