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The study aims to assess prevalence of smartphone addiction symptoms, and to ascertain whether depression or anxiety, independently, contributes to smartphone addiction level among a sample of Lebanese university students, while adjusting simultaneously for important sociodemographic, academic, lifestyle, personality trait, and smartphone-related variables. A random sample of 688 undergraduate university students (mean age = 20.64 ±1.88 years; 53% men) completed a survey composed of a) questions about socio-demographics, academics, lifestyle behaviors, personality type, and smartphone use-related variables; b) 26-item Smartphone Addiction Inventory (SPAI) Scale; and c) brief screeners of depression and anxiety (PHQ-2 and GAD-2), which constitute the two core DSM-IV items for major depressive disorder and generalized anxiety disorder, respectively. Prevalence rates of smartphone-related compulsive behavior, functional impairment, tolerance and withdrawal symptoms were substantial. 35.9% felt tired during daytime due to late-night smartphone use, 38.1% acknowledged decreased sleep quality, and 35.8% slept less than four hours due to smartphone use more than once. Whereas gender, residence, work hours per week, faculty, academic performance (GPA), lifestyle habits (smoking and alcohol drinking), and religious practice did not associate with smartphone addiction score; personality type A, class (year 2 vs. year 3), younger age at first smartphone use, excessive use during a weekday, using it for entertainment and not using it to call family members, and having depression or anxiety, showed statistically significant associations with smartphone addiction. Depression and anxiety scores emerged as independent positive predictors of smartphone addiction, after adjustment for confounders. Several independent positive predictors of smartphone addiction emerged including depression and anxiety. It could be that young adults with personality type A experiencing high stress level and low mood may lack positive stress coping mechanisms and mood management techniques and are thus highly susceptible to smartphone addiction.

The last 2 decades have seen an increase in the number of reports of excessive internet use. Therefore, this study aimed to examine internet use among university students to gain more insight into the novel phenomenon of addictive internet use (AIU). Data were collected by the means of an online questionnaire sent to 4391 students. Approximately 10% of the 4391 students could be included in the statistical analysis. Of those 483 students, almost all (99.2%) used the internet, and a quarter (24.8%) showed AIU. The students used the internet mostly for information searches, random browsing, social networking, and online shopping; however, AIU was seen most often in the areas of social networking, random browsing, information searches, gaming, and pornography. One in four of the respondents showed addictive behavior in at least one area of internet use. Students with AIU in the area of random browsing were significantly less far advanced in their studies than those without AIU, and well-being was significantly poorer across AIU groups than in those who did not show AIU. The study confirms the importance of AIU, as reflected in the high prevalence of AIU among the students and the significantly lower level of well-being in those with AIU. Undifferentiated consideration of AIU does not do justice to its various facets, and future research should consider all areas of internet use, with the aim to increase understanding of the underlying mechanisms of AIU and develop more differentiated treatment approaches.

Rationale Chronic alcohol misuse can escalate into alcohol use disorder (AUD). The causal mechanisms through which recreational social drinking develops into compulsive uncontrolled alcohol misuse are multifaceted. For example, stress is an important risk factor that influences alcohol craving in both healthy and addicted individuals. In addition, those that are high in impulsivity/risk taking drink more and are at greater risk of developing addiction. At present, however, it is not possible accurately to predict those at risk of escalation in alcohol use, or of developing AUD. Objectives The aim of this study was to investigate how underlying physiological and personality traits affect stress-induced craving for, and consumption of, alcohol, in a sample of social drinkers. The primary hypothesis was that impulsivity/risk-taking would modulate stress-induced alcohol craving and consumption. Methods Thirty-nine participants (22 male and 17 female; mean age = 23.92 years [SD = 4.90]) were randomly allocated to ‘stress’ and ‘no-stress’ groups; in the stress group, participants took part in the Trier Social Stress Test (TSST). Participants completed several questionnaires and computer tasks in order to assess prior alcohol use, impulsivity/risk-taking, stress-reactivity, craving and physiological biomarkers of stress. Finally, participants completed a voluntary drinking task, in which increasing numbers of presses on a computer keyboard were reinforced with 5-ml shots of 37% ABV vodka (plus mixer). Results Participants exposed to the TSST showed an increase in craving following the stressor. Several factors predicted voluntary drinking, including risky decision making, slow HR recovery from stress, poor vagal tone during recovery from stress and greater stress reactivity. Surprisingly, we found no correlation between craving and consumption. Conclusions Our data suggest that variation in physiological stress parameters and poor decision-making abilities increase risk of stress-induced alcohol consumption. This may provide a useful translational framework through which we can further study early predictive markers for the shift between controlled recreational drinking to uncontrolled alcohol misuse, including AUD.

Food addiction is a controversial concept. The potential influence of food addiction on patients' psychosocial functioning and well-being has not been well established. The purpose of this study was to examine the relationships between psychosocial functioning (depressive symptoms and health-related quality of life [HRQOL]) and food addiction as measured by the Yale Food Addiction Scale (YFAS). We also explored whether food addiction contributed additional variance in explaining psychosocial functioning, beyond demographic and clinical factors (e.g., binge eating). The sample included 178 participants (mean age=44.2±11.2years; BMI=40.9±5.9kg/m2; 88.2% female; 70.8% Black) with obesity seeking treatment for weight loss. Participants completed the Medical Outcomes Study 36-Item Short-Form Health Survey, Impact of Weight on Quality of Life-Lite, Patient Health Questionnaire, YFAS, and Questionnaire on Eating and Weight Patterns-5. Twelve (6.7%) participants met criteria for food addiction, with 4 (33.3%) of these participants having co-occurring binge eating disorder. After adjusting for covariates, the number of food addiction symptoms accounted for 6.5% to 16.3% of additional variance in general HRQOL, 5.0% to 21.5% in weight-related HRQOL, and 19.1% in symptoms of depression. In this treatment-seeking sample of participants, we found a low prevalence of food addiction, suggesting that addictive-like eating is unlikely to be a causal mechanism for most people with obesity. However, individuals who met criteria for food addiction had reduced psychosocial functioning compared to those who did not meet criteria. Individuals with addictive-like eating may require additional psychosocial support.

Longitudinal studies of prospective predictors for pathological Internet use (PIU) in adolescents as well as its course are lacking. This three-wave longitudinal study was conducted within the framework of the European Union-funded project “Saving and Empowering Young Lives in Europe” over a 2-year period. The sample consisted of 1444 students at the baseline investigation (T0); 1202 students after 1 year (T1); and 515 students after 2 years (T2). Structured self-report questionnaires were administered at all three time points. PIU was assessed using the Young Diagnostic Questionnaire (YDQ). In addition, demographic (i.e., gender), social (i.e., parental involvement), psychological (i.e., emotional problems), and Internet use-related factors (i.e., online activities) were assessed as prospective predictors. The prevalence of PIU was 4.3 % at T0, 2.7 % at T1 and 3.1 % at T2. However, only 3 students (0.58 %) had persistent categorical PIU (YDQ score of ≥5) over the 2-year period. In univariate models, a variety of variables that have been previously identified in cross-sectional investigations predicted PIU at T2. However, multivariate regression demonstrated that only previous PIU symptoms and emotional problems were significant predictors of PIU 2 years later (adjusted R 2 0.23). The stability of categorical PIU in adolescents over 2 years was lower than previously reported. However, current PIU symptoms were the best predictor of later PIU; emotional symptoms also predicted PIU over and above the influence of previous problematic Internet use. Both PIU symptoms and emotional problems may contribute to the vicious cycle that supports the perpetuation of PIU.

A between-subjects experiment examines the effects of different warning types and modified risk e-cigarette ad claims on adolescent e-cigarette craving and future e-cigarette susceptibility for two different themes. One theme focuses on nicotine and addiction, and the other on the effects of potentially harmful constituents (eg, flavored chemicals and lung disease). The effects of warning type (control, text-only, graphic health warning [GHW] and text) and modified risk e-cigarette ad claims (control, exposure reduction, risk reduction) are tested experimentally with two different arms (themes) for a sample of 1011 adolescents who had tried either e-cigarettes or cigarettes. For addiction, the text-only warning led to significantly less e-cigarette susceptibility than the no warning control condition. As expected, there were no differences between the GHW + text condition and text-only or control conditions for e-cigarette craving. An interaction between warning type and modified risk claims revealed significantly fewer e-cigarette cravings and less susceptibility for the text-only warning and no claim (control) condition than for any other condition. For fatal lung disease, the GHW + text condition led to fewer e-cigarette cravings and less susceptibility than the text-only warning and no warning (control) conditions. Warning type effects can be very different under different themes (eg, addiction, fatal lung disease). In general, our results point to the effectiveness of the text-only warning for addiction and GHW + text for fatal lung disease. Relative exposure and risk modification claims (eg, less nicotine; less addicting) tend to undercut addiction warnings. More than one type of e-cigarette warning may be necessary as e-cigarette research evolves. Our results show different warning type effects (eg, text-only; GHW + text) on e-cigarette craving and future susceptibility for adolescent experimenters depending on the risk theme (eg, addiction; lung disease) and presence of ad claims (eg, exposure and risk reduction). As research emerges on risks associated with e-cigarette use, it is important to first know what at-risk populations (eg, adolescents) believe about such risks. Such research will aid our understanding of what types of warnings might be most effective, especially in the presence of ad claims.

Research on electronic cigarette (e-cigarette) warnings has primarily focused on addiction warnings, such as the one soon to be required by the Food and Drug Administration (FDA) in the United States. However, reduced-risk warnings, similar to the warnings recently proposed for smokeless tobacco products, remain a future possibility for e-cigarettes. Thus, this brief report compares e-cigarette health risk perceptions based on reduced-risk warnings and the FDA addiction risk warning, and considers whether these warnings differ in believability, ease of comprehension, and perceptions about the clarity of risk communication. A quota sample of 672 smokers, e-cigarette users, dual users, and nonusers participated in this between-subjects experiment. Study participants were randomly assigned to one of three warning conditions, including the FDA-mandated addiction warning and two reduced-risk warnings. After exposure to the warning statement, participants responded to measures of health risk perceptions, believability, ease of comprehension, and perception about the clarity of risk communication. Results reveal that the addiction warning is perceived as more believable, easier to comprehend, and more clearly communicating the health risks of e-cigarettes use compared with the reduced-risk warnings. In addition, overall health risk perceptions and addiction risk perceptions based on the addiction warning are greater than health risk perceptions based on the reduced-risk warnings. In contrast, specific disease-related risk perceptions such as cancer, heart disease, lung disease, and harm to an unborn baby are greater for the reduced-risk warnings. This study provides a comparison of the forthcoming FDA-mandated e-cigarette addiction warning and reduced-risk warnings that have begun to be considered in the literature on a number of critical outcomes. This research provides a greater understanding of how variations of e-cigarette warnings, including addiction and reduced-risk warnings, are perceived by smokers, e-cigarette users, dual users, and nonusers. Specifically, findings show that overall health risk perceptions and addiction risk perceptions based on the addiction warning are greater than risk perceptions based on the reduced-risk warnings. In contrast, specific disease-related risk perceptions, such as cancer and heart disease, are greater for the reduced-risk warnings.

Problematic internet use (PIU) among youth has become a public health concern. Previous studies identified socio-demographic background risk factors for PIU. The effects of online activities on youth PIU behavior are not well investigated. This cross-sectional study assessed the roles of online activities for PIU behavior of undergraduate students in Bahir Dar University, North West Ethiopia. Data were collected from 812 randomly selected regular program students recruited from 10 departments. Respondents completed a pre-tested structured questionnaire. Hierarchical logistic regression models were used for analyses. The results indicated that social networking (75.5%), entertainment (73.6%), academic works (70.9%), and online gaming (21.6%) are the important online activities students are engaging in the internet. About 33% and 1.8% of students showed symptoms of mild and severe PIU, respectively. Taking online activities into account improved the model explaining PIU behavior of students. Online activities explained 46% of the variance in PIU. Using the internet for social networking (AOR = 7.078; 95% CI: 3.913-12.804) and online gaming (AOR = 2.175; 95% CI: 1.419-3.335) were risk factors for PIU. The findings revealed that more than a third of the respondents showed symptoms of PIU. Online activities improved the model explaining PIU behavior of students. Thus, university authorities need to be aware of the prevalence of PIU and introduce regulatory mechanisms to limit the usage of potentially addictive online activities and promoting responsible use of the internet.

Rationale Breathing exercises have been proposed as a way of combating cigarette cravings, potentially presenting a low-cost, easily scalable smoking cessation aid. Objective The aim of this study is to evaluate the acute impact of breathing exercises based on yogic pranayama on cravings in abstaining smokers. Methods Participants visited the laboratory on two occasions 24 h apart and were asked to abstain from smoking12 h prior to the first visit until the end of the second visit. Smokers ( N  = 96) were randomly allocated to a yogic breathing exercise (YBG) or video control (VCG) group. The former was instructed on breathing exercises, practised these for 10 min and asked to use these when experiencing cravings until the next visit. The latter was shown a breathing exercise video for 10 min and asked to concentrate on their breathing. Strength of urges to smoke, other craving measures and mood and physical symptoms associated with cigarette withdrawal were assessed at the beginning and end of the first visit, and again at the second visit. Results At immediate follow-up, in the laboratory, all craving measures were reduced in YBG compared with VCG (strength of urges: F (1, 96) = 16.1, p  < 0.001; cigarette craving: F (1, 96) = 11.3, p  = 0.001; desire to smoke: F (1, 96) = 6.6, p  = 0.012). There was no effect on mood or physical symptoms. Adherence to the breathing exercise regimen in the following 24 h was low, and at 24 h follow-up, there was no evidence of reduced cravings in YBG compared with VCG. Conclusions Simple yogic-style breathing exercises can reduce cigarette craving acutely in the laboratory. Further research is needed to determine how far this translates into field settings.