MétaCan
Menu
Back to cohort

The Use of Personal Digital Assistants at the Point of Care in an Undergraduate Nursing Program

2006· article· en· W2069316822 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCIN Computers Informatics Nursing · 2006
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsOntario Tech UniversityDurham College
Fundersnot available
KeywordsBachelorPersonal computerNursingMedical educationControl (management)Sample (material)MedicinePsychologyComputer science

Abstract

fetched live from OpenAlex

This study examined the relationships between the use of personal digital assistants and self-efficacy and the preparation for medication administration among second-year Bachelor of Science in Nursing students in a medical-surgical clinical environment. By using a controlled experimental method, the study attempted to support claims about the educational benefits of personal digital assistants which have generally been reported in more descriptive and anecdotal formats. The sample consisted of 36 students, of which two groups had personal digital assistants and two groups served as a control. The control groups were provided with paper resources equivalent to the software provided by the personal digital assistants. Findings showed a significant increase in self-efficacy in the groups with personal digital assistants.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.280
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it