The purpose of Part 2 is to develop a model for resource allocation of state prevention funds to be distributed to its substate jurisdictions based on the relative need for prevention services measured in terms of composite risk-factor index (COMRISK) scores computed for each county.
The risk factors are extracted from an extensive review of risk and protective factors addressed in the prevention literature.
Based on twenty-two risk and protective factors identified, we were able to explain 71.3 percent of the total variation in student drug using behavior observed at the individual level.
By aggregating individual COMRISK scores to the county level, we were able to determine aggregated COMRISK index scores at the county level.
By determining the proportion of each county's share of the total statewide COMRISK and by weighting the latter proportion by the population size of each county, we have devised Prevention Needs Index (PNI) score based on the risks for each county.
Finally, the county's share of PNI score as a proportion of the total statewide PNI score is computed.
The latter proportion is then multiplied by the total amount of prevention resources available at the state.
In this way, we were able to develop an alternative resource allocation model solely based on risk and protective factors for determining prevention needs of each county, independent of composite index score of drug use (COMDRUG) presented in Part 1. (...)
Mots-clés Pascal : Prévention, Toxicomanie, Facteur risque, Modèle, Algorithme, Allocation ressource, Floride, Etats Unis, Amérique du Nord, Amérique, Santé mentale, Homme
Mots-clés Pascal anglais : Prevention, Drug addiction, Risk factor, Models, Algorithm, Resource allocation, Florida, United States, North America, America, Mental health, Human
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 99-0028637
Code Inist : 002B18H05A. Création : 31/05/1999.