Abstract
Depression and anxiety are highly prevalent psychological disorders; our understanding of these conditions remains limited. Efforts to explain anxiety and depression have been constrained in part by binary classification systems. Dimensional approaches to understanding psychopathology may be more effective. The present study used latent profile analysis (LPA) to assess whether unique subgroups exist within a tri-level model of anxiety and depression. Participants (N = 627) completed self-report questionnaires from which tri-level model factors were derived. LPA was conducted on those factors. A 4-profile model offered optimal fit to the data at baseline. This model was replicated at a second time point. Models derived included profiles labelled ‘Mixed Fears,’ ‘Anxious Arousal,’ ‘Low Mood/Anhedonia,’ and ‘Sub-Clinical.’ Profiles were validated at Time 1 using diagnostic status and clinical severity ratings associated with mood and anxiety presentations. Profiles demonstrated flexibility in accommodating breadth in clinical presentations and common comorbidities. Latent variable models may offer more ecologically valid approaches to understanding psychopathology.
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Availability of data and material
Data is available upon email request to the corresponding author. Additionally, data has been submitted to open science framework and is publicly available: https://doi.org/10.17605/OSF.IO/WAJF6.
Code availability
Code for LPAs, diagnostic analyses, and CSR analyses is available upon request via email.
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Funding
This research was supported by a two-site grant from the National Institute of Mental Health (NIMH) to M. G. Craske (R01-MH065651) and to S. Mineka and R. E. Zinbarg (R01-MH065652). The content is the responsibility of the authors and does not necessarily represent the official views of the NIMH.
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J.S.Y developed the study concept. All authors contributed to study design. Data analysis was performed by J.S.Y. under the supervision of M.G.C and R.E.Z. in consultation with C.K.E. J.S.Y. drafted the paper and M.G.C., R.E.Z., C.K.E., and S.M. offered critical revisions. All authors reviewed the final version of the manuscript and approved the paper for submission.
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Julia S. Yarrington, Craig K. Enders, Richard E. Zinbarg, Susan Mineka, and Michelle G. Craske have no conflicts of interest to report.
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The present study was approved by the IRB at University of California, Los Angeles 1 and the IRB at Northwestern University. This study was performed in line with the principles of the Declaration of Helsinki.
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Yarrington, J.S., Enders, C.K., Zinbarg, R.E. et al. Examining the Dimensionality of Anxiety and Depression: a Latent Profile Approach to Modeling Transdiagnostic Features. J Psychopathol Behav Assess 44, 214–226 (2022). https://doi.org/10.1007/s10862-021-09913-z
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DOI: https://doi.org/10.1007/s10862-021-09913-z