The Impact of Burn Size on Community Participation
Bibliographic record
Abstract
OBJECTIVE: To assess the association of burn size and community participation as measured by the LIBRE Profile. SUMMARY OF BACKGROUND DATA: Burn size is an established clinical predictor of survival after burn injury. It is often a factor in guiding decisions surrounding early medical interventions; however, literature is inconclusive on its relationship to quality of life outcomes. METHODS: This is a secondary data analysis of a cross-sectional survey of adult burn survivors. Self-reported data were collected between October 2014 and December 2015 from 601 burn survivors aged ≥18 years with ≥5% total body surface area (TBSA) or burns to critical areas. Sociodemographic characteristics were compared between participants with small burns (≤40% TBSA burned) and large burns (>40% TBSA burned). Ordinary least squares regression models examined associations between burn size and LIBRE Profile scale scores with adjustments for sex, current work status, burns to critical areas, and time since burn injury. RESULTS: The analytic sample comprised 562 participants with data available for burn size. 42% of respondents had large burns (>40% TBSA burned) and 58% reported smaller burns (TBSA ≤40%). In adjusted regression models, patients with large burns tended to score lower on the Social Activities and Work & Employment scales ( P < 0.05) and higher on the Family & Friends scale ( P < 0.05). Participants with burns >40% TBSA scored lower for several individual items in the Social Activities scale and one item in the Work & Employment scale ( P < 0.05). CONCLUSIONS: Increasing burn size was found to be negatively associated with selected items of Work & Employment and Social Activities, but positively associated with aspects of Family & Friend Relationships. Future longitudinal studies are necessary to assess and understand the long-term social impact of burn injuries on adult populations.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".