Rehabilitation needs, preferences, barriers, and facilitators of individuals with sepsis: a qualitative study
Bibliographic record
Abstract
Purpose: To explore the rehabilitation needs, preferences, barriers, and facilitators of sepsis survivors. Methods: a caregiver of an individual with a past diagnosis of sepsis. We conducted semi-structured interviews on Zoom, guided by the COM-B Framework and transcribed interviews verbatim. Two reviewers conducted qualitative content analysis. Results: We included 22 participants. Participants identified the need for early and continued rehabilitation, including support for physical and cognitive health. They described barriers related to social isolation, finances, and lack of information on and accessibility to rehabilitation services. Participants reported that they preferred to participate in rehabilitation that included peer support, education for themselves and caregivers, and personalized services. Interview findings underscore the need to increase the accessibility of rehabilitation resources and the knowledge of sepsis survivors and their caregivers on the condition and the benefits of rehabilitation. Conclusion: We identified rehabilitation needs, preferences, barriers, and facilitators necessary to better support sepsis survivors in their recovery process. Future research should focus on tailoring strategies to improve the opportunity for rehabilitation for sepsis survivors and increasing the knowledge of sepsis in survivors and their caregivers to maximize participation in rehabilitation for individuals with sepsis.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".