The Responsiveness, Content Validity, and Convergent Validity of the Measure Yourself Concerns and Wellbeing (MYCaW) Patient-Reported Outcome Measure
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Bibliographic record
Abstract
OBJECTIVE: Measure Yourself Concerns and Wellbeing (MYCaW) is a patient-centered questionnaire that allows cancer patients to identify and quantify the severity of their "concerns" and "wellbeing," as opposed to using a predetermined list. MYCaW administration is brief and aids in prioritizing treatment approaches. Our goal was to assess the convergent validity and responsiveness of MYCaW scores over time, the generalizability of the existing qualitative coding framework in different complementary and integrative oncology settings and content validity. METHODS: Baseline and 6-week follow-up data (n = 82) from MYCaW and FACIT-SpEx questionnaires were collected for a service evaluation of the Living Well with the Impact of Cancer course at Penny Brohn Cance Care. MYCaW convergent validity was determined using Spearman's rank correlation test, and responsiveness indices assessed score changes over time. The existing qualitative coding framework was reviewed using a new data set (n = 158) and coverage of concern categories compared with items of existing outcome measures. RESULTS: Good correlation between MYCaW and FACIT-SpEx score changes were achieved (r = -0.57, P ≥ .01). MYCaW Profile and Concern scores were highly responsive to change: standardized response mean = 1.02 and 1.08; effect size = 1.26 and 1.22. MYCaW change scores showed the anticipated gradient of change according to clinically relevant degrees of change. Categories, including "spirituality," "weight change," and "practical concerns" were added to the coding framework to improve generalizability. CONCLUSIONS: MYCaW scores were highly responsive to change, allowing personalized patient outcomes to be quantified; the qualitative coding framework appears generalizable across different integrative oncology settings and has broader coverage of patient-identified concerns compared with existing cancer-related patient-reported outcome measures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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