Psychosocial Interventions for the Treatment of Cancer-Related Fatigue: An Umbrella Review
Bibliographic record
Abstract
Cancer-related fatigue is one of the most common symptoms of cancer and one of those referred by patients as the most disabling. However, we still do not have enough evidence to allow us to recommend effective and personalized approaches. GOAL: To provide evidence on the efficacy of ASCO-recommended psychosocial interventions for reducing cancer-related fatigue. METHODOLOGY: A general quantitative systematic review for nonprimary clinical interventions that allows the collection, synthesis and analysis of already published reviews. Systematic reviews of RTCs were selected as these make up the body of knowledge that provides the most evidence in an umbrella format. The results do not provide clear or comparable evidence regarding the different interventions, with moderate evidence standing out for cognitive interventions and mindfulness. CONCLUSIONS: Research gaps, study biases and the need for further research to ask more precise questions and to make reliable recommendations to mitigate the impact of cancer-related fatigue are evident.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".