A Qualitative Investigation of the Decision to Return to Sport After Anterior Cruciate Ligament Reconstruction
Bibliographic record
Abstract
BACKGROUND: Primary anterior cruciate ligament (ACL) reconstruction is known to have excellent outcomes, but many patients do not return to their preinjury level of sport participation. Previous studies have used subjective outcome scores to evaluate this discrepancy, but none to date has used qualitative, in-depth patient interviews. PURPOSE: To understand the factors influencing a patient's decision to return to his or her preinjury level of sport after ACL reconstruction. HYPOTHESIS: Extrinsic and intrinsic factors may affect one's decision to return to sport after primary ACL reconstruction despite good functional knee scores. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: An experienced interviewer conducted qualitative, semistructured interviews of 31 patients, aged 18 to 40 years, who had undergone primary ACL reconstruction surgery. All participated in sport before injury and had a minimum 2-year follow-up with no further surgeries or knee injuries. Qualitative analysis was then performed to derive codes, categories, and themes. An assessment of preinjury and current sport participation by type, level of competition, and Marx activity score, along with patient-reported knee function, was also conducted. RESULTS: Patient interviews revealed 3 overarching themes: fear, lifestyle changes, and innate personality traits. Elements of these factors were shown to largely influence the decision to return to the preinjury sport both in those patients who had returned and those who had not returned to sport. Less common factors included the surgeon's advice not to return, depressed mood, and persistent knee pain. CONCLUSION: Patients who did not return to their preinjury level of sport after primary ACL reconstruction despite having good knee function were largely influenced by fear, shifts in priority, and individual personalities. This study highlights the importance for treating physicians to recognize and address psychological factors and lifestyle changes that largely contribute to a patient's postoperative decision to return to sport. Results from this study will allow surgeons and health care professionals to educate patients contemplating surgery and to better understand the recovery process not only from sport-related surgeries but other surgical interventions with the goal of returning to activity.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".