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Record W2938930785 · doi:10.1371/journal.pone.0215153

Validating the Alberta Context Tool in a multi-site Australian Emergency Department nurse population

2019· article· en· W2938930785 on OpenAlexaffabout
Verena Schadewaldt, Benjamin McElduff, Catherine D’Este, Elizabeth McInnes, Simeon Dale, Anoja W. Gunaratne, Janet E. Squires, Dominique A. Cadilhac, Sandy Middleton

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersMedical Research CouncilNational Health and Medical Research CouncilAustralian Catholic University
KeywordsCronbach's alphaConfirmatory factor analysisExploratory factor analysisIntraclass correlationEmergency departmentContext (archaeology)PopulationPsychologyHealth careMedicineClinical psychologyFamily medicineNursingPsychometricsStatisticsStructural equation modelingEnvironmental healthMathematics

Abstract

fetched live from OpenAlex

The organisational context of healthcare settings has an essential role in how research evidence is used in clinical practice. The Alberta Context Tool (ACT) measures 10 concepts of organisational context with higher scores indicating a more positive work environment and potentially better use of research evidence in patient care. We assessed the psychometric properties of the ACT in Emergency Departments (EDs). This validation study was conducted as part of a multi-centre trial of triage, treatment and transfer (T3 Trial) of patients with stroke admitted to EDs. Stratified sampling with proportional allocation was used to recruit ED nurses from 26 participating hospitals at baseline. Nurses completed a survey containing the ACT. Structural validity was investigated by exploratory and confirmatory factor analysis. Reliability was assessed using Cronbach's alpha and intraclass correlation coefficients. Item-rest correlations and the average inter-item correlations were also assessed. 558 ED nurses completed the survey, comprised of 433 surveys without missing data. Our exploratory factor analysis produced a 14-factor structure, explaining 62% of variance of organisational context. For eight of ten concepts, item loadings matched the factor structure of the original ACT. Confirmatory factor analysis of the 10 ACT concepts showed moderate model fit (p = 0.001, root mean square error of approximation: 0.049, standardised root mean squared residual: 0.048). Cronbach's alphas showed very good internal consistency for nine of ten ACT concepts (α>0.7; 0.45-0.90). Item-rest correlations indicated that most ACT items (50 of 56 items) within any concept related well to the total score of the concept. Average inter-item correlations indicated potential redundant items for three concepts (feedback processes, leadership, staffing) that were above the threshold of 0.5. While identifying a few shortcomings for some ACT concepts in an ED context, the majority of findings confirm reliability and validity of the original ACT in an Australian population of ED 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 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)0.024
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.042
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.559
GPT teacher head0.578
Teacher spread0.019 · 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.

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
Published2019
Admission routes2
Has abstractyes

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