Web-based electronic health information systems for prostate cancer patients.
Bibliographic record
Abstract
INTRODUCTION: Providing men with prostate cancer (MPC) timely access to their health records and information (HRI) can enhance their ability to understand their condition and engage in shared medical decision making with their health care provider (HCP). The Internet is a potential means of enhancing such interactions. MATERIALS AND METHODS: Two surveys were conducted at a PC support group in Victoria, BC to identify the health information needs of MPC and the ability to access their HRI. Another objective was to identify the potential role of web-enabled HRI systems at meeting these needs. Sixty-one participants (41 men and 18 spouses/significant others (SS)) completed the first convenience survey and 16 participants then took part in a focus group meeting using a second questionnaire. RESULTS: The majority of men (median age 70 years) were knowledgeable with the computer and Internet. The majority of men (75%) desired the ability to access their HRI through means other than by meeting with their HCP, with the Internet ranking as one of the most desired methods. There was broad interest in accessing various parts of their health record and during different phases of their care. Most men were willing to try a personalized patient web-enabled HRI system. Over 70% of SS desired the ability to access their men's HRI. CONCLUSIONS: The surveys indicate that the Internet is a desirable means of accessing electronic HRI and support the potential role of web-enabled HRI systems for PC patients.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.038 | 0.005 |
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".