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Development of a Mobile Mindfulness Intervention for Alcohol Use Disorder and PTSD among OEF/OIF Veterans

Development of a Mobile Mindfulness Intervention for Alcohol Use Disorder and PTSD among OEF/OIF Veterans
开发针对 OEF/OIF 退伍军人酒精使用障碍和 PTSD 的移动正念干预措施
批准号:
9979357
负责人:
Jordan P Davis
金额:
$25.59万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-15 至 2023-08-31

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PROJECT SUMMARY/ABSTRACT The long-term goal of this proposal is to improve treatment outcomes for OEF/OIF veterans with alcohol use disorder (AUD) and posttraumatic stress disorder (PTSD) who are not currently accessing care through the Veterans Affairs Healthcare System (VA) or other settings. Many OEF/OIF veterans struggle with heavy drinking and related consequences and this can be especially pronounced with the co-occurrence of PTSD. Prior research has found aspects of self-regulation (emotion regulation, impulse control), stress, and craving to be important putative targets in AUD and PTSD symptom reduction. However, with upwards of 50% of veterans who have behavioral health needs not seeking treatment, it is imperative to utilize advances in technology to develop and test interventions that can reach non-treatment seeking veterans and target both symptoms of PTSD and AUD. As the proposed mechanisms (e.g., self-regulation) are becoming better understood regarding how they affect PTSD and AUD outcomes, approaches should focus on targeting these mechanisms and evaluating if they are essential facilitators of change. Mindfulness-based interventions (MBI) can target such mechanisms, but a gap in the knowledge persists regarding the utility of MBIs with veterans who screen positive for PTSD and AUD. Therefore, we propose to improve treatment outcomes for OEF/OIF veterans with PTSD and AUD by targeting self-regulation, stress, and cravings. We will develop and test a novel mobile MBI, Mobile Mindfulness Based Relapse Prevention (mMBRP), that will improve upon evidence- based in-person and group MBRP by reaching veterans outside of treatment settings. The engaging and easy- to-use mobile MBI integrates relapse prevention, stress reduction, and self-regulation skills and is relevant to issues surrounding stigma and barriers that veterans face when seeking services. The central hypothesis will be tested through a focus on three specific aims: (1) refine and add MBRP content to the popular VA- developed Mindfulness Coach mobile application through a beta testing phase where we test for feasibility and acceptability of the app, (2) pilot test the efficacy of the mMBRP mobile app on alcohol use and PTSD outcomes compared to control, and (3) assess mechanisms of change such as self-regulation, stress, and cravings, as well as exploratory moderators of gender, race/ethnicity, and recency of discharge, on mMBRP effects. The unique strengths of this proposal are its focus on an underserved population, utilization of mobile technology for intervention delivery, and use of a novel intervention known to effectively target self-regulation and stress. The expected results will define a viable and easy-to-access treatment that can improve both AUD and PTSD symptoms. Results of this study will have a positive impact on substance use outcomes for those who have experienced traumatic events and will identify mechanism of action for treatment success. The app can be disseminated through our partners in the VA and through targeted sharing on social media.
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会议论文
Multimethod Examination of Individual and Environmental Factors Associated with Alcohol Use and Behavioral Health Care Disparities Among Racial/Ethnic Minority and Women Veterans
  • 批准号:
    10721113
  • 项目类别:
  • 资助金额:
    $66.05万
  • 财政年份:
    2023
  • 负责人:
    Jordan P Davis
  • 依托单位:
Using Machine Learning to predict daily PTSD and cannabis use disorder symptoms among non-treatment seeking veterans
Using Machine Learning to predict daily PTSD and cannabis use disorder symptoms among non-treatment seeking veterans
Development of a Mobile Mindfulness Intervention for Alcohol Use Disorder and PTSD among OEF/OIF Veterans
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