In this paper, we demonstrate how the state-of-the-art machine learning and text mining techniques can be used to build effective social media-based substance use detection systems. Since a substance use ground truth is difficult to obtain on a large scale, to maximize system performance, we explore different feature learning methods to take advantage of a large amount of unsupervised social media data. We also demonstrate the benefit of using multi-view unsupervised feature learning to combine heterogeneous user information such as Facebook "likes" and "status updates" to enhance system performance. Based on our evaluation, our best models achieved 86 AUC for predicting tobacco use, 81 for alcohol use and 84 for drug use, all of which significantly outperformed existing methods. Our investigation has also uncovered interesting relations between a user's social media behavior (e.g., word usage) and substance use.
Substance use disorder (SUD) encompasses a complex pattern of behaviors. Many studies have been conducted to discover factors interacting with SUD. A growing number of studies have confirmed a strong association between personal traits and substance use. For example, @cite_38 found that smokers have significantly higher openness to experience and lower conscientiousness , a personality trait related to a tendency to show self-discipline, act dutifully, and aim for achievement. @cite_30 examined the links between alcohol consumption and personality and found that alcohol use is correlated positively with sociability and extraversion. @cite_17 conducted a study involving 1102 participants and found a link between drug use and low conscientiousness . @cite_22 revealed risk factors related to addiction such as age, sex, impulsivity, sweet-liking, novelty reactivity, proclivity for exercise, and environmental impoverishment. Additionally, addiction is also linked to environmental and social factors such as neighborhood environment @cite_31 , family environment @cite_14 @cite_21 and social norms @cite_12 @cite_29 .
@cite_30 @cite_38 @cite_14 @cite_22 @cite_29 @cite_21 @cite_31 @cite_12 @cite_17
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Research and clinical expertise indicates that impulsivity is an underlying feature of pathological gambling. This study examined the extent to which impulsive behavior, defined by the rate of discounting delayed monetary rewards, varies with pathological gambling severity, assessed by the South Oaks Gambling Screen (SOGS). Sixty-two pathological gamblers completed a delay discounting task, the SOGS, the Eysenck impulsivity scale, the Addiction Severity Index (ASI), and questions about gambling and substance use at intake to outpatient treatment for pathological gambling. In the delay discounting task, participants chose between a large delayed reward (US @math 1-$999) across a range of delays (6h to 25 years). The rate at which the delayed reward was discounted (k value) was derived for each participant and linear regression was used to identify the variables that predicted k values. Age, gender, years of education, substance abuse treatment history, and cigarette smoking history failed to significantly predict k values. Scores on the Eysenck impulsivity scale and the SOGS both accounted for a significant proportion of the variance in k values. The predictive value of the SOGS was 1.4 times that of the Eysenck scale. These results indicate that of the measures tested, gambling severity was the best single predictor of impulsive behavior in a delay discounting task in this sample of pathological gamblers. Psychosocial factors are the principle determinants of youth drug abuse. Among those factors, the most important direct influence on drug use is that of the peer cluster: “gangs,” best friends, or couples. Other psychosocial characteristics, however, set the stage for this involvement with drug-using peer clusters. Social characteristics that influence drug use in this way include the community, socioeconomic status, neighborhood environments, family, religion, and the school. Psychological characteristics tend to have only low correlations with drug use, but there is some influence on peer clusters from traits such as self-esteem, depression, anxiety, and introversion, particularly when these lead to anger. Implications for prevention and treatment are considered. Abstract Although research finds high rates of risky sexual and drug related behavior among homeless young people, little research had examined how the characteristics of their social networks encourage or constrain risky behaviors. Based on a sample of 145 homeless young adults in the Midwestern United States, results revealed that having used alcohol with at least one of their network members and the presence of more conflict was associated with engaging in a greater number of sexual risk taking behaviors. Correlates of engaging in a greater number of substance use related behaviors included having older peers within the network, having used illicit drugs with at least one network member, and the presence of more conflict. The presence of a family member in one’s network, however, was associated with fewer sexual and drug related risk behaviors. Overall, the social network characteristics of youth explained significant, additional variance beyond that of youth’s own characteristics and their early family histories. Associations of popularity with adolescent substance use were examined among 1793 6-8th grade students who completed an in-school survey. Popularity was assessed through both self-ratings and peer nominations. Students who scored higher on either measure of popularity were more likely to be lifetime cigarette smokers, drinkers, and marijuana users, as well as past month drinkers. Self-rated popularity was positively associated with past month marijuana use and heavy drinking, and peer-nominated popularity showed a quadratic association with past month heavy drinking. These results extend previous work and highlight that popularity, whether based on self-perceptions or peer friendship nominations, is a risk factor for substance use during middle school. Given the substantial increase in peer influence during early adolescence, prevention program effectiveness may be enhanced by addressing popularity as a risk factor for substance use or working with popular students to be peer leaders to influence social norms and promote healthier choices. Language: en We hypothesized that neighborhood disadvantage might function as a determinant of ‘exposure opportunity’, an intermediate step on a path toward starting to use drugs illicitly. Testing this hypothesis, we analyzed self-report data gathered in 1992 by means of confidential interviews with 1416 urban-dwelling middle-school participants in a longitudinal field study. Within this epidemiologic sample, 50 youths said that someone actively had offered them a chance to take cocaine or smoke crack; tobacco had been offered to 395 youths; alcohol to 429 youths. Using multiple logistic regression to hold constant grade, sex, minority status, and peer drug use, we found a moderately potent association between neighborhood disadvantage and exposure to cocaine: youths living in the most disadvantaged neighborhoods (highest tertile) were an estimated 5.6 times more likely to have been offered cocaine, as compared to those in relatively advantaged neighborhoods (P = 0.001). By comparison, there were weaker but statistically significant associations involving tobacco exposure opportunity (odds ratio, OR =1.7, P = 0.004) and alcohol exposure opportunity (OR = 1.9, P = 0.0005). Future research will clarify the etiologic significance of neighborhood disadvantage in pathways leading toward illicit drug use. • In a sample of 242 male and 201 female adoptees who had been separated at birth from biologic parents, adult adoptee diagnoses of alcohol abuse, drug abuse and antisocial personality were correlated with biologic and environmental factors. Three etiologic relationships with drug abuse were found: (1) drug abuse was highly correlated with antisocial personality, which in turn was predicted from antisocial biologic background; (2) a biologic background of alcohol problems predicted increased drug abuse in adoptees who did not have antisocial personalities; and (3) environmental factors of divorce and psychiatric disturbance in the adoptive family were associated with increased drug abuse. Aims To investigate whether adolescent heavy drinkers exhibit biased cognitive processing of alcohol-related cues and impulsive decision making. Design A between-subjects design was employed. Setting Classrooms in a single sixth-form college in Merseyside, UK. Participants Ninety adolescent students (mean age 16.83 years), of whom 38 were identified as heavy drinkers and 36 were identified as light drinkers, based on a tertile split of their weekly alcohol consumption. Measurements Participants provided information about alcohol consumption before completing measures of alcohol craving, delay discounting and an ‘alcohol Stroop’ in which they were required to name the colour in which alcohol-related and matched control words were printed. Findings Compared to light drinkers, heavy drinkers showed more pronounced discounting of delayed hypothetical monetary and alcohol rewards, which is indicative of a more short-term focus in decision making in heavy drinkers. Heavy drinkers were also slower to colour-name alcohol-related words, which indicates an attentional bias for alcohol-related cues. In all participants, measures of delay discounting and attentional bias were correlated moderately with each other, and also with the level of alcohol consumption and with alcohol craving. Conclusions In adolescents, heavy alcohol use is associated with biased attentional processing of alcohol-related cues and a shorter-term focus in decision making. Rationale: Impulsivity is implicated in drug dependence. Recent studies show problems with alcohol and opioid dependence are associated with rapid discounting of the value of delayed outcomes. Furthermore, discounting may be particularly steep for the drug of dependence. Objectives: We determined if these findings could be extended to the behavior of cigarette smokers. In particular, we compared the discounting of hypothetical monetary outcomes by current, never, and ex-smokers of cigarettes. We also examined discounting of delayed hypothetical cigarettes by current smokers. Methods: Current cigarette smokers (n=23), never-smokers (n=22) and ex-smokers (n=21) indicated preference for immediate versus delayed money in a titration procedure that determined indifference points at various delays. The titration procedure was repeated with cigarettes for smokers. The degree to which the delayed outcomes were discounted was estimated with two non-linear decay models: an exponential model and a hyperbolic model. Results: Current smokers discounted the value of delayed money more than did the comparison groups. Never- and ex-smokers did not differ in their discounting of money. For current smokers, delayed cigarettes lost subjective value more rapidly than delayed money. The hyperbolic equation provided better fits to the data than did the exponential equation for 74 out of 89 comparisons. Conclusions: Cigarette smoking, like other forms of drug dependence, is characterized by rapid loss of subjective value for delayed outcomes, particularly for the drug of dependence. Never- and ex-smokers could discount similarly because cigarette smoking is associated with a reversible increase in discounting or due to selection bias. Major depressive disorder (MDD) is known to result in neurophysiological and neurocognitive changes that affect control of motor, linguistic, and cognitive functions. MDD's impact on these processes is reflected in an individual's communication via coupled mechanisms: vocal articulation, facial gesturing and choice of content to convey in a dialogue. In particular, MDD-induced neurophysiological changes are associated with a decline in dynamics and coordination of speech and facial motor control, while neurocognitive changes influence dialogue semantics. In this paper, biomarkers are derived from all of these modalities, drawing first from previously developed neurophysiologically-motivated speech and facial coordination and timing features. In addition, a novel indicator of lower vocal tract constriction in articulation is incorporated that relates to vocal projection. Semantic features are analyzed for subject avatar dialogue content using a sparse coded lexical embedding space, and for contextual clues related to the subject's present or past depression status. The features and depression classification system were developed for the 6th International Audio Video Emotion Challenge (AVEC), which provides data consisting of audio, video-based facial action units, and transcribed text of individuals communicating with the human-controlled avatar. A clinical Patient Health Questionnaire (PHQ) score and binary depression decision are provided for each participant. PHQ predictions were obtained by fusing outputs from a Gaussian staircase regressor for each feature set, with results on the development set of mean F1=0.81, RMSE=5.31, and MAE=3.34. These compare favorably to the challenge baseline development results of mean F1=0.73, RMSE=6.62, and MAE=5.52. On test set evaluation, our system obtained a mean F1=0.70, which is similar to the challenge baseline test result. Future work calls for consideration of joint feature analyses across modalities in an effort to detect neurological disorders based on the interplay of motor, linguistic, affective, and cognitive components of communication. Abstract The present study examines the link between alcohol consumption and personality, using the California Psychological Inventory in a large well-adjusted sample and tests four hypotheses, including one that states that persons who drink no alcohol at all are less well adjusted than persons who drink moderate amounts. The results confirm the hypotheses. Alcohol consumed correlates positively with sociability and extraversion, but negatively with conscientiousness and willingness to conform. The results also show, in a large sample and using a comprehensive personality inventory, that persons who drink no alcohol at all are a little more withdrawn, a little less ambitious, a little less generally well-organised and competent, than people who drink in moderation. False consensus, or the tendency to overestimate the extent to which others share one's own attitudes and behaviors, was investigated in a study of 348 university students classified as non-drug users, cannabis-only users, or amphetamine+ cannabis users. Participants estimated the prevalence of cannabis and amphetamine use among students. Cannabis and amphetamine users made significantly higher estimates of cannabis use among students than did nonusers, whereas amphetamine users gave significantly higher estimates of amphetamine use than nonusers and cannabis-only users. Correlations between estimates of use among friends and other students were significantly positive for both drugs. The results suggest that students are motivated to overestimate the commonality of their own position on drug use and that their estimates may also be influenced by selective exposure. Depression is a major cause of disability world-wide. The present paper reports on the results of our participation to the depression sub-challenge of the sixth Audio Visual Emotion Challenge (AVEC 2016), which was designed to compare feature modalities (audio, visual, interview transcript-based) in gender-based and gender-independent modes using a variety of classification algorithms. In our approach, both high and low level features were assessed in each modality. Audio features were extracted from the low-level descriptors provided by the challenge organizers. Several visual features were extracted and assessed including dynamic characteristics of facial elements (using Landmark Motion History Histograms and Landmark Motion Magnitude), global head motion, and eye blinks. These features were combined with statistically derived features from pre-extracted features (emotions, action units, gaze, and pose). Both speech rate and word-level semantic content were also evaluated. Classification results are reported using four different classification schemes: i) gender-based models for each individual modality, ii) the feature fusion model, ii) the decision fusion model, and iv) the posterior probability classification model. Proposed approaches outperforming the reference classification accuracy include the one utilizing statistical descriptors of low-level audio features. This approach achieved f1-scores of 0.59 for identifying depressed and 0.87 for identifying not-depressed individuals on the development set and 0.52 0.81, respectively for the test set. Abstract : INTERCORRELATIONS AMONG RATINGS ON 35 PERSONALITY TRAITS, SELECTED AS REPRESENTATIVE OF THE PERSONALITY DOMAIN, WERE OBTAINED FOR EIGHT SAMPLES. These samples differed in length of acquaintanceship from three days to more than a year; in kind of acquaintanceship from assessment programs in a military training course to a fraternity house situation; in type of subject from airmen with only a high school education to male and female undergraduate students to firstyear graduate students; and in type of rater from very naive persons to clinical psychologists and psychiatrists with years of experience in the evaluation of personality. Centroid or multiplegroup factors were extracted and rotated orthogonally to simple structure. For one study, an independent solution was obtained in which analytic rotations were accomplished on an IBM 650 computer using Kaiser's normal varimax criterion. Five fairly strong and recurrent factors emerged from each analysis, labeled as (1) Surgency, (2) Agreeableness, (3) Dependability, (4) Emotional Stability, and (5) Culture. Background and aimsRecent research has suggested that social networking site use can be addictive. Although extensive research has been carried out on potential addiction to social networking sites, such as Facebook, Twitter, YouTube, and Tinder, only one very small study has previously examined potential addiction to Instagram. Consequently, the objectives of this study were to examine the relationships between personality, self-liking, daily Internet use, and Instagram addiction, as well as exploring the mediating role of self-liking between personality and Instagram addiction using path analysis.MethodsA total of 752 university students completed a self-report survey, including the Instagram Addiction Scale (IAS), the Big Five Inventory (BFI), and the Self-Liking Scale.ResultsResults indicated that agreeableness, conscientiousness, and self-liking were negatively associated with Instagram addiction, whereas daily Internet use was positively associated with Instagram addiction. The results also showed t... Abstract Two studies were conducted in order to develop a multidimensional instrument of driving style. In Study 1, we developed a self-report scale assessing four broad domains of driving style—the multidimensional driving style inventory (MDSI). A factor analysis revealed eight main factors, each one representing a specific driving style—dissociative, anxious, risky, angry, high-velocity, distress reduction, patient, and careful. In addition, significant associations were found between the eight factors, on the one hand, and gender, age, driving history, and personality measures of self-esteem, need for control, impulsive sensation seeking, and extraversion, on the other. In Study 2, further associations were found between the eight driving style factors and measures of trait anxiety and neuroticism. The discussion focused on the validity and utility of a multidimensional conceptualization of driving style. Introduction The prediction of patient response to new pharmacotherapies for alcohol dependence has usually not been successful with standard statistical techniques. We hypothesized that fuzzy logic, a qualitative computational approach, could predict response to 40 mg day citalopram and 40 mg day citalopram with a brief psychosocial intervention in alcohol-dependent patients. Methods Two data sets were formed with patients from our studies who received 40 mg day citalopram alone (n = 34) or 40 mg day citalopram and a brief psychosocial intervention (n = 28). The output variable, “response,” was the percentage decrease in alcohol intake from baseline. Input variables included age, gender, baseline alcohol intake, and levels of anxiety, depression, alcohol dependence, and alcohol-related problems. Results A fuzzy rulebase was created from the data of 26 randomly chosen patients who received 40 mg day citalopram and was used to predict the responses of the remaining eight patients. Eight rules related response with depression, anxiety, alcohol dependence, alcohol-related problems, age, and baseline alcohol intake. The average magnitude of the error in the predictions (RMSE) was 2.6 with a bias (ME) of 0.6. Predicted and actual response correlated (r = 0.99; p < 0.001). A fuzzy rulebase was created from the data of 28 randomly chosen patients who received 40 mg day citalopram and a brief psychosocial intervention and was used to predict the responses of the remaining five patients. Six rules related response with age, anxiety, depression, alcohol dependence, and baseline alcohol intake with good predictive performance (RMSE = 6.4; ME = −1.5; r = 0.96; p < 0.01). Conclusions This study indicates that fuzzy logic modeling can predict response to pharmacotherapies for alcohol dependence. Clinical Pharmacology & Therapeutics (1997) 62, 209–224; doi: In the television series The Wire, addicts Bubbles and Johnny regularly engage in bizarre and elaborate schemes to obtain drugs, ranging from robbing an ambulance to stealing drugs by lowering a fishing line from a rooftop. That these fictional crimes can be both so meticulously planned and yet focused on such narrow, shortsighted goals highlights a gap in our understanding of how the real brain deploys deliberative vs. automatic mechanisms to make decisions. On a standard account, people can deliberatively evaluate the consequences of candidate actions, which gives us our flexibility to dream up novel plans. Alternatively, the brain can crystallize repeatedly successful behaviors into habits: learned reflexes that free up resources by executing the behaviors automatically (although at the expense of inflexibility and, it is believed, underpinning pathological compulsions). As with most dichotomies, the problem with this view is that the world is not so black and white. Much as the drug-seeking behavior of addicts seems not to fit into either category, for healthy behaviors also, neither of these two sorts of decision making is very practical on its own. In PNAS, Cushman and Morris suggest a hybrid of these mechanisms, and show behavioral evidence that humans use it to plan actions (1). Abstract Purpose Disordered eating behavior—dieting, laxative use, fasting, binge eating—is common in college-aged women (11 –20 ). A documented increase in the number of young women experiencing eating psychopathology has been blamed on the rise of engagement with social media sites such as Facebook. We predicted that college-aged women's Facebook intensity (e.g., the amount of time spent on Facebook, number of Facebook friends, and integration of Facebook into daily life), online physical appearance comparison (i.e., comparing one's appearance to others' on social media), and online "fat talk" (i.e., talking negatively about one's body) would be positively associated with their disordered eating behavior. Methods In an online survey, 128 college-aged women (81.3 Caucasian, 6.7 Asian, 9.0 African-American, and 3.0 Other) completed items, which measured their disordered eating, Facebook intensity, online physical appearance comparison, online fat talk, body mass index, depression, anxiety, perfectionism, impulsivity, and self-efficacy. Results In regression analyses, Facebook intensity, online physical appearance comparison, and online fat talk were significantly and uniquely associated with disordered eating and explained a large percentage of the variance in disordered eating (60 ) in conjunction with covariates. However, greater Facebook intensity was associated with decreased disordered eating behavior, whereas both online physical appearance comparison and online fat talk were associated with greater disordered eating. Conclusions College-aged women who endorsed greater Facebook intensity were less likely to struggle with disordered eating when online physical appearance comparison was accounted for statistically. Facebook intensity may carry both risks and benefits for disordered eating. Abstract Causal effect modeling with naturalistic rather than experimental data is challenging. In observational studies participants in different treatment conditions may also differ on pretreatment characteristics that influence outcomes. Propensity score methods can theoretically eliminate these confounds for all observed covariates, but accurate estimation of propensity scores is impeded by large numbers of covariates, uncertain functional forms for their associations with treatment selection, and other problems. This article demonstrates that boosting, a modern statistical technique, can overcome many of these obstacles. The authors illustrate this approach with a study of adolescent probationers in substance abuse treatment programs. Propensity score weights estimated using boosting eliminate most pretreatment group differences and substantially alter the apparent relative effects of adolescent substance abuse treatment. Adolescents are developmentally sensitive to pathways that influence alcohol and other drug (AOD) use. In the absence of guidance, their routine engagement with social media may add a further layer of risk. There are several potential mechanisms for social media use to influence AOD risk, including exposure to peer portrayals of AOD use, socially amplified advertising, misinformation, and predatory marketing against a backdrop of lax regulatory systems and privacy controls. Here the authors summarize the influences of the social media world and suggest how pediatricians in everyday practice can alert youth and their parents to these risks to foster conversation, awareness, and harm reduction.