Assessing Actigraphy-Determined Movement Variability as a Novel Objective Marker of Suicidal Ideation and Behavior Risk in Veterans and Its Role in Integrated Suicide Risk Assessment

评估体动记录仪确定的运动变异性作为退伍军人自杀意念和行为风险的新客观标记及其在综合自杀风险评估中的作用

• 批准号: 10357565
• 负责人: ERIC G. SMITH
• 金额: --
• 依托单位: EDITH NOURSE ROGERS MEMORIAL VETERANS HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2022-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10357565
• 关键词: Acute; Admission activity; Alcohols; Alzheimer' s Disease; Anxiety; Characteristics; Clinical; Complement; Consent; Data; Devices; Diagnosis; Diagnostic; Distress; Drug Metabolic Detoxication; Enrollment; Equipment and supply inventories; Evaluation; Exclusion Criteria; Feeling suicidal; Health system; Healthcare; Hospitalization; Hour; Inpatients; Intention; Investigation; K-Series Research Career Programs; Letters; Machine Learning; Massachusetts; Measurement; Measures; Mental Depression; Mental Health; Methods; Military Hospitals; Movement; Nonlinear Dynamics; Parkinson Disease; Participant; Patient Self-Report; Patients; Perception; Performance; Pharmaceutical Preparations; Predictive Value; Prevention program; Principal Investigator; Procedures; Prospective cohort study; Provider; Psyche structure; Psychiatry; Psychotic Disorders; Recording of previous events; Reporting; Research; Research Design; Research Personnel; Risk; Risk Assessment; Risk Behaviors; Role; Safety; Sampling; Schizoaffective Disorders; Schizophrenia; Sensitivity and Specificity; Severities; Signal Transduction; Specificity; Standardization; Structure; Subgroup; Suicide; Suicide prevention; Symptoms; Testing; Time; Variant; Veterans; Visual; Wrist; actigraphy; analog; base; dysphoria; high risk; high risk population; hospital readmission; ideation; improved; inclusion criteria; indexing; monitoring device; movement analysis; neuropsychiatry; novel; psychiatric symptom; public health relevance; reducing suicide; regression trees; resilience; risk prediction; secondary analysis; suicidal; suicidal behavior; suicidal morbidity; suicidal risk; tool

 DESCRIPTION (provided by applicant): BACKGROUND AND AIMS: Suicide prevention is a top VHA priority. Suicide prevention in every health system is hampered by difficulties with predicting the risk of suicidal behavior, due to low base rates leading to very low positive predictive values. Very recently, machine learning regression tree methods have succeeded in better identifying a group at particularly high risk of suicide post-discharge from military hospitals. This advance is greatly needed, since the first months to year post-discharge has been repeatedly shown to be one of the very highest-risk periods for suicide that is known. Nevertheless, suicide and suicidal behavior risk prediction post-discharge (and at any other time) is still extremely challenging. For instance, this study's Principal Investigator has found that, in the relatively recent past, a large majority (73%) of VHA patients with depression denied suicidal ideation even when asked within 7 days of their suicide death. A clear need exists to develop measures of suicidal behavior risk that are not heavily dependent on patient self-report. Recently, our Co-Investigators conducted nonlinear dynamic analysis of movement data from non-Veteran inpatients and identified a signal that was correlated more strongly to suicidal ideation than any other characteristic tested. RESEARCH DESIGN: A prospective cohort study of 115-300 Veterans will be conducted to determine if the previously-identified specific actigraphy-based measurements highly associated with suicidal ideation in non- Veterans will predict suicidal ideation, suicidal behavior, and/or rehospitalizatin in Veterans. METHODS: An analysis of 115-300 Veterans admitted to the Bedford, Massachusetts VAMC acute psychiatry unit will be conducted. The primary analysis will focus upon 75-200 Veterans with current suicidal ideation or recent suicidal behavior (SI/SB) who do not have a primary psychotic disorder, Alzheimer's, or Parkinson's disease, and who are not undergoing alcohol detoxification. A separate analysis will be conducted of 40-100 patients undergoing alcohol detoxification, half with SI/SB and half without SI/SB. Participants will wear a small, unobtrusive, wristwatch-like actigraph on their nondominant wrist, and complete self-rated and clinician- rated assessments of suicidal ideation, as well as self-rated assessments of the severity of other psychiatric symptoms. A Resiliency Index (RI) will be calculated using nonlinear dynamic analysis of the amplitude of movements over time frames from 6 minutes - 2 hours. These time frames are the periods for which a clear structure to the movement data is evident, with patients with suicidal ideation showing less variation in amplitude than patients without suicidal ideation. If medications given for alcohol detoxification are determined to not interfere with the RI, then a secondary analysis will examine the entire sample of 115-300 Veterans. One Aim will focus upon determining whether the original Resiliency Index or alternative movement data indices, such as one based on the change in the movement data over the hospitalization, predicts the presence and severity of suicidal ideation among Veteran inpatients. This aim will also examine the sensitivity and specificity of the RI for detecting the presence of any suicidal ideation, and of substantial suicidal ideation. (In non- Veterans, the RI showed a sensitivity of 72% and a specificity of 100% for detecting any suicidal ideation, and 86% and 88%, respectively, for detecting substantial ideation). The second Aim will determine whether the RI predicts subsequent suicidal behavior or rehospitalization over the next 1 month, 4 months, or 1 year after discharge, alone or combined with data about symptom severity, past history, and the present hospitalization. IMPACT: This study will contribute substantially to the VHA's high priority efforts to reduce suicide and suicidal behavior among Veterans. The approach studied here potentially likely particular value for suicidal behavior risk assessment in that it is not dependent on patient self-report of symptoms. This study is strongly supported by the VHA Suicide Prevention Program as a novel and potentially highly beneficial approach to suicidal behavior risk assessment, alone or combined with other readily available information.

 描述(由申请人提供)： 背景和目的：预防自杀是VHA的首要任务。由于基准率低导致阳性预测值非常低，每个卫生系统的自杀预防都受到自杀行为风险预测困难的阻碍。最近，机器学习回归树方法成功地更好地识别了军队医院出院后自杀风险特别高的群体。这一进展是非常必要的，因为出院后的头几个月到一年一再被证明是已知的自杀风险最高的时期之一。然而，在出院后(以及在任何其他时间)预测自杀和自杀行为的风险仍然是极具挑战性的。例如，这项研究的首席调查员发现，在相对较近的过去，绝大多数(73%)的VHA 抑郁症患者即使在自杀死亡后7天内被问及自杀意念时，也否认有自杀想法。很明显，有必要开发不严重依赖患者自我报告的自杀行为风险衡量标准。最近，我们的合作调查员对非退伍军人住院患者的运动数据进行了非线性动态分析，发现了一个与自杀意念关联更强的信号，而不是任何其他测试的特征。研究设计：将对115-300名退伍军人进行前瞻性队列研究，以确定先前确定的与非退伍军人自杀意念高度相关的基于动作学的特定测量是否将预测退伍军人的自杀意念、自杀行为和/或再住院。方法：对马萨诸塞州贝德福德VAMC急性精神病科收治的115-300名退伍军人进行分析。初步分析将集中在75-200名有当前自杀意念或最近自杀行为(SI/SB)的退伍军人，他们没有原发精神障碍、阿尔茨海默氏症或帕金森氏症，也没有接受酒精戒毒。将对40-100名接受酒精戒毒的患者进行单独的分析，其中一半患有SI/SB，一半没有SI/SB。参赛者将穿着 在他们的非显性手腕上有小型的、不显眼的、手表状的活动记录仪，以及对自杀意念的完整的自我评估和临床医生评估，以及对其他精神症状严重程度的自我评估。弹性指数(RI)将通过对从6分钟到2小时的时间范围内的运动幅度的非线性动态分析来计算。在这些时间范围内，运动数据的清晰结构是显而易见的，有自杀意念的患者比没有自杀意念的患者表现出较小的幅度变化。如果用于戒酒的药物被确定不会干扰RI，那么二次分析将检查115-300名退伍军人的整个样本。一个目标将集中于确定原始的弹性指数或替代的运动数据指数，例如基于住院期间运动数据的变化的指数，是否预测退伍军人住院患者中自杀意念的存在和严重程度。这一目的还将检验RI在检测是否存在任何自杀意念和实质性自杀意念方面的敏感性和特异性。(在非退伍军人中，RI对检测任何自杀意念的敏感度和特异度分别为72%和100%，在检测实质性意念方面分别为86%和88%)。第二个目标将确定国际扶轮是否单独或结合有关症状严重程度、既往病史和目前住院情况的数据来预测出院后1个月、4个月或1年内随后的自杀行为或再住院。影响：这项研究将对VHA减少退伍军人自杀和自杀行为的高度优先努力做出重大贡献。这里研究的方法可能对自杀行为风险评估有潜在的特殊价值，因为它不依赖于患者对症状的自我报告。这项研究得到了VHA自杀预防计划的大力支持，它是一种新的、潜在的非常有益的自杀行为风险评估方法，无论是单独评估还是结合其他随时可用的信息进行评估。