Validity of a demand curve measure of nicotine reinforcement with adolescent smokers

Abstract

High or inelastic demand for drugs is central to many laboratory and theoretical models of drug abuse, but it has not been widely measured with human substance abusers. The authors used a simulated cigarette purchase task to generate a demand curve measure of nicotine reinforcement in a sample of 138 adolescent smokers. Participants reported the number of cigarettes they would purchase and smoke in a hypothetical day across a range of prices, and their responses were well-described by a regression equation that has been used to construct demand curves in drug self-administration studies. Several demand curve measures were generated, including breakpoint, intensity, elasticity, P_max, and O_max. Although simulated cigarette smoking was price sensitive, smoking levels were high (8+ cigarettes/day) at prices up to 50¢ per cigarette, and the majority of the sample reported that they would purchase at least 1 cigarette at prices as high as $2.50 per cigarette. Higher scores on the demand indices O_max (maximum cigarette purchase expenditure), intensity (reported smoking level when cigarettes were free), and breakpoint (the first price to completely suppress consumption), and lower elasticity (sensitivity of cigarette consumption to increases in cost), were associated with greater levels of naturalistic smoking and nicotine dependence. Greater demand intensity was associated with lower motivation to change smoking. These results provide initial support for the validity of a self-report cigarette purchase task as a measure of economic demand for nicotine with adolescent smokers.

Introduction

Behavioral economic theories of addiction view substance dependence as a state in which the reinforcing efficacy of drugs is high in comparison to the reinforcing efficacy of other activities that are available in an individual's environment (e.g., Loewenstein, 1999, Rachlin, 1997, Murphy et al., 2009a, Murphy et al., 2009b). Within this behavioral economic framework, demand curves have been used to describe the reinforcement efficacy of a drug or a specific dose of a drug within a specific context (Bickel et al., 2000). Demand curves plot consumption of a drug across a range of response costs or “prices,” and have demonstrated utility in preclinical research aimed at assessing the abuse liability of drugs or response to an experimental manipulation (for a review, see Hursh and Silberberg, 2008).

Recently several investigators have developed cost-efficient measures of drug demand that do not involve actual drug consumption and therefore can be administered in clinical settings in which actual drug consumption is prohibited or inadvisable. Hypothetical drug purchase tasks are modeled after laboratory drug self-administration procedures, but use hypothetical choices between drug and monetary amounts that are analogous to the choices participants would make in a laboratory drug administration procedure (Griffiths et al., 1996, Jacobs and Bickel, 1999, Petry and Bickel, 1998). For example, the initial question may assess drug or alcohol purchases at zero cost per unit (e.g., a single cigarette or alcoholic beverage), with subsequent questions gradually increasing in price up to a level at which consumption is drastically suppressed (e.g., $5 for a cigarette). The reported purchases can then be used to generate an individual's demand curve for the substance: a quantitative representation of their estimated consumption across a range of prices. Several reinforcement indices can be generated from demand curves, including demand intensity (number of cigarettes or drinks consumed when price = 0), O_max (maximum expenditure), P_max (the price at which demand become elastic), breakpoint (the price which completely suppresses consumption) and elasticity (the rate of decrease in consumption as a function of price).

Advantages of these tasks are their close resemblance to the laboratory tasks after which they are modeled and their ability to yield precise quantitative measures of participants’ choices (demand curves; Jacobs and Bickel, 1999). Simulation procedures have been widely used in experimental economics (Camerer, 1999), and in behavioral economic studies of addiction. For example, over 20 published studies provide strong support for the reliability, validity, and utility of the hypothetical delayed reward discounting (DRD) task with a variety of human populations (see Green and Myerson, 2004 for a review). Specifically, results suggest that although an individual's absolute level of discounting may vary across real versus hypothetical discounting paradigms, the relative level of discounting across paradigms is similar, as are the relations with naturalistic drug use (Madden et al., 2004). Although only a few studies have examined hypothetical purchase tasks, one study found a high degree of correspondence between choices on a hypothetical alcohol purchase task and actual laboratory based demand for alcohol (MacKillop et al., 2010a), and another study found that the reported consumption values and reinforcement metrics derived from a hypothetical alcohol purchase task demonstrated good to excellent test–retest reliability (Murphy et al., 2009b).

Although preclinical laboratory demand curve analyses have typically evaluated the reinforcing efficacy of several drug types or doses (Winger et al., 2002), hypothetical drug purchase tasks can assess potentially meaningful individual differences in susceptibility to drug reinforcement. In this context, economic demand may reflect strength of desire for drugs (i.e., motivational salience of drugs), and may vary across individuals, or within an individual over time or across contexts. The demand metrics may thus have clinical utility (MacKillop et al., 2010b); individual differences in consumption and expenditures on a simulated drug purchase task might capture important variability in the extent to which individuals value a substance. Although it is possible to obtain self reports of actual drug use and expenditures in the natural environment, which have been shown to predict substance use outcomes (e.g., Roddy and Greenwald, 2009, Tucker et al., 2009), advantages of simulation tasks include the ability to control for contextual influences on consumption through the use of a standard scenario and to model aspects of consumption that would be difficult to capture using naturalistic patterns of drug use and expenditures (Jacobs and Bickel, 1999). MacKillop and Murphy (2007) found that heavy drinkers who reported greater alcohol consumption and expenditures on a hypothetical alcohol purchase task were less likely to reduce their consumption in response to a brief motivational intervention. This study provided support for the validity and clinical utility of purchase tasks as a measure of strength of substance-related reinforcement.

The present study evaluated the initial construct validity of a Cigarette Purchase Task (CPT) among adolescent smokers. The CPT is a self-report measure of hypothetical cigarette purchases as a function of escalating prices. Estimated consumption at escalating prices can be modeled as a smoking demand curve from which various indices of smoking reinforcement can be derived. Jacobs and Bickel (1999) initially examined the validity of a CPT in a sample of nicotine- and heroin-dependent adults. They found that as price increased, self-reported consumption decreased, associated expenditures exhibited the characteristic inverted U-shaped curve (i.e., expenditures were low when price was low, increased at moderate prices, then decreased at very high prices), and that the data conformed with a quantitative model used in previous drug administration studies (Hursh and Silberberg, 2008). MacKillop et al. (2008) provided further support for the validity of the CPT in a small pilot study of 33 adult smokers. They found that the CPT exhibited strong convergent and divergent validity; most indices were significantly positively associated with nicotine-related variables (i.e., cigarettes/day, nicotine dependence), with the strongest relationships demonstrated between baseline smoking rate and dependence and intensity of demand and O_max.

The aim of the current study was to replicate and extend these findings with a sample of adolescent smokers. First, we were interested in characterizing the impact of cigarette price on adolescent smoking. Although epidemiological data attest to the price sensitivity of adolescent smoking initiation, smoking level, and smoking cessation (Chaloupka, 2003, Powell et al., 2005), the CPT allows for a more thorough investigation of reported demand for cigarettes across a wide range of prices, and also for the exploration of individual difference variables associated with price sensitivity, than is possible with epidemiological data on cigarette demand. Specifically, we investigated the ability of the CPT to generate prototypic demand curve data and the relationships between CPT variables and baseline smoking rate and nicotine dependence level. We also sought to examine the relationship between demand and motivation to change smoking. In this case, we hypothesized that the CPT demand measures would be negatively related to motivation to change smoking. Individuals for whom smoking is a more potent reinforcer will express less interest in reducing their smoking.