Factors That Influence the Choice to Undergo Surgery for Shoulder and Elbow Conditions
Bibliographic record
Abstract
BACKGROUND: Knowledge of the factors that influence the willingness of patients considering elective orthopaedic surgery is essential for patient-centered care. To date, however, these factors remain undefined in the orthopaedic population with shoulder and elbow disorders. QUESTIONS/PURPOSES: In a cohort of patients seeking surgical consultation for shoulder or elbow conditions, we sought to identify factors that influenced the willingness and decision to undergo surgery. METHODS: In this prospective study, 384 patients completed a questionnaire collecting socioeconomic and health status data before consultation from June 2009 to December 2010. An additional 120 patients who were offered surgery after consultation completed a second questionnaire on their perceptions and concerns regarding surgery. Logistic regression analyses were used to identify factors influencing the willingness and decision to undergo surgery. RESULTS: Lower income (odds ratio [OR], 0.02; CI, 0.02-0.08; p < 0.001) and living alone (OR, 0.25; CI, 0.08-0.77; p = 0.015) were negative predictors of willingness to consider surgery. Physical functioning did not influence willingness (p = 0.994). A greater perceived level of the likelihood of surgical success by the patient (OR, 41.84; CI, 5.24-333.82; p < 0.001) and greater fluency in the English language (OR, 28.39; CI, 3.49-230.88; p = 0.002) were positive predictors of willingness. Willingness to consider surgery as a possible treatment option before the consultation was a predictor of patients' ultimate decisions to undergo surgery (OR, 4.56; CI, 1.05-19.76; p = 0.042). Patients expressing concern about surgery being an inconvenience to daily life, however, were less likely to decide to proceed with surgery (OR, 0.12; CI, 0.02-0.68; p = 0.017). CONCLUSIONS: Many of the identified factors may act as barriers to potentially beneficial surgical interventions. Although most are not modifiable, an awareness of the influence of individual demographics and possible perceptions of patients' choices may show that more in-depth questioning and provisions for cultural differences may be required during the consultation to enable patients to make fully informed decisions. Future studies using qualitative methods would provide a greater in-depth understanding of patients' perceptions regarding surgery and their decision to proceed. Larger or more homogeneous cohorts also would enable additional identification of these factors for different shoulder and elbow conditions. LEVEL OF EVIDENCE: Level II, prognostic study. See the Instructions for Authors for a complete description of levels of evidence.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".