Examining the image of nursing among the children hospitalized in the oncology ward
Bibliographic record
Abstract
Abstract Introduction. Patients, as subjects of medical care, are becoming increasingly more demanding toward medical professionals which poses a challenge both for doctors and nurses. A variety of factors influences the professional image of a nurse. Different features are involved, including the nurse’s professional or interpersonal skills their personal beliefs, attitude, as well as social stereotypes about nurses. Aim. Looking at the image of nursing among the children hospitalized in the oncology ward. Material and methods. The authors used both literature review and a questionnaire of their own making. The literature review was done using data from the databases of Polish Central Medical Library. The research group comprised 32 children (aged from 8 to 17), all undergoing hospitalization in Hematology/Oncology and Child Transplantology in Lublin. The statistical calculations are made using Chi2 tests. The test results of p<0.05 were held as statistically significant. Results. The group was mostly composed of children aged 14 to 17 (56.25%). There were more boys (62.5%) than girls. The majority of children came from rural areas (71.87%) and most of them read through the documentation concerning the rules of the ward. Both nurses’ work and relations with patients were graded as “good” by the patients. Children pointed to “nice appearance” as the most important feature of every nurse. Discussion. A pediatric nurse should be patient, have lots of understanding, be sympathetic, caring and able to hold their nerve. Unfortunately, according to authors of earlier studies, not all nurses have these traits. This is due to the fact that the staff rarely involve in communication with the patients and they lack interpersonal skills. Conclusions. Children have a very high opinion on the work of nurses at the Hematology/Oncology and Child Transplantology Clinics. The children emphasized that the following features have the highest impact on their picture of the nurse: nice looks, being protective and caring. A research study conducted at the Hematology/Oncology and Child Transplantology Clinics shows the right features that a nurse should have
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".