Value of wireless personal digital assistants for practice: perceptions of advanced practice nurses
Bibliographic record
Abstract
AIMS AND OBJECTIVES: The aims were to explore advanced practice nurses' perceptions on wireless Personal Digital Assistant technologies, to establish the type and range of tools that would be useful to support their practice and to identify any requirements and limitations that may impact the implementation of wireless Personal Digital Assistants in practice. BACKGROUND: The wireless Personal Digital Assistant is becoming established as a hand-held computing tool for healthcare professionals. The reflections of advanced practice nurses' about the value of wireless Personal Digital Assistants and its potential to contribute to improved patient care has not been investigated. DESIGN: A qualitative interpretivist design was used to explore advanced practice nurses' perceptions on the value of wireless Personal Digital Assistant technologies to support their practice. METHODS: The data were collected using survey questionnaires and individual and focus group interviews with nurse practitioners, clinical nurse specialists and information technology managers based in British Columbia, Canada. An open-coding content analysis was performed using qualitative data analysis software. RESULTS: Wireless Personal Digital Assistant's use supports the principles of pervasivity and is a technology rapidly being adopted by advanced practice nurses. Some nurses indicated a reluctance to integrate wireless Personal Digital Assistant technologies into their practices because of the cost and the short technological life cycle of these devices. Many of the barriers which precluded the use of wireless networks within facilities are being removed. Nurses demonstrated a complex understanding of wireless Personal Digital Assistant technologies and gave good rationales for its integration in their practice. CONCLUSIONS: Nurses identified improved client care as the major benefit of this technology in practice and the type and range of tools they identified included clinical reference tools such as drug and diagnostic/laboratory reference applications and wireless communications. RELEVANCE TO CLINICAL PRACTICE: Nurses in this study support integrating wireless mobile computing technologies into their practice to improve client care.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".