Are multifaceted interventions more effective than single-component interventions in changing health-care professionals' behaviours? An overview of systematic reviews
Bibliographic record
Abstract
BACKGROUND: One of the greatest challenges in healthcare is how to best translate research evidence into clinical practice, which includes how to change health-care professionals' behaviours. A commonly held view is that multifaceted interventions are more effective than single-component interventions. The purpose of this study was to conduct an overview of systematic reviews to evaluate the effectiveness of multifaceted interventions in comparison to single-component interventions in changing health-care professionals' behaviour in clinical settings. METHODS: The Rx for Change database, which consists of quality-appraised systematic reviews of interventions to change health-care professional behaviour, was used to identify systematic reviews for the overview. Dual, independent screening and data extraction was conducted. Included reviews used three different approaches (of varying methodological robustness) to evaluate the effectiveness of multifaceted interventions: (1) effect size/dose-response statistical analyses, (2) direct (non-statistical) comparisons of multifaceted to single interventions and (3) indirect comparisons of multifaceted to single interventions. RESULTS: Twenty-five reviews were included in the overview. Three reviews provided effect size/dose-response statistical analyses of the effectiveness of multifaceted interventions; no statistical evidence of a relationship between the number of intervention components and the effect size was found. Eight reviews reported direct (non-statistical) comparisons of multifaceted to single-component interventions; four of these reviews found multifaceted interventions to be generally effective compared to single interventions, while the remaining four reviews found that multifaceted interventions had either mixed effects or were generally ineffective compared to single interventions. Twenty-three reviews indirectly compared the effectiveness of multifaceted to single interventions; nine of which also reported either a statistical (dose-response) analysis (N = 2) or a non-statistical direct comparison (N = 7). The majority (N = 15) of reviews reporting indirect comparisons of multifaceted to single interventions showed similar effectiveness for multifaceted and single interventions when compared to controls. Of the remaining eight reviews, six found single interventions to be generally effective while multifaceted had mixed effectiveness. CONCLUSION: This overview of systematic reviews offers no compelling evidence that multifaceted interventions are more effective than single-component interventions.
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 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 | 0.050 | 0.155 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.017 |
| Bibliometrics | 0.024 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".