Describing and exploring self‐esteem, physical self‐perceptions, physical activity and self‐efficacy in adolescent and young adult cancer survivors
Bibliographic record
Abstract
OBJECTIVES: (a) Describe levels of physical and global self-esteem and (b) explore the relationships between these types of self-esteem and physical activity (PA) behaviour, self-efficacy for PA and physical self-perceptions among adolescent and young adult (AYA) cancer survivors. METHODS: = 32.90 ± 4.38 years), who were on average 2.08 ± 1.37 years post-treatment, participated in this cross-sectional observational study. Descriptive statistics, correlations and hierarchical multivariate linear regression analyses were used to analyse the data. RESULTS: Moderate levels of physical and global self-esteem were reported. Both types of self-esteem were significantly related to physical self-perceptions, but not to PA behaviour nor self-efficacy for PA. Self-efficacy for PA moderated the relationship between physical self-perceptions and physical self-esteem, such that the association between physical self-perceptions and physical self-esteem was of stronger magnitude at higher levels of self-efficacy for PA than at lower levels of self-efficacy for PA. CONCLUSION: This study provides a starting point for describing self-esteem and identifying the circumstances under which self-esteem may be optimised among AYA cancer survivors. Fostering feelings of confidence, competence and control over PA may help to promote psychological well-being among AYA cancer survivors.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".