The Mediating Role of Sleep Quality in the Association Between Negative Affect and Cognitive Function Among Patients With Nasopharyngeal Carcinoma After Intensity-Modulated Radiotherapy
Bibliographic record
Abstract
BACKGROUND: Cognitive function impairment is a severe yet largely unrecognized adverse reaction among patients with nasopharyngeal carcinoma (NPC) following radiotherapy. OBJECTIVES: The aims of this study were to examine the level of cognitive function, explore the influencing factors of the cognitive function of NPC after intensity-modulated radiotherapy (IMRT), and identify the mediating role of sleep quality between negative affect and cognitive function. METHODS: In total, 200 patients with NPC after IMRT were recruited from a tertiary cancer center in Southern China between September 2020 and March 2021. Participants completed the demographic and disease-related questionnaire, Montreal Cognitive Assessment Scale, Profile of Mood States-Short Form, and Pittsburgh Sleep Quality Index. RESULTS: The mean Montreal Cognitive Assessment Scale scores were 24.42 after adjustment, with 54.5% of patients having cognitive function impairment. Education level, income, seeking rehabilitation knowledge, radiation dose, sleep quality, and negative affect entered the final regression model and explained 82.6% of cognitive function variance. The total and direct effects of negative affect and indirect effects via sleep quality on cognitive function were significant ( P < .05). CONCLUSIONS: Clinicians should pay close attention to patients with poor educational levels, low income, and having difficulties seeking rehabilitation knowledge and patients who accept higher radiation doses. Improving their sleep quality and positive affect may contribute to preventing or reducing cognitive function impairment. IMPLICATIONS FOR PRACTICE: Clinical nurses should pay more attention to cognitive function among NPC patients after IMRT and take effective measures or interventions to prevent and reduce their cognitive function impairment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".