Indicators for evaluating cancer organizations' support services: Performance and associations with empowerment
Bibliographic record
Abstract
BACKGROUND: Community-based cancer organizations provide services to support patients. An anticipated benefit of these services is patient empowerment. However, this outcome has not been evaluated because of the lack of validated health-related empowerment questionnaires in the cancer context. In this validation study, the authors assessed the extent to which 16 indicators used by the Canadian Cancer Society (CCS) and the Cancer Council Victoria, Australia (CCV) to evaluate their services were associated with health-related empowerment. METHODS: Cancer patients/survivors who were diagnosed < 3 years earlier and who used CCS programs completed a questionnaire that included the 16 CCS-CCV indicators and 5 scales from the Health Education Impact Questionnaire (heiQ) measuring key dimensions of empowerment. To determine whether the CCS-CCV indicators captured empowerment, differences in heiQ scores were compared between 2 groups: those with higher levels of agreement (agreeing or agreeing strongly) with an indicator and those with lower levels of agreement (agreeing slightly or disagreeing to any degree). RESULTS: Participation was 72% (207 of 289 eligible CCS users). Compared with participants who had lower levels of agreement on CCS-CCV indicators, those who had higher levels of agreement were more likely to report higher levels of empowerment on the different heiQ scales. For 15 of 16 indicators, these differences were significant (Wilcoxon rank-sum test; P < .10) on ≥ 1 of 5 heiQ scales and for 10 of 16 indicators on ≥ 3 of 5 heiQ scales. Two indicators were associated significantly with all 5 heiQ scales (cope better and feel more in control). CONCLUSIONS: Using CCS-CCV indicators to evaluate community-based cancer organizations' services will help determine whether these services are reaching one of their important goals: namely empowering 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 | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".