3 People’s perceptions about their anterior cruciate ligament injury and its care - a systematic review and qualitative evidence synthesis
Bibliographic record
Abstract
Introduction Understanding how people cope with the short- and long-term impacts of anterior cruciate ligament (ACL) rupture and what influences their choice of management (operative vs non-operative) is important to inform interventions that can support physical, psychological and social well-being along the recovery pathway. This review aimed to synthesise all qualitative research involving people post-ACL injury, to understand their perceptions of the injury and its care.Materials and Methods Following protocol registration, 6 databases were searched from inception to June 2024 for qualitative studies that included people post-ACL injury. Study quality was assessed using the Critical Appraisal Skills Programme (CASP) Qualitative Studies Checklist. Extracted data were synthesised using inductive thematic analysis.Results Fifty-six studies with 806 participants (52% female, 85% with ACL reconstruction) from 12 countries were included. Overall study quality was high (21% scored 10/10; 7% scored <8/10 on the CASP checklist). Five themes were identified and were consistent across study settings and time since injury. (1) Knowledge and beliefs around injury are shaped by external messages; (2) Injury disrupted self-identity; (3) Access to individual, interpersonal and community-level support can facilitate physical and psychological recovery; (4) The psychological roller-coaster including fear of re-injury and despair; (5) Accessing the right materials for tailored, holistic care.Conclusion As the first-ever qualitative synthesis of post-ACL injury studies, our findings provide clinicians and researchers with a clinically useful framework to improve their understanding of people's perceptions, experiences, and physical and non-physical needs after ACL injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.059 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".