AIMC Topic: Depression

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A social robot intervention on depression, loneliness, and quality of life for Taiwanese older adults in long-term care.

International psychogeriatrics
OBJECTIVES: To investigate the effect of a social robot intervention on depression, loneliness, and quality of life of older adults in long-term care (LTC) and to explore participants' experiences and perceptions after the intervention.

Identifying the presence and timing of discrete mood states prior to therapy.

Behaviour research and therapy
The present study tested a novel, person-specific method for identifying discrete mood profiles from time-series data, and examined the degree to which these profiles could be predicted by lagged mood and anxiety variables and time-based variables, i...

Artificial neural networks for predicting social comparison effects among female Instagram users.

PloS one
Systematic exposure to social media causes social comparisons, especially among women who compare their image to others; they are particularly vulnerable to mood decrease, self-objectification, body concerns, and lower perception of themselves. This ...

Predicting future onset of depression among community dwelling adults in the Republic of Korea using a machine learning algorithm.

Neuroscience letters
Because depression has high prevalence and cause enduring disability, it is important to predict onset of depression among community dwelling adults. In this study, we aimed to build a machine learning-based predictive model for future onset of depre...

Depression phenotype identified by using single nucleotide exact amplicon sequence variants of the human gut microbiome.

Molecular psychiatry
Single nucleotide exact amplicon sequence variants (ASV) of the human gut microbiome were used to evaluate if individuals with a depression phenotype (DEPR) could be identified from healthy reference subjects (NODEP). Microbial DNA in stool samples o...

Impact of age at onset on the phenomenology of depression in treatment-seeking adults in the STAR*D trial.

Journal of affective disorders
BACKGROUND: - Adolescence is characterized by biological, emotional, and behavioral changes. The onset of depression during this vulnerable time may confer specific risks. This study examined whether symptoms of depression were associated with age at...

Machine Learning Identifies Large-Scale Reward-Related Activity Modulated by Dopaminergic Enhancement in Major Depression.

Biological psychiatry. Cognitive neuroscience and neuroimaging
BACKGROUND: Theoretical models have emphasized systems-level abnormalities in major depressive disorder (MDD). For unbiased yet rigorous evaluations of pathophysiological mechanisms underlying MDD, it is critically important to develop data-driven ap...

Depression Prediction by Using Ecological Momentary Assessment, Actiwatch Data, and Machine Learning: Observational Study on Older Adults Living Alone.

JMIR mHealth and uHealth
BACKGROUND: Although geriatric depression is prevalent, diagnosis using self-reporting instruments has limitations when measuring the depressed mood of older adults in a community setting. Ecological momentary assessment (EMA) by using wearable devic...

Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis.

Human brain mapping
Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity ...