Predictors of Nurses??? Acceptance of an Intravenous Catheter Safety Device
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: It is important to determine the factors that predict whether nurses accept and use a new intravenous (IV) safety device because there are approximately 800,000 needlesticks per year with the risk of contracting a life-threatening bloodborne disease such as HIV or hepatitis C. OBJECTIVES: To determine the predictors of nurses' acceptance of the Protectiv Plus IV catheter safety needle device at a teaching hospital in Texas. METHOD: A one-time cross-sectional survey of nurses (N = 742) was conducted using a 34-item questionnaire. A framework was developed identifying organizational and individual predictors of acceptance. The three principal dimensions of acceptance were (a) satisfaction with the device, (b) extent to which the device is always used, and (c) nurse recommendations over other safety devices. Measurements included developing summary subscales for the variables of safety climate and acceptance. Descriptive statistics and multiple linear and logistic regression models were computed. RESULTS: The findings showed widespread acceptance of the device. Nurses who had adequate training and a positive institutional safety climate were more accepting (p <or=.001). Also, nurses who worked at the hospital a shorter period were more likely to be accepting of the device (p <or=.001). Nurses who felt that the safety climate was positive and who had used the device for at least 6 months were more likely to use the device (p <or=.001). DISCUSSION: To achieve maximum success in implementing IV safety programs, high quality training and an atmosphere of caring about nurse safety are required.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| 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 | 0.000 | 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 it