Predicting severity of non-clinical depression: preliminary findings using an integrated approach.
BACKGROUND
Depression is characterized by disturbances in affect, cognition, brain and body function, yet studies have tended to focus on single domains of dysfunction. An integrated approach may provide a more complete profile of the range of deficits characterized by depressed individuals, but it is unclear whether this approach is able to predict depression severity over and above that predicted by single tasks or domains of function. In this study, we examined the value of combining multiple domains of function in predicting depression severity.


METHODS
Participants contained in the International Brain Database, (http://www.brainresource.com) had completed three testing components including a web-based questionnaire of Personal History, the Brain Resource Cognition battery of Neuropsychological tests, Personality assessment and Psychophysiological testing. Two hundred and sixty six of these participants were able to be classified as either non-depressed, mild-moderately or severely (non-clinically) depressed, based on a depression screening questionnaire. Analysis of variance identified variables on which the categorized participants differed. Significant variables were then entered into a series of stepwise regressions to examine their ability to predict depression scores.


RESULTS
An integrated model including measures of affect (increased Neuroticism; decreased Emotional Intelligence), cognition (increased variability of reaction time during a working memory task; decreased "name the word component score" in the verbal interference task), brain (decreased left-lateralized P150 ERP component during a working memory task) and body function (increased negative skin conductance level gradient) were found to predict more of the variation in depression severity than any single domain of function.


CONCLUSIONS
On the basis of behavioral as well as Psychophysiological findings reported in this study, it was suggested that deficits in subclinically depressed individuals are more pronounced during automatic stages of stimulus processing, and that performance in these individuals may improve (to the level displayed by controls) when task demands are increased. Findings also suggest that it is important to consider disturbances across different domains of function in order to elucidate depression severity. Each domain may contribute unique explanatory information consistent with an integrative model of depression, taking into account the role of both behavior and underlying neural changes.
Kemp
Andrew H
AH
The Brain Dynamics Center, University of Sydney and Westmead Hospital, NSW 2145, Australia. info@brain-dynamics.net
Hopkinson
Patrick J
PJ
Stephan
Blossom C M
BC
Clark
C Richard
CR
Gordon
Evian
E
Bryant
Richard A
RA
Williams
Leanne M
LM
D000161:Acoustic Stimulation / Q000379:methods; D000339:Affect / Q000502:physiology; D000704:Analysis of Variance; D016022:Case-Control Studies; D003071:Cognition / Q000502:physiology; D003863:Depression / Q000145:classification / Q000175:diagnosis* / Q000503:physiopathology*; D004569:Electroencephalography / Q000379:methods; D005071:Evoked Potentials / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D008570:Memory, Short-Term / Q000502:physiology; D015233:Models, Statistical; D009483:Neuropsychological Tests / Q000706:statistics & numerical data*; D010552:Personality Assessment / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D011569:Psychiatric Status Rating Scales / Q000706:statistics & numerical data*; D011601:Psychophysics; D012044:Regression Analysis; D011795:Surveys and Questionnaires