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Supporting Evidence-Based Practice for Nurses through Information Technologies

2009· article· en· W2103914455 on OpenAlexaffabout
Diane Doran, R. Brian Haynes, André Kushniruk, Sharon E. Straus, Jeremy Grimshaw, Linda M. Hall, Adam Dubrowski, Tammie Di Pietro, Kristine Newman, Joan Almost, Ha Nguyen, Dawn Jedras

Bibliographic record

VenueWorldviews on Evidence-Based Nursing · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsMcMaster UniversityUniversity of VictoriaUniversity of CalgaryUniversity of OttawaMinistry of Health and Long Term CareUniversity of Toronto
Fundersnot available
KeywordsEvidence-based practiceKnowledge managementNursingPsychologyMedicineComputer scienceAlternative medicine

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate the usability of mobile information terminals, such as personal digital assistants (PDAs) or Tablet personal computers, to improve access to information resources for nurses and to explore the relationship between PDA or Tablet-supported information resources and outcomes. BACKGROUND: The authors evaluated an initiative of the Nursing Secretariat, Ontario Ministry of Health and Long-Term Care, which provided nurses with PDAs and Tablet PCs, to enable Internet access to information resources. Nurses had access to drug and medical reference information, best practice guidelines (BPGs), and to abstracts of recent research studies. METHOD: The authors took place over a 12-month period. Diffusion of Innovation theory and the Promoting Action on Research Implementation in Health Services (PARIHS) model guided the selection of variables for study. A longitudinal design involving questionnaires was used to evaluate the impact of the mobile technologies on barriers to research utilization, perceived quality of care, and on nurses' job satisfaction. The setting was 29 acute care, long-term care, home care, and correctional organizations in Ontario, Canada. The sample consisted of 488 frontline-nurses. RESULTS: Nurses most frequently consulted drug and medical reference information, Google, and Nursing PLUS. Overall, nurses were most satisfied with the Registered Nurses Association of Ontario (RNAO) BPGs and rated the RNAO BPGs as the easiest resource to use. Among the PDA and Tablet users, there was a significant improvement in research awareness/values, and in communication of research. There was also, for the PDA users only, a significant improvement over time in perceived quality of care and job satisfaction, but primarily in long-term care settings. IMPLICATIONS: It is feasible to provide nurses with access to evidence-based practice resources via mobile information technologies to reduce the barriers to research utilization.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.197
metaresearch head score (Gemma)0.493
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.197
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1970.493
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0130.012
Science and technology studies0.0030.004
Scholarly communication0.0190.011
Open science0.0080.009
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0090.002

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 head0.253
GPT teacher head0.569
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
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

Citations75
Published2009
Admission routes2
Has abstractyes

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