Library and Informatics Training May Improve Question Formulation among Public Health Practitioners
Bibliographic record
Abstract
A review of: Eldredge, Jonathan D., et al. “The Effect of Training on Question Formulation among Public Health Practitioners: Results from a Randomized Controlled Trial.” Journal of the Medical Library Association 96.4 (2008): 299-309. 28 Aug 2009 . Objectives – To determine whether providing library and informatics training to public health professionals would increase the number and sophistication of work-related questions asked by these workers. Design – Randomised controlled trial. Setting – New Mexico Department of Health. Subjects – Public health professionals from a variety of professions, including administrators, nursing professionals, nutritionists, epidemiologists, physicians, social workers, and others. Methods – All subjects received a three-hour training session on finding evidence-based public health information, with a focus on using PubMed. Two sessions were offered, two weeks apart. Participants were randomised to either an intervention group, which received instruction on the first date, or a control group, which received instruction on the second date. The intervening two weeks constitute the study period, in which both groups were surveyed by e-mail about their work-related question generation. Three times per week, subjects received e-mail reminders asking them to submit survey responses regarding all questions that had arisen in their practice, along with information about their attempts to answer them. Questions were tallied, and totals were compared between the two groups. Questions were also analysed for level of sophistication, and classified by the investigators as “background” questions, which are asked when one has little knowledge of the field, and can usually be answered using textbooks or other reference sources; and “foreground” questions, which are often asked when an individual is familiar with the subject, and looking for more sophisticated information that is usually found in journals and similar sources. This scheme for classifying questions was developed by Richardson and Mulrow (2001). Main Results The investigators found differences in both the number and sophistication of the questions asked between the control and intervention groups. The control group averaged only 0.69 questions per participant during the two-week observation period, while the intervention group averaged 1.24 questions. Investigators also found that a higher percentage of the questions asked by the intervention group were foreground questions (50.0%, versus 42.9%) for the control group. However, when two-tailed t-test analysis was performed on both the frequency of questions and the level of sophistication, the findings were no statistically significant within a 95% confidence interval. Conclusion This study suggests that library and informatics training for public health professionals may increase the number of questions that they ask on work-related topics, and also the sophistication of these questions. However, more studies need to be done to confirm these findings.
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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 | 0.014 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 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".