What can we learn from surveys? A systematic review of survey studies addressing femoroacetabular impingement syndrome
Bibliographic record
Abstract
Abstract The purpose of this study was to systematically review the methodology, response rate and quality of survey studies related to femoroacetabular impingement (FAI) syndrome. A search was conducted on three databases (PubMed, EMBASE, MEDLINE) for relevant studies from database inception to 27 January 2020. Data extracted included study and survey characteristics, as well as response rates. The quality of the included studies was also assessed using a previously published quality assessment tool. Data were analysed with means, ranges, standard deviations, 95% confidence intervals and bivariate analysis. Eleven studies (13 surveys) were included in this review out of a total of 1608 initial titles found. Surveys were most often administered via the Internet (72%) to orthopaedic surgeons (54%). The mean response rate was 70.4%. The mean quality score was moderate 13.3/24 (SD ±4.3). The criterion that most often scored high was ‘clearly defined purpose and objectives’ (11/11). The most common survey topic investigated surgeons’ knowledge regarding FAI diagnosis and management (n = 7). In addition, bivariate analysis between quality score and response rate showed no significant correlation (Spearman’s rho = −0.090, P = 0.85). Overall, survey studies related to FAI syndrome most often use Internet-based methods to administer surveys. The most common target audience is orthopaedic surgeons. The topics of the surveys most often revolve around orthopaedic surgeons’ knowledge and opinions relating to the diagnosis and management of FAI syndrome. The response rate is high in patient surveys and lower in larger surgeon surveys. Overall, the studies are of moderate quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".