# Anxiety Outcomes in Cognitive-Behavioral Therapy vs. Light Therapy for Seasonal Affective Disorder

> **NIH NIH R01** · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · 2020 · $16,472

## Abstract

Project Summary/Abstract
Depression and anxiety are highly comorbid, and this comorbidity is a negative prognostic
indicator of treatment outcomes with antidepressant medication. However, research conflicts on
the effects of comorbid anxiety on outcomes with cognitive-behavioral therapy (CBT) for
depression. The role of comorbid anxiety in treating a subtype of depression, winter seasonal
affective disorder (SAD), has yet to be studied. The current project proposes to examine anxiety
as both an outcome and a moderator of treatment outcomes in a parent trial comparing light
therapy and CBT tailored to SAD (CBT-SAD). Aim 1 will examine anxiety as an outcome after
acute treatment and at a follow-up one winter later. Aims 2 and 3 will examine baseline
anxiety—both dimensional and syndromal anxiety, respectively—as a predictor of SAD
treatment outcomes at post-treatment and at a follow-up one winter later. Anxiety disorders will
be assessed using the Structured Clinical Interview for DSM-5 (SCID-5) at intake. Anxiety will
be dimensionally assessed using the Beck Anxiety Inventory (BAI) at pre-, mid-, and post-
treatment, as well as at the one winter follow-up.

## Key facts

- **NIH application ID:** 10029783
- **Project number:** 3R01MH112819-02S2
- **Recipient organization:** UNIVERSITY OF VERMONT & ST AGRIC COLLEGE
- **Principal Investigator:** KELLY J. ROHAN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $16,472
- **Award type:** 3
- **Project period:** 2018-05-01 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10029783

## Citation

> US National Institutes of Health, RePORTER application 10029783, Anxiety Outcomes in Cognitive-Behavioral Therapy vs. Light Therapy for Seasonal Affective Disorder (3R01MH112819-02S2). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10029783. Licensed CC0.

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