Unmet needs of Australian and Canadian haematological cancer survivors: a cross‐sectional international comparative study
Bibliographic record
Abstract
OBJECTIVE: Few population-based studies have assessed the needs of haematological cancer survivors or conducted international comparisons. We aimed to assess and compare the unmet needs of Australian and Canadian haematological cancer survivors. METHODS: Two cross-sectional datasets were analysed. Survivors were recruited from population-based cancer registries and sent a self-report survey containing the Survivors Unmet Needs Survey. Australians were aged 18-80 years at the time of study and diagnosed in the last 3 years. Canadians were diagnosed 1-5 years prior and aged 19 years and over at diagnosis. RESULTS: A total of 268 Australian and 169 Canadian survivors returned a completed survey. 'Dealing with feeling tired' was identified as the highest concern by survivors. Country (LRχ(2)=4.0(1), p=0.045) was associated with survivors reporting a 'high/very high' unmet need with 'worry about earning money,' with Australians reporting marginally nonsignificantly higher odds than Canadians (OR 2.1; 95% CI; 0.99, 4.3). Country was not significantly associated with any other outcome. Having a personal expense in the last month as a result of having cancer, younger age at diagnosis, female sex, vocational or other level education, and consulting a health care professional for cancer treatment or concerns about cancer in the last month were associated with multiple areas of need. CONCLUSIONS: Australian and Canadian haematological cancer survivors were found to experience similar levels of unmet needs. Overall, haematological cancer survivors may require additional assistance in dealing with feeling tired.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".