Personalized networks of social anxiety disorder and depression and implications for treatment
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Introduction Social anxiety disorder (SAD) and major depressive disorder (MDD) often co-occur; however, there is limited research evaluating how cognitive-affective and behavioral factors maintain SAD and MDD for specific individuals. Evidence suggests that individuals exhibit symptom-level heterogeneity, necessitating a person-specific approach to assessment and intervention. We compared group and person-specific models of SAD-MDD comorbidity and hypothesized that individuals would demonstrate person-specific patterns of comorbidity factors that differed from the group. Methods Cisgender women (N = 35) with SAD and a current or past major depressive episode were recruited. Ages ranged from 18 to 37 years old and a majority of women were White (n = 18; 51.43%). Brief ecological momentary assessment surveys related to SAD-MDD comorbidity were administered five times a day for a month (T = 4,357). Results Multilevel and person-specific network analyses were used to examine between-, within-, and person-specific patterns. Intra-daily depressed mood demonstrated the strongest connections to other variables and exhibited additional, unexpected temporal effects. All models demonstrated person-specific patterns relevant to SAD-MDD comorbidity. Limitations These results are descriptive in nature from women with a similar psychiatric profile. Future research integrating intensive EMA and personalized modeling within the context of experimental design is needed to determine the extent to which individuals truly differ from the group. Conclusions Patterns of SAD-MDD comorbidity varied substantially across women, underscoring the potential for results from person-specific (idiographic) networks to inform the development and implementation of personalized directives for clinical assessment and intervention.
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Loneliness was revealed to be a common predictor of depressive mood and social avoidance at the group level; however, this was not the case when examining the idiographic networks.
“For example, loneliness was revealed to be a common predictor of depressive mood and social avoidance at the group level; however, this was not the case when examining the idiographic networks.”
From Studies of Social Anxiety Using Ambulatory Assessment: Systematic Review (2024) · cites this paper as Piccirillo and Rodebaugh [77]
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Rodebaugh, T. L., Levitan, J. M., & Messner, G. R. (2026) · Oxford University Press eBooks · doi:10.1093/9780197769676.003.0008
Self-citationDietiker, L., Zacher, A., Rühlmann, C., Quednow, B. B., & Kleim, B. (2026) · European Journal of Psychotraumatology · doi:10.1080/20008066.2026.2663662
Presseller, E. K., Farooq, F., Reyes-Madriz, E., Rouleau-Tang, M., Jacobson, N. C., Thomas, J. G., & Marsch, L. A. (2026) · JMIR Research Protocols · doi:10.2196/104849
The impact of physical activity on adolescent social anxiety: a growth curve model analysis
Qin, R., Wu, H., Zhou, J., Xia, H., & Wang, S. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1862581
Souri, H., Koopaei, M., Garavand, A., & Souri, F. (2026) · Current Cardiology Reports · doi:10.1007/s11886-026-02442-9
Adaptive learning for depression and anxiety prediction using behavioral time series
Winger, T., Helwig, N. E., & Srivastava, J. (2026) · Academia Global and Public Health · doi:10.20935/acadphealth8412
- Authors
- Piccirillo, M. L., & Rodebaugh, T. L.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Piccirillo, Marilyn L.
- Venue
- Journal of Affective Disorders
- Publisher
- Elsevier BV
- Published
- 2022-02
- Volume
- 298
- Issue
- Pt A
- Pages
- 262-276
- ISSN
- 0165-0327 (ISSN-L)
- PMC
- PMC8690310
- OpenAlex
- W3210032809
- Cited by
- 53
- References
- 55
- Citations by year
- 2026: 11 · 2025: 17 · 2024: 12 · 2023: 6 · 2022: 7
- FWCI
- 6.04
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Journal of Affective Disorders (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute of Mental Health (F31MH115641)
- National Institute on Alcohol Abuse and Alcoholism (T3211007455)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Clinical Psychology › Child and Adolescent Psychosocial and Emotional Development
- Keywords
- social anxiety disorder, major depressive disorder, comorbidities, temporal dynamics of symptoms, women, personalized treatment, ecological momentary assessment
- MeSH terms
- Phobia, Social, Adolescent, Adult, Anxiety, Depression, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, Surveys and Questionnaires, Comorbidity, Young Adult
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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