Agreement between Youth Self-Report and Biospecimen-Confirmed Substance Use: A Systematic Review

Adolescent risk behaviours are associated with educational attainment in early adulthood: results from the Raine Study cohort

BACKGROUND

Higher educational attainment is important for economic wellbeing and associated with better health and longevity. Previous research focused on intelligence, socioeconomic status and mental health or individual risk behaviours as predictors of educational attainment, but the role of multiple domains of adolescent risk behaviours is less clear. This study examined the association between multiple domains of risk behaviour in adolescence and educational attainment by 22 years-of-age.

METHODS

Young people (Generation 2, Gen2) and their parents (Generation 1, Gen1) participating in the Raine Study completed questionnaires at years 1, 5, 8, 10 (Gen1 only), 14, 17 (both) and 22 (Gen2 only). The Raine Study is an ongoing longitudinal study initiated in Perth, Western Australia, between 1989 and 1991. The 1,102 Gen2 participants who responded to questions about highest educational attainment were included in this study. The association between Gen2 self-reported risk behaviours (including age at commencement of drinking alcohol, smoking, sexual intercourse and drug use) and educational attainment (defined as self-reported years of completed high school: ≤10, 11, 12 or tertiary education (> 12)) at year 22, after adjusting for mother's age and combined parental education level, participant sex, and family income, educational performance and adolescent mental health, was explored using ordinal regression models and presented as odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

Ordinal models suggested that never smoking or starting older than 18 compared with smoking before age 15 (OR 2.02, 95%CI: 1.28-2.14); first drinking alcohol between 15 and 17 years compared with younger than 15 (OR 1.52, 95%CI: 1.08-2.14); and, first sexual intercourse aged ≥ 18 years compared with under 15 (OR 1.67, 95%CI: 1.08-2.57) were associated with higher levels of educational attainment at 22-year follow-up. Additionally, lower ("better") behavioural scores increased the odds of higher levels of attainment.

CONCLUSIONS

Absence of health risk behaviours at a younger age or later commencement was associated with higher educational attainment. Evidence-based interventions that address the societal influences underpinning risk behaviours in adolescents may support longer school retention.

Optimism, pessimism, and physical health among youth: a scoping review

OBJECTIVE

High levels of optimism (and low levels of pessimism) are associated with improved physical health in adults. However, relatively less is known about these relations in youth. The present study aimed to review the literature investigating optimism, pessimism, and physical health in children and adolescents from populations with and without health conditions.

METHODS

We conducted a scoping review up until February 2024. Studies were included if they sampled youth (average age ≤18 years) and treated optimism or pessimism as predictors of health behaviors or outcomes. Data on study and sample characteristics, health outcome, optimism construct, and findings were extracted from eligible papers and results were synthesized.

RESULTS

Sixty studies were retained. Most studies were conducted in North America, with adolescents, and used cross-sectional designs and self-reported measures of health. Measures of optimism and pessimism differed across studies. Roughly one-third of studies sampled medical populations. Health categories included substance use, diet and physical activity, sexual health practices, medical adherence, other health behaviors, cardiometabolic health, subjective health/health-related quality of life, pain, sleep, and oral health. Generally, we observed adaptive associations between optimism and health. Higher optimism and lower pessimism were most consistently associated with lower rates of substance use and lower cardiometabolic risk.

CONCLUSIONS

The presence of optimism or the absence of pessimism appears to be associated with various adaptive health outcomes among youth with and without health conditions. Developmental, methodological, and clinical considerations for future research are discussed, such as conducting longitudinal studies with objective measures of health and psychometrically validated instruments.

Adolescent substance use initiation and long-term neurobiological outcomes: insights, challenges and opportunities

The increased frequency of risk taking behavior combined with marked neuromaturation has positioned adolescence as a focal point of research into the neural causes and consequences of substance use. However, little work has provided a summary of the links between adolescent initiated substance use and longer-term brain outcomes. Here we review studies exploring the long-term effects of adolescent-initiated substance use with structural and microstructural neuroimaging. A quarter of all studies reviewed conducted repeated neuroimaging assessments. Long-term alcohol use, as well as tobacco use were consistently associated with smaller frontal cortices and altered white matter microstructure. This association was mostly observed in the ACC, insula and subcortical regions in alcohol users, and for the OFC in tobacco users. Long-term cannabis use was mostly related to altered frontal cortices and hippocampal volumes. Interestingly, cannabis users scanned more years after use initiation tended to show smaller measures of these regions, whereas those with fewer years since initiation showed larger measures. Long-term stimulant use tended to show a similar trend as cannabis in terms of years since initiation in measures of the putamen, insula and frontal cortex. Long-term opioid use was mostly associated with smaller subcortical and insular volumes. Of note, null findings were reported in all substance use categories, most often in cannabis use studies. In the context of the large variety in study designs, substance use assessment, methods, and sample characteristics, we provide recommendations on how to interpret these findings, and considerations for future studies.

Prevalence and correlates of appearance- and performance-enhancing drugs and substances use among a national sample of college students aged 18-30

Objective: To identify the lifetime prevalence and correlates of appearance- and performance-enhancing drugs and substances (APEDS) use among a national sample of US college and university students. Participants: Student participants from the 2020-2021 Healthy Minds Study (N = 7,401; ages 18-30 years). Methods: Lifetime prevalence of five forms of APEDS was estimated. Modified Poisson regression analyses were conducted to determine the sociodemographic correlates of protein and creatine supplement use. Results: Lifetime protein (23.8%) and creatine (7.7%) supplement use were most common among the sample. Older age within young adulthood, male sex, perceiving oneself to be normal weight or somewhat overweight, any athletics participation, and 2-3 or ≥ 5 h/week of exercise were associated with greater likelihood of lifetime protein and creatine supplement use. Conclusions: Awareness and prevention efforts on the potential harms of APEDS use are needed on campuses, particularly among males and those who participate in athletics and high-frequency exercise.

Editorial: Inconclusive (or "Elusive"): Concordance Between Substance Use Self-report and Toxicology for Diverse Youth Populations

Adolescent substance use is an important public health issue, with 15% of eighth graders (ages 13-14) reporting past-year cannabis use, 26% reporting alcohol use, and 23% reporting vaping nicotine in recent national surveys.1 Among youth and young adults in need of mental health services, co-occurring substance misuse is a topic of particular importance. This is particularly evident in special populations, such as youth in juvenile detention, youth living in rural communities, and youth in residential or foster care. Accurate drug use identification is necessary to determine substance use needs and sequelae in youth. Ideally, this is accomplished through a combination of self-report and toxicological biospecimen analysis, such as the use of hair toxicology. Yet, the consistency between self-reported substance use and robust toxicological analysis is understudied and has not been researched in large, diverse samples of youth. This has implications for both public health research and clinical practice. Of particular importance for research on health disparities in substance abuse problems and treatment is the likely possibility that reporting validity often varies by race/ethnicity and by other important subgroupings.

Concordance between substance use self-report and hair analysis in community-based adolescents

Background: Accurate drug use identification through subjective self-report and toxicological biosample (hair) analysis are necessary to determine substance use sequelae in youth. Yet consistency between self-reported substance use and robust, toxicological analysis in a large sample of youth is understudied.Objectives: We aim to assess concordance between self-reported substance use and hair toxicological analysis in community-based adolescents.Methods: Hair results by LC-MS/MS and GC-MS/MS and self-reported past-year substance use from an Adolescent Brain Cognitive Development (ABCD) Study subsample (N = 1,390; ages 9-13; 48% female) were compared. The participants were selected for hair selection through two methods: high scores on a substance risk algorithm selected 93%; 7% were low-risk, randomly selected participants. Kappa coefficients the examined concordance between self-report and hair results.Results: 10% of youth self-reported any past-year substance use (e.g. alcohol, cannabis, nicotine, and opiates), while a mostly non-overlapping 10% had hair results indicating recent substance use (cannabis, alcohol, non-prescription amphetamines, cocaine, nicotine, opiates, and fentanyl). In randomly selected low-risk cases, 7% were confirmed positive in hair. Combining methods, 19% of the sample self-reported substance use and/or had a positive hair sample. Kappa coefficient of concordance between self-report and hair results was low (kappa = 0.07; p = .007).Conclusions: Hair toxicology identified substance use in high-risk and low-risk ABCD cohort subsamples. Given low concordance between hair results and self-report, reliance on either method alone would incorrectly categorize 9% as non-users. Multiple methods for characterizing substance use history in youth improves accuracy. Larger representative samples are needed to assess the prevalence of substance use in youth.

Wearable Sensor and Mobile App-based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study (Preprint)

BACKGROUND

Digital health technologies using mobile apps and wearable devices are a promising approach to the investigation of substance use in the real world and for the analysis of predictive factors or harms from substance use. Moreover, consecutive repeated data collection enables the development of predictive algorithms for substance use by machine learning methods.

OBJECTIVE

We developed a new self-monitoring mobile app to record daily substance use, triggers, and cravings. Additionally, a wearable activity tracker (Fitbit) was used to collect objective biological and behavioral data before, during, and after substance use. This study aims to describe a model using machine learning methods to determine substance use.

METHODS

This study is an ongoing observational study using a Fitbit and a self-monitoring app. Participants of this study were people with health risks due to alcohol or methamphetamine use. They were required to record their daily substance use and related factors on the self-monitoring app and to always wear a Fitbit for 8 weeks, which collected the following data: (1) heart rate per minute, (2) sleep duration per day, (3) sleep stages per day, (4) the number of steps per day, and (5) the amount of physical activity per day. Fitbit data will first be visualized for data analysis to confirm typical Fitbit data patterns for individual users. Next, machine learning and statistical analysis methods will be performed to create a detection model for substance use based on the combined Fitbit and self-monitoring data. The model will be tested based on 5-fold cross-validation, and further preprocessing and machine learning methods will be conducted based on the preliminary results. The usability and feasibility of this approach will also be evaluated.

RESULTS

Enrollment for the trial began in September 2020, and the data collection finished in April 2021. In total, 13 people with methamphetamine use disorder and 36 with alcohol problems participated in this study. The severity of methamphetamine or alcohol use disorder assessed by the Drug Abuse Screening Test-10 or the Alcohol Use Disorders Identification Test-10 was moderate to severe. The anticipated results of this study include understanding the physiological and behavioral data before, during, and after alcohol or methamphetamine use and identifying individual patterns of behavior.

CONCLUSIONS

Real-time data on daily life among people with substance use problems were collected in this study. This new approach to data collection might be helpful because of its high confidentiality and convenience. The findings of this study will provide data to support the development of interventions to reduce alcohol and methamphetamine use and associated negative consequences.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/44275.