How Patients Experience and Give Meaning to Their Cancer-related Fatigue?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fatigue is a common experience occurring in 70% to 100% of advanced cancer patients with a great impact on quality of life and survival. Despite the complexity of this phenomenon, fatigue’s psychosocial dimensions are still not well understood. The aim of this study was to deepen how Italian patients perceive and give meaning to their cancer-related fatigue through the analysis of their language. The study was designed using ethnoscience, an approach that allows to explore how meaning is conveyed through language. We interviewed 16 cancer patients with different level of fatigue (5 mild, 5 moderate, 6 severe). The data analysis showed that fatigue affected three experiential dimensions (mind, body and interpersonal relationships) which are characterized by different symptomatic manifestations depending on the level of fatigue. Patients’ causal attributions also varied across levels of fatigue: patients with mild and moderate fatigue attributed their fatigue to psychological and contextual causes, whereas patients with severe fatigue attributed their fatigue to physical and medical causes. As fatigue affects multiple areas of patients' lives, this study suggests the importance of holistic treatments with a multidisciplinary approach able to support patient engagement and activation in their healthcare. This study also shows the importance of considering patients' causal attributions about fatigue, as these appeared to play a role in how patients managed fatigue. Finally, our data highlighted the importance of using a shared language when speaking with patients about fatigue as this may help patients to feel more understood and supported, thus also improving their quality of life and engagement in their care & cure process.
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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 it