Discrimination and insomnia: Examining depressive symptoms and nicotine withdrawal through a serial mediation model in a sample of smokers.

Insomnia is a common sleep disorder associated with poor health outcomes. Individuals from racially underrepresented groups as well as women tend to report more severe insomnia symptoms, and frequent experiences of discrimination have been found to drive such disparities. Smokers commonly experience sleep problems since nicotine can alter the sleep-wake cycle. Discrimination is associated with increased nicotine dependence, and such discrimination may also intensify tobacco withdrawal, specifically mood and cognitive-related aspects of withdrawal. The potential impact of discrimination on withdrawal symptoms and related mood symptoms like depression may lead to increases in insomnia symptoms. However, no studies to date have evaluated the indirect association of discrimination with insomnia severity through nicotine withdrawal and depressive symptoms. Therefore, this cross-sectional survey of n = 110 non-Hispanic Black and White current smokers (48.2 % Black, 69.1 % women) investigated these associations through a serial mediation model. Controlling for race, gender, nicotine dependence levels, and income, multivariate analyses supported a significant indirect effect of discrimination on insomnia severity through depressive symptoms. Analyses supported the hypothesized serial mediation model whereby discrimination is positively associated with depressive symptoms, which in turn are linked to more severe nicotine withdrawal, leading to greater insomnia severity. Smokers encountering frequent experiences of discrimination might be at increased risk of suffering insomnia as a result of their increased depressive and withdrawal symptoms. Future work is necessary to understand the role of depressive symptoms in these associations as well as possible implications for smoking relapse and success of smoking cessation programs.

Review of Popularity and Quality Standards of Opioid-Related Smartphone Apps.

PURPOSE OF REVIEW: Opioid misuse, addiction, and related harm is a global crisis that affects public health and social and economic welfare. Many of the strategies being used to combat the opioid crisis could benefit from improved access and dissemination, such as that afforded by smartphone apps. The goal of this study was to characterize the purpose, audience, quality and popularity of opioid-related smartphone apps. Using web scraping, available information from 619 opioid-related apps (e.g., popularity metrics) was downloaded from Google Play, and 59 apps met criteria for review. The apps were additionally coded for quality by two raters using an 8-item screener for the American Psychiatric Association App Evaluation Model. FINDINGS: Sixty one percent of apps targeted patients, 29% providers, 8% the general community, and 2% healthcare trainees. Regarding app purpose, 49% addressed treatment, 27% prevention, and 24% overdose. Only one app met all criteria on the screener for quality, and there was no association between a total score calculated for the screener and measures of app popularity (e.g., star ratings; R2=0.10, p=0.19). SUMMARY: Opioid-related apps available for consumers addressed key stakeholders (patients, providers, community) and were consistent with strategies to address the opioid crisis (prevention, treatment, overdose). However, there was little evidence that available opioid-related apps meet basic quality standards, and no relationship was found between app quality and popularity. This review was conducted at the level of consumer decision-making (i.e., the app store), where only a handful of opioid-related apps met quality standards enough to warrant a more detailed evaluation of the app before recommendation for use. Because smartphone apps could be a critical tool to increase access to and utilization of opioid prevention, treatment, and recovery services, further development and testing is sorely needed.

Pilot Randomized Controlled Trial of a Novel Smoking Cessation App Designed for Individuals With Co-Occurring Tobacco Use Disorder and Serious Mental Illness.

INTRODUCTION: High rates of tobacco use among people with serious mental illness (SMI), along with their unique needs, suggest the importance of developing tailored smoking cessation interventions for this group. Previous early-phase work empirically validated the design and content of Learn to Quit, a theory-based app designed for this population. METHODS: In a pilot randomized controlled trial, we compared the feasibility, acceptability, and preliminary efficacy of Learn to Quit versus QuitGuide, an app designed for the general population. All participants received nicotine replacement therapy and technical assistance. Daily smokers with SMI (N = 62) participated in the trial with outcomes assessed at weeks 4, 8, 12, and 16. RESULTS: Compared to QuitGuide, Learn to Quit participants had similar number of days of app use (34 vs. 32, p = .754), but larger number of app interactions (335 vs. 205; p = .001), longer durations of app use (4.24 hrs. vs. 2.14 hrs; p = .044), and higher usability scores (85 vs. 79, p = .046). At week 16, Learn to Quit led to greater reductions in cigarettes per day (12.3 vs. 5.9 for QuitGuide; p = 0.10). Thirty-day point prevalence abstinence was verified in 12% of Learn to Quit participants versus 3% of QuitGuide participants (odds ratio = 3.86, confidence interval = 0.41 to 36, p = .239). Changes in psychiatric symptoms and adverse events were not clinically significant between conditions. CONCLUSIONS: This pilot trial provides strong evidence of Learn to Quit's usability, feasibility, and safety. Preliminary evidence suggests the app may be efficacious. A randomized controlled efficacy trial is needed to test the app in a larger sample of smokers with SMI. IMPLICATIONS: This study suggests that the Learn to Quit app is a feasible approach to deliver smoking cessation treatment in patients with co-occurring tobacco use disorder and SMI. This means that, if found efficacious, this technology could be used to deploy smoking cessation treatment to larger segments of this population, hence improving public health. Therefore, a randomized controlled trial should be conducted to examine the efficacy of this digital intervention.