Meeting the needs of families: facilitating access to credible healthcare information
Bibliographic record
Abstract
EBN engages readers through a range of online social media activities to debate issues important to nurses and nursing. EBN Opinion papers highlight and expand on these debates . Following an increase in the use of the internet in everyday life, research has identified that individuals are increasingly turning to the internet as a means for identifying information about healthcare conditions.1 One study identified that 98% of parents surveyed used the internet to search for information about their child's condition.2 While the use of the internet as an information seeking source is not problematic in itself, a substantial proportion of information has been identified as not being credible, meaning that families are often faced with poor quality non-evidence-based healthcare information.3 Compounding this problem is the fact that families typically do not have access to the traditional academic sources in which research studies are published, and there is a lengthy 17-year gap between publication of research findings and implementation of findings in clinical practice.4 In order to address these issues, a Twitter chat took place to explore how we can better reach families with evidence-based healthcare information. ### Working collaboratively with families There was overwhelming agreement among chat participants about the importance of ensuring that families are able …
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".