Day-to-Day Variability in Self-Reported Cigarettes Per Day

Repetitive Transcranial Magnetic Stimulation for Tobacco Treatment in Cancer Patients: A Preliminary Report of a One-Week Treatment

Background

Smoking cessation represents a significant opportunity to improve cancer survival rates, reduces the risk of cancer treatment complications, and improves quality of life. However, about half of cancer patients who smoke continue to smoke despite the availability of several treatments. Previous studies demonstrate that repetitive transcranial magnetic stimulation (rTMS) over the left dorsolateral prefrontal cortex (DLPFC) decreases cue craving, reduces cigarette consumption, and increases the quit rate in tobacco use disorder. We investigated whether 5 sessions of rTMS can be safely and efficaciously used for smoking cessation in cancer patients.

Methods

We enrolled 11 treatment-seeking smokers with cancer (>5 cigarettes per day) in a randomized, double-blind, sham-controlled proof-of-concept study. Participants received 5 daily sessions of active 10 Hz rTMS of the left DLPFC (3000 pulses per session) or sham rTMS and were followed up for 1 month via phone assessments. Main outcomes included reductions in the number of smoked-cigarettes per day (primary) and craving (secondary). Adverse effects were reported daily by participants.

Results

Seven of 11 participants completed 5 sessions of rTMS over one week. Compared to sham treatment (n = 4), the active rTMS (n = 3) exhibited modest effects overtime on smoking (Cohen's f² effect size of 0.16) and large effects on cue craving (Cohen′s f² = 0.40). No serious side effects related to rTMS were reported in the treatment.

Conclusions

Five sessions of daily rTMS over the left DLPFC might benefit cancer patients who smoke cigarettes. However, further evidence is needed to determine with more certainty its therapeutic effect and adverse effects for cancer patients who smoke cigarettes.

Characterizing and Modeling Smoking Behavior Using Automatic Smoking Event Detection and Mobile Surveys in Naturalistic Environments: Observational Study

Background

There are 1.1 billion smokers worldwide, and each year, more than 8 million die prematurely because of cigarette smoking. More than half of current smokers make a serious quit every year. Nonetheless, 90% of unaided quitters relapse within the first 4 weeks of quitting due to the lack of limited access to cost-effective and efficient smoking cessation tools in their daily lives.

Objective

This study aims to enable quantified monitoring of ambulatory smoking behavior 24/7 in real life by using continuous and automatic measurement techniques and identifying and characterizing smoking patterns using longitudinal contextual signals. This work also intends to provide guidance and insights into the design and deployment of technology-enabled smoking cessation applications in naturalistic environments.

Methods

A 4-week observational study consisting of 46 smokers was conducted in both working and personal life environments. An electric lighter and a smartphone with an experimental app were used to track smoking events and acquire concurrent contextual signals. In addition, the app was used to prompt smoking-contingent ecological momentary assessment (EMA) surveys. The smoking rate was assessed based on the timestamps of smoking and linked statistically to demographics, time, and EMA surveys. A Poisson mixed-effects model to predict smoking rate in 1-hour windows was developed to assess the contribution of each predictor.

Results

In total, 8639 cigarettes and 1839 EMA surveys were tracked over 902 participant days. Most smokers were found to have an inaccurate and often biased estimate of their daily smoking rate compared with the measured smoking rate. Specifically, 74% (34/46) of the smokers made more than one (mean 4.7, SD 4.2 cigarettes per day) wrong estimate, and 70% (32/46) of the smokers overestimated it. On the basis of the timestamp of the tracked smoking events, smoking rates were visualized at different hours and were found to gradually increase and peak at 6 PM in the day. In addition, a 1- to 2-hour shift in smoking patterns was observed between weekdays and weekends. When moderate and heavy smokers were compared with light smokers, their ages (P<.05), Fagerström Test of Nicotine Dependence (P=.01), craving level (P<.001), enjoyment of cigarettes (P<.001), difficulty resisting smoking (P<.001), emotional valence (P<.001), and arousal (P<.001) were all found to be significantly different. In the Poisson mixed-effects model, the number of cigarettes smoked in a 1-hour time window was highly dependent on the smoking status of an individual (P<.001) and was explained by hour (P=.02) and age (P=.005).

Conclusions

This study reported the high potential and challenges of using an electronic lighter for smoking annotation and smoking-triggered EMAs in an ambulant environment. These results also validate the techniques for smoking behavior monitoring and pave the way for the design and deployment of technology-enabled smoking cessation applications.

International Registered Report Identifier (IRRID)

RR2-10.1136/bmjopen-2018-028284

Preventive Medication Patterns in Bipolar Disorder and Their Relationship With Comorbid Substance Use Disorders in a Cross-National Observational Study

OBJECTIVE

The potential role of sub-optimal pharmacological treatment in the poorer outcomes observed in bipolar disorder (BD) with vs. without comorbid substance use disorders (SUDs) is not known. Thus, we investigated whether patients with BD and comorbid SUD had different medication regimens than those with BD alone, in samples from France and Norway, focusing on compliance to international guidelines.

METHODS

Seven hundred and seventy patients from France and Norway with reliably ascertained BD I or II (68% BD-I) were included. Medication information was obtained from patients and hospital records, and preventive treatment was categorized according to compliance to guidelines. We used Bayesian and regression analyses to investigate associations between SUD comorbidity and medication. In the Norwegian subsample, we also investigated association with lack of medication.

RESULTS

Comorbid SUDs were as follows: current tobacco smoking, 26%, alcohol use disorder (AUD), 16%; cannabis use disorder (CUD), 10%; other SUDs, 5%. Compliance to guidelines for preventive medication was lacking in 8%, partial in 44%, and complete in 48% of the sample. Compliance to guidelines was not different in BD with and without SUD comorbidity, as was supported by Bayesian analyses (highest Bayes Factor = 0.16). Cross national differences in treatment regimens led us to conduct country-specific adjusted regression analyses, showing that (1) CUD was associated with increased antipsychotics use in France (OR = 2.4, 95% CI = 1.4-3.9, p = 0.001), (2) current tobacco smoking was associated with increased anti-epileptics use in Norway (OR = 4.4, 95% CI = 1.9-11, p < 0.001), and (3) AUD was associated with decreased likelihood of being medicated in Norway (OR = 1.2, 95% CI = 1.04-1.3, p = 0.038).

CONCLUSION

SUD comorbidity in BD was overall not associated with different pharmacological treatment in our sample, and not related to the level of compliance to guidelines. We found country-specific associations between comorbid SUDs and specific medications that warrant further studies.

Reduction of cardiovascular risk factors among young men with hypertension using an interactive decision aid: cluster-randomized control trial

BACKGROUND

Coronary heart disease (CHD) mortality among young men is very high and the prevention methods usable in family practice (FP) settings are limited (1,2). The objectives of this study were to investigate the cardiovascular risk profile among young males (18-50) visiting their family doctor (FD) and to find out if using an interactive computer-based decision aid (DA) has advantages in reducing cardiovascular risk factors compared to usual counselling at the FD's office.

METHODS

The study was a cluster-randomized controlled trial including hypertensive male patients aged 18-50 recruited by their FD in 2015-2016. Patients with cardiovascular complications were not included. FDs were randomly divided into intervention groups (n = 9) and control groups (n = 11). Altogether, FDs recruited 130 patients, 77 into the intervention group (IG) and 53 into the control group (CG). IG patients were counselled about cardiovascular risk factors using a computer-based DA. CG patients received usual counselling by their FD. Data was collected with questionnaires, clinical examinations and laboratory analyses at the baseline and at the follow-up visit three months later. We compared the cardiovascular risk factors of the IG and CG patients.

RESULTS

Baseline characteristics of the IG and CG patients were comparable. Of the whole study group, 51.5% (n = 67) of the patients had hypertension grade 1, 45.4% (n = 59) had grade 2 and 3.1% (n = 4) had grade 3. Twenty-seven per cent (n = 21) of the IG and 42% (n = 22) of the CG patients were smokers. We found that shared decision making with the DA was more effective in smoking reduction compared to usual FD counselling: 21 smoking patients in the IG reduced the number of cigarettes per day which is significantly more than the 22 smoking patients in the CG (- 3.82 ± 1.32 (SE Mean) versus + 2.32 ± 1.29; p = 0.001). Systolic blood pressure (SBP), diastolic blood pressure (DBP) and the number of cigarettes per day, all showed a statistically significant reduction among patients who were using the DA. Male patients with hypertension grade 2 had a significantly greater reduction in their SBP (- 6.003 ± 2.59 (SE Mean) versus + 1.86 ± 2.58; p = 0.038) grade 1. Reduction of DBP, cigarettes per day and CVD risk in general were nearly significant in the IG whereas the CG showed an increase in all of these parameters.

CONCLUSION

Using interactive DAs at FD's offices for counselling of young hypertensive male patients is one possibility to help patients understand their risk factors and make changes in their treatment choices. DAs can be more effective in achieving behavioural changes like reducing smoking or blood pressure compared to normal counselling.

Cannabidiol Cigarettes as Adjunctive Treatment for Psychotic Disorders - A Randomized, Open-Label Pilot-Study

Background: Psychotic disorders are associated with high rates of comorbid substance use disorders. Use of cannabis rich in tetrahydrocannabinol (THC) is linked to an increased risk of psychosis, worsening of psychotic symptoms, and an adverse course of psychotic disorders. Previous studies suggest oral cannabidiol (CBD) as possible novel antipsychotic agent; however, no studies evaluated the effects of smoked CBD. Objective: The main aim of the study was to clarify the antipsychotic potential of CBD used as adjunctive therapy simulating a naturalistic setting. Our trial is the first study evaluating the effects of smoked CBD-cigarettes as adjunctive therapy for psychotic symptoms. Methods: A randomized, placebo-controlled open-label trial of cigarettes containing CBD-rich cannabis (THC < 1%) as adjunctive therapy to standard psychiatric treatment was conducted (ClinicalTrials.gov identifier NCT04700930). Primary outcomes were mean scores of Positive and Negative Syndrome Scale (PANSS), Brøset Violence Checklist, the Beck's Depression Inventory (BDI), the Subjective Well-Being Under Neuroleptics Scale short form (SWN-K), and antipsychotic medication equivalent doses. Outcomes were assessed after 4 weeks of acute treatment and long-term follow-up after discontinuation of CBD-cigarettes after 25 weeks. Participants were 31 acutely psychotic patients with tobacco use disorder and a mean age of 35.1 ± 10.58 years (71% male). Comorbid cannabis use was diagnosed in 51.6%. Results: A discontinuous multilevel model revealed no significant group differences for primary outcomes. After 4 weeks of acute treatment, mean PANSS and BDI decreased in both groups, while an increase of antipsychotic medication equivalent was observed in the placebo group. Conclusions: The presented findings might suggest an antipsychotic medication sparing effect of CBD-cigarettes as adjunctive treatment of acute psychosis. However, the low number of participants did not allow for further statistical analysis. Hence, a larger study sample and a more rigorous study design (blinding of the interventional product, fixed dosing regimen) may reveal different results. Clinical Trial Registration: ClinicalTrials.gov, identifier: NCT04700930.

Validating E-Cigarette Dependence Scales Based on Dynamic Patterns of Vaping Behaviors

INTRODUCTION

Existing e-cigarette dependence scales are mainly validated based on retrospective overall consumption or perception. Further, given that the majority of adult e-cigarette users also use combustible cigarettes, it is important to determine whether e-cigarette dependence scales capture the product-specific dependence. This study fills in the current knowledge gaps by validating e-cigarette dependence scales using novel indices of dynamic patterns of e-cigarette use behaviors and examining the association between dynamic patterns of smoking and e-cigarette dependence among dual users.

METHODS

Secondary analysis was conducted on the 2-week ecological momentary assessment data from 116 dual users. The Smoothly Clipped Absolute Deviation penalty (SCAD) was adopted to select important indices for dynamic patterns of consumption or craving and estimate their associations with e-cigarette dependence scales.

RESULTS

The fitted linear regression models support the hypothesis that higher e-cigarette dependence is associated with higher levels of e-cigarette consumption and craving as well as lower instability of e-cigarette consumption. Controlling for dynamic patterns of vaping, dual users with lower e-cigarette dependence tend to report higher day-to-day dramatic changes in combustible cigarette consumption but not higher average levels of smoking.

CONCLUSIONS

We found that more stable use patterns are related to higher levels of dependence, which has been demonstrated in combustible cigarettes and we have now illustrated in e-cigarettes. Furthermore, the e-cigarette dependence scales may capture the product-specific average consumption but not product-specific instability of consumption.

IMPLICATIONS

This study provides empirical support for three e-cigarette dependence measures: PS-ECDI, e-FTCD, and e-WISDM, based on dynamic patterns of e-cigarette consumption and craving revealed by EMA data that have great ecological validity. This is the first study that introduces novel indices of dynamic patterns and demonstrates their potential applications in vaping research.

Two weeks of image-guided left dorsolateral prefrontal cortex repetitive transcranial magnetic stimulation improves smoking cessation: A double-blind, sham-controlled, randomized clinical trial

BACKGROUND

Previous studies have found that repetitive transcranial magnetic stimulation (rTMS) to the left dorsal lateral prefrontal cortex (LDLPFC) transiently reduces smoking craving, decreases cigarette consumption, and increases abstinence rates.

OBJECTIVE

We investigated whether 10 daily MRI-guided rTMS sessions over two weeks to the LDLPFC paired with craving cues could reduce cigarette consumption and induce smoking cessation.

METHODS

We enrolled 42 treatment-seeking nicotine-dependent smokers (≥10 cigarettes per day) in a randomized, double-blind, sham-controlled trial. Participants received 10 daily sessions over 2 weeks of either active or sham MRI-guided rTMS (10Hz, 3000 pulses each session) to the LDLPFC concurrently with video smoking cues. The primary outcome was a reduction in biochemically confirmed cigarette consumption with a secondary outcome of abstinence on the target quit date. We also recorded cue-induced craving and withdrawal symptoms.

RESULTS

Compared to sham (n = 17), participants receiving active rTMS (n = 21) smoked significantly fewer cigarettes per day during the 2-week treatment (mean [SD], 13.73[9.18] vs. 11.06[9.29], P < .005) and at 1-month follow-up (12.78[9.53] vs. 7.93[7.24], P < .001). Active rTMS participants were also more likely to quit by their target quit rate (23.81%vs. 0%, OR 11.67, 90% CL, 0.96-141.32, x2 = 4.66, P = .031). Furthermore, rTMS significantly reduced mean craving throughout the treatments and at follow-up (29.93[13.12] vs. 25.01[14.45], P < .001). Interestingly across the active treatment sample, more lateral coil location was associated with more success in quitting (-43.43[0.40] vs. -41.79[2.24], P < .013).

CONCLUSIONS

Daily MRI-guided rTMS to the LDLPFC for 10 days reduces cigarette consumption and cued craving for up to one month and also increases the likelihood of smoking cessation.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02401672.

Sex Differences in Subjective and Behavioral Responses to Stressful and Smoking Cues Presented in the Natural Environment of Smokers

INTRODUCTION

Some evidence suggests that female smokers may show more context-dependent smoking and that males may show more stereotyped smoking (regardless of stress or cue exposure). The goal of this study was to characterize sex differences in response to stressful and smoking cues ecologically presented in daily life and variability in day-to-day smoking behavior.

METHODS

Adult smokers (N = 177) provided ratings of mood and cigarette craving before and after stress and smoking cues were presented four times daily for 14 days via a mobile device. Linear mixed models tested whether (1) female smokers exhibited greater reactivity to stressful cues than male smokers; (2) pre-cue negative affect increased reactivity to smoking cues more in female smokers than male smokers; (3) across both sexes, greater reactivity to stressful and smoking cues correlated with greater quantity of smoking within a day; and (4) female smokers exhibited greater variability in cigarettes per day (CPD) relative to males.

RESULTS

Relative to male smokers, female smokers reported greater negative affect, stress, and craving in response to stressful cues, but not smoking cues, after accounting for time since last cigarette and pre-cue responding. No sex differences in CPD or variability in CPD were detected. Days with higher subjective reactivity to cues were not associated with increased smoking, in either males or females.

CONCLUSIONS

Sex differences were observed in response to stress but not smoking cues in the natural environment of regular cigarette smokers. Further research is necessary to evaluate whether stress reactivity in female smokers is associated with reduced latency to smoke following stress exposure in daily life.

IMPLICATIONS

This study provides naturalistic evidence that female smokers may not be more reactive to smoking cues than males, but experience heightened stress and craving following stress exposure. There was no evidence to support the hypothesis that amount smoked per day varied more for females, relative to males, as a result of more context-driven smoking for females.

An electronic, smart lighter to measure cigarette smoking: A pilot study to assess feasibility and initial validity

Understanding variability in smoking patterns may inform smoking cessation interventions. Retrospective reports of cigarettes smoked per day may be biased and typically do not provide temporal precision regarding when cigarettes are smoked. However, real-time, user-initiated tracking, such as logging each time a cigarette is smoked, can be burdensome over long time frames. In this study, adult, non-treatment seeking daily smokers (N = 22) used an electronic, smart lighter to light and timestamp cigarettes for 14 days. Participants reported number of cigarettes smoked per day (CPD) via a mobile device (daily diary) and retrospectively reported CPD at the end of the study using the Timeline Followback (TLFB). Self-reported lighter satisfaction and adherence varied with 68% of participants reporting that they liked using the lighter and participants reporting using the lighter for 92% of cigarettes smoked, on average. Lighter-estimated CPD did not differ from daily diary-estimated CPD, but was significantly lower than TLFB estimates. The lighter resulted in greater day-to-day variability relative to other methods and fewer rounded cigarette counts (digit bias) relative to the TLFB. The lighter appears to be feasible for capturing data on smoking patterns in daily smokers. Though false positive cigarettes are likely low, additional technologies that augment data captured from the lighter may be necessary to reduce false negatives (missed cigarettes) and alternative lighter designs may appeal more to certain smokers.

Tobacco smoking and other substance use disorders associated with recurrent suicide attempts in bipolar disorder

BACKGROUND

Suicide attempts (SA) are more frequent in bipolar disorder (BD) than in most other mental disorders. Prevention strategies would benefit from identifying the risk factors of SA recurrence in BD. Substance use disorders (SUD) (including tobacco-related) are strongly associated with both BD and SA, however, their specific role for the recurrence of SA in BD remains inadequately investigated. Thus, we tested if tobacco smoking - with or without other SUDs - was independently associated with recurrent SA in BD.

METHODS

916 patients from France and Norway with ascertained diagnoses of BD and reliable data about SA and SUD were classified as having no, single, or recurrent (≥2) SA. Five SUD groups were built according to the presence/absence/combination of tobacco, alcohol (AUD) and cannabis use disorders. Multinomial logistic regression was used to identify the correlates of SA recurrence.

RESULTS

338 (37%) individuals reported at least one SA, half of whom (173, 51%) reported recurrence. SUD comorbidity was: tobacco smoking only, 397 (43%), tobacco smoking with at least another SUD, 179 (20%). Regression analysis showed that tobacco smoking, both alone and comorbid with AUD, depressive polarity of BD onset and female gender were independently associated with recurrent SA.

LIMITATIONS

Lack of data regarding the relative courses of SA and SUD and cross-national differences in main variables.

CONCLUSION

Tobacco smoking with- or without additional SUD can be important risk factors of SA recurrence in BD, which is likely to inform both research and prevention strategies.

A geographically explicit ecological momentary assessment (GEMA) mixed method for understanding substance use

Tobacco use is increasingly concentrated within marginalized groups, including LGBTQ+ young adults. Developing tailored interventions to reduce tobacco-related health disparities requires understanding the mechanisms linking individual and contextual factors associated with tobacco use to behavior. This paper presents an in-depth exploration of three cases from a novel mixed method study designed to identify the situational factors and place-based practices of substance use among high-risk individuals. We combined geographically explicit ecological momentary assessment (GEMA) with an adapted travel diary-interview method. Participants (young adult bisexual smokers, ages 18-26) reported on non-smoking and smoking situations for 30 days with a smartphone app. GEMA surveys captured internal and external situational factors (e.g., craving intensity, location type, seeing others smoking). Continuous locational data was collected via smartphone GPS. Subsequently, participants completed in-depth interviews reviewing maps of their own GEMA data. GEMA data and transcripts were analyzed separately and integrated at the case level in a matrix. Using GEMA maps to guide the interview grounded discussion in participants' everyday smoking situations and routines. Interviews clarified participant interpretation of GEMA measures and revealed experiences and meanings of smoking locations and practices. The GEMA method identified the most frequent smoking locations/times for each participant (e.g., afternoons at university). Interviews provided description of associated situational factors and perceptions of smoking contexts (e.g., peer rejection of bisexual identity) and the roles of smoking therein (e.g., physically escape uncomfortable environments). In conclusion, this mixed method contributes to advancing qualitative GIS and other hypothesis-generating approaches working to reveal the richness of individuals' experiences of the everyday contexts of health behavior, while also providing reliable measures of situational predictors of behaviors of interest, such as substance use. Limitations of and future directions for the method are discussed.