This study examined whether the Structured Clinical Interview for DSM (SCID), a widely used semistructured interview designed to assess psychopathology categorically, can be adapted to identify reliable and valid severity dimensions of psychopathology. The present study also examined whether these severity dimensions have better psychometric properties (internal consistency, test-retest reliability, and concurrent and predictive validity) than categorical diagnoses. Participants (N = 234) were recruited from the community and clinics. Retest reliability and prospective predictive validity (symptoms and functioning 1 year later) were examined in subsamples of participants. Dimensional severity scales were created from an adapted version of the SCID for both current and lifetime major depression, alcohol, substance, post-traumatic stress disorder, panic, agoraphobia, social anxiety, specific phobia, obsessive-compulsive disorder, and generalized anxiety disorder. The SCID's severity scales demonstrated substantial internal consistency (all Cronbach's αs >.80), test-retest reliability, and concurrent and predictive validity. Symptom severity scales demonstrated significant incremental validity over and above categorical diagnoses for both current and prospective outcomes. The psychometric properties of SCID-identified symptom scales were far superior to the psychometrics of categorical diagnoses for both current and lifetime psychopathology. These results highlight the feasibility and utility of the SCID to assess reliable and valid symptom severity dimensions of both current and lifetime psychopathology.

Background The network theory suggests that psychopathology may reflect causal relationships between individual symptoms. Several studies have examined cross‐sectional relationships between individual symptoms in youth. However, these studies cannot address the directionality of the temporal relationships hypothesized by the network theory. Therefore, we estimated the longitudinal relationships between individual internalizing, externalizing, and attention symptoms in youth. Methods Data from 4,093 youth participants in the Adolescent Brain Cognitive Development (ABCD) study were used. Symptoms were assessed using the Brief Problem Monitor, which was administered at three time points spaced six months apart. Unique longitudinal relationships between symptoms at T1 and T2 were estimated using cross‐lagged panel network modeling. Network replicability was assessed by comparing this network to an identically estimated replication network of symptoms at T2 predicting symptoms at T3. Results After controlling for all other symptoms and demographic covariates, depressed mood, inattention, and worry at T1 were most predictive of other symptoms at T2. In contrast, threats of violence and destructiveness at T2 were most prospectively predicted by other symptoms at T1. The reciprocal associations between depressed mood and worthlessness were among the strongest bivariate relationships in the network. Comparisons between the original network and the replication network (correlation between edge lists = .61; individual edge replicability = 64%–84%) suggested moderate replicability. Conclusions Although causal inferences are precluded by the observational design and methodological considerations, these findings demonstrate the directionality of relationships between individual symptoms in youth and highlight depressed mood, inattention, and worry as potential influencers of other symptoms.

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Background: The network theory suggests that psychopathology may reflect causal relationships between individual symptoms. Several studies have examined cross-sectional relationships between individual symptoms in youth. However, these studies cannot address the directionality of the temporal relationships hypothesized by the network theory. Therefore, we estimated the longitudinal relationships between individual internalizing, externalizing, and attention symptoms in youth. Methods: Data from 4,093 youth participants in the Adolescent Brain Cognitive Development (ABCD) study were used. Symptoms were assessed using the Brief Problem Monitor, which was administered at three time points spaced six months apart. Unique longitudinal relationships between symptoms at T1 and T2 were estimated using cross-lagged panel network modeling. Network replicability was assessed by comparing this network to an identically estimated replication network of symptoms at T2 predicting symptoms at T3. Results: After controlling for all other symptoms and demographic covariates, depressed mood, inattention, and worry at T1 were most predictive of other symptoms at T2. In contrast, threats of violence and destructiveness at T2 were most prospectively predicted by other symptoms at T1. The reciprocal associations between depressed mood and worthlessness were among the strongest bivariate relationships in the network. Comparisons between the original network and the replication network (correlation between edge lists = .61; individual edge replicability = 64-84%) suggested moderate replicability. Conclusions: Although causal inferences are precluded by the observational design and methodological considerations, these findings demonstrate the directionality of relationships between individual symptoms in youth and highlight depressed mood, inattention, and worry as potential influencers of other symptoms.