Factors influencing oral care in intubated intensive care patients
Bibliographic record
Abstract
BACKGROUND: The practice of oral care in intensive care settings remains inconsistent among intubated patients, yet these patients are at high risk of developing ventilator-associated pneumonia. Therefore, it is important to adopt safe professional behaviour based on clinical practice guidelines. This study was based on Ajzen's (1985) theory of planned behavior, a conceptual framework that allows a better understanding of how internal and external factors influence behaviour adoption. AIMS AND OBJECTIVES: To study influential factors in how nurses practice oral care with intubated clients in intensive care settings, referring to the theory of planned behavior (TPB) constructs. DESIGN: A cross-sectional descriptive correlational design was conducted through a provincial postal survey in Quebec, Canada. METHODS: A questionnaire was completed by 375 nurses working in intensive care units (ICUs). RESULTS: Perceived behavioural control and attitude were the most important determinants in the level of intention to engage in oral care. Knowledge, available human and material resources, and number of years of experience in critical care nursing also seemed to be significant influencing factors. CONCLUSIONS: This study improved our understanding of the factors influencing the practice of oral care in intubated patients in the ICU, relying on TPB as an explanatory framework. It would be important to continue to study this professional behaviour and to work in collaboration with health care facilities to promote the importance of oral care as an imperative for the safety and quality of health care. RELEVANCE TO CLINICAL PRACTICE: The results of this study represent a solid foundation for advancing continuing education programmes and intensive care orientation programmes tailored to the needs of nurses.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".