Health Psychology Commons^™

Identifying Depression In The National Health And Nutrition Examination Survey Data Using A Deep Learning Algorithm, Jihoon Oh, Kyongsik Yun, Uri Maoz, Tae-Suk Kim, Jeong-Ho Chae

Psychology Faculty Articles and Research

Background

As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk factors of depression. However, accurately estimating epidemiological factors leading up to depression has remained challenging. Deep-learning algorithms can be applied to assess the factors leading up to prevalence and clinical manifestations of depression.

Methods

Customized deep-neural-network and machine-learning classifiers were assessed using survey data from 19,725 participants from the NHANES database (from 1999 through 2014) and 4949 from the South Korea NHANES (K-NHANES) database in 2014.

Results

A deep-learning algorithm showed area under the receiver operating characteristic curve (AUCs) …

Inquiry Into The Correlation Between Burnout And Depression, Irvin Sam Schonfeld, Jay Verkuilen, Renzo Bianchi

Publications and Research

The extent to which burnout refers to anything other than a depressive condition remains an object of controversy among occupational health specialists. In three studies conducted in two different countries and two different languages, we investigated the discriminant validity of burnout scales by evaluating the magnitude of the correlation between (latent) burnout and (latent) depression. In Study 1 (N = 911), burnout was assessed with the Maslach Burnout Inventory–General Survey’s Exhaustion subscale and depression with the depression module of the Patient Health Questionnaire (PHQ). In Study 2 (N = 1,386), the Shirom–Melamed Burnout Measure was used to assess burnout and …