Psychometric properties of the Malay translated eight-item electronic cigarette dependence scale (EDS-8) among electronic cigarette users in Malaysia.

Background: Electronic cigarettes (e-cigarettes) have become increasingly popular in recent years. Existing evidence indicates e-cigarettes used in isolation are less harmful than combustible cigarettes, yet emerging work has demonstrated that adults use e-cigarettes largely in combination with combustible cigarettes (i.e. dual use). Despite this data, little is understood about how exclusive and dual e-cigarette users may differ across behavioral outcomes, such as substance use dependence and behaviors among adults. Objectives: Thus, the current project examined differences in e-cigarette dependence, problematic alcohol use, cannabis use, and nonmedical prescription opioid use (e.g. methadone and oxycodone) across both exclusive and dual e-cigarette adult users. Results: Participants included 531 (53.6% female; Mage = 35.29 years, SD = 10.44) adults with past-month e-cigarette use. Dual users reported greater e-cigarette dependence, alcohol use, current cannabis use, and endorsement of nonprescription opioid use. Conclusions/Importance: Importantly, this work suggests that adults who use both combustible and e-cigarettes may constitute a group more vulnerable to experiencing problematic substance use and more severe e-cigarette dependence than exclusive e-cigarette users.

Psychometrically sound measures of e-cigarette dependence are lacking. We modified the PROMIS Item Bank v1.0-Smoking: Nicotine Dependence for All Smokers for use with e-cigarettes and evaluated the psychometrics of the 22-, 8-, and 4-item adapted versions, referred to as The E-cigarette dependence scale (EDS). Adults (1009) who reported using e-cigarettes at least weekly completed an anonymous survey in summer 2016 (50.2% male, 77.1% White, mean age 35.81 [10.71], 66.4% daily e-cigarette users, 72.6% current cigarette smokers). Psychometric analyses included confirmatory factor analysis, internal consistency, measurement invariance, examination of mean-level differences, convergent validity, and test-criterion relationships with e-cigarette use outcomes. All EDS versions had confirmable, internally consistent latent structures that were scalar invariant by sex, race, e-cigarette use (nondaily/daily), e-liquid nicotine content (no/yes), and current cigarette smoking status (no/yes). Daily e-cigarette users, nicotine e-liquid users, and cigarette smokers reported being more dependent on e-cigarettes than their counterparts. All EDS versions correlated strongly with one another, evidenced convergent validity with the Penn State E-cigarette Dependence Index and time to first e-cigarette use in the morning, and evidenced test-criterion relationships with vaping frequency, e-liquid nicotine concentration, and e-cigarette quit attempts. Similar results were observed when analyses were conducted within subsamples of exclusive e-cigarette users and duals-users of cigarettes and e-cigarettes. Each EDS version evidenced strong psychometric properties for assessing e-cigarette dependence in adults who either use e-cigarette exclusively or who are dual-users of cigarettes and e-cigarettes. However, results indicated little benefit of the longer versions over the 4-item EDS, which provides an efficient assessment of e-cigarette dependence. The availability of the novel, psychometrically sound EDS can further research on a wide range of questions related to e-cigarette use and dependence. In addition, the overlap between the EDS and the original PROMIS that was developed for assessing nicotine dependence to cigarettes provides consistency within the field.

Objective: Tobacco use is elevated among individuals with eating disorders (EDs). Yet, further research is needed to understand associations between cigarette and e-cigarette use patterns and ED symptomatology. To gain a more comprehensive understanding of tobacco use and EDs, this study characterized ED symptomatology and tobacco use patterns, including exclusive cigarette use, e-cigarette use, dual use, and nonuse. Method: Young adults aged 18-24 years who self-reported exclusive cigarette, e-cigarette, dual, or nonuse (N = 2500) were recruited via Lucid, an online survey management company. Participants completed questionnaires assessing body dissatisfaction, global ED psychopathology, binge eating and self-induced vomiting frequency, and demographics. ED diagnostic groups included: anorexia nervosa (AN), bulimia spectrum eating disorders (BSED), atypical AN, and night eating syndrome (NES). Results: Multinomial logistic models revealed those with AN were more likely to be dual users, those with atypical AN were more likely to be exclusive e-cigarette users, and participants with a BSED or NES were more likely to be exclusive e-cigarette or dual users, compared to those without an ED. General linear models suggested body dissatisfaction and global ED psychopathology were higher among exclusive e-cigarette and dual users, while binge eating and self-induced vomiting frequencies were greater among all tobacco use groups compared to nonusers. Discussion: Our findings suggest young adults with ED symptomatology were more likely to be users of e-cigarettes exclusively or dual users. It will be necessary to examine how these associations manifest using longitudinal and clinical populations in future research.

Changes in E-Cigarette Use Behaviors and Dependence in Long-term E-Cigarette Users

IntroductionExclusive e-cigarette use has been shown to be associated with reduced levels of respiratory symptoms relative to smoking combustible cigarettes; this association has been less frequently studied in smokers using advanced-generation e-cigarette devices. Advanced-generation devices generate denser vapor than either early generation or pod-style devices, and engender longer inhalations; these vaping topography patterns may contribute to respiratory symptoms.MethodsIn a single-session, cross-sectional study of exclusive e-cigarette users (N = 59) and dual users of e-cigarettes and cigarettes (N = 54), participants completed questionnaires, including the American Thoracic Society Questionnaire (ATSQ) and were videotaped vaping their own device in the lab for 1 hour. Using a hierarchical regression method, we examined whether topography variables, level of nicotine concentration used in their e-cigarette device in the past month, e-cigarette dependence, amount of e-cigarette use in the past month, and smoking status (any smoking in the last month vs. none) predicted ATSQ score severity.ResultsThere was a significant mean difference in ATSQ score across smoking status, with greater ATSQ scores for vapers who also smoked cigarettes (19.0, SD = 6.7) than for exclusive vapers (13.4, SD = 5.3). In the final model, of the predictors of interest, only cigarette smoking status predicted significantly greater ATSQ scores (overall F = 2.51, p = .006; R2 = .26; smoking status β = 0.39, p < .0001).ConclusionsFindings suggest that differences in respiratory symptoms between dual and exclusive e-cigarette users appear to be attributable to combustible cigarette smoking, rather than more intense or frequent e-cigarette use across groups.ImplicationsIn this comparison of exclusive advanced-generation vape device users (N = 59) versus dual users of these devices and combustible cigarettes (N = 54), we set out to determine the extent to which smoking status and e-cigarette use variables predicted self-reported respiratory symptom severity. We found that dual users showed greater respiratory symptom severity (ATSQ scores) than exclusive vapers. Despite examining vaping topography and other variables, smoking status and race were the only significant predictor of respiratory symptoms. We conclude that combustible cigarette use, not individual vaping topography, likely accounts for differences in respiratory symptoms between dual users and exclusive vapers.

BackgroundPopulation models have been developed to evaluate the impact of new tobacco products on the overall population. Reliable input parameters such as longitudinal tobacco use transitions are needed to quantify the net population health impact including the number of premature deaths prevented, additional life years, and changes in cigarette smoking prevalence.MethodsThis secondary analysis assessed transition patterns from PATH wave 1 (2013–14) to wave 2 (2014–15) among adult exclusive cigarette smokers, exclusive e-cigarette users, and dual users. Transition probabilities were calculated by taking into account factors including cigarette smoking and e-cigarette use histories and experimental or established use behaviors. Multinomial logistic regression models were constructed to further evaluate factors associated with transition patterns.ResultsDifferential transition probabilities emerged among study subgroups when taking into account cigarette smoking and e-cigarette use histories and experimental or established use behaviors. For example, overall 45% of exclusive e-cigarette users in wave 1 continued using e-cigarettes exclusively in wave 2. However, we observed approximately 11 to 14% of wave 1 exclusive experimental e-cigarette users continued to use e-cigarette exclusively in wave 2, compared to about 62% of exclusive established e-cigarette users. The history of cigarette smoking and e-cigarette use is another important factor associated with transition patterns. Among experimental e-cigarette users, 7.5% of individuals without a history of cigarette smoking transitioned to exclusive cigarette smoking, compared to 30% of individuals with a history of cigarette smoking. Additionally, 1.3% of exclusive cigarette smokers in wave 1 transitioned to exclusive e-cigarette use, with the highest transition probability (3.7%) observed in the established cigarette smoker with a history of e-cigarette use subgroup.ConclusionsProduct use histories and current use behaviors are important factors influencing transitions between product use states. Given that experimental users’ transition behaviors may be more variable and more influenced by tobacco use history, long-term predictions made by population models could be improved by the use of transition probabilities from established users. As transition patterns might be changing over time, long-term transition patterns can be examined through analysis of future waves of PATH data.

For electronic cigarettes (e-cigarettes) to be a viable substitute for combustible cigarettes, it is likely that they must be rewarding enough for regular use, indicated by factors such as craving and dependence, important aspects of reinforcement. This study aimed to understand short-term changes in measures of nicotine dependence between groups differing by use trajectory in a switching trial, and within group changes of these measures. Secondary data analysis of one arm of an e-cigarette randomized clinical trial. San Diego, California and Kansas City, Missouri, United States. 114 African American (n=60) and Latinx (n=54) smokers (58.8% male) attempting to switch to nicotine salt pod system (NSPS) e-cigarettes in a 6-week trial. At week 6, participants were classified by use trajectory: exclusive smokers (n=16), exclusive e-cigarette (n=32), or dual users (n=66). E-cigarette, cigarette, and total nicotine dependence (cigarette + e-cigarette), use patterns, cigarette craving and nicotine withdrawal, and cotinine were assessed at baseline and week 6 using standard measures. In between group comparisons, exclusive e-cigarette and dual users showed greater reductions in cigarette dependence (e-cigarette: -32.38, 95% CI=-37.7,-27.1; dual: -18.48, 95% CI=-22.2,-14.7), withdrawal (e-cigarette: -6.25, 95% CI=-8.52,-3.98; dual: -3.18, 95% CI=-5.02,-1.34), craving (e-cigarette: -11.44, 95% CI=-14.2,8.7; dual: -9.59, 95% CI=-11.6,-7.59), and cigarettes per day (CPD; e-cigarette: -11.19, 95% CI=-13.1,-9.27; dual: -9.39, 95% CI=-11.3, -7.52) compared with exclusive smokers. In within group analyses, e-cigarette and dual users showed reductions in craving and withdrawal from baseline to week 6. Exclusive e-cigarette and dual users, maintained cotinine levels (all Ps > 0.05) and showed reductions in CPD and cigarette dependence (all Ps < 0.01). Findings were inconclusive regarding changes in total nicotine dependence from baseline to week 6 among exclusive e-cigarette users (P=0.123). Dual users showed increased total nicotine dependence (P<0.001) and smokers showed decreased total dependence (P=0.004). Smokers who switch to nicotine salt pod system e-cigarettes maintain their nicotine levels and transfer their dependence, suggesting that nicotine salt pod system e-cigarettes have a similar reinforcement potential to cigarettes and facilitate switching.

Background: E-cigarette use (vaping) is an emerging public health problem. Depression has been found to be associated with e-cigarette use, and vaping and depression are each associated with elevated systemic inflammation. To date, the role of inflammation in the relationship between vaping and depression has not been explored. Objective: To assess the independent associations between e-cigarette use, depression, and inflammation, and to investigate whether the likelihood of depression among current e-cigarette users is associated with systemic inflammation. Methods: Nationally representative NHANES data from 2015–2018 were used (n = 4961). Systemic inflammation was defined as serum C-reactive protein (CRP) ≥ 8.0 mg/L. Depressed individuals were characterized by a score ≥ 10 on the Patient Health Questionnaire-9 (PHQ-9). Current e-cigarette users were defined as individuals who vaped at least once in the past 30 days and these individuals were stratified by use: exclusive users (reported smoking less than 100 combustible cigarettes in their lifetime), dual users (reported current use of electronic and combustible cigarettes), and e-cigarette users who were previous smokers. Bivariate analyses were used to assess independent associations between vaping, depression, and inflammation; and weighted logistic regression analyses adjusting for BMI, sex, and economic status were used to determine the odds ratios (ORs) for depression by e-cigarette category stratified by differential CRP levels. Results: Depression occurred in 16.7% of all e-cigarette users vs. 5.0% of those who never used e-cigarettes (p < 0.001). In adjusted analyses, the following elevated ORs were found: all current e-cigarette users with CRP <8 = 3.37 (95% CI: 2.06, 5.51) vs. CRP ≥8 = 6.70 (2.48, 18.11); exclusive e-cigarette users with CRP <8 = 1.91 (0.78, 4.69) vs. those with CRP ≥8 = 5.09 (1.44, 18.02); and dual users with CRP <8 = 4.31 (2.35, 7.89) vs. those with CRP ≥8 = 7.37 (1.85, 29.41). These ORs indicate that depression is associated with each category of e-cigarette use; however, we found this association did not vary by systemic inflammation level (interaction p-values > 0.05). Conclusion: While a pattern of greater ORs for depression among e-cigarette users with elevated CRP provides provocative findings that might suggest a potential role of inflammation in the association between vaping and depression, we failed to find evidence that inflammation clearly moderates this association. While it is possible that depression among e-cigarette users may be influenced by systemic inflammation, a reproduction of the current study is necessary among a larger cohort to elucidate the effect of inflammation on depression among e-cigarette users.

Prior research suggests that the e-Cigarette Wisconsin Inventory of Smoking Dependence Motives (e-WISDM) distinguishes primary (e-PDM) and secondary dependence (e-SDM); however, there is little research on these e-WISDM dimensions and prior research comprised dual users (using cigarettes and e-cigarettes) and those using older generations of e-cigarettes. Exclusive users of contemporary e-cigarettes (N = 164) completed the e-WISDM and a laboratory self-administration session and rated pre-use expectancies and post-use experiences. Only a 1-factor model limited to the primary scales (Automaticity, Tolerance, Craving, Loss of Control) achieved a good model fit. The e-PDM was correlated with the Penn State Electronic Cigarette Dependence Index (PS-ECDI), r = .79, p < .001. The e-PDM and PS-ECDI were similarly correlated with the use topography and self-reported measures. Analyses of motive profiles identified Taste, Tolerance, and Automaticity as the most strongly endorsed motives in the full sample. Subgroup analyses indicated primary motives were more elevated in daily versus non-daily e-cigarette users and participants with versus without a history of smoking cigarettes. Taste motives were stronger in users of third versus fourth-generation e-cigarettes. These findings suggest that the four e-PDM subscales are a concise, reliable, and valid measure of core e-cigarette dependence motives that are related to meaningful dependence attributes. Electronic cigarettes (e-cigarettes) are dependence-producing. Instruments that measure e-cigarette dependence are necessary to identify users who may have difficulty quitting e-cigarettes and who are at risk for use-related harms. The four subscales of the e-WISDM PDM index self-reported heavy e-cigarette use, craving, automatic or mindless use, and perceived loss of control over use. The current research supports the validity of the e-WISDM PDM as a measure of core e-cigarette dependence in users of today's e-cigarette devices.

Concurrent use of e-cigarettes and cannabis and associated COVID-19 symptoms, testing, and diagnosis among student e-cigarette users at four U.S. Universities

E-cigarette use reasons and associated e-cigarette use dependence among college students: A longitudinal examination

Behavioral economic purchase tasks are used to estimate the reinforcing value of drugs by asking participants how much they would purchase across a range of increasing prices. We sought to validate such a task for e-cigarettes in experienced users of advanced generation, tank-style devices. Dual users of cigarettes and e-cigarettes (N = 54) and exclusive e-cigarette users (N = 59) attended one session during which they completed assessments including two versions of the E-cigarette Purchase Task: one that asked how many puffs of their e-cigarette they would purchase in 24 hours at varying prices and one that asked how many mLs of e-liquid they would purchase. We correlated purchase task outcomes with other measures of e-cigarette use. We also compared the tasks across dual and exclusive users. Indices derived from the mLs-based task were more likely to be correlated with self-reported use rates, e-cigarette dependence, and cotinine levels than the puffs-based task. Exclusive users showed greater demand on than dual users only on the mLs version when using an F-test comparison method, while multivariate analysis of variance (MANOVA) results showed that dual users showed greater demand only on the puffs task. Results indicate that the mLs version had greater validity than the puffs version in terms of clinical indices. Dual users may still be on a trajectory to fully switching to e-cigarettes; thus, puffs as a measure may be more intuitive, as this measure is shared by cigarettes and e-cigarettes. For exclusive users, the unit they purchase their e-liquid in may be the most relevant unit and better capture their demand for that product. Behavioral economic purchase tasks have been widely used to understand nicotine use. We have developed two versions of a purchase task for e-cigarette use and compared the two versions in users of advanced generation e-cigarette devices. We found that the mLs version of the task better-reflected use patterns relative to a puffs version, which suggests that participants struggle to place monetary value on a unit of consumption (ie, puffs). Validated measures of e-cigarette reinforcement will be important as researchers and regulators determine which features of these products contribute to reinforcing efficacy.

Although e-cigarette use is on the rise, there is little understanding of cognitive-based individual difference factors that maintain maladaptive e-cigarette beliefs and dependence. The present investigation sought to test a theoretically-driven interactive model of e-cigarette health literacy and anxiety sensitivity (AS; fear of the consequences of anxiety) among 537 e-cigarette users (50.7% female, Mage = 35.2 years, SD = 10.1) in terms of perceived benefits and risks of e-cigarette use as well as dependence. Results indicated a significant interaction between e-cigarette health literacy and AS. The significant interaction effect for each dependent variable was evident over and above the main effects as well as the covariates of sex, income, education, and dual cigarette use (e-cigarette dependence was also controlled for the models of perceived benefits and risks). The form of this interaction indicated that greater e-cigarette health literacy was more strongly related to greater perceived benefits and risks of e-cigarette use as well as dependence among those with higher, relative to lower, AS. Overall, the current data suggest that individual differences in e-cigarette health literacy and AS may represent two important factors to consider in e-cigarette beliefs and dependence. This study provides the first empirical evidence of the potential role of two cognitive factors in relation to e-cigarette use beliefs and behavior. These data suggest future clinical research may benefit by understanding the potential therapeutic role of e-cigarette health literacy and AS for e-cigarette use behavior.

ObjectivesFrom early 2020, Malaysia had to implement nationwide lockdowns, quarantines, and other social distancing practices to contain the spread of COVID-19 virus, leading to symptoms of psychosocial burnout among the people. The aim of the present research is to develop and validate a Malay language version of the COVID-19 Burnout Scale (M-COVID-19-BS).MethodsThis three-phase study was conducted among Malaysian population. Phase 1 involved forward and backward translations of the Scale to Malay language by four professional bilingual translators. In Phase 2, the new M-COVID-19-BS instrument was piloted on 30 participants who suggested minor lexical modifications. Phase 3 consisted of online recruiting of Malaysian citizens to answer a composite questionnaire comprising the M-COVID-19-BS, Copenhagen Burnout Inventory (CBI), World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF), and Fear of COVID-19 Scale (FCV-19S). Data were statistically analyzed.ResultsThe composite four-part questionnaire in Malay was answered by N = 225 Malaysian citizens. The M-COVID-19-BS instrument demonstrated a good internal consistency (Cronbach’s alpha = 0.926) and had a unidimensional factor structure. M-COVID-19-BS scores positively correlated with the three CBI subscales, showing evidence of convergent validity. Negative correlation was reported between M-COVID-19-BS and WHOQOL-BREF, achieving discriminant validity. M-COVID-19-BS also exhibited moderate positive correlations with the FCV-19S, thus supporting its concurrent validity.ConclusionsResults demonstrate that M-COVID-19-BS is a valid and reliable instrument to assess burnout symptoms related to COVID-19 among Malay-speaking populations either collectively or as a self-care tool to detect burnout symptoms without needing to further burden the already overwhelmed Malaysian healthcare system.

BackgroundMajority of patients with chronic illnesses such as diabetes, receive care at primary care setting. Efforts have been made to restructure diabetes care in the Malaysian primary care setting in accordance with the Chronic Care Model (CCM). The Patient Assessment on Chronic Illness Care (PACIC) is a validated self-report tool to measure the extent to which patients with chronic illness receive care that aligns with the CCM. To date, no validated tool is available to evaluate healthcare delivery based on the CCM in the Malay language. Thus, the study aimed to translate the PACIC into the Malay language and validate the questionnaire among patients with diabetes in the Malaysian public primary care setting.MethodsThe English version of the PACIC questionnaire is a 20-item scale measuring five key components, which are patient activation, decision support, goal setting, problem solving and follow-up care. The PACIC underwent forward - backward translation and cross cultural adaptation process to produce the PACIC-Malay version (PACIC-M). Reliability was tested using internal consistencies and test-retest reliability analyses, while construct validity was tested using the exploratory factor analysis (EFA).ResultsThe content of PACIC-M and the original version were conceptually equivalent. Overall, the internal consistency by Cronbach’s α was .94 and the intra-class correlation coefficient was .93. One item was deleted (item 1) when the factor loading was < 0.4. The factor analyses using promax identified three components (‘Goal Setting/Tailoring and Problem solving/Contextual’, ‘follow-up/coordination’ and ‘patient activation and delivery system design/ decision support’); explaining 61.2% of the variation. The Kaiser-Meyer-Olkin (KMO) was 0.93 and Bartlett’s test of sphericity was p = .000. Therefore, the final version of the PACIC-M consisted of 19 items, framed within three components.ConclusionThe findings demonstrated that the PACIC-M measured different dimensions from the English version of PACIC. It is however; highly reliable and valid to be used in assessing three CCM model subscales. Further confirmatory factor analysis of PACIC-M should be conducted to confirm this new model.