Development and Psychometric Evaluation of the Cancer Distress Scales for Adolescent and Young Adults
Bibliographic record
Abstract
Purpose: The use of valid and reliable screening tools to measure distress may help to identify adolescent and young adults (AYA) with cancer who need additional support. Our study describes a two-phase approach to adapt the Australian AYA oncology and survivorship distress screening tools for use in Canada. Methods: Phase 1 involved refining the Australian AYA oncology and survivorship screening tools using cognitive interviews with AYA with cancer and feedback from experts. In phase 2, a field-test study was performed, and Rasch Measurement Theory (RMT) analysis was used for item reduction and to examine reliability and validity. Results: Cognitive interviews with 45 AYA with cancer and feedback from 25 experts resulted in a field-test version of the Cancer Distress Scales for AYA (CDS-AYA) consisting of 91 items that measure 9 constructs. The field-test sample included 515 participants. RMT analysis identified five scales (impact of cancer, physical, emotional, cancer worry, and cognitive) with ordered thresholds, good item fit (−3.70 to 2.82), and acceptable reliability (0.85–0.94). Reliability for the remaining four scales (employment, education, practical, and social) was low, and the scales were retained as checklists, with the exception of the social scale that was dropped. Conclusion: The final item-reduced CDS-AYA consist of 48 items in 5 scales, with 2 stand-alone items in the physical and emotional scales and 23 items in 3 checklists. The CDS-AYA can be used in research and in clinical practice to measure distress in AYA with cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".