The Cognitive Symptom Checklist-Work in cancer patients is related with work functioning, fatigue and depressive symptoms: a validation study
Bibliographic record
Abstract
PURPOSE: The study objectives are to translate the 21-item Cognitive Symptom Checklist-Work (CSC-W21) to Dutch (CSC-W DV) and to validate the CSC-W DV in working cancer patients. METHODS: The CSC-W21 was cross-culturally translated and adapted to a Dutch version. In this 19-item version, the dichotomous response option was changed to an ordinal five-point scale. A validation study of the CSC-W DV was conducted among cancer patients who had returned to work during or following cancer treatment. Internal consistency (Cronbach's α), structural validity (exploratory factor analysis) and construct validity (hypothesis testing) were evaluated. RESULTS: In a cohort of 364 cancer patients, 341 (94 %) completed the CSC-W DV (aged 50.6 ± 8.6 years, 60 % women). Exploratory factor analysis revealed two subscales 'working memory' and 'executive function'. The internal consistency of the total scale and subscales was high (Cronbach's α = 0.93-0.95). Hypothesis testing showed that self-reported cognitive limitations at work were related to work functioning (P < 0.001), fatigue (P = 0.001) and depressive symptoms (P < 0.001), but not to self-rated health (P = 0.14). CONCLUSIONS: The CSC-W DV showed high internal consistency and reasonable construct validity for measuring work-specific cognitive symptoms in cancer patients. The CSC-W DV was associated in expected ways with work functioning, fatigue and depressive symptoms. IMPLICATIONS FOR CANCER SURVIVORS: It is important to enhance knowledge about cognitive symptoms at work in cancer patients, to guide and support cancer patients as good as possible when they are back at work and to improve their work functioning over time.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".