Feasibility of combining biosensor and ecological momentary assessment to measure stress experiences among economically disadvantaged adolescents.

Adolescent stress is complex and impairing. Novel measures are needed to understand stress variability within individuals over time from a physiological as well as a subjective perspective. To test the feasibility of combining ecological momentary assessment (EMA) and wearable biosensors to assess adolescent stress, using an idiographic approach with experience sampling methods. A small sample (n = 23) of predominantly African American, economically disadvantaged adolescents were asked to complete EMA surveys four times per day and wear an armband measuring Heart rate (HR) and skin response for a 2-week period. Descriptive analyses examined number of hours of armband wear, percentage of viable data, and percentage of surveys completed by gender and race. Associations between biosensor data and EMA reports within and across individuals were also examined using hierarchical linear regression. EMA survey completion was good (81%) as was adherence to biosensor protocols, although technological difficulties interfered with collection of HR variability for youth with darker skin tones. Youth reported stressful events in 12.79% of EMA surveys, although 43% reported no negative mood experiences. Convergent validity was supported for detecting between-person (EMA) and within-person (EMA and biosensors) variability in stress across time, although associations across youth were highly variable. Results suggest value for biobehavioral methods in understanding day-to-day stress in adolescents but highlight variability in stress experiences as well as technological limitations, especially for youth of colour.

Power analysis for idiographic (within-subject) clinical trials: Implications for treatments of rare conditions and precision medicine.

Power analysis informs a priori planning of behavioral and medical research, including for randomized clinical trials that are nomothetic (i.e., studies designed to infer results to the general population based on interindividual variabilities). Far fewer investigations and resources are available for power analysis of clinical trials that follow an idiographic approach, which emphasizes intraindividual variabilities between baseline (control) phase versus one or more treatment phases. We tested the impact on statistical power to detect treatment outcomes of four idiographic trial design factors that are under researchers' control, assuming a multiple baseline design: sample size, number of observations per participant, proportion of observations in the baseline phase, and competing statistical models (i.e., hierarchical modeling versus piecewise regression). We also tested the impact of four factors that are largely outside of researchers' control: population size, proportion of intraindividual variability due to residual error, treatment effect size, and form of outcomes during the treatment phase (phase jump versus gradual change). Monte Carlo simulations using all combinations of the factors were sampled with replacement from finite populations of 200, 1750, and 3500 participants. Analyses characterized the unique relative impact of each factor individually and all two-factor combinations, holding all others constant. Each factor impacted power, with the greatest impact being from larger treatment effect sizes, followed respectively by more observations per participant, larger samples, less residual variance, and the unexpected improvement in power associated with assigning closer to 50% of observations to the baseline phase. This study's techniques and R package better enable a priori rigorous design of idiographic clinical trials for rare diseases, precision medicine, and other small-sample studies.

Addressing Barriers to Primary Care Screening and Referral to Prevention for Youth Risky Health Behaviors: Evidence Regarding Potential Cost-Savings and Provider Concerns.

Despite growing evidence and support for co-locating behavioral services in primary care to prevent risky health behaviors, implementation of these services has been limited due to a lack of reimbursement for services and negative perceptions among providers. We investigated potential to overcome these barriers based on new developments in healthcare funding and screening and referral to prevention (SRP) in primary care based on the Consolidated Framework for Implementation Research (CFIR), which could guide future SRP implementation strategies. To investigate the economic need for healthcare-based SRP, we quantified hospital charges to healthcare payors for services arising from adolescent risky behaviors (e.g., substance use, risky sex). Annual North Carolina (NC) hospital charges for these services exceeded $327 M (2019 dollars), suggesting high potential for cost savings if SRP can curb hospital services associated with risky behaviors. To investigate provider barriers and facilitators, we surveyed 151 NC pediatricians and 230 NC family therapists about their attitudes regarding a recently developed well-child visit SRP with family-based prevention. Both sets of professionals reported widespread need for and interest in the SRP but cited barriers of lack of reimbursement, training, and referrals to/from each other. Physicians, but not family therapists, reported concerns with poor patient or parent compliance. Many barriers could be resolved by co-locating family therapists in pediatric clinics to conduct well-child SRP. Our results support further research to develop business models for payor-funded SRP and CFIR-guided research to develop implementation strategies for primary care SRP to prevent adolescent risky health behaviors.

Could a continuous measure of individual transmissible risk be useful in clinical assessment of substance use disorder? Findings from the National Epidemiological Survey on Alcohol and Related Conditions.

OBJECTIVE: Toward meeting the need for a measure of individual differences in substance use disorder (SUD) liability that is grounded in the multifactorial model of SUD transmission, this investigation tested to what degree transmissible SUD risk is better measured using the continuous Transmissible Liability Index (TLI) (young adult version) compared to alternative contemporary clinical methods. METHOD: Data from 9535 18- to 30-year-olds in the 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions, a U.S. representative sample, were used to compute TLI scores and test hypotheses. Other variables were SUDs of each DSM-IV drug class, clinical predictors of SUD treatment outcomes, treatment seeking and usage, age of onset of SUDs and substance use (SU), and eligibility for SUD clinical trials. RESULTS: TLI scores account for variation in SUD risk over and above parental lifetime SUD, conduct and antisocial personality disorder criteria and frequency of SU. SUD risk increases two- to four-fold per standard deviation increment in TLI scores. The TLI is associated with SUD treatment seeking and usage, younger age of onset of SU and SUD, and exclusion from traditional clinical trials of SUD treatment. CONCLUSIONS: The TLI can identify persons with high versus low transmissible SUD risk, worse prognosis of SUD recovery and to whom extant SUD clinical trials results may not generalize. Recreating TLI scores in extant datasets facilitates etiology and applied research on the full range of transmissible SUD risk in development, treatment and recovery without obtaining new samples.

Psychometrics and Cross-Cultural Comparisons of the Illustration-Based Assessment of Liability and Exposure to Substance Use and Antisocial Behavior© for Children.

Elementary school-age child report instruments that do not require reading or interviews are lacking. In four samples, psychometric estimates for 5- to 9-year-olds were obtained for the Assessment of Liability and Exposure to Substance use and Antisocial behavior© (ALEXSA©), a child-report instrument that can be completed even by illiterate children. Invariance between minority groups vs Caucasians also was tested. Samples were: high-risk, low SES African-Americans (n=337), youth of varied ethnicities experiencing chronic stress (n=209), Mexican migrants in a reading remediation program (n=45), and U.S. twins (42 pairs) who were nearly all Caucasian. Validity criteria consisted of child-, parent-, teacher- and research evaluator-ratings on previously developed research and clinical instruments. Replicating results with older samples, ALEXSA factors had adequate or better reliabilities and demonstrated validity in all four studies. Ethnic invariance was found except for differences that were expected due to migrant's after-school program. In sum, psychometrics of the ALEXSA were supported for 5- to 9-year-olds of varied races/ethnicities, risk levels and academic skills.

The illustration-based Assessment of Liability and EXposure to Substance use and Antisocial behavior for children.

BACKGROUND/OBJECTIVES: Ontogenetic prevention of substance abuse requires that an individual's "profile" of substance abuse predictors is assessed to guide intervention decision-making ( [1] ). For child intervention, self-report data provide information that cannot be obtained from other sources such as parents or teachers. However, efficient child report instruments of substance abuse risk factors are lacking. The Assessment of Liability and EXposure to Substance use and Antisocial behavior((c)) (ALEXSA((c))) is an illustration-based, computerized child report assessment for early manifestations and predictors of substance abuse and antisocial behavior. METHODS: Construct validity and test-retest reliabilities of ALEXSA subscales were estimated in 272 nine to twelve-year old students from regular and remedial education classrooms. RESULTS: Anecdotal and quantitative data demonstrated that children enjoy the ALEXSA format. All factors and 34 of 39 subscales had good or better reliabilities. Nine factors were extracted: Disinhibition (example subscales are Irritability, Impulsivity), Sensation Seeking (e.g., Gambling, Social Disinhibition), Self Management (e.g., Planning and Concentration, Problem Solving), Family Discord (e.g., Family Behavior Problems, Family Conflict), Parent Fortification (e.g., Parental Monitoring, Parent Attachment), Social Contagion (e.g., Friends' Conduct Disorder Criteria, Peer Pressure Susceptibility), Social Support (e.g., Social Support: Adults, Number of Friends), Neighborhood Risks (e.g., Gang Exposure, Neighborhood Atmosphere), and School Protection (e.g., Academic Competency, School Commitment). SCIENTIFIC SIGNIFICANCE: The ALEXSA could provide efficient child reports for research, needs assessment, and outcomes to support etiology and prevention of substance abuse and antisocial behavior.

Using correlational analyses to improve prevention strategies based on survey data from youth.

Community coalition prevention models often select interventions based on the types of risk factors (outcome predictors) that are elevated. Variances and correlations between predictors and targeted behaviors also may vary between communities and provide information to improve the selection of interventions. Community differences in risk factor levels and correlations between predictors and problem behaviors were examined using a child self-report computer assessment (ALEXSA); prevention.psu.edu/people/ALEXSA.htm). Three school-based subsamples of children were studied. Means, prevalences, and correlations differed significantly between samples. Discussion addresses developmental considerations and illustrates how correlations between predictors and problem behaviors might improve the selection of interventions. This study is preliminary and should be replicated with larger community samples, more indicated/selected sample, and in more communities.

Utility analysis for clinical decision-making in small treatment settings.

Data-driven clinical decision-making can be difficult in settings that service relatively few patients because of the small samples available, the patients' potential dissimilarity from participants in published research, and highly limited resources. This study was designed to demonstrate how utility analyses might assist clinical decision-making in small treatment settings and provide data for promoting programmatic improvements. Data came from a study to identify rural juvenile delinquents suspected to not benefit from residential behavioral treatment. A prospective correlational design was used with data from a midwestern juvenile criminal justice residential unit in which about 30 males were treated annually. Outcomes included treatment performance measures and number of delinquent offenses during the year after treatment. Utility analyses suggested that delinquents who were less likely to benefit from residential treatment could be identified a priori using a modified Psychopathy Checklist, Revised. Cost utility analysis estimated $180,000 less would be spent on residential treatment as a result of selecting residents based on the pretreatment assessment. This money might be reallocated toward alternative intervention for delinquents who are not likely to benefit from the residential treatment. More importantly, results suggested specific alternative interventions for the delinquents who were less likely to benefit from the treatment by providing direct links to existing literature. Advantages of utility analysis research include strong external validity, minimal interference with treatment during data collection, results that estimate clinical and practical significance, and results that are easily communicated to laymen.