Regulatory Focus and Substance Use in Adolescents: Protective Effects of Prevention Orientation

Digital interventions for substance use disorders in young people: rapid review

BACKGROUND

Young people are disproportionately more likely than other age groups to use substances. The rise in substance use and related harms, including overdose, during the Covid-19 pandemic has created a critical need for more innovative and accessible substance use interventions. Digital interventions have shown effectiveness and can provide more engaging, less stigmatizing, and accessible interventions that meet the needs of young people. This review provides an overview of recent literature on the nature of recently published digital interventions for young people in terms of technologies used, substances targeted, intended outcomes and theoretical or therapeutic models employed.

METHODS

Rapid review methodology was used to identify and assess the literature on digital interventions for young people. An initial keyword search was conducted using MEDLINE the Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects (DARE), Health Technology Assessment Database (HTA) and PROSPERO for the years 2015-2020, and later updated to December 2021. Following a title/abstract and full-text screening of articles, and consensus decision on study inclusion, the data extraction process proceeded using an extraction grid developed for the study. Data synthesis relied on an adapted conceptual framework by Stockings, et al. that involved a three-level treatment spectrum for youth substance use (prevention, early intervention, and treatment) for any type of substance.

RESULTS

In total, the review identified 43 articles describing 39 different digital interventions. Most were early interventions (n = 28), followed by prevention interventions (n = 6) and treatment interventions (n = 5). The identified digital technologies included web-based (n = 14), game-based (n = 10), mobile-based (n = 7), and computer-based (n = 5) technologies, and virtual reality (n = 3). Most interventions targeted alcohol use (n = 20) followed by tobacco/nicotine (n = 5), cannabis (n = 2), opioids (n = 2), ketamine (1) and multiple, or any substances (n = 9). Most interventions used a personalized or normative feedback approach and aimed to effect behaviour change as the intended outcome. Interestingly, a harm reduction approach guided only one of the 39 interventions.

CONCLUSIONS

While web-based interventions represented the most common type of technology, more recently developed immersive and interactive technologies such as virtual reality and game-based interventions call for further exploration. Digital interventions focused mainly on alcohol use, reflecting less concern for tobacco, cannabis, co-occurring substance use, and illicit drug use. Specifically, the recent exacerbation in the opioid crisis throughout North American underlines the urgent need for more prevention-oriented digital interventions for opioid use. The uptake of digital interventions among youth also depends on the incorporation of harm reduction approaches.

Linking Self-Control to Negative Risk-Taking Behavior among Chinese Late Adolescents: A Moderated Mediation Model

Negative risk-taking behaviors refer to voluntary behaviors that lead to more harm than good. Low self-control is a crucial predictor of adolescents’ negative risk-taking behavior, but its internal mechanisms require further exploration. To reveal the working process underlying the association between self-control and adolescents’ negative risk-taking behaviors, we investigated the mediation of regulatory focus and the moderation of sense of power. A total of 2018 students (37.6% males) from two universities in Guangzhou, China, participated in a survey that investigated their self-control, negative risk-taking behavior, regulatory focus and sense of power. The results revealed that after controlling for the adolescents’ sex and their parents’ educational level, prevention focus partially mediated the association between self-control and negative risk-taking behavior. Moreover, sense of power moderated the association between self-control and prevention focus. Furthermore, the association between self-control and negative risk-taking behavior through prevention focus was stronger among adolescents with a high sense of power than among those with a low sense of power. Therefore, our findings suggest that regulatory focus and sense of power might be the mechanisms that explain how self-control is related to negative risk-taking behavior. These results thus provide a foundation for the prevention of and intervention in adolescents’ negative risk-taking behavior.