Dataset Information

Prevalence and co-occurrence of psychiatric symptom clusters in the U.S. adolescent population using DISC predictive scales.

ABSTRACT:

Objective

To estimate 12-month prevalence and co-occurrence of symptoms of specific mental problems among US adolescents (12-17 years) by age, sex and racial/ethnic subgroups.

Method

Data from the 2000 National Household Survey of Drug Abuse (NHSDA) adolescent sample are used to estimate prevalence and co-occurrence rates using the DISC predictive scales. Multiple logistic regressions were used to derive significant correlates of each domain of DPS-derived symptom cluster indicators of psychiatric problems and of severe comorbidity, with control of demographics and environmental factors.

Setting

The National Household Survey on Drug Abuse (NHSDA), a national household probability sample, includes a nationally representative sample of 12-17 year-old adolescents (N = 19,430), through in-home surveys.

Results

Three out of five adolescents screened positive for at least one DPS symptom cluster with estimates for specific symptom cluster ranging over 9.7% (substance use disorder), 13.4% (affective), 36.3% (disruptive-behavior), and 40.1% (anxiety). Co-occurrence was high with almost one-third of any DPS symptom cluster reporting multiple positive screens of four or more clusters. Blacks and younger females were most likely to report mental health problems and co-occurrence.

Conclusion

Mental health problems among U.S. youth may be far more common than previously believed, although these symptoms have not yet reached the point of clinical impairment. The data speak to important patterns of age, gender and racial/ethnic differences in mental health problems deserving of further study.

SUBMITTER: Chen KW

PROVIDER: S-EPMC1298317 | biostudies-literature | 2005 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prevalence and co-occurrence of psychiatric symptom clusters in the U.S. adolescent population using DISC predictive scales.

Chen Kevin W KW Killeya-Jones Ley A LA Vega William A WA

Clinical practice and epidemiology in mental health : CP & EMH 20051028

<h4>Objective</h4>To estimate 12-month prevalence and co-occurrence of symptoms of specific mental problems among US adolescents (12-17 years) by age, sex and racial/ethnic subgroups.<h4>Method</h4>Data from the 2000 National Household Survey of Drug Abuse (NHSDA) adolescent sample are used to estimate prevalence and co-occurrence rates using the DISC predictive scales. Multiple logistic regressions were used to derive significant correlates of each domain of DPS-derived symptom cluster indicato ...[more]

PMID: 16255774

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Project description:BackgroundPsychiatric traits are heritable, highly comorbid and genetically correlated, suggesting that genetic effects that are shared across disorders are at play. The aim of the present study is to quantify the predictive capacity of common genetic variation of a variety of traits, as captured by their PRS, to predict case-control status in a child and adolescent psychiatric sample including controls to reveal which traits contribute to the shared genetic risk across disorders.MethodPolygenic risk scores (PRS) of 14 traits were used as predictor phenotypes to predict case-control status in a clinical sample. Clinical cases (N = 1,402), age 1-21, diagnostic categories: Autism spectrum disorders (N = 492), Attention-deficit/ hyperactivity disorders (N = 471), Anxiety (N = 293), disruptive behaviors (N = 101), eating disorders (N = 97), OCD (N = 43), Tic disorder (N = 50), Disorder of infancy, childhood or adolescence NOS (N = 65), depression (N = 64), motor, learning and communication disorders (N = 59), Anorexia Nervosa (N = 48), somatoform disorders (N = 47), Trauma/stress (N = 39) and controls (N = 1,448, age 17-84) of European ancestry. First, these 14 PRS were tested in univariate regression analyses. The traits that significantly predicted case-control status were included in a multivariable regression model to investigate the gain in explained variance when leveraging the genetic effects of multiple traits simultaneously.ResultsIn the univariate analyses, we observed significant associations between clinical status and the PRS of educational attainment (EA), smoking initiation (SI), intelligence, neuroticism, alcohol dependence, ADHD, major depression and anti-social behavior. EA (p-value: 3.53E-20, explained variance: 3.99%, OR: 0.66), and SI (p-value: 4.77E-10, explained variance: 1.91%, OR: 1.33) were the most predictive traits. In the multivariable analysis with these eight significant traits, EA and SI, remained significant predictors. The explained variance of the PRS in the model with these eight traits combined was 5.9%.ConclusionOur study provides more insights into the genetic signal that is shared between childhood and adolescent psychiatric disorders. As such, our findings might guide future studies on psychiatric comorbidity and offer insights into shared etiology between psychiatric disorders. The increase in explained variance when leveraging the genetic signal of different predictor traits supports a multivariable approach to optimize precision accuracy for general psychopathology.

Project description:ObjectivesTo investigate the correspondence between diagnoses on sick leave certificates and diagnoses made in structured psychiatric interviews. Secondary aims were to investigate length of sick leave by diagnoses on sick leave certificates, diagnoses made in structured interviews and symptom severity.DesignObservational study consisting of a secondary analysis of data from a randomised controlled trial and an observational study.SettingThe regions of Stockholm and Västra Götaland, Sweden.Participants480 people on sick leave for common mental disorders.InterventionsParticipants were examined with structured psychiatric interviews and self-rated symptom severity scales.Outcome measures(1) Sick leave certificate diagnoses, (2) diagnoses from the Mini International Neuropsychiatric Interview and the Self-rated Stress-Induced Exhaustion Disorder (SED) Instrument (s-ED), (3) symptom severity (Montgomery-Asberg Depression Rating Scale-self-rating version and the Karolinska Exhaustion Disorder Scale) and (4) number of sick leave days.ResultsThere was little correspondence between diagnoses on sick leave certificates and diagnoses made in structured psychiatric interviews. Many participants on sick leave for SED, anxiety disorder or depression fulfilled criteria for other mental disorders. Most on sick leave for SED (76%) and anxiety disorder (67%) had depression (p=0.041). Length of sick leave did not differ by certificate diagnoses. Participants with SED (s-ED) had longer sick leave than participants without SED (144 vs 84 days; 1.72 (1.37-2.16); p<0.001). More severe symptoms were associated with longer sick leave.ConclusionDiagnoses on sick leave certificates did not reflect the complex and overlapping nature of the diagnoses found in the structured psychiatric interviews. This finding is relevant to the interpretation of information from health data registers, including studies and guidelines based on these data. A result of clinical interest was that more severe symptoms predicted long-term sick leave better than actual diagnoses.

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Dataset Information

Prevalence and co-occurrence of psychiatric symptom clusters in the U.S. adolescent population using DISC predictive scales.

Objective

Method

Setting

Results

Conclusion

Publications

Prevalence and co-occurrence of psychiatric symptom clusters in the U.S. adolescent population using DISC predictive scales.

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