Uncertainty and sense‐of‐self as targets for intervention for cancer‐related fatigue
Bibliographic record
Abstract
Cancer-related fatigue (CRF) can be a devastating consequence of cancer and cancer treatments, negatively impacting 50%-90% of cancer patients regardless of age, sex or diagnosis. Limited evidence and research exist to inform effective patient-centred interventions. To target symptom management, there must first be a broader understanding of the symptoms and the lived experience of the persons experiencing CRF and those caring for them, from a supportive as well as a healthcare perspective. This study set out to consider whether components of the language used or descriptors reported by patients, family members, and/or healthcare professionals may provide new insights for potential targets for intervention development. Descriptors from 84 responses (n = 84) from cancer survivors, family members and healthcare professionals were analysed for content. The descriptors reiterate the physical, emotional and functional consequences of CRF, but also reflect two new potential targets for intervention to mitigate the impacts of CRF: uncertainty and sense-of-self.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".