Informational needs of breast cancer patients on chemotherapy: differences between patients' and nurses' perceptions.
Bibliographic record
Abstract
BACKGROUND: Cancer and chemotherapy are sources of anxiety and worry for cancer patients. Information provision is therefore very important to empower them to overcome and adjust to the stressful experience. Thus, nurses should be aware of the informational needs of the patients throughout the course of their care. PURPOSE: The purpose of the study was to identify the important information required by breast cancer patients during the first and fourth cycles of chemotherapy from both the patients' and nurses' perceptions. METHODOLOGY: This is a longitudinal study used a questionnaire adapted from the Toronto Informational Needs Questionnaires-Breast Cancer (TINQ-BC). Some modifications were made to meet the specific objectives of the study. The study was conducted in the Chemotherapy Day Care at the University of Malaya Medical Centre (UMMC), Malaysia. A total of 169 breast cancer patients who met the inclusion criteria, and 39 nurses who were involved in their care were recruited into the study. RESULTS: The overall mean scores at first and fourth cycle of chemotherapy were 3.91 and 3.85 respectively: i.e., between 3 (or important) and 4 (or very important), which indicated a high level of informational needs. There was no significant difference in information needed by the breast cancer patients between the two cycles of chemotherapy (p=0.402). The most important information was from the subscale of disease, followed closely by treatment, physical care, investigative tests and psychosocial needs. Nurses had different views on the important information needed by breast cancer patients at both time points (p = 0.023). CONCLUSIONS: Breast cancer patients on chemotherapy have high levels of informational needs with no significant differences in information needed at first cycle as opposed to fourth cycle. There were differences between the perceptions of the breast cancer patients and the nurses on important information needed. A paradigm shift, with an emphasis on patients as the central focus, is needed to enhance the information giving sessions conducted by nurses based on the perceptions of the patients themselves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| 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 | 0.001 | 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".