Group-Personalized Regression Models for Predicting Mental Health Scores From Objective Mobile Phone Data Streams: Observational Study.

BACKGROUND: Objective behavioral markers of mental illness, often recorded through smartphones or wearable devices, have the potential to transform how mental health services are delivered and to help users monitor their own health. Linking objective markers to illness is commonly performed using population-level models, which assume that everyone is the same. The reality is that there are large levels of natural interindividual variability, both in terms of response to illness and in usual behavioral patterns, as well as intraindividual variability that these models do not consider. OBJECTIVE: The objective of this study was to demonstrate the utility of splitting the population into subsets of individuals that exhibit similar relationships between their objective markers and their mental states. Using these subsets, "group-personalized" models can be built for individuals based on other individuals to whom they are most similar. METHODS: We collected geolocation data from 59 participants who were part of the Automated Monitoring of Symptom Severity study at the University of Oxford. This was an observational data collection study. Participants were diagnosed with bipolar disorder (n=20); borderline personality disorder (n=17); or were healthy controls (n=22). Geolocation data were collected using a custom Android app installed on participants' smartphones, and participants weekly reported their symptoms of depression using the 16-item quick inventory of depressive symptomatology questionnaire. Population-level models were built to estimate levels of depression using features derived from the geolocation data recorded from participants, and it was hypothesized that results could be improved by splitting individuals into subgroups with similar relationships between their behavioral features and depressive symptoms. We developed a new model using a Dirichlet process prior for splitting individuals into groups, with a Bayesian Lasso model in each group to link behavioral features with mental illness. The result is a model for each individual that incorporates information from other similar individuals to augment the limited training data available. RESULTS: The new group-personalized regression model showed a significant improvement over population-level models in predicting mental health severity (P<.001). Analysis of subgroups showed that different groups were characterized by different features derived from raw geolocation data. CONCLUSIONS: This study demonstrates the importance of handling interindividual variability when developing models of mental illness. Population-level models do not capture nuances in how different individuals respond to illness, and the group-personalized model demonstrates a potential way to overcome these limitations when estimating mental state from objective behavioral features.

Heart rate variability in bipolar disorder and borderline personality disorder: a clinical review.

Heart rate variability (HRV) in psychiatric disorders has become an increasing area of interest in recent years following technological advances that enable non-invasive monitoring of autonomic nervous system regulation. However, the clinical interpretation of HRV features remain widely debated or unknown. Standardisation within studies of HRV in psychiatric disorders is poor, making it difficult to reproduce or build on previous work. Recently, a Guidelines for Reporting Articles on Psychiatry and Heart rate variability checklist has been proposed to address this issue. Here we assess studies of HRV in bipolar disorder and borderline personality disorder against this checklist and discuss the implication for ongoing research in this area.

Desynchronization of diurnal rhythms in bipolar disorder and borderline personality disorder.

It has long been proposed that diurnal rhythms are disturbed in bipolar disorder (BD). Such changes are obvious in episodes of mania or depression. However, detailed study of patients between episodes has been rare and comparison with other psychiatric disorders rarer still. Our hypothesis was that evidence for desynchronization of diurnal rhythms would be evident in BD and that we could test the specificity of any effect by studying borderline personality disorder (BPD). Individuals with BD (n = 36), BPD (n = 22) and healthy volunteers (HC, n = 25) wore a portable heart rate and actigraphy device and used a smart-phone to record self-assessed mood scores 10 times per day for 1 week. Average diurnal patterns of heart rate (HR), activity and sleep were compared within and across groups. Desynchronization in the phase of diurnal rhythms of HR compared with activity were found in BPD (+3 h) and BD (+1 h), but not in HC. A clear diurnal pattern for positive mood was found in all subject groups. The coherence between negative and irritable mood and HR showed a four-cycle per day component in BD and BPD, which was not present in HC. The findings highlight marked de-synchronisation of measured diurnal function in both BD but particularly BPD and suggest an increased association with negative and irritable mood at ultradian frequencies. These findings enhance our understanding of the underlying physiological changes associated with BPD and BD, and suggest objective markers for monitoring and potential treatment targets. Improved mood stabilisation is a translational objective for management of both patient groups.

Metastatic Neuroendocrine Carcinoma of Unknown Origin Arising in the Femoral Nerve Sheath.

BACKGROUND: Metastatic neuroendocrine carcinoma of unknown origin is a rare condition, usually presenting with lesions in the liver and/or lung. We present the first reported case of a metastatic neuroendocrine carcinoma of unknown origin arising in the femoral nerve sheath. CASE DESCRIPTION: Magnetic resonance imaging demonstrated what was thought to be a schwannoma in the left femoral nerve sheath in the proximal femoral triangle, immediately inferior to the anterior inferior iliac spine. At the time of operation, the tumor capsule was invading surrounding tissue, as well as three trunks of the femoral nerve. The patient underwent a subtotal resection, preserving the integrity of the residual functioning femoral nerve trunks. Histologic evaluation determined that the tumor had features consistent with a metastatic neuroendocrine carcinoma of unknown primary origin. The patient recovered well postoperatively, and subsequent radiologic evaluation failed to demonstrate a potential primary site. Unfortunately, the patient re-presented with disease progression and was subsequently referred to palliative care. CONCLUSIONS: We recommend that there is a definite role for surgery in the management of solitary neuroendocrine carcinoma of unknown origin.