Empirical Study of Nova Scotia Nurses’ Adoption of Healthcare Information Systems: Implications for Management and Policy-Making
Bibliographic record
Abstract
BACKGROUND: This paper used the Theory of Planned Behavior (TPB), which was extended, to investigate nurses' adoption of healthcare information systems (HIS) in Nova Scotia, Canada. METHODS: Data was collected from 197 nurses in a survey and data analysis was carried out using the partial least squares (PLS) technique. RESULTS: In contrast to findings in prior studies that used TPB to investigate clinicians' adoption of technologies in Canada and elsewhere, this study found no statistical significance for the relationships between attitude and subjective norm in relation to nurses' intention to use HIS. Rather, facilitating organizational conditions was the only TPB variable that explained sampled nurses' intention to use HIS at work. In particular, effects of computer habit and computer anxiety among older nurses were signified. CONCLUSION: To encourage nurses' adoption of HIS, healthcare administrators need to pay attention to facilitating organization conditions at work. Enhancing computer knowledge or competence is important for acceptance. Information presented in the study can be used by administrators of healthcare facilities in the research location and comparable parts of the world to further improve HIS adoption among nurses. The management of nursing professionals, especially in certain contexts (eg, prevalence of older nursing professionals), can make use of this study's insights.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".