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Is There a Core Process Across Depression and Anxiety?

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Abstract

There is emerging evidence of overlap across cognitive processes. One explanation of this overlap is the presence of a single, higher-order latent process. In this study we tested for a core process and its ability to account for symptoms of depression and anxiety. Using Structural Equation Modeling we compared a model where processes (worry, thought suppression and experiential avoidance) are treated as separate predictors of symptoms (anxiety and depression) against a model where they are represented by one latent factor. These models were applied in three analyses: a cross-sectional student sample; a longitudinal subset of this analogue sample; and a cross-sectional sample of individuals with long-term health conditions. Comparison of the models showed that while the two sets of models provided comparable fits to the data, the single factor models provided a more parsimonious solution. In addition, the latent factor explained a large proportion of variance in all measured processes, suggesting a high degree of overlap between them. It also explained more variance in symptoms than the processes separately. A Confirmatory Factor Analysis further supported a single factor solution, and the item loadings indicated that the core process represented a perceived inability to control negative thinking.

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Notes

  1. We also conducted the analyses in Fig. 1 after removing problematic items from the AAQ. This had little effect on the results of the analyses [Separate process: X2 (6) = 9.82, n.s,, CFI = 1.00, RMSEA = .05 (CI90 = .00, lower, .11, upper); Common Factor: X2 (8) = 12.85, n.s,, CFI = 1.00, RMSEA = .05 (CI90 = .00, lower, .10, upper); Chi-square change (2) = 3.08, n.s.]. We therefore only present the results of analyses using the complete scale.

  2. We also tested this model separately for depression [X2 (2) = 4.29, n.s,, CFI = .99, RMSEA = .07 (CI90 = .00, lower, .17, upper)] anxiety [X2 (2) = 3.60, n.s,, CFI = .99, RMSEA = .06 (CI90 = .00, lower, .16, upper)], and stress [X2 (2) = 5.46, n.s,, CFI = .99, RMSEA = .09 (CI90 = .00, lower, .18, upper)], all of which showed moderate to good fit. In all three models the common factor was a significant predictor of the outcome (B depression = .46, p < .001; B anxiety = .46, p < .001; B stress = .46, p < .001).

  3. We also conducted the analyses in Fig. 2 after removing problematic items from the AAQ. This had little effect on the results of the analyses [Separate process: X2 (6) = 15.61, p < .05, CFI = .97, RMSEA = .13 (CI90 = .05, lower, .21, upper); Common Factor: X2 (8) = 16.80, p < .05, CFI = .97, RMSEA = .11 (CI90 = .03, lower, .18, upper); Chi-square change (2) = 1.19, n.s.]. We therefore only present the results of analyses using the complete scale.

  4. We also tested this model separately for depression [X2 (2) = 1.65, n.s,, CFI = 1.00, RMSEA = .00 (CI90 = .00, lower, .19, upper)] anxiety [X2 (2) = .96, n.s,, CFI = 1.00, RMSEA = .00 (CI90 = .00, lower, .16, upper)], and stress [X2 (2) = 1.11, n.s,, CFI = 1.00, RMSEA = .00 (CI90 = .00, lower, .17, upper)], all of which showed moderate to good fit. In all three models the common factor was a significant predictor of the outcome (B depression = .34, p < .001; B anxiety = .50 p < .001; B stress = .37, p < .001).

  5. We also conducted the analyses in Fig. 4 after removing problematic items from the AAQ. This had little effect on the results of the analyses [Separate process: X2 (2) = 6.61, p < .05, CFI = .99, RMSEA = .11 (CI90 = .02, lower, .21, upper); Common Factor: X2 (4) = 11.23, p < .05, CFI = .99, RMSEA = .10 (CI90 = .03, lower, .17, upper); Chi-square change (2) = 4.62, n.s.]. We therefore only present the results of analyses using the complete scale.

  6. The common factor models were also separately for depression [X2 (2) = 4.56, n.s,, CFI = .99, RMSEA = .08 (CI90 = .00, lower, .19, upper)] and anxiety [X2 (2) = 5.47, n.s,, CFI = .99, RMSEA = .10 (CI90 = .00, lower, .20, upper)], both of which showed moderate to good fit. In both models the common factor was a significant predictor of the outcome (B depression = .63, p < .001; B anxiety = .83, p < .001).

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Acknowledgments

We acknowledge and thank Maaria Faruq for her contribution to the original questionnaires and data collection for Study 1; and Lars White and Lizzie Reilly who contributed to the study design. We also acknowledge the Emotion Regulation in Others and the Self (EROS) research group for their input during data analysis. We also acknowledge Peter Coventry, Angee Khara, Peter Bower, and Nawar Diar Bakerly, who contributed to the original study from which the sample from Study 2 is taken. During preparation of the manuscript Timothy Bird was supported by an interdisciplinary studentship from the Economic and Social Research Council and Medical Research Council [grant number ES/I024980/1].

Conflict of interest

None of the authors of the manuscript has declared any conflict of interest that may arise from being named as an author on the manuscript.

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  1. School of Psychological Sciences, The University of Manchester, Manchester, Coupland I, Oxford Road, Manchester, M13 9PL, UK

    Timothy Bird, Warren Mansell & Sara Tai

  2. Peninsula College of Medicine and Dentistry, Universities of Exeter and Plymouth, Exeter, UK

    Chris Dickens

  3. The NIHR Collaboration for Leadership in Applied Health Research and Care (PenCLAHRC), Plymouth, UK

    Chris Dickens

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Bird, T., Mansell, W., Dickens, C. et al. Is There a Core Process Across Depression and Anxiety?. Cogn Ther Res 37, 307–323 (2013). https://doi.org/10.1007/s10608-012-9475-2

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