Psychological distress and experiences of Adolescents and Young Adults with cancer during the COVID‐19 pandemic: A cross‐sectional survey
Bibliographic record
Abstract
BACKGROUND: This study investigated prevalence of psychological distress, factors associated with distress, and experiences of Adolescents and Young Adults (AYAs) with cancer during the COVID-19 pandemic. It also compared distress in this group to previously surveyed Canadian AYAs with cancer in 2018 by the Young Adults with Cancer in their Prime (YACPRIME) study. METHODS: A cross-sectional, online, self-administered survey of AYAs diagnosed with cancer between 15 and 39 years of age was conducted. Psychological distress was measured by the Kessler Psychological Distress Scale (K10). Associations between variables and high psychological distress (K10 ≥ 25), and comparison of prevalence of psychological distress with the YACPRIME study were done using multivariable logistic regression. Summative qualitative content analysis analyzed participant experiences during this pandemic. RESULTS: We included 805 participants. High psychological distress was present in over two-thirds of the group (68.0%; 95% CI, 64.7%-71.2%). Employment impact during pandemic (AOR (adjusted odds ratio), 2.16; 95% CI, 1.41-3.31) and hematologic malignancy (AOR, 1.76; 95% CI 1.08-2.97) were associated with higher psychological distress, while older age [AOR, 0.95; 95% CI, 0.92-0.99] and personal income < $40,000 (AOR, 0.38; 95% CI, 0.24-0.58) were associated with lower distress. Adjusted odds of experiencing psychological distress among AYAs with cancer during pandemic compared to pre-pandemic years was 1.85 (95% CI: 1.36-2.53). Overarching themes of pandemic experiences included: inferior quality of life, impairment of cancer care, COVID-19 related concerns and extreme social isolation. CONCLUSION: AYAs diagnosed with cancer are experiencing high psychological distress during this pandemic. Distress screening and evidence-based interventions to alleviate distress are essential.
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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 | 0.001 | 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 | 0.001 |
| 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".