Automated Text Messaging to Improve Depression Treatment in Low-Income Settings

描述（由申请人提供）：抑郁症治疗（心理治疗和药物治疗）的依从性差，限制了其在社区环境中的有效性。依从性问题在低收入环境中尤为明显。需要创新和具有成本效益的方法来提高对治疗的依从性并最大限度地利用精神卫生资源。基于移动电话的短信（或短信服务：SMS）是一种无处不在的技术，已被用于各种社会经济地位的各种健康应用。这项技术有可能通过提高依从性来提高心理健康治疗的保真度。拟议中的研究项目将测试在群体认知行为疗法（CBT）中加入自动短信辅助疗法是否能提高抑郁症患者的依从性（作业依从性、出勤率、药物依从性），并进一步减轻抑郁症症状。短信辅助将1)提示患者监测情绪、想法和行为，2)提供药物和预约提醒，3)发送个性化的基于CBT的提示。患者提供的信息将在临床环境中用于强调思想、行为和症状之间的相互关系。研究项目的结果将通知R01进一步测试卫生信息技术（HIT）在低收入环境中的应用。通过该奖项获得的经验将补充以前的培训，并为我在低收入社区将卫生信息技术应用于精神卫生服务方面的成功临床研究生涯做好准备。这个K23（指导病人导向的职业发展奖）申请描述了一个培训和研究计划，旨在通过使用短信作为心理治疗的辅助手段来改善低收入社区的抑郁症治疗。在Kurt C. Organista, Ricardo F. Mu¿oz和Patricia A. Arean的指导下，申请人寻求1)基于社区的心理健康服务研究，2)健康信息技术和3)混合方法研究方面的高级培训。为了在这些领域取得进一步的专门知识，提出了各种培训经验，并以一项研究试验作为职业发展计划的核心。

DESCRIPTION (provided by applicant): Poor adherence to depression treatments (psychotherapy and pharmacotherapy) limits their effectiveness in community settings. Problems with adherence are especially pronounced in low-income settings. Innovative and cost-effective methods are needed to improve adherence to treatments and maximize mental health resources. Mobile phone based text messaging (or short messaging service: SMS) is a ubiquitous technology that has been used in various health applications across socioeconomic status. This technology has the potential to increase the fidelity of mental health treatments via increased adherence. The proposed research project will test whether adding an automated SMS adjunct to group cognitive behavioral therapy (CBT) for depression can increase adherence (homework adherence, attendance, medication adherence) and further reduce depression symptoms. The SMS adjunct will 1) prompt patients to monitor mood, thoughts and behaviors, 2) will provide medication and appointment reminders and 3) will send personalized CBT based tips. The information that patients provide will be used within the clinical setting to highlight interrelations between thoughts, behaviors and symptoms. The results of the research project will inform an R01 to do further testing of health information technology (HIT) applications in low-income settings. The experience gained through this award will complement previous training and prepare me for a successful clinical research career in the application of health information technologies to mental health services in low-income communities. This K23 (Mentored Patient-Oriented Career Development Award) application delineates a training and research plan seeking to improve depression treatment in low-income communities through the use of text messaging as an adjunct to psychotherapy. The applicant is seeking advanced training in 1) community based mental health services research, 2) health information technology and 3) mixed methods research via mentorship from Kurt C. Organista, Ricardo F. Mu¿oz, and Patricia A. Arean. To achieve further expertise in these areas, various training experiences are proposed with a research trial serving as the core of the career development plan.