Prevalence of sleep disturbance among adolescents with substance use: a systematic review and meta-analysis

Profiles of physician follow-up care, correlates and outcomes among patients affected by an incident mental disorder

OBJECTIVES

This study identified profiles of outpatient physician follow-up care and other practice features, mostly after detection of incident mental disorders (MD), and associated these profiles with patient characteristics and subsequent adverse outcomes.

METHODS

A cohort of 170,957 patients age 12 + with a new or recurrent MD detected in 2019-20 was investigated based on data from the Quebec Integrated Chronic Disease Surveillance System. Latent class analysis was performed to identify follow-up care profiles, mostly within one year of MD detection. Bivariate analyses tested associations between profiles and patient characteristics; logistic regressions examined relationships between profiles and adverse outcomes after one year.

RESULTS

Five profiles were identified: Profiles 2 and 5 (64%) offered low mental health (MH) outpatient follow-up care, while the others dispensed higher MH follow-up care. Profiles differed in patient characteristics and related outcomes. Labelled "Follow-up care by usual psychiatrist", Profile 1 (1% of sample) included younger patients with the most health and social issues. Profile 2 (50%), "Low MH follow-up care but high prior consultations for physical reasons", mostly integrated older patients with chronic physical illnesses. Profile 3 (11%), "Follow-up care by general practitioners (GP) and psychiatrists", referred to physicians other than the usual ones (e.g., walk-in practice) and encompassed patients with severe MD conditions. Profile 4 (23%), "High follow-up care by usual GP and prior consultations for physical reasons", showed the typical characteristics of patients treated in primary care (more common MD, women, less materially and socially deprived). Profile 5 (15%), "Low MH follow-up care and prior consultations for physical reasons", integrated more younger men, materially deprived patients, and with substance-related disorders (SRD) or co-occurring MD-SRD. More Profile 1 and 3 patients lived in university regions - those of Profile 4 were the least numerous in such regions. More Profile 5 patients lived in metropolitan and rural areas. Risk of death was higher in Profiles 5, 2, 3, and risk of frequent ED use and hospitalization higher in Profiles 1, 3, and 5 - patients with severe health and social issues.

CONCLUSION

The study confirmed the need to improve prompt, adequate and continuous follow-up care for patients with incident MD.

Insomnia in Patients With Substance Use Disorders: Assessment and Management

Insomnia, characterized by difficulty initiating or maintaining sleep, or poor sleep quality, is highly prevalent among individuals with substance use disorders (SUDs). The relationship between the 2 conditions is often bidirectional. We reviewed the impact of various substances (alcohol, stimulants, opioids, and cannabis) on sleep architecture and their potential to contribute to insomnia. The role of insomnia as a risk factor for different SUDs is also explored. Assessment strategies for co-occurring insomnia and SUDs are discussed, emphasizing the importance of reassessment throughout various phases of substance use treatment. Evidence-based nonpharmacologic and pharmacologic interventions for managing insomnia in SUD patients are presented, highlighting the importance of tailoring treatment approaches to individual needs and substance-specific considerations. Assessment and management of comorbid insomnia and SUDs is crucial but can be difficult; however, studies have shown some benefits using nonpharmacologic and pharmacologic approaches.

Self-Perceived Health, Mood, and Substance Use Among Adolescents: An Analysis to Enhance Family, Community, and Mental Health Care

BACKGROUND

Adolescence is a critical period for developing self-perception, emotional well-being, and health behaviors. Mental health disorders represent a substantial burden for adolescents worldwide. This study examines self-perceived health, mood, and substance use among adolescents, identifying associated risk factors.

METHOD

A cross-sectional study was conducted with 121 adolescents aged from 14 to 18 from a secondary school in Baix Llobregat, Catalonia. Data were collected through questionnaires, and descriptive and comparative analyses were performed.

RESULTS

Poor self-perceived health and negative mood were associated with higher alcohol and tobacco use. Girls exhibited better emotional regulation than boys.

CONCLUSIONS

Poor health perception and negative mood are linked to increased substance use. Early intervention should focus on emotional well-being and prevention, involving both families and schools.

A Longitudinal Examination between Chronotype and Insomnia in Youths: A Cross-Lagged Panel Analysis

Adolescence and young adulthood are transitional periods associated with significant changes and challenges, leading to a heightened vulnerability to sleep disturbances and mental health difficulties. This stage is often associated with an increased preference for eveningness, manifested as a later chronotype. The current study aimed to investigate the directionality of the association between chronotype, based on an individual's sleep-wake behaviour, and insomnia in young people using a two-wave panel design with a 12-month interval. A total of 370 participants aged 15-24 (mean age: 21.0 ± 2.0, 72.7% female) were recruited from local secondary schools and universities. Insomnia symptoms were assessed using the Insomnia Severity Index, while chronotype was measured using the Munich Chronotype Questionnaire. Temporal associations were analysed using a series of cross-lagged panel models. The best fitting and most parsimonious model indicated that a later chronotype at baseline predicts more severe insomnia symptoms at the 12-month follow-up after accounting for autoregressive effects. However, the opposite causal model, where baseline insomnia symptoms predicted the chronotype at the 12-month follow-up, was not supported. These findings suggest that a late chronotype may be a potential risk factor for the development of insomnia in young people, emphasising the importance of considering circadian factors in the prevention and treatment of sleep disturbances among this population.

Strengthening Neuroplasticity in Substance Use Recovery Through Lifestyle Intervention

The incidence of substance use and behavioral addictions continues to increase throughout the world. The Global Burden of Disease Study shows a growing impact in disability-adjusted life years due to substance use. Substance use impacts families, communities, health care, and legal systems; yet, the vast majority of individuals with substance use disorders do not seek treatment. Within the United States, new legislation has attempted to increase the availability of buprenorphine, but the impact of substance use continues. Although medications and group support therapy have been the mainstay of treatment for substance use, lifestyle medicine offers a valuable adjunct therapy that may help strengthen substance use recovery through healthy neuroplastic changes.

VC, Niez RA, Delos Santos FE, Magramo MM, Yap-Tan AR, Sy FAR, Kasimieh O. Predictors and Prevalence of Alcohol and Cannabis Co-use Among Filipino Adolescents: Evidence From a School-based Student Health Survey

OBJECTIVES

This study explored the prevalence and predictors of alcohol and cannabis co-use among 9263 Filipino adolescents, using data from the 2019 Global School-based Student Health Survey (GSHS).

METHODS

We conducted a cross-sectional secondary analysis of the GSHS, targeting adolescents aged 13-17 years and excluding cases with incomplete data on alcohol and cannabis use. Our analysis employed the bivariate chi-square test of independence and multivariable logistic regression using Stata version 18 to identify significant predictors of co-use, with a p-value threshold set at 0.05.

RESULTS

The weighted prevalence of co-users was 4.2% (95% confidence interval [CI], 3.4 to 5.3). Significant predictors included male sex (adjusted odds ratio [aOR], 4.50; 95% CI, 3.31 to 6.10; p<0.001) and being in a lower academic year, specifically grade 7 (aOR, 4.08; 95% CI, 2.39 to 6.99; p<0.001) and grade 8 (aOR, 2.20; 95% CI, 1.30 to 3.72; p=0.003). Poor sleep quality was also a significant predictor (aOR, 1.77; 95% CI, 1.29 to 2.44; p<0.001), as was a history of attempted suicide (aOR, 5.31; 95% CI, 4.00 to 7.06; p<0.001). Physical inactivity was associated with lower odds of co-use (aOR, 0.45; 95% CI, 0.33 to 0.62; p<0.001). Additionally, non-attendance of physical education classes (aOR, 1.48; 95% CI, 1.06 to 2.05; p=0.021), infrequent unapproved parental checks (aOR, 1.37; 95% CI, 1.04 to 1.80; p=0.024), and lower parental awareness of free-time activities (aOR, 0.63; 95% CI, 0.45 to 0.87; p=0.005) were associated with higher odds of co-use. Factors not significantly linked to co-use included age group, being in grade 9, always feeling lonely, having no close friends, being bullied outside school, and whether a parent or guardian understood the adolescent's worries.

CONCLUSIONS

The findings highlight the critical need for comprehensive interventions in the Philippines, addressing not only physical inactivity and parental monitoring but also focusing on sex, academic grade, participation in physical education classes, sleep quality, and suicide attempt history, to effectively reduce alcohol and cannabis co-use among adolescents.

Cannabinoid Use and Obstructive Sleep Apnea: A Retrospective Cohort Study

BACKGROUND

Obstructive sleep apnea (OSA) is a sleep disorder with no widely accepted pharmacological therapy. Cannabinoids have been suggested to reduce OSA severity in small human studies. The purpose of this retrospective cohort study was to explore the association of self-reported cannabis use on OSA severity and sleep parameters in a large cohort of adults undergoing in-laboratory polysomnography.

METHODS

Sleep and medication data were collected for all consecutive adults who completed diagnostic polysomnography at Sunnybrook Health Sciences Centre from 2010 to 2022. Multivariable linear regression models were employed that adjusted for age, sex, and BMI (minimally adjusted model), as well as medication and comorbidity data (maximally adjusted model). An exploratory subgroup analysis was additionally run in patients with moderate to severe OSA.

RESULTS

Of 6,958 individuals (mean age 54.7 ± 16.3, BMI 29.1 ± 6.8, 51.0% female), 71 reported cannabis use. In our minimally adjusted models, cannabis use predicted a reduced respiratory disturbance index (RDI) (β: -4.8 [95% CI: -9.4, -0.2]; p = 0.042); this association became nonsignificant in the fully adjusted models. In an exploratory analysis of patients with moderate to severe OSA (n = 613), cannabis use (n = 7) predicted increased stage N3 sleep (β: 33.5 [95% CI: 15.6, 51.4]; p < 0.001) and decreased REM sleep (β: 16.0 [95% CI: 0.3, 31.7]; p = 0.046).

CONCLUSION

Self-reported cannabis use was not associated with OSA severity after adjusting for confounders. In an exploratory subgroup analysis of patients with moderate to severe OSA, cannabis use impacted sleep architecture. Future studies should further explore these findings.

Leveraging big data for causal understanding in mental health: a research framework

Over the past 30 years there have been numerous large-scale and longitudinal psychiatric research efforts to improve our understanding and treatment of mental health conditions. However, despite the huge effort by the research community and considerable funding, we still lack a causal understanding of most mental health disorders. Consequently, the majority of psychiatric diagnosis and treatment still operates at the level of symptomatic experience, rather than measuring or addressing root causes. This results in a trial-and-error approach that is a poor fit to underlying causality with poor clinical outcomes. Here we discuss how a research framework that originates from exploration of causal factors, rather than symptom groupings, applied to large scale multi-dimensional data can help address some of the current challenges facing mental health research and, in turn, clinical outcomes. Firstly, we describe some of the challenges and complexities underpinning the search for causal drivers of mental health conditions, focusing on current approaches to the assessment and diagnosis of psychiatric disorders, the many-to-many mappings between symptoms and causes, the search for biomarkers of heterogeneous symptom groups, and the multiple, dynamically interacting variables that influence our psychology. Secondly, we put forward a causal-orientated framework in the context of two large-scale datasets arising from the Adolescent Brain Cognitive Development (ABCD) study, the largest long-term study of brain development and child health in the United States, and the Global Mind Project which is the largest database in the world of mental health profiles along with life context information from 1.4 million people across the globe. Finally, we describe how analytical and machine learning approaches such as clustering and causal inference can be used on datasets such as these to help elucidate a more causal understanding of mental health conditions to enable diagnostic approaches and preventative solutions that tackle mental health challenges at their root cause.

The effect of bullying victimization on sleep quality among Chinese medical students: Timing, duration, and patterns

BACKGROUND

Bullying victimization (BV) is a potential factor to sleep quality, but the role of BV characteristics in this association remains unclear. This study aimed to investigate correlation between the timing, duration, and patterns of BV and sleep quality among Chinese medical students.

METHODS

4035 participants (mean age of 19.2 ± 1.0) were recruited. BV patterns from pre-school to college were estimated using latent class analysis. Multinomial logistic regression was conducted to evaluate the odds ratio (OR) and 95 % confidence interval (CI) between sleep quality and BV. E values were used to assess unmeasured confounding.

RESULTS

Three patterns of BV were identified as follows: persistent BV (6.2 %), moderate BV (10.5 %), and low BV (83.3 %). BV during pre-school, elementary school, junior high school, senior high school, and college were all positively associated with poor sleep quality. The ORs were 2.30 (1.43-3.70), 3.00 (2.28-3.95), 2.71 (2.14-3.43), 3.34 (2.57-4.33) and 4.13 (3.19-5.36), respectively. The E value were 4.03 (2.21-NA), 5.45 (3.99-NA), 4.86 (3.70-NA), 6.14 (4.58-NA), 7.73 (5.83-NA), respectively. Those who experienced more periods of BV were more strongly associated with poor sleep quality, presenting a dose-response relationship [OR = 1.78, 95 % CI: 1.63-1.95, E value: 2.96 (2.64-NA)]. Those who experienced moderate BV [OR = 2.58, 95 % CI: 1.99-3.35; E value: 4.60 (3.39-NA)] and persistent BV [OR = 4.01, 95 % CI: 2.95-5.46; E value: 7.48(5.35-NA)] had higher odds of poor sleep quality.

LIMITATIONS

Retrospective design may introduce recall bias.

CONCLUSION

BV was positively related to poor sleep quality and chronic exposure to BV had a cumulative effect on poor sleep quality.