Predicting smoking cessation, reduction and relapse six months after using the Stop-Tabac app for smartphones: a machine learning analysis.

An analysis of predictors of smoking behaviour among users of smoking cessation apps can provide useful information beyond what is already known about predictors in other contexts. Therefore, the aim of the present study was to identify the best predictors of smoking cessation, smoking reduction and relapse six months after starting to use the smartphone app Stop-Tabac. Secondary analysis of 5293 daily smokers from Switzerland and France who participated in a randomised trial testing the effectiveness of this app in 2020, with follow-up at one and six months. Machine learning algorithms were used to analyse the data. The analyses for smoking cessation included only the 1407 participants who responded after six months; the analysis for smoking reduction included only the 673 smokers at 6-month follow-up; and the analysis for relapse at 6 months included only the 502 individuals who had quit smoking after one month. Smoking cessation after 6 months was predicted by the following factors (in this order): tobacco dependence, motivation to quit smoking, frequency of app use and its perceived usefulness, and nicotine medication use. Among those who were still smoking at follow-up, reduction in cigarettes/day was predicted by tobacco dependence, nicotine medication use, frequency of app use and its perceived usefulness, and e-cigarette use. Among those who had quit smoking after one month, relapse after six months was predicted by intention to quit, frequency of app use, perceived usefulness of the app, level of dependence and nicotine medication use. Using machine learning algorithms, we identified independent predictors of smoking cessation, smoking reduction and relapse. Studies on the predictors of smoking behavior among users of smoking cessation apps may provide useful insights for the future development of these apps and future experimental studies. ISRCTN Registry: ISRCTN11318024, 17 May 2018. http://www.isrctn.com/ISRCTN11318024

Interactions between nutrition and gastrointestinal infections with parasitic nematodes in goats

Parasitic nematodes of the digestive tract remain one of the main constraints to goat production both in temperate and tropical countries. The usual mode of control of these gastrointestinal nematodes (GIN) based on the repeated use of anthelmintics is now strongly questioned because of the increasing development of resistance to these molecules. Among the alternative methods to anthelmintics currently available, the manipulation of host nutrition in order to improve the host resistance and/or resilience to parasitic infections seems to represent one of the most promising options to reduce the dependence on conventional chemotherapy and to favour the sustainable control of gastro intestinal nematode infections. This paper will review the available information on the interactions between nutrition and nematode parasitism in dairy or meat goats both in temperate and tropical conditions. It will refer to quantitative aspects of the diet (influence of the protein and/or energy parts) as well as to qualitative components (effects of plant secondary metabolites on worm biology) and will discuss the specificities of goats in regard of theses interactions

Toxicity assessment of refill liquids for electronic cigarettes.

We analyzed 42 models from 14 brands of refill liquids for e-cigarettes for the presence of micro-organisms, diethylene glycol, ethylene glycol, hydrocarbons, ethanol, aldehydes, tobacco-specific nitrosamines, and solvents. All the liquids under scrutiny complied with norms for the absence of yeast, mold, aerobic microbes, Staphylococcus aureus, and Pseudomonas aeruginosa. Diethylene glycol, ethylene glycol and ethanol were detected, but remained within limits authorized for food and pharmaceutical products. Terpenic compounds and aldehydes were found in the products, in particular formaldehyde and acrolein. No sample contained nitrosamines at levels above the limit of detection (1 μg/g). Residual solvents such as 1,3-butadiene, cyclohexane and acetone, to name a few, were found in some products. None of the products under scrutiny were totally exempt of potentially toxic compounds. However, for products other than nicotine, the oral acute toxicity of the e-liquids tested seems to be of minor concern. However, a minority of liquids, especially those with flavorings, showed particularly high ranges of chemicals, causing concerns about their potential toxicity in case of chronic oral exposure

1923 - A.C.C Bible Lecture Week, Abilene Christian College

This is program for the 1923 Sixth Annual Bible Lecture Week at Abilene Christian College. Uploaded by Jackson Hager

The Stop-tabac smartphone application for smoking cessation: a randomized controlled trial.

To test whether the Stop-tabac smartphone application (app) increased smoking cessation rates. A two-arm, parallel-group, individually randomized, double-blind, controlled trial. A total of 5293 daily smokers (Stop-tabac = 2639, control = 2654) enrolled on app stores and on the internet in 2019-20, who lived in France or Switzerland. The Stop-tabac application includes immediate feedback during episodes of craving and withdrawal; individually tailored counseling messages with notifications sent during 6 months; a discussion forum; fact sheets; modules on nicotine replacement therapy and e-cigarettes; and calculators of cigarettes not smoked, money saved and days of life gained since quitting. The control application included five brief pages and calculators as above. Primary outcome: self-reported smoking cessation after 6 months (no puff of tobacco in the past 4 weeks), with non-responders counted as smokers. self-reported use of nicotine medications. Participants were aged 36 years on average; 66% were women who smoked 15 cigarettes/day, and 64% screened positive for depression. Stop-tabac participants used the app over a longer period than control participants (23 versus 11 days, P < 0.001). Smoking cessation rates after 6 months were 9.9% in the Stop-tabac group versus 10.3% in the control group (odds ratio = 0.96, 95% confidence interval = 0.80-1.45, P = 0.63). Rates of use of nicotine medications after entry in the study were 38 versus 30% after 6 months (χ <sup>2</sup> = 8.3, P = 0.004) in the Stop-tabac and control groups. After 6 months, 26% of participants in the Stop-tabac group and 8% in the control group said that the app helped them 'a lot' or 'enormously' to quit smoking (χ <sup>2</sup> = 113, P < 0.001). In smokers enrolled on the app stores and the internet, allocation to the Stop-tabac smoking cessation app did not increase smoking cessation rates, but increased rates of use of nicotine medications

The Stop-Tabac smartphone application for smoking cessation: study protocol for a randomized controlled trial in the general population.

Smartphone-based support can reach thousands of smokers and help those who would otherwise try to quit smoking by themselves with little chance of success. Nicotine medications double the chances of quitting smoking, but few smokers use them, and they often use them for too short a time and at an insufficient dose. It is therefore important to increase access to support for smoking cessation and compliance with nicotine therapy. The objectives of this study are to assess whether the Stop-Tabac application (app) is effective for smoking cessation and to examine whether the outcome is influenced by the personal characteristics of participants. Trial design: this is a two-arm, parallel-group, superiority, individually randomized, "placebo" controlled trial in 5200 smokers, with follow up after 1 week, 1 month and 6 months. The participants are adult daily smokers (N = 5200) enrolled on the Internet, living in France or Switzerland. The intervention is the Stop-tabac fully-automated app for smartphones, which was launched in 2012 and continuously improved thereafter. It includes fact sheets; calculators of cigarettes not smoked, money saved, and years of life gained; an interactive "coach" that provides automated, individually tailored counseling messages based on the user's personal profile, sent regularly for 6 months; immediate feedback during episodes of craving and tobacco withdrawal symptoms; a discussion forum ("The Tribe") where participants provide and receive social support; a quiz that informs users in a playful way; and a module on nicotine therapy that includes personalized feedback and follow up. The outcome is self-reported smoking cessation after 6 months (no puff of tobacco in the past 4 weeks), and after 1 week and 1 month (no puff in the past 7 days). Participants will be randomized automatically based on a list of random numbers. Participants, assistants in charge of collecting follow-up data and data analysts will be blinded to allocation. Funding is provided by the Swiss National Science Foundation, CHF 194,942 (EUR 182,200, USD 200,700), grant 32003_179369. JFE's salary is paid by the University of Geneva, YK's salary is paid by the Lausanne University Hospitals. There is little evidence from randomized trials of the impact of health apps in general and of smoking cessation apps in particular. This study will fill this gap. ISRCTN Registry: ISRCTN11318024. Registered on 17 May 2018

Treating tobacco companies fairly but with no leap of faith.

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Predicting the Users' Level of Engagement with a Smartphone Application for Smoking Cessation: Randomized Trial and Machine Learning Analysis.

Studies of the users' engagement with smoking cessation application (apps) can help understand how these apps are used by smokers, in order to improve their reach and efficacy. The present study aimed at identifying the best predictors of the users' level of engagement with a smartphone app for smoking cessation and at examining the relationships between predictors and outcomes related to the users' level of engagement with the app. A secondary analysis of data from a randomized trial testing the efficacy of the Stop-Tabac smartphone app was used. The experimental group used the "full" app and the control group used a "dressed down" app. The study included a baseline and 1-month and 6-month follow-up questionnaires. A total of 5,293 participants answered at least the baseline questionnaires; however, in the current study, only the 1,861 participants who answered at least the baseline and the 1-month follow-up questionnaire were included. Predictors were measured at baseline and after 1 month and outcomes after 6 months. Data were analyzed using machine learning algorithms. The best predictors of the outcomes were, in decreasing order of importance, intention to stop smoking, dependence level, perceived helpfulness of the app, having quit smoking after 1 month, self-reported usage of the app after 1 month, belonging to the experimental group (vs. control group), age, and years of smoking. Most of these predictors were also significantly associated with the participants' level of engagement with the app. This information can be used to further target the app to specific groups of users, to develop strategies to enroll more smokers, and to better adapt the app's content to the users' needs

Saliva cotinine levels in smokers and nonsmokers.

The authors collected by mail self-reported data on smoking habits and saliva samples that were analyzed for cotinine concentration in 222 smokers and 97 nonsmokers. Participants were members of the University of Geneva (Switzerland) in 1995. The 207 cigarette-only smokers smoked on average 10.7 cigarettes/day and had a median concentration of cotinine of 113 ng/ml. The cotinine concentration was moderately associated with the number of cigarettes smoked per day (+14 ng/ml per additional cigarette, p < 0.001, R2 = 0.45) and was 54 ng/ml higher in men than in women after adjustment for cigarettes per day and for the Fagerström Test for Nicotine Dependence. The cotinine level was not associated with the nicotine yield of cigarettes (r= 0.08). In nonsmokers, the median concentration of cotinine was 2.4 ng/ml. The cotinine concentration was 1.5 times higher in nonsmokers whose close friends/spouses were smokers than in nonsmokers whose close friends/spouses were nonsmokers (p = 0.05). A cutoff of 7 ng/ml of cotinine distinguished smokers from nonsmokers with a sensitivity of 92.3% and a specificity of 89.7%; a cutoff of 13 ng/ml provided equally satisfactory results (sensitivity, 86.5%; specificity, 95.9%). This study provides evidence for the construct validity of both questionnaires and saliva cotinine for the assessment of active and passive exposure to tobacco smoke