Patient journey following lumbar spinal fusion surgery (FuJourn): A multicentre exploration of the immediate post-operative period using qualitative patient diaries
Bibliographic record
Abstract
The aim of this study was to capture and understand the immediate recovery journey of patients following lumbar spinal fusion surgery and explore the interacting constructs that shape their journey. A qualitative study using Interpretive Phenomenological Analysis (IPA) approach. A purposive sample of 43 adult patients (≥16 years) undergoing ≤4 level instrumented fusion for back and/or leg pain of degenerative cause, were recruited pre-surgery from 4 UK spinal surgery centres. Patients completed a weekly diary expressed in their own words for the first 4 weeks following surgery to capture their life as lived. Diary content was based on previous research findings and recorded progress, recovery, motivation, symptoms, medications, healthcare appointments, rehabilitation, positive/negative thoughts, and significant moments; comparing to the previous week. To maximise completion and data quality, diaries could be completed in paper form, word document, as online survey or as audio recording. Strategies to enhance diary adherence included a weekly prompt. A framework analysis for individual diaries and then across participants (deductive and inductive components) captured emergent themes. Trustworthiness was enhanced by strategies including reflexivity, attention to negative cases and use of critical co-investigators. Twenty-eight participants (15 female; n = 18 (64.3%) aged 45-64) contributed weekly diaries (12 withdrew post-surgery, 3 did not follow through with surgery). Adherence with diaries was 89.8%. Participants provided diverse and vivid descriptions of recovery experiences. Three distinct recovery trajectories were identified: meaningful recovery (engagement in physical and functional activities to return to functionality/mobility); progressive recovery (small but meaningful improvement in physical ability with increasing confidence); and disruptive recovery (limited purpose for meaningful recovery). Important interacting constructs shaped participants' recovery including their pain experience and self-efficacy. This is the first account of immediate recovery trajectories from patients' perspectives. Recognition of a patient's trajectory may inform patient-centred recovery, follow-up and rehabilitation to improve patient outcomes.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".