Surgical Recovery Through the Lens of Patients with Colorectal Disease: A Qualitative Study in an Enhanced Recovery after Surgery Setting
Bibliographic record
Abstract
BACKGROUND: As perioperative care shifts to a more patient-centered model, understanding needs and experiences of patients is vital. Gaining such insight can enhance the alignment of care with patient priorities, encouraging adherence to recovery-oriented interventions. We aimed to explore patient-defined recovery and the elements that modify the recovery process for patients with colorectal disease under enhanced recovery after surgery (ERAS) care. STUDY DESIGN: A qualitative study was conducted at an ERAS-participating hospital in Alberta, Canada, between April 2018 and June 2019. A co-design focus group set the research direction, and semistructured interviews were conducted postoperatively in-hospital or within 3 months postdischarge. Diverse patient ages and colorectal conditions were targeted through purposive sampling. Interviews were transcribed verbatim and analyzed through manifest and latent content analysis. RESULTS: Twenty patients with mean age 62 (SD 13) years and 45% with cancer (17 interview, 2 focus group + interview, and 1 focus group only) were enrolled. Recovery was defined by patients as the return to normal routines and four themes were identified. First, phases of recovery: recovery was described as multidimensional phases distinctively as early, late or long-term, and the endpoint. Second, recovery facilitators: recovery was supported through positive mindsets, conscious recovery, and taking an active role. Third, recovery barriers: recovery was hindered by negative mindsets and treatment side effects. Finally, recovery catalysts: communication, autonomy, and expectations facilitated active or passive recovery. CONCLUSIONS: Our patient-oriented recovery model may contribute a new dimension to the ERAS framework by capturing patients' recovery experiences. Further research is encouraged to explore its value in enhancing patient-centered care within ERAS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".