Evaluating the Effects of a Self-Help Mobile Phone App on Worry and Rumination Experienced by Young Adults: Randomized Controlled Trial.

Background: Delivery of preventative interventions via mobile phone apps offers an effective and accessible way to address the global priority of improving the mental health of adolescents and young adults. A proven risk factor for anxiety and depression is elevated worry and rumination, also known as repetitive negative thinking (RNT).

Objective: This was a prevention mechanism trial that aimed to investigate whether an RNT-targeting self-help mobile phone app (MyMoodCoach) reduces worry and rumination in young adults residing in the United Kingdom.

Mood instability in patients with unipolar depression measured using smartphones and the association with measures of wellbeing, recovery and functioning.

Objective: While mood instability is strongly linked to depression, its ramifications remain unexplored. In patients diagnosed with unipolar depression (UD), our objective was to investigate the association between mood instability, calculated based on daily smartphone-based patient-reported data on mood, and functioning, quality of life, perceived stress, empowerment, rumination, recovery, worrying and wellbeing.

Methods: Patients with UD completed daily smartphone-based self-assessments of mood for 6 months, making it possible to calculate mood instability using the Root Mean Squared Successive Difference (rMSSD) method.

Using digital phenotyping to classify bipolar disorder and unipolar disorder - exploratory findings using machine learning models.

The aims were to investigate 1) differences in smartphone-based data on phone usage between bipolar disorder (BD) and unipolar disorder (UD) and 2) by using machine learning models, the sensitivity, specificity, and AUC of the combined smartphone data in classifying BD and UD. Daily smartphone-based self-assessments of mood and same-time passively collected smartphone data on smartphone usage was available for six months. A total of 64 patients with BD and 74 patients with UD were included.

The effect of smartphone-based monitoring and treatment including clinical feedback versus smartphone-based monitoring without clinical feedback in bipolar disorder: the SmartBipolar trial-a study protocol for a randomized controlled parallel-group trial.

Introduction: A substantial proportion of patients with bipolar disorder experience daily subsyndromal mood swings, and the term "mood instability" reflecting the variability in mood seems associated with poor prognostic factors, including impaired functioning, and increased risk of hospitalization and relapse. During the last decade, we have developed and tested a smartphone-based system for monitoring bipolar disorder. The present SmartBipolar randomized controlled trial (RCT) aims to investigate whether (1) daily smartphone-based outpatient monitoring and treatment including clinical feedback versus (2) daily smartphone-based monitoring without clinical feedback or (3) daily smartphone-based mood monitoring only improves mood instability and other clinically relevant patient-related outcomes in patients with bipolar disorder.

Mood instability and activity/energy instability in patients with bipolar disorder according to day-to-day smartphone-based data - An exploratory post hoc study.

Background: Alterations and instability in mood and activity/energy has been associated with impaired functioning and risk of relapse in bipolar disorder. The present study aimed to investigate whether mood instability and activity/energy instability are associated, and whether these instability measures are associated with stress, quality of life and functioning in patients with bipolar disorder.

Methods: Data from two studies were combined for exploratory post hoc analyses.

Irritability in bipolar disorder and unipolar disorder measured daily using smartphone-based data: An exploratory post hoc study.

Objective: To investigate (i) the proportions of time with irritability and (ii) the association between irritability and affective symptoms and functioning, stress, and quality of life in patients with bipolar disorder (BD) and unipolar depressive disorder (UD).

Methods: A total of 316 patients with BD and 58 patients with UD provided self-reported once-a-day data on irritability and other affective symptoms using smartphones for a total of 64,129 days with observations. Questionnaires on perceived stress and quality of life and clinical evaluations of functioning were collected multiple times during the study.

Differences in mobility patterns according to machine learning models in patients with bipolar disorder and patients with unipolar disorder.

Background: It is essential to differentiate bipolar disorder (BD) from unipolar disorder (UD) as the course of illness and treatment guidelines differ between the two disorders. Measurements of activity and mobility could assist in this discrimination.

Aims: 1) To investigate differences in smartphone-based location data between BD and UD, and 2) to investigate the sensitivity, specificity, and AUC of combined location data in classifying BD and UD.

Reducing worry and rumination in young adults via a mobile phone app: study protocol of the ECoWeB (Emotional Competence for Well-Being in Young Adults) randomised controlled trial focused on repetitive negative thinking.

Background: Promoting well-being and preventing poor mental health in young people is a major global priority. Building emotional competence skills via a mobile app may be an effective, scalable and acceptable way to do this. A particular risk factor for anxiety and depression is elevated worry and rumination (repetitive negative thinking, RNT).

Automatically Generated Smartphone Data in Young Patients With Newly Diagnosed Bipolar Disorder and Healthy Controls.

Smartphones may facilitate continuous and fine-grained monitoring of behavioral activities automatically generated data and could prove to be especially valuable in monitoring illness activity in young patients with bipolar disorder (BD), who often present with rapid changes in mood and related symptoms. The present pilot study in young patients with newly diagnosed BD and healthy controls (HC) aimed to (1) validate automatically generated smartphone data reflecting physical and social activity and phone usage against validated clinical rating scales and questionnaires; (2) investigate differences in automatically generated smartphone data between young patients with newly diagnosed BD and HC; and (3) investigate associations between automatically generated smartphone data and smartphone-based self-monitored mood and activity in young patients with newly diagnosed BD. A total of 40 young patients with newly diagnosed BD and 21 HC aged 15-25 years provided daily automatically generated smartphone data for 3-779 days [median (IQR) = 140 (11.

Mood and Activity Measured Using Smartphones in Unipolar Depressive Disorder.

Smartphones comprise a promising tool for symptom monitoring in patients with unipolar depressive disorder (UD) collected as either patient-reportings or possibly as automatically generated smartphone data. However, only limited research has been conducted in clinical populations. We investigated the association between smartphone-collected monitoring data and validated psychiatric ratings and questionnaires in a well-characterized clinical sample of patients diagnosed with UD.

Prevalences of comorbid anxiety disorder and daily smartphone-based self-reported anxiety in patients with newly diagnosed bipolar disorder.

Background: Around 40% of patients with bipolar disorder (BD) additionally have anxiety disorder. The prevalence of anxiety in patients with newly diagnosed BD and their first-degree relatives (UR) has not been investigated.ObjectiveTo investigate (1) the prevalence of a comorbid anxiety diagnosis in patients with newly diagnosed BD and their UR, (2) sociodemographic and clinical differences between patients with and without a comorbid anxiety diagnosis and (3) the association between smartphone-based patient-reported anxiety and observer-based ratings of anxiety and functioning, respectively.

Service User Experiences of Integrating a Mobile Solution (IMPACHS) Into Clinical Treatment for Psychosis.

Innovative technological solutions are increasingly being introduced into psychotherapy. Understanding service user perspectives is a key aspect in adapting this technology to treatment. This study investigated service users' personal experience of the utility, challenges, and rewards of using an mHealth solution in cognitive behavioral therapy for psychosis (CBTp).

The effect of smartphone-based monitoring and treatment on the rate and duration of psychiatric readmission in patients with unipolar depressive disorder: The RADMIS randomized controlled trial.

Background: Patients with unipolar depressive disorder are frequently hospitalized, and the period following discharge is a high-risk-period. Smartphone-based treatments are receiving increasing attention among researchers, clinicians, and patients. We aimed to investigate whether a smartphone-based monitoring and treatment system reduces the rate and duration of readmissions, more than standard treatment, in patients with unipolar depressive disorder following hospitalization.

Smartphone-based activity measurements in patients with newly diagnosed bipolar disorder, unaffected relatives and control individuals.

Background: In DSM-5 activity is a core criterion for diagnosing hypomania and mania. However, there are no guidelines for quantifying changes in activity. The objectives of the study were (1) to investigate daily smartphone-based self-reported and automatically-generated activity, respectively, against validated measurements of activity; (2) to validate daily smartphone-based self-reported activity and automatically-generated activity against each other; (3) to investigate differences in daily self-reported and automatically-generated smartphone-based activity between patients with bipolar disorder (BD), unaffected relatives (UR) and healthy control individuals (HC).

Patient-evaluated cognitive function measured with smartphones and the association with objective cognitive function, perceived stress, quality of life and function capacity in patients with bipolar disorder.

Background: Cognitive impairments in patients with bipolar disorder (BD) have been associated with reduced functioning.

Aims: To investigate the association between (1) patient-evaluated cognitive function measured daily using smartphones and stress, quality of life and functioning, respectively, and (2) patient-evaluated cognitive function and objectively measured cognitive function with neuropsychological tests.

Methods: Data from two randomized controlled trials were combined.

Daily mobility patterns in patients with bipolar disorder and healthy individuals.

Background: Alterations in energy and activity in bipolar disorder (BD) differ between affective states and compared with healthy control individuals (HC). Measurements of activity could discriminate between BD and HC and in the monitoring of affective states within BD. The aims were to investigate differences in 1) passively collected smartphone-based location data (location data) between BD and HC, and 2) location data in BD between affective states.

Daily self-reported and automatically generated smartphone-based sleep measurements in patients with newly diagnosed bipolar disorder, unaffected first-degree relatives and healthy control individuals.

Objectives: (1) To investigate daily smartphone-based self-reported and automatically generated sleep measurements, respectively, against validated rating scales; (2) to investigate if daily smartphone-based self-reported sleep measurements reflected automatically generated sleep measurements and (3) to investigate the differences in smartphone-based sleep measurements between patients with bipolar disorder (BD), unaffected first-degree relatives (UR) and healthy control individuals (HC).

Methods: We included 203 patients with BD, 54 UR and 109 HC in this study. To investigate whether smartphone-based sleep calculated from self-reported bedtime, wake-up time and screen on/off time reflected validated rating scales, we used the Pittsburgh Sleep Quality Index (PSQI) and sleep items on the Hamilton Depression Rating Scale 17-item (HAMD-17) and the Young Mania Rating Scale (YMRS).

Mood, activity, and sleep measured via daily smartphone-based self-monitoring in young patients with newly diagnosed bipolar disorder, their unaffected relatives and healthy control individuals.

Diagnostic evaluations and early interventions of patients with bipolar disorder (BD) rely on clinical evaluations. Smartphones have been proposed to facilitate continuous and fine-grained self-monitoring of symptoms. The present study aimed to (1) validate daily smartphone-based self-monitored mood, activity, and sleep, against validated questionnaires and clinical ratings in young patients with newly diagnosed BD, unaffected relatives (UR), and healthy controls persons (HC); (2) investigate differences in daily smartphone-based self-monitored mood, activity, and sleep in young patients with newly diagnosed BD, UR, and HC; (3) investigate associations between self-monitored mood and self-monitored activity and sleep, respectively, in young patients with newly diagnosed BD.

Daily estimates of clinical severity of symptoms in bipolar disorder from smartphone-based self-assessments.

Currently, the golden standard for assessing the severity of depressive and manic symptoms in patients with bipolar disorder (BD) is clinical evaluations using validated rating scales such as the Hamilton Depression Rating Scale 17-items (HDRS) and the Young Mania Rating Scale (YMRS). Frequent automatic estimation of symptom severity could potentially help support monitoring of illness activity and allow for early treatment intervention between outpatient visits. The present study aimed (1) to assess the feasibility of producing daily estimates of clinical rating scores based on smartphone-based self-assessments of symptoms collected from a group of patients with BD; (2) to demonstrate how these estimates can be utilized to compute individual daily risk of relapse scores.

Mood instability in patients with newly diagnosed bipolar disorder, unaffected relatives, and healthy control individuals measured daily using smartphones.

Objectives: To investigate whether mood instability (MI) qualify as a trait marker for bipolar disorder (BD) we investigated: 1) differences in smartphone-based self-reported MI between three groups: patients with newly diagnosed BD, unaffected first-degree relatives (UR), and healthy control individuals (HC); 2) the correlation between MI and functioning, stress, and duration of illness, respectively; and 3) the validity of smartphone-based self-evaluated mood ratings as compared to observer-based ratings of depressed and manic mood.

Methods: 203 patients with newly diagnosed BD, 54 UR and 109 HC were included as part of the longitudinal Bipolar Illness Onset study. Participants completed daily smartphone-based mood ratings for a period of up to two years and were clinically assessed with ratings of depression, mania and functioning.

Forecasting Mood in Bipolar Disorder From Smartphone Self-assessments: Hierarchical Bayesian Approach.

Background: Bipolar disorder is a prevalent mental health condition that is imposing significant burden on society. Accurate forecasting of symptom scores can be used to improve disease monitoring, enable early intervention, and eventually help prevent costly hospitalizations. Although several studies have examined the use of smartphone data to detect mood, only few studies deal with forecasting mood for one or more days.

Hypomania/Mania by DSM-5 definition based on daily smartphone-based patient-reported assessments.

Introduction: The DSM-5 has introduced elevated/irritable mood and increased activity/ energy as equal and necessary criterion A symptoms for a diagnosis of (hypo)mania. The impact of these changes is poorly elucidated. The aim of the study was to investigate differences in the prevalence of elevated/irritable mood with and without co-occurring increased activity, and the associations between these, in patients with an ICD-10 and DSM-IV diagnosis of BD, using real life daily smartphone-based patient-reported measures of mood, irritability and activity.