Dataset Information

A Mobile Application for Monitoring and Management of Depressed Mood in a Vulnerable Pregnant Population.

ABSTRACT:

Objective

This study tested whether a mood tracking and alert (MTA) mobile application (app) improved mental health care delivery in a high-risk obstetric population.

Methods

Pregnant women with depressive symptomatology at <32 weeks gestation were followed for eight weeks after randomization to a control patient portal (PP) app alone or with the MTA app. The MTA app monitored activity, assessed mood, and alerted obstetric providers of signs of worsening mood.

Results

Seventy-two women enrolled (PP, N=24; MTA, N=48). MTA users had significantly more contacts addressing mental health, and as gestational age increased, they rated ability to manage their own health significantly better than women in the control group. Women who received telephone contact from a provider triggered by an MTA app alert were significantly more likely to receive a mental health specialist referral.

Conclusions

A mobile MTA app improved service delivery and patient engagement among patients with perinatal depression symptoms.

SUBMITTER: Hantsoo L

PROVIDER: S-EPMC5750085 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Publications

A Mobile Application for Monitoring and Management of Depressed Mood in a Vulnerable Pregnant Population.

Hantsoo Liisa L Criniti Stephanie S Khan Annum A Moseley Marian M Kincler Naomi N Faherty Laura J LJ Epperson C Neill CN Bennett Ian M IM

Psychiatric services (Washington, D.C.) 20171016 1

<h4>Objective</h4>This study tested whether a mood tracking and alert (MTA) mobile application (app) improved mental health care delivery in a high-risk obstetric population.<h4>Methods</h4>Pregnant women with depressive symptomatology at <32 weeks gestation were followed for eight weeks after randomization to a control patient portal (PP) app alone or with the MTA app. The MTA app monitored activity, assessed mood, and alerted obstetric providers of signs of worsening mood.<h4>Results</h4>Seven ...[more]

PMID: 29032705

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Project description:Inflammation plays a significant role in the pathophysiology of depression. However, not all individuals exposed to inflammatory challenge develop depression, and identifying those at risk is necessary to develop targeted monitoring, prevention, and treatment strategies. Within a randomized double-blind placebo-controlled study (n = 115), we examined whether leukocyte transcriptome profiles predicted inflammation-induced depressed mood in volunteers who received low-dose intravenous endotoxin (n = 58; aged 18-50). At baseline, transcription factor (TF) activities were assessed using genome-wide transcriptional profiling of peripheral blood mononuclear cells and promoter-based bioinformatic analyses. Then, participants were administered endotoxin. Self-reported depressed mood was assessed using the Profile of Mood States. Based on extant studies linking transcriptional profiles to depressive disorder, we examined whether post-endotoxin depressed mood is predicted by baseline activity of TFs related to immune activation, sympathetic activation, and glucocorticoid insensitivity: respectively, nuclear factor kappa B (NF-kB), cAMP response element-binding protein (CREB), and glucocorticoid receptor (GR). Twenty-one participants (36%) experienced an increase in depressed mood from baseline to 2 h post endotoxin, when depressive response peaks. Bioinformatics analyses controlling for age, sex, ethnicity, body mass index, and physical sickness response revealed that post-endotoxin depressed mood was predicted by increased baseline activity of TFs related to inflammation (NF-kB) and beta-adrenergic signaling (CREB) and by decreased activity of GR-related TFs (P's < 0.001). Inflammation-induced depressed mood is predicted by peripheral transcriptome profiles related to immune activation, sympathetic activation, and glucocorticoid insensitivity. With further replication, these stress-related molecular profiles could be used for a novel genomic approach for identifying individuals at high-risk for the inflammatory subtype of depression.

Dataset Information

A Mobile Application for Monitoring and Management of Depressed Mood in a Vulnerable Pregnant Population.

Objective

Methods

Results

Conclusions

Publications

A Mobile Application for Monitoring and Management of Depressed Mood in a Vulnerable Pregnant Population.

Similar Datasets

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