O que a internet ensina à paciente obstétrica sobre a analgesia de parto?
Bibliographic record
Abstract
Observa‐se um crescimento da busca de informação no público geral sobre temas médicos na internet, inclusive em anestesiologia. O objetivo deste estudo foi avaliar a informação existente ao leigo na internet em língua portuguesa sobre analgesia de parto para a população brasileira. Com o uso do termo “anestesia de parto”, os 20 primeiros sites encontrados no Google em novembro de 2014 foram avaliados por dois médicos residentes e classificados como médicos e não médicos. Legibilidade e desenho – acessibilidade, confiabilidade e navegabilidade – foram comparados por meio das ferramentas Fresh (Flesch Reading Ease Score) e Lida (Minervation Validation Tool for Healthcare Websites). O conteúdo dos sites foi confrontado em relação à literatura médica. Sites médicos e não médicos foram considerados de difícil leitura de acordo com o Fresh. Em relação ao desenho, não houve diferença entre os grupos quanto à navegabilidade. Entretanto, a acessibilidade foi considerada superior em sites não médicos (p = 0,042); enquanto que a confiabilidade foi maior em sites médicos (p = 0,019). Com aumento da busca de informações em saúde na internet e aumento da preocupação de melhorar a qualidade de assistência ao parto, é fundamental que o conteúdo disponível ao leigo sobre analgesia de parto seja de qualidade e compreendido. Este estudo demonstrou que tanto sites médicos como não médicos são de difícil leitura; e que os sites não médicos são mais acessíveis, enquanto os médicos são mais precisos. It has been observed a general public increased search on the Internet for health information, including Anesthesiology. The objective of this study was to evaluate the information available to the lay person in Portuguese on the internet about labor analgesia for the Brazilian population. Using the term “labor anesthesia”, the first 20 sites found on Google in November 2014 were evaluated by two resident physicians and classified as medical and non‐medical. Legibility and Design ‐ accessibility, reliability and navigability‐were compared using Flesch Reading Ease Score (FRESH) and Minervation validation tool for healthcare websites (LIDA) tools. The websites’ content was confronted with that of the medical literature. Medical and non‐medical websites were considered difficult to read according to FRESH. Regarding the design, there was no difference between groups regarding navigability, however, accessibility was considered superior in non‐medical websites (p = 0.042); while reliability was higher in medical websites (p = 0.019). With the increased search for health information on the Internet and concern about improving the quality of childbirth care, it is fundamental that the content available to the layperson about labor analgesia is of quality and well understood. This study demonstrated that both medical and non‐medical websites are difficult to read and that non‐medical websites are more accessible while the medical ones are more accurate.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".