Healthy Canadian adolescents’ perspectives of cancer using metaphors: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: Cancer has been described using metaphors for over 4 decades. However, little is known about healthy adolescents' perspectives of cancer using metaphors. This paper reports on findings specific to adolescents' perspectives of cancer using metaphors. The findings emerged from a qualitative ethnographic study that sought to understand Canadian adolescents' conceptualisation of cancer and cancer prevention. DESIGN: To arrive at a detailed description, data were obtained using individual interviews, focus groups and photovoice. SETTING: 6 high schools from a western Canada province. PARTICIPANTS: 75 Canadian adolescents. RESULTS: Use of 4 metaphors emerged from the data: loss (cancer as the sick patient and cancer as death itself); military (cancer as a battle); living thing (haywire cells and other living things) and faith (cancer as God's will) metaphors, with the loss and military metaphors being the ones most frequently used by adolescents. Adolescents' descriptions of cancer were partly informed by their experiences with family members with cancer but also what occurs in their social worlds including mass media. Adolescents related cancer to emotions such as sadness and fear. Accordingly, more holistic and factual cancer descriptions, education and psychosocial support are needed to direct cancer messaging and clinical practice. CONCLUSIONS: Findings from this study suggest that the public and healthcare providers be more aware of how they communicate cancer messages.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".