Gender Differences in Negative Mood, Emotional Intelligence and Tobacco Use among Young Adults

The substance use behaviors change of first-year college students before and during COVID-19 pandemic

OBJECTIVE

This article tests the substance use behaviors of college students before and during COVID-19 pandemic.

METHODS

In-depth assessment and nightly survey data was used from a longitudinal study (n = 675) which examined student substance use during the 2019-2020 academic year, both before and during the onset of the COVID-19 pandemic. Changes in beer/wine, tobacco, liquor, and marijuana use before versus during the pandemic, in addition to the interaction of COVID-19, were tested with gender and subjective social status.

RESULTS

Marijuana use significantly decreased from a weekly prevalence of 9.9% before COVID-19 to 6.4% during COVID-19 (p = 0.002). A similar decrease was seen in liquor use (10.6% before COVID to 6.4% during COVID, p = 0.01). There was no significant change observed for beer/wine use or for tobacco use.

CONCLUSION

In the wake of the COVID-19 pandemic, liquor, and marijuana use decreased for college students, while other substance use stayed the same.

Sex and age disparities in the influence of tobacco smoking on depression: Evidence from the Taiwan Biobank

INTRODUCTION

The global tobacco epidemic poses a notable challenge to global health due to its association with various tobacco-related diseases. Although tobacco smoking is associated with depression, the exact mechanism by which tobacco smoking increases the risk of depression is unclear. This study explored the potential effects of tobacco smoking on depression.

METHODS

We used data in the analysis from the Taiwan Biobank of 27916 individuals recruited from 2015 to 2020. To investigate the associations between tobacco use and depression, the results of the depression-measuring subscale of the Patient Health Questionnaire-4 as well as data on participants' tobacco consumption and other relevant covariates, were analyzed.

RESULTS

Participants who smoked were more likely to report depression than those who did not smoke (AOR=1.50; 95% CI: 1.21-1.86). Furthermore, depression was significantly higher in women who smoked than in their male counterparts (females: AOR=1.68; 95% CI: 1.27-2.23, and males: AOR=1.32; 95% CI: 0.96-1.80). Women aged <55 years and who smoked were more likely to report depression, whereas this trend was not observed in those aged ≥55 years (<55 years: AOR=1.75; 95% CI: 1.23-2.48), and ≥55 years: AOR=1.58; 95% CI: 0.97-2.56).

CONCLUSIONS

Tobacco smoking is a significant factor associated with depression, particularly in younger women. The increasing prevalence of tobacco use for years among younger women in Taiwan might contribute to shifts in the associations between depression and tobacco use in women.

Convergent Validity Analysis between the Profile of Emotional Competences Full-Form and the Trait Emotional Intelligence Questionnaire Full-Form

Emotional dispositions have been found to influence outcomes and have applications in many areas, such as in the clinical, health, social, educational, and organizational domains. Specifically, they may influence individuals’ addictive behaviour tendencies. The aim of this study was to investigate the convergent validity between two questionnaires measuring individual differences linked to emotional dispositions, the Profile of Emotional Competences (PEC) full-form, and the Trait Emotional Intelligence Questionnaire (TEIQue) full-form. Examining the convergent validity will identify the similarities and the unique aspects of each questionnaire. Our hypotheses were based on relationships displaying large effect sizes (r > .50). A sample of 1026 participants took part in this study (Mage = 21.35 years old, age range = 18–30). Participants completed both the PEC and the TEIQue in a counterbalanced order. Results indicated large overlaps between the two questionnaires; however, two main differences emerged: first, the PEC allows capturing precisely the emotional dispositions at the intrapersonal and interpersonal levels, while the TEIQue mixes both levels; second, the competence “using emotions”, both for one’s own emotions and for others’ emotions, is not comprehensively reflected in the TEIQue. Overall, the PEC may help to capture more specifically the distinction between intrapersonal and interpersonal emotional competences. Future research should investigate comparatively the criterion validity of both questionnaires with specific outcome variables. Future research and applied work with addiction aiming at clarifying the implication of both intrapersonal and interpersonal emotional competences may consider to rather use the PEC than the TEIQue.

Multimodal prediction of trait emotional intelligence-Through affective changes measured using non-contact based physiological measures

Inability to efficiently deal with emotionally laden situations, often leads to poor interpersonal interactions. This adversely affects the individual's psychological functioning. A higher trait emotional intelligence (EI) is not only associated with psychological wellbeing, educational attainment, and job-related success, but also with willingness to seek professional and non-professional help for personal-emotional problems, depression and suicidal ideation. Thus, it is important to identify low (EI) individuals who are more prone to mental health problems than their high EI counterparts, and give them the appropriate EI training, which will aid in preventing the onset of various mood related disorders. Since people may be unaware of their level of EI/emotional skills or may tend to fake responses in self-report questionnaires in high stake situations, a system that assesses EI using physiological measures can prove affective. We present a multimodal method for detecting the level of trait Emotional intelligence using non-contact based autonomic sensors. To our knowledge, this is the first work to predict emotional intelligence level from physiological/autonomic (cardiac and respiratory) response patterns to emotions. Trait EI of 50 users was measured using Schutte Self Report Emotional Intelligence Test (SSEIT) along with their cardiovascular and respiratory data, which was recorded using FMCW radar sensor both at baseline and while viewing affective movie clips. We first examine relationships between users' Trait EI scores and autonomic response and reactivity to the clips. Our analysis suggests a significant relationship between EI and autonomic response and reactivity. We finally attempt binary EI level detection using linear SVM. We also attempt to classify each sub factor of EI, namely-perception of emotion, managing own emotions, managing other's emotions, and utilization of emotions. The proposed method achieves an EI classification accuracy of 84%, while accuracies ranging from 58 to 76% is achieved for recognition of the sub factors. This is the first step towards identifying EI of an individual purely through physiological responses. Limitation and future directions are discussed.