Validating the Alberta Context Tool in a multi-site Australian Emergency Department nurse population
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".