Cognitive complaints in brain tumor patients and their relatives’ perspectives
Bibliographic record
Abstract
BACKGROUND: Cognitive deficits have been frequently assessed in brain tumor patients. However, self-reported cognitive complaints have received little attention so far. Cognitive complaints are important as they often interfere with participation in society. In this study, cognitive complaints were systematically assessed in brain tumor patients. As patients' experiences and relatives' estimations may vary, the level of agreement was investigated. METHODS: , assessing cognitive complaints across 10 daily life activities and cognitive domains (total, memory, executive, attention). Cognitive complaints scores were compared between patients with different clinical characteristics (tumor type, number of treatments, the absence/presence of epilepsy). Complaints difference scores in patient-relative pairs were calculated to explore the level of agreement using intraclass correlations (ICC). Furthermore, we explored whether the level of agreement was related to (1) the magnitude of cognitive complaints in patient-relative pairs and (2) patients' cognitive functioning (assessed with the Montreal Cognitive Assessment). RESULTS: Patients and relatives reported most cognitive complaints during work/education (100%) and social contacts (88.1%). Patients with different clinical characteristics reported comparable cognitive complaints scores. Overall, the level of agreement in patient-relative pairs was moderate-good (ICC 0.73-0.86). Although in 24% of the pairs, there was a substantial disagreement. The level of agreement was not related to the magnitude of complaints in patient-relative pairs or patients' cognitive functioning. CONCLUSION: Both the perspectives of brain tumor patients and their relatives' on cognitive complaints are important. Clinicians could encourage communication to reach mutual understanding.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".