# Does Adding a Tailored Cognitive Behavioral Therapy (CBT) Mobile Skills App Mediate Higher Rates of Depression Recovery, Adjustment, and Quality of Life in OEF/OIF Veterans Compared to Standard CBT?

> **NIH VA I01** · VETERANS HEALTH ADMINISTRATION · 2020 · —

## Abstract

Cognitive Behavioral Therapy (CBT) is the leading evidence-based psychotherapy for depression, which
affects 18.5% of Operation Enduring Freedom (OEF), Operation Iraqi Freedom (OIF), and Operation New
Dawn (OND) Veterans (hereafter referred to as OEF/OIF). Yet, OEF/OIF Veterans had only a 30% average
reduction in mean depression scores from the initial to later phase of treatment. This was true despite the
rigorous training and certification procedures for VA CBT-D. Improving the rate of depression recovery and
remission is vital to enhance OEF/OIF Veteran’s ability to improve work and home adjustment and overall
quality of life.
 Broad access to all key ingredients of CBT, including skills practice (homework), is associated with
improved and faster recovery from depression. OEF/OIF Veterans and patients with depression have reported
many barriers (i.e., time, chaotic lifestyles, and low energy) to following through with their skills practice
assignments. In the absence of targeted strategies/interventions to address the barriers that prevent CBT skills
practice, OEF/OIF Veterans will remain unable to reap the full benefits/effects of CBT. With specific tailored
interventions to address this gap in treatment, OEF/OIF Veterans will improve rates of recovery from
depression, diminished home and work adjustment, and poor quality of life.
 Leveraging the technological savvy of this generation of Veterans to improve access to CBT skills
practice is a logical tactic to address this gap in treatment. Smartphone apps have been identified as a useful
widely-used tool to improve the effectiveness of psychological treatments. There is, however, a paucity of
empirical studies on the use of mobile apps in the treatment of depressed OEF/OIF Veterans and in
psychological treatment overall. The promising pilot results of a comprehensive tailored smartphone app for
CBT skills practice for OEF/OIF Veterans (“CBT MobileWork-V”), leads us to propose a larger-scale
randomized clinical trial (RCT) to measure the efficacy of CBT enhanced with CBTMobileWork-V (the
experimental arm) for improving CBT understanding and skill acquisition and depressive symptoms, in
OEF/OIF Veterans with depression compared to standard CBT-D. Specifically, over a 27-month period we
propose to randomize 268 eligible OEF/OIF Veterans with depressive symptoms, to either CBT augmented
with the comprehensive CBT skill training smartphone app CBT MobileWork-V or standard CBT-D with
traditional skills practice methods (i.e., paper and pencil). The Specific Aims of this study are:
Primary Aim 1) To assess whether CBT-D augmented with CBT MobileWork-V (hereafter referred to as CBT-
D+) promotes greater CBT understanding and skill acquisition compared to traditional CBT-D.
Primary Aim 2a) To examine the short-term effect in depressive symptoms after 12 weeks of CBT-D+ versus
standard CBT-D.
Primary Aim 2b) To examine the long-term effect in depressive symptoms at 6 months post treatment of the
CBT-D+...

## Key facts

- **NIH application ID:** 9837942
- **Project number:** 1I01RX002908-01A2
- **Recipient organization:** VETERANS HEALTH ADMINISTRATION
- **Principal Investigator:** Judith Ann Callan
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2020-01-01 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9837942

## Citation

> US National Institutes of Health, RePORTER application 9837942, Does Adding a Tailored Cognitive Behavioral Therapy (CBT) Mobile Skills App Mediate Higher Rates of Depression Recovery, Adjustment, and Quality of Life in OEF/OIF Veterans Compared to Standard CBT? (1I01RX002908-01A2). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9837942. Licensed CC0.

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