Using the behavior change technique ontology to characterize the content of implementation strategies: a secondary analysis of 151 trials targeting evidence-based nursing practice
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Bibliographic record
Abstract
BACKGROUND: Implementation strategies are essential for translating evidence into routine clinical practice. Their effectiveness depends on specifying and deploying behavior change techniques (BCTs): observable, irreducible components that target determinants of clinician behavior. The Behavior Change Technique Ontology (BCTO) standardizes the identification and labeling of BCTs, yet it has been applied only sparingly in implementation research to date. PURPOSE: To characterize the nature and extent of BCTs explicitly reported or retrospectively identified in implementation trials that targeted evidence-based nursing practice. METHODS: In this secondary analysis of a prior systematic review, we coded BCTs across 151 implementation trials with a manual derived from the 281-item BCTO. One to two coders per study applied coding rules in NVivo; disagreements were resolved by consensus. Feasibility indicators included coder certainty ("Definitely" vs "Probably" present) and the need for extra coding rules. RESULTS: Trials contained 907 BCT instances: 857 in intervention arms, 50 in controls. We identified 100 of the BCTO's 281 techniques (35.6%), spanning 17 of its 20 parent groups. Intervention arms featured a median of four BCT instances (IQR 3-7) and four unique BCTs (IQR 3-5). The five most common BCTs were Instruct how to perform behavior (n = 273), Arrange informational support (n = 127), Deliver informational support (n = 83), Demonstrate behavior (n = 62), and Practice behavior (n = 43). Only 37% of BCT instances were coded with high certainty, and 17 supplementary decision rules were required for consistent coding. CONCLUSIONS: Implementation strategies targeting nursing practice rely on instructional and informational BCTs, with limited use of goal-directed, feedback-intensive or context-altering techniques that could enhance impact. CLINICAL TRIAL INFORMATION: The Clinical Trials Registration PROSPERO CRD42019130446.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it