Objectives: Our novel tool to standardise the evaluation of medicine acceptability was developed using observational data on medicines use measured in a paediatric population included for this purpose (0-14 years). Using this tool, any medicine may be positioned on a map and assigned to an acceptability profile. The present exploration aimed to verify its statistical reliability.
Methods: Permutation test has been used to verify the significance of the relationships among measures highlighted by the acceptability map. Bootstrapping has been used to demonstrate the accuracy of the model (map, profiles and scores of acceptability) regardless of variations in the data. Lastly, simulations of enlarged data sets (×2; ×5; ×10) have been built to study the model's consistency.
Key Findings: Permutation test established the significance of the meaningful pattern identified in the data and summarised in the map. Bootstrapping attested the accuracy of the model: high RV coefficients (mean value: 0.930) verified the mapping stability, significant Adjusted Rand Indexes and Jaccard coefficients supported clustering validity (with either two or four profiles), and agreement between acceptability scores demonstrated scoring relevancy. Regarding enlarged data sets, these indicators reflected a very high consistency of the model.
Conclusions: These results highlighted the reliability of the model that will permit its use to standardise medicine acceptability assessments.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5765461 | PMC |
| http://dx.doi.org/10.1111/jphp.12829 | DOI Listing |
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