Characterizing Anxiety in Melanoma Patients
Bibliographic record
Abstract
BACKGROUND: Over half of melanoma patients experience significantly elevated anxiety levels leading to psychological distress and delays in diagnosis and treatment. OBJECTIVE: To identify melanoma patients likely to experience high levels of anxiety, we characterize the contributing factors and coping strategies and investigated potential anxiety-alleviating interventions. METHOD: Surveys were sent to 94 melanoma patients at Women's College Hospital's Pigmented Lesion Clinic assessing self-reported anxiety, contributing factors, coping strategies, and potential assisting services. RESULTS: Risk factors for anxiety include female gender (p=0.002) and increasing age (p=0.004) but not melanoma depth. Major factors contributing to anxiety are prognosis, fear of death, and the attitude of the diagnosing doctor. Major coping strategies include family support, doctor assistance, and self-distraction. Potentially useful services for decreasing anxiety include the provision of detailed information pamphlets. CONCLUSION: Melanoma patients likely to experience high anxiety can be predicted and managed in ways that minimize the distress experienced.
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".