Understanding At-Risk Youths: Average PAI-A Scores and Their Associations with Impulsivity-Related Constructs

Scoping Review: Transdiagnostic Measurement of Impulsivity Domains in Youth Using the UPPS Impulsive Behavior Scales

OBJECTIVE

Impulsivity contributes to many clinically relevant behaviors impacting youth. A scoping review was conducted to characterize existing research using the Urgency, Premeditation (lack of), Perseverance (lack of), Sensation Seeking (UPPS) Impulsive Behavior Scales in youth populations, to review the psychometric and validity data of UPPS, and to summarize findings related to sex/gender and diagnostic populations of youth.

METHOD

PubMed, Embase, and PsycNET databases were searched from January 1, 2001 (original UPPS publication) through October 2, 2022, according to PRISMA extension for Scoping Reviews guidelines. Articles were reviewed for inclusion/exclusion by 2 authors. Original research articles in English using any UPPS version or subscale in persons aged ≤21 years were included.

RESULTS

Inclusion criteria were met by 45 articles, with low bias and moderate-to-high quality. Most were cross-sectional studies; studies investigated diverse community and clinical samples. The UPPS demonstrated consistent factor structure, good reliability, and good external validity with other measures of impulsive behaviors and conditions associated with impaired impulse control. Some studies observed differences in UPPS domain scores between sex/gender groups or differential patterns in relationships between UPPS domains and clinical variables. UPPS subscale scores often differed in youth with attention-deficit/hyperactivity disorder, conduct disorders, substance use, and excess weight/obesity compared with control youth. UPPS domains commonly had interactions with sex/gender, sociodemographic, and diagnosis-related variables.

CONCLUSION

The current literature suggests that the UPPS has utility in measuring distinct components of impulsivity in clinical and nonclinical populations of youth. Specificity in discriminating diagnostic groups and predicting risk currently remains uncertain. Further research is needed to integrate UPPS measures with experimental models and additional neurobiological methods and to assess longitudinal developmental trajectories.

PLAIN LANGUAGE SUMMARY

Impulsivity contributes to many clinically relevant behaviors and mental health disorders that impact youth. The Urgency, Premeditation, Perseverance, Sensation Seeking (UPPS) Impulsive Behavior Scale has been increasingly used in research to measure deficits in impulse control. In this scoping review the authors examined 45 studies that used versions of the UPPS to measure different domains of impulsivity in youth aged 21 years and younger. The authors found evidence in the literature for the validity and reliability of the UPPS and its variants in measuring impulsivity in youth. Certain patterns of UPPS subscale scores corresponded with clinical behaviors and diagnoses including attention-deficit/hyperactivity disorder (ADHD), conduct disorder, substance use, and excessive weight/obesity. Despite this, there remain gaps in the literature regarding the stability of UPPS measures over time and ability of the UPPS to predict clinical outcomes.

Test-Retest Reliability of Self-Reported Substance Use and Sexual Risk Behavior Among at-Risk Adolescents

Adolescents often engage in behaviors such as substance use and risky sexual activity that can lead to negative health and psychological consequences for themselves and others. Accurate measurement of these behaviors in surveys is challenging given that the behaviors are often viewed as undesirable and/or are illegal, so it is important to test the psychometric properties of instruments used to assess adolescent risk behaviors. The current study aimed to assess the test-retest reliability of a widely used measure of youth risk-taking behavior, the Youth Risk Behavior Survey (YRBS). A sample of 156 at-risk adolescents aged 16-18 years (81% male; 61% White) completed the YRBS retrospectively across intervals ranging from 3 to 12 days during their stay in a residential program at which they were under close supervision and had limited ability to engage in new risk behaviors. Participants were asked to complete the YRBS based on their "typical" (pre-program) behavior at both administrations, which were 10-14 weeks into their stay. The reliability of responses was assessed using kappa and weighted kappa analyses. Findings indicate moderate to substantial reliability for nearly all items, suggesting that at-risk youth reliably reported their engagement in health risk behaviors across multiple administrations and supporting the psychometric strength of the YRBS measure for use with this population.

Evaluating Measures of Externalizing Personality Pathology Traits in Black and White American Adolescents in a Program for at-Risk Youths

Adolescent personality assessment measures can aid in the identification of traits that are associated with various types of maladjustment. Externalizing personality pathology traits (e.g., antisocial, borderline, and narcissistic personality disorder features) are particularly relevant for many problematic outcomes, yet measures that assess these traits have not been validated extensively in diverse samples. The present study aimed to examine the properties of measures of externalizing personality pathology traits in a sample of White (n = 184) and Black (n = 99) adolescents participating in a residential program for at-risk youth. The fit of the proposed structure for these measures was tested in the sample as a whole and in each racial group separately. Associations between these measures and the count of disciplinary infractions received while in the program were also tested. Measures were found to have less than optimal fit in this sample, especially among Black adolescents. Suggestions for future research and clinical use of these measures are discussed.

Using the Personality Assessment Inventory-Adolescent in Legal Settings

The Personality Assessment Inventory-Adolescent (PAI-A; Morey et al., 2007) is a self-report measure of personality and psychopathology appropriate for use with individuals aged 12-18. It is modeled after the Personality Assessment Inventory (PAI; Morey, 1991), a measure widely used with adults in clinical and legal settings. The PAI-A assesses a variety of features that have utility in legal settings, including validity scales that assess approach to testing, clinical scales measuring common types of psychopathology, and treatment consideration scales that provide indicators of treatment motivation and other factors that may be important for predicting outcomes. The PAI-A has been included in a limited number of research studies and few of those have focused on justice-involved youths. Additionally, because juvenile court records are not typically publicly available, there is limited information about the PAI-A available in case law. This manuscript reviews the properties, strengths, and weaknesses of the PAI-A and its existing literature. Factors for mental health and legal professionals to consider in relation to the admissibility of this measure, questioning and cross-examination, and how the PAI-A may be received in court are also discussed.

Classification of Adolescent Psychiatric Patients at High Risk of Suicide Using the Personality Assessment Inventory by Machine Learning

OBJECTIVE

There are growing interests on suicide risk screening in clinical settings and classifying high-risk groups of suicide with suicidal ideation is crucial for a more effective suicide preventive intervention. Previous statistical techniques were limited because they tried to predict suicide risk using a simple algorithm. Machine learning differs from the traditional statistical techniques in that it generates the most optimal algorithm from various predictors.

METHODS

We aim to analyze the Personality Assessment Inventory (PAI) profiles of child and adolescent patients who received outpatient psychiatric care using machine learning techniques, such as logistic regression (LR), random forest (RF), artificial neural network (ANN), support vector machine (SVM), and extreme gradient boosting (XGB), to develop and validate a classification model for individuals with high suicide risk.

RESULTS

We developed prediction models using seven relevant features calculated by Boruta algorithm and subsequently tested all models using the testing dataset. The area under the ROC curve of these models were above 0.9 and the RF model exhibited the best performance.

CONCLUSION

Suicide must be assessed based on multiple aspects, and although Personality Assessment Inventory for Adolescent assess an array of domains, further research is needed for predicting high suicide risk groups.