Effect of implementation interventions on nurses’ behaviour in clinical practice: a systematic review, meta-analysis and meta-regression protocol
Bibliographic record
Abstract
BACKGROUND: Practitioner-level implementation interventions such as audit and feedback, communities of practice, and local opinion leaders have shown potential to change nurses' behaviour in clinical practice and improve patients' health. However, their effectiveness remains unclear. Moreover, we have a paucity of data regarding the use of theory in implementation studies with nurses, the causal processes-i.e. mechanisms of action-targeted by interventions to change nurses' behaviour in clinical practice, and the constituent components-i.e. behaviour change techniques-included in interventions. Thus, our objectives are threefold: (1) to examine the effectiveness of practitioner-level implementation interventions in changing nurses' behaviour in clinical practice; (2) to identify, in included studies, the type and degree of theory use, the mechanisms of action targeted by interventions and the behaviour change techniques constituting interventions and (3) to examine whether intervention effectiveness is associated with the use of theory or with specific mechanisms of action and behaviour change techniques. METHODS: We will conduct a systematic review based on the Cochrane Effective Practice and Organization of Care (EPOC) Group guidelines. We will search six databases (CINAHL, EMBASE, ERIC, PsycINFO, PubMed and Web of Science) with no time limitation for experimental and quasi-experimental studies that evaluated practitioner-level implementation interventions aiming to change nurses' behaviour in clinical practice. We will also hand-search reference lists of included studies. We will perform screening, full-text review, risk of bias assessment, and data extraction independently with the Covidence systematic review software. We will assess the quality of evidence using the GRADEpro software. We will code included studies independently for theory use (Theory Coding Scheme), mechanisms of action (coding guidelines from Michie) and behaviour change techniques (Behaviour Change Technique Taxonomy v1) with QSR International's NVivo qualitative data analysis software. Meta-analyses will be performed using the Review Manager (RevMan) software. Meta-regression analyses will be performed with IBM SPSS Statistics software. DISCUSSION: This review will inform knowledge users and researchers interested in designing, developing and evaluating implementation interventions to support nurses' behaviour change in clinical practice. Results will provide key insights regarding which causal processes-i.e. mechanisms of action-should be targeted by these interventions, and which constituent components-i.e. behaviour change techniques-should be included in these interventions to increase their effectiveness. SYSTEMATIC REVIEW REGISTRATION: The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD42019130446).
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| grok | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| opus | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | medium |
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 | 0.116 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".