Experiences and perceptions of adults pre- and/or post-lumbar spine surgery: a meta-ethnography
Bibliographic record
Abstract
Study Design Qualitative meta-ethnography. Pre-registered with OSF:10.17605/OSF.IO/UTZE6.Purpose To understand the patient experience pre- and/or post-lumbar spine surgery.Methods Literature search: A literature search was conducted in MEDLINE, EMBASE, EmCare and CINAHL from inception to October 17, 2022. Study selection criteria: Peer-reviewed qualitative or mixed-method studies of English text investigating the beliefs, perceptions, or experiences of adults (≥18 years old) pre- and/or post-lumbar spine surgery for degenerative, non-traumatic or non-infectious concerns. Data synthesis: The eMERGE meta-ethnography reporting guidelines were followed to create themes and subthemes from the original themes of the included studies. A quality appraisal was performed using the McMaster Quality Appraisal tool.Results We included 18 studies and identified five themes that were separated into pre- and post-operative categories. The two pre-operative themes included [Citation1]: the influence of physiotherapy interventions on patients’ experiences, and [Citation2] the importance of education/the power of communication, and the three post-operative themes included [Citation1]: psychosocial coping [Citation2], redefining oneself post-operatively, and [Citation3] experience with the healthcare system.Conclusions These findings emphasize the complexity of the peri-operative experience for individuals undergoing lumbar spine surgery. Future research should focus on addressing psychosocial factors that may optimize patient experiences and recovery following LSS.
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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 | 0.051 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".