Four levels of outcomes of information‐seeking: A mixed methods study in primary health care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Primary health care practitioners routinely search for information within electronic knowledge resources. We proposed four levels of outcomes of information‐seeking: situational relevance, cognitive impact, information use, and patient health outcomes. Our objective was to produce clinical vignettes for describing and testing these levels. We conducted a mixed methods study combining a quantitative longitudinal study and a qualitative multiple case study. Participants were 10 nurses, 10 medical residents, and 10 pharmacists. They had access to an online resource, and did 793 searches for treatment recommendations. Using the Information Assessment Method ( IAM ), participants rated their searches for each of the four levels. Rated searches were examined in interviews guided by log reports and a think‐aloud protocol. Cases were defined as clearly described searches where clinical information was used for a specific patient. For each case, interviewees described the four levels of outcomes. Quantitative and qualitative data were merged into clinical vignettes. We produced 130 clinical vignettes. Specifically, 46 vignettes (35.4%) corresponded to clinical situations where information use was associated with one or more than one type of positive patient health outcome: increased patient knowledge ( n = 28), avoidance of unnecessary or inappropriate intervention ( n = 25), prevention of disease or health deterioration ( n = 9), health improvement ( n = 6), and increased patient satisfaction ( n = 3). Results suggested information use was associated with perceived benefits for patients. This may encourage clinicians to search for information more often when they feel the need. Results supported the four proposed levels of outcomes, which can be transferable to other information‐seeking contexts.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| 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 it