Psychopharmacology · 2013
Demand curves for hypothetical cocaine in cocaine-dependent individuals.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод в очереди
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Bruner Natalie R, Johnson Matthew W
Аннотация
RATIONALE: Drug purchasing tasks have been successfully used to examine demand for hypothetical consumption of abused drugs including heroin, nicotine, and alcohol. In these tasks, drug users make hypothetical choices whether to buy drugs, and if so, at what quantity, at various potential prices. These tasks allow for behavioral economic assessment of that drug's intensity of demand (preferred level of consumption at extremely low prices) and demand elasticity (sensitivity of consumption to price), among other metrics. However, a purchasing task for cocaine in cocaine-dependent individuals has not been investigated.
OBJECTIVES: This study examined a novel Cocaine Purchasing Task and the relation between resulting demand metrics and self-reported cocaine use data.
METHODS: Participants completed a questionnaire assessing hypothetical purchases of cocaine units at prices ranging from $0.01 to $1,000. Demand curves were generated from responses on the Cocaine Purchasing Task. Correlations compared metrics from the demand curve to measures of real-world cocaine use.
RESULTS: Group and individual data were well modeled by a demand curve function. The validity of the Cocaine Purchasing Task was supported by a significant correlation between the demand curve metrics of demand intensity and O max (determined from Cocaine Purchasing Task data) and self-reported measures of cocaine use. Partial correlations revealed that after controlling for demand intensity, demand elasticity and the related measure, P max, were significantly correlated with real-world cocaine use.
CONCLUSIONS: Results indicate that the Cocaine Purchasing Task produces orderly demand curve data, and that these data relate to real-world measures of cocaine use.
OBJECTIVES: This study examined a novel Cocaine Purchasing Task and the relation between resulting demand metrics and self-reported cocaine use data.
METHODS: Participants completed a questionnaire assessing hypothetical purchases of cocaine units at prices ranging from $0.01 to $1,000. Demand curves were generated from responses on the Cocaine Purchasing Task. Correlations compared metrics from the demand curve to measures of real-world cocaine use.
RESULTS: Group and individual data were well modeled by a demand curve function. The validity of the Cocaine Purchasing Task was supported by a significant correlation between the demand curve metrics of demand intensity and O max (determined from Cocaine Purchasing Task data) and self-reported measures of cocaine use. Partial correlations revealed that after controlling for demand intensity, demand elasticity and the related measure, P max, were significantly correlated with real-world cocaine use.
CONCLUSIONS: Results indicate that the Cocaine Purchasing Task produces orderly demand curve data, and that these data relate to real-world measures of cocaine use.