DEVELOPMENT AND CASE-CONTROL VALIDATION OF THE CANADIAN MEN’S HEALTH FOUNDATION’S SELF RISK-ASSESSMENT TOOL: “YOU CHECK”
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 and Objective: To facilitate the engagement of men in the evaluation of their own health status and risk of disease, we have developed and validated the Canadian Men’s Health Foundation’s self-risk assessment tool (“You Check”). In a single questionnaire, the “You Check” tool estimates the 10-year risk for myocardial infarction (MI), diabetes type 2 (DM), osteoporosis (OS), erectile dysfunction (ED), and low testosterone (LT). Additionally, the tool provides the user with his risk-factor profi le for prostate cancer and his current risk of depression (using the Center for Epidemiologic Studies Depression scale). Materials and Methods: Known risk factors for each disease were collated, the questionnaire designed, and risk scores for each dis-ease were assigned by clinical experts. A risk formula was developed using the sum of risk scores divided by their own range. We validated the risk models with case-control data from a retrospective review of 400 outpatient records from 4 Vancouver family practice clinics. Maximal correct classifi cation proportions were determined and used as thresholds for categorization of risk to low, medium, or high categories. Results: For DM, sensitivity and specifi city were 0.86 and 0.96 respectively and the Area Under Curve was 0.88 (95% Confi dence Interval [CI] 0.81-0.94). For MI these values were 0.70 and 0.93, and 0.75 (0.65-0.85); for LT 0.70 and 0.90 and 0.75 (0.66–0.84); for OS 0.70 and 0.86 and 0.70 (0.61–0.80); and for ED 0.42 and 0.96 and 0.66 (0.58–0.75). Conclusion: This is the fi rst comprehensive men’s health self-risk assessment tool for 7 important diseases. Moderate internal validity was demonstrated for 5 diseases, meeting the public health objectives of “You Check” which is now in the public domain and under appropriate monitoring and evaluation (https://youcheck.ca).
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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 | 0.017 | 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 | 0.000 |
| Open science | 0.000 | 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