Multiple addictive behaviors in young adults: Student norms for the Shorter PROMIS Questionnaire (original) (raw)
Compulsive use of alcohol among college students
Psychiatry Research, 2013
Among college students alcohol consumption is associated with other high-risk behaviors that can lead to short-and long-term negative health consequences. Identification of college students consuming alcohol who are at high risk for problems may have important public health implications. This study examines the ability of the CHQ compulsive use of alcohol item to detect high-risk behaviors relative to other screening measures and its association with different dimensions of compulsive drinking. Three hundred thirty-two college students completed measures on compulsive drinking and hazardous behaviors. Results showed that among male students the CHQ compulsive use of alcohol item was not sensitive to detect hazardous alcohol consumption but co-occurred with the use of illicit drugs. Among female students it was sensitive to detect heavy drinking but not alcohol or drug problems. Among college students compulsive use of alcohol corresponds to an urge to consume alcohol that may be associated with use of illicit drugs in male students, with heavy drinking in female students and with substance use problems. This study suggest that the CHQ compulsive use of alcohol item should not be used as a standalone screening for alcohol or drug problems but it could be considered a marker for at-risk behaviors.
International Journal of Mental Health and Addiction
This study deals with the uncertainty in defining behavioral addictions (BAs). BAs are characterized by specific compulsive behaviors, regardless of potential negative consequences. However, to differentiate a behavior from a leisure activity to an addictive one is still an object of debate in the literature. Accordingly, this study aimed to assess the psychometric properties of the Behavioral Addictions Questionnaire (BAQ) as a possible screening tool for multiple BAs (i.e., shopping, food addiction, gambling, sex, work, exercise, Internet, videogames, and smartphone). BAQ aims to give a dimensional and quantitative assessment of addictive behaviors in a continuum, including both the adaptive and maladaptive features of the behaviors. Five hundred and seventy-six healthy adults (age range: 18–88) participated in the study, completing a survey including the BAQ questionnaire. Considering both exploratory and confirmatory factor analyses, statistical examination suggested good psycho...
The relationships between behavioral addictions and the five-factor model of personality
Journal of Behavioral Addictions, 2013
Aims: Although relationships between addiction and personality have previously been explored, no study has ever simultaneously investigated the interrelationships between several behavioral addictions, and related these to the main dimensions of the five-factor model of personality. Methods: In this study, 218 university students completed questionnaires assessing seven different behavioral addictions (i.e., Facebook addiction, video game addiction, Internet addiction, exercise addiction, mobile phone addiction, compulsive buying, and study addiction) as well as an instrument assessing the main dimensions of the five-factor model of personality. Results: Of the 21 bivariate intercorrelations between the seven behavioral addictions, all were positive (and nine significantly). The results also showed that (i) Neuroticism was positively associated with Internet addiction, exercise addiction, compulsive buying, and study addiction, (ii) Extroversion was positively associated with Facebook addiction, exercise addiction, mobile phone addiction, and compulsive buying, (iii) Openness to experience was negatively associated with Facebook addiction and mobile phone addiction, (iv) Agreeableness was negatively associated with Internet addiction, exercise addiction, mobile phone addiction, and compulsive buying, and (v) Conscientiousness was negatively associated with Facebook addiction, video game addiction, Internet addiction, and compulsive buying and positively associated with exercise addiction and study addiction. Conclusions: The positive associations between the seven behavioral addictions suggest one or several underlying pathological factors. Hierarchical multiple regressions showed that personality traits explained between 6% and 17% of the variance in the seven behavioral addictions, suggesting that personality to a varying degree explains scores on measures of addictive behaviors.
Conceptualizing addiction has been a matter of intense debate for decades. For many, addiction theory has applied only to alcohol, tobacco or drug ingestion, with most definitions concentrated on these substances. Despite such focus, there is increasing empirical evidence to illustrate a wider number of behaviours are potentially addictive such as gambling, overeating, sex love, exercise, videogame playing/ pinball internet use, buying/shopping and work (see Sussman, Lisha, & Griffiths, 2011). Such diversity has led to new, broader definitions of what constitutes an addictive behaviour.
What is addiction? Age-related differences in the meaning of addiction
Drug and Alcohol Dependence, 2007
In a sample of families from a midwestern community study of cigarette smoking, we examined adolescents' and adults' definitions of "addiction", and related these definitions to their perceived addictiveness of cigarette smoking. Both adolescents and adults viewed addiction as multi-faceted, including both appetitive aspects and compulsive aspects. However, for adolescents, the two dimensions were equally important to the overall meaning of addiction, whereas for adults, the compulsive dimension was more important than was the appetitive dimension. The two dimensions of addiction were related to the perceived addictiveness of smoking, but differently for adolescents and adults. For adolescents, the appetitive dimension was a significant predictor whereas, for adults, the compulsive dimension was significant (and appetitive scores were predictive only at high levels of endorsement of the compulsive factor). These findings have potential implications for prevention programs for adolescents. Adolescents may perceive messages about "addiction" as communicating that the behavior in question has appetitive value in addition to a potential for inducing loss of control, and this may weaken the effectiveness of these messages.
Prevalence and characteristics of addictive behaviors in a community sample: A latent class analysis
While addictions to substances such as alcohol, tobacco, and other drugs have been extensively investigated, interest has been growing in potential non-substance-related addictive behaviors (e.g., excessive gambling, buying or playing video games). In the current study, we sought to determine the prevalence and characteristics of a wide range of addictive behaviors in a general population sample and to identify reliable subgroups of individuals displaying addictive behaviors. Seven hundred seventy participants completed an online survey. The survey screened for the presence and characteristics of the main recognized substance and behavioral addictions (alcohol, tobacco, cannabis, other drugs, gambling, compulsive shopping, intensive exercise, Internet and mobile phone overuse, intensive work involvement, and overeating) in a three-month period. Key aspects of addiction were measured for each reported behavior, including negative outcomes, emotional triggers (positive and negative emotional contexts), search for stimulation or pleasure, loss of control, and cognitive salience. Latent class analysis allowed us to identify three theoretically and clinically relevant subgroups of individuals. The first class groups problematic users, i.e., addiction-prone individuals. The second class groups at-risk users who frequently engage in potentially addictive behaviors to regulate emotional states (especially overinvolvement in common behaviors such as eating, working, or buying). The third class groups individuals who are not prone to addictive behaviors. The existence of different groups in the population sheds new light on the distinction between problematic and non-problematic addiction-like behaviors.
CNS spectrums, 2006
Taking into account the importance of act prevention on the development of addictions, we assessed the presence of multiple addictions in an adolescent high-school population, also assessing the prevalence of Internet abuse and the impact on disability. Adolescence seems to be a critical period of addiction vulnerability, based on social but also neurobiological factors. The earlier onset of behavioral/substance dependence seems to predict greater addiction severity, morbidity, and multiple addictive disorders. Data were collected from a sample of 275 students in Florence, Italy, high schools through surveys distributed in classes. The sample had an average age of 16.67+/-1.85 years (52.4% males, 47.6% females). To assess multiple addiction we used the 16 subscales of the Shorter PROMIS Questionnaire, to assess Internet addiction prevalence we used the Internet Addiction Scale, and to quantify disability symptoms, we used the Sheehan Disability Scale. Caffeine abuse, sex, relationsh...
Addiction behavior practiced by the Adolescent: An observational cross-sectional study
Indian journal of forensic and community medicine, 2021
Background: As with tobacco use, alcohol use shows a monotonic increase during adolescents and young adulthood, particularly during the transition out of high school and excessive alcohol consumption can lead to lifelong problems and chronic diseases. Objective: To study the addiction behavior practiced by the Adolescent. Study Design: An observational cross-sectional study. Setting: The present study was carried out in Department of Community Medicine, Santosh Medical College, Ghaziabad & Urban area of district Ghaziabad. 750 Adolescents aged 10 to 19 years studying in the selected schools of urban Ghaziabad were included for the study. The period of study was from November 2011 to October 2012. Results: Proportion was higher (64.8%) in male adolescents in comparison to female adolescents (33.9%). The prevalence of drugs, smoking, tobacco chewing and drinking among adolescents was found to be 2.5%, 21.7%, 9.6% and 15.5% respectively. Among the adolescents, who used tobacco chewing, 61.1% of them were ever users and 38.9% were current users. The students who used smoking, 50.3% of them were ever users and 49.7% were current users. Students who used addicting substance, their encouragement to start addiction was maximum from peers (33.0%). About three-fourth (75.4%) of adolescents who used addicting substance had knowledge of health hazards of addicting substances. Conclusion: The study evokes an urgent need to stimulate an action to identify those at risk and those who need treatment and prevention of progression of the health risk behaviors, among the adolescents.
Dusunen Adam: The Journal of Psychiatry and Neurological Sciences
Prevalence of risky behaviors and relationship of risky behaviors with substance use among university students Objective: This study aims to evaluate the prevalence of risky behaviors, frequently encountered in young adulthood, and the relationship between such behaviors and substance use in the university population. Method: This cross sectional, web-based, self-report study was carried out in a state university with 53,003 students. The power analysis was conducted according to the lowest prevalence (0.01%-0.6%) of substance use in universities in Turkey. A sample of 3,184 people was found to be sufficient for the research. The data of 2,973 individuals who completed the Addiction Profile Index was evaluated. Frequency tests, Pearson chi-square and logistic regression were used in the statistical analysis. Results: As participants 1,629 (54.8%) females and 1,344 (45.2%) males were included in the study. Suicidal plans or attempts and self-harming behaviors were significantly more prevalent among female students; carrying a weapon (penknife/knife/gun), engaging in physical fights, sustaining injuries in physical fights, early sexual relation experiences, condom usage, cigarette, alcohol, energy drink and substance consumption were significantly more prevalent among male students (p<0.001). Frequent suicidal plans or attempts (11.3 times) and early sexual experiences, before the age of 15 (16.6 times) were found to be riskier behaviors with regard to substance use; as the consumption of cigarettes, alcohol and energy drink increased, so did the risk of substance use. Conclusion: Gender is a distinctive characteristic with regard to risky behaviors among young people. The relationship between risky behaviors and substance use suggests that one risky behavior may lead to another. As such, it is necessary to evaluate the substance use among young people with risky behaviors and to examine other risky behaviors which accompany the substance use problems.
Aims: Although relationships between addiction and personality have previously been explored, no study has ever simultaneously investigated the interrelationships between several behavioral addictions, and related these to the main dimensions of five-factor model of personality. Method: In this study, 218 university students completed questionnaires assessing seven different behavioral addictions (i.e., Facebook addiction, video game addiction, Internet addiction, exercise addiction, mobile phone addiction, compulsive buying, and study addiction) as well as an instrument assessing the main dimension of the five-factor model of personality. Results: Of the 21 bivariate intercorrelations between the seven behavioral addictions, all were positive (and nine significantly). The results also showed that (i) Neuroticism was positively associated with Internet addiction, exercise addiction, compulsive buying and study addiction, (ii) Extroversion was positively associated with Facebook addiction, exercise addiction, mobile phone addiction, and compulsive buying, (iii) Openness to experience was negatively associated with Facebook addiction and mobile phone addiction, (iv) Agreeableness was negatively associated with Internet addiction, exercise addiction, mobile phone addiction, and compulsive buying, and (v) Conscientiousness was negatively associated with Facebook addiction, video game addiction, Internet addiction, and compulsive buying and positively associated with exercise addiction and study addiction. Conclusions: The positive associations between the seven behavioral addictions suggest one or several underlying pathological factors. Hierarchical multiple regressions showed that personality traits explained between 6% and 17% of the variance in the seven behavioural addictions, suggesting that personality to a varying degree explain scores on measures of addictive behaviors.