Depression and social anxiety symptoms explain substance use problems beyond amount/frequency of substance use

Validation of the Reasons for Quitting Smoking Cannabis Scale Among People with Cannabis Use Disorder

BACKGROUND

The prevalence of cannabis use disorder (CUD) has increased in the last ten years with medicinal and recreational legalization across the United States and increasing accessibility worldwide. Estimates suggest that 8-18% of individuals who use cannabis meet diagnostic criteria for CUD, leading to significant impairments across functioning. However, there are currently no measures that assess the reasons for quitting smoking cannabis to use in treatments with validation evidence in those with CUD.

METHOD

We validated the Reasons for Quitting Smoking Cannabis Scale (RQSCS) in adults (n = 133) who meet the diagnostic criteria for CUD as part of a laboratory-based clinical trial on transdermal nicotine patches for cannabis withdrawal symptoms (R01DA031006). We conducted standard psychometric testing, including exploratory factor analyses, estimating internal consistencies, exploring demographic variation, and testing construct validity.

RESULTS

The RQSCS demonstrated a four-factor structure, including: (1) cognitive health, (2) social functioning, (3) health problems, (4) reputation, and a single item that assesses experimental incentive; λs > .410), with acceptable to high internal consistencies for each subscale (αs > .725). The scale demonstrated strong construct validity and minor demographic variation. Finally, all subscales were sensitive to detecting reasons for quitting cannabis and differentially predicted cannabis use 31 days after the study.

CONCLUSION

The RQSCS is a psychometrically robust, timely instrument for assessing the reasons for quitting smoking cannabis in individuals with CUD. The scale has the potential to provide useful information for clinicians attempting to help those with CUD reduce or cease their cannabis use, informing individualized treatment plans and enhancing motivation for change.

A latent profile analysis of social anxiety, depression, and pregaming motives among heavy-drinking college students

BACKGROUND

Pregaming is a high-risk drinking behavior that is associated with heavy drinking and negative alcohol-related consequences. College students may engage in pregaming for several reasons, including to enhance social experiences or cope with negative affect. Research shows that associations between drinking, social anxiety, and depression are multifaceted. However, our understanding of the complex associations of mental health symptoms with pregaming motives and behaviors remains limited.

METHODS

This study examined heterogeneity in how pregaming motives, social anxiety, and depression associate with past 30-day pregaming variables (quantity, frequency, and negative consequences). We used latent profile analysis (LPA) in a sample of heavy-drinking university students (N = 479).

RESULTS

LPA results indicated four profiles: mild/moderate social anxiety and depression symptoms, moderate motives (n = 285), minimal social anxiety and depression symptoms, low motives (n = 61), subclinical/elevated social anxiety and depression symptoms, high motives (n = 75), and clinically elevated social anxiety and depression symptoms, moderate motives (n = 58). The subclinical/elevated symptoms, high motives profile reported the highest pregaming frequency and consequences, including blackouts. Individuals in the clinically elevated symptoms, moderate motives profile reported more consequences than those in the minimal symptoms, low motives and mild/moderate symptoms, moderate motives profiles. Individuals in the minimal symptoms, low motives profile reported the fewest consequences.

CONCLUSIONS

Among these students, social anxiety and pregaming motives were associated with more frequent pregaming and social anxiety and depression were associated with greater negative consequences. Interventions that target pregaming-specific motives among students with mental health symptoms may be warranted to reduce this risky behavior and associated drinking-related harm.

Internet Addiction, Symptoms of Anxiety, Depressive Symptoms, Stress Among Higher Education Students During the COVID-19 Pandemic

Poor mental health is a growing concern among young people during the coronavirus disease 2019 (COVID-19) pandemic. The aim of this study was to assess the associations of Internet addiction with depressive symptoms, anxiety symptoms, and stress in higher education students during the COVID-19 pandemic, as well as to examine these mental health problems in the context of study-related characteristics. The research sample consisted of 3,099 participants from the Czech Republic (CZ: 1,422) and Slovak Republic (SK: 1,677). The Internet Addiction Test (IAT), the Generalized Anxiety Disorder (GAD-7) scale, the Patient Health Questionnaire for depressive symptoms (PHQ-9), and the Perceived Stress Scale (PSS) were used to measure mental health problems. The analyses also included demographic data (gender and age) and study-related characteristics (form of study, degree of study, field of study, distance between college and home, and housing during the semester). Based on the results of frequency and descriptive analyses, the prevalence of mental health problems was high. The most serious levels of Internet addiction (IAT cut-off point ≥ 50), to which attention should be paid, were found in 3.5% of Czech and 6.2% of Slovak students. Using the standard cut-off point of GAD-7 ≥ 10, 14.1% of Czech and 11.6% of Slovak students were identified with anxiety symptoms. Regarding the PHQ-9 with the cut-off point ≥ 10, 23.4% of Czech and 19.1% of Slovak students had depressive symptoms, which should be addressed. Using the PSS cut-off point ≥ 27, 12.9% of Czech students and 9.1% of Slovak students perceived high stress. The quantile regression analysis showed that Internet addiction was positively associated with anxiety symptoms, depressive symptoms, and stress in all of the analyzed cases (p-value < 0.001). In terms of study-related characteristics, the binomial logistic regression analysis revealed that risk factors for mental health problems in Czech and Slovak students were mainly full-time form of study and living away from home during the semester. Internet addiction, anxiety symptoms, depressive symptoms, and stress are issues that require increased attention, and professionals and policy-makers should implement interventions to effectively prevent and help students with psychological problems.