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Measurement-Based Care Benchmarks and Bipolar Classification in ABCD Youth
Eric A Youngstrom1,2, Amanda J Thompson1, Yinuo Liu1
1Nationwide Children's Hospital.
Objective:
To test whether two brief mania measures, the Parent General Behavior Inventory-10 Mania form (PGBI-10M) and 7-Up, retain useful psychometric properties in a large population cohort, and to evaluate whether the PGBI-10M can identify Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS)-defined bipolar spectrum disorders in that setting.
Method:
Analyses used 11,000+ youths across late childhood and early adolescence from the Adolescent Brain Cognitive Development (ABCD) Study. For both PGBI-10M and 7-Up, we estimated descriptive statistics, internal consistency, confirmatory factor models, graded response models, and measurement-based care benchmarks (minimally important difference, reliable change, and clinical cutpoints). For the PGBI-10M, receiver operating characteristic (ROC) analyses estimated concurrent classification accuracy for bipolar diagnoses at baseline and 2-year follow-up and compared area under the curve (AUC) values with prior outpatient and community mental health samples.
Results:
Scores were lower than in clinical samples, but both measures remained psychometrically sound. The PGBI-10M showed alpha=.87-.88 and omega=.88; the 7-Up showed alpha=.78 and omega=.79. Longitudinal analyses indicated threshold differences across waves, likely reflecting caregiver recalibration and developmental changes, with modest impact on estimates. ABCD-based benchmarks supported meaningful and reliable change. The PGBI-10M discriminated bipolar cases (AUC=0.68 baseline; 0.77 follow-up), though performance was lower than in clinical samples. Positive predictive values were low in this population.
Conclusion:
The PGBI-10M and 7-Up support monitoring of manic and mixed symptoms, but the PGBI-10M alone is insufficient for universal bipolar screening. Brief mania scales are best used for targeted assessment and longitudinal monitoring within multi-informant workflows.
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