Why do you dance? Development of the Dance Motivation Inventory (DMI)

Dancing is a popular form of physical exercise and studies have show that dancing can decrease anxiety, increase self-esteem, and improve psychological wellbeing. The aim of the current study was to explore the motivational basis of recreational social dancing and develop a new psychometric instrument to assess dancing motivation. The sample comprised 447 salsa and/or ballroom dancers (68% female; mean age 32.8 years) who completed an online survey. Eight motivational factors were identified via exploratory factor analysis and comprise a new Dance Motivation Inventory: Fitness, Mood Enhancement, Intimacy, Socialising, Trance, Mastery, Self-confidence and Escapism. Mood Enhancement was the strongest motivational factor for both males and females, although motives differed according to gender. Dancing intensity was predicted by three motivational factors: Mood Enhancement, Socialising, and Escapism. The eight dimensions identified cover possible motives for social recreational dancing, and the DMI proved to be a suitable measurement tool to assess these motives. The explored motives such as Mood Enhancement, Socialising and Escapism appear to be similar to those identified in other forms of behaviour such as drinking alcohol, exercise, gambling, and gaming

Compulsive buying gradually increased during the first six months of the Covid-19 outbreak

Background and aims: The current Covid-19 situation offers a natural experiment to explore the effect of a chronic stressor on compulsive buying tendencies over an extended period of time. Design: Survey method of sampling every three days a new cohort during the first six months of the Covid-19 pandemic (March-October 2020) in the United States. Participants: Total (clean) sample of N = 1,430 (39.3% female, mean age = 36.4 years). Measurements: Online and offline compulsive buying separately, distress, economic position, income and age were assessed. Findings: Both online and offline compulsive buying increased during the data collection period ( τ = 0.24, τ = 0.22, respectively, both P < 0.001). Individuals with self-reported high economic position (EP) reported the highest tendency for compulsive buying throughout the entire time frame, although the increase in compulsive buying tendencies over time was the most pronounced among the economically less privileged. Online compulsive buying increased after the CARES Act (first stimulus package) by an effect size of d = 0.33. When entered into a regression model, EP had the strongest effect on compulsive buying after accounting for the effect of distress, income and age. The high-EP group reported the strongest correlation between distress and compulsive buying (r = 0.67, P < 0.001, 95% CI: 0.57–0.76). Conclusions: Compulsive buying tendency gradually increased during the first six months of the Covid-19 pandemic especially after the CARES Act.Peer Reviewe

Negativity in delayed affective recall is related to the borderline personality trait

The present study assessed selected factors that contribute to the recollection of emotional memories over time. Participants with high-trait borderline personality disorder (BPD) watched a randomly selected positive, negative, or neutral character in a video clip (stimulus) and were asked to recall the content immediately, then 2, 4, and 6 days later. In the final sample (N = 558, average age: 33 years, 65% female), general impression had the strongest effect on recall after accounting for the effect of current mood, extremity of the responses, and level of BPD, regardless of stimulus valence. The level of BPD had an effect only when negative evaluative wording (e.g., "guilty") was used. In conclusion, people with high-trait BPD tend to remember negative stimuli more negatively over time (unlike neutral or positive stimuli), and this effect is mostly related to general impression.Peer Reviewe

Measuring compulsive buying behaviour: Psychometric validity of three different scales and prevalence in the general population and in shopping centres

Due to the problems of measurement and the lack of nationally representative data, the extent of compulsive buying behaviour (CBB) is relatively unknown. Methods: The validity of three different instruments was tested: Edwards Compulsive Buying Scale (ECBS; Edwards, 1993), Questionnaire About Buying Behavior (QABB; Lejoyeux & Adès, 1994) and Richmond Compulsive Buying Scale (RCBS; Ridgway, et. al., 2008) using two independent samples. One was nationally representative of the Hungarian population (N=2710) while the other comprised shopping mall customers (N=1447). Results: A new, four-factor solution for the ECBS was developed (ECBS-R), and confirmed the other two measures. Additionally, cut-off scores were defined for all measures. Results showed that the prevalence of CBB is 1.85% (with QABB) in the general population but significantly higher in shopping mall customers (8.7% with ECBS-R, 13.3% with QABB and 2.5% with RCBS-R). Conclusions: Due to the diversity of content, each measure identifies a somewhat different CBB group

Prevalence of problematic internet use in Slovenia

BACKGROUND: Internet use is an integral part of our everyday activities; however, Internet use may become problematic and harmful in a minority of cases. The majority of reported prevalence rates of problematic Internet use refer to adolescent samples, whereas epidemiological studies on representative adult populations are lacking. This study aimed to reveal the prevalence and characteristics of problematic Internet use in Slovenia. METHODS: Problematic Internet Use Questionnaire (PIUQ) was included in European Health Interview Study (EHIS) on representative Slovenian sample. The frequency of Internet use and problematic Internet use were both assessed. RESULTS: 59.9% of Slovenian adult population uses the Internet daily, and 3.1% are at risk of becoming problematic Internet users, 11% in the age group from 20 to 24 years. Those being at risk for becoming problematic Internet users are younger (mean age 31.3 vs. 48.3 for non-problematic users), more likely to be males (3.6% of males, whereas 2.6% of females are affected), students (12.0%), unemployed (6.3%) or unable to work (8.7%), single (6.5%), with high education (4.5%). Regression analysis revealed that the strongest predictor of being at risk for problematic Internet use is age (ß=-0.338, p<0.001); followed by high educational level (ß=0.145; p<0.001) and student status (ß=0.136; p<0.001). CONCLUSION: 3.1% of Slovenian adult population are at risk of becoming problematic Internet users, whereas 3 out of 20 Slovenian adolescents aged from 18 to 19 years are at risk (14.6%). Prevention programs and treatment for those affected are paramount, especially for the young generation

The Inventory of Personality Organization: A valid instrument to detect the severity of personality dysfunction

Background and aims In the eleventh revision of the International Classification of Diseases (ICD-11), the severity of personality dysfunction became the central dimension of personality disorder’s (PDs) definition, besides the trait domain qualifiers. Personality functioning, also known as personality organization (PO), is becoming an increasingly important concept in administering, predicting, and measuring severity and nature of personality disturbance. Otto Kernberg and his team developed several tools to measure personality impairment. The Inventory of Personality Organization (IPO) is a self-report rating scale for the measurement of PO. Aim of this study was to identify severity groups according to the level of PO and to explore their validity. Materials and methods A clinical sample of 118 patients was recruited from a 4-weeks in-patient cognitive psychotherapy program. Beside the IPO, Structured Clinical Interview for the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders, (DSM-IV.) Axis I and II, Symptom Check List-90 (SCL-90), State-Trait Anger Expression Inventory and Dissociative Experience scale (DES). Two types of analyses were conducted: a person-centered (latent profile) analysis and various variable-centered tests to confirm the factor structure of IPO and calculate group differences. Results The three-factor (CFI = 0.990, TLI = 0.990, RMSEA = 0.022, SRMR = 0.089) and the five-factor (CFI = 0.995, TLI = 0.995, RMSEA = 0.014, SRMR = 0.090) models of the IPO was supported. Latent class analysis identified three subgroups of PO: “Well-integrated,” “Moderately integrated,” and “Disintegrated” classes. There were no significant differences between the three classes in the number of Axis 1 diagnoses (p = 0.354; η2 = 0.01). Group differences in the number of PDs, the number of PD symptoms as well as in the presence of borderline and depressive PD were significant (all p < 0.001; V = 0.35–0.42; η2 = 0.15–0.26). Persons with more severe PO problem level had higher rates of psychopathological symptoms, state and trait anger, and dissociative characteristics (all p < 0.001; η2 = 0.13–0.36). Conclusion The IPO can be an appropriate instrument to measure the severity of personality disorganization and to classify participants along a continuum of severity in this regard. Our results present further evidence that the severity of personality dysfunction, the central dimension of the ICD-11 and the Alternative Model for PDs is detectable with an instrument, the IPO, that was initially developed to detect the disturbances in PO.Peer Reviewe

Relating Compulsivity and Impulsivity With Severity of Behavioral Addictions: A Dynamic Interpretation of Large-Scale Cross-Sectional Findings

Background and Aim: Impulsivity and compulsivity are two key temperament traits involved in behavior regulation. The aim of this study was to test several existing theories in explaining the role of impulsivity and compulsivity in symptom severity in various behavioral addictions. Methods: Data were collected from a (representative) general population sample (N = 2,710, mean age:39.8 years (SD:13.6), 51% woman), and from people who are at increased risk of having a behavioral addiction (N = 9,528 in total, mean age: 28.11 (SD:8.3), 34.3% woman), including people with problematic gaming and internet use, pathological gambling, exercise dependence, compulsive buying and work addiction. Symptom severity, reward driven impulsivity and relief driven compulsivity were assessed. Results: For non-problematic groups, impulsivity is present to about the same extent as compulsivity, whereas for problematic groups, compulsivity dominates over impulsivity in all groups (except for gambling). The strength of the correlation between impulsivity and compulsivity is higher in more severe forms of the disorders (from r = 0.18 to r = 0.59 in the representative population). Discussion: Based on these data, it appears that relief-driven behavior (negative reinforcement) dominates over reward-driven behavior (positive reinforcement) in more severe cases of a behavioral addiction. Conclusion: This is the first large-scale study to find empirical support for the neuroscientific theory on the dominance of compulsivity (“needing”) over impulsivity (“wanting”) in more severe cases of a behavioral addiction. Although longitudinal research is needed, a possible shift from impulsivity to compulsivity takes place, similar to substance use addictions, which maintains the circle of addiction.Peer Reviewe

Study addiction: a cross-cultural longitudinal study examining temporal stability and predictors of its changes

Background and aims: "Study addiction" has recently been conceptualized as a behavioral addiction and defined within the framework of work addiction. Using a newly developed measure to assess this construct, the Bergen Study Addiction Scale (BStAS), the present study examined the 1-year stability of study addiction and factors related to changes in this construct over time, and is the first longitudinal investigation of study addiction thus far. Methods: The BStAS and the Ten Item Personality Inventory were administered online together with questions concerning demographics and study-related variables in two waves. In Wave 1, a total of 2,559 students in Norway and 2,177 students in Poland participated. A year later, in Wave 2, 1,133 Norwegians and 794 Polish, who were still students completed the survey. Results: The test–retest reliability coefficients for the BStAS revealed that the scores were relatively stable over time. In Norway, scores on the BStAS were higher in Wave 2 than in Wave 1, whereas in Poland, the reverse pattern was observed. Learning time outside classes at Wave 1 was positively related to escalation of study addiction symptoms over time in both samples. Being female and scoring higher on neuroticism was related to an increase in study addiction in the Norwegian sample only. Conclusions: Study addiction appears to be temporally stable, and the amount of learning time spent outside classes predicts changes in study addiction 1 year later