A Survey of PDA Use by Palliative Medicine Practitioners
Bibliographic record
Abstract
This paper describes the results of a Web survey on the use of personal digital assistants (PDAs) by physicians across Canada involved with the delivery of palliative medicine in different settings. Seventy-two physicians responded to the survey from April to July 2005. The survey revealed 58.3% of respondents currently use PDAs on a daily basis, mostly to organize their practice and to look up medical references. Some use their PDAs to store patient information and to access a central electronic patient record (EPR). In terms of potential PDA use in palliative medicine, six thematic areas are suggested: medical references, EPR, staying connected, personal productivity, clinical research, and issues/concerns. For implications, healthcare organizations should consider mobile technology as part of their information systems strategy. The feasibility of a portable EPR for palliative medicine should be explored, and an information-based approach can help advance palliative medicine research in Canada.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".