Cigarette smoking accounts for over 430,000 deaths annually in the U.S. 
and is responsible for over 5 million fatalities per year worldwide 
. Efforts to educate the public about the hazards of smoking have been ongoing since they were first identified 
. These efforts along with restrictions on advertising and locations where people can smoke have steadily reduced the prevalence of smoking in the U.S. from a high of 42% in 1965 to about 20% in most recent surveys 
. In addition, rates of initiation in adolescents have declined, thereby reducing the recruitment of new smokers to the population 
. Despite these successes, the rate of quitting smoking in recent years has declined and, although many try to quit, only about 5% are successful annually 
. As a result of this and a growing population, there are almost as many smokers in the U.S. today as there were at the height of the epidemic in the 1960’s. Clearly, in order to continue reducing smoking prevalence, greater efforts will be needed to reach smokers who fail to quit.
One effort by the U. S. government to encourage quitting has been to place textual warnings about the hazards of smoking on the sides of cigarette packs. Although such warnings have been in place in the U.S. since 1965, they have not changed since 1984 and are easy to ignore 
. In an effort to increase the effectiveness of these warnings, recent legislation empowers the U. S. Food and Drug Administration (FDA) to impose larger pictorial warnings on the front and back of cigarette packs similar to those that were first introduced in Canada and elsewhere. Research indicates that these enhanced warnings not only draw the smoker’s attention but also succeed in creating aversive emotional reactions to the prospect of smoking 
. In addition, studies of the effects of introducing pictorial warnings in Australia and the UK indicate that they increase smokers’ thoughts about
These findings have led researchers and policy makers to conclude that the warnings work, despite the lack of direct evidence that they increase quit rates 
. Indeed, research conducted to evaluate immediate effects of pictorial warnings in the U.S. indicates that the warnings seldom change intentions to quit 
. A large FDA test of 36 different pictorial warning labels presented to two age groups of smokers (18–24 vs. 25+) revealed that out of 72 tests, only 6 increased intentions to try to
. A smaller replication with fewer warnings but larger sample sizes per condition found that, although pictorial warnings enhanced smokers’ aversion to smoking, they produced no overall effects on intentions to try to quit in the near future 
Intentions are important because they are critical precursors to behavior change 
. Unless a smoker strongly intends to quit, it will be difficult, if not impossible, to overcome the cravings and withdrawal symptoms that maintain this addictive habit 
. Indeed, models of health behavior change, such as Protection Motivation Theory (PMT) 
, the Health Belief Model (HBM) 
, and the Theory of Reasoned Action (TRA) 
, predict that intentions should increase as the perceived risks of smoking increase. Nevertheless, although pictorial warnings encourage smokers to think about quitting
, the warnings do not appear to enhance the likelihood that the average smoker will actually try to quit. Thus, the failure of warnings to influence intentions poses a paradox for any theory that assumes that people act in their own best interests, especially when they recognize threats to those interests.
Recent neuroscience research provides insight into the paradoxical effects of warning labels. This research has identified two neuropsychological systems that influence the development of an addiction and that explain why smoking cessation is difficult. First, ingestion of nicotine, the addictive drug in tobacco, alters the mesocorticolimbic dopamine system that controls expectations of reward 
. Over time, these expectations become conditioned to the act of smoking itself, thus making the person who smokes sensitive to any cues associated with the act and enhancing the desire to smoke when exposed to them 
. Second, repeated acts of smoking transfer control over the habit to dorsal striatal circuits that undermine prefrontal control 
and that turn the habit into a compulsion, leaving the smoker with reduced sense of control over the behavior 
. Although this description of the two systems is necessarily abbreviated, it is clear that these changes in the reward and control systems make it difficult for the addict to resist the pull of smoking cues and the craving elicited by them. Thus, despite the desire to quit that most smokers report 
, their perceived efficacy to do so is lacking. This conflict between desire and efficacy often leaves smokers without sufficient motivation and, hence, intention to quit the habit.
In view of the powerful neuropsychological processes identified by neuroscience research, we translated those insights into a behavioral decision making model that can account for the paradoxical finding that despite enhancing desires to quit, warnings do not appear to change intentions to do so. We first describe the model and then present a test of its major predictions.
A Model of Intentions to Quit an Addictive Behavior such as Smoking
The efficacy-desire model (EDM) proposes that the intention to quit smoking (Iq
) is a function of the difference between the motivation to smoke (Ms
) and the motivation to quit (Mq
The focus on these competing motivations is not novel; other models of health behavior change, such as PMT 
and the HBM 
, suggest that intending to quit an unhealthy behavior is a function of influences on these competing motivations. Indeed, any theory of rational choice suggests that all the smoker needs in order to quit is more desire to do so than to continue smoking 
The distinction between the motivations stems from the reward system’s powerful influence on goal seeking 
and its circuits specialized for detecting both harmful (negative) and beneficial (positive) environments 
. These circuits produce corresponding forms of negative and positive affect that, respectively, underlie desires to avoid or approach such objects as cigarettes 
. Although these desires are often reciprocally related, they are independent sources of motivation that can have unique influences and effects.
In addition to the essential role of desires, the EDM recognizes that motivation is also determined by the perceived efficacy to satisfy desires. Self-efficacy is a familiar concept that has long been featured in models of behavior change 
. In regard to smoking, even if smokers desire to quit the habit, they are unlikely to try unless they believe that they can implement the behavior. Neuroscience models of addiction also focus on self-efficacy by emphasizing the important role of the brain’s control system in undermining the ability to quit an addiction. Theories of behavior change, such as the TRA (15), treat desires (e.g., attitudes) and efficacy as additive influences on intentions. However, because both efficacy and desire are needed to motivate behavior, the EDM treats these expectancies and desires as multiplicative determiners of motivation, a common assumption in psychological models of motivation 
. Thus, inserting the respective efficacies (Eq, Es
) and desires (Dq, Ds
) for quitting and smoking into eq. (1) produces:
For an addiction such as smoking, both components of Ms
are likely to be high. Indeed, the more one practices a behavior, the greater the skill and sense of efficacy for controlling it 
. The same is unfortunately not the case for quitting. Even if the smoker wants to quit (Dq
), no motivation and hence intention will be formed unless the smoker’s sense of efficacy (Eq
) is also high. As is often the case for addictive habits 
, the smoker may strongly desire to quit but not believe that it is possible to do so. However, in deriving predictions from this model, it is important to consider individual differences in the various components of the model and the ways in which they are related to each other.
shows the relations between the components of the model at the individual level. Although desire and efficacy to engage in a behavior are likely to be positively related, we show no relation between Ds
under the assumption that Es
has reached asymptote in most smokers, leaving little room for any relation with Ds
. However, for quitting
an addictive habit, such as smoking, the relation between efficacy and desire to quit is likely to be negative. Efficacy for quitting the behavior is at its peak in the early stages of acquiring the habit, usually in adolescence, when the young smoker believes he or she will not have much difficulty stopping 
. However, as the habit progresses, the smoker finds it increasingly difficult to stop even if the desire to do so increases. This process creates an inverse relation between Eq
Efficacy-Desire Model of quit intentions showing relations between components of the model as they relate to the reward and control systems of addiction models.
Neuroscience models of addiction specifically predict that greater frequency of smoking (represented in by parameter β) reduces Eq while it simultaneously increases Ds. It is also likely that frequency of smoking increases Dq, given what we know about smokers’ wishes to quit. But even leaving this out of the model, neuroscience models of addiction predict that the more one smokes, the lower one’s quit-efficacy (hence lower Mq) and the greater one’s desire to continue smoking (hence higher Ms). This disparity between Mq and Ms makes it difficult for the smoker to quit and shows why smokers are so conflicted by their addiction, wishing to quit but nevertheless continuing the habit.
The model makes interesting predictions regarding the effects of a warning, which, based on what we know about their effects 
, should increase Dq
and reduce Ds
. shows such a warning (whose intensity is indicated by parameter α
) directly affecting Dq
. Because Dq
are inversely related, the effect on Dq
in eq. (2) with eq. (3) shows that the model makes the novel prediction that for an addictive habit, Mq
is an inverted U-shape function of Eq
That is, assuming that individual differences in Eq range from negative to positive valence, Mq rises as Eq increases, but at an intermediate point, begins to decline. Although theories of behavior change predict that efforts to change behavior increase as efficacy increases, the EDM suggests that, for an addictive habit, this effect only holds up to a point, after which the motivation to do so declines. Furthermore, whether the habit is addictive or not, the effect of α depends on Eq, with an enhanced effect for positive values of Eq and a depressed effect for negative values of Eq.
The path linking Ds
in suggests that these desires should be inversely related. However, consistent with a bivalent model of affect 
, we assume that these desires are somewhat independent. Hence, the effect of the warning on Ds
Eq. (4) expresses the intuitive result that Ds
is positively related to the heaviness of the habit (β
) and inversely related to the strength of the warning (α
). Inserting eqs. (3) and (4) into eq. (2) yields the following overall relationship between Iq
and the respective efficacies for quitting and smoking:
We show examples of the hypothetical relation between Iq
for different values of α
in , assuming that Es
are constant and that Es
is higher on average than Eq (.5 vs. 0).
The inverted U-shape relation is especially apparent when α
0. This shows that persons who smoke will have equally weak intentions to quit smoking not only when their efficacy is low but also when it is high. Indeed, absent any health warnings, smokers will have the greatest intentions to quit when their efficacy is at a moderate level. The prediction that low efficacy produces low intentions is not surprising since most theories expect this result. However, the model also predicts that those who think they can quit easily will not be motivated to do so either. This is a critical prediction of the model that will be tested for the first time in the present research.
Relations between intention to quit smoking (Iq) and quit efficacy (Eq) by three levels of warning intensity (α) scaled from 0, .5. to 1.0.
A second critical prediction of the model is the effect of the warning. As seen in , the effect of α
primarily increases the intention to quit among those with
That is the point in the relation where all three curves in converge. Indeed, those with weaker Eq
actually begin to exhibit a reduction
in quit intention. Thus, the model makes the counterintuitive prediction that those with the strongest desires to quit (i.e., those who have smoked the longest) will be least motivated to respond rationally to warnings about the hazards of their habit, and this will be the case despite the fact that their response to the warning (created by an increase in α
) is just as strong as the response among those with weaker desires to quit. This may explain the paradoxical effects of warnings observed in previous research. The quit-enhancing effects of increases in α
will primarily be observed among those whose efficacy for quitting exceeds their efficacy for smoking. Indeed, warnings for those with weak efficacy for quitting will actually result in weaker intentions to quit.
We tested the major predictions of the model in an experimental context in which smokers were randomly assigned to see one example of a pack of cigarettes with a warning that was varied systematically in intensity across experimental conditions. This provided the opportunity to observe the effects of a warning in the context of individual differences in both the efficacy and desire components of the model. In addition to the predicted U-shape function shown in , we tested the prediction that increases in the intensity of warnings (represented by α) produced by adding an emotionally charged picture will lead to divergent effects on Iq depending on Eq. In addition, the EDM predicts that the greater the amount smoked (β), the lower the intention to quit. However, variation in β should only shift the curve up or down (it should be independent of Eq and α), and it should only interact with Es, which we assume is at a high and relatively fixed level for all smokers. In addition, as shown in , frequency of smoking should be inversely related to Eq but positively related to Ds. Finally, in support of the expected inverse relation between Eq and Dq, length of time smoking (using age of the smoker as a proxy) should be positively related to Dq but negatively related to Eq.