Development and evaluation of a decision aid for patients with stage IV non‐small cell lung cancer
Bibliographic record
Abstract
Although guidelines for treating stage IV non-small cell lung cancer suggest that the patient's values should be considered in decision-making, there are no practical tools available to assist them with their decision-making. OBJECTIVE: To develop and evaluate a decision aid that incorporates patient values. DESIGN AND SAMPLE: (1) Before/after evaluation with patients referred to a regional cancer centre. (2) Mailed survey of thoracic surgeons and respirologists in Ontario. INTERVENTION: An audio-tape guided individuals to review a booklet describing stage IV non-small cell lung cancer, its impact and possible coping strategies, treatment options, benefits and risks, and examples of the decision-making of others. Patients then used a worksheet to consider and communicate personal issues involved in the choice, including: personal values using a 'weigh-scale'; questions; preferred role in decision-making; and predisposition. MEASURES: (1) Patient questionnaires eliciting knowledge, the decision, decisional conflict and acceptability of the decision aid. (2) Physician questionnaires eliciting attitudes toward the decision aid. RESULTS: (1) Twenty of 30 patients used the aid in decision-making. Users thought that the aid was acceptable and significantly improved their knowledge about options and outcomes (P < 0.001), and reduced their decisional conflict (P < 0.001). (2) The majority of the 29 physicians who reviewed the decision aid found it acceptable, were comfortable providing it to patients and said that they were likely to use it. CONCLUSION: The decision aid is a useful and acceptable adjunct to personal counselling.
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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 | 0.014 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".