Many family physicians will not manually update PDA software: anobservational study
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
BACKGROUND: In a prospective study to explore connections between clinical information delivery and information retrieval, 41 Canadian family physicians searched an electronic knowledge resource (EKR) as needed for practice. Research software, called the Information Assessment Method (IAM), prompted family physicians to report on the situational relevance, perceived cognitive impact and application of their retrieved information hits. Both the IAM and the EKR needed periodic updating to properly address our research questions. OBJECTIVE: To determine the frequency of software updating when manual or semi-automatic approaches are used by family physicians. METHODS: Each family physician received a handheld computer (PDA) that ran the Windows Mobile 6 operating system. For technical reasons, both the IAM and the EKR were accessed offline on PDA. To update the EKR and the IAM, family physicians were asked to synchronize their PDA to their PC. Updating the IAM was a manual process, whereas updating the EKR was semi-automatic. RESULTS: We found: (1) about 25% of family physicians never or rarely updated PDA software on their own, (2) a large number of software updates were never installed and (3) the semi-automatic method was associated with a small increase in the proportion of installed software updates (58.9% versus 48.6% for the manual method). CONCLUSIONS: When a wireless internet connection is not used to update PDA software, sociotechnical issues complicate mobile data collection and data transfer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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