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基于综合风险因素指数评分的药物滥用预防资金资源分配算法:佛罗里达州案例研究——第二部分

Algorithms for resource allocation of substance abuse prevention funds based on composite risk-factor index score: a case study on state of Florida--Part 2.

作者信息

Kim S, Wurster L, Williams C, Hepler N

机构信息

DataBase ER, Inc., Tampa, Florida, USA.

出版信息

J Drug Educ. 1998;28(3):169-84. doi: 10.2190/0HRM-1X1W-HV36-WAEG.

Abstract

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. A comparison of three models for resource allocation has shown a significant amount of similarity of the total funds computed for each county. Accordingly, no preference is made among the resource allocation models suggested, although it is emphasized that the final decision concerning the level of funding must be made on the selection of the resource allocation algorithms rather than the suggested amount of funding computed for each county.

摘要

第二部分的目的是开发一种模型,用于将州预防资金分配给其下属辖区,分配依据是根据为每个县计算的综合风险因素指数(COMRISK)得分衡量的预防服务相对需求。风险因素是从对预防文献中涉及的风险和保护因素的广泛审查中提取的。基于确定的22个风险和保护因素,我们能够解释在个体层面观察到的学生药物使用行为总变异的71.3%。通过将个体COMRISK得分汇总到县一级,我们能够确定县一级的汇总COMRISK指数得分。通过确定每个县在全州COMRISK总量中所占的比例,并根据每个县的人口规模对后一比例进行加权,我们基于每个县的风险设计了预防需求指数(PNI)得分。最后,计算每个县的PNI得分占全州PNI总得分的比例。然后将后一比例乘以该州可用的预防资源总量。通过这种方式,我们能够开发一种仅基于风险和保护因素的替代资源分配模型,以确定每个县的预防需求,而不依赖于第一部分中提出的药物使用综合指数得分(COMDRUG)。对三种资源分配模型的比较表明,为每个县计算的总资金有很大的相似性。因此,在建议的资源分配模型之间没有偏好,不过需要强调的是,关于资金水平的最终决定必须基于资源分配算法的选择,而不是为每个县计算的建议资金量。

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