Experience of Fatigue in Adolescents Living With Cancer
Bibliographic record
Abstract
This article reports on a small-scale exploratory study conducted with cohorts of adolescents during and after treatment of cancer to explore experiences of fatigue and perceptions of its impact on functioning. A concurrent mixed method design was used to enable detailed understanding of the phenomenon of fatigue in these groups of individuals through convergence of quantitative and qualitative data. Participants completed an investigator-designed Fatigue and Quality of Life Diary for a period of 1 week. Second, they took part in a semistructured interview to explore issues around fatigue and functioning in more detail. Eight adolescents undergoing treatment participated in the study, along with 6 in early remission (1-2 years off treatment) and 8 receiving follow-up (5 or more years off treatment). Data gained from these sources suggested that fatigue can be a considerable problem for adolescents during and after treatment, and that it may not necessarily abate quickly. Some individuals perceived that their quality of life remained compromised many years after treatment, and it seemed that fatigue might play an important part in this. These preliminary findings suggest that research into management of fatigue in this adolescent group is warranted, along with research and development to determine how best to provide supportive care once treatment finishes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".