Adolescent and Young Adult Cancer Patients’ Experiences With Treatment Decision-making
Bibliographic record
Abstract
BACKGROUND: Adolescents and young adults (AYAs) with cancer generally want to engage in decision-making but are not always able to do so. We evaluated cancer treatment decision-making among AYAs, including decisional engagement and regret. METHODS: We surveyed 203 AYA patients with cancer aged 15 to 29 (response rate 74%) treated at a large academic center and their oncologists. Patients were approached within 6 weeks of diagnosis and asked to report decision-making preferences and experiences (Decisional Roles Scale) and the extent to which they regretted their initial treatment decision (Decisional Regret Scale) assessed at baseline and 4 and 12 months later. RESULTS: A majority of AYAs (58%) wanted to share responsibility for decision-making with oncologists; half (51%) preferred limited involvement from parents. Although most AYAs held roles they preferred, those who did not reported holding more passive roles relative to oncologists (P < .0001) and parents (P = .002) than they desired. Nearly one-quarter of patients (24%; 47 of 195) experienced regret about initial cancer treatment decisions at baseline, with similar rates at 4 (23%) and 12 (19%) months. In a multivariable model adjusted for age, decisional roles were not associated with regret; instead, regret was less likely among patients who trusted oncologists completely (odds ratio 0.17 [95% confidence interval 0.06–0.46]; P < .001) and who reported that oncologists understood what was important to them when treatment started (odds ratio 0.13 [95% confidence interval 0.04–0.42]; P < .001). CONCLUSIONS: Nearly one-fourth of AYA patients expressed regret about initial treatment decisions. Although some AYAs have unmet needs for decisional engagement, attributes of the patient-oncologist relationship, including trust and mutual understanding, may be most protective against regret.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".