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Record W2569514613 · doi:10.4018/ijtd.2017010101

Using an Extended Theory of Planned Behavior to Study Nurses' Adoption of Healthcare Information Systems in Nova Scotia

2017· article· en· W2569514613 on OpenAlexafffundabout
Princely Ifinedo

Bibliographic record

VenueInternational Journal of Technology Diffusion · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsCape Breton University
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCape Breton University
KeywordsNova scotiaTheory of planned behaviorHabitNorm (philosophy)PsychologyAnxietyHealth careApplied psychologyKnowledge managementSocial psychologyComputer sciencePolitical scienceSociologyControl (management)

Abstract

fetched live from OpenAlex

This study used the theory of planned behavior (TPB), which was extended to include relevant constructs such as computer self-efficacy, anxiety and habit, to investigate registered nurses' (RNs') adoption of healthcare information systems (HIS) in Nova Scotia, Canada. An analysis of data collected from 197 RNs in a cross-sectional survey showed that their attitudes towards HIS were positively impacted by computer self-efficacy and computer anxiety (lack thereof). RNs' attitudes toward HIS and facilitating organizational conditions significantly influenced intentions to use HIS at work. Contrary to prediction, subjective norm did not influence RNs' intentions to use HIS in the research setting. Computer habit mattered for RNs' acceptance of HIS. Information from the study benefits the management of RNs' HIS use in Nova Scotia, in particular, and comparable parts of Canada and the world.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.116
GPT teacher head0.443
Teacher spread0.327 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2017
Admission routes3
Has abstractyes

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