Unconventional Therapy Use Among Children With Cancer in Saskatchewan
Bibliographic record
Abstract
The study aimed to estimate the prevalence of unconventional therapy use among children with cancer in Saskatchewan, including identification of the most commonly used therapies, and to describe families' expectations and experiences in doing so. Researchers used a cross-sectional survey design with semi-structured telephone interviews to suit the descriptive and explor atory inquiry and the population focus. The personal telephone interviews occurred during the fall and winter of 1996 to 1997, with the parents coming from a wide range of geographic areas in the province of Saskatchewan. Parents of all children who were aged 14 years or younger when diagnosed with cancer during 1994 and 1995 in Saskatchewan and still living at the time of the study were identified through the provincial cancer registry with the assistance of the Saskatchewan Cancer Agency. Of the 44 families partici pating (92% of those eligible), 36% reported using unconventional therapy for their child's cancer; another 21% considered it. Reasons included comple menting medical treatment, coping with side effects; making the child stron ger ; and stopping the cancer. Experiences were generally positive. Reasons for not using unconventional therapies included the child doing well and parents placing confidence in the medical system. Parents identified a need for better quality information about unconventional therapies. Unconventional therapies play a substantial complementary role in cancer care for children. Families need support to identify safe and potentially helpful therapies when they choose that route. This requires: more research about therapies' effectiveness; more accessible, quality information; and more training for health professionals in understanding and discussing unconventional therapies. There is considerable research showing that use of unconventional therapies, also known as comple mentary or alternative therapies, is high among adult cancer patients. Although it is likely reasonable to assume this may also be true for children, there is almost no research on children's use of unconventional therapies for cancer. Knowing the extent of children's use of unconventional therapies and whether those experiences have been beneficial or harmful is essential for parents and health professionals making quality care decisions for children.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".