321 Perceived Value of Knowledge Translation Intervention Designed to Facilitate Burn Survivors’ Work Reintegration
Bibliographic record
Abstract
Returning to work can be a substantial challenge for burn survivors. Approximately 28% never return to any form of employment, resulting in lower health-related quality of life. In other conditions, open communication has been identified as a facilitator for return to work (RTW). A knowledge translation (KT) intervention in the form of an educational video was developed for adult burn survivors to facilitate their RTW and promote communication with co-workers and employers. Following its implementation, the impact on the RTW process needed to be evaluated, thus a mixed methods, cross-sectional study was performed. Burn survivors included in the KT intervention were recruited and compared to a control group (CG). The CG included burn survivors who were admitted prior to the development of the educational video or who did not have an opportunity to review the video due to the timing of their transfer to another facility or rapid discharge. The CG were selectively invited to participate so that the two groups’ mean age, gender and percent total body surface area burned were similar. Semi-structured interviews were conducted to gather information about their RTW process and outcomes. Qualitative data was analyzed through thematic analysis and quantitative data was summarized and compared using Mann-Whitney tests. Overall, both groups were satisfied with their RTW process. Participants from the CG identified more barriers related to support received, particularly at work. More participants from the CG also indicated psychological symptoms and social challenges such as post-traumatic stress disorder, self-consciousness and discomfort with questions as a barrier to RTW. Many participants from the KT group indicated that the video gave them tools to explain and provide others with a better understanding of their lived experience. It is possible that the video facilitated more open communication by empowering burn survivors to explain their situation on their own, thus reducing the prevalence of social and psychological barriers among the KT group by allowing them to self-advocate for more support. The video should continue to be used, however, it should be expanded to provide additional information about RTW facilitators such as progressive RTW, flexible schedules, and task modifications or accommodations.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".