Online resources as a source of information for exercise and physical activity in solid organ transplant recipients
Bibliographic record
Abstract
Introduction: Exercise training post-transplant has been shown to improve physical function and quality of life in solid organ transplant (SOT) recipients. Online resources in the form of websites and videos are commonly used to provide education and instruction on exercise and physical activity in SOT; however, the content and quality of these online resources has not been evaluated. Methods: The first 200 websites and videos identified on Google and YouTube using the English search term "exercise and physical activity in solid organ transplantation" were analyzed. Website and video content was evaluated based on 25 key components of exercise and physical activity in SOT as described in established exercise program recommendations. Website and video quality was determined using DISCERN, Global Quality Scale (GQS), and Patient Education Materials and Assessment Tool (PEMAT; threshold for which material is deemed understandable or actionable is >70%). Parametric and non-parametric tests were used to assess website and video characteristics, content, and quality metrics. Results: = 34) were identified, with the two most common categories being foundation/advocacy organizations and scientific resources. The average reading grade level of websites was 13 ± 3. Website and video content scores varied significantly (websites 11.3 ± 6.4; videos 8.4 ± 5.3). DISCERN total score and GQS score were low (median range for DISCERN 2.5-3.0; median for GQS 2.0 for both websites and videos, out of 5). PEMAT understandability and actionability scores were also low across websites and videos (mean range 57%-67% and 47%-65%, respectively). Foundation/advocacy websites had higher content and quality scores compared to scientific organizations and news/media articles. Conclusions: To our knowledge, this is the first comprehensive assessment of online content and quality of website and video resources on physical activity and exercise in adult SOT recipients. There were a limited number of online English patient-directed resources related to physical activity in SOT, most of which only partly captured items outlined in consensus exercise program recommendations and were of low quality and understandability and actionability. This work provides important insight to the English-speaking transplant community on the current state of online exercise health information and provides future direction for resource development.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".