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Open trial of a personalized modular treatment for mood and anxiety
Open accessAbstract
Psychosocial treatments for mood and anxiety disorders are generally effective, however, a number of treated individuals fail to demonstrate clinically-significant change. Consistent with the decades-old aim to identify 'what works for whom,' personalized and precision treatments have become a recent area of interest in medicine and psychology. The present study followed the recommendations of Fisher (2015) to employ a personalized modular model of cognitive-behavioral therapy. Employing the algorithms provided by Fernandez, Fisher, and Chi (2017), the present study collected intensive repeated measures data prior to therapy in order to perform person-specific factor analysis and dynamic factor modeling. The results of these analyses were then used to generated personalized modular treatment plans on a person-by-person basis. Thirty-two participants completed therapy. The average number of sessions was 10.38. Hedges g's for the Hamilton Rating Scale for Depression (HRSD) and Hamilton Anxiety Rating Scale (HARS) were 2.33 and 1.62, respectively. The change per unit time was g = .24/session for the HRSD and g = 0.17/session for the HARS. The current open trial provides promising data in support of personalization, modularization, and idiographic research paradigms.
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“The identification of which active elements work for whom could improve outcomes via develop ment of personalized treatment protocols, where individuals receive a specific suite of active elements suited to their needs (Fisher et al., 2019; Rubel, Fisher, Husen, & Lutz, 2018).”
From Measuring the active elements of cognitive-behavioral therapies (2023) · cites this paper as Fisher et al., 2019
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Metadata
- Authors
- Fisher, A. J., Bosley, H. G., Fernandez, K. C., Reeves, J. W., Soyster, P. D., Diamond, A. E., & Barkin, J.
- Affiliations
- University of California, Berkeley (US)
- Center for Creative Leadership (US)
- Corresponding author
- Fisher, Aaron J.
- Venue
- Behaviour Research and Therapy
- Publisher
- Elsevier BV
- Published
- 2019-05
- Volume
- 116
- Pages
- 69-79
- ISSN
- 0005-7967 (ISSN-L)
- OpenAlex
- W2915885068
- Cited by
- 156
- References
- 63
- Citations by year
- 2026: 12 · 2025: 16 · 2024: 30 · 2023: 17 · 2022: 22 · 2021: 23 · 2020: 27 · 2019: 9
- FWCI
- 23.78
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- public-domain
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Behaviour Research and Therapy (publishedVersion)
- PubMed (publishedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion, public-domain)
- PsyArXiv (OSF Preprints) (submittedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
- Social Sciences › Psychology › Clinical Psychology › Personality Disorders and Psychopathology
- Keywords
- personalized treatment, mood disorders, anxiety disorders, depression, anxiety, treatment response prediction, idiographic research
- MeSH terms
- Adolescent, Adult, Algorithms, Anxiety Disorders, Major Depressive Disorder, Female, Humans, Male, Middle Aged, Cognitive Behavioral Therapy, Young Adult, Precision Medicine
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