Body image among adolescents and young adults diagnosed with cancer: A scoping review
Bibliographic record
Abstract
OBJECTIVE: Cancer and treatment can produce temporary or permanent body changes, which may affect the body image (BI) of adolescents and young adults diagnosed with cancer (AYAs). This evidence has not been comprehensively summarized. A scoping review was conducted to explore the available evidence on BI among AYAs and identify the definitions, theories, models, frameworks, measures, and methods used to assess BI. METHODS: Databases MEDLINE, EMBASE, PsycINFO (via Ovid) and CINAHL and Gender Studies (via EBSCO) were searched to identify published studies from 1 January 2000 to 25 November 2019. Inclusion criteria were: qualitative, quantitative, or mixed methodology; at least one BI-related measure or theme; published in English; and majority of the sample between 13 and 39 years at diagnosis and a mean age at diagnosis between 13 and 39 years. Two authors screened the titles, abstracts, and full-text articles and data were extracted and summarized. RESULTS: The search yielded 11,347 articles and 82 met inclusion criteria. Articles included 45 quantitative, 33 qualitative, and four mixed-methods studies. The majority of studies used cross-sectional designs, while BI definitions, theories, models, frameworks, and measures were varied. Studies explored descriptive, psychological, physical, coping, and social factors, with BI being described most often as an outcome rather than a predictor. CONCLUSIONS: Theory-based research that employs a holistic BI definition and uses longitudinal or intervention study designs or a qualitative methodology is needed to better understand the BI experience of AYAs and inform the development of strategies and programs to reduce BI concerns and increase positive body experiences.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".