Addictive behaviors最新文献

Background and objectives: Cannabis use remains a major concern for adolescent health. Monitoring adolescent cannabis use trends and whether demographic subgroups might be differentially impacted remains important for public health planning.

Methods: Data from the 1991-2023 Youth Risk Behavior Survey (YRBS), a biennial school-based survey representative of US high school students, were analyzed. Cross-tabulations and logistic regression models were calculated to examine lifetime, recent, and early-age cannabis use. Trends in cannabis use were examined by sex and race/ethnicity.

Results: Across different demographic groups, adolescent cannabis use rates have largely followed a similar inverted-U pattern, with rates peaking in 1999 and subsequently declining. Lifetime cannabis use decreased from 47.3% (95% CI: 44.5-50.2%) in 1999 to 30.1% (95% CI: 27.8-32.3%) in 2023. Recent use declined from 27.1% (95% CI: 24.6-29.6%) to 17.8% (95% CI: 16.2-19.4%). Early-age initiation declined from 11.5% (95% CI: 9.7-13.3%) to 6.5% (95% CI: 4.7-8.4%). A significant gender shift occurred: while males historically reported higher rates, in 2023, females demonstrated higher prevalence of both lifetime (33.4% vs. 27.0%) and recent use (19.4% vs. 16.4%). Consistent racial/ethnic differences persisted, with Asian adolescents reporting consistently lower prevalence and non-Hispanic Black and Hispanic adolescents reporting higher rates across most metrics.

Conclusion: Rates of lifetime, recent, and early-age cannabis rose through the 1990s, peaked around 1999, and have since declined. Where males formerly reported higher cannabis use rates, females now report higher rates of lifetime and recent cannabis use. Such convergence, noted to be robust across racial/ethnic groups, merits further study.

Background: In 2021, the U.S. Food and Drug Administration (FDA) authorized marketing of the first e-cigarette, Vuse Solo; subsequently, other e-cigarettes and related products were authorized or denied marketing. We examined how FDA authorization affects perceptions of and intentions to use e-cigarettes.

Methods: Cross-sectional survey of N = 6,098 participants 13-40 years old; embedded experiments: (1) Randomized to a statement indicating FDA authorized marketing of Vuse Solo (Treatment) or no statement (Control). Participants reported perceptions of Vuse Solo health harms, benefits, and intentions to use. (2) Viewed a fictional e-cigarette ("NovaStik") with a brief description, including a randomized statement: NovaStik was "FDA authorized" (Condition 1), "Not FDA authorized" (Condition 2), or "FDA denied" (Condition 3). Participants reported perceptions of NovaStik and intentions to use. T-tests and ANOVAs evaluated differences in responses by condition; multi-variate regression examined differences in treatment effects by sex, age group, and past 30-day tobacco use.

Results: Experiment 1: treatment participants perceived Vuse Solo as less harmful than control participants (p's < 0.01); there were no differences in perceptions of addictiveness or intentions to use Vuse Solo by condition. Experiment 2: there were statistically significant differences in all NovaStik perceptions and intentions items (p's < 0.001). Participants in the FDA-authorized condition reported more positive perceptions and intentions compared to those in the "Not Authorized" or "Denied" conditions.

Discussion: Viewing information that e-cigarettes were FDA-authorized was associated with lower perceptions of health harms and higher intentions to use. Findings suggest that stated FDA authorization can have unintended effects on e-cigarette perceptions and intentions.

Introduction: Motivation-phase smoking treatment can increase treatment reach and abstinence in persons unmotivated to quit smoking. However, Motivation-phase treatment is modestly and inconsistently effective. This research aims to identify factors that may influence the effectiveness of the two intervention components most commonly used in Motivation-phase treatment: nicotine replacement therapy (NRT) and reduction counseling.

Methods: An exploratory, secondary analysis of a 4-factor, randomized trial enrolled 577 primary care patients who were willing to reduce, but not quit, smoking. Participants were randomized to the following interventions: smoking reduction counseling, nicotine mini-lozenge, behavioral activation counseling, and 5Rs-motivational counseling. Using a precision medicine approach, machine learning analyses determined whether demographic and smoking variables identified persons more likely to benefit from the interventions with regard to 24-hour quit attempts, entry into cessation treatment, and self-reported 7-day point prevalence abstinence at 1 year.

Results: Quitting self-efficacy predicted the likelihood of making a quit attempt and entering cessation treatment. At high levels of self-efficacy (>3.5 out of 5), there were no significant effects of interventions. At low levels of self-efficacy (≤3.5 out of 5), receiving reduction counseling reduced the odds of making a quit attempt (OR = 0.51, p = 0.002), and receiving mini-lozenge reduced the odds of entering cessation treatment (OR = 0.55, p = 0.02). No significant effects were found for smoking abstinence.

Conclusions: Baseline quitting self-efficacy may identify persons who will not be aided by standard Motivation-phase treatment and thus require a different therapeutic approach. These results raise questions about whom to treat, and how to treat, individuals who decline cessation treatment.

Introduction: The co-use of substances confers risks above single-product use and has significant public health implications. This study investigated trends in past 30-day co-use of nicotine/tobacco products with alcohol and cannabis in the US using Population Assessment of Tobacco and Health Study data from Waves 4-6 (December 2016-November 2021).

Methods: All wave 4-6 PATH participants age 15+ were included in analyses. Changes across wave in past 30-day co-use of cigarettes, e-cigarettes, and other tobacco products (OTP; cigars, filtered cigars, smokeless, hookah, snus, and cigarillo) with alcohol and cannabis, moderated by age (15-17,18-24, 25-34,35-64, 65+), and controlling for demographics were investigated.

Results: Changes in co-use of tobacco products with cannabis and alcohol varied across age and product. Cigarette and alcohol co-use was most prevalent across all adult ages, with rates declining over time among young adults (18-24, 25-34) but stable in older adults (65+). Rates of e-cigarette and alcohol co-use increased among young adults, possibly supplanting alcohol and cigarette co-use. E-cigarette and alcohol co-use was the most popular pattern of co-use in youth, with initially increasing and then declining prevalence. Co-use of e-cigarette and cannabis increased at Wave 5 among those 15-17, 18-24, and 25-34, although this increase lessened in all groups except those age 25-34 at Wave 6. Cigarette and cannabis co-use rates, and co-use rates of OTP with both cannabis and alcohol were generally stable or decreasing.

Conclusions: Findings highlight the complex interplay between substance use patterns and developmental stages and the dynamic nature of co-use in ever-evolving tobacco and cannabis marketplaces.

Existing evidence suggests that problematic smartphone use (PSU) and disengagement may form part of a spiraling process. This investigation explores this process among first-year undergraduates, distinguishing within-person fluctuations from between-person rank order stability. Over 30 consecutive days, 104 first-year undergraduates in China (M_age = 18.62, SD = 0.96, 55.1% female) completed daily surveys that assessed PSU and disengagement. Dynamic structural equation modeling indicated a bidirectional lagged association whereby higher-than-usual PSU on a given day was prospectively associated with higher-than-usual disengagement the next day, and higher-than-usual disengagement on a given day was prospectively associated with higher-than-usual PSU the next day. Individuals with higher PSU than their peers tended to report greater disengagement, with PSU consistently amplifying its impact on disengagement. Neither family socioeconomic status nor gender significantly influenced the model. The findings highlight a harmful cycle of daily reinforcement at the within-person level, coupled with consistent associations at the between-person level. Given the importance of the first year of university, the findings underscore the need for targeted interventions that address both PSU and disengagement and aim to attenuate their bidirectional association.

There is limited longitudinal data examining national gambling trends in Australia. This study examines longitudinal trends in gambling participation and higher-risk gambling in Australia from 2015 to 2022 using data from the nationally representative Household Income and Labour Dynamics in Australia (HILDA) panel study. Study participants were HILDA respondents aged 15 and older in 2015, 2018, or 2022 who completed the Problem Gambling Severity Index (PGSI; N = 44,836 observations). Gambling participation was based on self-reported typical monthly expenditure on 10 gambling activities. Gambling risk was assessed using the 9-item PGSI and categorised as low-risk (0-2) or higher-risk (3+) gambling. Age and sex were included as socio-demographic variables. The results indicated that monthly gambling participation declined from 37.1% in 2015 to 32.9% in 2022 but levels of higher-risk gambling did not reduce at the same rate. Higher-risk gambling was independently associated with participation in electronic gaming machines (EGMs; OR = 8.0, p < 0.001), race betting (OR = 2.3, p < 0.001) and sports betting (OR = 1.5, p = 0.01). These were the most popular forms of gambling among those aged under 25. Although overall gambling participation in Australia has declined to 2022, this did not result in a reduction to higher-risk gambling. Young adults were the least likely to gamble, but show disproportionate participation in EGMs, race, and sports betting, and an increasing rate of higher-risk gambling.

Objective: It is critical to understand the characteristics of people who use cannabis during pregnancy. We examined the prevalence and sociodemographic and clinical correlates of current, recent, former, and never cannabis use among pregnant individuals in the U.S.

Methods: We analyzed pooled data from 1,992 pregnant participants in the National Survey on Drug Use and Health (NSDUH) from 2021 to 2023. We used multinomial regression to identify correlates of cannabis use status (i.e., never use vs. current [past 30-day], recent [past 2-12-month], and former [nonuse in the past year], respectively).

Results: Overall, nearly 7% of pregnant participants reported current cannabis use. Among current users, 31% reported any doctor-recommended cannabis use in the past year and 52% bought their cannabis from a dispensary. Compared to never users, current cannabis use was more likely among those aged 18-25 (vs. 26+; Relative Risk Ratio [RRR] = 2.08, 95% CI: 1.04-4.18), unmarried (vs. married; RRR = 2.54, 95% CI: 1.05-6.14), with greater education (vs. < high school; RRR = 2.97, 95% CI: 1.42-6.23), past 30-day cigarette use (RRR = 2.57, 95% CI: 1.11-5.94), alcohol use (RRR = 7.24, 95% CI: 1.52-34.49), e-cigarette use (RRR = 4.92, 95% CI: 1.71-14.10), or serious psychological distress (RRR = 6.25, 95% CI: 2.46-15.85); current use was less likely among those perceiving some risk of weekly cannabis use (vs. no risk; RRR = 0.07, 95% CI: 0.03-0.14). Recent use (vs. never use) was less likely in states where cannabis was illegal (RRR = 0.45, 95% CI: 0.22-0.95).

Conclusion: Cannabis use during pregnancy remains high among certain subgroups. Future research should develop tailored interventions targeting motivations of cannabis use during pregnancy, such as risk perceptions and polysubstance use, which negatively impact maternal and fetal health.

Background: Cannabis and cannabidiol (CBD) use have grown recently among U.S. adults, yet little is known about their exclusive or combined use at the population level. This study sought to assess the prevalence and contributing factors of distinct use patterns.

Methods: Data from the 2023 National Survey of Drug Use and Health study were analyzed for adolescents (12-17,n = 11,572) and adults (18+,n = 45,133). Past-month cannabis and CBD use over the past 30 days, including patterns (non-use, exclusive, and dual-use), were reported and associated factors were examined by multinomial regressions.

Results: In 2023, 15.4% and 9.8% of participants reported past-month cannabis and CBD use, respectively; while 8.9, 3.4%, and 6.4% reported exclusive cannabis use, exclusive CBD use, and dual-use, respectively. Cannabis and CBD use were most common among individuals aged 18-34, while dual use was highest in 18-25-year-olds (10.8%). Exclusive cannabis use peaked in 26-34-year-olds (14.8%), and exclusive CBD use was most prevalent in adults 65+ (5.0%). Youth females (vs. males) and those living above the poverty line (vs. in poverty) were more likely to report exclusive CBD use. Adolescents with fair or poor health (vs. excellent/good) were more likely to report exclusive cannabis (AOR = 3.2,p < 0.001), exclusive CBD (AOR = 3.0,p = 0.002), and dual-use (AOR = 3.0, p < 0.001). Based on adolescent regression results, state medical cannabis legalization was associated with higher exclusive cannabis use(AOR = 1.8,p = 0.01). Based on adult regression results, state medical cannabis legalization was associated with higher exclusive cannabis use (AOR = 1.5, p < 0.001) and dual-use (AOR = 1.5, p < 0.001).

Conclusions: Cannabis and CBD use exhibited distinct usage patterns. As cannabis legalization policies continue to evolve, public health professionals should focus on tailored interventions to mitigate potential side effects associated with complex cannabis use.

Background: Intimate partner violence (IPV) is a global public health concern. Although some studies have identified cross-sectional associations between IPV victimization and smoking, longitudinal research remains limited. This study investigated the association between IPV victimization and smoking initiation and cessation among Korean adults.

Methods: This study included adult participants from the Korean Welfare Panel Study 2009-2023 (n = 13,450; observations = 108,932). Experiences of non-physical and overt physical IPV within the past year were assessed. The outcome measure was the incidence of smoking initiation and cessation in the following year. Generalized estimating equations were used to account for repeated measures. Odds ratios and 95% confidence intervals (CIs) were calculated to represent the associations.

Results: Among the overall sample, individuals exposed to non-physical or physical IPV had 1.36-fold (95% CI: 1.18-1.56) and 2.69-fold (95% CI: 1.77-4.08) higher odds of smoking initiation, respectively, compared to those not exposed to IPV. Furthermore, verbal IPV, threats of physical IPV, and physical IPV were associated with 1.43-fold (95% CI: 1.24-1.63), 1.74-fold (95% CI: 1.26-2.39), and 2.44-fold (95% CI: 1.60-3.72) increased odds of smoking initiation, respectively. These associations were observed in both men and women. However, no clear association was found between IPV and smoking cessation in the subsequent years.

Conclusion: This study demonstrates that individuals who experienced IPV had an increased likelihood of smoking initiation one year after exposure. Consequently, policy interventions aimed at preventing IPV are warranted.

Evidence on the longitudinal associations between problematic social media use (PSMU) and mental health is inconsistent. While some studies suggest that PSMU predicts later poor mental health, others do not. There is also limited evidence on the role of sleep in these associations. To clarify these questions the present study investigated the associations between PSMU and mental health, and the mediating role of sleep. The eMediate study participants (n = 437, 49.7 % female, mean age = 22.62 ± 1.82 years) who completed four surveys of social media use, sleep, and mental health at three-month intervals were included. Multilevel mediation analyses were conducted to examine the associations between the variables. PSMU significantly predicted subsequent depressive and anxiety symptoms. Insomnia symptoms and poor sleep quality partially mediated these associations. Insomnia was a stronger mediator than sleep quality. Results also showed that PSMU was indirectly associated with wellbeing through insomnia and poor sleep quality. This study identifies poor sleep as a pathway through which PSMU may impact mental health, highlighting the importance of addressing sleep problems to mitigate the effect of PSMU on wellbeing. Important practical implications for both mental health and future research are discussed.