Clinical pathway for the screening, assessment and management of anxiety and depression in adult cancer patients: Australian guidelines
Bibliographic record
Abstract
PURPOSE: A clinical pathway for anxiety and depression in adult cancer patients was developed to guide best practice in Australia. METHODS: The pathway was based on a rapid review of existing guidelines, systematic reviews and meta-analyses, stakeholder interviews, a Delphi process with 87 multidisciplinary stakeholders and input from a multidisciplinary advisory panel. RESULTS: The pathway recommends formalized routine screening for anxiety and depression in patients with cancer at key points in the patient's journey. The Edmonton Symptom Assessment System or distress thermometer with problem checklist is recommended as brief screening tools, combined with a more detailed tool, such as the Hospital Anxiety and Depression Scale, to identify possible cases. A structured clinical interview will be required to confirm diagnosis. When anxiety or depression is identified, it is recommended that one person in a treating team takes responsibility for coordinating appropriate assessment, referral and follow-up (not necessarily carrying these out themselves). A stepped care model of intervention is proposed, beginning with the least intensive available that is still likely to provide significant health gain. The exact intervention, treatment length and follow-up timelines, as well as professionals involved, are provided as a guide only. Each service should identify their own referral network based on local resources and current service structure, as well as patient preference. DISCUSSION: This clinical pathway will assist cancer services to design their own systems to detect and manage anxiety and depression in their patients, to improve the quality of care.
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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 | 0.037 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".