The Effect of Risk Attitude and Uncertainty Comfort on Primary Care Physicians' Use of Electronic Information Resources
Bibliographic record
Abstract
Background: Clinicians use information regularly in clinical care. New electronic information resources provided in push, pull, and prompting formats have potential to improve information support but have not been designed for individualization. Physicians with differing risk status use healthcare resources differently often without an improvement in outcomes.Questions: Do physicians who are risk seeking or risk avoiding and comfortable or uncomfortable with uncertainty use or prefer electronic information resources differently when answering simulated clinical questions and can the processes be modeled with existing theoretical models?Design: Cohort study.Methods: Primary care physicians in Canada and the United States were screened for risk status. Those with high and low scores on 2 validated scales answered 23 multiple-choice questions and searched for information using their own electronic resources for 2 of these questions. They also answered 2 other questions using information from 2 electronic information sources: PIER© and Clinical Evidence© .Results: The physicians did not differ for number of correct answers according to risk status although the number of correct answers was low and not substantially higher than chance. Their searching process was consistent with 2 information-seeking models from information science (modified Wilson Problem Solving and Card/Pirolli Information Foraging/Information Scent models). Few differences were seen for any electronic searching or information use outcome based on risk status although those physicians who were comfortable with uncertainty used more searching heuristics and spent less effort on direct searching. More than 20% of answers were changed after searching—almost the same number going from incorrect to correct and from correct to incorrect. These changes from a correct to incorrect answer indicate that some electronic information resources may not be ideal for direct clinical care or integration into electronic medical record systems.Conclusions: Risk status may not be a major factor in the design of electronic information resources for primary care physicians. More research needs to be done to determine which computerized information resources and which features of these resources are associated with obtaining and maintaining correct answers to clinical questions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".