Nurse Research Experiences and Attitudes Toward the Conduct of Intensive Care Research
Bibliographic record
Abstract
OBJECTIVE: To characterize ICU nurses' research experience, work environments, and attitudes toward clinical research in critically ill adults and children. DESIGN: Cross-sectional survey. SETTING: Eight (seven adult and one pediatric) academic ICUs affiliated with the Canadian Critical Care Trials Group. PARTICIPANTS: Four hundred eighty-two ICU nurses. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Response rate was 56%. Most participants had over 6 years of ICU experience (61%) and held a baccalaureate nursing degree (57%). Most participants (63%) had provided care for patients receiving research study procedures more than five times in the past 12 months and agreed that research leads to improved care for the critically ill (78%) and eligible patients should be approached for research participation (78%). Few perceived practicalities of nursing care are considered in study design (20%); 41% agreed that research studies increases nursing workload. Few participants reported receiving adequate information about study progress (24%) or findings (26%). Principal factor analysis identified three factors each in the environmental and attitudinal domains. Linear regression models demonstrated that positive relationships between researchers and clinicians were associated with favorable perceptions of research impact on nursing care (p < 0.001), ICU research acceptability (p < 0.001), and nursing engagement in research (p < 0.05). Nurses with more formal education reported more favorable attitudes toward nursing engagement in research (p < 0.01) and research acceptability (p < 0.01). Lack of experience in study protocol development and/or data analysis was associated with less favorable attitudes about nursing engagement in research (p < 0.01) and impact of research on nursing care (p < 0.01). CONCLUSION: In these research-intensive ICUs, nurses frequently care for research participants and believe ICU research is important. Inclusion of nurses in study protocol development, improved communication of study progress and findings, and investigation of research-related nursing workload are warranted. Such interventions will support intervention fidelity and data reliability during study conduct and translation of evidence into practice on study completion.
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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 | 0.023 | 0.086 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".