The present work examines associations between TikTok Use Disorder (TTUD) tendencies, fear of missing out (FoMO) and everyday cognitive failure. In line with prior studies on problematic social media use, we observed in N = 720 TikTok users (249 males, 471 females; mean age = 37.78 years) − who completed the TikTok Use Disorder Questionnaire (TTUD-Q), the FoMO Scale, and the Cognitive Failure Questionnaire (CFQ) − that both higher trait and state FoMO went along with more self-reported cognitive failure in everyday life. This association was mediated by TTUD tendencies, albeit to different degrees. The distinction between general FoMO tendencies and situational, online-related state FoMO appears to be important for understanding putative mechanisms behind the here presented associations and is discussed further. Overall, the findings suggest that higher disordered use tendencies of TikTok may be linked to more cognitive failure, potentially due to frequent app-related interruptions of everyday activities. However, these conclusions are limited by the self-report nature of data and the cross-sectional design which precludes causal inference.

Research on young adult alcohol use often overlooks the influence of specific social network members on daily alcohol use. This pilot study combined egocentric social network methods with a daily diary design to examine how network members influence drinking at the day level. Participants (N = 21) identified six social network members they frequently drank with and saw in person and then reported on these individuals in a 21-day study. Daily reports captured self-reported alcohol use and social network members presence and alcohol use from the previous day. Across 417 morning reports, participants drank on 77days (18.5%), consuming an average of 2.36 drinks (SD = 1.70) on those days. Linear mixed-effects models showed that being with a given network member who was drinking was associated with consuming 1.75 more drinks than the participant's average. Network members who contributed to higher alcohol use were more likely to be people the participant intended to drink with in the future and who had frequently consumed alcohol in the past month, regardless of whether it was with the participant. The findings from this pilot study provide preliminary evidence that the drinking of and anticipating future drinking with certain network members contributes to greater alcohol use and suggests that interventions could use personalized feedback to help individuals recognize the network members who facilitate heavier drinking.

Problematic social media usage (PUSM) has become a growing public health issue, with adolescents being particularly vulnerable. The absence of a standardized diagnostic tool has hindered consistent clinical identification and research advancement. To address this gap, the present study systematically evaluated the applicability of the DSM-5 Internet gaming disorder (IGD) criteria for diagnosing PUSM. A total of 405 participants were recruited and divided into five groups: PUSM, gaming disorder (GD), regular social media users (RSMU), regular gamers (RG), and healthy controls (HC). In this study, patients were evaluated using both ICD-11 and DSM-5. The ICD-11 criteria served as an external criterion, providing a benchmark for the validity testing of the DSM-5 framework. The DSM-5 IGD criteria demonstrated excellent diagnostic accuracy (>80%) for both PUSM and GD, except "deception". The ICD-11 and DSM-5 criteria exhibited high consistency, though the ICD-11 criteria adopted a stricter diagnostic threshold. No significant differences were observed between the PUSM and GD groups in terms of symptom profiles, functional impairment, or clinical severity. This study provides empirical support for adopting the DSM-5 IGD diagnostic criteria as a standardized clinical tool for assessing PUSM. However, the "deception" criterion requires further validation due to its weak diagnostic performance. The findings further confirm the conceptual and symptomatic homogeneity between PUSM and IGD, supporting their classification within a unified behavioral addiction framework.

Cannabis is often used alongside other substances, including cigarettes and alcohol. The objective of this study was to identify how the combination of these substances may affect sleep health. Data from an online, national survey of 518 adults (35.2±13.4years old; 65% female) were analyzed. Respondents reported their cannabis, cigarette, and alcohol use. Hazardous cannabis use was assessed using the Cannabis Use Disorder Identification Test - Revised (CUDIT-R). Sleep, insomnia, and daytime sleepiness were assessed using the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Epworth Sleepiness Scale (ESS), respectively. Sleep health was assessed using PSQI and ISI items about sleep quality, satisfaction, trouble staying awake, bedtime, waketime, sleep efficiency, and duration. Linear regression models examined associations of CUDIT-R and substance use with sleep scales and the individual sleep items, adjusting for sociodemographic factors. One-quarter used only cannabis, 45% alcohol and cannabis, 12% cigarettes and cannabis, and 19% all three substances (polysubstance use). Average scores were 10.4±5.7 on the CUDIT-R, 8.0±4.1 on the PSQI, 11.3±6.2 on the ISI, and 6.4±4.2 on the ESS. A higher CUDIT-R was associated with higher PSQI (β=0.09, 95% CI=0.01, 0.17) and ESS scores (β=0.16, 95% CI=0.07, 0.26). Compared to individuals who only use cannabis, individuals with polysubstance use had higher PSQI, ISI, and ESS scores and reported worse sleep quality and less sleep satisfaction. Sleep quality and satisfaction were most impaired by polysubstance use, whereas hazardous cannabis use increased sleepiness. The combined use of substances is detrimental to sleep health and highlights an area for public health messaging and awareness.