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Development and Validation of the Questionnaire of Vaping Craving

Development and Validation of the Questionnaire of Vaping Craving Abstract Introduction Craving may represent core motivational processes in tobacco dependence, but there is no psychometrically evaluated measure of craving for e-cigarettes (vaping craving). This research developed and validated a brief measure of vaping craving. Methods The measure was evaluated in two studies. In Study 1, a 42-item questionnaire assessing a wide range of vaping craving content was administered to 209 current e-cigarette users. In Study 2, a 10-item questionnaire derived from Study 1 results was administered to 224 current e-cigarette users. Participants were recruited from Amazon’s Mechanical Turk, an online labor market. Results Principal factor analysis identified the strongest loading items (.815–.867) on the first extracted factor (77% of the factor variance) for inclusion in a 10-item Questionnaire of Vaping Craving (QVC). This item set, with an internal consistency (α) of .97, focused on desire and intent to vape, and anticipation of positive outcomes related to e-cigarette use. Confirmatory factor analysis revealed the items had strong factor loadings that were significantly predicted by the latent vaping craving construct (ps < .001). Higher vaping craving was significantly associated with the level of e-cigarette use, greater negative mood, and lower confidence in ability to quit vaping (ps < .01). Among participants who also smoked tobacco (87%), vaping craving was more strongly associated with e-cigarette dependence than tobacco dependence. Conclusions The findings support the reliability and validity of the QVC and suggest it could be used in laboratory and clinical settings as a psychometrically sound measure of vaping craving. Implications This study is the first reporting the development and validation of a brief, practical, multi-item measure to assess vaping craving. This psychometrically sound assessment for vaping craving could improve understanding of the nature of vaping craving, advance current tobacco cessation strategies, and increase users’ ability to cope with craving. Introduction Electronic cigarettes (e-cigarettes) have experienced an unprecedented and exponential increase in popularity since their 2007 debut in the United States.1 Indeed, during 2016, 15.4% of the general adult population reported ever using e-cigarettes.2 Some experts predict that sales will exceed those of tobacco cigarettes by the year 2020.3 Research has not adequately kept pace with the rapid emergence of the e-cigarette phenomenon. For example, research on craving for an e-cigarette (or vaping craving) is virtually nonexistent. The popular claim that e-cigarettes help reduce craving for tobacco cigarettes does seem to be well substantiated in the literature;4,5 however, the nature of vaping craving itself is unclear. A validated measure of vaping craving is needed to better understand the underlying processes supporting e-cigarette use, which, as of yet, has not been developed. Craving is a highly salient experience for chronic drug users6 and, according to many models of addiction, a critical precipitant of drug-use.7 Craving is often hypothesized to precede relapse episodes and contribute to high relapse rates.8 Further, reductions in craving are associated with better clinical outcomes in smoking cessation trials (eg, varenicline).9 The importance of craving in the characterization of tobacco use disorder is exemplified by the addition of craving to the diagnostic criteria for substance use disorders in the newest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5).10 A validated assessment of craving is critical for understanding a key feature of the diagnosis of tobacco use disorder. Psychometrically sound craving assessments for e-cigarettes could improve understanding of the nature of vaping craving, advance current tobacco cessation strategies, and increase users’ ability to cope with craving. To date, measurements of vaping craving have largely been adapted from the tobacco cigarette literature and have yet to be empirically validated.11,12 One issue with this approach is that measures of tobacco cigarette craving may not tap into unique features of e-cigarettes that are potentially critical to vaping craving. For example, e-liquid flavoring may be an important motivator of e-cigarette use.13 There are many widely used and empirically validated measures to assess tobacco cigarette craving, and one of the most widely used measures is the Questionnaire on Smoking Urges (QSU).14 Some studies have translated the QSU to e-cigarette-type language (eg, using “vaping” instead of “smoking”),12,15,16 but there is no published information about the psychometrics (ie, reliability and validity) of these assessments. Examinations of the latent structure of multi-item craving questionnaires for various drugs of abuse typically find that, though craving can have multidimensional features, a strong, general craving factor nearly always emerges in the analyses.14,17,18 This general craving factor can be captured with relatively few items, which allows for the development of brief craving assessments. Indeed, many researchers prefer brief craving instruments presumably to minimize the response burden for their research participants. As one example, the brief (10-item) form of the QSU17 is used much more commonly in research than the original 32-item version.14 The goal of the present research was to develop and validate a brief, multi-item measure of vaping craving to assess the general craving factor that we predicted would emerge from a larger candidate item set. Instead of using only one measure of craving to identify items potentially relevant to vaping craving, as was done in previous research, we generated items from two widely used and empirically validated measures of craving, the QSU14 and the Cocaine Craving Questionnaire (CCQ).18 The QSU encompasses four previously recognized conceptualizations of smoking craving14 that were posited to be relevant to vaping craving: desire to vape, anticipation of positive outcomes, anticipation of relief from withdrawal symptoms, and intention to vape. Items from the CCQ were considered for inclusion because they introduced an additional conceptualization, lack of control over use, which might be implicated in motivation to use e-cigarettes. Both the QSU and CCQ have been shown to be reliable and valid measures for the assessment of tobacco and cocaine craving, respectively. We adjusted the language used in the QSU and CCQ items to be appropriate for e-cigarettes (eg, using “vape” instead of “smoke”). In addition, we generated two novel items to capture sensory experiences (ie, olfactory and gustatory sensations) that might be uniquely implicated in motivation to vape e-cigarettes. The proposed vaping craving questionnaire was developed and evaluated in a two-step process with independent samples of e-cigarette users. In the first study, we used exploratory factor analyses to identify items capturing a general craving factor to be included in the Questionnaire of Vaping Craving (QVC). In the second study, we evaluated the psychometrics of the questionnaire and examined its initial convergent and discriminant validity. Methods Study 1 Participants Using guidelines from Floyd and Widaman (1995),19 it was determined that 210 participants were needed to conduct factor analyses for the 42 candidate vaping craving items (5 participants per item). Participants were recruited through Amazon’s Mechanical Turk (MTurk; www.MTurk.com), a popular online labor market for questionnaire validation. MTurk provides access to a large and diverse sample20 and has been shown to be a promising tool to recruit participants with addictive behaviors.21 MTurk also serves as a viable platform to conduct experiments22,23 and validate questionnaires.24,25 Participants were required to be at least 18 years old and have vaped e-cigarettes at least 4 times per week over the past 4 weeks. A total of 232 participants initially completed the assessments. Fifteen participants were excluded for completing the entire set of questionnaires under the amount of time recommended by Qualtrics26 (10 min). Seven participants were excluded due to reporting initiating e-cigarette use over 14 years ago (prior to e-cigarette availability), and one participant was excluded for taking the survey twice and providing inconsistent responses. The remaining 209 participants were adults ages 21 to 69 (M = 32.9, SD = 8.6). Table 1 lists the participant characteristics for Study 1. All participant exclusions have been reported. Table 1. Sample Characteristics M (SD) or % Characteristic Study 1 (n = 209) Study 2 (n = 224) p Value Age 32.9 (8.6) 32.8 (8.8) .91 % Male 66.0% 65.2% .93 Race / Ethnicity  % Caucasian 78.0% 71.4% .12  % Black 8.6% 8.9% .91  % Asian 7.7% 13.8% .04†  % American Indian 3.8% 4.0% .92  % Asian Indian 2.8% 3.1% .88  % Other 3.8% 3.6% .89  % Hispanic / Latino 16.3% 13.4% .40 % ≥ Some college education 85.2% 89.3% .20 % Employed (full or part-time) 84.7% 90.6% .80 Annual income (USD) 34930 (24045) 36598 (24904) .48 Electronic Cigarette Use  Days vaped in past 30 — 19.2 (9.5) —  Times vaped per day (exact) — 13.4 (22.9) —  Times vaped per week (past 4 weeks) 7.9 (1.9) 7.8 (1.9) .10  Times vaped per day (range) 11.3 (10.9) 10.1 (10.1) .24  Cartridges or mL e-liquid vaped per day 3.0 (2.8) 3.1 (3.1) .73  Amount of nicotine in e-liquid (mg/mL)a 9.0 (8.8) 8.7 (7.8) .70  Time since last vaped (hrs) 16.9 (34.7) 26.3 (48.7) .02†  Vaping onset age 28.8 (9.0) 27.2 (8.8) .06  % ≥ 1 e-cigarette quit attempt 20.1% 16.1% .06 Tobacco Cigarette Use  Days smoked in past 30 — 22.6 (9.4) —  Cigarettes smoked per day (ordinal scale) 11.6 (8.7) 9.4 (7.4) .99  Time since last smoked (hrs) 8.6 (28.0) 18.9 (50.3) .01†  Smoking onset age 16.2 (3.5) 16.9 (3.9) .04†  % ≥ 1 tobacco cigarette quit attempt 83.0% 88.3% .08 M (SD) or % Characteristic Study 1 (n = 209) Study 2 (n = 224) p Value Age 32.9 (8.6) 32.8 (8.8) .91 % Male 66.0% 65.2% .93 Race / Ethnicity  % Caucasian 78.0% 71.4% .12  % Black 8.6% 8.9% .91  % Asian 7.7% 13.8% .04†  % American Indian 3.8% 4.0% .92  % Asian Indian 2.8% 3.1% .88  % Other 3.8% 3.6% .89  % Hispanic / Latino 16.3% 13.4% .40 % ≥ Some college education 85.2% 89.3% .20 % Employed (full or part-time) 84.7% 90.6% .80 Annual income (USD) 34930 (24045) 36598 (24904) .48 Electronic Cigarette Use  Days vaped in past 30 — 19.2 (9.5) —  Times vaped per day (exact) — 13.4 (22.9) —  Times vaped per week (past 4 weeks) 7.9 (1.9) 7.8 (1.9) .10  Times vaped per day (range) 11.3 (10.9) 10.1 (10.1) .24  Cartridges or mL e-liquid vaped per day 3.0 (2.8) 3.1 (3.1) .73  Amount of nicotine in e-liquid (mg/mL)a 9.0 (8.8) 8.7 (7.8) .70  Time since last vaped (hrs) 16.9 (34.7) 26.3 (48.7) .02†  Vaping onset age 28.8 (9.0) 27.2 (8.8) .06  % ≥ 1 e-cigarette quit attempt 20.1% 16.1% .06 Tobacco Cigarette Use  Days smoked in past 30 — 22.6 (9.4) —  Cigarettes smoked per day (ordinal scale) 11.6 (8.7) 9.4 (7.4) .99  Time since last smoked (hrs) 8.6 (28.0) 18.9 (50.3) .01†  Smoking onset age 16.2 (3.5) 16.9 (3.9) .04†  % ≥ 1 tobacco cigarette quit attempt 83.0% 88.3% .08 aTwenty-eight participants in Study 1 and twenty-six in Study 2 did not know the amount of nicotine in their e-liquid; †p < .05. View Large Table 1. Sample Characteristics M (SD) or % Characteristic Study 1 (n = 209) Study 2 (n = 224) p Value Age 32.9 (8.6) 32.8 (8.8) .91 % Male 66.0% 65.2% .93 Race / Ethnicity  % Caucasian 78.0% 71.4% .12  % Black 8.6% 8.9% .91  % Asian 7.7% 13.8% .04†  % American Indian 3.8% 4.0% .92  % Asian Indian 2.8% 3.1% .88  % Other 3.8% 3.6% .89  % Hispanic / Latino 16.3% 13.4% .40 % ≥ Some college education 85.2% 89.3% .20 % Employed (full or part-time) 84.7% 90.6% .80 Annual income (USD) 34930 (24045) 36598 (24904) .48 Electronic Cigarette Use  Days vaped in past 30 — 19.2 (9.5) —  Times vaped per day (exact) — 13.4 (22.9) —  Times vaped per week (past 4 weeks) 7.9 (1.9) 7.8 (1.9) .10  Times vaped per day (range) 11.3 (10.9) 10.1 (10.1) .24  Cartridges or mL e-liquid vaped per day 3.0 (2.8) 3.1 (3.1) .73  Amount of nicotine in e-liquid (mg/mL)a 9.0 (8.8) 8.7 (7.8) .70  Time since last vaped (hrs) 16.9 (34.7) 26.3 (48.7) .02†  Vaping onset age 28.8 (9.0) 27.2 (8.8) .06  % ≥ 1 e-cigarette quit attempt 20.1% 16.1% .06 Tobacco Cigarette Use  Days smoked in past 30 — 22.6 (9.4) —  Cigarettes smoked per day (ordinal scale) 11.6 (8.7) 9.4 (7.4) .99  Time since last smoked (hrs) 8.6 (28.0) 18.9 (50.3) .01†  Smoking onset age 16.2 (3.5) 16.9 (3.9) .04†  % ≥ 1 tobacco cigarette quit attempt 83.0% 88.3% .08 M (SD) or % Characteristic Study 1 (n = 209) Study 2 (n = 224) p Value Age 32.9 (8.6) 32.8 (8.8) .91 % Male 66.0% 65.2% .93 Race / Ethnicity  % Caucasian 78.0% 71.4% .12  % Black 8.6% 8.9% .91  % Asian 7.7% 13.8% .04†  % American Indian 3.8% 4.0% .92  % Asian Indian 2.8% 3.1% .88  % Other 3.8% 3.6% .89  % Hispanic / Latino 16.3% 13.4% .40 % ≥ Some college education 85.2% 89.3% .20 % Employed (full or part-time) 84.7% 90.6% .80 Annual income (USD) 34930 (24045) 36598 (24904) .48 Electronic Cigarette Use  Days vaped in past 30 — 19.2 (9.5) —  Times vaped per day (exact) — 13.4 (22.9) —  Times vaped per week (past 4 weeks) 7.9 (1.9) 7.8 (1.9) .10  Times vaped per day (range) 11.3 (10.9) 10.1 (10.1) .24  Cartridges or mL e-liquid vaped per day 3.0 (2.8) 3.1 (3.1) .73  Amount of nicotine in e-liquid (mg/mL)a 9.0 (8.8) 8.7 (7.8) .70  Time since last vaped (hrs) 16.9 (34.7) 26.3 (48.7) .02†  Vaping onset age 28.8 (9.0) 27.2 (8.8) .06  % ≥ 1 e-cigarette quit attempt 20.1% 16.1% .06 Tobacco Cigarette Use  Days smoked in past 30 — 22.6 (9.4) —  Cigarettes smoked per day (ordinal scale) 11.6 (8.7) 9.4 (7.4) .99  Time since last smoked (hrs) 8.6 (28.0) 18.9 (50.3) .01†  Smoking onset age 16.2 (3.5) 16.9 (3.9) .04†  % ≥ 1 tobacco cigarette quit attempt 83.0% 88.3% .08 aTwenty-eight participants in Study 1 and twenty-six in Study 2 did not know the amount of nicotine in their e-liquid; †p < .05. View Large Tobacco cigarette smokers were not explicitly recruited, although smoking behavior was assessed among the 171 (81.8%) participants who reported concurrent tobacco cigarette use. Participants who were dual-users in our sample reported initiating tobacco cigarette smoking at a younger age (M = 16.2, SD = 3.4) compared with vaping (M = 28.8, SD = 9.0), t(170) = 16.48, p = <.001) and smoking an average of 11.6 (SD = 8.68) cigarettes per day. The majority (79.5%) of this sample had made one or more attempts to quit smoking tobacco cigarettes in their lifetime. The large proportion of dual-users was not surprising and reflects the general population of e-cigarette users. Almost all population-based studies show that, among those using e-cigarettes, the majority are current or former smokers.27 Our sample was representative of e-cigarette users in terms of gender and ethnicity relative to nationally representative estimates.28 It is generally more common for e-cigarette users to be in their early 20s (18–24)28 but the average age of participants in this sample was also reasonably representative of e-cigarette users.28 Questionnaire Materials and Procedure Participants were recruited from MTurk and linked to a survey in Qualtrics26 that contained questions to determine eligibility. The survey description disguised the study as an interview about “health” to reduce the likelihood that respondents would falsely endorse e-cigarette use to gain study entry. Participants were asked about their use of six consumable products over the past 6 months, including fast food, energy drinks, artificial sweeteners, alcohol, tobacco cigarettes, and e-cigarettes. Those who reported using a product were asked about their recent consumption quantity (ranging from “never in the past 4 weeks” to “9+ times in the past 4 weeks”). The question assessing e-cigarette use during the past 4 weeks was developed for use in the current study. Participants who were deemed eligible received an opportunity to continue to the questionnaire survey, which began with an informed consent page. They were asked to refrain from vaping or smoking while completing the assessments. Participants who completed the study received $3 for their participation. This research was approved by the Institutional Review Board (IRB) at the University at Buffalo. E-cigarette dependence was assessed with the Penn State Electronic Cigarette Dependence Index (PS-ECDI)29 which demonstrated acceptable internal consistency in this study, α = .71. The tobacco cigarette version of this questionnaire (PS-CDI; Penn State Cigarette Dependence Index)29 was administered for comparison purposes, and also demonstrated acceptable internal consistency, α = .72. Neither the PS-ECDI nor the PS-CDI has undergone a full psychometric validation. Therefore, a validated measure of nicotine dependence, the 12-item Nicotine Addiction Taxon Scale (NATS),30 was administered, which demonstrated good internal consistency, α = .83. Participants completed measures on their smoking and vaping history, including onset (“How old were you when you smoked/vaped your first tobacco/e-cigarette cigarette (in years)?”), past use (eg, “How soon after your first tobacco/e-cigarette did you start smoking/vaping daily?” 1 = I have never smoked/vaped daily, 10 = 2 years or more), and current use (eg, “How long ago did you smoke/use your last tobacco/e-cigarette? 1 = < 30 minutes, 8 = > 1 week; “During the past 30 days, how many days did you vape an e-cigarette?” __ days; open-ended response), confidence in ability to quit for one year (1 = not at all confident, 5 = extremely confident), and number of prior quit attempts. Participants also completed various questions related to their current vaping behaviors that were specifically designed for use in this study (e.g., “On average, what level or amount of nicotine is in your e-liquid?” 1 = < 1 mg/mL, 7 = > 42 mg/mL, 8 = I don’t know, 9 = My e-liquid does not contain nicotine; “On average, how many cartridges or milliliters of e-liquid are you currently vaping each day?” 1 = < 1, 5 = > 10; “How many times per day do you usually use your electronic cigarette?” 1 = 0 – 4, 6 = 30+). To examine whether participants’ current mood would be associated with craving ratings, the 9-item Mood Form31 was administered (eg, “Please indicate how much you are experiencing the following mood right now:” (negative mood) “Unhappy” 1 = Not at all, 7 = Extremely; (positive mood) “Happy” 1 = Not at all, 7 = Extremely). The Mood Form31 demonstrated excellent internal consistency (negative mood α= .93, positive mood α = .92). Questionnaires were completed in a fixed order: PS-CDI, smoking history questions, NATS, PS-ECDI, vaping history questions, demographics, Mood Form, and vaping craving questions. The vaping history questions were developed for use in the current study. Vaping Craving Questions A broad set of vaping craving questions was used to identify potential items for inclusion in the final questionnaire. Items were generated from the QSU14 and the CCQ.18 The 32 items of the QSU and 8 items assessing lack of control over use of the CCQ (item 23 dropped) were modified to assess vaping craving by replacing “smoke” and “smoking” with “vape” or “vaping”, and “cigarette” and “cocaine” with “e-cigarette.” Some item wording was adjusted to enhance succinctness and comprehensibility, and all items were written to be positively keyed. To accommodate criterion A4 of the DSM-5 for Tobacco Use Disorder, “strong” was added to the item, “I have a [strong] desire for an e-cigarette right now.” Because e-cigarette liquid (ie, “e-liquid”) comes in a variety of flavors and scents, two additional items were designed to capture motivational qualities that might be important to vaping craving, including distinctive gustatory (“Right now, the flavor of an e-cigarette would be pleasant”) and olfactory sensory experiences (“I would enjoy the smell of an e-cigarette now”). Vaping craving ratings were made on a 7-point scale (1 = strongly disagree to 7 = strongly agree). The vaping craving questions were administered in an individually randomized order. All measures for Study 1 have been reported. All questions and response options are available upon request from the authors. Study 2 Participants Participant recruitment was largely similar to Study 1. Of note, individuals who reported initiating e-cigarette use more than 14 years prior to their participation in the study were deemed ineligible (whereas in Study 1, these participants’ data were not used in analyses). A total of 236 participants recruited from the MTurk community completed the questionnaires. Of these participants, six were excluded for completing the questionnaire under the amount of time recommended by Qualtrics (8 min). Three were excluded for reporting initiating tobacco cigarette use older than their current age, and three were excluded for reporting the same answer for every vaping craving question (and the same answer for most, if not all, other questionnaires). The remaining participants were 224 adults ages 20 to 68 (M = 32.75, SD = 8.76). Smoking behavior was assessed among the 195 (87%) participants who reported concurrent tobacco cigarette use. The sample was generally similar to Study 1; however, there were more Asian participants in Study 2 (p = .04) and longer latencies since last vaped (p = .02). Table 1 lists the participant characteristics for Study 2. All participant exclusions have been reported. Materials and Procedure Procedures were largely similar to Study 1. In Study 2, open-ended questions developed for use in the current study were included to obtain exact estimates of the number of days vaped and smoked in the past 30 and average number of times vaped and cigarettes smoked per day. The PS-CDI (α = .73), PS-ECDI (α = .74), NATS (α = .87), and Mood Form (negative mood α = .92, positive mood α = .93) demonstrated acceptable to excellent internal consistency. Only the 10 items selected for the QVC were administered in Study 2, which were presented in an individually randomized order. All measures for Study 2 have been reported. Data sets, analytic methods, and study materials are available upon request to the third author. Data Analyses In Study 1, we used principal factor analysis (PFA) to identify vaping craving items to comprise the final QVC. Based on other previously validated craving measures for addictive substances (eg, Alcohol Urge Questionnaire;32 CCQ;18 QSU14), we hypothesized that a strong general vaping craving factor would emerge. We examined factor loadings of the 42-candidate vaping craving items to: (1) determine whether a general craving factor would emerge, and, if so, (2) select the strongest loading items for inclusion in a final 10-item assessment of vaping craving. The PFA was conducted using PROC FACTOR in SAS version 9.4.33 In Study 2, we used confirmatory factor analysis (CFA) to determine if the latent vaping craving construct would predict observed QVC ratings in a second sample of e-cigarette users. Fit indices, factor loadings, and reliability of the items were evaluated. The CFA was conducted using Robust Maximum Likelihood estimation in Mplus version 8.34 Pearson correlations were used to establish convergent and discriminant validity using the reduced item set. Relationships between QVC ratings and variables predicted to be associated with vaping craving were examined, including quantity and frequency of vaping, time since last vaped, e-cigarette dependence (PS-ECDI), confidence in ability to quit vaping, and negative mood. In order to evaluate discriminant validity, we examined associations between QVC ratings and quantity and frequency of tobacco cigarette use, time since last smoked, tobacco and nicotine dependence (PS-CDI and NATS, respectively), and confidence in ability to quit smoking tobacco cigarettes. Tobacco cigarette measures were expected to be more weakly related to QVC ratings than measures specific to e-cigarettes. In these analyses, we removed items specific to craving from e-cigarette, tobacco cigarette, and nicotine dependence measures (PS-ECDI, PS-CDI, NATS) to eliminate overlap in item content and to assess whether the QVC was related to dependence measures without trait-level craving items included. QVC data were treated as continuous in all analyses. Correlations between the QVC and tobacco cigarette measures (both with the craving items and without) appear in Table 3. Missing data for both studies were present only on tobacco cigarette measures for those who indicated they did not smoke cigarettes. These participants were dropped from tobacco-specific correlation analyses. Table 3. Correlations Between the Questionnaire of Vaping Craving (QVC) and E-Cigarette, Mood, and Tobacco Cigarette Measures Variable, N = 224 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. QVC — 2. No. days vaped in past 30 .19* — 3. Times vaped per day .12 .40*** — 4. Cartridges / mL e-liquid vaped per day .31*** .33*** .42*** — 5. Nicotine in e-liquid (mg/mL) .05 .14† .05 .07 — 6. Time since last vaped −.27*** −.47*** −.21* −.22** .09 — 7. Confidence in quitting vaping −.45*** −.29*** −.32*** −.37*** −.04 .23** — 8. E-cigarette dependence (no craving) .47*** .38*** .53*** .47*** .11 −.26*** −.54*** — 9. E-cigarette dependence .51*** .41*** .52*** .47*** .11 −.29*** −.57*** .98*** — 10. Negative mood .33*** .54 −.05 −.05 .10 −.04 −.12 .28*** −.04 — 11. Positive mood .01 −.12 −.13 −.03 −.05 .03 .12 −.02 .29*** −.08 Variable, N = 195 1. 12. 13. 14. 15. 16. 17. 18. 19. 12. No. days smoked in past 30 −.11 — 13. Cigarettes smoked per day .04 .36*** — 14. Time since last smoked .00 −.55*** −.20** — 15. Confidence in quitting smoking −.09 −.29*** −.13 .27** — 16. Tobacco dependence (no craving) .27** .45*** .57*** −.41*** −.37*** — 17. Tobacco dependence .27** .46*** .56*** −.42*** −.40*** .99*** — 18. Nicotine dependence (no craving) .19** .48*** .46*** −.40*** −.44*** .70*** .72*** — 19. Nicotine dependence .22* .48*** .46*** −.40*** −.47*** .71*** .74*** .99*** — Variable, N = 224 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. QVC — 2. No. days vaped in past 30 .19* — 3. Times vaped per day .12 .40*** — 4. Cartridges / mL e-liquid vaped per day .31*** .33*** .42*** — 5. Nicotine in e-liquid (mg/mL) .05 .14† .05 .07 — 6. Time since last vaped −.27*** −.47*** −.21* −.22** .09 — 7. Confidence in quitting vaping −.45*** −.29*** −.32*** −.37*** −.04 .23** — 8. E-cigarette dependence (no craving) .47*** .38*** .53*** .47*** .11 −.26*** −.54*** — 9. E-cigarette dependence .51*** .41*** .52*** .47*** .11 −.29*** −.57*** .98*** — 10. Negative mood .33*** .54 −.05 −.05 .10 −.04 −.12 .28*** −.04 — 11. Positive mood .01 −.12 −.13 −.03 −.05 .03 .12 −.02 .29*** −.08 Variable, N = 195 1. 12. 13. 14. 15. 16. 17. 18. 19. 12. No. days smoked in past 30 −.11 — 13. Cigarettes smoked per day .04 .36*** — 14. Time since last smoked .00 −.55*** −.20** — 15. Confidence in quitting smoking −.09 −.29*** −.13 .27** — 16. Tobacco dependence (no craving) .27** .45*** .57*** −.41*** −.37*** — 17. Tobacco dependence .27** .46*** .56*** −.42*** −.40*** .99*** — 18. Nicotine dependence (no craving) .19** .48*** .46*** −.40*** −.44*** .70*** .72*** — 19. Nicotine dependence .22* .48*** .46*** −.40*** −.47*** .71*** .74*** .99*** — Table displays Pearson correlations between the Questionnaire of Vaping Craving (QVC) and e-cigarette (variable 1–10) and tobacco cigarette measures (variable 12–19) from Study 2. E-cigarette, tobacco cigarette, and nicotine dependence measures show correlations with items specific to craving removed from these measures (no craving) and with craving items included. †p < .05, *p ≤ .01, **p ≤ .001, ***p ≤ .0001. View Large Table 3. Correlations Between the Questionnaire of Vaping Craving (QVC) and E-Cigarette, Mood, and Tobacco Cigarette Measures Variable, N = 224 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. QVC — 2. No. days vaped in past 30 .19* — 3. Times vaped per day .12 .40*** — 4. Cartridges / mL e-liquid vaped per day .31*** .33*** .42*** — 5. Nicotine in e-liquid (mg/mL) .05 .14† .05 .07 — 6. Time since last vaped −.27*** −.47*** −.21* −.22** .09 — 7. Confidence in quitting vaping −.45*** −.29*** −.32*** −.37*** −.04 .23** — 8. E-cigarette dependence (no craving) .47*** .38*** .53*** .47*** .11 −.26*** −.54*** — 9. E-cigarette dependence .51*** .41*** .52*** .47*** .11 −.29*** −.57*** .98*** — 10. Negative mood .33*** .54 −.05 −.05 .10 −.04 −.12 .28*** −.04 — 11. Positive mood .01 −.12 −.13 −.03 −.05 .03 .12 −.02 .29*** −.08 Variable, N = 195 1. 12. 13. 14. 15. 16. 17. 18. 19. 12. No. days smoked in past 30 −.11 — 13. Cigarettes smoked per day .04 .36*** — 14. Time since last smoked .00 −.55*** −.20** — 15. Confidence in quitting smoking −.09 −.29*** −.13 .27** — 16. Tobacco dependence (no craving) .27** .45*** .57*** −.41*** −.37*** — 17. Tobacco dependence .27** .46*** .56*** −.42*** −.40*** .99*** — 18. Nicotine dependence (no craving) .19** .48*** .46*** −.40*** −.44*** .70*** .72*** — 19. Nicotine dependence .22* .48*** .46*** −.40*** −.47*** .71*** .74*** .99*** — Variable, N = 224 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. QVC — 2. No. days vaped in past 30 .19* — 3. Times vaped per day .12 .40*** — 4. Cartridges / mL e-liquid vaped per day .31*** .33*** .42*** — 5. Nicotine in e-liquid (mg/mL) .05 .14† .05 .07 — 6. Time since last vaped −.27*** −.47*** −.21* −.22** .09 — 7. Confidence in quitting vaping −.45*** −.29*** −.32*** −.37*** −.04 .23** — 8. E-cigarette dependence (no craving) .47*** .38*** .53*** .47*** .11 −.26*** −.54*** — 9. E-cigarette dependence .51*** .41*** .52*** .47*** .11 −.29*** −.57*** .98*** — 10. Negative mood .33*** .54 −.05 −.05 .10 −.04 −.12 .28*** −.04 — 11. Positive mood .01 −.12 −.13 −.03 −.05 .03 .12 −.02 .29*** −.08 Variable, N = 195 1. 12. 13. 14. 15. 16. 17. 18. 19. 12. No. days smoked in past 30 −.11 — 13. Cigarettes smoked per day .04 .36*** — 14. Time since last smoked .00 −.55*** −.20** — 15. Confidence in quitting smoking −.09 −.29*** −.13 .27** — 16. Tobacco dependence (no craving) .27** .45*** .57*** −.41*** −.37*** — 17. Tobacco dependence .27** .46*** .56*** −.42*** −.40*** .99*** — 18. Nicotine dependence (no craving) .19** .48*** .46*** −.40*** −.44*** .70*** .72*** — 19. Nicotine dependence .22* .48*** .46*** −.40*** −.47*** .71*** .74*** .99*** — Table displays Pearson correlations between the Questionnaire of Vaping Craving (QVC) and e-cigarette (variable 1–10) and tobacco cigarette measures (variable 12–19) from Study 2. E-cigarette, tobacco cigarette, and nicotine dependence measures show correlations with items specific to craving removed from these measures (no craving) and with craving items included. †p < .05, *p ≤ .01, **p ≤ .001, ***p ≤ .0001. View Large Results Study 1 The first factor accounted for 77.4% of the common factor variance. The eigenvalues for the first three factors were 21.40, 3.26 (10.2% of variance), and 1.11 (3.5%). The 10 strongest loading items on the first factor (range = .815–.867) were included in the QVC. Table 2 lists the 10 strongest loading items on the first factor. The content of these items focused on desire (6 items) and intent (2 items) to vape, as well as anticipation of positive outcomes related to e-cigarette use (2 items). Internal consistency for the 10 items was excellent, α = .96. Table 2. Questionnaire of Vaping Craving (QVC) Items and Content, Meansa and Standard Deviations, and Factor Loadings Factor Loadingsb Item Content Area Study 2 M (SD) Study 1 (PFA) Study 2 (CFA) I have a strong desire for an e-cigarette right now. Desire 3.88 (1.96) .827 .953 I have an urge for an e-cigarette. Desire 3.96 (1.88) .832 .907 All I want right now is an e-cigarette. Desire 3.53 (1.91) .830 .898 I am missing vaping right now. Desire 3.79 (1.90) .843 .889 I am craving an e-cigarette right now. Desire 3.83 (1.84) .815 .888 I need to vape now. Desire 3.53 (1.94) .854 .881 I am going to vape as soon as possible. Intention 4.11 (1.84) .867 .869 I will vape as soon as I get the chance. Intention 4.18 (1.82) .817 .840 Nothing would be better than vaping right now. Positive outcome 3.46 (1.86) .841 .836 Vaping would make me happier now. Positive outcome 4.44 (1.75) .832 .774 QVC Average Score 3.86 (1.67) Factor Loadingsb Item Content Area Study 2 M (SD) Study 1 (PFA) Study 2 (CFA) I have a strong desire for an e-cigarette right now. Desire 3.88 (1.96) .827 .953 I have an urge for an e-cigarette. Desire 3.96 (1.88) .832 .907 All I want right now is an e-cigarette. Desire 3.53 (1.91) .830 .898 I am missing vaping right now. Desire 3.79 (1.90) .843 .889 I am craving an e-cigarette right now. Desire 3.83 (1.84) .815 .888 I need to vape now. Desire 3.53 (1.94) .854 .881 I am going to vape as soon as possible. Intention 4.11 (1.84) .867 .869 I will vape as soon as I get the chance. Intention 4.18 (1.82) .817 .840 Nothing would be better than vaping right now. Positive outcome 3.46 (1.86) .841 .836 Vaping would make me happier now. Positive outcome 4.44 (1.75) .832 .774 QVC Average Score 3.86 (1.67) M = mean; SD = standard deviation. aItems were rated on a 7-point scale (1 = strongly disagree, 7 = strongly agree). bFactor loadings were obtained using principal factor analysis (PFA) in Study 1 (N = 209) and confirmatory factor analysis (CFA) in Study 2 (N = 224). View Large Table 2. Questionnaire of Vaping Craving (QVC) Items and Content, Meansa and Standard Deviations, and Factor Loadings Factor Loadingsb Item Content Area Study 2 M (SD) Study 1 (PFA) Study 2 (CFA) I have a strong desire for an e-cigarette right now. Desire 3.88 (1.96) .827 .953 I have an urge for an e-cigarette. Desire 3.96 (1.88) .832 .907 All I want right now is an e-cigarette. Desire 3.53 (1.91) .830 .898 I am missing vaping right now. Desire 3.79 (1.90) .843 .889 I am craving an e-cigarette right now. Desire 3.83 (1.84) .815 .888 I need to vape now. Desire 3.53 (1.94) .854 .881 I am going to vape as soon as possible. Intention 4.11 (1.84) .867 .869 I will vape as soon as I get the chance. Intention 4.18 (1.82) .817 .840 Nothing would be better than vaping right now. Positive outcome 3.46 (1.86) .841 .836 Vaping would make me happier now. Positive outcome 4.44 (1.75) .832 .774 QVC Average Score 3.86 (1.67) Factor Loadingsb Item Content Area Study 2 M (SD) Study 1 (PFA) Study 2 (CFA) I have a strong desire for an e-cigarette right now. Desire 3.88 (1.96) .827 .953 I have an urge for an e-cigarette. Desire 3.96 (1.88) .832 .907 All I want right now is an e-cigarette. Desire 3.53 (1.91) .830 .898 I am missing vaping right now. Desire 3.79 (1.90) .843 .889 I am craving an e-cigarette right now. Desire 3.83 (1.84) .815 .888 I need to vape now. Desire 3.53 (1.94) .854 .881 I am going to vape as soon as possible. Intention 4.11 (1.84) .867 .869 I will vape as soon as I get the chance. Intention 4.18 (1.82) .817 .840 Nothing would be better than vaping right now. Positive outcome 3.46 (1.86) .841 .836 Vaping would make me happier now. Positive outcome 4.44 (1.75) .832 .774 QVC Average Score 3.86 (1.67) M = mean; SD = standard deviation. aItems were rated on a 7-point scale (1 = strongly disagree, 7 = strongly agree). bFactor loadings were obtained using principal factor analysis (PFA) in Study 1 (N = 209) and confirmatory factor analysis (CFA) in Study 2 (N = 224). View Large Study 2 Estimation of the Robust Maximum Likelihood model chi-square indicated inadequate fit, χ2 (35, N = 224) = 162.50, p < .0001, CFI = .924, SRMR = .031, RMSEA = .128. Considering the poor fit of the initial model, modification indices were examined to determine whether freeing error covariances (ie, letting the error terms correlate with each other) would have led to a significant increment in fit. Modification indices suggested freeing the covariances for three pairs of items: “I need to vape now” and “Nothing would be better than vaping right now,” “I am going to vape as soon as possible” and “I will vape as soon as I get the chance,” and “I have an urge for an e-cigarette,” and “I am craving an e-cigarette right now,” would significantly improve model fit, χ2s ≥ 12.84, ps < .05. Examination of these items indicated similar language that may have resulted in larger error covariances. These covariances were freed to improve model fit. Fit indices for the final CFA model indicated good fit35 for the one-factor solution, χ2 (32, N = 224) = 66.41, p = .0003, CFI = .980, SRMR = .021, RMSEA = .06. All 10 items had strong factor loadings35 (.774–.953; Table 2) and were significantly predicted by the latent vaping craving construct, ts ≥ 24.63, ps < .001. QVC ratings were significantly correlated with several e-cigarette measures (Table 3; N = 224). Higher vaping craving was associated with vaping more cartridges or mL of e-liquid per day (p < .0001), vaping more days in the past 30 (p < .01), less time since last vaped (p < .0001), lower confidence in one’s ability to quit vaping (p < .0001), and greater negative mood (p < .0001). Vaping craving was associated with tobacco dependence (PS-CDI, N = 195, adjusted R2 = .07, p = .0001) and nicotine dependence (NATS, N = 195, adjusted R2 = .03, p = .007), though weaker relationships were found compared to that with e-cigarette dependence. When controlling for tobacco dependence and nicotine dependence in separate regression models, e-cigarette dependence (PS-ECDI) was more strongly related to vaping craving, ∆R2 = .18 and .21, respectively, ps < .0001 (see Supplemental Materials for regression tables). Vaping craving was not significantly associated with times vaped per day, the amount of nicotine in one’s e-liquid, or any other tobacco cigarette measures. These analyses were run in SAS version 9.4.33 Discussion This research was explicitly designed to develop a brief, practical vaping craving questionnaire. As predicted, analyses of a large, diverse item set representing a variety of craving related concepts revealed a strong, general craving factor that accounted for approximately 77% of the common factor variance. This supports previous research demonstrating that, though craving can have multidimensional features, a general craving factor nearly always emerges.14,17,18 The QVC also demonstrated excellent internal consistency, α = .96. This is comparable to the reliabilities reported in the original publications of the QSU-Brief, α = .97 and the CCQ, α = .93. The ten items comprising the QVC were the items with the strongest loadings on the general craving factor. Five of these items were derived from the QSU-Brief and clearly capture the desire aspect of craving (“I have a strong desire for an e-cigarette right now,” “I have an urge for an e-cigarette,” “All I want right now is an e-cigarette,” “I am going to vape as soon as possible,” and “Nothing would be better than vaping right now”). Though all 10 QSU-Brief items were translated for use with e-cigarettes and included in the original 42-item pool, not all were retained for the final QVC. This suggests that vaping craving may be distinct from tobacco cigarette craving and should be assessed as such. The inclusion of desire is consistent with the definition of craving typically adopted by the field.36,37 Structural analyses of craving questionnaires generally show that the primary or first principal factor that emerges in these analyses is often dominated by statements of desire and intention to use,38 a pattern that similarly emerged in the QVC analyses. The items capturing desire included statements of both “craving” and “urge,” and the most strongly loading of all items in the confirmatory analysis of Study 2 was, “I have a strong desire for an e-cigarette right now.” Interestingly, the semantic content of these items conforms to the description used in the DSM-510 for the craving criterion in the diagnosis of substance use disorders, viz. “Craving, or a strong desire or urge to use a substance.” Notably, some multi-item craving questionnaires do not explicitly include desire items (eg, Tobacco Craving Questionnaire;39 Marijuana Craving Questionnaire40), which brings into question their content validity. The pattern of correlations between the QVC and a variety of measures related to tobacco and e-cigarette use provided support for the convergent and discriminant validity of the QVC. Participants with higher vaping craving tended to be heavier e-cigarettes users (ie, these participants tended to vape more e-liquid per day, vaped more days in the past 30, vaped more recently, had lower confidence in their ability quit vaping, and were higher on e-cigarette dependence). Additionally, among duals users of tobacco and e-cigarettes, vaping craving was more strongly associated with e-cigarette dependence than with tobacco or nicotine dependence. This further supports that vaping craving may be distinct from tobacco and nicotine dependence. Strengths The QVC pioneers the effort to create psychometrically sound measures to assess motivational aspects supporting e-cigarette use (specifically, vaping craving). Moreover, the questionnaire offers a practical, multi-item measure to assess vaping craving, which is notably absent from e-cigarette research. Further, the QVC may improve the understanding of vaping craving and advance current tobacco cessation strategies. Its use may help to develop strategies to increase users’ ability to cope with both tobacco and e-cigarette craving, and identify smokers who are more likely to relapse when using e-cigarettes as a smoking cessation aid, thus allowing for appropriate adjustments to their treatment planning. An additional strength of this study is that, unlike some previous questionnaire research, the standard battery of questionnaires containing the QVC was administered electronically. This allowed identification and exclusion of poor data (eg, excluding those who completed the questionnaires in an unreasonably short amount of time). Finally, the brevity of the QVC allows it to be easily used in both research and clinical settings. Of note, this questionnaire was developed from the onset as a short form, and the questionnaire was directly tested in that format in Study 2. Limitations The current research used Amazon MTurk workers and, though they have been shown to generate reliable data for a variety of research questions,25,26 we did not have face-to-face contact with the participants and could not confirm their use of either tobacco or e-cigarettes. This issue, of course, applies to nearly any online or anonymous survey-based research on drug users. Our assertions about the psychometric properties of the QVC are restricted to samples most similar to those recruited for this research and may not generalize to other populations of interest (eg, e-cigarette-only users, adolescents, treatment-seeking individuals). For instance, though the gustatory and olfactory items in the original 42-item did not load strongly onto the first general craving factor, this could have been a function of the sample. It is possible that these types of items would be more salient to e-cigarette-only or novice users. These studies were not powered to detect aspects of vaping craving that may differ between e-cigarette-only users and dual-users; future work should explore this issue. Additionally, the type (ie, generation) of e-cigarettes used by participants was not assessed. Nicotine administration levels vary considerably across devices,15 and, therefore, the type of e-cigarettes participants used may have affected their vaping craving. Finally, this questionnaire only assessed a general vaping craving factor. There may be more nuanced facets of craving that can only be evaluated with a larger number of items of more diverse content. Conclusions Overall, the QVC demonstrated high reliability and clear convergent and discriminant validity. The QVC offers a psychometrically sound measurement of vaping craving that can be used in laboratory and clinical settings. Supplementary Material Supplementary data are available at Nicotine & Tobacco Research online. Funding None to report. Declaration of Interests The authors have no conflicts of interest to report. Acknowledgments The authors would like to acknowledge the research assistants in the Smoking Research Lab for their assistance on this project; specifically, Deonna Coleman, Cynthia Nguyen, Tosin Orisadare-Johnson, David Woloszyn, Ali Barton, Anna Blatto, and Coraima Veliz. This research was not preregistered with an analysis plan in an independent institutional registry. References 1. Rom O , Pecorelli A , Valacchi G , Reznick AZ . Are E-cigarettes a safe and good alternative to cigarette smoking ? Ann N Y Acad Sci . 2015 ; 1340 ( 1 ): 65 – 74 . Google Scholar Crossref Search ADS PubMed 2. Schoenborn C , Clarke T . QuickStats: Percentage of adults who ever used an e-cigarette and percentage who currently use e-cigarettes, by age group – National Health Interview Survey, United States, 2016 . MMWR Morb Mortal Wkly Rep . 2017 ; 66 : 892 . Google Scholar Crossref Search ADS PubMed 3. Wells J . 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Development and Validation of the Questionnaire of Vaping Craving

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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1462-2203
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1469-994X
DOI
10.1093/ntr/nty046
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Abstract

Abstract Introduction Craving may represent core motivational processes in tobacco dependence, but there is no psychometrically evaluated measure of craving for e-cigarettes (vaping craving). This research developed and validated a brief measure of vaping craving. Methods The measure was evaluated in two studies. In Study 1, a 42-item questionnaire assessing a wide range of vaping craving content was administered to 209 current e-cigarette users. In Study 2, a 10-item questionnaire derived from Study 1 results was administered to 224 current e-cigarette users. Participants were recruited from Amazon’s Mechanical Turk, an online labor market. Results Principal factor analysis identified the strongest loading items (.815–.867) on the first extracted factor (77% of the factor variance) for inclusion in a 10-item Questionnaire of Vaping Craving (QVC). This item set, with an internal consistency (α) of .97, focused on desire and intent to vape, and anticipation of positive outcomes related to e-cigarette use. Confirmatory factor analysis revealed the items had strong factor loadings that were significantly predicted by the latent vaping craving construct (ps < .001). Higher vaping craving was significantly associated with the level of e-cigarette use, greater negative mood, and lower confidence in ability to quit vaping (ps < .01). Among participants who also smoked tobacco (87%), vaping craving was more strongly associated with e-cigarette dependence than tobacco dependence. Conclusions The findings support the reliability and validity of the QVC and suggest it could be used in laboratory and clinical settings as a psychometrically sound measure of vaping craving. Implications This study is the first reporting the development and validation of a brief, practical, multi-item measure to assess vaping craving. This psychometrically sound assessment for vaping craving could improve understanding of the nature of vaping craving, advance current tobacco cessation strategies, and increase users’ ability to cope with craving. Introduction Electronic cigarettes (e-cigarettes) have experienced an unprecedented and exponential increase in popularity since their 2007 debut in the United States.1 Indeed, during 2016, 15.4% of the general adult population reported ever using e-cigarettes.2 Some experts predict that sales will exceed those of tobacco cigarettes by the year 2020.3 Research has not adequately kept pace with the rapid emergence of the e-cigarette phenomenon. For example, research on craving for an e-cigarette (or vaping craving) is virtually nonexistent. The popular claim that e-cigarettes help reduce craving for tobacco cigarettes does seem to be well substantiated in the literature;4,5 however, the nature of vaping craving itself is unclear. A validated measure of vaping craving is needed to better understand the underlying processes supporting e-cigarette use, which, as of yet, has not been developed. Craving is a highly salient experience for chronic drug users6 and, according to many models of addiction, a critical precipitant of drug-use.7 Craving is often hypothesized to precede relapse episodes and contribute to high relapse rates.8 Further, reductions in craving are associated with better clinical outcomes in smoking cessation trials (eg, varenicline).9 The importance of craving in the characterization of tobacco use disorder is exemplified by the addition of craving to the diagnostic criteria for substance use disorders in the newest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5).10 A validated assessment of craving is critical for understanding a key feature of the diagnosis of tobacco use disorder. Psychometrically sound craving assessments for e-cigarettes could improve understanding of the nature of vaping craving, advance current tobacco cessation strategies, and increase users’ ability to cope with craving. To date, measurements of vaping craving have largely been adapted from the tobacco cigarette literature and have yet to be empirically validated.11,12 One issue with this approach is that measures of tobacco cigarette craving may not tap into unique features of e-cigarettes that are potentially critical to vaping craving. For example, e-liquid flavoring may be an important motivator of e-cigarette use.13 There are many widely used and empirically validated measures to assess tobacco cigarette craving, and one of the most widely used measures is the Questionnaire on Smoking Urges (QSU).14 Some studies have translated the QSU to e-cigarette-type language (eg, using “vaping” instead of “smoking”),12,15,16 but there is no published information about the psychometrics (ie, reliability and validity) of these assessments. Examinations of the latent structure of multi-item craving questionnaires for various drugs of abuse typically find that, though craving can have multidimensional features, a strong, general craving factor nearly always emerges in the analyses.14,17,18 This general craving factor can be captured with relatively few items, which allows for the development of brief craving assessments. Indeed, many researchers prefer brief craving instruments presumably to minimize the response burden for their research participants. As one example, the brief (10-item) form of the QSU17 is used much more commonly in research than the original 32-item version.14 The goal of the present research was to develop and validate a brief, multi-item measure of vaping craving to assess the general craving factor that we predicted would emerge from a larger candidate item set. Instead of using only one measure of craving to identify items potentially relevant to vaping craving, as was done in previous research, we generated items from two widely used and empirically validated measures of craving, the QSU14 and the Cocaine Craving Questionnaire (CCQ).18 The QSU encompasses four previously recognized conceptualizations of smoking craving14 that were posited to be relevant to vaping craving: desire to vape, anticipation of positive outcomes, anticipation of relief from withdrawal symptoms, and intention to vape. Items from the CCQ were considered for inclusion because they introduced an additional conceptualization, lack of control over use, which might be implicated in motivation to use e-cigarettes. Both the QSU and CCQ have been shown to be reliable and valid measures for the assessment of tobacco and cocaine craving, respectively. We adjusted the language used in the QSU and CCQ items to be appropriate for e-cigarettes (eg, using “vape” instead of “smoke”). In addition, we generated two novel items to capture sensory experiences (ie, olfactory and gustatory sensations) that might be uniquely implicated in motivation to vape e-cigarettes. The proposed vaping craving questionnaire was developed and evaluated in a two-step process with independent samples of e-cigarette users. In the first study, we used exploratory factor analyses to identify items capturing a general craving factor to be included in the Questionnaire of Vaping Craving (QVC). In the second study, we evaluated the psychometrics of the questionnaire and examined its initial convergent and discriminant validity. Methods Study 1 Participants Using guidelines from Floyd and Widaman (1995),19 it was determined that 210 participants were needed to conduct factor analyses for the 42 candidate vaping craving items (5 participants per item). Participants were recruited through Amazon’s Mechanical Turk (MTurk; www.MTurk.com), a popular online labor market for questionnaire validation. MTurk provides access to a large and diverse sample20 and has been shown to be a promising tool to recruit participants with addictive behaviors.21 MTurk also serves as a viable platform to conduct experiments22,23 and validate questionnaires.24,25 Participants were required to be at least 18 years old and have vaped e-cigarettes at least 4 times per week over the past 4 weeks. A total of 232 participants initially completed the assessments. Fifteen participants were excluded for completing the entire set of questionnaires under the amount of time recommended by Qualtrics26 (10 min). Seven participants were excluded due to reporting initiating e-cigarette use over 14 years ago (prior to e-cigarette availability), and one participant was excluded for taking the survey twice and providing inconsistent responses. The remaining 209 participants were adults ages 21 to 69 (M = 32.9, SD = 8.6). Table 1 lists the participant characteristics for Study 1. All participant exclusions have been reported. Table 1. Sample Characteristics M (SD) or % Characteristic Study 1 (n = 209) Study 2 (n = 224) p Value Age 32.9 (8.6) 32.8 (8.8) .91 % Male 66.0% 65.2% .93 Race / Ethnicity  % Caucasian 78.0% 71.4% .12  % Black 8.6% 8.9% .91  % Asian 7.7% 13.8% .04†  % American Indian 3.8% 4.0% .92  % Asian Indian 2.8% 3.1% .88  % Other 3.8% 3.6% .89  % Hispanic / Latino 16.3% 13.4% .40 % ≥ Some college education 85.2% 89.3% .20 % Employed (full or part-time) 84.7% 90.6% .80 Annual income (USD) 34930 (24045) 36598 (24904) .48 Electronic Cigarette Use  Days vaped in past 30 — 19.2 (9.5) —  Times vaped per day (exact) — 13.4 (22.9) —  Times vaped per week (past 4 weeks) 7.9 (1.9) 7.8 (1.9) .10  Times vaped per day (range) 11.3 (10.9) 10.1 (10.1) .24  Cartridges or mL e-liquid vaped per day 3.0 (2.8) 3.1 (3.1) .73  Amount of nicotine in e-liquid (mg/mL)a 9.0 (8.8) 8.7 (7.8) .70  Time since last vaped (hrs) 16.9 (34.7) 26.3 (48.7) .02†  Vaping onset age 28.8 (9.0) 27.2 (8.8) .06  % ≥ 1 e-cigarette quit attempt 20.1% 16.1% .06 Tobacco Cigarette Use  Days smoked in past 30 — 22.6 (9.4) —  Cigarettes smoked per day (ordinal scale) 11.6 (8.7) 9.4 (7.4) .99  Time since last smoked (hrs) 8.6 (28.0) 18.9 (50.3) .01†  Smoking onset age 16.2 (3.5) 16.9 (3.9) .04†  % ≥ 1 tobacco cigarette quit attempt 83.0% 88.3% .08 M (SD) or % Characteristic Study 1 (n = 209) Study 2 (n = 224) p Value Age 32.9 (8.6) 32.8 (8.8) .91 % Male 66.0% 65.2% .93 Race / Ethnicity  % Caucasian 78.0% 71.4% .12  % Black 8.6% 8.9% .91  % Asian 7.7% 13.8% .04†  % American Indian 3.8% 4.0% .92  % Asian Indian 2.8% 3.1% .88  % Other 3.8% 3.6% .89  % Hispanic / Latino 16.3% 13.4% .40 % ≥ Some college education 85.2% 89.3% .20 % Employed (full or part-time) 84.7% 90.6% .80 Annual income (USD) 34930 (24045) 36598 (24904) .48 Electronic Cigarette Use  Days vaped in past 30 — 19.2 (9.5) —  Times vaped per day (exact) — 13.4 (22.9) —  Times vaped per week (past 4 weeks) 7.9 (1.9) 7.8 (1.9) .10  Times vaped per day (range) 11.3 (10.9) 10.1 (10.1) .24  Cartridges or mL e-liquid vaped per day 3.0 (2.8) 3.1 (3.1) .73  Amount of nicotine in e-liquid (mg/mL)a 9.0 (8.8) 8.7 (7.8) .70  Time since last vaped (hrs) 16.9 (34.7) 26.3 (48.7) .02†  Vaping onset age 28.8 (9.0) 27.2 (8.8) .06  % ≥ 1 e-cigarette quit attempt 20.1% 16.1% .06 Tobacco Cigarette Use  Days smoked in past 30 — 22.6 (9.4) —  Cigarettes smoked per day (ordinal scale) 11.6 (8.7) 9.4 (7.4) .99  Time since last smoked (hrs) 8.6 (28.0) 18.9 (50.3) .01†  Smoking onset age 16.2 (3.5) 16.9 (3.9) .04†  % ≥ 1 tobacco cigarette quit attempt 83.0% 88.3% .08 aTwenty-eight participants in Study 1 and twenty-six in Study 2 did not know the amount of nicotine in their e-liquid; †p < .05. View Large Table 1. Sample Characteristics M (SD) or % Characteristic Study 1 (n = 209) Study 2 (n = 224) p Value Age 32.9 (8.6) 32.8 (8.8) .91 % Male 66.0% 65.2% .93 Race / Ethnicity  % Caucasian 78.0% 71.4% .12  % Black 8.6% 8.9% .91  % Asian 7.7% 13.8% .04†  % American Indian 3.8% 4.0% .92  % Asian Indian 2.8% 3.1% .88  % Other 3.8% 3.6% .89  % Hispanic / Latino 16.3% 13.4% .40 % ≥ Some college education 85.2% 89.3% .20 % Employed (full or part-time) 84.7% 90.6% .80 Annual income (USD) 34930 (24045) 36598 (24904) .48 Electronic Cigarette Use  Days vaped in past 30 — 19.2 (9.5) —  Times vaped per day (exact) — 13.4 (22.9) —  Times vaped per week (past 4 weeks) 7.9 (1.9) 7.8 (1.9) .10  Times vaped per day (range) 11.3 (10.9) 10.1 (10.1) .24  Cartridges or mL e-liquid vaped per day 3.0 (2.8) 3.1 (3.1) .73  Amount of nicotine in e-liquid (mg/mL)a 9.0 (8.8) 8.7 (7.8) .70  Time since last vaped (hrs) 16.9 (34.7) 26.3 (48.7) .02†  Vaping onset age 28.8 (9.0) 27.2 (8.8) .06  % ≥ 1 e-cigarette quit attempt 20.1% 16.1% .06 Tobacco Cigarette Use  Days smoked in past 30 — 22.6 (9.4) —  Cigarettes smoked per day (ordinal scale) 11.6 (8.7) 9.4 (7.4) .99  Time since last smoked (hrs) 8.6 (28.0) 18.9 (50.3) .01†  Smoking onset age 16.2 (3.5) 16.9 (3.9) .04†  % ≥ 1 tobacco cigarette quit attempt 83.0% 88.3% .08 M (SD) or % Characteristic Study 1 (n = 209) Study 2 (n = 224) p Value Age 32.9 (8.6) 32.8 (8.8) .91 % Male 66.0% 65.2% .93 Race / Ethnicity  % Caucasian 78.0% 71.4% .12  % Black 8.6% 8.9% .91  % Asian 7.7% 13.8% .04†  % American Indian 3.8% 4.0% .92  % Asian Indian 2.8% 3.1% .88  % Other 3.8% 3.6% .89  % Hispanic / Latino 16.3% 13.4% .40 % ≥ Some college education 85.2% 89.3% .20 % Employed (full or part-time) 84.7% 90.6% .80 Annual income (USD) 34930 (24045) 36598 (24904) .48 Electronic Cigarette Use  Days vaped in past 30 — 19.2 (9.5) —  Times vaped per day (exact) — 13.4 (22.9) —  Times vaped per week (past 4 weeks) 7.9 (1.9) 7.8 (1.9) .10  Times vaped per day (range) 11.3 (10.9) 10.1 (10.1) .24  Cartridges or mL e-liquid vaped per day 3.0 (2.8) 3.1 (3.1) .73  Amount of nicotine in e-liquid (mg/mL)a 9.0 (8.8) 8.7 (7.8) .70  Time since last vaped (hrs) 16.9 (34.7) 26.3 (48.7) .02†  Vaping onset age 28.8 (9.0) 27.2 (8.8) .06  % ≥ 1 e-cigarette quit attempt 20.1% 16.1% .06 Tobacco Cigarette Use  Days smoked in past 30 — 22.6 (9.4) —  Cigarettes smoked per day (ordinal scale) 11.6 (8.7) 9.4 (7.4) .99  Time since last smoked (hrs) 8.6 (28.0) 18.9 (50.3) .01†  Smoking onset age 16.2 (3.5) 16.9 (3.9) .04†  % ≥ 1 tobacco cigarette quit attempt 83.0% 88.3% .08 aTwenty-eight participants in Study 1 and twenty-six in Study 2 did not know the amount of nicotine in their e-liquid; †p < .05. View Large Tobacco cigarette smokers were not explicitly recruited, although smoking behavior was assessed among the 171 (81.8%) participants who reported concurrent tobacco cigarette use. Participants who were dual-users in our sample reported initiating tobacco cigarette smoking at a younger age (M = 16.2, SD = 3.4) compared with vaping (M = 28.8, SD = 9.0), t(170) = 16.48, p = <.001) and smoking an average of 11.6 (SD = 8.68) cigarettes per day. The majority (79.5%) of this sample had made one or more attempts to quit smoking tobacco cigarettes in their lifetime. The large proportion of dual-users was not surprising and reflects the general population of e-cigarette users. Almost all population-based studies show that, among those using e-cigarettes, the majority are current or former smokers.27 Our sample was representative of e-cigarette users in terms of gender and ethnicity relative to nationally representative estimates.28 It is generally more common for e-cigarette users to be in their early 20s (18–24)28 but the average age of participants in this sample was also reasonably representative of e-cigarette users.28 Questionnaire Materials and Procedure Participants were recruited from MTurk and linked to a survey in Qualtrics26 that contained questions to determine eligibility. The survey description disguised the study as an interview about “health” to reduce the likelihood that respondents would falsely endorse e-cigarette use to gain study entry. Participants were asked about their use of six consumable products over the past 6 months, including fast food, energy drinks, artificial sweeteners, alcohol, tobacco cigarettes, and e-cigarettes. Those who reported using a product were asked about their recent consumption quantity (ranging from “never in the past 4 weeks” to “9+ times in the past 4 weeks”). The question assessing e-cigarette use during the past 4 weeks was developed for use in the current study. Participants who were deemed eligible received an opportunity to continue to the questionnaire survey, which began with an informed consent page. They were asked to refrain from vaping or smoking while completing the assessments. Participants who completed the study received $3 for their participation. This research was approved by the Institutional Review Board (IRB) at the University at Buffalo. E-cigarette dependence was assessed with the Penn State Electronic Cigarette Dependence Index (PS-ECDI)29 which demonstrated acceptable internal consistency in this study, α = .71. The tobacco cigarette version of this questionnaire (PS-CDI; Penn State Cigarette Dependence Index)29 was administered for comparison purposes, and also demonstrated acceptable internal consistency, α = .72. Neither the PS-ECDI nor the PS-CDI has undergone a full psychometric validation. Therefore, a validated measure of nicotine dependence, the 12-item Nicotine Addiction Taxon Scale (NATS),30 was administered, which demonstrated good internal consistency, α = .83. Participants completed measures on their smoking and vaping history, including onset (“How old were you when you smoked/vaped your first tobacco/e-cigarette cigarette (in years)?”), past use (eg, “How soon after your first tobacco/e-cigarette did you start smoking/vaping daily?” 1 = I have never smoked/vaped daily, 10 = 2 years or more), and current use (eg, “How long ago did you smoke/use your last tobacco/e-cigarette? 1 = < 30 minutes, 8 = > 1 week; “During the past 30 days, how many days did you vape an e-cigarette?” __ days; open-ended response), confidence in ability to quit for one year (1 = not at all confident, 5 = extremely confident), and number of prior quit attempts. Participants also completed various questions related to their current vaping behaviors that were specifically designed for use in this study (e.g., “On average, what level or amount of nicotine is in your e-liquid?” 1 = < 1 mg/mL, 7 = > 42 mg/mL, 8 = I don’t know, 9 = My e-liquid does not contain nicotine; “On average, how many cartridges or milliliters of e-liquid are you currently vaping each day?” 1 = < 1, 5 = > 10; “How many times per day do you usually use your electronic cigarette?” 1 = 0 – 4, 6 = 30+). To examine whether participants’ current mood would be associated with craving ratings, the 9-item Mood Form31 was administered (eg, “Please indicate how much you are experiencing the following mood right now:” (negative mood) “Unhappy” 1 = Not at all, 7 = Extremely; (positive mood) “Happy” 1 = Not at all, 7 = Extremely). The Mood Form31 demonstrated excellent internal consistency (negative mood α= .93, positive mood α = .92). Questionnaires were completed in a fixed order: PS-CDI, smoking history questions, NATS, PS-ECDI, vaping history questions, demographics, Mood Form, and vaping craving questions. The vaping history questions were developed for use in the current study. Vaping Craving Questions A broad set of vaping craving questions was used to identify potential items for inclusion in the final questionnaire. Items were generated from the QSU14 and the CCQ.18 The 32 items of the QSU and 8 items assessing lack of control over use of the CCQ (item 23 dropped) were modified to assess vaping craving by replacing “smoke” and “smoking” with “vape” or “vaping”, and “cigarette” and “cocaine” with “e-cigarette.” Some item wording was adjusted to enhance succinctness and comprehensibility, and all items were written to be positively keyed. To accommodate criterion A4 of the DSM-5 for Tobacco Use Disorder, “strong” was added to the item, “I have a [strong] desire for an e-cigarette right now.” Because e-cigarette liquid (ie, “e-liquid”) comes in a variety of flavors and scents, two additional items were designed to capture motivational qualities that might be important to vaping craving, including distinctive gustatory (“Right now, the flavor of an e-cigarette would be pleasant”) and olfactory sensory experiences (“I would enjoy the smell of an e-cigarette now”). Vaping craving ratings were made on a 7-point scale (1 = strongly disagree to 7 = strongly agree). The vaping craving questions were administered in an individually randomized order. All measures for Study 1 have been reported. All questions and response options are available upon request from the authors. Study 2 Participants Participant recruitment was largely similar to Study 1. Of note, individuals who reported initiating e-cigarette use more than 14 years prior to their participation in the study were deemed ineligible (whereas in Study 1, these participants’ data were not used in analyses). A total of 236 participants recruited from the MTurk community completed the questionnaires. Of these participants, six were excluded for completing the questionnaire under the amount of time recommended by Qualtrics (8 min). Three were excluded for reporting initiating tobacco cigarette use older than their current age, and three were excluded for reporting the same answer for every vaping craving question (and the same answer for most, if not all, other questionnaires). The remaining participants were 224 adults ages 20 to 68 (M = 32.75, SD = 8.76). Smoking behavior was assessed among the 195 (87%) participants who reported concurrent tobacco cigarette use. The sample was generally similar to Study 1; however, there were more Asian participants in Study 2 (p = .04) and longer latencies since last vaped (p = .02). Table 1 lists the participant characteristics for Study 2. All participant exclusions have been reported. Materials and Procedure Procedures were largely similar to Study 1. In Study 2, open-ended questions developed for use in the current study were included to obtain exact estimates of the number of days vaped and smoked in the past 30 and average number of times vaped and cigarettes smoked per day. The PS-CDI (α = .73), PS-ECDI (α = .74), NATS (α = .87), and Mood Form (negative mood α = .92, positive mood α = .93) demonstrated acceptable to excellent internal consistency. Only the 10 items selected for the QVC were administered in Study 2, which were presented in an individually randomized order. All measures for Study 2 have been reported. Data sets, analytic methods, and study materials are available upon request to the third author. Data Analyses In Study 1, we used principal factor analysis (PFA) to identify vaping craving items to comprise the final QVC. Based on other previously validated craving measures for addictive substances (eg, Alcohol Urge Questionnaire;32 CCQ;18 QSU14), we hypothesized that a strong general vaping craving factor would emerge. We examined factor loadings of the 42-candidate vaping craving items to: (1) determine whether a general craving factor would emerge, and, if so, (2) select the strongest loading items for inclusion in a final 10-item assessment of vaping craving. The PFA was conducted using PROC FACTOR in SAS version 9.4.33 In Study 2, we used confirmatory factor analysis (CFA) to determine if the latent vaping craving construct would predict observed QVC ratings in a second sample of e-cigarette users. Fit indices, factor loadings, and reliability of the items were evaluated. The CFA was conducted using Robust Maximum Likelihood estimation in Mplus version 8.34 Pearson correlations were used to establish convergent and discriminant validity using the reduced item set. Relationships between QVC ratings and variables predicted to be associated with vaping craving were examined, including quantity and frequency of vaping, time since last vaped, e-cigarette dependence (PS-ECDI), confidence in ability to quit vaping, and negative mood. In order to evaluate discriminant validity, we examined associations between QVC ratings and quantity and frequency of tobacco cigarette use, time since last smoked, tobacco and nicotine dependence (PS-CDI and NATS, respectively), and confidence in ability to quit smoking tobacco cigarettes. Tobacco cigarette measures were expected to be more weakly related to QVC ratings than measures specific to e-cigarettes. In these analyses, we removed items specific to craving from e-cigarette, tobacco cigarette, and nicotine dependence measures (PS-ECDI, PS-CDI, NATS) to eliminate overlap in item content and to assess whether the QVC was related to dependence measures without trait-level craving items included. QVC data were treated as continuous in all analyses. Correlations between the QVC and tobacco cigarette measures (both with the craving items and without) appear in Table 3. Missing data for both studies were present only on tobacco cigarette measures for those who indicated they did not smoke cigarettes. These participants were dropped from tobacco-specific correlation analyses. Table 3. Correlations Between the Questionnaire of Vaping Craving (QVC) and E-Cigarette, Mood, and Tobacco Cigarette Measures Variable, N = 224 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. QVC — 2. No. days vaped in past 30 .19* — 3. Times vaped per day .12 .40*** — 4. Cartridges / mL e-liquid vaped per day .31*** .33*** .42*** — 5. Nicotine in e-liquid (mg/mL) .05 .14† .05 .07 — 6. Time since last vaped −.27*** −.47*** −.21* −.22** .09 — 7. Confidence in quitting vaping −.45*** −.29*** −.32*** −.37*** −.04 .23** — 8. E-cigarette dependence (no craving) .47*** .38*** .53*** .47*** .11 −.26*** −.54*** — 9. E-cigarette dependence .51*** .41*** .52*** .47*** .11 −.29*** −.57*** .98*** — 10. Negative mood .33*** .54 −.05 −.05 .10 −.04 −.12 .28*** −.04 — 11. Positive mood .01 −.12 −.13 −.03 −.05 .03 .12 −.02 .29*** −.08 Variable, N = 195 1. 12. 13. 14. 15. 16. 17. 18. 19. 12. No. days smoked in past 30 −.11 — 13. Cigarettes smoked per day .04 .36*** — 14. Time since last smoked .00 −.55*** −.20** — 15. Confidence in quitting smoking −.09 −.29*** −.13 .27** — 16. Tobacco dependence (no craving) .27** .45*** .57*** −.41*** −.37*** — 17. Tobacco dependence .27** .46*** .56*** −.42*** −.40*** .99*** — 18. Nicotine dependence (no craving) .19** .48*** .46*** −.40*** −.44*** .70*** .72*** — 19. Nicotine dependence .22* .48*** .46*** −.40*** −.47*** .71*** .74*** .99*** — Variable, N = 224 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. QVC — 2. No. days vaped in past 30 .19* — 3. Times vaped per day .12 .40*** — 4. Cartridges / mL e-liquid vaped per day .31*** .33*** .42*** — 5. Nicotine in e-liquid (mg/mL) .05 .14† .05 .07 — 6. Time since last vaped −.27*** −.47*** −.21* −.22** .09 — 7. Confidence in quitting vaping −.45*** −.29*** −.32*** −.37*** −.04 .23** — 8. E-cigarette dependence (no craving) .47*** .38*** .53*** .47*** .11 −.26*** −.54*** — 9. E-cigarette dependence .51*** .41*** .52*** .47*** .11 −.29*** −.57*** .98*** — 10. Negative mood .33*** .54 −.05 −.05 .10 −.04 −.12 .28*** −.04 — 11. Positive mood .01 −.12 −.13 −.03 −.05 .03 .12 −.02 .29*** −.08 Variable, N = 195 1. 12. 13. 14. 15. 16. 17. 18. 19. 12. No. days smoked in past 30 −.11 — 13. Cigarettes smoked per day .04 .36*** — 14. Time since last smoked .00 −.55*** −.20** — 15. Confidence in quitting smoking −.09 −.29*** −.13 .27** — 16. Tobacco dependence (no craving) .27** .45*** .57*** −.41*** −.37*** — 17. Tobacco dependence .27** .46*** .56*** −.42*** −.40*** .99*** — 18. Nicotine dependence (no craving) .19** .48*** .46*** −.40*** −.44*** .70*** .72*** — 19. Nicotine dependence .22* .48*** .46*** −.40*** −.47*** .71*** .74*** .99*** — Table displays Pearson correlations between the Questionnaire of Vaping Craving (QVC) and e-cigarette (variable 1–10) and tobacco cigarette measures (variable 12–19) from Study 2. E-cigarette, tobacco cigarette, and nicotine dependence measures show correlations with items specific to craving removed from these measures (no craving) and with craving items included. †p < .05, *p ≤ .01, **p ≤ .001, ***p ≤ .0001. View Large Table 3. Correlations Between the Questionnaire of Vaping Craving (QVC) and E-Cigarette, Mood, and Tobacco Cigarette Measures Variable, N = 224 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. QVC — 2. No. days vaped in past 30 .19* — 3. Times vaped per day .12 .40*** — 4. Cartridges / mL e-liquid vaped per day .31*** .33*** .42*** — 5. Nicotine in e-liquid (mg/mL) .05 .14† .05 .07 — 6. Time since last vaped −.27*** −.47*** −.21* −.22** .09 — 7. Confidence in quitting vaping −.45*** −.29*** −.32*** −.37*** −.04 .23** — 8. E-cigarette dependence (no craving) .47*** .38*** .53*** .47*** .11 −.26*** −.54*** — 9. E-cigarette dependence .51*** .41*** .52*** .47*** .11 −.29*** −.57*** .98*** — 10. Negative mood .33*** .54 −.05 −.05 .10 −.04 −.12 .28*** −.04 — 11. Positive mood .01 −.12 −.13 −.03 −.05 .03 .12 −.02 .29*** −.08 Variable, N = 195 1. 12. 13. 14. 15. 16. 17. 18. 19. 12. No. days smoked in past 30 −.11 — 13. Cigarettes smoked per day .04 .36*** — 14. Time since last smoked .00 −.55*** −.20** — 15. Confidence in quitting smoking −.09 −.29*** −.13 .27** — 16. Tobacco dependence (no craving) .27** .45*** .57*** −.41*** −.37*** — 17. Tobacco dependence .27** .46*** .56*** −.42*** −.40*** .99*** — 18. Nicotine dependence (no craving) .19** .48*** .46*** −.40*** −.44*** .70*** .72*** — 19. Nicotine dependence .22* .48*** .46*** −.40*** −.47*** .71*** .74*** .99*** — Variable, N = 224 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. QVC — 2. No. days vaped in past 30 .19* — 3. Times vaped per day .12 .40*** — 4. Cartridges / mL e-liquid vaped per day .31*** .33*** .42*** — 5. Nicotine in e-liquid (mg/mL) .05 .14† .05 .07 — 6. Time since last vaped −.27*** −.47*** −.21* −.22** .09 — 7. Confidence in quitting vaping −.45*** −.29*** −.32*** −.37*** −.04 .23** — 8. E-cigarette dependence (no craving) .47*** .38*** .53*** .47*** .11 −.26*** −.54*** — 9. E-cigarette dependence .51*** .41*** .52*** .47*** .11 −.29*** −.57*** .98*** — 10. Negative mood .33*** .54 −.05 −.05 .10 −.04 −.12 .28*** −.04 — 11. Positive mood .01 −.12 −.13 −.03 −.05 .03 .12 −.02 .29*** −.08 Variable, N = 195 1. 12. 13. 14. 15. 16. 17. 18. 19. 12. No. days smoked in past 30 −.11 — 13. Cigarettes smoked per day .04 .36*** — 14. Time since last smoked .00 −.55*** −.20** — 15. Confidence in quitting smoking −.09 −.29*** −.13 .27** — 16. Tobacco dependence (no craving) .27** .45*** .57*** −.41*** −.37*** — 17. Tobacco dependence .27** .46*** .56*** −.42*** −.40*** .99*** — 18. Nicotine dependence (no craving) .19** .48*** .46*** −.40*** −.44*** .70*** .72*** — 19. Nicotine dependence .22* .48*** .46*** −.40*** −.47*** .71*** .74*** .99*** — Table displays Pearson correlations between the Questionnaire of Vaping Craving (QVC) and e-cigarette (variable 1–10) and tobacco cigarette measures (variable 12–19) from Study 2. E-cigarette, tobacco cigarette, and nicotine dependence measures show correlations with items specific to craving removed from these measures (no craving) and with craving items included. †p < .05, *p ≤ .01, **p ≤ .001, ***p ≤ .0001. View Large Results Study 1 The first factor accounted for 77.4% of the common factor variance. The eigenvalues for the first three factors were 21.40, 3.26 (10.2% of variance), and 1.11 (3.5%). The 10 strongest loading items on the first factor (range = .815–.867) were included in the QVC. Table 2 lists the 10 strongest loading items on the first factor. The content of these items focused on desire (6 items) and intent (2 items) to vape, as well as anticipation of positive outcomes related to e-cigarette use (2 items). Internal consistency for the 10 items was excellent, α = .96. Table 2. Questionnaire of Vaping Craving (QVC) Items and Content, Meansa and Standard Deviations, and Factor Loadings Factor Loadingsb Item Content Area Study 2 M (SD) Study 1 (PFA) Study 2 (CFA) I have a strong desire for an e-cigarette right now. Desire 3.88 (1.96) .827 .953 I have an urge for an e-cigarette. Desire 3.96 (1.88) .832 .907 All I want right now is an e-cigarette. Desire 3.53 (1.91) .830 .898 I am missing vaping right now. Desire 3.79 (1.90) .843 .889 I am craving an e-cigarette right now. Desire 3.83 (1.84) .815 .888 I need to vape now. Desire 3.53 (1.94) .854 .881 I am going to vape as soon as possible. Intention 4.11 (1.84) .867 .869 I will vape as soon as I get the chance. Intention 4.18 (1.82) .817 .840 Nothing would be better than vaping right now. Positive outcome 3.46 (1.86) .841 .836 Vaping would make me happier now. Positive outcome 4.44 (1.75) .832 .774 QVC Average Score 3.86 (1.67) Factor Loadingsb Item Content Area Study 2 M (SD) Study 1 (PFA) Study 2 (CFA) I have a strong desire for an e-cigarette right now. Desire 3.88 (1.96) .827 .953 I have an urge for an e-cigarette. Desire 3.96 (1.88) .832 .907 All I want right now is an e-cigarette. Desire 3.53 (1.91) .830 .898 I am missing vaping right now. Desire 3.79 (1.90) .843 .889 I am craving an e-cigarette right now. Desire 3.83 (1.84) .815 .888 I need to vape now. Desire 3.53 (1.94) .854 .881 I am going to vape as soon as possible. Intention 4.11 (1.84) .867 .869 I will vape as soon as I get the chance. Intention 4.18 (1.82) .817 .840 Nothing would be better than vaping right now. Positive outcome 3.46 (1.86) .841 .836 Vaping would make me happier now. Positive outcome 4.44 (1.75) .832 .774 QVC Average Score 3.86 (1.67) M = mean; SD = standard deviation. aItems were rated on a 7-point scale (1 = strongly disagree, 7 = strongly agree). bFactor loadings were obtained using principal factor analysis (PFA) in Study 1 (N = 209) and confirmatory factor analysis (CFA) in Study 2 (N = 224). View Large Table 2. Questionnaire of Vaping Craving (QVC) Items and Content, Meansa and Standard Deviations, and Factor Loadings Factor Loadingsb Item Content Area Study 2 M (SD) Study 1 (PFA) Study 2 (CFA) I have a strong desire for an e-cigarette right now. Desire 3.88 (1.96) .827 .953 I have an urge for an e-cigarette. Desire 3.96 (1.88) .832 .907 All I want right now is an e-cigarette. Desire 3.53 (1.91) .830 .898 I am missing vaping right now. Desire 3.79 (1.90) .843 .889 I am craving an e-cigarette right now. Desire 3.83 (1.84) .815 .888 I need to vape now. Desire 3.53 (1.94) .854 .881 I am going to vape as soon as possible. Intention 4.11 (1.84) .867 .869 I will vape as soon as I get the chance. Intention 4.18 (1.82) .817 .840 Nothing would be better than vaping right now. Positive outcome 3.46 (1.86) .841 .836 Vaping would make me happier now. Positive outcome 4.44 (1.75) .832 .774 QVC Average Score 3.86 (1.67) Factor Loadingsb Item Content Area Study 2 M (SD) Study 1 (PFA) Study 2 (CFA) I have a strong desire for an e-cigarette right now. Desire 3.88 (1.96) .827 .953 I have an urge for an e-cigarette. Desire 3.96 (1.88) .832 .907 All I want right now is an e-cigarette. Desire 3.53 (1.91) .830 .898 I am missing vaping right now. Desire 3.79 (1.90) .843 .889 I am craving an e-cigarette right now. Desire 3.83 (1.84) .815 .888 I need to vape now. Desire 3.53 (1.94) .854 .881 I am going to vape as soon as possible. Intention 4.11 (1.84) .867 .869 I will vape as soon as I get the chance. Intention 4.18 (1.82) .817 .840 Nothing would be better than vaping right now. Positive outcome 3.46 (1.86) .841 .836 Vaping would make me happier now. Positive outcome 4.44 (1.75) .832 .774 QVC Average Score 3.86 (1.67) M = mean; SD = standard deviation. aItems were rated on a 7-point scale (1 = strongly disagree, 7 = strongly agree). bFactor loadings were obtained using principal factor analysis (PFA) in Study 1 (N = 209) and confirmatory factor analysis (CFA) in Study 2 (N = 224). View Large Study 2 Estimation of the Robust Maximum Likelihood model chi-square indicated inadequate fit, χ2 (35, N = 224) = 162.50, p < .0001, CFI = .924, SRMR = .031, RMSEA = .128. Considering the poor fit of the initial model, modification indices were examined to determine whether freeing error covariances (ie, letting the error terms correlate with each other) would have led to a significant increment in fit. Modification indices suggested freeing the covariances for three pairs of items: “I need to vape now” and “Nothing would be better than vaping right now,” “I am going to vape as soon as possible” and “I will vape as soon as I get the chance,” and “I have an urge for an e-cigarette,” and “I am craving an e-cigarette right now,” would significantly improve model fit, χ2s ≥ 12.84, ps < .05. Examination of these items indicated similar language that may have resulted in larger error covariances. These covariances were freed to improve model fit. Fit indices for the final CFA model indicated good fit35 for the one-factor solution, χ2 (32, N = 224) = 66.41, p = .0003, CFI = .980, SRMR = .021, RMSEA = .06. All 10 items had strong factor loadings35 (.774–.953; Table 2) and were significantly predicted by the latent vaping craving construct, ts ≥ 24.63, ps < .001. QVC ratings were significantly correlated with several e-cigarette measures (Table 3; N = 224). Higher vaping craving was associated with vaping more cartridges or mL of e-liquid per day (p < .0001), vaping more days in the past 30 (p < .01), less time since last vaped (p < .0001), lower confidence in one’s ability to quit vaping (p < .0001), and greater negative mood (p < .0001). Vaping craving was associated with tobacco dependence (PS-CDI, N = 195, adjusted R2 = .07, p = .0001) and nicotine dependence (NATS, N = 195, adjusted R2 = .03, p = .007), though weaker relationships were found compared to that with e-cigarette dependence. When controlling for tobacco dependence and nicotine dependence in separate regression models, e-cigarette dependence (PS-ECDI) was more strongly related to vaping craving, ∆R2 = .18 and .21, respectively, ps < .0001 (see Supplemental Materials for regression tables). Vaping craving was not significantly associated with times vaped per day, the amount of nicotine in one’s e-liquid, or any other tobacco cigarette measures. These analyses were run in SAS version 9.4.33 Discussion This research was explicitly designed to develop a brief, practical vaping craving questionnaire. As predicted, analyses of a large, diverse item set representing a variety of craving related concepts revealed a strong, general craving factor that accounted for approximately 77% of the common factor variance. This supports previous research demonstrating that, though craving can have multidimensional features, a general craving factor nearly always emerges.14,17,18 The QVC also demonstrated excellent internal consistency, α = .96. This is comparable to the reliabilities reported in the original publications of the QSU-Brief, α = .97 and the CCQ, α = .93. The ten items comprising the QVC were the items with the strongest loadings on the general craving factor. Five of these items were derived from the QSU-Brief and clearly capture the desire aspect of craving (“I have a strong desire for an e-cigarette right now,” “I have an urge for an e-cigarette,” “All I want right now is an e-cigarette,” “I am going to vape as soon as possible,” and “Nothing would be better than vaping right now”). Though all 10 QSU-Brief items were translated for use with e-cigarettes and included in the original 42-item pool, not all were retained for the final QVC. This suggests that vaping craving may be distinct from tobacco cigarette craving and should be assessed as such. The inclusion of desire is consistent with the definition of craving typically adopted by the field.36,37 Structural analyses of craving questionnaires generally show that the primary or first principal factor that emerges in these analyses is often dominated by statements of desire and intention to use,38 a pattern that similarly emerged in the QVC analyses. The items capturing desire included statements of both “craving” and “urge,” and the most strongly loading of all items in the confirmatory analysis of Study 2 was, “I have a strong desire for an e-cigarette right now.” Interestingly, the semantic content of these items conforms to the description used in the DSM-510 for the craving criterion in the diagnosis of substance use disorders, viz. “Craving, or a strong desire or urge to use a substance.” Notably, some multi-item craving questionnaires do not explicitly include desire items (eg, Tobacco Craving Questionnaire;39 Marijuana Craving Questionnaire40), which brings into question their content validity. The pattern of correlations between the QVC and a variety of measures related to tobacco and e-cigarette use provided support for the convergent and discriminant validity of the QVC. Participants with higher vaping craving tended to be heavier e-cigarettes users (ie, these participants tended to vape more e-liquid per day, vaped more days in the past 30, vaped more recently, had lower confidence in their ability quit vaping, and were higher on e-cigarette dependence). Additionally, among duals users of tobacco and e-cigarettes, vaping craving was more strongly associated with e-cigarette dependence than with tobacco or nicotine dependence. This further supports that vaping craving may be distinct from tobacco and nicotine dependence. Strengths The QVC pioneers the effort to create psychometrically sound measures to assess motivational aspects supporting e-cigarette use (specifically, vaping craving). Moreover, the questionnaire offers a practical, multi-item measure to assess vaping craving, which is notably absent from e-cigarette research. Further, the QVC may improve the understanding of vaping craving and advance current tobacco cessation strategies. Its use may help to develop strategies to increase users’ ability to cope with both tobacco and e-cigarette craving, and identify smokers who are more likely to relapse when using e-cigarettes as a smoking cessation aid, thus allowing for appropriate adjustments to their treatment planning. An additional strength of this study is that, unlike some previous questionnaire research, the standard battery of questionnaires containing the QVC was administered electronically. This allowed identification and exclusion of poor data (eg, excluding those who completed the questionnaires in an unreasonably short amount of time). Finally, the brevity of the QVC allows it to be easily used in both research and clinical settings. Of note, this questionnaire was developed from the onset as a short form, and the questionnaire was directly tested in that format in Study 2. Limitations The current research used Amazon MTurk workers and, though they have been shown to generate reliable data for a variety of research questions,25,26 we did not have face-to-face contact with the participants and could not confirm their use of either tobacco or e-cigarettes. This issue, of course, applies to nearly any online or anonymous survey-based research on drug users. Our assertions about the psychometric properties of the QVC are restricted to samples most similar to those recruited for this research and may not generalize to other populations of interest (eg, e-cigarette-only users, adolescents, treatment-seeking individuals). For instance, though the gustatory and olfactory items in the original 42-item did not load strongly onto the first general craving factor, this could have been a function of the sample. It is possible that these types of items would be more salient to e-cigarette-only or novice users. These studies were not powered to detect aspects of vaping craving that may differ between e-cigarette-only users and dual-users; future work should explore this issue. Additionally, the type (ie, generation) of e-cigarettes used by participants was not assessed. Nicotine administration levels vary considerably across devices,15 and, therefore, the type of e-cigarettes participants used may have affected their vaping craving. Finally, this questionnaire only assessed a general vaping craving factor. There may be more nuanced facets of craving that can only be evaluated with a larger number of items of more diverse content. Conclusions Overall, the QVC demonstrated high reliability and clear convergent and discriminant validity. The QVC offers a psychometrically sound measurement of vaping craving that can be used in laboratory and clinical settings. Supplementary Material Supplementary data are available at Nicotine & Tobacco Research online. Funding None to report. 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Nicotine and Tobacco ResearchOxford University Press

Published: Jan 1, 2019

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