National Academies Press: OpenBook

Public Health Consequences of E-Cigarettes (2018)

Chapter: 8 Dependence and Abuse Liability

« Previous: 7 Modes of Action
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 205
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 206
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 207
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 208
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 209
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 210
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 211
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 212
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 213
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 214
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 215
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 216
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 217
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 218
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 219
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 220
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 221
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 222
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 223
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 224
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 225
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 226
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 227
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 228
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 229
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 230
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 231
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 232
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 233
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 234
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 235
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 236
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 237
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 238
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 239
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 240
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 241
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 242
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 243
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 244
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 245
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 246
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 247
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 248
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 249
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 250
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 251
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 252
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 253
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 254
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 255
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 256
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 257
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 258
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 259
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 260
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 261
Suggested Citation:"8 Dependence and Abuse Liability." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
×
Page 262

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

8 Dependence and Abuse Liability Studies on the health effects of combustible tobacco have focused on physical disease endpoints (e.g., cancer, cardiovascular disease, respiratory disease). However, combustible tobacco use also has important effects on mental health, including tobacco dependence syndrome. Tobacco use disorder, which is a medical condition recognized by World Health Organization’s International Classification of Diseases (ICD), has a past-year prevalence of 20 percent among all U.S. adults in 2012-2013 (Chou et al., 2016). It produces clinically significant distress and impairment to those affected. As with other substance use disorders, tobacco dependence1 is characterized by unpleasant withdrawal symptoms and loss of behavioral control over use, which result in dependent individuals spending considerable time obtaining or using combustible tobacco cigarettes, interfering with the ability to fulfill important social or occupational role obligations and having a variety of other social and physical consequences (Fiore et al., 2008; Volkow et al., 2016). As with other psychiatric disorders, the symptoms of tobacco dependence are experienced by the user as subjectively distressing (Hughes, 2006) and are linked to neurobiological adaptations in the brain’s circuitry underpinning emotion, motivation, and cognition (Markou, 2008). While the amount of tobacco use is associated with risk and severity of tobacco dependence, the correlation is typically of moderate magnitude and dependence symptoms are reported by an appreciable portion of infrequent and low-intensity tobacco users (Japuntich et al., 2009; Reyes-Guzman et al., 2017), indicating that dependence is a unique outcome in and of itself that is influenced by a combination of the amount of tobacco exposure and other factors. Overall, the tobacco dependence syndrome is an important primary health endpoint to consider. Nicotine is the principal pharmacological agent that causes dependence on combustible tobacco cigarettes (Benowitz, 2008). Because nicotine is delivered via a pulmonary route, the speed, efficiency, and magnitude of nicotine delivered in “bolus” form produces a higher addiction potential of nicotine relative to other nicotine-delivery devices with slower pharmacokinetics (see Chapter 4 for a detailed review of nicotine pharmacokinetics). While 1 The committee uses the term “dependence” to describe the constellation of behavioral symptoms associated with the problematic use of tobacco and nicotine products. While earlier versions of the Diagnostic and Statistical Manual of Mental Disorders (DSM) used the term “dependence” to describe the mental health syndrome caused by problematic tobacco use, DSM-5 no longer uses the term dependence and now uses “tobacco use disorder,” which includes many of the symptoms previously identified for the DSM-IV nicotine dependence disorder. Much of the field uses the term “dependence” to describe the mental health symptoms caused by the compulsive use of tobacco, which includes but is not limited to the DSM-IV nicotine dependence operationalizations of the construct. 8-1 PREPUBLICATION COPY: UNCORRECTED PROOFS

8-2 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES nicotine is necessary, the pharmacological action of nicotine is not sufficient to account for the high addiction potential of combustible tobacco cigarettes (Rose, 2006). “Non-nicotine factors” associated with tobacco self-administration (e.g., taste, smell, and sensations associated with the act of smoking) are critical to the establishment and maintenance of dependence on combustible tobacco cigarettes (Fagerström, 2012). Habitual combustible tobacco cigarette smokers will continue smoking “denicotinized cigarettes” (i.e., cigarettes made with engineered tobacco leaves that contain only trace amounts of nicotine) or very low nicotine-containing cigarettes (i.e., engineered cigarettes with roughly 2 to 3 percent of the amount in a normal cigarette) for extended periods of time (Donny et al., 2007, 2015). Like other drugs of abuse, denicotinized cigarette smoking can cause a significant release of dopamine in the brain’s reward circuit of regular combustible tobacco cigarette smokers, albeit at lower levels (Domino et al., 2013). Behaviors that have no direct pharmacological effects produce symptoms of addiction (e.g., gambling) and may be associated with dysregulation in brain reward circuits (Quester and Romanczuk-Seiferth, 2015). For these reasons, it is now established that combustible tobacco cigarette dependence is not merely addiction to the nicotine, per se (Rose, 2006). This has prompted experts to call for the reframing and relabeling of the tobacco use disorder concept and measurement away from terms that prioritize nicotine, such as “nicotine dependence,” to conceptualizations and terms that acknowledge the role of non-nicotine factors, such as the term “cigarette dependence” or “tobacco dependence” (Fagerström, 2012). Given this background, this section focuses on “e-cigarette dependence,” the constellation of behaviors and symptoms that are distressing to the user and promote the compulsive use of e-cigarettes due to nicotine and non-nicotine factors (Strong et al., 2017). Like combustible tobacco cigarettes, if e-cigarette use were to cause dependence symptoms, the symptoms would be strongly influenced, but not entirely caused by, nicotine per se. Preclinical researchers attempting to uncover the reasons why combustible tobacco cigarettes have such a high addiction potential struggled for decades because animal models were challenged by the fact that, unlike other drugs of abuse, rodents did not easily acquire habitual self-administration of nicotine intravenously (Caggiula et al., 2009). Ultimately, it was discovered that when intravenous nicotine administration was paired with other non-pharmacological sensory stimuli that is pleasant and rewarding (e.g., a sound paired with sucrose) (Caggiula et al., 2009), rats would more easily acquire habitual nicotine self-administration in a manner similar to other drugs of abuse. Based on such research and others, it is now established that addiction potential of tobacco products is dependent on the stimulus context that coincides with nicotine administration. The combination of pleasant stimuli associated with the tobacco self- administration ritual (e.g., the taste, smells, sight, and sensations of inhaling and exhaling as well as the hand-to-mouth movements) and the drug itself synergize to account for the high addiction potential of combustible tobacco cigarettes. Given what is known about the role of nicotine and non-nicotine factors in tobacco product dependence, it is plausible that e-cigarette use may cause dependence symptoms, and the reason may not merely be explained by the fact the e-cigarettes are a nicotine delivery device. Most e-cigarette products are available in desirable flavors and have other characteristics that generate aerosols with a unique profile of pleasurable sensory stimuli due to the taste, sights, smells, and airway sensations, that (like combustible tobacco cigarettes) could have synergistic effects with nicotine on dependence risk. Such enjoyable sensory stimuli in combination with the delivery of “boluses” of nicotine via a pulmonary route (as in combustible tobacco cigarettes) may produce a dependence potential with e-cigarette use. However, it is also possible that e- PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-3 cigarettes may not produce symptoms of dependence, or, that they produce dependence, but at a risk that is significantly lower than combustible tobacco cigarettes. Unlike these cigarettes that reliably and quickly deliver nicotine to the brain, the efficiency, speed, and magnitude of nicotine delivery to the user varies widely across different e-cigarette products and user characteristics (see Chapter 4 for a detailed review of nicotine delivery). Relative to a combustible tobacco cigarette, variations in e-cigarette product characteristics and other conditions have been shown to produce plasma nicotine levels that are below, equal to, or exceed those (Breland et al., 2017). In addition, non-nicotine pharmacological components of combustible tobacco smoke (e.g., monoamine oxidase inhibitors) and other additives may also contribute to the dependence risk caused by combustible tobacco cigarettes (Fagerström, 2012); these compounds may not be present in e-cigarette aerosol. Hence, whether e-cigarettes cause dependence and what the relative magnitude of risk is relative to combustible tobacco cigarettes are questions that cannot be answered solely by the translation of knowledge about nicotine and combustible cigarettes and necessitate a review of the empirical evidence. Furthermore, given the wide variety of products that may alter the nicotine delivery and sensory experience of e- cigarettes, it is plausible that variations in e-cigarette product characteristics affect risk of dependence. Because combustible tobacco cigarette dependence symptoms are known to produce distress as well as social and functional impairment (APA, 2013; Hughes, 2006), independent of the impact of smoking on physical disease, evidence that e-cigarette use cause dependence symptoms would warrant consideration in regulatory policies directed toward e- cigarette manufacture, distribution, and sales. CHARACTERIZATION OF DISEASE ENDPOINTS AND INTERMEDIATE OUTCOMES The strongest evidence to characterize the potential association between e-cigarette use and dependence would include methodologically rigorous epidemiologic studies with e-cigarette dependence symptoms as an endpoint. While there is no widely agreed-upon method of assessing and diagnosing e-cigarette dependence yet, the initial efforts to operationalize dependence as a health outcome of e-cigarettes have adapted methods of assessing combustible tobacco cigarette dependence to e-cigarettes (Foulds et al., 2015; Strong et al., 2017). Essentially many of the same survey or interview questions aimed at assessing symptom presence or severity are used, but the term “e-cigarettes” is substituted for “cigarettes” on the measure. For instance, the U.S. Population Assessment of Tobacco and Health (PATH) Study, a nationally representative survey of tobacco use, adapted dependence measures based on the American Psychiatric Association’s (APA’s) Diagnostic and Statistical Manual for Mental Disorders (DSM) definition of cigarette use disorder. PATH also employed other validated questionnaires that collectively assess various symptoms recognized to be part of the nicotine dependence syndrome, including compulsion to smoke, intensity of smoking (e.g., cigarettes per day), distressing withdrawal symptoms upon abstinence, typical time until to first use after awakening each day, and craving for the product. The key manifestations of the DSM and the ICD drug dependence classification system, which are common to tobacco products and all other substances of abuse, and are summarized in Box 8-1. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-4 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES BOX 8 -1 Criteria for Tobacco Use Disorder from the American Psychiatric Association’s Diagnostic and Statistical Manual for Mental Disorders, 5th Edition A problematic pattern of tobacco use leading to clinically significant impairment or distress, as manifested by at least two of the following factors, occurring within a 12-month period: 1. Tobacco is often taken in larger amounts or over a longer period than was intended. 2. There is a persistent desire or unsuccessful efforts to cut down or control tobacco use. 3. A great deal of time is spent in activities necessary to obtain or use tobacco. 4. Craving, or a strong desire or urge to use tobacco. 5. Recurrent tobacco use resulting in a failure to fulfill major role obligations at work, school, or home. 6. Continued tobacco use despite having persistent or recurrent social or interpersonal problems caused or exacerbated by the effects of tobacco (e.g., arguments with others about tobacco use). 7. Important social, occupational, or recreational activities are given up or reduced because of tobacco use. 8. Recurrent tobacco use in situations in which it is physically hazardous (e.g., smoking in bed). 9. Tobacco use is continued despite knowledge of having a persistent or recurrent physical or psychological problem that is likely to have been caused or exacerbated by tobacco. 10. Tolerance, as defined by either of the following: a. A need for markedly increased amounts of tobacco to achieve the desired effect. b. A markedly diminished effect with continued use of the same amount of tobacco. 11. Withdrawal, as manifested by either of the following: a. The characteristic withdrawal syndrome for tobacco (refer to Criteria A and B of the criteria set for tobacco withdrawal). b. Tobacco (or a closely related substance, e.g., nicotine) is taken to relieve or avoid withdrawal symptoms. SOURCE: American Psychiatric Association, 2013. E-cigarette dependence can be operationalized as a category (e.g., having at least one or more symptoms, surpassing a “clinical” threshold of two symptoms or more (APA, 2013), or on a continuum with a score reflecting a gradient of severity of dependence from none, mild, moderate, or severe. Additional well-established measures of tobacco dependence include the Fagerström Test for Cigarette Dependence (Heatherton et al., 1991), the Heaviness of Smoking Index (HSI), the Hooked on Nicotine Checklist (DiFranza et al., 2002), the Nicotine Dependence Syndrome Scale (Shiffman et al., 2004), and the Wisconsin Inventory of Smoking Dependence Motives (Piper et al., 2004). These measures assess similar symptoms to APA and ICD symptoms (e.g., tolerance, withdrawal) and evaluate other domains reflecting other motives for tobacco use or manifestations of habitual smoking (e.g., strong motive to use tobacco to alleviate negative emotions, smoking automatically and instinctually without thinking about it). Supportive evidence comes from human laboratory investigations that apply “abuse liability” testing methods to e-cigarettes and reflect important intermediate outcomes. Abuse PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-5 liability tests typically involve human laboratory behavioral pharmacology experiments that test the acute effects of controlled drug administration on indicators that are suspected to be proxies of the likelihood that the drug will produce dependence, including subjective effects (e.g., mood enhancement, drug liking) or behavioral choices indicating the motivational value of the drug (e.g., amount of money willing to trade for the drug, willingness to execute a demanding behavior to obtain the drug) (Henningfield et al., 2011). Abuse liability testing is a long-used paradigm relied on by public health regulatory agencies, such as the Food and Drug Administration (FDA), to indicate whether a novel compound is likely to produce dependence. It is particularly useful for screening the potential for dependence of novel psychoactive compounds (e.g., sedatives, stimulants) prior to obtaining epidemiologic data on reports of dependence in the population. Lab abuse liability evidence may not be an exact replication of what occurs in the natural ecology, yet cross-drug differences in lab-obtained abuse liability data concord with cross-drug differences in population-level dependence risk among use initiators (Griffiths and Wolf, 1990; Kollins, 2003; Wagner and Anthony, 2002). There is a well- developed literature applying the abuse liability paradigm to combustible tobacco cigarettes and, more recently, emerging literature on the abuse liability of non-traditional tobacco products with specific methodologic guidelines put forth from tobacco product abuse liability testing experts (Carter et al., 2009; Henningfield et al., 2011). OPTIMAL STUDY DESIGN Primary Endpoint: Epidemiologic Evidence of Dependence Symptoms Caused by E- Cigarettes The optimal epidemiologic study would be a longitudinal cohort investigation that follows individuals who initiate e-cigarette use and tracks the development, escalation, and persistence of e-cigarette dependence symptoms in a nationally representative sample. In such a design, descriptive population-level estimates of the speed, likelihood, and duration of dependence symptoms among ever e-cigarette users would permit inferences regarding the dependence potential of e-cigarettes, with estimates of greater prevalence, speed, and duration of dependence symptoms being indicative of greater dependence risk caused by e-cigarettes. In addition, studies of the association between levels of e-cigarette exposure and likelihood of dependence would also provide key data, with evidence of a dose–response being supportive of greater dependence risk caused by e-cigarette use. A critical confounder is the use of other tobacco products (namely combustible tobacco cigarettes), which is strongly associated with e-cigarette use (Kasza et al., 2017; Schoenborn and Gindi, 2015). A large portion of adults in the United States ages 25 or older who use e-cigarettes are current or prior regular smokers (CDC, 2016), many of whom have tobacco use disorder (Chou et al., 2016). Individuals with considerable histories of smoking report using e-cigarettes to alleviate nicotine withdrawal caused by their cessation of combustible tobacco cigarettes or to satisfy cravings for such cigarettes (Etter and Bullen, 2014). For current or recent ex-smokers, any behavioral signs or symptoms indicative of dependence on e-cigarettes (e.g., short duration between awakening and time of first e-cigarette) could be attributed as merely an artifact of dependence-like behavior produced by smoking. The confounder of smoking is particularly problematic for dual users; statistical adjustment of smoking behavior may be insufficient for making inferences regarding whether dependence is produced by e-cigarettes. In former smokers PREPUBLICATION COPY: UNCORRECTED PROOFS

8-6 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES who transitioned to using only e-cigarettes, their dependence-like habits with e-cigarettes may be driven by desire to regulate nicotine levels carried over from when they were smoking. In such cases, statistical adjustment of total combustible tobacco cigarette exposure (e.g., pack years), age of smoking onset, duration of smoking, and severity and duration of combustible tobacco cigarette dependence could provide some insight for determining whether dependence-like symptoms are the result of e-cigarette use or whether they reflect transference of nicotine dependence from prior combustible tobacco use. Although both reflect forms of dependence, as described above, the committee’s interest is in whether e-cigarette use may cause dependence on e-cigarettes apart from dependence on nicotine alone. The optimal epidemiologic design would follow a nationally representative sample of never-users of tobacco products who initiate use of e-cigarettes and never go on to start using other tobacco products; it would assess the prevalence and association between e-cigarette exposure and e-cigarette dependence symptoms to determine if there is a dose–response association, and if thresholds of exposure that increase risk are comparable to exposure thresholds for combustible tobacco cigarettes. However, the majority of never-smokers who use e-cigarettes are youth and young adults (Jamal et al., 2017; Kasza et al., 2017), and a significant portion of them transition to become combustible tobacco cigarette users within several years of e-cigarette use (Soneji et al., 2017). Thus, the incidence of “pure” cases of e-cigarette dependence in the absence of exposure to other tobacco products is likely to be low even if e- cigarettes were to cause dependence. Supplementary Intermediate Endpoint: Abuse Liability Evidence For the abuse liability literature used to provide secondary evidence, the optimal design would involve a within-subject, cross-over counterbalanced design in which each participant provides data on abuse liability indexes in response to a laboratory “challenge” of at least two conditions, one involving e-cigarettes. Randomized between-subject designs would also provide strong evidence. For example, designs may involve controlled e-cigarette administration challenges with pre- versus post measures of subjective pleasant effects, with, ideally, comparison data on these measures with no challenge or a sham challenge (e.g., puffing from an unlit combustible tobacco cigarette; see (Vansickel et al., 2010). Additional strong designs have an active comparator, such as the comparison of abuse liability indexes across two e-cigarette products that vary on an important dimension of product diversity (e.g., nicotine concentration, flavoring), the comparison of an e-cigarette to a combustible tobacco cigarette, or the comparison of an e-cigarette to an alternative nicotine delivery product (e.g., nicotine gum). Null findings of studies with active controls (or evidence that e-cigarettes have less abuse liability than combustible tobacco cigarettes) should not be interpreted as evidence that e-cigarettes do not produce dependence. However, positive findings from active control studies would provide supportive evidence that e-cigarettes produce dependence to some degree and can address questions regarding the relative dependence risk caused by e-cigarettes compared with combustible tobacco cigarettes or across e-cigarettes with differing product characteristics. From a practical and scientific perspective, the ideal comparator in an abuse liability study would be a nicotine product known to have low abuse liability (e.g., nicotine lozenge, gum, or transdermal patch). For the majority of the research, the ideal challenge in laboratory abuse testing involves an experimentally controlled administration whereby the number and pace of puffs is standardized to control the dose administered (e.g., Goldenson et al., 2016). Less ideal (but PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-7 perhaps more ecologically valid), the participant is permitted to self-administer the product ad libitum (ad lib), which can result in systematic differences in the “dose” of exposure across experimental conditions. For instance, when comparing the pleasant effects of a high versus low nicotine e-cigarette, condition challenge involving 5 minutes of ad lib use and the participants self-administer an average of twice as many puffs with the high dose will leave unclear whether differences between conditions are caused by the nicotine level or the number of puffs taken. Thus, how e-cigarettes are used will influence their abuse liability, and patterns of use vary substantially. For example, some users cluster their puffs in cigarette-like sessions or vape intermittently throughout the day in short clusters. Large clusters of puffs in relatively quick succession result in a near-bolus dose of nicotine, rapid rise in blood nicotine levels, and likely greater nicotine-related effects (positive reinforcement). This type of vaping may be associated with greater abuse liability of e-cigarettes. On the other hand, intermittent vaping in short clusters of puffs results in gradual increase in blood nicotine levels throughout the day. This type of vaping may be done for negative reinforcement (to alleviate nicotine withdrawal symptoms). Because it is unethical to expose tobacco-product naïve subjects to e-cigarettes, the majority of research includes either e-cigarette naïve or inexperienced smokers willing to try e- cigarettes or experienced e-cigarette users. E-cigarette–naïve smokers may be unfamiliar with proper use of e-cigarettes, and therefore may produce levels of nicotine exposure that are lower than those of experienced users of the same product (due to differences in puffing topography; see Chapter 3) (Farsalinos et al., 2014; Vansickel and Eissenberg, 2013). Thus, studies using e- cigarette naïve smokers without proper training of use may result in underestimation of the abuse liability of the product. An important consideration is the types of outcomes that could be considered evidence of abuse liability in studies that conduct controlled tests of e-cigarette administration. Several controlled laboratory studies of regular smokers who have been acutely deprived from nicotine test the effects of e-cigarette use administration on nicotine withdrawal symptoms, combustible tobacco cigarette craving, and other factors believed to maintain smoking behavior. Such studies are not considered to provide evidence regarding whether e-cigarettes produce dependence. The suppression of withdrawal and combustible tobacco cigarette craving is known to be caused by a number of products with little or no abuse liability, including FDA-approved smoking cessation medications. By contrast, subjective euphoria, liking, sensory satisfaction, and willingness to exert effort to obtain e-cigarettes are considered evidence of abuse liability, consistent with guidelines provided by FDA and the National Institute on Drug Abuse (ADAMHA, 1989). These particular outcomes generally are not affected by FDA-approved smoking cessations. Ancillary Evidence: Clinical Trials Involving Product Exposure Outside A Laboratory A number of research studies provide participants (usually e-cigarette–naïve smokers) with an e-cigarette product to use ad lib in the natural ecology for a multiday period. At the end of the period, retrospective reports of the rewarding effects of the product are sometimes collected. While these types of clinical trials may have relevant comparison conditions (e.g., e- cigarette products with differing levels of nicotine strength), which strengthens causal inference, the uncontrolled conditions allow for a number of systematic differences in level of exposure to the product, use of other tobacco product, and other factors that may confound comparisons across conditions. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-8 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES QUESTIONS ADDRESSED BY THE LITERATURE Given that e-cigarettes have been widely available for only the past several years, long- term data on whether dependence symptoms emerge among never-smoking e-cigarette users is unavailable. Hence, in the epidemiologic data, cross-sectional evidence using e-cigarette dependence symptom measures were considered. Such studies were required to report data on e- cigarette dependence symptoms (e.g., craving for e-cigarettes, short time to first e-cigarette after awakening, difficulty refraining from e-cigarette use in situations when vaping is not allowed; see the section on the characterization of disease endpoints, above); mere reporting on the frequency of use was not considered relevant to dependence. The abuse liability literature was used as supportive evidence. Clinical trials were considered ancillary evidence. Several epidemiologic studies report the prevalence, distribution, and correlates of e- cigarette dependence, including whether frequency of e-cigarette use is associated with symptoms of e-cigarette dependence (Dawkins and Corcoran, 2014; Dawkins et al., 2016; Etter, 2015, 2016; Etter and Eissenberg, 2015; Foulds et al., 2015; Goldenson et al., 2016; Gonzalez Roz et al., 2017; Hobkirk et al., 2017; Johnson et al., 2017; Liu et al., 2017; Nichols et al., 2016; Rostron et al., 2016; Strong et al., 2017; Yingst et al., 2015). Descriptive epidemiologic reports on base rates and the distribution of e-cigarette dependence symptoms that show a meaningful portion of e-cigarette users report symptoms of e-cigarette dependence provide evidence to address the question, “Does use of e-cigarettes have an effect on e-cigarette dependence risk?” Additional epidemiologic evidence that the level of exposure to e-cigarettes has a dose–response association with e-cigarette dependence symptom outcomes further addressed that question. In certain experimental studies, data on the prevalence or severity of e-cigarette dependence scores are presented for the purpose of describing the sample used. Because such studies are typically in smaller and non-representative samples, they were used as additional epidemiologic evidence. Human laboratory studies of the effects of e-cigarettes (versus a comparator other than combustible tobacco cigarettes) were also supportive evidence. Some epidemiologic studies compared the dependence severity of e-cigarettes to other tobacco products for the typical user (Strong et al., 2017). Some human laboratory studies compared the effects of e-cigarettes to combustible tobacco cigarettes. Collectively, these two streams of evidence address the question, “Is the effect of e-cigarette use on e-cigarette dependence risk weaker than the effect of cigarette use on cigarette dependence?” Finally, there is an emerging epidemiologic literature on whether e-cigarette users who use products with certain characteristics (e.g., high nicotine concentration) report different levels of e-cigarette dependence than e-cigarette users of products without such characteristics (e.g., low nicotine concentration). Furthermore, there is a human laboratory literature that compares the effects of e-cigarettes with varying product dimensions (e.g., nicotine concentration, flavor) on abuse liability outcomes. Collectively, these streams of evidence address the question, “Do e- cigarettes with certain product characteristics have stronger effects on e-cigarette dependence risk than those with other product characteristics?” For each study reviewed, the committee took into account the methodological rigor to grade the strength of evidence. As described above in the Optimal Study Design section, for epidemiologic data factors such as the representativeness of the sampling strategy, incorporation of particular exclusions (e.g., excluding current smokers) and covariate adjustment, if relevant, were used to grade the weight of evidence provided by each study. For abuse liability studies, issues such as the inclusion of a comparison condition and sample size were considered. PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-9 EPIDEMIOLOGY The search resulted in 14 studies that reported epidemiologic data that matched the requirements above. Review of the studies revealed a natural clustering of different types of studies distinguished by their methodology and rigor. Three studies used nationally representative samples; six online survey studies that did not use a systematic sampling method; two in-person studies used a non-representative sampling (e.g., recruited users at an e-cigarette convention); and three additional laboratory-based studies incidentally reported data on e- cigarette dependence symptoms to describe the sample. A brief description of each study’s finding and whether the result provides evidence that is in support of or against, or inconclusive are reviewed in Tables 8-1 and 8-2. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-10 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES TABLE 8-1 Epidemiologic Studies on E-cigarettes and Dependence E-Cigarettes Have Lower Dependence Product E-Cigarettes Potential Than Characteristics Have Some Combustible Alter Dependence Tobacco Dependence Study Study Population Dependence Measure Results Risk Cigarettes? Risk? Nationally Representative Studies Liu 2017a Wave 1 adult Self-reported time-to-first- Moderate to high endorsement of e- + + interview group of use (in minutes), and cigarette dependence symptoms. PATH database: questionnaire: “Do you 156 e-cigarette consider yourself addicted E-cigarette dependence in e-cigarette- users; 3,430 to cigarettes/e-cigarettes?” exclusive users was lower than cigarette combustible “Do you ever have strong dependence in cigarette-exclusive smokers tobacco cigarette cravings to smoke (e.g., after adjusting for potential users cigarettes/use e- confounders, cigarette smokers were cigarettes?” “In the past 12 significantly more likely to have strong months, did you find it cravings, believe they really needed to use difficult to keep from the product, and consider themselves smoking cigarettes/using e- addicted). cigarettes in places where it was prohibited?” “Have Time-to-first-use: 15% of e-cigarette users you ever felt like you really said 5 minutes; 24% of cigarettes users said needed to smoke the same. After adjustment, e-cigarette cigarettes/use e- users had significantly longer time to first cigarettes?” use than cigarette smokers. Rostron National Adult Average number of Sizable rates of dependence symptoms + + 2016b Tobacco Survey cigarettes smoked per day, endorsed in e-cigarette-only users (23%- (2012-2013): time to first tobacco use 46%). Exclusive e-cigarette users were less 60,192 total after waking, whether or likely than users of other products to report respondents, daily not respondents sometimes withdrawal/craving symptoms, still reported single tobacco wake at night to use a dependence symptoms (e.g., craving for product users: tobacco product, have had tobacco). n = 124 e-cigarettes a strong craving to use any PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-11 n = 131 cigars tobacco product in the past Dual cigarette and e-cigarette users and e- n = 3,963 cigs 30 days, have felt like they cigarette polyusers (cigarette, cigar, e- really needed to use a cigarette) were significantly more likely to tobacco product in the past report strong craving for tobacco in past 30 30 days, have had a time days compared with exclusive cigarette when they wanted to use a smokers. tobacco product so much that it was difficult to think Symptoms were less prevalent in users of of anything else in the past only e-cigarettes and only cigars than 30 days, if the statement people who used both cigarettes and cigars that they feel restless or (e.g., exclusive e-cigarette users reported irritable after not using longer median time-to-first use than tobacco for a while was exclusive cigarette smokers). “not at all true,” “sometimes true,” “often true,” or “always true.” Strong Adult, established Used four tools (the With levels of tobacco dependence + + 2017c users of a tobacco “Hooked on Nicotine anchored at 0.0 (SD = 1.0) among cigarette- product from Wave Checklist” [3 items], only users, mean tobacco dependence was 1 PATH study: Wisconsin Inventory of more than a full standard deviation lower Cigarette-only Smoking Dependence for e-cigarette-only users (mean = 1.37; respondents (n = Motives or WISDM [12 SD = 2.36), cigar-only users (mean = 8,689), e-cigarette- items], the Nicotine 1.92; SD = 2.11), and hookah-only users only respondents (n Dependence Syndrome (mean = 1.71; SD = 0.53). = 437), cigar-only Scale [NDSS] [4 items], respondents (n = the Diagnostic and Higher level of tobacco dependence among 706), hookah-only Statistical Manual criteria daily groups when compared with non-daily respondents (n = [4 items], and “Time to e-cigarette-only users (mean difference = 461), smokeless- First Tobacco Use” [1 0.40, SE = 0.07, F(1,10) = 35.1, p < 0.002). only respondents (n item]) to obtain 24 tobacco = 971) dependence symptoms Studies Using Non-Representative Sampling Gonzalez- 39 experienced e- Fagerström Test for E-cigarette users were dependent on e- + + Roz 2017d cigarette users, Nicotine Dependence liquids containing nicotine, but were less 36% of whom were (FTND) and NDSS, CO nicotine dependent than current tobacco dual users and urinary cotinine smokers (FTND 4.38 ± 1.93 versus 5.57 ± PREPUBLICATION COPY: UNCORRECTED PROOFS

8-12 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES 1.48 and NDSS-T 26.26 ± 5.29 versus 40.50 ± 8.14, respectively). This trend was true for all NDSS measures (impulsivity, priority, tolerance, continuity, and stereotyping). Johnson 131 current e- FTND and select questions Most users did not wake up during the night + + 2017e cigarette users who from Penn State Electronic to use their device. One quarter of users attended Orlando Cigarette Dependence reported time-to-first-use within 5 minutes Vape Convention Index (PSECDI) of waking; another 20% reported within 6- (October 17, 2015) 15 minutes. More than two-thirds of users would rather forgo other e-cigarette sessions throughout the day than give up their morning session. 50% of respondents used their product 30 times per day for at least 10 minutes. Over 50% said they had ever experienced moderate to extremely strong cravings and 60% had such urges over the past week. 31% reported irritability and 27% reported anxiety if they could not use their device. 60% of users received an FTND score of at least 5. Presence of nicotine in e-liquid and length of e-cigarette use (less than or more than 1 year) were significantly associated with nicotine dependence scores. More than 70 percent of those who had used an e-cigarette for more than 1 year were classified as moderately or highly nicotine dependent compared with 45% of those who were users for less than 1 year. Anonymous Web Surveys of E-cigarette Users Dawkins Never (n = 6; 4%), Author-constructed survey 68% of respondents said “very much so” to + + 2013f current (n = 218; “E-cigarette use is as satisfying as tobacco 16%), and former smoking.” 13.3% answered “not at all” to (n = 1,123; 83%) the question “I crave e-cigarettes as much PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-13 smokers, and as I do/did tobacco”; 18.4% said “very current e-cigarette much so” in response to the same question. users Etter 374 adult daily Online non-representative Median time to first e-cigarette ranged from + 2015g users of e- survey 15 to 45 minutes. Users who said e- cigarettes who had Used adapted FTND, cigarettes “definitely” decreased tobacco quit smoking in the NDSS, CDS tools to assess cravings were more likely to report e- previous 62 days dependence on e- cigarettes also alleviated withdrawal cigarettes; also measured symptoms such as anxiety, nervousness, urge to use e-cigarette with anger, irritability, frustration, depressed MPSS (2 items); used mood, sadness, restlessness, impatience, modified version item of mood swings compared with those who said craving subscale of WSWS e-cigarettes had a weak effect on craving. Etter and 1,284 adult daily Used adapted FTND, Ex-smokers who used only e-cigarettes + + + Eissenberg users of e- NDSS, CDS tools to assess reported significantly lower time to first 2015h cigarettes dependence on e-cigarettes cigarette when smoked combustible tobacco and nicotine gum; also cigarettes versus time to first e-cigarette; measured unsuccessful time to first e-cigarette less than 30 minutes attempts to quit product, on average. Lower time to first e-cigarette and perceptions of associated with nicotine versus placebo use. likeliness to succeed if 62% of daily dual users said their current stopped using product and dependence on e-cigarettes was weaker addiction to e-cigarette or than dependence on tobacco cigarettes. nicotine gum compared with combustible tobacco Daily e-cigarette users who used nicotine- cigarette containing devices had higher e-FTND scores than those who used non-nicotine- containing devices. Some evidence that gum dependence more severe; not adjusted for confounding. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-14 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Etter 2016i 1,672 adult current Online non-representative Median time to first e-cigarette ranged from + + + users of e- survey 15 to 30 minutes and was lower for those cigarettes (daily who reported greater throat hit. and occasionally) Strength of throat hit was associated with satisfaction and dependence variables: “Like the taste of the vapor produced by e- cigarette” (% agree: very weak: 75%; rather weak: 78%; average: 88%; rather strong: 90%; very strong: 88%; 2 = 64.9; p < .001); “Likes the sensation when inhales vapor” (% agree: very weak: 60%; rather weak: 81%; average: 86%; rather strong: 92%; very strong: 91%; 2 = 99.6; p < .001); and “It feels so good to vape” (% agree: very weak: 59%; rather weak: 68%; average: 75%; rather strong: 81%; very strong: 91%; 2 = 41.8; p < .001). “Addiction to the e-cigarette” (scale of 0 to 100: very weak: 50%; rather weak: 50%; average: 65%; rather strong: 70%; very strong: 65%; KW = 32.9; p < .001); “I am a prisoner of the electronic cigarette” (% agree: very weak: 17%; rather weak: 21%; average: 26%; rather strong: 28%; very strong: 19%; 2 = 43.3; p < .001); “I am unable to stop vaping” (% agree: average: 25%; 2 = 41.4; p < .001); “If decided to stop using e-cigarette, likely to succeed” (% agree: very weak: 55%; rather weak: 36%; average: 30%; rather strong: 28%; very strong: 42%; 2 = 51.5; p < .001); PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-15 “Stopping using e-cigarette for good would be very difficult” (% agree: very weak: 6%; rather weak: 23%; average: 28%; rather strong: 30%; very strong: 35%; 2 = 56.7; p < .001); “Felt the urge to vape today” (% a lot of the time + almost all the time + all the time: very weak: 15%; rather weak: 27%; average: 32%; rather strong: 35%; very strong: 31%; 2 = 46.5; p = .001) “Use the e-cigarette because they are addicted to it” (% very true: very weak: 2%; rather weak: 6%; average: 8%; rather strong: 9%; very strong: 9% 2 = 31.2; p = .002); and “Former smokers: addiction to e-cigarette compared with former addiction to tobacco cigarette” (% same or stronger: very weak: 12%; rather weak: 15%; average: 25%; rather strong: 25%; very strong: 23%; 2 = 49.7; p < .001) PREPUBLICATION COPY: UNCORRECTED PROOFS

8-16 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Foulds 3,609 adult former Penn State Cigarette The overall E-Cig Dependence Index for e- + + + 2015j smokers who Dependence Index and cigarette users was significantly lower than currently use e- Penn State Electronic their Cigarette Dependence Index, as was cigarettes Cigarette Dependence the individual score on every other item. Index More than 90% reported they had experienced strong urges to smoke and withdrawal symptoms when a smoker, but only 25%-35% reported experiencing these symptoms of dependence as an e-cig user. Those who have used e-cigs for a longer time, who have previously tried more e-cig models, who currently use an e-cig larger than a cigarette, with a button, with more than one battery, that cost more than $50 and who use a higher concentration of nicotine liquid, tend to have a higher e-cig dependence index (all p < .05). Those using zero nicotine liquid had a significantly lower e-cig dependence index than those using 1-12 mg/ml (p < .001), who were significantly lower than those using 13 or greater mg/ml nicotine liquid (p < .001). Yingst Current advanced Online survey asking, “Did Advanced generation versus first + + 2015k generation e- you switch to your current generation: significantly more dependence cigarette preferred type of e-cig on e-cigarettes (despite liquid with lower device users (n = because it gives you a more nicotine concentration) than first generation 3,373); Current satisfying “hit” than device users; also shorter time to first use. first generation previous e-cigs your e-cigarette device tried?” (Yes/No); also Advanced generation user was less likely to users (n = 1,048) PSECDI be a current smoker. Reported switching to current device because delivered a more satisfying throat hit. PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-17 Descriptive Data on E-Cigarette Dependence Symptoms in Small Laboratory Studies Dawkins 11 experienced Adapted FTND; CDS eFTND mean = 4.73 (SD 1.35) (range 2-7) + 2016l male vapers e-cigarette self-rated addiction item rating completed 60 min mean = 3.18 (SD 1.17) (range 1-5) of ad lib vaping under low (6 mg/ml) and high (24 mg/ml) nicotine liquid conditions in two separate sessions Goldenson 20 e-cigarette users PSECDI; FTCD PSECDI: mean 8.4 (95% CI = 6.4-10.4) + 2016m ( 1 day/week for FTCD in past 30-day smokers: mean 6.3 1 month; smoking (95% CI = 5.8-6.8) 15 combustible tobacco cigarettes/day; no use of smoking cessation medication) Hobkirk 9 adult past month PSECDI The sample’s average self-reported + 2017n (20 or more days in dependence on e-cigarettes was low based the past 28) e- on PSECDI total scores, which ranged from cigarette users 3 to 8 (M = 6.33; SD =1.80) out of a possible score range from 0 to 20. Nichols 7 e-cigarette users PSECDI PSEDCI: low to medium levels of e- + 2016o cigarette dependence (M = 7, SD = 3). NOTES: + = positive evidence; = no positive evidence; +/ = mixed results (some outcomes or analyses yielded positive evidence and others did not yield positive evidence); 0 = inconclusive evidence to determine whether the results are positive or not. SOURCES: a Liu et al., 2017. b Rostron et al., 2016. c Strong et al., 2017. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-18 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES d Gonzalez Roz et al., 2017. e J ohnson et al., 2017. f Dawkins et al., 2013. g Etter and Eissenberg, 2015. h Etter, 2015. I Etter, 2016. j Foulds et al., 2015. k Yingst et al., 2015. l Dawkins et al., 2016. m Goldenson et al., 2016. n Hobkirk et al., 2017. o Nichols et al., 2016. PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-19 TABLE 8-2 Laboratory/Experimental Studies on Dependence and Abuse Liability E-Cigarettes Have Lower Dependence Product E-Cigarettes Potential Than Characteristics Have Some Combustible Alter Study Study Dependence Dependence Tobacco Dependence Study Design Population Device Measure Measure Results Risk Cigarettes? Risk? Studies Testing the Effects of Flavor Audrain- Laborat 32 young “e-GO” tank-style e- Modified Fruit and dessert flavored e- + + McGovern ory adult smokers cigarette with a 2.4 ml satisfaction cigarettes had a significantly 2016a who vaped at refillable e-liquid tank subscale of higher reward value than least once the Cigarette unflavored e-cigarettes; fruit 2 flavored e-liquid Evaluation flavor preferred. Users took options: fruit-flavored Scale for e- significantly more flavored (green apple), and cigarette use, puffs than unflavored. dessert-flavored RRVF, and Menthol cigarette smokers (chocolate), with 6, 12, number of took significantly more (at or 18 mg/ml of nicotine flavored least three times as many) e- depending on the versus cigarette puffs as non- nicotine content of the unflavored e- menthol smokers. participant’s usual cigarette puffs smoking rate consumed PREPUBLICATION COPY: UNCORRECTED PROOFS

8-20 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Goldenson Laborat 20 e-cigarette Joyetech “Delta 23 Visual Significant effect of flavor on + + 2016b ory and users ( 1 Atomizer” tanks Analogue each appeal outcome: sweet- used day/week for connected to a Joyetech Scale flavored solutions produced epidemi 1 month; “eVic Supreme” battery; assessing higher appeal ratings than ologic smoking 15 20 e-cigarette solutions “How much non-sweet and flavorless data combustible in 10 flavors were either did you like solutions. No significant tobacco 0 or 6 mg/ml nicotine (10 it?” “Would main effects of nicotine or cigarettes/day flavors included 6 sweet- you use it flavor × nicotine interaction ; no use of flavored [peach, again?” “How effects. smoking watermelon, blackberry, much would cessation cotton candy, cola, and you pay for a Significant effect of nicotine medication) sweet lemon tea], 3 non- day’s worth of on throat hit: a stronger sweet-flavored [mint, it?” “How throat hit in nicotine versus tobacco, and menthol], sweet was it?” placebo solutions. and a single flavorless “How strong solution) was the throat Ratings of sweetness hit?” and positively associated with “What flavor each appeal outcome: is it?” sweeter associated with increased liking, willingness to use again, and amount willing to pay for a day’s worth of solution. Throat hit not associated with willingness to use again and subjective value and were inversely associated with liking. Rosbrook Laborat 18-45 years Challenge study General No significant effects of and Green ory of age controlled vaping Labeled menthol or nicotine on 2016c (n = 32) Magnitude liking. Liking was low and Experiment Scale and did not vary significantly #1 Labeled across menthol or nicotine Hedonic Scale concentrations. PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-21 Rosbrook Laborat 18-45 years Challenge study General Average liking ratings of the +/ +/ and Green ory of age controlled vaping Labeled e-liquid flavors did not 2016c (n = 32) Magnitude exceed “like slightly” on the Experiment Scale and Labeled Hedonic Scale. #2 Labeled Hedonic Scale A trend toward higher ratings for liking of the menthol and menthol-mint flavors over the unflavored e-liquid was supported by a main effect of flavor (F2,60 = 8.11, p < .001). St.Helen Laborat 14 e-cig users Inpatient crossover study Minnesota No difference in mCEQ +/ +/ 2017d ory with strawberry, tobacco, Nicotine reward or satisfaction and user’s usual flavor e- Withdrawal subscale between strawberry liquid. Nicotine levels Scale, and tobacco e-liquids, except were nominally 18 Questionnaire ratings of sensations in throat mg/ml in the strawberry for Smoking and chest (significantly (pH 8.29) and tobacco Urges higher with tobacco). (pH 9.10) e-liquids and modified for ranged between 3-18 mg/ e-cigarettes, Usual brand e-liquids had ml in the usual brands Positive and significantly more (mean pH 6.80). Negative satisfaction and enjoyment of Affect sensations than experimenter Schedule, and provided liquids. modified Cigarette Evaluation Questionnaire Studies Testing the Effects of Nicotine Concentration Baldassarri Laborat Adult “e-Go type e-cigarette”; Fagerström Ratings of product liking 2017e ory and experienced nicotine concentrations Test for were similar after each e- epidemi e-cigarette with a linear range of 0.5 Nicotine cigarette use (0 mg/ml = 80 ± PREPUBLICATION COPY: UNCORRECTED PROOFS

8-22 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES ologic users (n = 4) to 50 mcg/ml Dependence 28; 8 mg/ml = 75 ± 38; 36 and cigarette adapted for e- mg/ml = 74 ± 26). smokers (n = cigarettes 3) Liking following use of the tobacco cigarette was [37 ± 40]; this did not differ compared with the e-cigarette at either liquid strength (8 mg/ml: 75 ± 38; 36 mg/ml: 74 ± 26). Dawkins Laborat 11 “eVic™ supreme” e- Change in Mean (SD) percentage hit 0 2016f ory experienced cigarette from Joyetech, craving and and satisfaction levels were male vapers fitted with a “Nautilus withdrawal 61.86 (31.50) and 60.70 completed 60 Aspire” tank e-cigarette symptoms (17.30) respectively in the min with 6 mg/ ml (low) and (MPSS) high condition and 44.73 of ad lib 24 mg/ ml (high) nicotine (23.00) and 46.89 (16.93) in vaping under Halo Smokers’ Angels Visual the low condition. These low (6 brand e-liquid Analogue differences did not reach mg/ml) and Scale statistical significance (hit: Z high (24 assessing = 1.60, p = 0.11; mg/ml) positive (hit satisfaction: Z = 1.69, p = nicotine and 0.09). liquid satisfaction) conditions in and adverse two separate effects sessions associated with nicotine and e-cigarette use PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-23 Goldenson Laborat 20 e-cigarette Joyetech “Delta 23 Visual Significant effect of flavor on + + 2016g ory and users ( 1 Atomizer” tanks Analogue each appeal outcome: sweet- used day/week for connected to a Joyetech Scale flavored solutions produced epidemi 1 month; “eVic Supreme” battery; assessing higher appeal ratings than ologic smoking 15 20 e-cigarette solutions “How much non-sweet and flavorless data combustible in 10 flavors were either did you like solutions. No significant tobacco 0 or 6 mg/ml nicotine (10 it?”, “Would main effects of nicotine or cigarettes/day flavors included 6 sweet- you use it flavor × nicotine interaction ; no use of flavored [peach, again?”, “How effects. smoking watermelon, blackberry, much would cessation cotton candy, cola and you pay for a Significant effect of nicotine medication) sweet lemon tea], 3 non- day’s worth of on throat hit: a stronger sweet-flavored [mint, it?”, “How throat hit in nicotine versus tobacco and menthol] sweet was placebo solutions. and a single flavorless it?”, “How solution) strong was the Ratings of sweetness throat hit?”, positively associated with and “What each appeal outcome: flavor is it?” sweeter associated with increased liking, willingness to use again, and amount willing to pay for 1 day’s worth of solution. Throat hit not associated with willingness to use again and subjective value and were inversely associated with liking. Perkins Laborat Adult E-cigarettes with as 36 Reward Nicotine: significantly + + 2015h ory dependent mg/ml nicotine; reinforcement greater liking compared with smokers (n = “Rawhide Red task the placebo e-cigarette 28) in a fully (Tobacco)” for within- nonmenthol and subjects “Freeport (Menthol)” for PREPUBLICATION COPY: UNCORRECTED PROOFS

8-24 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES design menthol flavors Rosbrook Laborat 18-45 years Challenge study General No significant effects of and Green ory of age controlled vaping Labeled menthol or nicotine on 2016i (n = 32) Magnitude liking. Liking was low and Experiment Scale and did not vary significantly #1 Labeled across menthol or nicotine Hedonic Scale concentrations. Rosbrook Laborat 18-45 years Challenge study General Average liking ratings of the +/ +/ and Green ory of age controlled vaping Labeled e-liquid flavors did not 2016i (n = 32) Magnitude exceed “like slightly” on the Experiment Scale and Labeled Hedonic Scale. #2 Labeled Hedonic Scale A trend toward higher ratings for liking of the Menthol and Menthol–Mint flavors over the unflavored E-liquid was supported by a main effect of Flavor (F2,60 = 8.11, p < .001). Significant effect of nicotine on coolness/cold perceptions. Comparison of E-Cigarette to Combustible Tobacco Cigarettes and Other Products PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-25 Stiles 2017j Laborat 59 e-cig Vuse Solo were Questionnaires The mean maximum scores + + ory naïve evaluated in this study, : Product (Emax) on the Product smokers containing either 14, 29, Liking, Urge Liking questionnaire were or 36 mg of nicotine. to Smoke, substantially lower for the Vuse Solo e-cigarettes Urge for three Vuse Solo e-cigarettes are composed of a Product, Intent compared with the cigarette battery, heating element, to Use Product condition (LS [least square] microchips, sensor, and a Again, mean Emax scores ranging cartridge containing Product from 4.13 to 4.57, LS mean propylene glycol, Effects Emax = 9.06, p < 0.001 for glycerin, nicotine, all, respectively), and flavorings, and water. somewhat higher than The three devices were nicotine gum (LS mean presented without brand Emax = 3.21, p < 0.05 for style information and all). A similar pattern was were visually seen with the Intent to Use indistinguishable by Again questionnaire. The subjects. mean Emax intent to use again scores were substantially lower for the three Vuse Solo ECs (LS mean Emax scores ranging from 4.07 to 4.75) compared with the cigarette condition (LS mean Emax = 6.81, p < 0.001 for all), and higher than nicotine gum (LS mean Emax = 3.29, p < 0.006 for all). A similar pattern was also shown for the Liking for Positive Effects measure. Strasser Trial 28 e-cigarette 5 first-generation design Withdrawal Compared with cigarette + 2017k naïve current brands: NJOY, 18mg Symptom smoking, e-cigarettes smokers nicotine; V2, 18mg Checklist and provided significantly lower nicotine; Green Smoke, questionnaire nicotine levels (25%-50%), 18.9-20.7mg nicotine; of Smoking reduced CO exposure, and PREPUBLICATION COPY: UNCORRECTED PROOFS

8-26 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES blu, 20-24mg nicotine; Urges lower ratings of liking (p < and White Cloud, 23-24 .05). No differences by brand mg nicotine detected. E-cigarette use on Day 5 significantly reduced levels of craving and withdrawal; similar results at Day 10. Vansickel Laborat 32 e-cigarette 16-18 mg/ml first Questionnaire Significant condition by time + 2010l ory naïve generation devices that of Smoking interactions were observed smokers didn’t give nicotine yield Urges Brief for ratings of “satisfying,” in blood. Users’ own (QSU Brief); “pleasant,” “taste good,” brand of cigarettes versus visual “dizzy,” “calm,” sham (unlit cigarette) analogue scale “concentrate,” “awake,” and versus “NPRO” e- “reduce hunger.” cigarette versus “HYDRO” e-cigarette Vansickel Laborat 20 e-cigarette “Vapor King” (KR808 Questionnaire Effects of the highest + + 2012m ory naïve model) automatic e- of Smoking magnitude were observed for smokers cigarette, 18mg Urges Brief ratings of “pleasant” (F6,114 = (QSU Brief); 21.1, p < .0001), visual “satisfying” (F6,114 = 19.5, p < analogue scale .0001), and “taste good” (F6,114 = 20.2, p = .0001). Cross-over values were greater in the own brand versus $ choice condition relative to the e-cigarette versus $ condition. Collapsed across time, the average crossover value was $1.06 (SD = $0.16) in the e- cigarette versus $ condition and $1.50 (SD = $0.26) PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-27 in the own brand versus $ condition. Clinical Trials Meier 2017n Laborat 24 adult bluCig starter kit with up Minnesota Modified Cigarette ory/Cros smokers, no to seven cartridges Nicotine Evaluation Scale scores for s-over vaping in past prefilled with 16 mg Withdrawal vaping did not differ between 6 months nicotine solution Scale; Brief active and placebo e- Wisconsin cigarettes. Within a double-blind Inventory of randomized crossover Smoking design, smokers (n = 24; Dependence 75% male; M age = 48.5 Motives; years) smoked as usual Glover- for 1 week, followed by Nilsson two counterbalanced Smoking naturalistic (i.e., ad Behavioral libitum use) weeks of Questionnaire; either placebo or active and modified first generation e- Cigarette cigarettes Evaluation Scale PREPUBLICATION COPY: UNCORRECTED PROOFS

8-28 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Steinberg Clinical 41 e-cigarette Device type unknown. Modified The total Psychological + 2014o trial naïve Each participant used e- Cigarette Rewards scores were higher cigarette and nicotine Evaluation for the tobacco cigarette and inhaler each for 3 days, Questionnaire e-cigarette compared with the in random order, with a inhaler. E-cigarettes scored washout period between significantly lower on each one. aversion scores than tobacco cigarette. Compared with inhaler, e-cigarette scored higher on measures of perception such as helpful for not smoking and effective for quitting, similar to cigarette, acceptable to smokers, and cool image. NOTE: + = positive evidence; = no positive evidence; +/ = mixed results (some outcomes or analyses yielded positive evidence and others did not yield positive evidence); 0 = inconclusive evidence to determine whether the results are positive or not. SOURCES: a Audrain-McGovern et al., 2016. b Goldenson et al., 2016. c Rosbrook and Green, 2016. d St.Helen et al., 2017. e Baldassarri et al., 2017. f Dawkins et al., 2016. g Goldenson et al., 2016. h Perkins et al., 2015. I Rosbrook and Green, 2016. j Stiles et al., 2017. k Strasser et al., 2016. l Vansickel et al., 2010. m Vansickel et al., 2012. n Meier et al., 2017. o Steinberg et al., 2014. PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-29 Nationally Representative Studies Rostron and colleagues (2016) analyzed reports of dependence symptoms among those who were exclusive daily users of e-cigarettes (n = 124), combustible tobacco cigarettes (n = 3,963), or cigars (n = 131) within the past 30 days as well as dependence poly-product users in the past thirty days. Data were drawn in the 2012-2013 National Adult Tobacco Survey (NATS), a nationally representative cross-sectional telephone survey. For each product used and each dependence symptom, participants were asked whether they experienced the symptom within the past 30 days. The questions were worded identically across the different products—a strength of the study, which facilitated cross-product comparisons. Among daily e-cigarette users, there were appreciable prevalence rates of various dependence symptoms, including use within 30 min of awakening (46.1 percent, 95% CI = 35.1 percent, 57.4 percent), strong cravings (46.2 percent [95% CI: 35.2, 57.5]), need to use (46.2 percent [95% CI: 35.2, 57.5]), and withdrawal symptoms upon abstinence (22.8 percent [95% CI: 14.8, 33.4]). Prevalence rates for each dependence symptom were significantly lower among exclusive daily e-cigarette users as compared with exclusive combustible tobacco cigarette smokers and were not significantly different from symptom prevalence estimates for exclusive daily cigar users. Poly product users of e-cigarettes and combustible tobacco products reported higher prevalence of most symptoms than exclusive e-cigarette, combustible tobacco cigarette, and cigar smokers. Given the representative sampling, this study provides strong evidence on dependence symptom prevalence estimates in the United States. The separation of exclusive e-cigarette users from poly users facilitates inferences that dependence symptoms are not manifestations of dependence toward use of any form of nicotine or tobacco that are driven by dependence on another tobacco product. A limitation is that comparisons across different groups of users did not statistically adjust for possible confounding factors, such has prior history of tobacco use and demographics factors. In addition, the data were collected in 2012-2013 when prevalence of e- cigarette use was low and the marketplace was saturated with early model devices (e.g., cigalikes) and products, which may have had fairly poor nicotine delivery and lack variety in flavorings (Breland et al., 2017). Modern e-cigarette devices and e-liquids with greater appeal and nicotine delivery effectiveness have become more widely available and popular within the past few years, but were uncommon when this study was performed. Hence, the generalizability to the current environment is questionable and there is a possibility that e-cigarette prevalence estimates may be different than what would be observed today. In sum, this study provides strong evidence that dependence symptoms are common among daily e-cigarette users and suggestive evidence that the probability of experiencing dependence symptoms is lower for e- cigarettes compared with combustible tobacco cigarettes and not different in comparison to cigars. Liu and colleagues (2017) analyzed the relative level of dependence among adult, exclusive everyday users of e-cigarettes (n = 156) and combustible tobacco cigarettes (n = 3,430) in the past 30 days. Among adult participants in the Wave 1 of the PATH study in 2013-2014. Four binary dependence symptoms were examined (yes/no), which included identical wording for assessment of e-cigarette and combustible tobacco cigarette dependence: • “Do you consider yourself addicted to cigarettes/e-cigarettes?”; • “Do you ever have strong cravings to smoke cigarettes/use e-cigarettes?”; PREPUBLICATION COPY: UNCORRECTED PROOFS

8-30 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES • “In the past 12 months, did you find it difficult to keep from smoking cigarettes/using e-cigarettes in places where it was prohibited?” • “Have you ever felt like you really needed to smoke cigarettes/use e-cigarettes?” In addition, time to first product use after awakening was also assessed as a quantitative outcome. Results showed high prevalence for both e-cigarettes and combustible tobacco cigarettes for most dependence symptoms—consider yourself addicted (e-cigarettes: 77.2 percent; combustible tobacco cigarettes: 94.0 percent), strong cravings (e-cigarettes: 72.8 percent versus combustible tobacco cigarettes: 86.9 percent), difficulty refraining from use where prohibited (e-cigarettes: 5.6 percent versus combustible tobacco cigarettes: 28.6 percent), feel need to use (e-cigarettes: 71.5 percent versus combustible tobacco cigarettes: 88.5 percent), time to first use after awakening (grand mean [95% CI] e-cigarettes: 23.46 [19.47, 28.27] minutes versus combustible tobacco cigarettes: 19.25 [18.25, 20.30] minutes). Of note, as described in Chapter 1, overall prevalence of e-cigarette use is low in the PATH study relative to other nationally representative surveys. Regression analyses adjusted for demographics showed that, relative to exclusive daily combustible tobacco cigarette users, exclusive daily e-cigarette users reported lower prevalence for each dependence symptom and longer time to first use. A strength of this study was the report on the product characteristics used among the e- cigarette users, which provides information generalizability on a key source of potential variability in dependence risk (i.e., device type). Among e-cigarette users, 96.3 percent reported that the e-cigarette they used most of the time was rechargeable, 76.5 percent reported that they were able to refill their e-cigarette or e-cigarette cartridges with e-liquid, and 95.8 percent reported using e-cigarettes that usually contained nicotine. The analyses excluded those who used more than one product in the past 30 days, which reduces the impact of current exposure to other products on reports of e-cigarette dependence symptoms. Comparisons in dependence symptoms between e-cigarette and combustible tobacco cigarette users adjusted for sociodemographics, which helps to rule out some confounding effects. Prior tobacco use history characteristics were not adjusted for in the analysis, leaving unclear whether chronicity and level of prior tobacco product exposure, which may directly influence risk of dependence on any tobacco product, may differ between e-cigarette and combustible cigarette users and explain group differences in dependence. It is possible that one of the groups consumed more tobacco or had greater total exposure to nicotine in their lifetime prior to the past 30 days. The authors reported 92.9 percent of exclusive daily e-cigarette users were former regular combustible tobacco cigarette smokers; hence, both groups had chronic cigarette exposure. Previous tobacco consumption could produce chronic neurobiological alterations that may increase liability dependency on any product, including e-cigarettes. Consequently, the prevalence estimates reported may be less than what would be observed for e- cigarette users who have little history of use of other tobacco products. Finally, some the symptoms are likely to be less valid indicators of the underlying addiction to e-cigarettes as compared with combustible tobacco cigarettes. For example, the symptom “difficulty refraining from use in places where prohibited,” which is a well-validated symptom of combustible tobacco cigarette dependence, may be less relevant to e-cigarette because there are fewer restrictions on where e-cigarettes may be used. Indeed, the authors reported that the majority of e-cigarette users reported living in a place that allows the use of their product anywhere and at any time inside their home (61.9 percent), compared with only 26.5 percent of the combustible tobacco cigarette smokers. In sum, this study provides strong PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-31 evidence that the prevalence and severity of e-cigarette dependence symptoms in exclusive users are fairly high overall in the U.S. population, but not as high as what is found in exclusive combustible tobacco cigarette smokers. A separate analysis of PATH Wave 1 2013-2014 data (Strong et al., 2017) looked at whether responses to dependence symptom questions mapped on to a common “latent dimension” of dependence severity for various tobacco products. Like the other studies, survey questions for each dependence symptom were worded identically across different tobacco products, and a primary goal was to compare results across mutually exclusive past year tobacco user groups, including: combustible tobacco cigarette only (n = 8,689), e-cigarette only (n = 437), cigar only (traditional, cigarillo, or filtered) (n = 706), hookah only (n = 461), smokeless tobacco only (n = 971), combustible tobacco cigarette plus e-cigarette (n = 709), and multiple tobacco product users (n = 2,314). Wording of each symptom interview question are listed in Table 8-3. To satisfy the study inclusion criteria for current established use, for combustible tobacco cigarettes, a current established user is defined as an adult who has smoked at least 100 cigarettes in his/her lifetime and now smokes every day or some days. For all other tobacco products, a current established user is defined as an adult who has ever used the product “fairly regularly” and now uses it every day or some days. Though both Liu and colleagues (2017) and Strong and colleagues (2017) use PATH Wave 1 data, the samples are only partially overlapping, as Strong and colleagues is a more inclusive sample of daily and non-daily users, whereas Liu and colleagues included daily users. Hence, the results from the two studies provide results from non-redundant data sources. Another difference between the studies was the data analytic approach. Liu and colleagues used regression modeling. A unique strength of Strong and colleagues was the application of item response-based statistical modeling, which permitted assessment of whether the extent to which each symptom was a valid indicator of the underlying latent dependence syndrome and whether its validity differed dependent on whether it was being reported for one product versus another (i.e., “differential item functioning”). The latent dimension is empirically estimated upon a common dimension inter-symptom association using factor analytic techniques. Once a common latent dimension is ascribed and only items that are equally valid indicators of the dimension are retained to estimate the dimension, comparisons in the relative “severity” of dependence on the dimension can be made with greater rigor and assurance of a common metric. Without doing so, any differences in the relative prevalence or severity of a particular dependence symptom across different user groups could be ascribed to the symptom being a less valid indicator for use of one product versus another. For example, the study found that reporting difficulty refraining from using the product in places where it was prohibited was less strongly associated with the latent dependence dimension for exclusive e-cigarette users than for combustible tobacco cigarette users, which may be in part due to less comprehensive indoor air quality restrictions against e- cigarette use than combustible tobacco cigarette use, making this particular symptom a less relevant indicator of e-cigarette dependence than of combustible tobacco cigarette dependence. The study then used the empirically-validated latent dimension to compare the average severity of dependence across different tobacco product user groups. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-32 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES TABLE 8-3 Tobacco Dependence Instruments and Questions Included, Examined in Response Models, and Retained on a Final Common Tobacco Dependence Instrument in the Population Assessment on Tobacco and Health Study Wave 1 Final Item Common Number Original Instrument Domain Question Text Instrument 1 HONC Loss of control Do you consider yourself addicted to [product]? No 2 HONC Craving Do you ever have strong cravings to [product]? No 3 HONC Craving Have you ever felt like you really needed [product]? No 4 WISDM: Primary Automaticity I find myself reaching for [product] without thinking about it. Yes 5 WISDM: Primary Craving I frequently crave [product]. Yes 6 WISDM: Primary Craving My urges keep getting stronger if I don’t use [product]. Yes 7 WISDM: Primary Loss of control Tobacco products control me. Yes 8 WISDM: Primary Loss of control My [product] use is out of control. Yes 9 WISDM: Primary Tolerance I usually want to use [product] right after I wake up. Yes 10 WISDM: Primary Craving I can only go a couple of hours without using [product]. Yes 11 WISDM: Primary Automaticity I frequently find myself almost using [product] without thinking about Yes it. 12 WISDM: Secondary Negative Using [product] would really help me feel better if I’ve been feeling Yes reinforcement down. 13 WISDM: Secondary Cognitive Using [product] helps me think better. Yes enhancement 14 WISDM: Secondary Social Most of the people I spend time with are tobacco users. No reinforcement 15 WISDM: Secondary Affiliative I [would] feel alone without my [product]. Yes attachment 16 NDSS Loss of control I would find it really hard to stop using [product]. Yes 17 NDSS Loss of control I would find it hard to stop using [product] for a week. Yes 18 NDSS Withdrawal After not using [product] for a while, I need/I would like to use Yes [product] in order to feel less restless and irritable. 19 NDSS Withdrawal After not using [product] for a while, I need to use [product] in order to Yes keep myself from experiencing any discomfort. 20 DSM: Risky Use Use despite Do you believe that [product] is causing a health problem or making it No consequences worse? 21 DSM: Social Give up In the past 12 months, did you give up or cut down on activities that No impairment activities were enjoyable or important to you because [product] was not permitted at the activity? PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-33 22 DSM: Impaired Loss of control In the past 12 months, did you find it difficult to keep from using Yes control [product] in places where it was prohibited? 23 DSM: Withdrawal Withdrawal Withdrawal Syndrome No 24 Time to first tobacco Tolerance On days that you smoke, how soon after you wake up do you typically No smoke your first cigarette of the day? Please enter the number of minutes or hours. NOTE: The Final Common Instrument identifies as “Yes” the 16 items used to compare levels of tobacco dependence (TD) across product users. Items labeled “No” were set aside due to evidence of poor relation to overall levels of TD or differences in how the items measured TD symptoms across products. SOURCE: Strong et al., 2017. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-34 PUBLI HEALTH CONSEQU IC H UENCES OF E-CIGARET TTES Differential It Function D tem ning (DIF) analyses sup a pported use o 16 of the 2 examined of 24 d tobacco dependence (TD) indicat for com d tors mparisons acrross differen tobacco pr nt roduct users. Three ite were om ems mitted from further analyses because they were in fu nvalid indicaators of the l latent dependen dimensio in multipl user (i.e., “most of the people I sp nce on le e pend time wi are tobac ith cco users”; “ttobacco use is causing a health problem”; “givin up activities as tobacc use not ng co allowed” others were retained or eliminated based on D analysis and the auth ”); o d DIF hors’ judgem ment, including retaining sy g ymptom ind dicators that may have yi m ielded statist tically signif ficant DIF thhat were not of clinical or practical significance. Using the it response o s tem e-based mod to estima del ate the latent dependence severity ac t e cross all grou using the validated 1 item cross-product ups e 16 dependen index, mean tobacco product dep nce m o pendence sev verity scores were 1.37 standard s deviation units lower for e-cigare only use than comb n r ette ers mbustible toba acco cigaret only users tte s (see Figu 8-1). E-cigarette only users were comparable to cigar onl users and slightly high ure y e ly her than hook only use Poly-pro kah ers. oduct users of e-cigarette and other products we comparab o es ere ble to combu ustible tobacco cigarette only users. Among e-cig A garette only users, the 70.1 percent ( (SE ± 2.12 peercent) of ex xclusive e-ciggarette users who were d s daily users scored signif ficantly higher on the latent dependence dimension than non-da exclusiv e-cigarette users (mea difference in t e aily ve e an e standard deviation un = 0.40, SE = 0.07). Overall, e-ci nits S O igarette only users did ha a lower level y ave of TD, bu increased frequency of use was significantly a ut o associated w increasin levels of TD. with ng FIGURE 8-1 Distribut tion of tobacc dependenc among each tobacco pro co ce h oduct use grou in the up Population Assessment on Tobacco and Health Study Wave 1 t S 1. SOURCE Strong et al 2017. E: l., PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

DEPENDENCE AND ABUSE LIABILITY 8-35 The results of this study highlight the importance of considering the relative validity of symptom indicators across different tobacco products. Given that certain measurements of dependence symptoms differ in their relative validity, the prevalence and means severity estimates may be less accurate and perhaps biased for one product versus another. Nonetheless, the bulk of the indicator symptoms (21 of 24) in this study exhibited consistent relationships with the primary dependence dimension for each product, suggesting that that any error or bias across products may be modest, and 16 of the 24 were deemed to have minimal or no differential validity across products after substantial empirical scrutiny. The highly rigorous approach of estimating a well-vetted index with a comprehensive set of items is a major strength of the study, as was the use of a large nationally representative sample and separation of multiple mutually exclusive single and poly-product user groups. In addition to providing precise mean dependence severity estimates of e-cigarette users relative to other user groups, this study shows that frequency of e-cigarette use is significantly associated with severity of dependence. This provides additional evidence that, as with combustible tobacco cigarettes and other drugs of abuse, dependence severity is higher among those who use more frequency. Limitations include the use of a cross-sectional design, which leaves unclear whether the association between level of e-cigarette use and dependence is a result of greater exposure to the product increasing severity of dependence, more frequent use as a consequence of the strong drive to use, or other confounding influences. The omission of other covariates in these analyses and comparisons of dependence severity across different product user groups further leaves unclear the role of alternate explanations for observed associations other than a causal effect. In sum, this study provides robust evidence that the typical level of dependence symptoms among exclusive e- cigarette users is comparable to cigar users and lower than combustible tobacco cigarette users in the U.S. population. In addition, the association between frequency of use and dependence among exclusive e-cigarette users further suggests that dependence symptoms are directly linked to e-cigarette exposure. Studies Using Non-Representative Sampling Johnson and colleagues (2017) surveyed 117 e-cigarette users attending a large Southeastern e-cigarette convention in fall of 2015. Modified questions from the Fagerström Test for Cigarette Dependence (FTCD) adapted for e-cigarette use and other questions were administered via a paper and pencil survey at the convention center lobby. Total scores were then categorized into one of four categories to approximate the clinical cutoffs for the FTCD. These categories were “low dependence” (score = 1 to 2, n = 20, 17.1 percent of respondents), “low to moderate dependence” (score = 3 to 4, n = 26, 22.2 percent), “moderate dependence” (score 5 to 7; n = 53, 45.3 percent), and “high dependence” (score = 8 or higher; n = 18, 15.4 percent of respondents). Hence, a significant proportion of the sample was classified as moderate or high dependence. Of the sample, 10 percent also used combustible tobacco cigarettes. This low prevalence may reflect a selection bias. Although smokers were not removed from the analysis, current or past smoking status were not significantly different across the modified-FTCD e- cigarette dependence severity categories suggesting the confounder of current smoking was modest. Length of e-cigarette use was positively associated with e-cigarette dependence category. More than half of respondents who have used e-cigarettes for more than a year were ranked as moderately or highly nicotine dependent (70.5 percent). Less than half (45.7 percent) who have used e-cigarettes for less than a year were ranked as moderately to highly nicotine dependent. There is a statistical trend for differences between those who used e-liquid with PREPUBLICATION COPY: UNCORRECTED PROOFS

8-36 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES (versus without) nicotine and modified-FTCD dependence level (p = .054). Among those who used e-liquid without nicotine, 36.4 percent were classified as low, 22.7 percent were low-to- moderate, 36.4 percent were moderate, and 4.6 percent were high dependence. In those who used e-liquid with nicotine, the distribution was shifted toward more severe dependence, such that 12.8 percent were low, 22.3 percent were low-to-moderate, 46.8 percent were moderate, and 18.1 percent were high. The idiosyncratic and highly selected sample limits the generalizability of the findings and raises considerable questionability regarding the generalizability of the prevalence estimates. Furthermore, the sample was modest and statistical comparisons did not adjust for confounders. In sum, this study provides weak suggestive evidence that dependence symptoms are of appreciable prevalence, associated with chronicity of use, and are higher among those who use nicotine. In a letter to the editor, Gonzalez-Roz and colleagues (2017) reported nicotine dependence levels in a sample of “experienced e-cigarette users” (n = 39; males = 77 percent) and current combustible tobacco cigarette smokers (n = 42; males = 57 percent). The authors administered adapted and non-adapted versions of both the FTCD and the Nicotine Dependence Syndrome Scale (NDSS) to e-cigarette and combustible tobacco cigarette users, respectively. The authors also collected biochemical markers of carbon monoxide and urinary cotinine analysis. Based on the mean scores of each group the authors concluded that “(1) e-cigarette users were dependent on e-liquids containing nicotine, (2) e-cigarette users were found to be less nicotine dependent than current tobacco cigarette smokers [on all self-report measures]” (Gonzalez Roz et al., 2017, pp. 136-137). Cotinine values did not significant differ between the groups, while CO was higher in smokers than e-cigarette users. This study is subject to the same limitations that all cross-sectional studies using dependence symptom measures that are not psychometrically validated via item-response modeling. Furthermore, because details regarding the recruitment strategy, population, and other variables (e.g., demographics) were not provided nor were adjusted analyses performed, clear conclusions regarding the contribution of this study to the evidence base could not be drawn. This study was judged to provide very weak evidence that e-cigarette dependence symptoms are of appreciable prevalence and severity in e-cigarette users at levels lower than combustible tobacco cigarette users. Anonymous Web Surveys of E-Cigarette Users Foulds and colleagues (2015) collected data on the prevalence and correlates of e- cigarette dependence symptoms among e-cigarette users who completed an online survey. Participation in the survey was voluntary and anonymous; data were collected from December 2012 to August 2014. Participants were recruited by following links to the survey, which the investigators posted on a range of medical websites and those popular among e-cigarette users such as http://www.webMD.com and http://www.e-cigaretteforum.com. Visitors to these sites could also send or post a link to the survey to friends and other websites. The analysis was limited to 3,609 respondents who were exclusive current daily e-cigarette users who had not smoked combustible tobacco cigarettes in the past 30 days. Participants were asked to report on 10 dependence symptoms that comprise the Penn State Electronic Cigarette Dependence Index (PSECDI), which assesses frequency of use, time to first use after awakening, difficulty refraining from use when prohibited, craving, and other related symptoms. An analogously worded cigarette dependence index was also completed. Because participants were all past smokers, they were asked “Think back to a time when you were primarily a traditional cigarette smoker…before you used e-cigs. To the best of your ability, answer the following questions PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPEND DENCE AND ABUSE LI D IABILITY 8-37 regarding your cigare smoking at that time Within-person compa g ette g e.” arisons of th dependenc he ce symptom showed th for nearly all question symptom were more likely and reported at ms hat y ns, ms e higher levels when participants were asked to recall their experience with combu w o r ustible tobac cco cigarettes than their current expe s c erience with e-cigarettes. The M(SD) composite dependence . ) e score for e-cigarettes was 8.1 (3.5), which wo r s ould be classsified as betw tween “low” and “mediu um” severity dependence, which was significantly lower than the correspo d , y n onding M(SD) dependen nce score for combustible tobacco cig r e garettes 14.5 (3.7), whic would be classified as “high” seve 5 ch s erity dependen The e-ci nce. igarette vers combusti tobacco cigarette co sus ible omparison w a “within was n- subject” comparison that rules ou systematic confounder that occur across diffe ut c rs r ferent populatio Howeve given that recall error and other reporting bia for historical ons. er, t rs ases informati were pre ion esent only fo e-cigarette use, these r or e results are hiighly impact by poten ted ntial methodological confo founding. Th authors co he onducted a re egression mo in whic number of odel ch f demograp and e-c phic cigarette and combustible tobacco cig d e garette use c characteristic were inclu cs uded as simulttaneous preddictors of PSECDI score. PSECDI w significan higher in women (versus . was ntly n men), Wh hites (versus other races those with s s), hout (versus with) a college educatio those wh are on, ho older (ve ersus younge those wh have used e-cigs for a longer time those who have previo er), ho d e, ously tried mor e-cigarette models, tho who cur re e ose rrently use an device larg than a co n ger ombustible tobacco cigarette (versus a cigali model), those who us with those who use a more advan c ike t se e nced device with a button (versus othe models), a device that costs greate versus less than $50, a w er t er and those wh use a high concentra ho her ation of nico otine liquid (see Figure 8 8-2). FIGURE 8-2 Depende ence score as a function of nicotine con centration. f NOTE: Pe State Electronic Cigar enn rette Depende ence Index wa adjusted fo gender, age race, educat as or e, tion level, day used an e-cigarette, e-cig ys garette size, e-cigarette but tton, battery, and number o e-cigarettes All of s. between group p values < .003 exce between (1 1-6 and 7-1 mg group, and (2) 13-18 and 19+ mg g ept 1) 12 , g group. SOURCE Foulds et al 2015. E: l., PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

8-38 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Because participation was anonymous and the recruitment method allowed for anyone to complete the survey, the representativeness of the sample is uncertain. The authors note that “those who found out about the survey on specialist websites and took the time to complete the survey are a particularly experienced and likely ‘pro-e-cig’ sample of e-cig users, and it is possible their answers were designed to make e-cigs look ‘good’ relative to traditional cigarettes” (Foulds et al., 2015, p. 191). The authors attempted to address this via sensitivity analyses adjusting for and restricting to self-reported public advocacy for e-cigarettes online (which was reported by 42 percent of participants) and being an e-cigarette retailer (3 percent), which did not affect the main results. The non-representative sample is a limitation, but the fairly large sample is a strength. In sum, this study provides suggestive evidence that e-dependence symptoms are of appreciable severity and lower than for combustible tobacco cigarettes. Higher nicotine concentration and other device characteristics typically associated with greater power and nicotine yield (e.g., newer generation, higher price) are associated with more severe e- cigarette dependence symptoms. A study by Yingst and colleagues (2015) drew from the same dataset as in Foulds and colleagues (2015), and compared dependence symptoms among participants using “first generation” devices (n = 1,048; same size as a combustible tobacco cigarette with no button) and “advanced generation” devices (n = 3,373; larger than a cigarette with a manual button); participants were ever combustible tobacco cigarette smokers who reported using an e-cigarette at least 30 days in their lifetime. Results showed that participants currently using an advanced (compared with first) generation device exhibited greater scores on the PSECDI dependence symptom composite dependence (M(SD): 8.3 (3.3) versus 7.1 (4.0)) and short time to first e- cigarette after wakening (M(SD): 38.7 (60.0) versus 67.3 (116.1) minutes) despite using a liquid with a lower nicotine concentration (M(SD): 15.1(6.6) versus 19.1(12.7) mg/ml). These results were not adjusted for potential confounding covariates, although device type was also associated with dependence scores in the Foulds and colleagues analysis, which did adjust for many relevant confounding factors. While subject to the same limitations as Foulds and colleagues and providing some replicatory findings, this study provides confirmatory evidence that advanced (compared with first) generation devices are associated with higher dependence, and this association is clearly not driven by differences in the nicotine concentration of the liquid. The authors speculate that because advanced generation devices provide more power and greater nicotine delivery per equivalent nicotine composition in e-liquid (Shihadeh and Eissenberg, 2015), greater nicotine exposure to the user may account for the higher dependence levels in advanced versus first generation device users. Dawkins and colleagues (2013) conducted a study of never (n = 6; 4 percent), current (n = 218; 16 percent); and former (n = 1123; 83 percent) smokers who were also current e-cigarette users. Participants recruited on e-cigarette retailer websites completed a web survey on e- cigarette dependence and use characteristics, including several survey questions addressing factors relevant to dependence and abuse liability. In the whole sample, the proportion of survey responses indicating the highest level of endorsement (i.e., “very much so”) was 56.2 percent for an item indicative of abuse liability (“I get a definite nicotine hit from the e-cigarette”) and 18.4 percent for an item indicative of possible dependence (“crave e-cigarettes as much as I do/did tobacco”). The representativeness of this study is questionable given the recruitment method and the cursory survey. In sum, this study provides weak suggestive evidence in support of dependence symptoms (and abuse liability to some degree) in e-cigarette use that is lower than corresponding dependence in combustible tobacco use. PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-39 In a series of three papers reporting on an overlapping sample, Etter (2016; 2015) and Etter and Eissenberg (2015) reported the prevalence and correlates of dependence symptoms among nicotine and tobacco product using respondents in internet surveys. The investigators posted links to the e-cigarette survey on health-related websites, smoking cessation websites, and websites selling e-cigarettes or with information about them October 2012 to September 2014. They collected data for nicotine gum users between 2004 and 2007, also on the Internet. The Fagerström Test for Cigarette Dependence, the Nicotine Dependence Syndrome Scale, the Cigarette Dependence Scale, and adaptations of these scales for e-cigarettes and nicotine gums were used. Additional questions assessing correlates were also included. In Etter and Eissenberg (2015), users of nicotine-containing e-cigarettes reported higher dependence ratings than users of nicotine-free e-cigarettes. The authors also found that, among former smokers, those who had used e-cigarettes for more than three months (long-term users) were less dependent on e-cigarettes than those who used nicotine gum for more than three months were dependent on the gum. Dependence ratings between short-term (3 months or less) users of gums or e-cigarettes had few differences. Cross product findings were judged to carry little weight given the dramatic difference in sampling, methodology, and time frame (2004-2007 versus 2012-2014) across the gum and e-cigarette use groups. The nicotine strength comparisons among e-cigarette users were judged to provide weak evidence, given the non-representative sample and the lack of adjustment for confounders. In Etter (2015), 374 daily users of e-cigarettes who had quit smoking in the previous 2 months had a median time to first e-cigarette that ranged from 15 to 45 minutes across groups, depending on whether participants’ response to the question “Does e-cigarette relieve desire or craving to smoke?” was definitely (median = 15 min), a lot (median = 20), or somewhat/no/maybe (median = 45). This suggests mild to moderate levels of dependence for this particular symptom in the sample and that dependence is higher among those who report that e- cigarettes alleviate combustible tobacco cigarette cravings. No additional relevant analyses were reported. This provides additional weak suggestive evidence of mild to moderate levels of dependence in a sample of e-cigarette users. In Etter (2016), answers from 1,672 current users of e-cigarettes were obtained. Across sample subgroups, responses to dependence- and abuse liability-relevant questions differed by how respondents rated the strength of the throat hit (“very weak,” “rather weak,” “average,” “rather strong,” and “very strong”). The “throat hit” is the specific sensation felt in the back of the throat by users when they inhale e-cigarette aerosol that is also reported with combustible tobacco cigarettes and is believed to be a pleasant sensation of slight irritation of the airways. Unadjusted comparisons indicated that the time of the first e-cigarette tended to be shorter among users who reported a stronger throat hit (indicating more severe dependence), and the median time across the groups ranged from 15 to 30, indicating medium levels of dependence. High prevalence estimates for survey questions assessing rewarding effects and euphoria, indicative of product abuse liability were found overall, including “like the taste of the vapor” (range 75 to 90 percent across groups differentiated by strength of throat hit), “like sensation of vapor when inhaling” (60 to 92 percent), and “feels so good to vape” (59 to 91 percent). For each of these questions, the prevalence tended to be higher among e-cigarette users reporting stronger throat hit in unadjusted comparisons. Overall, this study provides additional suggestive evidence that dependence symptoms and experiences indicative of abuse liability are of moderate to high prevalence and severity and may be higher in those who obtain a stronger throat hit from their product. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-40 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES In sum, the collective papers across these three studies provide suggestive evidence that e-cigarette dependence symptoms and subjective effects of vaping indicative of abuse liability are of appreciable prevalence and severity in samples of users and may associate with nicotine concentration and user characteristics. Additional Descriptive Data on E-Cigarette Dependence Symptoms In four small laboratory studies of current e-cigarette users (Goldensen and colleagues [n = 20], Hobkirk and colleagues [n = 9], Nichols and colleagues [n = 7], and Dawkins and colleagues [n = 11]), mean dependence symptom reports were incidentally reported to provide descriptive data on the sample (Dawkins et al., 2016; Goldenson et al., 2016; Hobkirk et al., 2017; Nichols et al., 2016). For the three studies that reported PSESCDI composite scores the range was 6.0 to 8.4, indicating low to moderate levels of nicotine dependence. Dawkins 2016 reported a modified FTCD for e-cigarette mean score of 4.73 and a mean self-rated addiction to e-cigarettes on a 1-5 scale of 3.18 (1.17) in their sample indicating moderate nicotine dependence (Dawkins et al., 2016). These data provide additional suggestive confirmatory data to reports in the epidemiologic data reviewed above that e-cigarette dependence symptoms are non-negligible in various samples of users. HUMAN LABORATORY STUDIES The search resulted in 9 articles that reported original data from 10 separate studies that matched the requirements above (see Table 8-2 for a summary of these studies). Review of the articles revealed that five of the studies compared the effects of e-cigarette products varying in e- liquid flavoring on abuse liability outcomes. Three of these five studies as well as three additional studies also addressed the effect of varying e-cigarette concentration on abuse liability. One of the studies tested nicotine concentration effects. Two studies compared the effects of e-cigarette administration with combustible tobacco cigarette administration among smokers. Studies Testing the Effects of Flavor Goldenson and colleagues (2016) conducted a double-blind, cross-over design study among young adults who reported using e-cigarettes in the past 30 days (n = 20, ages 19 to 34, 80 percent current smokers). Participants used e-cigarette devices with Joyetech “Delta 23 Atomizer” tanks connected to a Joyetech “eVic Supreme” battery (recent-generation device) filled with e-cigarette solutions (Dekang Biotechnology Co., Ltd., 50/50 propylene glycol/vegetable glycerin) in 10 flavors (6 sweet: peach, watermelon, blackberry, cotton candy, cola, and sweet lemon tea; 3 non-sweet: mint, tobacco, and menthol; and 1 flavorless). The participants self-administered 20 standardized 2-puff doses of aerosolized e-cigarette solutions in 3 flavors (sweet versus non-sweet versus flavorless), either with nicotine (6 mg/ml) or without (0 mg/ml [placebo]). After each administration, participants rated three abuse liability indicators (liking, willingness to use again, and perceived monetary value), perceived sweetness, and throat hit strength. Each flavor was presented twice (once in 6mg/ml and once in placebo) resulting in 20 total administrations all occurring on a single visit. Before testing, participants were trained on how to follow the standardized puffing procedure that was used for each trial to equalize the PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-41 “dose” of product administered for each condition, which involved a 10-second preparation, 4- second inhalation, 1-second hold, and 2-second exhale—approximating typical vaping topography. Results showed that sweet-flavored solutions produced significant greater abuse liability rating for each index compared with non-sweet and flavorless (ps < .0001). Throat hit ratings were greater for nicotine than placebo, but did not significantly increase abuse liability nor interact with flavor effects on abuse liability outcomes. Controlling for flavor and nicotine, perceived sweetness was positively associated with each abuse liability outcome. To account for the influence of pre-existing flavor preferences, the authors examined results in a subsample of participants who reported regularly using non-sweet flavors (n = 9). Consistent with results in the overall sample, all outcomes were positively associated with sweetness ratings (ps < 0.0001). As in the overall sample, results among the subsample showed higher mean abuse liability ratings for sweet flavored solutions compared with non-sweet and flavorless solutions. However, for each appeal rating, the main effects for flavors (ps = 0.09 to 0.17) and pairwise contrasts of sweet-flavored to non-sweet or flavorless solutions (ps = 0.06 to 0.23) did not reach statistical significance. Additional tests of whether participants could correctly guess the characterizing flavor of each liquid administered after each administration indicated that participants’ accuracy was not significantly better than chance guessing, suggesting upholding of the study blind to participants regarding the flavor they received. The study strengths include the use of three to five different flavors per flavor category and analyses correlating sweetness ratings with abuse liability outcomes, suggesting a more generalized phenomenon across multiple different types of products that e-liquids with flavors that produce perceptions of sweetness also were of higher abuse liability. The standardized puffing procedure to equate the dose of administration was also a strength of the study, because it can prevent confounding of flavor or nicotine condition with the duration of puff taken. The null nicotine finding should be interpreted with the caveat that the study design was not well suited to detect and isolate nicotine’s pharmacological effects, given that participants were rapidly exposed to multiple products with and without nicotine in a short time frame and that participants were not required to be deprived from nicotine to participate in the test session. Therefore, the participants likely had to base their ratings on the acute sensory response rather than a more generalized pharmacological effect that may take several minutes to generate. In addition, outcomes were limited to self-report, which reflects one aspect of abuse liability that may or may not be parallel with other indicators (e.g., willingness to work for vaping). In sum, this study provides fairly strong evidence that sweet flavorings enhance subjective abuse liability indexes in young adults and provides limited evidence regarding the impact of nicotine on abuse liability. Using a within-subjects design, Audrain-McGovern and colleagues (2016) conducted three human laboratory sessions among young adult daily smokers who had previously tried e- cigarettes at least once, but used e-cigarettes less often than daily (n = 32). Participants used an “e-GO” tank-style e-cigarette with a single 2.2-2.4 ohm resistance coil that could not be adjusted, 650 mAh rechargeable lithium ion battery, and a 2.4 ml refillable e-liquid tank. The first session asked participants to rate unflavored and sweet (green apple and chocolate) flavored e-cigarettes with nicotine on how satisfying and good they tasted to evaluate the rewarding value of flavoring. The sweet flavor that produced the higher reward rating for each the respective participant was used as the “flavored” product to use over the next two sessions for comparison with the unflavored e-cigarette. To assess the relative reinforcing value of a sweet flavored e- PREPUBLICATION COPY: UNCORRECTED PROOFS

8-42 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES cigarette compared with an unflavored e-cigarette, the second session applied a choice task that evaluated the willingness to “work” in the form of moving a computer mouse to hit targets on one of two computer screens, to earn points toward flavored or unflavored e-cigarette puffs. Session 3 measured the absolute reinforcing value of sweet-flavored versus unflavored e- cigarettes via a 90-min ad libitum vaping session where puffs from each e-cigarette product (sweet flavored versus unflavored) were counted. Results of the study were clear and consistent. Rating on a 1-7 scale, the average subjective rewarding value rating was significantly higher for the chocolate-flavored (M = 3.69, SD = 1.78), and green apple-flavored (M = 4.22, SD = 1.55) product than the unflavored (M = 3.11, SD = 1.55) product. Participants worked harder for flavored e-cigarette puffs than for unflavored e-cigarette puffs (p < 0.0001). Total work was 596.31 responses (mouse clicks on targets) for the flavored e-cigarette (SD = 520.25; range 0 to 1,375) and 126.66 for the unflavored e-cigarette). During ad lib use over a 90-minute period, participants took twice as many flavored puffs than unflavored e-cigarette puffs (40 versus 23 puffs; IRR = 2.028, CI 1.183-3.475, p = 0.01). The study strengths include the use of three different abuse liability outcomes, each of which provides unique information about abuse liability (i.e., one addressing the subjective experience, one addressing the motivation to obtain the product, one addressing self- administration under unconstrained conditions) and each yielding convergent results. A limitation was e-cigarette exposure eligibility criteria in the sample—all were ever users who had not progressed to become daily users—which may restrict generalizability to users who may be most prone to dependence (i.e., those who have already become daily vapers). At the same time, because all had experience using e-cigarettes, the likelihood that inability to use e-cigarettes properly had an impact on findings is low. In addition, the subjective reward finding should be interpreted with the caveat that one of the two items in the subjective reward index was “tasted good,” which would be expected to be highly dependent on flavor. A more ideal subjective reward outcome would involve the inclusion of multiple elements indicative of self-reported reward value (e.g., product liking, mood elevation, desire to use again) to parse whether the result depended entirely on the fact that the sweet-flavored products tasted better than the unflavored product. Because all products contained nicotine, whether the effects of flavor on abuse liability would generalize across different nicotine concentrations (including no nicotine) is unknown. Overall, the study provides clear and consistent evidence across three different types of abuse liability outcomes indicating that sweet-flavored products produced higher abuse liability than unflavored products in young adult smokers. Rosbrook and Green (2016) conducted two experiments testing the effects of e-cigarette administration varying in menthol and nicotine concentration on subjective abuse liability ratings and sensory effects. Each experiment involved 32 adult smokers ages 18 to 45 (6 subjects participated in both experiments). In both experiments, the majority of subjects were self- reported menthol cigarette smokers (25 in experiment 1 and 26 in experiment 2). Five subjects in experiment 1 and twelve subjects in experiment 2 reported using e-cigarettes regularly. Both studies used the V2 Standard E-Cigarette device (79 mm; VMR Products, LLC) and V2 blank cartridges. In the first experiment, cartridges were filled with 15 different e-liquids (Pace Engineering Concepts, LLC) with 5 different concentrations of nicotine (0, 6, 12, 18, 24 mg/ml) and 3 different concentrations of menthol (0.0 percent, 0.5 percent or 3.5 percent l-menthol) in a 70/30 propylene glycol (PG)/glycerol base. In the second experiment, the cartridges were filled with six different e-liquids each at 0 or 24 mg/ml nicotine: two menthol and two menthol–mint PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-43 commercial flavors (70/30 PG/glycerol; AmericaneLiquidStore) and two unflavored e-liquids (PG/glycerol base only; Pace Engineering Concepts, LLC). Participants were trained in the puffing and rating procedure prior to the testing, which involved taking two “priming puffs” into the mouth only, then to fully inhale the third puff as they normally would when smoking a combustible tobacco cigarette and to exhale through the mouth. After exhalation the subject was prompted to rate liking or disliking the flavor on a scale with 11 semantic labels, ranging from “most dislike imaginable” to “most like imaginable” with “neutral” in the middle and other intermediate descriptors. Participants also rated three other sensory effects. Testing occurred on a single day for both experiments and participants were required to be deprived from tobacco overnight. The study was double blind. For both experiments, the e-liquids were only “slightly liked” on average. For the first experiment, the degree of liking did not vary significantly across nicotine or menthol concentrations. For the second experiment, the main effect of flavor showed higher ratings for liking of the commercial menthol and menthol–mint flavors over the unflavored e-liquid (p < 0.001). Nicotine and nicotine x flavor interactions were not significant. Sensory effect ratings of nicotine and menthol were reported, suggesting independent and interactive effects of nicotine and menthol in an expected direction on outcomes like coolness and harshness/irritation. The sensory effect results were consistent with the known effects of these substances from the combustible tobacco cigarette literature and validate the robustness of the menthol and nicotine manipulations. The results of these experiments should be interpreted within the following caveats. All participants were combustible tobacco cigarette smokers, most of whom did not report frequent use of e-cigarettes. Hence, most participants may have been unfamiliar with e-cigarettes and how to use them, which could impact sensitivity to manipulations in flavor and nicotine. Also, such individuals would be expected to be less likely to be prone to dependence on e-cigarettes given that most were not (yet) users. The use of a relatively low-powered device that likely delivers less nicotine and flavor constituents than do more powerful devices leaves unclear whether these results would generalize to other popular products. Critically, all e-liquids for the first experiment and the unflavored liquid for the second experiment were created by a private engineering company and were merely PG, glycerol, and l-Menthol. E-liquids available on the marketplace generally contain numerous other additives to enhance the sweetness and remove aversive tastes and sensory qualities (see Chapter 5 for discussion of flavorings). Hence, the absence of effects of menthol flavoring on liking in the first experiment may bear modest relevance to the mentholated e-liquids used in the population. Indeed, in the second experiment when commercial menthol and menthol mint flavorings were used, the liking ratings were significantly higher relative to the unflavored solution containing only PG and glycerol. Finally, the use of a single item rating of liking is a very narrow indicator of abuse liability. In sum, this study provides moderately strong controlled evidence that commercially available menthol and menthol-mint flavors produce greater subjective product liking than unflavored e-liquids among smokers. In a study by St.Helen and colleagues (2017), 11 males and 3 females participated in a 3- day inpatient crossover study with strawberry, tobacco, and their usual flavor e-liquid on subjective product liking ratings indicative of abuse liability and other outcomes. Exclusive e- cigarette users or dual users of fewer than five combustible tobacco cigarettes per day, who used second and/or third generation e-cigarettes at least 25 days per month for the past 3 months or more, and had saliva cotinine levels at least 30 ng/ml were eligible. Commercially available PREPUBLICATION COPY: UNCORRECTED PROOFS

8-44 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES strawberry and tobacco test e-liquids (Bulkejuice.com) with 60/40 and 56/44 PG/glycerol and with 19-20 mg/ ml nicotine were used in the two test e-liquid conditions, The participants own e- liquid was used for the comparison condition, each of which had sweet characterizing flavor names (with the exception of one participant who used a flavor that was “tobacco/vanilla”), with a range from 1.6 mg/ ml to 186.7mg/ ml across participants (M[SD] = 7.4 [5.3]) and a mean(SD) PG/glycerol ratio of 63/37 (18/18). For each session from 4 to 10 p.m., subjects could vape ad libitum to become acclimatized to the assigned flavor for the next day. Participants were abstinent overnight until the morning standardized session of 15 puffs, which was followed by 4 hours of abstinence, and then a 90-minute ad lib use session followed by subjective measures. For the standardized puffing procedure, participants took 15 puffs, one puff every 30 seconds, from the e-cigarette. Puff duration was not controlled by the study. Multiple blood draws were taken, and subjective questionnaires were administered 5 to 15 minutes post puffing. Results showed that for the standardized session, the tobacco and strawberry test e- liquids were not significantly different for mood enhancement or any subjective satisfaction or reward rating. While statistical tests for comparisons to the usual brand e-liquid were not reported, positive mood M(SD) change scores from pre to post administration were 2.8 (1.6) for usual brand compared with 0.2 (1.1) and 0.4 (1.6) for strawberry and tobacco, respectively, which are suggestive of greater mood enhancement for usual brand than the test e-liquids. A similar pattern was found for M(SD) satisfaction ratings (usual brand: 17.1 [0.9], strawberry: 12.4 [1.2]; tobacco: 13.2 [1.5]). After the ad lib session, mean ± SEM for the “taste good” ratings of the strawberry, tobacco, and usual e-liquids were 3.4 ± 0.4, 3.1 ± 0.5, and 5.9 ± 0.3, respectively (maximum possible score of this item is 7). The usual flavor was rated significantly higher than the strawberry and tobacco e-liquids (p-values < 0.001), while the strawberry and tobacco e-liquids were not significantly different for this outcome. For average satisfaction, subjects reported ratings with the strawberry (p = 0.002) and tobacco (p < 0.001) e-liquids compared with the usual brand e-liquids. Ratings of enjoyment of sensations in chest and throat were lower for both the strawberry (p = 0.022) and tobacco (p = 0.019) e-liquids compared with the usual brand e- liquids. The findings of the study should be interpreted with the caveat that the primary goal was to determine effects of flavorings on nicotine pharmacokinetics, and subjective measures were secondary outcomes. Hence, the study sample size, although appropriate for studying effects on nicotine blood yield, was underpowered to detect meaningful effects for subjective abuse liability relevant outcomes. Nonetheless, the controlled design, inclusion of both standardized and ad lib testing conditions, and inclusion of regular e-cigarette users with experimentally controlled tobacco product deprivation enhances the internal validity of the study, particularly for the standardized session test results. The ad lib session subjective ratings are subject to between condition variations in the “dose” of product self-selected by the participants. As the e- liquids self-selected by the user varied widely in nicotine concentration, PG/VG, and characterizing flavor, the particular product characteristics driving differences between usual brand and test e-liquids cannot be determined. At the same time, there is ecological validity to be gained by the using the participants own e-liquids given their ability to self-select the product likely to be highly rewarding to their own preferences. In sum, the study provides tentative evidence that self-selected e-liquids produce greater satisfaction and potential other indicators of abuse liability than experimenter provided e-liquids in experienced e-cigarette users. PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-45 Studies Testing the Effects of Nicotine Concentration Using a double-blind within-participants design, counterbalanced design with two conditions (low and high nicotine), Dawkins and colleagues (2016) conducted a study of experienced vapers who completed 60 minutes of ad libitum vaping in two separate sessions. The participants were eleven experienced male e-cigarette users (reported using e-cigarettes daily for more than 3 months) who currently used a second- or third-generation e-cigarette, and used 24 mg/ml at least once in the past 6 months. Participants abstained from nicotine use (including from e-cigarettes) for 12 hours prior to study commencement and were tested individually. In the laboratory, the investigators provided the participants with the study device—a Joyetech “eVic™ supreme” e-cigarette with a “Nautilus Aspire” tank; 3.9 V [8.5 W; 1.8 resistance], adjusted to the largest airflow and filled with Halo Smokers’ Angels brand e- liquid (50/50 PG/glycerol, 6 mg/ml [low] or 24 mg/ml [high] labeled nicotine). The researchers asked study participants to vape ad libitum for 60 minutes, after which they completed a Visual Analogue Scale rating assessing positive effects indicative of abuse liability (e.g., hit and satisfaction) and other effects for the preceding product self-administered. Hit and satisfaction levels (mean percentage [SD]) were higher in the high nicotine condition (hit: 61.86 [31.50); satisfaction: 60.70 [17.30]) than in the low nicotine condition (hit: 44.73 [23.00]; satisfaction 46.89 [16.93]), but these differences did not reach statistical significance. Given that the sample size was small (n = 11), it is likely that the study was underpowered to detect effects, which raises the possibility that the non-significant differences may be type-II errors. Liquid consumption, puff number, and puff duration were significantly higher in the low nicotine condition compared with the high nicotine condition (all ps < 0.01), which the authors interpreted engaging in compensatory puffing behavior in order to increase nicotine yield toward titration to achieve equal nicotine exposure in the two conditions. Approximately twice the overall puff consumption was recorded from the 6 mg/ml versus the 24 mg/ml conditions. Despite the fact that the amount of product consumed was clearly more in low versus high nicotine condition, the evidence trended toward greater subjective abuse lability indicators addressing a pharmacological drug effect (i.e., “hit” rating) and subjective satisfaction in the higher nicotine condition. Thus, even though the study design allowing consumption to be uncontrolled was likely biased toward larger effects for low nicotine due to more consumption in this condition, the results tended to show the opposite. Strengths include the inclusion of experienced vapers and experimentally controlled deprivation from nicotine prior to the test session, which is a strong design for detecting abuse liability effects due to the pharmacological effects of nicotine exposure. Limitations include very small sample limited to males only. Taken together, these findings provide tentative evidence that nicotine may enhance some subjective effects indicative of abuse liability; however, no firm conclusion can be drawn due to the absence of statistically significant results (ps = .09 to .11). In a fully within-subjects design involving adult DSM-IV diagnosed nicotine-dependent smokers (n = 28), Perkins and colleagues (2015) examined the effect of controlled administration of e-cigarettes with 36 mg/ml nicotine concentration compared with a placebo on subjective abuse liability ratings and other measures. None of the participants reporting using e-cigarettes weekly either currently or in the past, and none had used within the prior 2 weeks of participating, suggesting relatively little e-cigarette use experience. In two counterbalanced lab sessions, each following overnight abstinence., participants self-administered e-cigarettes from PrimeVapor LLC, with pre-filled cartridges containing a glycerol-based e-liquid (labeled PREPUBLICATION COPY: UNCORRECTED PROOFS

8-46 PUBLI HEALTH CONSEQU IC H UENCES OF E-CIGARET TTES nicotine concentratio 36 mg/ml or 0 mg/ml) in either th “Rawhide Red (Tobac c on ) he cco)” non- menthol flavor and “Freeport (M Menthol)” me enthol flavor A KR808D Type aut r. D-1 tomatic e- cigarette battery was used. The procedure inv p volved self-aadministratio of 10 fou on ur-second puffs over 5 minutes. To co m ontrol the “d dose” of exposure, the re esearchers em mployed com mputer-prese ented instructio to guide and standard the prec timing a duration of each puf inhalation. ons dize cise and n ff . After the first set of 10 puffs, sub e 1 bjects indica on a 0-1 00 visual an ated nalog scale (aanchored by “not y at all” an “extremely”) several ratings relev to abuse liability (e.g “liking”) nd r vant e g., Results showed that participants prov R vided significcantly highe ratings on an indicator of er r strength of drug effec (e.g., “how much nico o ct w otine”) and o two indica on ators of subj jective rewar rd (i.e., “lik king” and “saatisfied”) for the nicotine e-cigarette than the pla r e acebo produc (see Figur 8- ct re 3). Other outcomes were studied that are not considered within the sc r w cope of the rreview. The highly co T ontrolled tigh design with an adequa ht sample for a within-subje ately sized s ect laborator study mak this study highly rigo ry kes y orous. Becau subjectiv abuse liab use ve bility reports were not a primary outcome, the data collected were fair cursory an do not ad rly nd ddress multip ple manifesta ations of abu liability. Outside of this factor an the use of what would be conside use t nd f d ered a less pow werful devic the metho were ver strong. In sum, this st ce, ods ry tudy provide rigorous es evidence that e-cigar rettes with a high dose of nicotine ve f ersus placebo increase ab o buse liability y ratings am mong combu ustible tobac cigarette cco e-dependent smokers. FIGURE 8-3 Subjectiv reward res ve sponses for th nicotine e-c he cigarette and the placebo ( (non-nicotine) e- ) cigarette. NOTE: *p < .05 betwe e-cigarette ** = < .01 between e-cigarettes; *** = < .001 be p een es; 1 ** etween e- cigarettes. SOURCE Adapted fro Perkins et al., 2015. E: om t PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

DEPENDENCE AND ABUSE LIABILITY 8-47 A study conducted by Baldessarri and colleagues (2017) included four daily e-cigarette users who had been vaping 1 month or longer and three smokers who consumed more than 10 combustible tobacco cigarettes per day for the past year. The goal was to study nicotine receptor occupancy using a positron emission tomography neuroimaging protocol examining responses to an e-cigarette or combustible tobacco cigarette challenge. Self-report product liking ratings were collected. However, inspection of the study showed that four e-cigarette users participated in two scans each (8 mg/ml and 36 mg/ml EC), and only two of the users underwent a third scan with a placebo (0 mg/ml EC). Hence, the sample was too small to permit meaningful within-person comparisons across e-cigarette nicotine doses. The three healthy smokers participated in one scan with the combustible tobacco cigarette challenge, but did not participate in the e-cigarette challenge, making cross-product comparisons confounded by between-subject group differences. Thus, this study could not be used to make any conclusions regarding the evidence. As reviewed above in the section on studies testing the flavor effects, Goldenson and colleagues (2016) and Rosbrook and colleagues (2016) each examined the effects of varying nicotine concentration on study outcomes and found no significant effect of nicotine variation on abuse liability relevant measures. However, both studies used a multi-condition exposure paradigm in which conditions of varying nicotine levels were administered within a short time frame and in small doses (e.g., either a single puff or two puffs). These designs are aimed to address the sensory effects of manipulations and are poorly suited for isolating the effect of a single pharmacologically-active dose of nicotine, which requires a sufficient dosage amount (e.g., likely at least 10 puffs), following a period of nicotine deprivation. Hence, the nicotine effect findings from these studies are considered to provide little weight to the evidence determinations regarding whether nicotine concentration alters the abuse liability of e-cigarettes. Comparisons of E-Cigarettes to Combustible Tobacco Cigarettes and Other Products In 28 e-cigarette naïve current smokers, Strasser and colleagues (2016) compared the effects of own brand combustible tobacco cigarette smoking on abuse liability outcomes versus an e-cigarette product as a within subject design factor. As an additional between-subjects factor, when the participants were challenged with an e-cigarette, subjects were randomized to receive one of five brands of e-cigarette cigalike brands to determine whether brand variation within the e-cigarette class affected study outcomes: (1) NJOY, 18 mg nicotine; (2) V2, 18 mg nicotine; (3) Green Smoke, 18.9-20.7 mg nicotine; (4) blu, 20-24 mg nicotine; and (5) White Cloud, 23-24 mg nicotine. On day 1, participants were allowed to smoke their own regular brand of combustible tobacco cigarette for a 10-minute period and then provided subjective rewarding effects of the combustible tobacco cigarette (e.g., satisfying, calming, pleasant, smoke another right now). Participants were then provided with their supply of e-cigarettes based on randomization and instructed to refrain from any tobacco/nicotine use aside from the e-cigarette provided for the remaining 9 study days. Participants were instructed to use their assigned e-cigarette as much as desired. Participants returned to lab on days 5 and 10 for 2 identical testing sessions that followed the exact procedures as described for day 1, except that participants used the e-cigarette ad libitum during a 10-minute vaping period, and ratings were based on the e-cigarette challenge. The main finding of the study in regard to the abuse liability outcome was that when comparing the relative self-reported liking assessed at day 1 (M = 627.0; SE = 43.0; in reference to their own combustible tobacco cigarette), and later, reports of liking of the e-cigarette were significantly lower at day 5 (M = 340.4; SE = 31.2) and day 10 (M = 343.6; SE = 39.6). There was no main effect for e-cigarette brand or an interaction effect for e-cigarette liking (p > .05). PREPUBLICATION COPY: UNCORRECTED PROOFS

8-48 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES The study result should be interpreted with the caveat of having a very small sample size for brand versus brand between-group comparisons (n = 6 per group). All participants were current daily combustible tobacco cigarette smokers who had no or minimal prior e-cigarette use experience and who were willing to switch to e-cigarettes for 10 days, making this particular group perhaps not generalizable to certain segments of the population at risk for e-cigarette dependence. As noted by the author, the study used an older cigalike model and results may not extend to newer-generation devices. The use of only tobacco flavor also tempered the authors’ conclusions. Hence, the test might have been biased toward detecting lower product liking for e- cigarettes relative to the standard brand. In addition, the ad lib uncontrolled puff administration resulted in the participants using their own combustible tobacco cigarette for a longer period of time during the 10 minute self-administration interval than the duration of use of the e-cigarette products in the 10 minute interval. In sum, this study provides fairly weak evidence regarding lower abuse liability of first generation e-cigarette device relative to own brand combustible tobacco cigarettes among e-cigarette naïve smokers and inconclusive evidence whether or not product variation within the e-cigarette product class affects abuse liability. Stiles and colleagues (2017) evaluated the abuse liability of three e-cigarettes (Vuse Solo brand, labeled nicotine concentrations of 14, 29, or 36 mg per e-liquid cartridge; solvent, flavoring additives, or characterizing labels and device properties not reported) relative to “high- and low-abuse liability” comparator products (usual brand combustible tobacco cigarettes and nicotine gum, respectively) among 45 e-cigarette–naïve smokers. For inclusion in the study, subjects were required to be adults ages 21 to 60, smoke 10 or more non-menthol 83 mm (king size) to 100 mm combustible tobacco cigarettes per day for at least 6 months, and typically smoke their first combustible tobacco cigarette of the day within 30 minutes of waking. Products used as comparators were any combustible, filtered, nonmenthol brand style, 83 mm [king size] to 100 mm in length for the high-abuse liability comparator and Nicorette® White Ice Mint nicotine polacrilex gum, 4 mg (GlaxoSmithKline Consumer Healthcare, L.P.) for the low-abuse liability product. Subjects participated in a 7-day ambulatory home use trial of each product before each of five test visits to allow subjects to become accustomed to using the new products. Subjects were required to abstain from smoking for 12 hours prior to reporting to the clinic on the morning of each test visit. The testing consisted of up to 10 minutes use of Vuse Solo or smoking of one combustible tobacco cigarette, or up to 30 minutes using nicotine gum according to the package instructions. Five questionnaires were administered to assess subjective endpoints: Product Liking, Intent to Use Product Again, Product Effects, Urge to Smoke, and Urge for Product measured at multiple time points out to 2 hours following use. Results showed that product liking was lower for the three Vuse Solo e-cigarettes (LS [least square] mean peak scores ranging from 4.13 to 4.57) compared with combustible tobacco cigarettes (LS mean peak score value = 9.06, p < 0.001 for all), and higher than nicotine gum (LS mean peak score value = 3.21, p < 0.05 for all). Ratings of Intent to Use Again followed a similar pattern. Whether the three different doses of nicotine were different from one another on abuse liability outcomes was not reported, though inspection of mean scores across the conditions suggests the differences are smaller among the different e-cigarette products than PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-49 TABLE 8-4 Product Liking for Vuse Solo E-Cigarettes with Different Nicotine Concentrations Compared with Usual Brand Combustible Tobacco Cigarette and Nicotine Gum LS means Parameter Vuse Solo Vuse Solo Vuse Solo Usual Brand Nicotine 14 mg 29 mg 36 mg Cigarette Gum Product Liking (AUEC15-360) 1,396.68a,b 1,430.66 a,b 1,190.01 a,b 3,116.52 799.38 Emax 4.36 a,b 4.57 a,b 4.13 a,b 9.06 3.21 Intent to Use Again (AUEC15-360) 1,619.43 a,b 1,635.82 a,b 1,400.99 a,b 2,369.30 1,091.84 Emax 4.71 a,b 4.75 a,b 4.07 a,b 6.81 3.29 Liking of Positive Effects (AUEC15-360) 727.42 800.57 a 673.67 889.74 444.17 Emax 6.71 a,b 6.51 a,b 5.99 a 8.31 5.47 Disliking of Negative Effects (AUEC15-360) 502.66 827.42 740.85 423.38 422.14 Emax 6.03 6.41 6.67 5.80 6.28 NOTE: a = Significantly different from usual brand cigarette, p < 0.05; ,b = Significantly different from nicotine gum, p < 0.05 SOURCE: Stiles et al., 2017. relative difference from combustible tobacco cigarette and gum conditions (see Table 8-4). Subjects used the greatest e-liquid in the Vuse Solo 14 mg device (0.061 g), followed by Vuse Solo 29 mg (0.048 g), and Vuse Solo 36 mg (0.026 g) based on the average difference in the weights of the e-liquid cartridges. Strengths of the study include use of multiple doses of nicotine to elucidate pharmacological dose–response effects and inclusion of both combustible tobacco cigarette and nicotine gum as active comparator conditions. However, the failure to control the amount of product administered across visits due to the ad lib design for the test session as well as uncontrolled exposure during the 7-day ambulatory period leaves the confounding effects of exposure on study outcomes unclear. Furthermore, the study did not provide data on the flavoring additives, vehicle compound, and device parameters (e.g., voltage, resistance) used. Hence, the generalizability beyond the product to other e-cigarettes that vary in nicotine concentration is unclear. In sum, this study provides suggestive evidence that an e-cigarette product may have intermediate abuse liability relative to nicotine gum (low abuse liability) and combustible tobacco cigarettes (higher abuse liability) among e-cigarette naïve smokers. Vansickel and colleagues (2012) conducted a study of e-cigarette-naïve current smokers. Participants completed a behavioral choice abuse liability task evaluating the relative reinforcing value of e-cigarette and usual brand combustible tobacco cigarettes versus money; subjective abuse liability ratings were also collected. Participants were given a “Vapor King” (KR808 model) e-cigarette with a rechargeable 3.7 v battery and air flow sensor with a lighted display end and disposable cartomizer to use. “WOW Cowboy” or “WOW Cowboy Menthol” tobacco flavored cartomizers (18 mg/ml nicotine; commonly used nicotine strength; Vapor4Life) were matched to participants’ combustible tobacco cigarette flavor preference (i.e., non-menthol, or menthol). The first of four, within-subject sessions was an e-cigarette administration session that involved six, 10-puff bouts (30-second interpuff interval) with each bout separated by 30- minutes. In the remaining three sessions, participants made choices among 10 e-cigarette puffs and varying amounts of money, 10 own brand puffs and varying amounts of money, and 10 e- cigarette puffs and a varying number of own brand combustible tobacco cigarette puffs, respectively, using a standardized multiple-choice procedure. The primary outcome for three choice sessions was the “crossover value,” the point at which participants chose to receive (1) money over 10 puffs from the e-cigarette, (2) money over 10 puffs of their own brand PREPUBLICATION COPY: UNCORRECTED PROOFS

8-50 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES combustible tobacco cigarette, or (3) own brand puffs over 10 puffs from the e-cigarette, for each respective session. Results showed that after the first administration session, e-cigarette administration increased ratings on these measures with each successive sampling session, for ratings of “pleasant” (F6,114 = 21.1, p < .0001), “satisfying” (F6,114 = 19.5, p < .0001), “taste good” (F6,114 = 20.2, p = .0001), and “use another right now.” For the choice procedure sessions, crossover values were greater in the own brand combustible tobacco cigarettes versus money choice condition relative to the crossover or the e-cigarette versus money condition. Collapsed across time, the average crossover value was $1.06 (SD = $0.16) for choosing money versus e- cigarette, but was $1.50 (SD = $0.26) for choosing money over own brand combustible tobacco cigarette, indicating greater reinforcing effects of smoking. For the task of pitting choices of e- cigarette and own brand combustible tobacco cigarette puffs, the average crossover value, collapsed across time, was 3 own brand puffs (SD = 0.4 puffs), indicating that 10 e-cigarette puffs were equivalent to 3 own-brand puffs. It can be concluded that the e-cigarette carried some abuse liability (albeit lower than combustible tobacco cigarettes) because probability of choosing vaping systematically increased as monetary values decreased, suggesting there was a significant reward value ascribed to e-cigarettes, and participants were willing to forgo a meaningful amount of money for e-cigarette puffs. The use of multiple operationalizations of abuse liability and a rigorous behavioral choice procedure to ascribe a relative value of e-cigarettes versus both money and combustible tobacco cigarettes are key strengths. The study also showed that the e-cigarette administration significantly increased plasma nicotine, verifying that the manipulation was robust. However, the nicotine boost was lower than what is typically observed via a standard combustible tobacco cigarette. Hence, the abuse liability estimates could reflect conditions and products that may underestimate what regular smokers may choose to use. In sum, this study provides strong evidence that e-cigarettes possess abuse liability in regular smokers and suggestive evidence that the relative abuse liability is lower than the smoker’s usual combustible tobacco cigarette brand used. In a study by Vansickel and colleagues (2010), 32 e-cigarette naïve smokers took 10 standardized puffs from one of four conditions in a within-subject cross-over design: own brand combustible tobacco cigarette, “NPRO” electronic cigarettes (NPRO, NJOY; 18 mg cartridge), “Hydro” electronic cigarettes (Hydro, Crown 7; 16 mg cartridge), or sham (unlit combustible tobacco cigarette) conditions. Participants were daily smokers of 15 or more cigarettes per day and e-cigarette naïve. Flavor (tobacco or menthol) of the product was matched to the preferred flavor used for participants own combustible tobacco cigarette brand. Five, 15, 30, and 45 minutes after the 10 puffs of the respective product (including puffs of the unlit “sham” combustible tobacco cigarette), participants responded to the subjective effect questionnaires. This cycle was repeated twice for each study visit/product condition. The authors found significant condition-by-time interactions for ratings of “satisfying,” “pleasant,” and “taste good.” In particular, ratings of “satisfying” and “pleasant” increased significantly at all time points with use of the Hydro e-cigarette, NPRO e-cigarette, and own- brand combustible tobacco cigarettes. Ratings of “satisfying” and “pleasant” increased significantly higher for own-brand combustible cigarettes than those for Hydro e-cigarette or NPRO e-cigarette (see Figure 8-4). This study had strengths in that a detailed four condition comparison was made, including two separate products with a strong inactive control condition (i.e., sham) and an active PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPEND DENCE AND ABUSE LI D IABILITY 8-51 comparis condition (i.e., usual brand comb son n l bustible tobaacco cigarett The mult te). ti-time point t detailed assessment strategy incr a s reased statisttical power. One strength was the assessment of h f biomarke and physiological ou ers utcomes sens sitive to nico otine. These r results indic cated that, wi ithin the first 5 minutes of administrat f tion, smoking own-brand combustibl tobacco cigarettes g d le significan increase plasma ni ntly ed icotine and heart rate, bu use of the NPRO e-cig h ut garette, Hydr e- ro cigarette, and sham smoking did not. Thus, th first-gene , s he eration produ used in this study w ucts were likely ineeffective at delivering ni d icotine and th reflect a insensitive test of abu liability hus an e use relative to the produc available in the mark cts ketplace toda Furtherm ay. more, the e-ci igarette naïve participan were like not well- nts ely -versed in prroper use of e-cigarettes for obtainin efficient ng nicotine yield. Nonet y theless, there were still some differen e s nces betwee these prod en ducts and the e sham con ndition. In su this stud provides additional su um, dy a uggestive evvidence that ee-cigarette products may carry some abuse liability, but not at levels as high as c s l s combustible tobacco e cigarettess. Clin nical Trials The search re T evealed two clinical trials in which sm c mokers were provided p e products to u at use their own leisure. Th section de n his escribes seco ondary outco omes, which involved ra h atings of e- cigarette and other co omparison products base on recall o use exper ed of riences. In a cross-ove trial, 38 cu n er urrent smoke (age 18 a older) us e-cigaret or nicoti ers and sed ttes ine oral inhalers each for 3 days, in random orde with a wa r r er, ashout period in between (Steinberg et d n al., 2014) The resear ). rchers provid the parti ded icipants with three e-cigarettes (disp h posable, reguular- FIGURE 8-4 Interac E ctions between time and condition (H Hydro e-ciga arette, NPRO e-cigarette O e, own-bran combustib tobacco cigarette, an sham [unl combustib tobacco c nd ble nd lit ble cigarette]) fo or subjectiv effects. ve SOURCE Vansickel et al., 2010 E: l 0. PR REPUBLICA ATION COP UNCO PY: ORRECTED PROOFS D

8-52 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES flavor blu e-cigarettes with 20-24 mg/ml nicotine) and nicotine inhalers (plastic, pen-shaped containers with cartridges containing 10 mg nicotine and that deliver up to 2 mg nicotine each; Pfizer). Participants were instructed on how to use each device. As recommended by the blu instruction manual, the researchers instructed the participants to puff the device as they would their usual combustible tobacco cigarettes; participants were also instructed to use a new device each day. As described in the package insert for the inhalers, participants were instructed to inhale deeply into back of throat or puff in short breaths, trying to use 80 inhalations over 20 minutes. Participants were instructed to use the first product assigned as they wished for a three- day period, which provided sufficient time for participants to learn how to use the devices. After the first product-use period, subjects participated in a post-use visit during which researchers collected product ratings. This was followed by a 3-day washout period, during which participants were instructed to smoke their usual combustible tobacco cigarettes as they wished before using the next product. To gain insight into craving and satisfaction during the product use periods, subjects were instructed to use the e-cigarettes and nicotine inhalers as combustible tobacco cigarette substitutes, but were told that cigarette smoking was permissible if absolutely necessary. The researchers collected retrospective ratings at three time points: baseline, after the 3-day e-cigarette use period, and after the 3-day inhaler use period. The e-cigarette had a higher total satisfaction score (13.9 versus 6.8 [p < 0.001]; range for responses 3-21) and higher reward score (15.8 versus 8.7 [p < 0.001]; range for responses 5-35) than the inhaler. Ratings of combustible tobacco cigarettes and e-cigarette did not differ significantly. In a study, Meier and colleagues (2017) used a double-blind randomized crossover design, smokers (n = 24; 75 percent male; M age = 48.5 years) smoked as usual for one week, followed by two counterbalanced weeks of ad libitum use of first generation e-cigarettes (blu) cigarettes with up to seven prefilled cartridges containing either 16 mg or 0 mg nicotine (regular tobacco flavor or menthol flavor available only). Participants were instructed “this e-cig may or may not contain nicotine; we ask that you try it at least once, but use it however you like; smoke regular cigarettes as you wish.” At the end of each visit, participants reported no differences between the active and placebo e-cigarettes in satisfaction (nicotine M(SD): 3.49 (0.3) versus placebo M(SD): 3.18 (0.3)) or rewarding effects (2.38 (0.2) versus placebo M(SD): 2.36 (0.2)). Collectively these findings provide little additional weight to conclusions given the uncontrolled nature of e-cigarette exposure and use of early generation products CONCLUSIONS Conclusion 8-1. There is substantial evidence that e-cigarette use results in symptoms of dependence on e-cigarettes. Finding: There are several supportive findings from good-quality observational studies with very few or no credible opposing findings that (1) dependence symptoms are of appreciable prevalence or severity or higher in epidemiologic studies of users; and (2) greater frequency or chronicity of use is associated with greater likelihood or severity of dependence symptoms. These are supported by well-designed abuse liability studies that e-cigarette use increases abuse liability, with less credible studies also providing supportive evidence. A firm conclusion can be made, but minor limitations, including chance, bias, and confounding factors, cannot be ruled out with reasonable confidence. PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-53 Conclusion 8-2. There is moderate evidence that risk and severity of dependence are lower for e-cigarettes than combustible tobacco cigarettes. Finding: There are several supportive findings from fair-quality studies with very few or no credible opposing findings. A general conclusion can be made, but limitations, including chance, bias, and confounding factors, cannot be ruled out with reasonable confidence. Conclusion 8-3. There is moderate evidence that variability in e-cigarette product characteristics (nicotine concentration, flavoring, device type, and brand) is an important determinant of risk and severity of e-cigarette dependence. Finding: Some findings support that nicotine concentration, flavoring, device generation, and brand are associated with outcomes indicative of level of dependence risk, with very few or no credible opposing findings. A general conclusion can be made, but limitations, including chance, bias, and confounding factors, cannot be ruled out with reasonable confidence. REFERENCES ADAMHA (Alcohol, Drug Abuse, and Mental Health Administration). 1989. Testing for abuse liability of drugs in humans. https://archives.drugabuse.gov/pdf/monographs/92.pdf (accessed October 9, 2017). APA (American Psychiatric Association). 2013. Diagnostic and statistical manual of mental disorders. 5th ed. Washington, D.C.: American Psychiatric Association. Audrain-McGovern, J., A. A. Strasser, and E. P. Wileyto. 2016. The impact of flavoring on the rewarding and reinforcing value of e-cigarettes with nicotine among young adult smokers. Drug and Alcohol Dependence 166:263-267. Baldassarri, S. R., A. T. Hillmer, J. M. Anderson, P. Jatlow, N. Nabulsi, D. Labaree, K. P. Cosgrove, S. S. O’Malley, T. Eissenberg, S. Krishnan-Sarin, and I. Esterlis. 2017. Use of electronic cigarettes leads to significant beta2-nicotinic acetylcholine receptor occupancy: Evidence from a pet imaging study. Nicotine & Tobacco Research. Benowitz, N. L. 2008. Neurobiology of nicotine addiction: Implications for smoking cessation treatment. American Journal of Medicine 121(4 Suppl 1):S3-S10. Breland, A., E. Soule, A. Lopez, C. Ramoa, A. El-Hellani, and T. Eissenberg. 2017. Electronic cigarettes: What are they and what do they do? Annals of the New York Academy of Sciences 1394(1):5-30. Caggiula, A. R., E. C. Donny, M. I. Palmatier, X. Liu, N. Chaudhri, and A. F. Sved. 2009. The role of nicotine in smoking: A dual-reinforcement model. Nebraska Symposium on Motivation 55:91-109. Carter, L. P., M. L. Stitzer, J. E. Henningfield, R. J. O’Connor, K. M. Cummings, and D. K. Hatsukami. 2009. Abuse liability assessment of tobacco products including potential reduced exposure products (PREPs). Cancer Epidemiology, Biomarkers and Prevention 18(12):3241-3262. CDC (Centers for Disease Control and Prevention). 2016. Quickstats: Cigarette smoking status among current adult e-cigarette users, age group—National Health Interview Survey, section sign United States, 2015. Morbidity and Mortality Weekly Report 65(42):1177. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-54 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Chou, S. P., R. B. Goldstein, S. M. Smith, B. Huang, W. J. Ruan, H. Zhang, J. Jung, T. D. Saha, R. P. Pickering, and B. F. Grant. 2016. The epidemiology of DSM-5 nicotine use disorder: Results from the national epidemiologic survey on alcohol and related conditions-III. Journal of Clinical Psychiatry 77(10):1404-1412. Dawkins, L., and O. Corcoran. 2014. Acute electronic cigarette use: Nicotine delivery and subjective effects in regular users. Psychopharmacology (Berl) 231(2):401-407. Dawkins, L., J. Turner, A. Roberts, and K. Soar. 2013. “Vaping” profiles and preferences: An online survey of electronic cigarette users. Addiction 108(6):1115-1125. Dawkins, L. E., C. F. Kimber, M. Doig, C. Feyerabend, and O. Corcoran. 2016. Self-titration by experienced e-cigarette users: Blood nicotine delivery and subjective effects. Psychopharmacology (Berl) 233(15-16):2933-2941. DiFranza, J. R., J. A. Savageau, K. Fletcher, and et al. 2002. Measuring the loss of autonomy over nicotine use in adolescents: The DANDY (Development and Assessment of Nicotine Dependence in Youths) study. Archives of Pediatrics & Adolescent Medicine 156(4):397-403. Domino, E. F., L. Ni, J. S. Domino, W. Yang, C. Evans, S. Guthrie, H. Wang, R. A. Koeppe, and J. K. Zubieta. 2013. Denicotinized versus average nicotine tobacco cigarette smoking differentially releases striatal dopamine. Nicotine & Tobacco Research 15(1):11-21. Donny, E. C., E. Houtsmuller, and M. L. Stitzer. 2007. Smoking in the absence of nicotine: Behavioral, subjective and physiological effects over 11 days. Addiction 102(2):324-334. Donny, E. C., R. L. Denlinger, J. W. Tidey, J. S. Koopmeiners, N. L. Benowitz, R. G. Vandrey, M. al’Absi, S. G. Carmella, P. M. Cinciripini, S. S. Dermody, D. J. Drobes, S. S. Hecht, J. Jensen, T. Lane, C. T. Le, F. J. McClernon, I. D. Montoya, S. E. Murphy, J. D. Robinson, M. L. Stitzer, A. A. Strasser, H. Tindle, and D. K. Hatsukami. 2015. Randomized trial of reduced-nicotine standards for cigarettes. New England Journal of Medicine 373(14):1340-1349. Etter, J. F. 2015. Explaining the effects of electronic cigarettes on craving for tobacco in recent quitters. Drug and Alcohol Dependence 148:102-108. Etter, J. F. 2016. Throat hit in users of the electronic cigarette: An exploratory study. Psychology of Addictive Behaviors 30(1):93-100. Etter, J. F., and C. Bullen. 2014. A longitudinal study of electronic cigarette users. Addictive Behaviors 39(2):491-494. Etter, J. F., and T. Eissenberg. 2015. Dependence levels in users of electronic cigarettes, nicotine gums and tobacco cigarettes. Drug and Alcohol Dependence 147:68-75. Fagerström, K. 2012. Determinants of tobacco use and renaming the FTND to the Fagerström Test for Cigarette Dependence. Nicotine & Tobacco Research 14(1):75-78. Farsalinos, K. E., D. Tsiapras, S. Kyrzopoulos, M. Savvopoulou, and V. Voudris. 2014. Acute effects of using an electronic nicotine-delivery device (electronic cigarette) on myocardial function: Comparison with the effects of regular cigarettes. BMC Cardiovascular Disorders 14. Fiore, M. C., C. R. Jaen, and T. B. Baker. 2008. Treating tobacco use and dependence: 2008 update, Clinical practice guideline. Rockville, MD: U.S. Department of Health and Human Services, Public Health Service. Foulds, J., S. Veldheer, J. Yingst, S. Hrabovsky, S. J. Wilson, T. T. Nichols, and T. Eissenberg. 2015. Development of a questionnaire for assessing dependence on electronic cigarettes PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-55 among a large sample of ex-smoking e-cigarette users. Nicotine & Tobacco Research 17(2):186-192. Goldenson, N. I., M. G. Kirkpatrick, J. L. Barrington-Trimis, R. D. Pang, J. F. McBeth, M. A. Pentz, J. M. Samet, and A. M. Leventhal. 2016. Effects of sweet flavorings and nicotine on the appeal and sensory properties of e-cigarettes among young adult vapers: Application of a novel methodology. Drug and Alcohol Dependence 168:176-180. Gonzalez Roz, A., R. Secades Villa, and S. Weidberg. 2017. Evaluating nicotine dependence levels in e-cigarette users. Adicciones 29(2):136-138. Griffiths, R. R., and B. Wolf. 1990. Relative abuse liability of different benzodiazepines in drug abusers. Journal of Clinical Psychopharmacology 10(4):237-243. Heatherton, T. F., L. T. Kozlowski, R. C. Frecker, and K. O. Fagerström. 1991. The Fagerström Test for Nicotine Dependence: A revision of the Fagerström Tolerance Questionnaire. British Journal of Addiction 86(9):1119-1127. Henningfield, J. E., D. K. Hatsukami, M. Zeller, and E. Peters. 2011. Conference on abuse liability and appeal of tobacco products: Conclusions and recommendations. Drug and Alcohol Dependence 116(1-3):1-7. Hobkirk, A. L., T. T. Nichols, J. Foulds, J. M. Yingst, S. Veldheer, S. Hrabovsky, J. Richie, T. Eissenberg, and S. J. Wilson. 2017. Changes in resting state functional brain connectivity and withdrawal symptoms are associated with acute electronic cigarette use. Brain Research Bulletin. Hughes, J. R. 2006. Clinical significance of tobacco withdrawal. Nicotine & Tobacco Research 8(2):153-156. Jamal, A., A. Gentzke, S. Hu, K. A. Cullen, B. J. Apelberg, D. M. Homa, and B. A. King. 2017. Tobacco use among middle and high school students—United States, 2011-2016. Morbidity and Mortality Weekly Report 66(23):597-603. Japuntich, S. J., M. E. Piper, T. R. Schlam, D. M. Bolt, and T. B. Baker. 2009. Do smokers know what we’re talking about? The construct validity of nicotine dependence questionnaire measures. Psychological Assessment 21(4):595-607. Johnson, J. M., J. L. Muilenburg, S. L. Rathbun, X. Yu, L. P. Naeher, and J. S. Wang. 2017. Elevated nicotine dependence scores among electronic cigarette users at an electronic cigarette convention. Journal of Community Health. Kasza, K. A., B. K. Ambrose, K. P. Conway, N. Borek, K. Taylor, M. L. Goniewicz, K. M. Cummings, E. Sharma, J. L. Pearson, V. R. Green, A. R. Kaufman, M. Bansal-Travers, M. J. Travers, J. Kwan, C. Tworek, Y. C. Cheng, L. Yang, N. Pharris-Ciurej, D. M. van Bemmel, C. L. Backinger, W. M. Compton, and A. J. Hyland. 2017. Tobacco-product use by adults and youths in the United States in 2013 and 2014. New England Journal of Medicine 376(4):342-353. Kollins, S. H. 2003. Comparing the abuse potential of methylphenidate versus other stimulants: A review of available evidence and relevance to the adhd patient. Journal of Clinical Psychiatry 64(Suppl 11):14-18. Liu, G., E. Wasserman, L. Kong, and J. Foulds. 2017. A comparison of nicotine dependence among exclusive e-cigarette and cigarette users in the path study. Preventive Medicine. Markou, A. 2008. Review. Neurobiology of nicotine dependence. Philosophical Transactions of the Royal Society B: Biological Sciences 363(1507):3159-3168. PREPUBLICATION COPY: UNCORRECTED PROOFS

8-56 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Meier, E., A. E. Wahlquist, B. W. Heckman, K. M. Cummings, B. Froeliger, and M. J. Carpenter. 2017. A pilot randomized crossover trial of electronic cigarette sampling among smokers. Nicotine & Tobacco Research 19(2):176-182. Nichols, T. T., J. Foulds, J. M. Yingst, S. Veldheer, S. Hrabovsky, J. Richie, T. Eissenberg, and S. J. Wilson. 2016. Cue-reactivity in experienced electronic cigarette users: Novel stimulus videos and a pilot FMRI study. Brain Research Bulletin 123:23-32. Perkins, K. A., J. L. Karelitz, and V. C. Michael. 2015. Reinforcement enhancing effects of acute nicotine via electronic cigarettes. Drug and Alcohol Dependence 153:104-108. Piper, M. E., T. M. Piasecki, E. B. Federman, D. M. Bolt, S. S. Smith, M. C. Fiore, and T. B. Baker. 2004. A multiple motives approach to tobacco dependence: The wisconsin inventory of smoking dependence motives (wisdm-68). Journal of Consulting and Clinical Psychology 72(2):139-154. Quester, S., and N. Romanczuk-Seiferth. 2015. Brain imaging in gambling disorder. Current Addiction Reports 2(3):220-229. Reyes-Guzman, C. M., R. M. Pfeiffer, J. Lubin, N. D. Freedman, S. D. Cleary, P. H. Levine, and N. E. Caporaso. 2017. Determinants of light and intermittent smoking in the United States: Results from three pooled national health surveys. Cancer Epidemiology, Biomarkers & Prevention 26(2):228-239. Rosbrook, K., and B. G. Green. 2016. Sensory effects of menthol and nicotine in an e-cigarette. Nicotine & Tobacco Research 18(7):1588-1595. Rose, J. E. 2006. Nicotine and nonnicotine factors in cigarette addiction. Psychopharmacology 184(3):274-285. Rostron, B. L., M. J. Schroeder, and B. K. Ambrose. 2016. Dependence symptoms and cessation intentions among us adult daily cigarette, cigar, and e-cigarette users, 2012-2013. BMC Public Health 16(1):814. Schoenborn, C. A., and R. M. Gindi. 2015. Electronic cigarette use among adults: United States, 2014. NCHS Data Brief (217):1-8. Shiffman, S., A. J. Waters, and M. Hickcox. 2004. The Nicotine Dependence Syndrome scale: A multidimensional measure of nicotine dependence. Nicotine & Tobacco Research 6(2):327-348. Shihadeh, A., and T. Eissenberg. 2015. Electronic cigarette effectiveness and abuse liability: Predicting and regulating nicotine flux. Nicotine & Tobacco Research 17(2):158-162. Soneji, S., J. L. Barrington-Trimis, T. A. Wills, A. M. Leventhal, J. B. Unger, L. A. Gibson, J. Yang, B. A. Primack, J. A. Andrews, R. A. Miech, T. R. Spindle, D. M. Dick, T. Eissenberg, R. C. Hornik, R. Dang, and J. D. Sargent. 2017. Association between initial use of e-cigarettes and subsequent cigarette smoking among adolescents and young adults: A systematic review and meta-analysis. JAMA Pediatrics 171(8):788-797. St.Helen, G., D. A. Dempsey, C. M. Havel, P. Jacob, 3rd, and N. L. Benowitz. 2017. Impact of e-liquid flavors on nicotine intake and pharmacology of e-cigarettes. Drug and Alcohol Dependence 178:391-398. Steinberg, M. B., M. H. Zimmermann, C. D. Delnevo, M. J. Lewis, P. Shukla, E. J. Coups, and J. Foulds. 2014. E-cigarette versus nicotine inhaler: Comparing the perceptions and experiences of inhaled nicotine devices. Journal of General Internal Medicine 29(11):1444-1450. Stiles, M. F., L. R. Campbell, D. W. Graff, B. A. Jones, R. V. Fant, and J. E. Henningfield. 2017. Pharmacodynamic and pharmacokinetic assessment of electronic cigarettes, combustible PREPUBLICATION COPY: UNCORRECTED PROOFS

DEPENDENCE AND ABUSE LIABILITY 8-57 cigarettes, and nicotine gum: Implications for abuse liability. Psychopharmacology (Berl). Strasser, A. A., V. Souprountchouk, A. Kaufmann, S. Blazekovic, F. Leone, N. L. Benowitz, and R. A. Schnoll. 2016. Nicotine replacement, topography, and smoking phenotypes of e- cigarettes. Tobacco Regulatory Science 2(4):352-362. Strong, D. R., J. Pearson, S. Ehlke, T. Kirchner, D. Abrams, K. Taylor, W. M. Compton, K. P. Conway, E. Lambert, V. R. Green, L. C. Hull, S. E. Evans, K. M. Cummings, M. Goniewicz, A. Hyland, and R. Niaura. 2017. Indicators of dependence for different types of tobacco product users: Descriptive findings from Wave 1 (2013–2014) of the Population Assessment of Tobacco and Health (PATH) study. Drug and Alcohol Dependence 178:257-266. Vansickel, A. R., and T. Eissenberg. 2013. Electronic cigarettes: Effective nicotine delivery after acute administration. Nicotine & Tobacco Research 15(1):267-270. Vansickel, A. R., C. O. Cobb, M. F. Weaver, and T. E. Eissenberg. 2010. A clinical laboratory model for evaluating the acute effects of electronic “cigarettes:” Nicotine delivery profile and cardiovascular and subjective effects. Cancer Epidemiology, Biomarkers & Prevention 19(8):1945-1953. Vansickel, A. R., M. F. Weaver, and T. Eissenberg. 2012. Clinical laboratory assessment of the abuse liability of an electronic cigarette. Addiction 107(8):1493-1500. Volkow, N. D., G. F. Koob, and A. T. McLellan. 2016. Neurobiologic advances from the brain disease model of addiction. New England Journal of Medicine 374(4):363-371. Wagner, F. A., and J. C. Anthony. 2002. From first drug use to drug dependence; developmental periods of risk for dependence upon marijuana, cocaine, and alcohol. Neuropsychopharmacology 26(4):479-488. Yingst, J. M., S. Veldheer, S. Hrabovsky, T. T. Nichols, S. J. Wilson, and J. Foulds. 2015. Factors associated with electronic cigarette users’ device preferences and transition from first generation to advanced generation devices. Nicotine & Tobacco Research 17(10):1242-1246. PREPUBLICATION COPY: UNCORRECTED PROOFS

Next: 9 Cardiovascular Disease »
Public Health Consequences of E-Cigarettes Get This Book
×
Buy Prepub | $114.00 Buy Paperback | $105.00
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

Millions of Americans use e-cigarettes. Despite their popularity, little is known about their health effects. Some suggest that e-cigarettes likely confer lower risk compared to combustible tobacco cigarettes, because they do not expose users to toxicants produced through combustion. Proponents of e-cigarette use also tout the potential benefits of e-cigarettes as devices that could help combustible tobacco cigarette smokers to quit and thereby reduce tobacco-related health risks. Others are concerned about the exposure to potentially toxic substances contained in e-cigarette emissions, especially in individuals who have never used tobacco products such as youth and young adults. Given their relatively recent introduction, there has been little time for a scientific body of evidence to develop on the health effects of e-cigarettes.

Public Health Consequences of E-Cigarettes reviews and critically assesses the state of the emerging evidence about e-cigarettes and health. This report makes recommendations for the improvement of this research and highlights gaps that are a priority for future research.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!