Psychological Assessment最新文献

Missing observations in intensive longitudinal data may be attributable to between-person differences and within-person states, either of which may systematically bias assessment of associations between predictors and outcomes. We examined this issue in intensive longitudinal data from people receiving medication for opioid use disorder (n = 306), each of whom was asked to provide an end-of-day (EOD) report via smartphone every night for 8 weeks, along with thrice-daily randomly prompted reports (person-moments = 39,321). We examined whether missing EOD reports were associated with mood, stress, craving, and substance use, estimated both as within-person changes (in random-prompt entries) and between-person characteristics (means across random-prompt entries). Between-person characteristics were the strongest correlates of missing EOD reports, though the magnitudes of the associations were modest. Greater likelihood of missingness was associated with greater mean low-arousal mood (i.e., fatigue; OR = 1.13, 95% CI [1.01, 1.27]), stress (OR = 1.14, 95% CI [1.02, 1.28]) and proportions of random-prompt entries with heroin craving (OR = 1.14, 95% CI [1.02, 1.27]). Within participants, the likelihood of a missing EOD report decreased when positive mood was higher than typical (OR = 0.82, 95% CI [0.68, 0.99]). We conclude that people who tend to have more difficult day-to-day experiences (i.e., higher stress, craving), and moments when people's moods are more positive, may contribute to under- or overestimation of effects tested in EOD data. The adaptive delivery of surveys based on person- and prompt-level characteristics (i.e., following elevated positive moods) could be one approach to maximizing survey completion. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

The purpose of this study is to investigate the factor structure of the Alabama Parenting Questionnaire-9 (APQ-9) in a clinical service-seeking population. The present study utilized data from 544 caregivers of children presenting to a psychological clinic in the southeastern United States to examine the factor structure of the APQ-9. Structural and measurement models of the APQ-9 were produced using a structural equation modeling approach to confirmatory factor analysis. The structural model demonstrated acceptable fit to a three-factor model structure. Three factors (Positive Parenting, Inconsistent Discipline, and Poor Supervision) yielded significant associations between factors. Results provide psychometric validation for the APQ-9 in a clinical services-seeking population. The measurement model indicated that only Inconsistent Discipline and Poor Supervision were significantly associated with externalizing symptoms. Given these results, clinicians may feel confident using the APQ-9 in their clinical practice as a valid indicator of the parenting experience prior to providing clinical services and thereby accurately evaluate ways to improve parent and child well-being. Further research is necessary to examine associations between the three factors and externalizing behaviors. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Risk assessments are often mandated within the juvenile justice system (JJS). Yet, it is unclear whether these protocols reflect equitable clinical tools, and little is known about the community's perspectives on commonly assessed risk domains. In response, we introduced, and subsequently tested, a multifaceted definition for fairness in risk assessment. An embedded mixed-method study was conducted, such that Study 1 informed Study 2's methods, and the studies were subsequently integrated. In Study 1, caregivers (N = 22) and adolescents (N = 21; Mage = 14.28; 42.9% identified as Black, 42.6% White; 66.7% Male) involved with a JJS-diversion or probation program completed qualitative interviews on risk domains for offending behavior. Next, we examined the statistical fairness of salient risk domains from Study 1 in a sample of JJS-involved adolescents (N = 1,354; Mage = 16.04; 41.4% Black, 33.5% Hispanic, 20.2% White; 86.4% as male). An evidence-based medicine analytic approach, which was compared to artificial neural networks, tested subpopulation differences across performance indices. Overall, temperament, peer relations, cognitive styles, and school functioning emerged as salient risk domain themes across identities and informants. Subsequently, moral disengagement and delinquent peers emerged as equitable predictors of prospective violent and nonviolent rule-breaking behavior. A model comprised of these predictors was acceptable (i.e., areas under the curves ≥ 0.70; diagnostic likelihood ratios ≥ 2.0) and equitable. Artificial neural network models did not improve prediction. Risk assessments focused on moral disengagement and peer delinquency may lead to community-aligned and statistically fair assessment processes. These findings can lead to more equitable and engaging JJS risk-management approach. (PsycInfo Database Record (c) 2026 APA, all rights reserved).