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Record W2581592925 · doi:10.1136/bmjopen-2016-013958

Healthy Canadian adolescents’ perspectives of cancer using metaphors: a qualitative study

2017· article· en· W2581592925 on OpenAlexafffundabout
Roberta L. Woodgate, David Busolo

Bibliographic record

VenueBMJ Open · 2017
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsMedicineQualitative researchPsychosocialCancerSadnessFocus groupPublic healthPhotovoicePsychiatryNursingAngerSociology

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0180.009
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.246
GPT teacher head0.557
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2017
Admission routes3
Has abstractyes

Explore more

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