Table 2.
Average cluster ratings compared between disciplines
| Cluster | Importance | Feasibility | ||||
|---|---|---|---|---|---|---|
| IMP experts | UCD experts | da | IMP experts | UCD experts | da | |
| 1. Access resources | 3.5 | 3.2 | 0.18 | 2.9 | 2.5 | 0.35* |
| 2. Promote leadership and collaboration | 3.9 | 3.8 | 0.05 | 3.5 | 3.3 | 0.17 |
| 3. Incentivize the innovation | 3.2 | 2.6 | 0.28* | 2.0 | 1.6 | 0.25 |
| 4. Monitor change | 3.8 | 3.4 | 0.31* | 3.4 | 3.0 | 0.33* |
| 5. Support providers | 3.6 | 2.9 | 0.50* | 3.8 | 2.9 | 0.68* |
| 6. Facilitate change | 4.0 | 3.8 | 0.19 | 4.0 | 3.6 | 0.28* |
| 7. Develop and test solutions rapidly | 3.0 | 3.7 | − 0.43* | 3.7 | 4.4 | − 0.65* |
| 8. Understand systems and context | 3.8 | 3.8 | − 0.01 | 4.0 | 4.1 | − 0.11 |
| 9. Consider user needs and experiences | 3.0 | 3.3 | − 0.27 | 3.5 | 4.1 | − 0.50* |
| 10. Co-design solutions | 3.8 | 4.1 | − 0.28* | 3.8 | 4.2 | − 0.32* |
Importance and feasibility values reflect the product of an expert panel (valid response n = 54) rating 66 discrete implementation and user-centered design strategies on a scale from 1 to 5. Comparisons based on F10,43 multivariate tests; * = p < 0.05
IMP experts implementation experts, UCD experts user-centered design experts
aCohen’s d effect size, also known as the standardized mean difference; calculated such that positive values reflect higher ratings by implementation experts and negative values reflect higher ratings by UCD experts; thresholds are d = 0.2 for small effect, d = 0.5 for medium effect, and d = 0.8 for large effect