Identifying Factors Associated With Perceived Success in the Transition From Hospital to Home After Brain Injury
Bibliographic record
Abstract
OBJECTIVE: : To identify the factors associated with perceived success of the transition from hospital to home after traumatic brain injury (TBI). DESIGN: : Prospective longitudinal cohort design with data collection at discharge and 1, 3, and 6 months postdischarge. PARTICIPANTS: : A total of 127 individuals with TBI discharged to the community and 83 significant others. MAIN MEASURES: : An analog scale (0-100) of perceived success of the transition from hospital to home rated by individuals and significant others; Sentinel Events Questionnaire; EuroQol Group Quality-of-Life measure visual analog scale; Sydney Psychosocial Reintegration Scale; Mayo-Portland Adaptability Inventory-4; short form of the Depression, Anxiety, Stress Scales; Craig Hospital Inventory of Environmental Factors; and Caregiver Strain Index. RESULTS: : Greater perceived success of transition for individuals with a TBI was associated with higher levels of health-related quality of life, level of community integration, and more severe injury. Among survivors, sentinel events such as returning to work and independent community access and changing living situation were associated with greater perceived success; financial strain and difficulty accessing therapy services were associated with less success. Among significant others, lower ratings of transition success were associated with higher significant other stress levels as well as lower levels of community integration and changes in the living situation of the individual with TBI. CONCLUSION: : A combination of sentinel events and personal and environmental factors influences the perceptions of individuals and their families regarding the success of the transition from hospital to home.
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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 | 0.001 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".