Trajectories of depression and anxiety symptom change during psychological therapy
Open accessAbstract
BACKGROUND: Forty-percent of the variance in psychological treatment outcomes is estimated to be explained by symptom change by the third treatment session. However, change may not be uniform across patient groups and symptom domains. This study aimed to identify subgroups of patients with different trajectories of depression and anxiety symptom change during psychological therapy and identify baseline patient characteristics associated with these trajectories. METHODS: 4394 patients attending two psychological treatment services completed sessional, self-report depression and anxiety measures. Trajectories of symptom change were investigated using latent class growth analysis. Multinomial logistic regression was used to explore associations between baseline patient characteristics and trajectory classes. RESULTS: A number of distinct trajectories were identified. Anxiety symptom trajectories could be distinguished by the third treatment session, but for depression symptoms there was a class displaying limited change until session six followed by rapid improvement in symptoms thereafter. Compared to the non-responding trajectories, depression and anxiety trajectories indicating treatment response were associated with lower baseline severity, better social functioning and lower incidence of phobic anxiety, but not with medication prescription status. LIMITATIONS: Data came from two services, so wider generalisability is unknown. Predictors were limited to data routinely collected in the services; unmeasured factors may have improved the prediction of trajectories. CONCLUSIONS: Baseline characteristics and symptom change early in therapy can help identify different trajectories of symptom change. This knowledge could aid clinical decision making and help improve treatment outcomes. By ignoring distinct trajectories, clinicians may incorrectly consider patients as "not-on-track" and unnecessarily change or end therapy that would otherwise benefit patients.
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Growth mixture modeling has been useful for recognizing classes of patients who share similar longitudinal trajectories of depressive symptoms.
“recognizing classes of patients who share similar longitudinal trajectories of depressive symptoms (Bombardier et al., 2016; Gomez et al., 2017; Saunders et al., 2019; Saunders et al., 2020).”
From Time in treatment: Examining mental illness trajectories across inpatient psychiatric treatment (2020) · cites this paper as Saunders et al., 2019
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- Authors
- Saunders, R., Buckman, J. E. J., Cape, J., Fearon, P., Leibowitz, J., & Pilling, S.
- Affiliations
- University College London (GB)
- Camden and Islington NHS Foundation Trust (GB)
- Corresponding author
- Saunders, Rob
- Venue
- Journal of Affective Disorders
- Publisher
- Elsevier BV
- Published
- 2019-04
- Volume
- 249
- Pages
- 327-335
- ISSN
- 0165-0327 (ISSN-L)
- PMC
- PMC6428692
- OpenAlex
- W2917847013
- Cited by
- 99
- References
- 18
- Citations by year
- 2026: 20 · 2025: 16 · 2024: 18 · 2023: 11 · 2022: 17 · 2021: 9 · 2020: 3 · 2019: 5
- FWCI
- 9.93
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Affective Disorders (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Institute for Health Research (201292/Z/16/Z)
- University College London
- Wellcome Trust
- Topics
- Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Keywords
- depression, anxiety, psychotherapy, treatment response, early treatment response, baseline predictors, social functioning, phobic anxiety, drug prescribing, treatment outcome prediction
- MeSH terms
- Adult, Anxiety Disorders, Depressive Disorder, Female, Humans, Male, Middle Aged, Psychotherapy, Logistic Models, Treatment Outcome
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