Cognitive Dysfunction and Its Predictors in Adult Patients With Cancer Receiving Chemotherapy: A Cross-Sectional Correlational Study
Bibliographic record
Abstract
BACKGROUND: Chemotherapy-related cognitive dysfunction, one of the most frequently reported symptoms in patients with cancer, has a negative impact on the daily lives of patients. No research has examined cognitive dysfunction and its potential predictors in adult patients with cancer receiving chemotherapy in Saudi Arabia. PURPOSE: The purpose of this study was to examine the sociodemographic, clinical, and psychological factors associated with cognitive dysfunction in adult patients with cancer receiving chemotherapy. METHODS: A cross-sectional correlational study was carried out with a convenience sample of 100 adult patients with cancer receiving chemotherapy at a university teaching hospital in Saudi Arabia. The Montreal Cognitive Assessment, the Hospital Anxiety and Depression Scale, and sociodemographic and clinical surveys were completed by participants. Descriptive statistics and linear regression were used to analyze the data. RESULTS: The data showed that the participants experienced moderate-to-severe cognitive dysfunction. Participants performed poorly in the divided attention and memory cognitive domains. Age, educational level, and depression factors were found to be significant predictors of cognitive dysfunction. CONCLUSIONS/IMPLICATIONS FOR PRACTICE: Cognitive dysfunction is commonly seen in patients with cancer receiving chemotherapy. Chemotherapy, age, and psychological factors increase susceptibility to cognitive dysfunction in adult patients with cancer. Oncology nurses should be aware that patients with cancer may be extremely vulnerable to cognitive dysfunction. Furthermore, age and psychological factors must be considered when developing symptom management and supportive care intervention programs to reduce the incidence of negative cognitive outcomes in this population.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".