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Record W1662793467 · doi:10.1371/journal.pone.0127405

Reliability and Validity of the Alberta Context Tool (ACT) with Professional Nurses: Findings from a Multi-Study Analysis

2015· article· en· W1662793467 on OpenAlexafffundabout
Janet E. Squires, Leslie A. Hayduk, Alison M. Hutchinson, Ranjeeta Mallick, Peter Norton, Greta G. Cummings, Carole A. Estabrooks

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of CalgaryUniversity of AlbertaUniversity of OttawaOttawa Hospital
FundersCanadian Institutes of Health Research
KeywordsCronbach's alphaContext (archaeology)Confirmatory factor analysisReliability (semiconductor)PsychologyValidityPredictive validityHealth careApplied psychologyPsychometricsClinical psychologyStructural equation modelingStatisticsGeographyMathematics

Abstract

fetched live from OpenAlex

Although organizational context is central to evidence-based practice, underdeveloped measurement hinders its assessment. The Alberta Context Tool, comprised of 59 items that tap 10 modifiable contextual concepts, was developed to address this gap. The purpose of this study to examine the reliability and validity of scores obtained when the Alberta Context Tool is completed by professional nurses across different healthcare settings. Five separate studies (N = 2361 nurses across different care settings) comprised the study sample. Reliability and validity were assessed. Cronbach's alpha exceeded 0.70 for 9/10 Alberta Context Tool concepts. Item-total correlations exceeded acceptable standards for 56/59 items. Confirmatory Factor Analyses coordinated acceptably with the Alberta Context Tool's proposed latent structure. The mean values for each Alberta Context Tool concept increased from low to high levels of research utilization(as hypothesized) further supporting its validity. This study provides robust evidence for reliability and validity of scores obtained with the Alberta Context Tool when administered to professional nurses.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.536

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 communication0.0000.000
Open science0.0000.000
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 head0.089
GPT teacher head0.310
Teacher spread0.221 · 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

Citations40
Published2015
Admission routes3
Has abstractyes

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