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A Reformulated Architecture of Cognitive Risks for Psychopathology: Common and Specific Dimensions and Links to Internalizing Outcomes in Adolescence.


ABSTRACT: Multiple cognitive risk products (dysfunctional attitudes [DA], negative inferential style [NIS], self-criticism, dependency, rumination) predict internalizing disorders; however, an optimal structure to assess these risks is unknown. We evaluated the fit, construct validity, and utility of a bifactor, single, and correlated factor model in a community sample of 382 adolescents (age 11-15 years; 59% female). The bifactor, hierarchical single, and correlated factor models all fit well. The bifactor model included a common factor (c), capturing covariance across all cognitive risk measures, and specific latent factors for DA, NIS, dependency and rumination. Construct validity of these factor structures was evaluated with external validators, including depression and anxious arousal (AA) symptoms, positive affect (PA) and negative affect (NA), and onset of depression diagnostic onset over 2 years. C was associated with higher depression, NA, and AA; lower PA; and predicted depressive episodes. Hierarchical single and correlated factor models also related to external validators.

SUBMITTER: Schweizer TH 

PROVIDER: S-EPMC6581618 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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A Reformulated Architecture of Cognitive Risks for Psychopathology: Common and Specific Dimensions and Links to Internalizing Outcomes in Adolescence.

Schweizer Tina H TH   Snyder Hannah R HR   Hankin Benjamin L BL  

Assessment 20181008 2


Multiple cognitive risk products (dysfunctional attitudes [DA], negative inferential style [NIS], self-criticism, dependency, rumination) predict internalizing disorders; however, an optimal structure to assess these risks is unknown. We evaluated the fit, construct validity, and utility of a bifactor, single, and correlated factor model in a community sample of 382 adolescents (age 11-15 years; 59% female). The bifactor, hierarchical single, and correlated factor models all fit well. The bifact  ...[more]

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