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Empirically derived patterns of psychiatric symptoms in youth: A latent profile analysis.

ABSTRACT: BACKGROUND:By conceptualizing domains of behavior transdiagnostically, the National Institute of Mental Health Research Domain Criteria (NIMH RDoC) initiative facilitates new ways of studying psychiatric symptoms. In this study, latent profile analysis (LPA) was used to empirically derive classes or patterns of psychiatric symptoms in youth that transect traditional nosologic boundaries. METHODS:Data were drawn from 509 children and adolescents (ages 7-18 years; mean age =12.9 years; 54% male) who were evaluated in the NIMH Emotion and Development Branch and were heterogeneous with respect to presenting diagnoses and symptoms. Youth and/or their parents completed measures of several core symptom dimensions: irritability, anxiety, depression, and attention deficit hyperactivity disorder (ADHD). LPA was used to parse response patterns into distinct classes, based on the levels of, and interrelations among, scores on the different measures. RESULTS:Five classes emerged: low levels of symptomatology (52% of sample); anxiety and mild depressive symptoms (17%); parent-reported irritability and ADHD (16%); irritability and mixed comorbid symptoms (10%); and high levels of irritability, anxiety, depression, and ADHD (5%). Importantly, these latent classes cut across informants and the clinical conditions for which youth were initially evaluated. Further, the classes characterized by irritability exhibited the poorest overall functioning. LIMITATIONS:These data were cross-sectional. Examination of external validators, including neurobiological correlates and symptom course, is warranted. CONCLUSIONS:Results inform our understanding of the structure of psychiatric symptoms in youth and suggest new ways to operationalize psychopathology and examine it in relation to neurobiology.

SUBMITTER: Kircanski K

PROVIDER: S-EPMC5360533 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Empirically derived patterns of psychiatric symptoms in youth: A latent profile analysis.

Kircanski Katharina K Zhang Susan S Stringaris Argyris A Wiggins Jillian Lee JL Towbin Kenneth E KE Pine Daniel S DS Leibenluft Ellen E Brotman Melissa A MA

Journal of affective disorders 20160921

<h4>Background</h4>By conceptualizing domains of behavior transdiagnostically, the National Institute of Mental Health Research Domain Criteria (NIMH RDoC) initiative facilitates new ways of studying psychiatric symptoms. In this study, latent profile analysis (LPA) was used to empirically derive classes or patterns of psychiatric symptoms in youth that transect traditional nosologic boundaries.<h4>Methods</h4>Data were drawn from 509 children and adolescents (ages 7-18 years; mean age =12.9 yea ...[more]

PMID: 27692699

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Project description:Engagement is a key metric that researchers can use to assess whether participants received the intended dose of a digital health intervention. However, the prevailing approach has predominantly focused on individual paradata metrics, resulting in a fragmented understanding of overall engagement. To address this limitation, our study utilizes person-centered approaches that allow for the simultaneous capture of multiple engagement metrics within imi-a web application specifically designed to support the mental health of lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority youth (LGBTQ+ youth). This person-centered approach enabled us to explore the association between engagement patterns and stress appraisal outcomes within the imi intervention arm. Utilizing latent profile analysis, we classified users into two engagement forms: overall engagement (total number of sessions, pages visited, and external links clicked and their cumulative time spent using imi) and content engagement (number of pages viewed across imi's four core guides: gender, stress, queerness, and stigma). We identified two profiles for each form: a "high engagement" profile and an "average engagement" profile, with the majority of participants assigned to the "average engagement" profile. Our analyses revealed a significant association between overall engagement profiles and stress appraisals, with the "high engagement" profile demonstrating higher challenge appraisals and marginal improvements in threat appraisals compared to the "average engagement" profile. However, no such associations were observed for content engagement profiles and stress appraisal outcomes. The two person-centered approaches used were consistent with prior results utilizing a variable-centered approach, indicating a stronger intervention effect among individuals who exhibit higher engagement in digital health interventions. Although both methods yielded comparable findings, the person-centered approach mitigates concerns related to multi-collinearity and adds additional nuance and context to the study of digital engagement.

Project description:BackgroundLatent class models (LCMs) have been used in exploring dietary behaviors over a wide set of foods and beverages in a given population, but are prone to overgeneralize these habits in the presence of variation by subpopulations.ObjectivesThis study aimed to highlight unique dietary consumption differences by both study site and ethnic background of Hispanic/Latino populations in the United States, that otherwise might be missed in a traditional LCM of the overall population. This was achieved using a new model-based clustering method, referred to as robust profile clustering (RPC).MethodsA total of 11,320 individuals aged 18-74 y from the Hispanic Community Health Study/Study of Latinos (2008-2011) with complete diet data were classified into 9 subpopulations, defined by study site (Bronx, Chicago, Miami, San Diego) and ethnic background. At baseline, dietary intake was ascertained using a food propensity questionnaire. Dietary patterns were derived from 132 food groups using the RPC method to identify patterns of the general Hispanic/Latino population and those specific to an identified subpopulation. Dietary patterns derived from the RPC were compared to those identified from an LCM.ResultsThe LCM identified 48 shared consumption behaviors of foods and beverages across the entire cohort, whereas significant consumption differences in subpopulations were identified in the RPC model for these same foods. Several foods were common within study site (e.g., chicken, orange juice, milk), ethnic background (e.g., papayas, plantain, coffee), or both (e.g., rice, tomatoes, seafood). Post hoc testing revealed an improved model fit in the RPC model [Deviance Information Criterion DICRPC = 2.3 × 104, DICLCM = 9.5 × 106].ConclusionsDietary pattern behaviors of Hispanics/Latinos in the United States tend to align by ethnic background for some foods and by location for other foods. Consideration of both factors is imperative to better understand their contributions to population health and developing targeted nutrition intervention studies.

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Empirically derived patterns of psychiatric symptoms in youth: A latent profile analysis.

Publications

Empirically derived patterns of psychiatric symptoms in youth: A latent profile analysis.

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