Ståle Pallesen

Development of a Facebook Addiction Scale.

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.

The association between sleep duration, body mass index and metabolic measures in the Hordaland Health Study.

Several studies show that short self‐reported sleep duration is associated with elevated body mass index (BMI). Short sleep duration may change appetite hormones, but whether this also influences metabolic measures like cholesterol and triglycerides is less clear. Furthermore, obesity is linked to increases in blood pressure, and recently, short sleep duration has been shown to be an independent risk factor for hypertension. This is a population‐based cross‐sectional study (The Hordaland Health Study). A subgroup of 8860 subjects, aged 40–45 years, answered a sleep questionnaire. Body weight, height and blood pressure were measured, and non‐fasting blood samples were collected and analyzed for total cholesterol, HDL‐cholesterol and triglycerides. Sleep duration was divided into the following subgroups: <5, 5–5.99, 6–6.99, 7–7.99, 8–8.99 and ≥9 h. The results show that short sleep duration was associated with elevated BMI and increased prevalence of obesity. Similar to BMI, levels of cholesterol, triglycerides, systolic and diastolic blood pressure were higher in subjects with short sleep duration. This co‐variation seemed to be attributed to variables like gender, smoking and BMI. In conclusion, our study confirms a clear association between short sleep duration and elevated BMI and obesity. Furthermore, levels of total cholesterol, HDL‐cholesterol, triglycerides and blood pressure were associated with sleep duration.

Individual differences in tolerance to shift work – A systematic review

Shift work tolerance is a term describing the ability to adapt to shift work without adverse consequences. In this paper we systematically review literature published investigating the relation between individual differences such as age, gender, personality, morningness/eveningness as well as biological variables and different measures of shift work tolerance from 1998 till 2009. A total of 60 articles were included in this review, of which ten studies were classified as longitudinal, while the rest were classified as cross-sectional. Overall, the studies indicate that young age, male gender, low scores on morningness, high scores on flexibility and low scores on languidity, low scores on neuroticism, high scores on extraversion and internal locus of control and some genetic dispositions are related to higher shift work tolerance. More longitudinal studies, especially concerning personality, are needed to make conclusions about the predictive power of individual differences for shift work tolerance.

Problematic Video Game Use: Estimated Prevalence and Associations with Mental and Physical Health

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.

A new scale for measuring insomnia: the Bergen Insomnia Scale.

A new scale for the measurement of insomnia, the Bergen Insomnia Scale, was constructed on the basis of current formal and clinical diagnostic criteria for insomnia. There are six items, of which the first three pertain to sleep onset, maintenance, and early morning wakening insomnia, respectively. The last three items refer to not feeling adequately rested, experiencing daytime impairment, and being dissatisfied with current sleep. This scale was validated in three samples, 320 students, 2,645 community persons, and 225 patients. Cronbach alphas in the three samples were .79, .87, and .80, respectively. The 2-wk. test-retest reliability for students was .77. In the student and the patient samples, a two-factor solution was found, nocturnal symptoms and daytime symptoms, but in the community sample, a one-factor solution was found. The Bergen Insomnia Scale discriminated well between the patient sample and the other two. In all three, values of convergent and discriminative validity in relation to other self-report measures were good, as well as in relation to polysomnographic data for patients. It is concluded that the Bergen Insomnia Scale has good psychometric properties. It is one of very few insomnia scales which provide normative data for comparisons and which has been validated against subjective as well as polysomnographic data.

Sleep and use of electronic devices in adolescence: results from a large population-based study

Objectives Adolescents 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. Design A large cross-sectional population-based survey study from 2012, the youth@hordaland study, in Hordaland County in Norway. Setting Cross-sectional general community-based study. Participants 9846 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. Outcomes Sleep variables calculated based on self-report including bedtime, rise time, time in bed, sleep duration, sleep onset latency and wake after sleep onset. Results Adolescents 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). Conclusions Use 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.

The relationships between behavioral addictions and the five-factor model of personality

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.

Shift Work Disorder in Nurses – Assessment, Prevalence and Related Health Problems

Background This study investigates the prevalence of symptoms of shift work disorder in a sample of nurses, and its association to individual, health and work variables. Methodology/Principal Findings We investigated three different shift work disorder assessment procedures all based on current diagnostic criteria and employing symptom based questions. Crude and adjusted logistic regression analyses were performed with symptoms of shift work disorder as the dependent variable. Participants (n = 1968) reported age, gender, work schedule, commuting time, weekly work hours, children in household, number of nights and number of shifts separated by less than 11 hours worked the last year, use of bright light therapy, melatonin and sleep medication, and completed the Bergen Insomnia Scale, Epworth Sleepiness Scale, Global Sleep Assessment Questionnaire, Diurnal Scale, Revised Circadian Type Inventory, Dispositional Resilience (Hardiness) Scale – Revised, Fatigue Questionnaire, questions about alcohol and caffeine consumption, as well as the Hospital Anxiety and Depression Scale. Conclusions/Significance Prevalence rates of symptoms of shift work disorder varied from 32.4–37.6% depending on the assessment method and from 4.8–44.3% depending on the work schedule. Associations were found between symptoms of shift work disorder and age, gender, circadian type, night work, number of shifts separated by less than 11 hours and number of nights worked the last year, insomnia and anxiety. The different assessment procedures yielded similar results (prevalence and logistic regression analyses). The prevalence of symptoms indicative of shift work disorder was high. We argue that three symptom-based questions used in the present study adequately assess shift work disorder in epidemiological studies.

The bidirectional association between depression and insomnia: the HUNT study.

Objective Depression and insomnia are closely linked, yet our understanding of their prospective relationships remains limited. The aim of the current study was to investigate the directionality of association between depression and insomnia. Methods Data were collected from a prospective population-based study comprising the most recent waves of the Nord-Trøndelag Health Study (HUNT) (the HUNT2 in 1995–1997 and the HUNT3 in 2006–2008). A total of 24,715 persons provided valid responses on the relevant questionnaires from both surveys. Study outcomes were onset of depression or insomnia at HUNT3 in persons not reporting the other disorder in HUNT2. Results Both insomnia and depression significantly predicted the onset of the other disorder. Participants who did not have depression in HUNT2 but who had insomnia in both HUNT2 and HUNT3 had an odds ratio (OR) of 6.2 of developing depression at HUNT3. Participants who did not have insomnia in HUNT2 but who had depression in both HUNT2 and HUNT3 had an OR of 6.7 of developing insomnia at HUNT3. ORs were only slightly attenuated when adjusting for potential confounding factors. Conclusions The results support a bidirectional relationship between insomnia and depression. This finding stands in contrast to the previous studies, which have mainly focused on insomnia as a risk factor for the onset of depression.

Sleep patterns and insomnia among adolescents: a population-based study.

The aim of the current study was to examine sleep patterns and rates of insomnia in a population‐based study of adolescents aged 16–19 years. Gender differences in sleep patterns and insomnia, as well as a comparison of insomnia rates according to DSM‐IV, DSM‐V and quantitative criteria for insomnia (Behav. Res. Ther., 41, 2003, 427), were explored. We used a large population‐based study in Hordaland county in Norway, conducted in 2012. The sample included 10 220 adolescents aged 16–18 years (54% girls). Self‐reported sleep measurements included bedtime, rise time, time in bed, sleep duration, sleep efficiency, sleep onset latency, wake after sleep onset, rate and frequency and duration of difficulties initiating and maintaining sleep and rate and frequency of tiredness and sleepiness. The adolescents reported short sleep duration on weekdays (mean 6:25 hours), resulting in a sleep deficiency of about 2 h. A majority of the adolescents (65%) reported sleep onset latency exceeding 30 min. Girls reported longer sleep onset latency and a higher rate of insomnia than boys, while boys reported later bedtimes and a larger weekday–weekend discrepancy on several sleep parameters. Insomnia prevalence rates ranged from a total prevalence of 23.8 (DSM‐IV criteria), 18.5 (DSM‐V criteria) and 13.6% (quantitative criteria for insomnia). We conclude that short sleep duration, long sleep onset latency and insomnia were prevalent in adolescents. This warrants attention as a public health concern in this age group.