Affective Computing for Late-Life Mood and Cognitive Disorders

Affective computing (also referred to as artificial emotion intelligence or emotion AI) is the study and development of systems and devices that can recognize, interpret, process, and simulate emotion or other affective phenomena. With the rapid growth in the aging population around the world, affective computing has immense potential to benefit the treatment and care of late-life mood and cognitive disorders. For late-life depression, affective computing ranging from vocal biomarkers to facial expressions to social media behavioral analysis can be used to address inadequacies of current screening and diagnostic approaches, mitigate loneliness and isolation, provide more personalized treatment approaches, and detect risk of suicide. Similarly, for Alzheimer's disease, eye movement analysis, vocal biomarkers, and driving and behavior can provide objective biomarkers for early identification and monitoring, allow more comprehensive understanding of daily life and disease fluctuations, and facilitate an understanding of behavioral and psychological symptoms such as agitation. To optimize the utility of affective computing while mitigating potential risks and ensure responsible development, ethical development of affective computing applications for late-life mood and cognitive disorders is needed.

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Suicidal Thinking and Behavior During Treatment With Sertraline in Late-Life Depression

American Journal of Geriatric Psychiatry ◽

10.1097/jgp.0b013e318050c9c2 ◽

2007 ◽

Vol 15 (7) ◽

pp. 573-580 ◽

Cited By ~ 12

Author(s):

J Craig Nelson ◽

Kevin Delucchi ◽

Lon Schneider

Keyword(s):

Late Life ◽

Late Life Depression ◽

Suicidal Thinking ◽

And Behavior

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Role of severity and gender in the association between late-life depression and all-cause mortality

International Psychogeriatrics ◽

10.1017/s1041610212002190 ◽

2012 ◽

Vol 25 (4) ◽

pp. 677-684 ◽

Cited By ~ 16

Author(s):

Hyun-Ghang Jeong ◽

Jung Jae Lee ◽

Seok Bum Lee ◽

Joon Hyuk Park ◽

Yoonseok Huh ◽

...

Keyword(s):

Depressive Disorder ◽

Depressive Disorders ◽

Proportional Hazards ◽

Cognitive Disorders ◽

Late Life ◽

Cox Proportional Hazards ◽

Community Dwelling ◽

Late Life Depression ◽

All Cause Mortality ◽

And Gender

ABSTRACTBackground: Mortality associated with depression may be influenced by severity of depression and gender. We investigated the differential impacts on all-cause mortality of late-life depression by the type of depression (major depressive disorder, MDD; minor depressive disorder, MnDD; subsyndromal depression, SSD) and gender after adjusting comorbid conditions in the randomly sampled elderly.Methods: One thousand community-dwelling elderly individuals were enrolled. Standardized face-to-face clinical interviews, neurological examination, and physical examination were conducted to diagnose depressive disorders and comorbid cognitive disorders. Depressive disorders were diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria and SSD to study-specific operational criteria. Five-year survivals were compared between groups using Cox proportional hazards models.Results: By the end of 2010, 174 subjects (17.4%) died. Depressive disorder (p = 0.001) and its interaction term with gender (p < 0.001) were significant in predicting five-year survival. MDD was an independent risk factor for mortality in men (hazard ratio = 3.65, 95% confidence interval = 1.67–7.96) whereas MnDD and SSD were not when other risk factors were adjusted.Conclusions: MDD may directly confer the risk of mortality in elderly men whereas non-major depression may be just an indicator of increased mortality in both genders.

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Refining Evidence-Based Treatments for Late-Life Depression

GeroPsych ◽

10.1024/1662-9647/a000127 ◽

2015 ◽

Vol 28 (2) ◽

pp. 67-76

Author(s):

Grace C. Niu ◽

Patricia A. Arean

Keyword(s):

Older Adults ◽

Mental Illness ◽

Brain Plasticity ◽

Late Life ◽

Aging Population ◽

The United States ◽

Future Research ◽

Evidence Based ◽

Late Life Depression ◽

Evidence Based Treatments

The recent increase in the aging population, specifically in the United States, has raised concerns regarding treatment for mental illness among older adults. Late-life depression (LLD) is a complex condition that has become widespread among the aging population. Despite the availability of behavioral interventions and psychotherapies, few depressed older adults actually receive treatment. In this paper we review the research on refining treatments for LLD. We first identify evidence-based treatments (EBTs) for LLD and the problems associated with efficacy and dissemination, then review approaches to conceptualizing mental illness, specifically concepts related to brain plasticity and the Research Domain Criteria (RDoc). Finally, we introduce ENGAGE as a streamlined treatment for LLD and discuss implications for future research.

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