Andres De Los Reyes

Bio: Andres De Los Reyes is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Social anxiety & Mental health. The author has an hindex of 39, co-authored 130 publications receiving 8427 citations. Previous affiliations of Andres De Los Reyes include Yale University.

Informant discrepancies in the assessment of childhood psychopathology: a critical review, theoretical framework, and recommendations for further study.

Abstract: Discrepancies often exist among different informants' (e.g., parents, children, teachers) ratings of child psychopathology. Informant discrepancies have an impact on the assessment, classification, and treatment of childhood psychopathology. Empirical work has identified informant characteristics that may influence informant discrepancies. Limitations of previous work include inconsistent measurement of informant discrepancies and, perhaps most importantly, the absence of a theoretical framework to guide research. In this article, the authors present a theoretical framework (the Attribution Bias Context Model) to guide research and theory examining informant discrepancies in the clinic setting. Needed directions for future research and theory include theoretically driven attention to conceptualizing informant discrepancies across informant pairs (e.g., parent-teacher, mother-father, parent-child, teacher-child) as well as developing experimental approaches to decrease informant discrepancies in the clinic setting.

The validity of the multi-informant approach to assessing child and adolescent mental health.

Abstract: Child and adolescent patients may display mental health concerns within some contexts and not others (e.g., home vs. school). Thus, understanding the specific contexts in which patients display concerns may assist mental health professionals in tailoring treatments to patients' needs. Consequently, clinical assessments often include reports from multiple informants who vary in the contexts in which they observe patients' behavior (e.g., patients, parents, teachers). Previous meta-analyses indicate that informants' reports correlate at low-to-moderate magnitudes. However, is it valid to interpret low correspondence among reports as indicating that patients display concerns in some contexts and not others? We meta-analyzed 341 studies published between 1989 and 2014 that reported cross-informant correspondence estimates, and observed low-to-moderate correspondence (mean internalizing: r = .25; mean externalizing: r = .30; mean overall: r = .28). Informant pair, mental health domain, and measurement method moderated magnitudes of correspondence. These robust findings have informed the development of concepts for interpreting multi-informant assessments, allowing researchers to draw specific predictions about the incremental and construct validity of these assessments. In turn, we critically evaluated research on the incremental and construct validity of the multi-informant approach to clinical child and adolescent assessment. In so doing, we identify crucial gaps in knowledge for future research, and provide recommendations for "best practices" in using and interpreting multi-informant assessments in clinical work and research. This article has important implications for developing personalized approaches to clinical assessment, with the goal of informing techniques for tailoring treatments to target the specific contexts where patients display concerns. (PsycINFO Database Record

The Validity of the Multi-Informant Approach to Assessing Child and Adolescent Mental Health

Abstract: Child and adolescent patients may display mental health concerns within some contexts and not others (e.g., home vs. school). Thus, understanding the specific contexts in which patients display concerns may assist mental health professionals in tailoring treatments to patients’ needs. Consequently, clinical assessments often include reports from multiple informants who vary in the contexts in which they observe patients’ behavior (e.g., patients, parents, teachers). Previous meta-analyses indicate that informants’ reports correlate at low-to-moderate magnitudes. However, is it valid to interpret low correspondence among reports as indicating that patients display concerns in some contexts and not others? We meta-analyzed 341 studies published between 1989 and 2014 that reported cross-informant correspondence estimates, and observed low-to-moderate correspondence (mean internalizing: r = .25; mean externalizing: r = .30; mean overall: r = .28). Informant pair, mental health domain, and measurement method moderated magnitudes of correspondence. These robust findings have informed the development of concepts for interpreting multi-informant assessments, allowing researchers to draw specific predictions about the incremental and construct validity of these assessments. In turn, we critically evaluated research on the incremental and construct validity of the multi-informant approach to clinical child and adolescent assessment. In so doing, we identify crucial gaps in knowledge for future research, and provide recommendations for “best practices” in using and interpreting multi-informant assessments in clinical work and research. This article has important implications for developing personalized approaches to clinical assessment, with the goal of informing techniques for tailoring treatments to target the specific contexts where patients display concerns.

Introduction to the Special Section: More Than Measurement Error: Discovering Meaning Behind Informant Discrepancies in Clinical Assessments of Children and Adolescents

Abstract: Discrepancies often arise among multiple informants' reports of child and adolescent psychopathology and related constructs (e.g., parenting, family relationship quality and functioning, parental monitoring). Recently, studies using various designs (laboratory, longitudinal, randomized controlled trial, meta-analysis) have revealed that discrepancies among informants' reports (a) yield important information regarding where children express behaviors (time course, features of the context[s] of behavioral expression) and about the informants who observe their expression, (b) demonstrate stability over time in both community and clinic settings, (c) predict poor child and adolescent outcomes in ways that the individual informants' reports do not, and (d) can be used to identify meaningful treatment outcomes patterns within randomized controlled trials. Using existing data sources, the articles in this special section expand upon this emerging body of research. In particular, the articles illustrate how clinical science and practice can use informant discrepancies to increase understanding of the causes and consequences of, as well as treatments for, child and adolescent psychopathology.

Measuring Informant Discrepancies in Clinical Child Research.

Abstract: Discrepancies among informants' ratings of child psychopathology have important implications for diagnosis, assessment, and treatment. Typically, parents and children complete measures (e.g., self-report checklists, diagnostic instruments) to assess child dysfunction. Ratings gathered from these sources reveal relatively little agreement on the nature and extent of the child's social, emotional, and behavioral problems. This article reviews and illustrates the most frequently used methods of measuring informant discrepancies in the clinical child literature (i.e., raw difference, standardized difference, and residual difference scores) and outlines key considerations to influence their selection. The authors conclude that frequently used methods of measuring informant discrepancies are not interchangeable and recommend that future investigations examining informant discrepancies in clinical child research use the standardized difference score as their measure of informant discrepancies.

Using Multivariate Statistics

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An Introduction To The Event Related Potential Technique

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Informant discrepancies in the assessment of childhood psychopathology: a critical review, theoretical framework, and recommendations for further study.

Abstract: Discrepancies often exist among different informants' (e.g., parents, children, teachers) ratings of child psychopathology. Informant discrepancies have an impact on the assessment, classification, and treatment of childhood psychopathology. Empirical work has identified informant characteristics that may influence informant discrepancies. Limitations of previous work include inconsistent measurement of informant discrepancies and, perhaps most importantly, the absence of a theoretical framework to guide research. In this article, the authors present a theoretical framework (the Attribution Bias Context Model) to guide research and theory examining informant discrepancies in the clinic setting. Needed directions for future research and theory include theoretically driven attention to conceptualizing informant discrepancies across informant pairs (e.g., parent-teacher, mother-father, parent-child, teacher-child) as well as developing experimental approaches to decrease informant discrepancies in the clinic setting.

Linking "big" personality traits to anxiety, depressive, and substance use disorders: a meta-analysis.

Abstract: We performed a quantitative review of associations between the higher order personality traits in the Big Three and Big Five models (i.e., neuroticism, extraversion, disinhibition, conscientiousness, agreeableness, and openness) and specific depressive, anxiety, and substance use disorders (SUD) in adults. This approach resulted in 66 meta-analyses. The review included 175 studies published from 1980 to 2007, which yielded 851 effect sizes. For a given analysis, the number of studies ranged from three to 63 (total sample size ranged from 1,076 to 75,229). All diagnostic groups were high on neuroticism (mean Cohen's d = 1.65) and low on conscientiousness (mean d = -1.01). Many disorders also showed low extraversion, with the largest effect sizes for dysthymic disorder (d = -1.47) and social phobia (d = -1.31). Disinhibition was linked to only a few conditions, including SUD (d = 0.72). Finally, agreeableness and openness were largely unrelated to the analyzed diagnoses. Two conditions showed particularly distinct profiles: SUD, which was less related to neuroticism but more elevated on disinhibition and disagreeableness, and specific phobia, which displayed weaker links to all traits. Moderator analyses indicated that epidemiologic samples produced smaller effects than patient samples and that Eysenck's inventories showed weaker associations than NEO scales. In sum, we found that common mental disorders are strongly linked to personality and have similar trait profiles. Neuroticism was the strongest correlate across the board, but several other traits showed substantial effects independent of neuroticism. Greater attention to these constructs can significantly benefit psychopathology research and clinical practice.

Network Analysis: An Integrative Approach to the Structure of Psychopathology

Abstract: In network approaches to psychopathology, disorders result from the causal interplay between symptoms (e.g., worry → insomnia → fatigue), possibly involving feedback loops (e.g., a person may engage in substance abuse to forget the problems that arose due to substance abuse). The present review examines methodologies suited to identify such symptom networks and discusses network analysis techniques that may be used to extract clinically and scientifically useful information from such networks (e.g., which symptom is most central in a person's network). The authors also show how network analysis techniques may be used to construct simulation models that mimic symptom dynamics. Network approaches naturally explain the limited success of traditional research strategies, which are typically based on the idea that symptoms are manifestations of some common underlying factor, while offering promising methodological alternatives. In addition, these techniques may offer possibilities to guide and evaluate therape...