YouTube As an Information Source for Femoroacetabular Impingement: A Systematic Review of Video Content
Bibliographic record
Abstract
PURPOSE: This study was carried out to assess the quality of information available on YouTube regarding femoroacetabular impingement (FAI). METHODS: YouTube was searched on September 7, 2013 using the search terms FAI, femoroacetabular impingement, and hip impingement. Analysis was restricted to the first 3 pages of results for each search term. English language was a prerequisite for inclusion. Videos were evaluated by 2 independent reviewers (M.G.M., D.J.H.) using novel scoring checklists for diagnosis and treatment of FAI. Interobserver reliability analysis was evaluated using the intraclass correlation coefficient (ICC). Videos were grouped according to quality assessment score, and the group means were analyzed for differences in video characteristics using the analysis of variance (ANOVA) model. Videos were characterized by the source of content. RESULTS: After filtering 1,288,324 potential videos, 52 videos were identified and included for analysis. The mean video quality assessment scores were 3.1 for diagnosis and 2.9 for treatment (maximum score = 16). No videos were scored as excellent (quality assessment score > 12). Effective resources included 3 videos on diagnosis and one video on treatment. No statistically significant differences were found between high- and low-scoring videos for duration, days online, views per day, likes, likes per day, likes per view, dislikes, or likes-dislikes difference for either diagnosis or treatment (P > .05 for all). The source of most of the videos was educational (67%), and most of these included physicians (66%). CONCLUSIONS: Patients searching YouTube for videos pertaining to FAI will be presented with a sizeable repository of content of overall low quality. As such, physicians need to recognize the potential influence of YouTube videos on patients' preconceptions of their conditions and the effect on the physician-patient consultation. This review highlights the need for evidence-based, comprehensive educational videos addressing FAI diagnosis and treatment. LEVEL OF EVIDENCE: Level V, systematic review of non-peer-reviewed resources.
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 | 0.011 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".