Sleep to Reduce Incident Depression Effectively (STRIDE)

睡眠可有效减少抑郁事件 (STRIDE)

• 批准号: 10204310
• 负责人: CHRISTOPHER L DRAKE
• 金额: $ 12.02万
• 依托单位: HENRY FORD HEALTH SYSTEM
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10204310
• 关键词: Accidents; Address; Behavior; Behavioral; Caring; Chronic; Clinical; Clinical Trials; Cognitive; Cognitive Therapy; Data; Detection; Development; Disease; Disease remission; Dissemination and Implementation; Effectiveness; Exposure to; Future; Goals; Health Services Accessibility; Impairment; Improve Access; Incidence; Individual; Injury; Intervention; Major Depressive Disorder; Mediating; Mediator of activation protein; Mental Depression; Mental Health; Modeling; Online Systems; Outcome; Participant; Patients; Pharmaceutical Preparations; Plant Roots; Population; Populations at Risk; Predictive Value; Prevention; Prevention strategy; Preventive care; Preventive measure; Primary Health Care; Provider; Randomized; Recurrence; Relapse; Research; Residual state; Resistance; Resources; Risk; Risk Factors; Safety; Sampling; Sequential Multiple Assignment Randomized Trial; Sleep; Sleeplessness; Specialist; Symptoms; Testing; Therapeutic; Thinking; Time; Training; Treatment Efficacy; Treatment outcome; base; care systems; clinical care; clinical practice; clinically significant; critical period; depression prevention; depressive symptoms; digital; disorder prevention; disorder risk; effectiveness evaluation; evidence base; expectation; falls; flexibility; follow up assessment; follow-up; health disparity; high risk; hypnotic; improved; innovation; low socioeconomic status; medical specialties; mobile application; modifiable risk; prevent; preventive intervention; primary care setting; public health priorities; racial minority; recruit; relapse prediction; risk stratification; sedative; sleep health; targeted treatment; treatment effect; treatment response; trial design

Prevention of major depressive disorder (MDD) is a public health priority. Innovative strategies to identify those at-risk for MDD are in critical need to appropriately direct preventive care. Individuals with insomnia are >3 times more likely to develop depression than normal sleepers. Insomnia precedes ~50% of all incident and relapse depression cases. Thus, insomnia may serve as an entry point for preventing MDD. Our preliminary data not only show that insomnia treatment alleviates depressive symptoms, but may also reduce likelihood of future depression development, thereby identifying insomnia a viable target for depression prevention. Identification and treatment of insomnia typically occurs in primary care and is commonly treated with hypnotic medications. However, hypnotics have significant limitations, including residual impairment, injury due to falls and accidents, and abuse potential. Cognitive-behavioral therapy for insomnia (CBT-I) is recommended as first-line treatment for its safety advantages and superior treatment efficacy. Unfortunately, widespread implementation of CBT-I is severely limited by the national shortage of trained practitioners in clinical practice. Innovative stepped care approaches rooted in primary care hold potential to increase access to care, which may improve insomnia therapeutics and reduce rates of MDD by targeting a robust yet modifiable risk factor in insomnia. Our proposal uses digital CBT-I (dCBT-I) as a widely available first-line intervention to increase care access and reduce need for specialist resources. Our proposal also adds clinician-based face-to-face CBT-I only for treatment-resistant patients who need a more personalized and flexible approach from specialty care. We propose a large-scale stepped care clinical trial in the primary care setting that utilizes sequential, multiple assignment, randomized trial (SMART) design to determine the effectiveness of dCBT-I alone and in combination with face-to-face CBT-I for insomnia and the prevention of MDD. An important innovative component of the trial is the 1- and 2-year follow-up assessments to determine the durability of effectiveness over time and assess the impact on MDD incidence and relapse. Early risk-detection and prevention is especially critical in those at elevated risk for depression to reduce health disparities. Thus, individuals with elevated vulnerability to MDD (e.g., low socioeconomic status and racial minorities) will be included in significant numbers to test for potential moderation of treatment effects stratified by risk. Finally, dCBT-I and CBT-I have been shown to reduce rumination (negative repetitive thinking), which may help mitigate MDD development. As such, we will determine whether changes in rumination (a modifiable risk- factor and potential key therapy target) mediates the effects of our stepped care model on MDD prevention. This project will test a highly scalable model of sleep care in a large primary care system to determine the potential for wide dissemination and implementation to address the high volume of population need for safe and effective insomnia treatment and associated prevention of depression.

预防重度抑郁症（MDD）是公共卫生的优先事项。创新战略， 那些有MDD风险的人迫切需要适当的预防护理。失眠的人是 比正常睡眠者患抑郁症的可能性高3倍。约占所有事件的50%， 抑郁症复发病例。因此，失眠可以作为预防MDD的切入点。我们的初步 数据显示，失眠治疗不仅可以减轻抑郁症状，而且还可以减少 未来抑郁症的发展，从而确定失眠症预防抑郁症的可行目标。 失眠症的识别和治疗通常发生在初级保健中，通常采用 催眠药然而，催眠药有明显的局限性，包括残余损伤， 到福尔斯和事故，以及滥用的可能性。推荐失眠症认知行为疗法（CBT-I） 以其安全性优势和上级治疗疗效作为一线治疗。不幸的是， 由于全国缺乏训练有素的临床实践人员，第一阶段能力建设的实施受到严重限制。 植根于初级保健的创新性阶梯式护理方法有可能增加获得护理的机会， 可能会改善失眠疗法，并通过靶向一个强大但可改变的风险因素， 失眠我们的建议使用数字CBT-I（dCBT-I）作为广泛可用的一线干预措施，以增加护理 获取和减少对专家资源的需求。我们的提案还增加了基于临床医生的面对面CBT-I 仅适用于需要更个性化和更灵活的专科护理方法的难治性患者。 我们提出了一个大规模的阶梯式护理临床试验，在初级保健设置，利用顺序， 多重分配、随机试验（SMART）设计，以确定dCBT-I单药治疗和 与CBT-I面对面治疗相结合，用于失眠和预防MDD。重要的创新 试验的一个组成部分是1年和2年的随访评估，以确定有效性的持久性 并评估对MDD发病率和复发的影响。早期风险检测和预防是 对于那些抑郁症风险较高的人来说，减少健康差距尤为重要。因此， 对MDD的脆弱性增加（例如，低社会经济地位和少数民族）将被纳入 显著数字，以检验按风险分层的治疗效应的潜在适度。 最后，dCBT-I和CBT-I已被证明可以减少反刍（消极重复思维），这可能 帮助缓解MDD开发。因此，我们将确定反刍的变化（一种可改变的风险- 因素和潜在的关键治疗目标）介导我们的分级护理模式对MDD预防的影响。 该项目将在大型初级保健系统中测试高度可扩展的睡眠护理模型，以确定 广泛传播和实施的潜力，以满足大量人口对安全 有效的失眠治疗和抑郁症的相关预防。