The Health Information Literacy Research Project
Bibliographic record
Abstract
OBJECTIVES: This research studied hospital administrators' and hospital-based health care providers' (collectively, the target group) perceived value of consumer health information resources and of librarians' roles in promoting health information literacy in their institutions. METHODS: A web-based needs survey was developed and administered to hospital administrators and health care providers. Multiple health information literacy curricula were developed. One was pilot-tested by nine hospital libraries in the United States and Canada. Quantitative and qualitative methods were used to evaluate the curriculum and its impact on the target group. RESULTS: A majority of survey respondents believed that providing consumer health information resources was critically important to fulfilling their institutions' missions and that their hospitals could improve health information literacy by increasing awareness of its impact on patient care and by training staff to become more knowledgeable about health literacy barriers. The study showed that a librarian-taught health information literacy curriculum did raise awareness about the issue among the target group and increased both the use of National Library of Medicine consumer health resources and referrals to librarians for health information literacy support. CONCLUSIONS: It is hoped that many hospital administrators and health care providers will take the health information literacy curricula and recognize that librarians can educate about the topic and that providers will use related consumer health services and resources.
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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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".