[Family Health Program: interview by Denise Elvira Pires de Pires].
Bibliographic record
Abstract
Nursing is a profession committed to the promotion of human beings. It takes into consideration their freedom, uniqueness and dignity. Therefore, communication plays an important role within the nursing process and its results, and it is also a fundamental component of the treatment. However, in the context of Brazilian hospitals, communication between nurses and patients is limited to the performance of these professionals' technical role. The purpose of this study is to analyse the case of a hospitalized female adolescent, focusing on the communication that happens between her and the nursing professionals who provide her assistance. This analysis was based on Bales' categories. Through the technique of direct observation, the behavior resultant from the interaction between nurses and the adolescent was analysed on a total of 30 hours during five days. The observation showed 428 units of interaction which were classified, by qualified professionals, in positive, negative and neutral socio-emotional areas. Considering the high incidence of interactions in the neutral area (89.2%), authors recommend a humanistic correction in the communication during the nursing process. This change in communication can qualify patient's care as well as generate satisfaction at work through empathy and solidarity.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".