Identifying cognitive markers of late-life suicide

识别晚年自杀的认知标志

• 批准号: 8477073
• 负责人: Katalin Szanto
• 金额: $ 32.4万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2014-08-19
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8477073
• 关键词: Accounting; Affect; Affective; Age; Aging; Alcohol consumption; Attention; Behavioral; Brain Injuries; Characteristics; Clinical; Cognition; Cognitive; Cognitive deficits; Cohort Studies; Collaborations; Conflict (Psychology); Confounding Factors (Epidemiology); Country; DSM-IV; Data; Decision Making; Depressed mood; Discrimination; Disease susceptibility; Economics; Education; Elderly; Ensure; Environment; Evaluation; Event; Experimental Psychology; Failure; Feeling suicidal; Future; Gender; Health Services Research; Impaired cognition; Impairment; Individual; Intervention; K-Series Research Career Programs; Language; Lead; Life; Longitudinal Studies; Major Depressive Disorder; Measures; Medical; Memory; Mental Depression; Mentors; Minority; Modeling; Mood Disorders; Moods; Multivariate Analysis; National Institute of Mental Health; Neurobiology; Neurocognitive; Outcome; Participant; Pathway interactions; Performance; Persons; Pharmaceutical Preparations; Prevention; Principal Investigator; Process; Prospective Studies; Protocols documentation; Psychiatric Diagnosis; Psychopathology; Psychosocial Assessment and Care; Punishment; Race; Recording of previous events; Recovery; Recruitment Activity; Research; Research Design; Research Infrastructure; Research Personnel; Research Project Grants; Reversal Learning; Rewards; Risk; Risk Factors; Risk Management; Sampling; Self-Injurious Behavior; Serum; Services; Severities; Short-Term Memory; Social Environment; Social isolation; Solutions; Staging; Statistical Methods; Strategic Planning; Subgroup; Substance abuse problem; Suicide; Suicide attempt; Suicide prevention; Testing; Time; Uncertainty; Universities; Visuospatial; aged; base; burden of illness; clinical practice; cognitive control; cognitive function; computational neuroscience; computerized; depressive symptoms; disability; executive function; follow-up; geriatric depression; geriatric mental health; high risk; in vivo; information processing; insight; novel; physical conditioning; predictive modeling; processing speed; prospective; psychologic; psychosocial; public health relevance; resilience; social; social cognition; stressor; suicidal; suicidal behavior; suicidal individual; suicidal morbidity; suicidal risk; suicide attempter; suicide rate; theories; translational neuroscience; treatment as usual; treatment strategy

DESCRIPTION (provided by applicant): Although depression commonly precedes late-life suicidal behavior, clinicians still cannot confidently identify depressed elderly who are most likely to attempt or die by suicide. Thus, there is a great need for better predictive models regarding suicidal behavior in the elderly. This revised R01 (MH085651) application is to investigate specific cognitive vulnerabilities to late-life suicidal behavior. We focus on features that may cause accumulation of stressors, undermine deterrents, and facilitate the final decision to take one's life. Our preliminary data indicate that deficits in (1) specific aspects of cognitive control that involve reward/punishment processing, and in (2) social cognition distinguish depressed elderly suicide attempters from depressed non- suicidal elderly, while the two groups show similar global cognition, working memory, and forward planning. Building on this preliminary evidence, this new-investigator R01 will include key cognitive probes in a large- enough sample to test hypotheses that impairments in decision-making, affective processing, reversal learning, and social cognition are specifically associated with suicide attempts in depressed elders. We propose to assess 100 suicide attempters, 80 non-suicidal depressed individuals, and 60 non-psychiatric control subjects, aged 60 and older, using theory-driven computerized assessments as well as traditional tests of cognitive performance. Participants will undergo extensive clinical characterization of their suicidal behavior, psychopathology, psychosocial stressors, physical health, possible brain injury from suicide attempts, and medication exposure. The three groups will be similar in demographic characteristics and medical illness burden, and the two depressed groups will have similar severity of depression. To determine whether the identified impairments persist over time despite changes in mood state, we will repeat cognitive assessments four months after baseline (when substantial clinical improvement can reasonably be anticipated based on our pilot data). We will also prospectively explore the effect of cognitive status on suicide-related outcomes during this follow-up period. In collaboration with the biostatistical team of our late-life depression center and our external statistical consultant, we propose to use multivariate analyses of covariance to compare cognitive functions across groups, as well as discriminant function analysis to create a compact cognitive battery and to test its utility for correctly identifying suicide attempters beyond known risk factors. We will use mixed effects models to examine stability of cognitive impairments across mood states. Statistical analysis will account for factors that may affect cognition: severity of depression, medical illness burden, serum anticholinergicity, and other relevant factors identified by preliminary analyses. This project builds upon an ongoing K23, where the PI has shown the feasibility of recruiting, assessing, and longitudinally following suicidal elders with a high rate of suicidal behavior during follow-up. The research project will be conducted at the University of Pittsburgh, in collaboration with the Experimental Psychology Department, University of Cambridge.

描述（由申请人提供）：虽然抑郁症通常先于晚年自杀行为，但临床医生仍然无法自信地确定最有可能尝试自杀或死于自杀的抑郁老年人。因此，非常需要更好的老年人自杀行为预测模型。本修订版R 01（MH 085651）申请旨在研究晚年自杀行为的特定认知脆弱性。我们专注于可能导致压力源积累的特征，破坏威慑力，并促进最终决定结束一个人的生命。我们的初步数据表明，（1）涉及奖励/惩罚处理的认知控制特定方面的缺陷，以及（2）社会认知的缺陷将抑郁的老年自杀倾向者与抑郁的非自杀老年人区分开来，而两组显示出相似的整体认知，工作记忆和前瞻性计划。基于这一初步证据，这一新的研究者R 01将在足够大的样本中包括关键的认知探针，以测试决策，情感处理，逆转学习和社会认知障碍与抑郁症老年人自杀企图特别相关的假设。我们建议评估100名自杀未遂者，80名非自杀抑郁症患者和60名非精神病对照组，年龄60岁及以上，使用理论驱动的计算机评估以及传统的认知能力测试。受试者将接受广泛的临床表征，包括自杀行为、精神病理学、心理社会应激源、身体健康、自杀企图可能造成的脑损伤和药物暴露。这三个组在人口统计学特征和医疗疾病负担方面相似，两个抑郁组的抑郁严重程度相似。为了确定尽管情绪状态发生变化，但识别出的障碍是否会随着时间的推移而持续存在，我们将在基线后4个月重复认知评估（根据我们的初步数据，可以合理预期临床改善）。我们还将前瞻性地探讨在随访期间认知状态对自杀相关结局的影响。与我们的晚年抑郁症中心的生物统计团队和我们的外部统计顾问合作，我们建议使用协方差的多变量分析来比较各组的认知功能，以及判别函数分析来创建一个紧凑的认知电池，并测试其效用，以正确识别自杀倾向者超出已知的风险因素。我们将使用混合效应模型来检查跨情绪状态的认知障碍的稳定性。统计分析将解释可能影响认知的因素：抑郁症的严重程度、医疗疾病负担、血清抗胆碱能性和初步分析确定的其他相关因素。该项目建立在正在进行的K23的基础上，其中PI已经证明了招募、评估和纵向随访随访自杀行为发生率高的自杀老人的可行性。该研究项目将在匹兹堡大学与剑桥大学实验心理学系合作进行。