Online Tonsillectomy Resources: Are Parents Getting Consistent and Readable Recommendations?
Bibliographic record
Abstract
Objective Parents frequently refer to information on the Internet to confirm or broaden their understanding of surgical procedures and to research postoperative care practices. Our study evaluated the readability, comprehensiveness, and consistency around online recommendations directed at parents of children undergoing tonsillectomy. Study Design A cross-sectional study design was employed. Setting Thirty English-language Internet websites. Subjects and Methods Three validated measures of readability were applied and content analysis was employed to evaluate the comprehensiveness of information in domains of perioperative education. Frequency effect sizes and percentile ranks were calculated to measure dispersion of recommendations across sites. Results The mean readability level of all sites was above a grade 10 level with fewer than half of the sites (n = 14, 47%) scoring at or below the eight-grade level. Provided information was often incomplete with a noted lack of psychosocial support and skills-training recommendations. Content analysis showed 67 unique recommendations spanning the full perioperative period. Most recommendations had low consensus, being reported in 5 or fewer sites (frequency effect size <16%). Conclusion Many online parent-focused resources do not meet readability recommendations, portray incomplete education about perioperative care and expectations, and provide recommendations with low levels of consensus. Up-to-date mapping of the research evidence around recommendations is needed as well as improved efforts to make online information easier to read.
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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 | 0.008 | 0.122 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".