Smartphone monitoring of mood instability in young depressed patients: A latent-class analyses
This study captured daily and weekly mood ratings using a smartphone from bipolar
disorder (BD) and unipolar major depression disorder (MDD) subjects at high (HRMDD) and
low risk (LRMDD) for developing Bipolar Disorder (BD) and healthy controls (HC). Method:
40 subjects (18–30 yr)(6 BD, 13 HRMDD, 16 LRMDD and 5 HC) were studied and a total of
2401 daily and 744 weekly ratings were collected. HRMDD and LRMDD subjects were
naturalistically treated with antidepressants. We investigate if latent-class analyses of ratings …
disorder (BD) and unipolar major depression disorder (MDD) subjects at high (HRMDD) and
low risk (LRMDD) for developing Bipolar Disorder (BD) and healthy controls (HC). Method:
40 subjects (18–30 yr)(6 BD, 13 HRMDD, 16 LRMDD and 5 HC) were studied and a total of
2401 daily and 744 weekly ratings were collected. HRMDD and LRMDD subjects were
naturalistically treated with antidepressants. We investigate if latent-class analyses of ratings …
This study captured daily and weekly mood ratings using a smartphone from bipolar disorder (BD) and unipolar major depression disorder (MDD) subjects at high (HRMDD) and low risk (LRMDD) for developing Bipolar Disorder (BD) and healthy controls (HC).
Method
40 subjects (18 – 30 yr) (6 BD, 13 HRMDD, 16 LRMDD and 5 HC) were studied and a total of 2401 daily and 744 weekly ratings were collected. HRMDD and LRMDD subjects were naturalistically treated with antidepressants. We investigate if latent-class analyses of ratings can detect mood instability among MDD and BD groups.
Results
Our analyses revealed four underlying mood states correlating with clinical mood states. There was a trend for greater number of state changes in BD and HRMDD subjects compared to LRMDD and HC groups.
Conclusion
Smartphone ratings may adequately capture mood instability in BD subjects and at risk HRMDD subjects and offers a prudent way for monitoring development of serious manic symptoms.
pmc.ncbi.nlm.nih.gov
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