The Bergen Facebook Addiction Scale (BFAS), initially a pool of 18 items, three reflecting each of the six core elements of addiction (salience, mood modification, tolerance, withdrawal, conflict, and relapse), was constructed and administered to 423 students together with several other standardized self-report scales (Addictive Tendencies Scale, Online Sociability Scale, Facebook Attitude Scale, NEO–FFI, BIS/BAS scales, and Sleep questions). That item within each of the six addiction elements with the highest corrected item-total correlation was retained in the final scale. The factor structure of the scale was good (RMSEA = .046, CFI = .99) and coefficient alpha was .83. The 3-week test-retest reliability coefficient was .82. The scores converged with scores for other scales of Facebook activity. Also, they were positively related to Neuroticism and Extraversion, and negatively related to Conscientiousness. High scores on the new scale were associated with delayed bedtimes and rising times.

Pallesen, S. (2016). The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study. Psychology of Addictive Behaviors

Social media has become an increasingly popular leisure activity over the last decade.Although most people's social media use is non-problematic, a small number of users appear to engage in social media excessively and/or compulsively. The main objective of this study was to examine the associations between addictive use of social media, narcissism, and selfesteem. A cross-sectional convenient sample of 23,532 Norwegians (M age =35.8 years;range=16-88 years) completed an open web-based survey including the Bergen Social Media Addiction Scale (BSMAS), the Narcissistic Personality Inventory-16, and the Rosenberg SelfEsteem Scale. Results demonstrated that lower age, being female, being single, being a student, lower education, lower income, lower self-esteem, and narcissism were associated with higher scores on the BSMAS, explaining a total of 17.5% of the variance. Although most effect sizes were relatively modest, the findings supported the notion of addictive social media use reflecting a need to feed the ego (i.e., narcissistic personality traits) and an attempt to inhibit a negative self-concept (i.e., basic cognitions). The results were also consistent with demographic predictions and associations taken from central theories concerning "addiction", indicating that females may tend to develop more addictive use of activities involving social interaction than males. However, the cross-sectional study design makes inferences about directionality impossible.Keywords: Behavioral addiction; Online social networking addiction; Narcissism; Selfesteem; Personality; Cognition Addictive use of social media, narcissism, and self-esteem 3

A nationwide survey was conducted to investigate the prevalence of video game addiction and problematic video game use and their association with physical and mental health. An initial sample comprising 2,500 individuals was randomly selected from the Norwegian National Registry. A total of 816 (34.0 percent) individuals completed and returned the questionnaire. The majority (56.3 percent) of respondents used video games on a regular basis. The prevalence of video game addiction was estimated to be 0.6 percent, with problematic use of video games reported by 4.1 percent of the sample. Gender (male) and age group (young) were strong predictors for problematic use of video games. A higher proportion of high frequency compared with low frequency players preferred massively multiplayer online role-playing games, although the majority of high frequency players preferred other game types. Problematic use of video games was associated with lower scores on life satisfaction and with elevated levels of anxiety and depression. Video game use was not associated with reported amount of physical exercise.

ObjectivesAdolescents spend increasingly more time on electronic devices, and sleep deficiency rising in adolescents constitutes a major public health concern. The aim of the present study was to investigate daytime screen use and use of electronic devices before bedtime in relation to sleep.DesignA large cross-sectional population-based survey study from 2012, the youth@hordaland study, in Hordaland County in Norway.SettingCross-sectional general community-based study.Participants9846 adolescents from three age cohorts aged 16–19. The main independent variables were type and frequency of electronic devices at bedtime and hours of screen-time during leisure time.OutcomesSleep variables calculated based on self-report including bedtime, rise time, time in bed, sleep duration, sleep onset latency and wake after sleep onset.ResultsAdolescents spent a large amount of time during the day and at bedtime using electronic devices. Daytime and bedtime use of electronic devices were both related to sleep measures, with an increased risk of short sleep duration, long sleep onset latency and increased sleep deficiency. A dose–response relationship emerged between sleep duration and use of electronic devices, exemplified by the association between PC use and risk of less than 5 h of sleep (OR=2.70, 95% CI 2.14 to 3.39), and comparable lower odds for 7–8 h of sleep (OR=1.64, 95% CI 1.38 to 1.96).ConclusionsUse of electronic devices is frequent in adolescence, during the day as well as at bedtime. The results demonstrate a negative relation between use of technology and sleep, suggesting that recommendations on healthy media use could include restrictions on electronic devices.

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.

Research into excessive work has gained increasing attention over the last 20 years. Terms such as "workaholism,""work addiction" and "excessive work" have been used interchangeably. Given the increase in empirical research, this study presents the development of the Bergen Work Addiction Scale (BWAS), a new psychometrically validated scale for the assessment of work addiction. A pool of 14 items, with two reflecting each of seven core elements of addiction (i.e., salience, mood modification, tolerance, withdrawal, conflict, relapse, and problems) was initially constructed. The items were then administered to two samples, one recruited by a web survey following a television broadcast about workaholism (n = 11,769) and one comprising participants in the second wave of a longitudinal internet-based survey about working life (n = 368). The items with the highest corrected item-total correlation from within each of the seven addiction elements were retained in the final scale. The assumed one-factor solution of the refined seven-item scale was acceptable (root mean square error of approximation = 0.077, Comparative Fit Index = 0.96, Tucker-Lewis Index = 0.95) and the internal reliability of the two samples were 0.84 and 0.80, respectively. The scores of the BWAS converged with scores on other workaholism scales, except for a Work Enjoyment subscale. A suggested cut-off for categorization of workaholics showed good discriminative ability in terms of working hours, leadership position, and subjective health complaints. It is concluded that the BWAS has good psychometric properties.

Nonmedical AAS use is a serious widespread public health problem.