Daily mood monitoring of symptoms using smartphones in bipolar disorder: A pilot study assessing the feasibility of ecological momentary assessment

Moment-to-moment affective dynamics in schizophrenia and bipolar disorder

BACKGROUND

Affective disturbances in schizophrenia and bipolar disorder may represent a transdiagnostic etiological process as well as a target of intervention. Hypotheses on similarities and differences in various parameters of affective dynamics (intensity, successive/acute changes, variability, and reactivity to stress) between the two disorders were tested.

METHODS

Experience sampling method was used to assess dynamics of positive and negative affect, 10 times a day over 6 consecutive days. Patients with schizophrenia (n = 46) and patients with bipolar disorder (n = 46) were compared against age-matched healthy controls (n = 46).

RESULTS

Compared to controls, the schizophrenia group had significantly more intense momentary negative affect, a lower likelihood of acute changes in positive affect, and reduced within-person variability of positive affect. The bipolar disorder group was not significantly different from either the schizophrenia group or the healthy control group on any affect indexes. Within the schizophrenia group, level of depression was associated with weaker reactivity to stress for negative affect. Within the bipolar disorder group, level of depression was associated with lower positive affect.

CONCLUSIONS

Patients with schizophrenia endured a more stable and negative affective state than healthy individuals, and were less likely to be uplifted in response to happenings in daily life. There is little evidence that these affective constructs characterize the psychopathology of bipolar disorder; such investigation may have been limited by the heterogeneity within group. Our findings supported the clinical importance of assessing multiple facets of affective dynamics beyond the mean levels of intensity.

Across and Within- Individual Associations Between Everyday Activities and Quality of Life Relevant Measures, in Workers with Type 1 Diabetes

Relationships between activity engagement and health related quality of life (HRQOL) can differ based on the level of analyses. For instance, greater exercise on average may be linked with lower fatigue across individuals (between-person level), whereas the momentary experience of exercise may be associated with increased fatigue within an individual (within-person level). Disentangling the between- and within-person associations between everyday activities and HRQOL outcomes may provide insights for personalized lifestyle-oriented health promotion efforts for individuals with chronic conditions. The purpose of this paper was to examine the between- and within-person relationships between activity engagement and HRQOL relevant measures in a sample of 92 workers with type 1 diabetes (T1D), from whom we collected ecological momentary assessment (EMA) data 5-6 times daily over 14 days. At each EMA prompt, information was collected on the activity participants just engaged in, and HRQOL relevant metrics (e.g. mental health, blood glucose, fatigue, functioning). Momentary reports of "caring for others", and more frequently "caring for others", were both associated with decreased HRQOL. Reporting napping 10% or more of the time during a person's waking hours, but not the momentary experience of napping, was associated with decreased HRQOL. Momentary reports of sleeping were associated with low activity satisfaction relative to other activities, but higher activity importance. Study results provided a quantitative representation of the lived experience of T1D covering multiple types of activity engagement, which potentially has health promotion implications for workers with T1D.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11482-023-10171-2.

Fathers' sensitive parenting enhanced by prenatal video-feedback: a randomized controlled trial using ultrasound imaging

BACKGROUND

The aim of this study was to evaluate an interaction-based prenatal parenting intervention program aimed at promoting parental sensitivity and involvement in expectant fathers using ultrasound images: Prenatal Video-Feedback Intervention to Promote Positive Parenting (VIPP-PRE).

METHODS

In this randomized controlled trial, 73 first-time, healthy expectant fathers were enrolled. Participants were randomly assigned to the VIPP-PRE intervention (n = 39) or a dummy intervention (n = 34). Parental sensitivity was coded from video-recorded 10-min interactions with an infant simulator at a prenatal pretest and with fathers' own infant at a postnatal posttest. Prenatal and postnatal involvement was assessed via an application on participants' smartphones.

RESULTS

Fathers receiving VIPP-PRE demonstrated increased sensitivity across the perinatal period, relative to fathers receiving a dummy intervention. Fathers' involvement with the infant increased significantly from the prenatal to postnatal period, regardless of the intervention.

CONCLUSIONS

Prenatal video-feedback using ultrasound imaging of the unborn child has the potential to promote the quality of parenting in an important, but understudied, population and period: men in the transition to fatherhood. Future research should examine the long-term effectiveness of VIPP-PRE and its effectiveness in increasing parenting quality in at-risk families.

IMPACT

This study identifies a brief and focused prenatal intervention using assisted interactions between the father and his baby by means of ultrasound imaging as a promising strategy to improve sensitive fathering in the early postnatal phase. Our study shows that pregnancy provides a window of opportunity for promoting prenatal involvement and bonding in expectant fathers, with potential long-term benefits for the future father-child relationship. Ultrasound measures are currently used to monitor fetal growth and development, but our results suggest that they may also create an opportunity for stimulating father-infant interaction to promote postnatal caregiving quality.

Understanding the Subjective Experience of Long-term Remote Measurement Technology Use for Symptom Tracking in People With Depression: Multisite Longitudinal Qualitative Analysis

BACKGROUND

Remote measurement technologies (RMTs) have the potential to revolutionize major depressive disorder (MDD) disease management by offering the ability to assess, monitor, and predict symptom changes. However, the promise of RMT data depends heavily on sustained user engagement over extended periods. In this paper, we report a longitudinal qualitative study of the subjective experience of people with MDD engaging with RMTs to provide insight into system usability and user experience and to provide the basis for future promotion of RMT use in research and clinical practice.

OBJECTIVE

We aimed to understand the subjective experience of long-term engagement with RMTs using qualitative data collected in a longitudinal study of RMTs for monitoring MDD. The objectives were to explore the key themes associated with long-term RMT use and to identify recommendations for future system engagement.

METHODS

In this multisite, longitudinal qualitative research study, 124 semistructured interviews were conducted with 99 participants across the United Kingdom, Spain, and the Netherlands at 3-month, 12-month, and 24-month time points during a study exploring RMT use (the Remote Assessment of Disease and Relapse-Major Depressive Disorder study). Data were analyzed using thematic analysis, and interviews were audio recorded, transcribed, and coded in the native language, with the resulting quotes translated into English.

RESULTS

There were 5 main themes regarding the subjective experience of long-term RMT use: research-related factors, the utility of RMTs for self-management, technology-related factors, clinical factors, and system amendments and additions.

CONCLUSIONS

The subjective experience of long-term RMT use can be considered from 2 main perspectives: experiential factors (how participants construct their experience of engaging with RMTs) and system-related factors (direct engagement with the technologies). A set of recommendations based on these strands are proposed for both future research and the real-world implementation of RMTs into clinical practice. Future exploration of experiential engagement with RMTs will be key to the successful use of RMTs in clinical care.

The interplay of daily affect and impulsivity measured by mobile surveys in bipolar disorder

Background

Impulsivity is a prominent feature of bipolar disorder associated with various negative sequelae; moreover, it may be a precursor to shifts in affect or mood, but little is known about its association with affect on a day-to-day timescale. Ecological momentary assessments (a method that captures moment-to-moment ratings of psychological states by repeatedly sampling the same individual) of impulsivity and affect using mobile surveys allow for more nuanced examination of mechanisms of mood and behavior dysregulation. However, few existing studies have validated an ecological momentary assessment of impulsivity in bipolar disorder and examined its time-lagged associations with positive and negative affect. 70 participants with bipolar disorder and 102 healthy comparisons participated in an intensive longitudinal study: they underwent 14 days of ecological momentary assessment data collection annually for 1–4 years. Multiple measures of impulsivity and affect were collected using self-report, behavioral, and ecological momentary assessment modalities; these measures were compared, and levels of impulsivity were compared between bipolar disorder and healthy comparison groups. Time-lagged analyses using daily means explored the next-day predictive relationship of impulsivity on positive/negative affect, and vice versa.

Results

The ecological momentary measure of impulsivity was moderately correlated with the self-report but not behavioral impulsivity measure. Bipolar disorder participants evinced higher self-report, behavioral, and daily impulsivity than healthy comparison participants. Time-lagged analyses revealed a bi-directional association between high impulsivity and high next-day negative (but not positive) affect. Post hoc analyses showed that impulsivity specifically predicted next-day anger and anxiety.

Conclusions

Our multimodal assessment of impulsivity allowed for an examination of the day-to-day course of impulsivity and affect, crucial steps toward understanding the mechanisms of mood symptom and episode onset in bipolar disorder.

Understanding the development of bipolar disorder and borderline personality disorder in young people: a meta-review of systematic reviews

BACKGROUND

There is ongoing debate on the nosological position of bipolar disorder (BD) and borderline personality disorder (BPD). Identifying the unique and shared risks, developmental pathways, and symptoms in emerging BD and BPD could help the field refine aetiological hypotheses and improve the prediction of the onset of these disorders. This study aimed to: (a) systematically synthesise the available evidence from systematic reviews (SRs) and meta-analyses (MAs) concerning environmental, psychosocial, biological, and clinical factors leading to the emergence of BD and BPD; (b) identify the main differences and common features between the two disorders to characterise their complex interplay and, (c) highlight remaining evidence gaps.

METHODS

Data sources were; PubMed, PsychINFO, Embase, Cochrane, CINAHL, Medline, ISI Web of Science. Overlap of included SRs/MAs was assessed using the corrected covered area process. The methodological quality of each included SR and MA was assessed using the AMSTAR.

RESULTS

22 SRs and MAs involving 249 prospective studies met eligibility criteria. Results demonstrated that family history of psychopathology, affective instability, attention deficit hyperactivity disorder, anxiety disorders, depression, sleep disturbances, substance abuse, psychotic symptoms, suicidality, childhood adversity and temperament were common predisposing factors across both disorders. There are also distinct factors specific to emerging BD or BPD.

CONCLUSIONS

Prospective studies are required to increase our understanding of the development of BD and BPD onset and their complex interplay by concurrently examining multiple measures in BD and BPD at-risk populations.

Initial Psychometric Properties of 7 NeuroUX Remote Ecological Momentary Cognitive Tests Among People With Bipolar Disorder: Validation Study

BACKGROUND

As smartphone technology has become nearly ubiquitous, there is a growing body of literature suggesting that ecological momentary cognitive testing (EMCT) offers advantages over traditional pen-and-paper psychological assessment. We introduce a newly developed platform for the self-administration of cognitive tests in ecologically valid ways.

OBJECTIVE

The aim of this study is to develop a Health Insurance Portability and Accountability Act-compliant EMCT smartphone-based platform for the frequent and repeated testing of cognitive abilities in everyday life. This study examines the psychometric properties of 7 mobile cognitive tests covering domains of processing speed, visual working memory, recognition memory, and response inhibition within our platform among persons with and without bipolar disorder (BD). Ultimately, if shown to have adequate psychometric properties, EMCTs may be useful in research on BD and other neurological and psychiatric illnesses.

METHODS

A total of 45 persons with BD and 21 demographically comparable healthy volunteer participants (aged 18-65 years) completed smartphone-based EMCTs 3 times daily for 14 days. Each EMCT session lasted approximately 1.5 minutes. Only 2 to 3 tests were administered in any given session, no test was administered more than once per day, and alternate test versions were administered in each session.

RESULTS

The mean adherence to the EMCT protocol was 69.7% (SD 20.5%), resulting in 3965 valid and complete tests across the full sample. Participants were significantly more likely to miss tests on later versus earlier study days. Adherence did not differ by diagnostic status, suggesting that BD does not interfere with EMCT participation. In most tests, age and education were related to EMCT performance in expected directions. The average performances on most EMCTs were moderately to strongly correlated with the National Institutes of Health Toolbox Cognition Battery. Practice effects were observed in 5 tests, with significant differences in practice effects by BD status in 3 tests.

CONCLUSIONS

Although additional reliability and validity data are needed, this study provides initial psychometric support for EMCTs in the assessment of cognitive performance in real-world contexts in BD.

A systematic review of engagement reporting in remote measurement studies for health symptom tracking

Remote Measurement Technologies (RMTs) could revolutionise management of chronic health conditions by providing real-time symptom tracking. However, the promise of RMTs relies on user engagement, which at present is variably reported in the field. This review aimed to synthesise the RMT literature to identify how and to what extent engagement is defined, measured, and reported, and to present recommendations for the standardisation of future work. Seven databases (Embase, MEDLINE and PsycINFO (via Ovid), PubMed, IEEE Xplore, Web of Science, and Cochrane Central Register of Controlled Trials) were searched in July 2020 for papers using RMT apps for symptom monitoring in adults with a health condition, prompting users to track at least three times during the study period. Data were synthesised using critical interpretive synthesis. A total of 76 papers met the inclusion criteria. Sixty five percent of papers did not include a definition of engagement. Thirty five percent included both a definition and measurement of engagement. Four synthetic constructs were developed for measuring engagement: (i) engagement with the research protocol, (ii) objective RMT engagement, (iii) subjective RMT engagement, and (iv) interactions between objective and subjective RMT engagement. The field is currently impeded by incoherent measures and a lack of consideration for engagement definitions. A process for implementing the reporting of engagement in study design is presented, alongside a framework for definition and measurement options available. Future work should consider engagement with RMTs as distinct from the wider eHealth literature, and measure objective versus subjective RMT engagement.Registration: This review has been registered on PROSPERO [CRD42020192652].

Detecting Mental Health Behaviors Using Mobile Interactions: Exploratory Study Focusing on Binge Eating

BACKGROUND

Binge eating is a subjective loss of control while eating, which leads to the consumption of large amounts of food. It can cause significant emotional distress and is often accompanied by purging behaviors (eg, meal skipping, overexercising, or vomiting).

OBJECTIVE

The aim of this study was to explore the potential of mobile sensing to detect indicators of binge-eating episodes, with a view toward informing the design of future context-aware mobile interventions.

METHODS

This study was conducted in 2 stages. The first involved the development of the DeMMI (Detecting Mental health behaviors using Mobile Interactions) app. As part of this, we conducted a consultation session to explore whether the types of sensor data we were proposing to capture were useful and appropriate, as well as to gather feedback on some specific app features relating to self-reporting. The second stage involved conducting a 6-week period of data collection with 10 participants experiencing binge eating (logging both their mood and episodes of binge eating) and 10 comparison participants (logging only mood). An optional interview was conducted after the study, which discussed their experience using the app, and 8 participants (n=3, 38% binge eating and n=5, 63% comparisons) consented.

RESULTS

The findings showed unique differences in the types of sensor data that were triangulated with the individuals' episodes (with nearby Bluetooth devices, screen and app use features, mobility features, and mood scores showing relevance). Participants had a largely positive opinion about the app, its unobtrusive role, and its ease of use. Interacting with the app increased participants' awareness of and reflection on their mood and phone usage patterns. Moreover, they expressed no privacy concerns as these were alleviated by the study information sheet.

CONCLUSIONS

This study contributes a series of recommendations for future studies wishing to scale our approach and for the design of bespoke mobile interventions to support this population.

Affective Dynamics and Mean Levels of Preschool Irritability and Sadness: Predictors of Children's Psychological Functioning Two Years Later

Although irritability and sadness are cardinal symptoms of depression, they are also common in preschoolers. The daily experiences of these emotions are not well-understood during early childhood, yet may provide insight into identification of early depressive symptoms. The current longitudinal study examined daily mean levels and emotion dynamics of preschool-aged children's irritability and sadness and psychiatric outcomes in early school-age. Parents (n = 291) completed 14 consecutive daily diaries about their preschoolers' emotions. Two years later, parents (n = 164) completed a semi-structured clinical interview and questionnaires about their children's psychological functioning. Strong correlations between mean and dynamic measures (rs = 0.65-0.91) were identified. Preschoolers' mean daily levels and dynamics of irritability (variability, instability, inertia) and sadness (instability, inertia) predicted symptoms and impairment 2 years later. Sadness instability and inertia continued to predict difficulties after adjusting for mean daily sadness. Fine-grained daily measures of preschoolers' affect may be help identify children at-risk for psychological problems.

Process and Outcome Evaluations of Smartphone Apps for Bipolar Disorder: Scoping Review

Background

Mental health apps (MHAs) provide opportunities for accessible, immediate, and innovative approaches to better understand and support the treatment of mental health disorders, especially those with a high burden, such as bipolar disorder (BD). Many MHAs have been developed, but few have had their effectiveness evaluated.

Objective

This systematic scoping review explores current process and outcome measures of MHAs for BD with the aim to provide a comprehensive overview of current research. This will identify the best practice for evaluating MHAs for BD and inform future studies.

Methods

A systematic literature search of the health science databases PsycINFO, MEDLINE, Embase, EBSCO, Scopus, and Web of Science was undertaken up to January 2021 (with no start date) to narratively assess how studies had evaluated MHAs for BD.

Results

Of 4051 original search results, 12 articles were included. These 12 studies included 435 participants, and of these, 343 had BD type I or II. Moreover, 11 of the 12 studies provided the ages (mean 37 years) of the participants. One study did not report age data. The male to female ratio of the 343 participants was 137:206. The most widely employed validated outcome measure was the Young Mania Rating Scale, being used 8 times. The Hamilton Depression Rating Scale-17/Hamilton Depression Rating Scale was used thrice; the Altman Self-Rating Mania Scale, Quick Inventory of Depressive Symptomatology, and Functional Assessment Staging Test were used twice; and the Coping Inventory for Stressful Situations, EuroQoL 5-Dimension Health Questionnaire, Generalized Anxiety Disorder Scale-7, Inventory of Depressive Symptomatology, Mindfulness Attention Awareness Scale, Major Depression Index, Morisky-Green 8-item, Perceived Stress Scale, and World Health Organization Quality of Life-BREF were used once. Self-report measures were captured in 9 different studies, 6 of which used MONARCA. Mood and energy levels were the most commonly used self-report measures, being used 4 times each. Furthermore, 11 of the 12 studies discussed the various confounding factors and barriers to the use of MHAs for BD.

Conclusions

Reported low adherence rates, usability challenges, and privacy concerns act as barriers to the use of MHAs for BD. Moreover, as MHA evaluation is itself developing, guidance for clinicians in how to aid patient choices in mobile health needs to develop. These obstacles could be ameliorated by incorporating co-production and co-design using participatory patient approaches during the development and evaluation stages of MHAs for BD. Further, including qualitative aspects in trials that examine patient experience of both mental ill health and the MHA itself could result in a more patient-friendly fit-for-purpose MHA for BD.

Adjunctive dietary intervention for bipolar disorder: a randomized, controlled, parallel-group, modified double-blinded trial of a high n-3 plus low n-6 diet

OBJECTIVE

To investigate the preliminary efficacy of a high n-3 plus low n-6 (H3-L6) dietary intervention in improving mood stability in Bipolar Disorder (BD) when compared to dietary intervention with usual U.S. levels of n-6 and n-3 polyunsaturated fatty acid (PUFA) intakes (control diet, CD).

METHODS

This 2-arm, parallel-group, randomized, modified double-blind, controlled 48-week study of 12-week intensive diet intervention in subjects with BD was conducted at a single suburban-rural site in the mid-Atlantic region. Participants with DSM-IV TR BD I or II with hypomanic or depressive symptoms were randomized, stratified on gender (N = 82). The intervention included the provision of group-specific study foods and dietary counseling. Variability of mood symptoms was measured by a twice-daily, 12-week ecological momentary analysis (EMA) paradigm, and group differences were analyzed using multilevel models. Circulating n-3 and n-6 fatty acids were measured at baseline and after 4, 8, and 12 weeks of diet exposure.

RESULTS

All 82 randomized participants were included in biochemical analyses. Seventy participants completed at least 2 EMA surveys and were included in primary EMA analyses. Variability in mood, energy, irritability, and pain as measured using EMA was reduced in the H3-L6 group compared to the CD group. No significant differences in mean ratings of mood symptoms, or any other symptom measures, were detected. The dietary intervention effect on target PUFAs significantly differed by the group over time.

CONCLUSIONS

A dietary intervention adjunctive to usual care showed preliminary efficacy in improving variability in mood symptoms in participants with BD.

TRIAL REGISTRATION

ClinicalTrials.Gov NCT02272010.

Patients' adherence to smartphone apps in the management of bipolar disorder: a systematic review

Background

Despite an increasing number of available mental health apps in the bipolar disorder field, these tools remain scarcely implemented in everyday practice and are quickly discontinued by patients after downloading. The aim of this study is to explore adherence characteristics of bipolar disorder patients to dedicated smartphone interventions in research studies.

Methods

A systematic review following PRISMA guidelines was conducted. Three databases (EMBASE, PsychInfo and MEDLINE) were searched using the following keywords: "bipolar disorder" or "mood disorder" or “bipolar” combined with “digital” or “mobile” or “phone” or “smartphone” or “mHealth” or “ehealth” or "mobile health" or “app” or “mobile-health”.

Results

Thirteen articles remained in the review after exclusion criteria were applied. Of the 118 eligible studies, 39 did not provide adherence characteristics. Among the selected papers, study length, sample size and definition of measures of adherence were strongly heterogeneous. Activity rates ranged from 58 to 91.6%.

Conclusion

The adherence of bipolar patients to apps is understudied. Standardised measures of adherence should be defined and systematically evaluated in future studies dedicated to these tools.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40345-021-00224-6.

A pilot study on ecological momentary assessment in asylum-seeking children and adolescents resettled to Germany: Investigating compliance, post-migration factors, and the relation between daily mood, sleep patterns, and mental health

Background

Asylum-seeking children and adolescents (ASCs) resettled to western countries show elevated levels of psychological distress. While research on the mental health of ASCs is increasing, less is known about their day-to-day living experiences such as their daily mood, sleep patterns, and post-migration factors. Moreover, no examination in situ, using smartphone-assisted ecological momentary assessment (EMA), has been conducted up to now among ASCs. Furthermore, we do not know if screening measures succeed in reflecting the daily mood of ASCs experienced in everyday life.

Methods

We undertook a smartphone-assisted EMA study over a two-week period with 3 measurements a day. Participants were N = 40 ASCs from 10 different countries who had resettled to Germany. They completed standardized questionnaires screening for history of trauma and clinical symptoms (post-traumatic stress symptoms, depression, and anxiety) that were carried out in interview-like settings, and they participated in the subsequent EMA where they rated mood, sleep parameters, and post-migration factors on a daily basis. Multilevel models of clinical symptoms, daily mood, and sleep parameters were computed based on a total of 680 measurements.

Results

The multiply traumatized and highly distressed participants reported different levels of discrimination, and various social activities and contacts in the EMA. The overall compliance rate was shown to be 40.5%. Higher PTSS and anxiety scores were associated with lower levels of daily mood and poorer outcomes of some sleep parameters. Depression scores were not associated with any of the variables assessed in the EMA.

Conclusions

Smartphone-assisted EMA among ASCs resettled to Germany proved to be implementable despite a rather low compliance rate. Not only do ASCs show high symptom levels, they are also affected by these symptoms in their daily lives. The results emphasize the need for concise screenings and psychological treatment for this high-risk population. Limitations include the convenient nature of the sample and the lack of a comparison group.

Mobile App-Based Self-Report Questionnaires for the Assessment and Monitoring of Bipolar Disorder: Systematic Review

Background

Bipolar disorder is a chronic, progressive illness characterized by recurrent episodes of mania and depression. Self-report scales have historically played a significant role in the monitoring of bipolar symptoms. However, these tools rely on episodic memory, which can be unreliable and do not allow the clinician to monitor brief episodic symptoms or the course of symptoms over shorter periods of time. Mobile app–based questionnaires have been suggested as a tool to improve monitoring of patients with bipolar disorder.

Objective

This paper aims to determine the feasibility and validity of mobile app–based self-report questionnaires.

Methods

We performed a systematic review of the literature according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The PubMed, PsycInfo, Web of Science, Ovid MEDLINE, and EMBASE databases were searched for papers published in English that assessed adherence to and the validity of mobile app–based self-report questionnaires. Relevant studies published from database creation to May 22, 2020, were identified, and results examining the validity of and rates of adherence to app-based self-report questionnaires are reported.

Results

A total of 13 records were identified for inclusion in this review. Of these studies, 4 assessed the concurrent validity of mobile app–based self-report tools, with the majority of findings indicating significant associations between data collected using these tools and the Young Mania Rating Scale, Hamilton Depression Rating Scale-17, or Montgomery-Åsberg Depression Rating Scale (P<.001 to P=.24). Three studies comparing the variability or range of symptoms between patients with bipolar disorder and healthy controls suggested that these data are capable of differentiating between known groups. Two studies demonstrated statistically significant associations between data collected via mobile app–based self-report tools and instruments assessing other clinically important factors. Adherence rates varied across the studies examined. However, good adherence rates (>70%) were observed in all but 1 study using a once-daily assessment. There was a wide range of adherence rates observed in studies using twice-daily assessments (42%-95%).

Conclusions

These findings suggest that mobile app–based self-report tools are valid in the assessment of symptoms of mania and depression in euthymic patients with bipolar disorder. Data collected using these tools appear to differ between patients with bipolar disorder and healthy controls and are significantly associated with other clinically important measures. It is unclear at this time whether these tools can be used to detect acute episodes of mania or depression in patients with bipolar disorder. Adherence data indicate that patients with bipolar disorder show good adherence to self-report assessments administered daily for the duration of the study periods evaluated.

Validating Biobehavioral Technologies for Use in Clinical Psychiatry

The last decade has witnessed the development of sophisticated biobehavioral and genetic, ambulatory, and other measures that promise unprecedented insight into psychiatric disorders. As yet, clinical sciences have struggled with implementing these objective measures and they have yet to move beyond "proof of concept." In part, this struggle reflects a traditional, and conceptually flawed, application of traditional psychometrics (i.e., reliability and validity) for evaluating them. This paper focuses on "resolution," concerning the degree to which changes in a signal can be detected and quantified, which is central to measurement evaluation in informatics, engineering, computational and biomedical sciences. We define and discuss resolution in terms of traditional reliability and validity evaluation for psychiatric measures, then highlight its importance in a study using acoustic features to predict self-injurious thoughts/behaviors (SITB). This study involved tracking natural language and self-reported symptoms in 124 psychiatric patients: (a) over 5-14 recording sessions, collected using a smart phone application, and (b) during a clinical interview. Importantly, the scope of these measures varied as a function of time (minutes, weeks) and spatial setting (i.e., smart phone vs. interview). Regarding reliability, acoustic features were temporally unstable until we specified the level of temporal/spatial resolution. Regarding validity, accuracy based on machine learning of acoustic features predicting SITB varied as a function of resolution. High accuracy was achieved (i.e., ~87%), but only when the acoustic and SITB measures were "temporally-matched" in resolution was the model generalizable to new data. Unlocking the potential of biobehavioral technologies for clinical psychiatry will require careful consideration of resolution.

Real-time mobile monitoring of bipolar disorder: a review of evidence and future directions

Rapidly accumulating data from mobile assessments are facilitating our ability to track patterns of emotions, behaviors, biologic rhythms, and their contextual influences in real time. These approaches have been widely applied to study the core features, traits, changes in states, and the impact of treatments in bipolar disorder (BD). This paper reviews recent evidence on the application of both passive and active mobile technologies to gain insight into the role of the circadian system and patterns of sleep and motor activity in people with BD. Findings of more than two dozen studies converge in demonstrating a broad range of sleep disturbances, particularly longer duration and variability of sleep patterns, lower average and greater variability of motor activity, and a shift to later peak activity and sleep midpoint, indicative of greater evening orientation among people with BD. The strong associations across the domains tapped by real-time monitoring suggest that future research should shift focus on sleep, physical/motor activity, or circadian patterns to identify common biologic pathways that influence their interrelations. The development of novel data-driven functional analytic tools has enabled the derivation of individualized multilevel dynamic representations of rhythms of multiple homeostatic regulatory systems. These multimodal tools can inform clinical research through identifying heterogeneity of the manifestations of BD and provide more objective indices of treatment response in real-world settings. Collaborative efforts with common protocols for the application of multimodal sensor technology will facilitate our ability to gain deeper insight into mechanisms and multisystem dynamics, as well as environmental, physiologic, and genetic correlates of BD.

Feasibility of gathering momentary and daily assessments of fear of crime using a smartphone application (STUNDA): Methodological considerations and findings from a study among Swedish university students

The introduction of experience research using smartphone applications has enabled researchers to explore previously uncharted territories within the social science landscape. The use of experience research methodologies may both avoid some of the biases associated with conventional survey methods and enable researchers to gather information on situational dimensions of different outcomes. While existing smartphone-based experience research is found in several scientific disciplines, one outcome that has rarely been studied using this approach is fear of crime. Although fear of crime here only serves as an example of an outcome that may benefit from being examined in situ, the main focus of this article is directed at assessing the feasibility of gathering momentary and daily assessments on fear of crime using an experience sampling research design. A sample of 191 university students participated in a non-incentivized research study by downloading the smartphone application STUNDA, completing a baseline survey and repeatedly answering signal-contingent surveys, event-contingent surveys, and daily assessments across a self-defined study period. The results indicate that it is feasible to conduct research on fear of crime using a smartphone application. However, variations in participation across groups indicate that the methodology is perhaps best suited to dedicated groups of participants with a special interest in the studied outcome. Methodological considerations and implications for future research are discussed.

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).

METHODS

A total of 203 patients with BD, 54 UR, and 109 HC were included. On a smartphone-based app, the participants daily reported their activity level on a scale from -3 to + 3. Additionally, participants owning an android smartphone provided automatically-generated data, including step counts, screen on/off logs, and call- and text-logs. Smartphone-based activity was validated against an activity questionnaire the International Physical Activity Questionnaire (IPAQ) and activity items on observer-based rating scales of depression using the Hamilton Depression Rating scale (HAMD), mania using Young Mania Rating scale (YMRS) and functioning using the Functional Assessment Short Test (FAST). In these analyses, we calculated averages of smartphone-based activity measurements reported in the period corresponding to the days assessed by the questionnaires and rating scales.

RESULTS

(1) Smartphone-based self-reported activity was a valid measure according to scores on the IPAQ and activity items on the HAMD and YMRS, and was associated with FAST scores, whereas the majority of automatically-generated smartphone-based activity measurements were not. (2) Daily smartphone-based self-reported and automatically-generated activity correlated with each other with nearly all measurements. (3) Patients with BD had decreased daily self-reported activity compared with HC. Patients with BD had decreased physical (number of steps) and social activity (more missed calls) but a longer call duration compared with HC. UR also had decreased physical activity compared with HC but did not differ on daily self-reported activity or social activity.

CONCLUSION

Daily self-reported activity measured via smartphone represents overall activity and correlates with measurements of automatically generated smartphone-based activity. Detecting activity levels using smartphones may be clinically helpful in diagnosis and illness monitoring in patients with bipolar disorder. Trial registration clinicaltrials.gov NCT02888262.

A Smartphone App to Monitor Mood Symptoms in Bipolar Disorder: Development and Usability Study

BACKGROUND

There is considerable scientific interest in finding new and innovative ways to capture rapid fluctuations in functioning within individuals with bipolar disorder (BD), a severe, recurrent mental disorder associated with frequent shifts in symptoms and functioning. The use of smartphones can provide valid and real-world tools for use in measurement-based care and could be used to inform more personalized treatment options for this group, which can improve standard of care.

OBJECTIVE

We examined the feasibility and usability of a smartphone to capture daily fluctuations in mood within BD and to relate daily self-rated mood to smartphone use behaviors indicative of psychomotor activity or symptoms of the illness.

METHODS

Participants were 26 individuals with BD and 12 healthy control individuals who were recruited from the Prechter Longitudinal Study of BD. All were given a smartphone with a custom-built app and prompted twice a day to complete questions of mood for 28 days. The app automatically and unobtrusively collected phone usage data. A poststudy satisfaction survey was also completed.

RESULTS

Our sample showed a very high adherence rate to the daily momentary assessments (91% of the 58 prompts completed). Multivariate mixed effect models showed that an increase in rapid thoughts over time was associated with a decrease in outgoing text messages (β=-.02; P=.04), and an increase in impulsivity self-ratings was related to a decrease in total call duration (β=-.29; P=.02). Participants generally reported positive experiences using the smartphone and completing daily prompts.

CONCLUSIONS

Use of mobile technology shows promise as a way to collect important clinical information that can be used to inform treatment decision making and monitor outcomes in a manner that is not overly burdensome to the patient or providers, highlighting its potential use in measurement-based care.

Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study

BACKGROUND

Smartphone-based ecological momentary assessment (EMA) is a promising methodology for mental health research. The objective of this study is to determine the feasibility of smartphone-based active and passive EMA in psychiatric outpatients and student controls.

METHODS

Two smartphone applications -MEmind and eB²- were developed for behavioral active and passive monitoring. The applications were tested in psychiatric patients with a history of suicidal thoughts and/or behaviors (STB), psychiatric patients without a history of STB, and student controls. Main outcome was feasibility, measured as response to recruitment, retention, and EMA compliance. Secondary outcomes were patterns of smartphone usage.

RESULTS

Response rate was 87.3% in patients with a history of STB, 85.1% in patients without a history of STB, and 75.0% in student controls. 457 participants installed the MEmind app (120 patients with a history of STB and 337 controls) and 1,708 installed the eB² app (139 patients with a history of STB, 1,224 patients with no history of STB and 346 controls). For the MEmind app, participants were followed-up for a median of 49.5, resulting in 22,622 person-days. For the eB² application, participants were followed-up for a median of 48.9 days, resulting in 83,521 person-days. EMA compliance rate was 65.00% in suicidal patients and 75.21% in student controls. At the end of the follow-up, over 60% of participants remained in the study.

LIMITATIONS

Cases and controls were not matched by age and sex. Cases were patients who were receiving adequate psychopharmacological treatment and attending their appointments, which may result in an overstatement of clinical compliance.

CONCLUSIONS

Smartphone-based active and passive monitoring are feasible methods in psychiatric patients in real-world settings. The development of applications with friendly interfaces and directly useful features can help increase engagement without using incentives. The MEmind and eB² applications are promising clinical tools that could contribute to the management of mental disorders. In the near future, these applications could serve as risk monitoring devices in the clinical practice.

The utility of smartphone-based, ecological momentary assessment for depressive symptoms

BACKGROUND

Major Depressive Disorder (MDD) is a common and debilitating mood disorder. Individuals with MDD are often misdiagnosed or diagnosed in an untimely manner, exacerbating existing functional impairments. Ecological momentary assessment (EMA) involves the repeated sampling of an individual's symptoms within their natural environment and has been demonstrated to assist in illness assessment and characterization. Capturing data in this way would set the stage for improved treatment outcomes and serve as a complementary resource in the management and treatment of depressive symptoms.

METHODS

Online databases PubMed/MedLine and PsycINFO were searched using PRISMA guidelines and combinations of the following keywords: EMA, depression, smartphone app, diagnosing, symptoms, phone, app, ecological momentary assessment, momentary assessment, data mining, unobtrusive, passive data, GPS, sensor.

RESULTS

A total of nineteen original articles were identified using our search parameters and ten articles met the inclusion criteria for full-text review. Among the ten relevant studies, three studies evaluated feasibility, seven evaluated detection, and three evaluated treatment of MDD.

LIMITATIONS

Limitations include that the design of all of the studies included in this review are non-randomized. It should be noted that most of the studies included were pilot studies and/or exploratory trials lacking a control group.

CONCLUSIONS

Available evidence suggests that the use of passive smartphone-based applications may lead to improved management of depressive symptoms. This review aids the creation of new EMA applications, highlights the potential of EMA usage in clinical settings and drug development, emphasizes the importance for regulation of applications in the mental health field, and provides insight into future directions.

Behavioral activation system (BAS) dysregulation and bipolar spectrum psychopathology in daily life: An online-diary study

Dysregulation of the behavioral activation system (BAS) has been theorized to be a core factor underlying mood swings in bipolar disorder (BD). However, few studies have directly addressed BAS dysregulation and more research is needed to understand its dynamic expression in daily life. The aim of this study was to directly assess BAS dysregulation, and to examine its moderating effect on the relationship between life events and bipolar spectrum symptoms via multilevel modeling. Korean young adults (n = 100) were screened using the Hypomanic Personality Scale (HPS) from a large sample (N = 1,591). They completed online diaries for 7 consecutive days including the Daily Events Record as well as bipolar spectrum symptoms. BAS-activating and/or -deactivating scores were allocated to each reported life event by an expert consensus rating. Cross-level interaction analysis showed that the occurrence of BA life events contributed to a steeper increase in bipolar spectrum symptoms, particularly for individuals with high BAS dysregulation. The present study suggests that BAS dysregulation is a unique construct that deserves further exploration in BD.

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

Internet- and mobile-based approaches have become increasingly significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are substantially related to the social and global functioning or the suicidality of patients, these aspects have so far not sufficiently been considered within the context of mobile-based disease management approaches. As a multiprofessional research team, we have developed a new and emotion-sensitive assistance system, which we have adapted to the needs of patients with bipolar disorder. Next to the analysis of self-assessments, third-party assessments, and sensor data, the new assistance system analyzes audio and video data of these patients regarding their emotional content or the presence of emotional cues. In this viewpoint, we describe the theoretical and technological basis of our emotion-sensitive approach and do not present empirical data or a proof of concept. To our knowledge, the new assistance system incorporates the first mobile-based approach to analyze emotional expressions of patients with bipolar disorder. As a next step, the validity and feasibility of our emotion-sensitive approach must be evaluated. In the future, it might benefit diagnostic, prognostic, or even therapeutic purposes and complement existing systems with the help of new and intuitive interaction models.

A Web-Based Adaptation of the Quality of Life in Bipolar Disorder Questionnaire: Psychometric Evaluation Study

BACKGROUND

Quality of life (QoL) is considered a key treatment outcome in bipolar disorder (BD) across research, clinical, and self-management contexts. Web-based assessment of patient-reported outcomes offer numerous pragmatic benefits but require validation to ensure measurement equivalency. A web-based version of the Quality of Life in Bipolar Disorder (QoL.BD) questionnaire was developed (QoL Tool).

OBJECTIVE

This study aimed to evaluate the psychometric properties of a web-based QoL self-report questionnaire for BD (QoL Tool). Key aims were to (1) characterize the QoL of the sample using the QoL Tool, (2) evaluate the internal consistency of the web-based measure, and (3) determine whether the factor structure of the original version of the QoL.BD instrument was replicated in the web-based instrument.

METHODS

Community-based participatory research methods were used to inform the development of a web-based adaptation of the QoL.BD instrument. Individuals with BD who registered for an account with the QoL Tool were able to opt in to sharing their data for research purposes. The distribution of scores and internal consistency estimates, as indicated by Cronbach alpha, were inspected. An exploratory factor analysis using maximum likelihood and oblique rotation was conducted. Inspection of the scree plot, eigenvalues, and minimum average partial correlation were used to determine the optimal factor structure to extract.

RESULTS

A total of 498 people with BD (349/498, 70.1% female; mean age 39.64, SD 12.54 years; 181/498, 36.3% BD type I; 195/498, 39.2% BD type II) consented to sharing their QoL Tool data for the present study. Mean scores across the 14 QoL Tool domains were, in general, significantly lower than that of the original QoL.BD validation sample. Reliability estimates for QoL Tool domains were comparable with that observed for the QoL.BD instrument (Cronbach alpha=.70-.93). Exploratory factor analysis supported the extraction of an 11-factor model, with item loadings consistent with the factor structure suggested by the original study. Findings for the sleep and physical domains differed from the original study, with this analysis suggesting one shared latent construct.

CONCLUSIONS

The psychometric properties of the web-based QoL Tool are largely concordant with the original pen-and-paper QoL.BD, although some minor differences in the structure of the sleep and physical domains were observed. Despite this small variation from the factor structure identified in the QoL.BD instrument, the latent factor structure of the QoL Tool largely reproduced the original findings and theoretical structure of QoL areas relevant to people with BD. These findings underscore the research and clinical utility of this instrument, but further comparison of the psychometric properties of the QoL Tool relative to the QoL.BD instrument is warranted. Future adaptations of the QoL Tool, including the production of an app-based version of the QoL Tool, are also discussed.

Objective Characterization of Activity, Sleep, and Circadian Rhythm Patterns Using a Wrist-Worn Actigraphy Sensor: Insights Into Posttraumatic Stress Disorder

BACKGROUND

Wearables have been gaining increasing momentum and have enormous potential to provide insights into daily life behaviors and longitudinal health monitoring. However, to date, there is still a lack of principled algorithmic framework to facilitate the analysis of actigraphy and objectively characterize day-by-day data patterns, particularly in cohorts with sleep problems.

OBJECTIVE

This study aimed to propose a principled algorithmic framework for the assessment of activity, sleep, and circadian rhythm patterns in people with posttraumatic stress disorder (PTSD), a mental disorder with long-lasting distressing symptoms such as intrusive memories, avoidance behaviors, and sleep disturbance. In clinical practice, these symptoms are typically assessed using retrospective self-reports that are prone to recall bias. The aim of this study was to develop objective measures from patients' everyday lives, which could potentially considerably enhance the understanding of symptoms, behaviors, and treatment effects.

METHODS

Using a wrist-worn sensor, we recorded actigraphy, light, and temperature data over 7 consecutive days from three groups: 42 people diagnosed with PTSD, 43 traumatized controls, and 30 nontraumatized controls. The participants also completed a daily sleep diary over 7 days and the standardized Pittsburgh Sleep Quality Index questionnaire. We developed a novel approach to automatically determine sleep onset and offset, which can also capture awakenings that are crucial for assessing sleep quality. Moreover, we introduced a new intuitive methodology facilitating actigraphy exploration and characterize day-by-day data across 49 activity, sleep, and circadian rhythm patterns.

RESULTS

We demonstrate that the new sleep detection algorithm closely matches the sleep onset and offset against the participants' sleep diaries consistently outperforming an existing open-access widely used approach. Participants with PTSD exhibited considerably more fragmented sleep patterns (as indicated by greater nocturnal activity, including awakenings) and greater intraday variability compared with traumatized and nontraumatized control groups, showing statistically significant (P<.05) and strong associations (|R|>0.3).

CONCLUSIONS

This study lays the foundation for objective assessment of activity, sleep, and circadian rhythm patterns using passively collected data from a wrist-worn sensor, facilitating large community studies to monitor longitudinally healthy and pathological cohorts under free-living conditions. These findings may be useful in clinical PTSD assessment and could inform therapy and monitoring of treatment effects.

Clinical or gimmickal: The use and effectiveness of mobile mental health apps for treating anxiety and depression

OBJECTIVES

The increase in ownership of smartphones and tablet devices has seen a worldwide government push, championed by the World Health Organization, towards digital healthcare services generally. Mental health has been a strong presence in the digitisation of healthcare because of the potential to solve some of the difficulties in accessing face-to-face services. This review summarises the recent history of e-mental health services and illuminates two very different paths. The first is the considerable amount of research that has proven the effectiveness of many online mental health programmes for personal computers and laptops, resulting in widespread acceptance of their ability to make a contribution in an individual's recovery from anxiety and depression. The second is associated with the more recent development of apps for smartphones and tablet devices and the contrasting paucity of research that has accompanied this burgeoning area of e-mental health. This review also outlines the current state of play for research into the effectiveness of mobile mental health apps for anxiety and depression, including issues associated with methodology, and offers sources of practical advice for clinicians wanting more information about these new digital tools.

CONCLUSION

Research into the effectiveness of mental health apps is lacking, and the majority have no evidence of efficacy. Clinicians need to be aware of what apps have such evidence and should exercise caution when recommending apps to patients. Suggestions are offered on the direction of future research, including an appeal to further include clinicians in the development and efficacy testing of mental health apps.

Use of ecological momentary assessment to detect variability in mood, sleep and stress in bipolar disorder

Objective

Our aim was to study within-person variability in mood, cognition, energy, and impulsivity measured in an Ecological Momentary Assessment paradigm in bipolar disorder by using modern statistical techniques. Exploratory analyses tested the relationship between bipolar disorder symptoms and hours of sleep, and levels of pain, social and task-based stress. We report an analysis of data from a two-arm, parallel group study (bipolar disorder group N = 10 and healthy control group N = 10, with 70% completion rate of 14-day surveys). Surveys of bipolar disorder symptoms, social stressors and sleep hours were completed on a smartphone at unexpected times in an Ecological Momentary Assessment paradigm twice a day. Multi-level models adjusted for potential subject heterogeneity were adopted to test the difference between the bipolar disorder and health control groups.

Results

Within-person variability of mood, energy, speed of thoughts, impulsivity, pain and perception of skill of tasks was significantly higher in the bipolar disorder group compared to health controls. Elevated bipolar disorder symptom domains in the evening were associated with reduced sleep time that night. Stressors were associated with worsening of bipolar disorder symptoms. Detection of symptoms when an individual is experiencing difficulty allows personalized, focused interventions.

Mood Monitoring Over One Year for People With Chronic Obstructive Pulmonary Disease Using a Mobile Health System: Retrospective Analysis of a Randomized Controlled Trial

Background

Comorbid anxiety and depression can add to the complexity of managing treatment for people living with chronic obstructive pulmonary disease (COPD). Monitoring mood has the potential to identify individuals who might benefit from additional support and treatment.

Objective

We used data from the sElf-management anD support proGrammE (EDGE) trial to examine: (1) the extent to which the mood-monitoring components of a mobile health system for patients with COPD were used by participants; (2) the levels of anxiety and depression symptoms among study participants; (3) the extent to which videos providing advice about coping with low mood were viewed; and (4) the characteristics of participants with differing levels of mood and utilization of mood monitoring.

Methods

A total of 107 men and women with a clinical diagnosis of COPD, aged ≥40 years old, were recruited to the intervention arm of the EDGE trial. Participants were invited to complete the Patient Health Questionnaire-8 and the Generalized Anxiety Disorder-7 test every four weeks using a tablet computer. Mood disturbance based on these measures was defined as a score ≥5 on either scale. Participants reporting a mood disturbance were automatically directed (signposted) to a stress or mood management video. Study outcomes included measures of health status, respiratory quality of life, and symptoms of anxiety and depression.

Results

Overall, 94 (87.9%) participants completed the 12-month study. A total of 80 participants entered at least one response each month for at least ten months. On average, 16 participants (range 8-38 participants) entered ≥2 responses each month. Of all the participants, 47 (50%) gave responses indicating a mood disturbance. Participants with a mood disturbance score for both scales (n=47) compared with those without (n=20) had lower health status (P=.008), lower quality of life (P=.009), and greater anxiety (P<.001) and increased depression symptoms (P<.001). Videos were viewed by 64 (68%) people over 12 months. Of the 220 viewing visualizations, 70 (34.7%) began after being signposted. Participants signposted to the stress management video (100%; IQR 23.3-100%) watched a greater proportion of it compared to those not signposted (38.4%; IQR 16.0-68.1%; P=.03), whereas duration of viewing was not significantly different for the mood management video.

Conclusions

Monitoring of anxiety and depression symptoms for people with COPD is feasible. More than half of trial participants reported scores indicating a mood disturbance during the study. Signposting participants to an advisory video when reporting increased symptoms of a mood disturbance resulted in a longer view-time for the stress management video. The opportunity to elicit measures of mood regularly as part of a health monitoring system could contribute to better care for people with COPD.

Electronic Ecological Momentary Assessment (EMA) in youth with bipolar disorder: Demographic and clinical predictors of electronic EMA adherence

BACKGROUND

Ecological momentary assessment (EMA) is increasingly used to characterize patients' daily lives, monitor mood, and test efficacy of treatment interventions. However, few studies have examined patient characteristics impacting adherence with EMA protocols, and to our knowledge, no such study has been conducted in youth with bipolar disorder (BD).

METHODS

As part of a larger observational study, 14- to 21-year-olds diagnosed with BD, and who were between episodes of illness (n = 39, 19.0 ± 2.05 Mean ± Standard Deviation years old, 74.4% female) and psychiatrically healthy controls (n = 47, 18.3 ± 2.40 years old, 66.0% female) completed baseline diagnostic and symptom severity interviews, and were instructed to complete diary assessments of mood, sleep, and behavior electronically three times per day for 21 consecutive days (i.e., in total 5418 (or 63 per person) diary entries). Multiple regression was used to examine effects of BD participants' demographic and clinical characteristics on diary completion rates.

RESULTS

53.8 ± 9.3 diary entries per person were actually completed. Adherence rates were high (87.5% of healthy controls and 80.4% of adolescents with BD), but were still significantly poorer in youth with BD. Adequate adherence (≥80%) rates were also significantly poorer in youth with BD relative to healthy controls (56.4% versus 83.0%). Among youth with BD, more lifetime suicide attempts and higher current mood elevation symptom severity predicted significantly poorer adherence.

LIMITATIONS

Limited sample size/generalizability.

CONCLUSIONS

Findings highlight the importance of considering the impact of patient characteristics on adherence with EMA protocols among youth with severe mental illness.

User Engagement in Mental Health Apps: A Review of Measurement, Reporting, and Validity

OBJECTIVE

Despite the potential benefits of mobile mental health apps, real-world results indicate engagement issues because of low uptake and sustained use. This review examined how studies have measured and reported on user engagement indicators (UEIs) for mental health apps.

METHODS

A systematic review of multiple databases was performed in July 2018 for studies of mental health apps for depression, bipolar disorder, schizophrenia, and anxiety that reported on UEIs, namely usability, user satisfaction, acceptability, and feasibility. The subjective and objective criteria used to assess UEIs, among other data, were extracted from each study.

RESULTS

Of 925 results, 40 studies were eligible. Every study reported positive results for the usability, satisfaction, acceptability, or feasibility of the app. Of the 40 studies, 36 (90%) employed 371 indistinct subjective criteria that were assessed with surveys, interviews, or both, and 23 studies used custom subjective scales, rather than preexisting standardized assessment tools. A total of 25 studies (63%) used objective criteria-with 71 indistinct measures. No two studies used the same combination of subjective or objective criteria to assess UEIs of the app.

CONCLUSIONS

The high heterogeneity and use of custom criteria to assess mental health apps in terms of usability, user satisfaction, acceptability, or feasibility present a challenge for understanding real-world low uptake of these apps. Every study reviewed claimed that UEIs for the app were rated highly, which suggests a need for the field to focus on engagement by creating reporting standards and more carefully considering claims.

Use of Ecological Momentary Assessment and Intervention in Treatment With Adults

This article reviews the use of ecological momentary assessment (EMA) and ecological momentary intervention (EMI) in clinical research applications. EMA refers to a method of data collection that attempts to capture respondents' activities, emotions, and thoughts in the moment, in their natural environment. It typically uses prompts administered through a personal electronic device, such as a smartphone or tablet. EMI extends this technique and includes the use of microlevel interventions administered through personal electronic devices. These technological developments hold promise for enhancing psychological treatments by prompting the patient outside of therapy sessions in his or her day-to-day environment. Research suggests that EMI may be beneficial to participants and that this effect is amplified when EMI is delivered in the context of ongoing psychotherapy. EMI may reflect a cost-effective mechanism to enhance therapeutic outcomes.

Systematic Review of Symptom Assessment Measures for Use in Measurement-Based Care of Bipolar Disorders

OBJECTIVE

Utilization of measurement-based care (MBC) for bipolar disorders is limited, in part because of uncertainty regarding the utility of available measures. The aim of this study was to synthesize the literature on patient-reported and clinician-observed measures of symptoms of bipolar disorder and the potential use of these measures in MBC.

METHODS

A systematic review of multiple databases (PubMed, Embase, PsycINFO, Cochrane Library, and other gray literature) was conducted in June 2017 to identify validated measures. Data on the psychometric properties of each measure were extracted and used to assess the measure's clinical utility on the basis of established guidelines.

RESULTS

Twenty-eight unique measures were identified in 39 studies, including four patient-reported and six clinician-observed measures assessing manic symptoms, three patient-reported and five clinician-observed measures of depressive symptoms, and six patient-reported and four clinician-observed measures of both symptom types. Patient-reported measures with the highest clinical utility included the Altman Self-Rating Mania Scale for assessment of manic symptoms, the Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR) (depressive symptoms), and the Internal State Scale (both types). Highly rated clinician (C)-observed scales were the Bech-Rafaelsen Mania Rating Scale (mania), the QIDS-C (depressive symptoms), and the Bipolar Inventory of Symptoms Scale (both types).

CONCLUSIONS

Suitable choices are available for MBC of bipolar disorders. The choice of a measure could be informed by clinical utility score and may also depend on how clinicians or practices weigh each category of the clinical utility scale and on the clinical setting and presenting problem.

Bipolar Prodrome Symptom Scale - Abbreviated Screen for Patients: Description and validation

OBJECTIVE

There is no standard method for assessing symptoms of the prodrome to bipolar disorder (BD), which has limited progress toward early identification and intervention. We aimed to validate the Bipolar Prodrome Symptom Scale-Abbreviated Screen for Patients (BPSS-AS-P), a brief self-report derived from the validated, clinician-rated Bipolar Prodrome Symptom Interview and Scale-Full Prospective (BPSS-FP), as a means to screen and identify people for whom further evaluation is indicated.

METHOD

Altogether, 134 participants (aged 12-18 years) were drawn from a study of the pre-syndromal stage of mood and psychotic disorders. All participants had chart diagnoses of a mood- or psychosis-spectrum disorder. Participants were interviewed with the BPSS-FP and completed measures of mania and non-mood psychopathology. Prior to being interviewed, patients completed the BPSS-AS-P. Scores on the BPSS-AS-P were determined by summing the severity and frequency ratings for each item.

RESULTS

BPSS-AS-P scores were highly reliable (Cronbach's alpha = 0.94) and correlated with the interview-based BPSS-FP Mania Symptom Index (r = 0.55, p < .0001). BPSS-AS-P scores had good convergent validity, correlating with the General Behavior Inventory-10M (r = 0.65, p < .0001) and Young Mania Rating Scale; r = 0.48, p < .0001). The BPSS-AS-P had good discriminant validity, not being correlated with scales measuring positive and negative symptoms of psychotic disorders (p-values = 0.072-0.667).

LIMITATIONS

Findings are limited by the cross-sectional nature of the study by the fact that the participants were all treatment-seeking. Future studies need to evaluate the predictive validity of the BPSS-AS-P for identifying those who develop BD in a community sample.

CONCLUSION

BPSS-AS-P has promise as a screening tool for people at risk for BD. Adopting the BPSS-AS-P would support the goal of characterizing the prodrome systematically in order to facilitate research and clinical care.

The user experiences and clinical outcomes of an online personal health record to support self-management of bipolar disorder: A pretest-posttest pilot study

BACKGROUND

Self-management comprises knowledge, behavior, activities and resources providing people with bipolar disorder (BD) control over fluctuating mood and activity-patterns. The 'Self-management and Dialogue in Bipolar Disorder' project entailed the tailoring of an online personal health record (PHR) originally designed for the chronically ill to monitor condition and share information with their clinician to people with BD (PHR-BD). The aim of this study was to evaluate the feasibility, utility and user-experiences of participants with BD, relatives, and healthcare professionals who worked with the PHR-BD.

METHODS

Post-test online closed- and open ended questionnaires were used to collect information on utility, and user-experiences with PHR-BD. A pre-posttest design to evaluate clinical effects on quality of life, empowerment, symptom reduction, changes in mood and activity, and illness burden and severity at baseline and at 12-months follow-up.

RESULTS

Sixty-six participants with BD logged in at baseline. At study endpoint thirty-nine participants with BD, eleven professionals and one family caregiver filled out the evaluations. No significant differences in the clinical outcomes from baseline were found. Qualitative evaluations showed a frequent utility of the mood chart modules, improved communication between clinician and participant with BD and, increased insight in influencing factors of mood fluctuations.

LIMITATIONS

Small convenience sample, no controls.

CONCLUSIONS

The option to alternate the interface from a prospective to a retrospective mood chart , and integration with the personal crisis plan was considered to be of added value in self-managing BD. The findings of this study will guide the future implementation of the PHR-BD.

Design limitations to bipolar II treatment efficacy studies: A challenge and a revisionist strategy

BACKGROUND

Trials examining medication efficacy for bipolar II disorder commonly employ a set of standardized interval measures to assess outcomes. The key issue is whether such interval measures pick up changes in the severity, duration and frequency of depressive, hypomanic and euthymic episodes.

METHOD

We examine the application of measures most commonly used to monitor progress in nine studies involving participants with a bipolar II disorder and published in journals with a moderate to high impact factor.

RESULTS

Studies rarely provided interval details for assessing depressive and hypomanic symptoms. None specified whether ratings of depressive and hypomanic symptoms were based on severity, duration or number of symptoms, and none recorded any data on euthymic periods.

LIMITATIONS

Our sample of reviewed studies was small and our analyses focused only on the three most commonly used outcome measures. We advocate for complementary subjective daily mood monitoring strategies but recognize that such strategies need to be validated in future studies.

CONCLUSIONS

We argue that interval ratings undertaken weekly or over longer periods may compromise efficacy data. We recommend that userguides be developed to ensure standard outcome measures are employed consistently across trials, and that specific details be published in trial papers about how measures were employed and what mood episode characteristics were measured at each assessment. We also argue for daily ratings to be used as an outcome measure to provide data on severity, frequency and duration of depressive, hypomanic and euthymic periods in intervention studies of those with a bipolar II disorder.

Disease management apps and technical assistance systems for bipolar disorder: Investigating the patients´ point of view

BACKGROUND

Smartphone-based disease management has become increasingly interesting for research in the field of bipolar disorders. This article investigates the attitudes of persons affected by this disorder towards the appropriation of mobile apps or assistance systems for the management of their disease.

METHODS

We conducted two separate studies. Study 1 was an online survey with 88 participants. In study 2 we consulted 15 participants during a semi-structured interview. All the participants had formerly been diagnosed with bipolar disorder.

RESULTS

More than half of the participants of study 1 and most participants of study 2 agreed with the use of an app or assistance system for self-ratings, third party ratings and an objective symptom monitoring. Potential interventions that were popular in both groups included a regular feedback, the visualization of monitored data and advice in crises.

LIMITATIONS

With study 1 we were not able to ensure correct diagnoses or to interact in a flexible way. In Study 2 those issues were resolved, but the small number of participants raises the question of a possible generalisability of the results. Furthermore, for both studies a selection bias could not be excluded.

CONCLUSIONS

Our results indicate positive attitudes of bipolar patients towards disease management apps and assistance systems. Even new and innovative features such as partner apps or the analysis of facial expressions in video data were appreciated and daily interactions were favoured. However, the variety of answers calls for flexible systems which allow activating or deactivating certain features.

Engagement in mobile phone app for self-monitoring of emotional wellbeing predicts changes in mental health: MoodPrism

BACKGROUND

Mobile apps are being used increasingly for mental health purposes, but evidence of their efficacy remains limited. The mechanisms underlying any effects of such apps are also unclear. This study examined the effectiveness of a self-monitoring mobile phone app by investigating the relationships between app engagement and mental health outcomes.

METHOD

Participants downloaded the MoodPrism app from the iOS and Android app stores, completing in-app assessments at start of use and again 30days later. The app prompted participants daily to complete a short mood questionnaire and formulated their responses into a mood diary. Data from 234 assessment completers (73% female; M age = 34.8 years) were analysed via hierarchical and mediation regressions.

RESULTS

In this community sample, app engagement ratings predicted decreases in depression and anxiety, and increases in mental well-being. These effects were mediated by increases in emotional self-awareness, but only for participants who were clinically depressed or anxious at the time of the baseline assessment. Mental health literacy and coping self-efficacy did not play mediating roles.

LIMITATIONS

Findings suggest that other influential mediators may have not been measured, and future studies could verify the findings by using alternative methodologies, such as comparison with a control group.

CONCLUSIONS

Engaging with an emotional wellbeing self-monitoring app may reduce depressive and anxious symptoms, and increase mental well-being. Increases in emotional self-awareness may mediate these changes in clinical populations, and further research is needed to reveal other mechanisms that mental health apps can utilize.

Variability in phase and amplitude of diurnal rhythms is related to variation of mood in bipolar and borderline personality disorder

Variable mood is an important feature of psychiatric disorders. However, its measurement and relationship to objective measureas of physiology and behaviour have rarely been studied. Smart-phones facilitate continuous personalized prospective monitoring of subjective experience and behavioural and physiological signals can be measured through wearable devices. Such passive data streams allow novel estimates of diurnal variability. Phase and amplitude of diurnal rhythms were quantified using new techniques that fitted sinusoids to heart rate (HR) and acceleration signals. We investigated mood and diurnal variation for four days in 20 outpatients with bipolar disorder (BD), 14 with borderline personality disorder (BPD) and 20 healthy controls (HC) using a smart-phone app, portable electrocardiogram (ECG), and actigraphy. Variability in negative affect, positive affect, and irritability was elevated in patient groups compared with HC. The study demonstrated convincing associations between variability in subjective mood and objective variability in diurnal physiology. For BPD there was a pattern of positive correlations between mood variability and variation in activity, sleep and HR. The findings suggest BPD is linked more than currently believed with a disorder of diurnal rhythm; in both BPD and BD reducing the variability of sleep phase may be a way to reduce variability of subjective mood.

PlenadrEMA: effect of dual-release versus conventional hydrocortisone on fatigue, measured by ecological momentary assessments: a study protocol for an open-label switch pilot study

INTRODUCTION

Patients with adrenal insufficiency have impaired health-related quality of life (QoL). The dual-release hydrocortisone preparation, Plenadren, has been developed to mimic the physiological cortisol release more closely than conventional hydrocortisone treatment. Plenadren has been shown to improve QoL, in particular fatigue, in patients with primary adrenal insufficiency. However, the effect has not been investigated in patients with secondary adrenal insufficiency; furthermore, no study has taken the diurnal variation of fatigue into account. To assess diurnal variations, it is necessary to use repeated daily measurements, such as ecological momentary assessments (EMAs). This study aims to evaluate EMAs of fatigue as outcome in future large-scale randomised clinical trials.

METHODS AND ANALYSIS

The PlenadrEMA trial is an investigator-initiated open-label switch pilot trial of the effect of Plenadren versus conventional hydrocortisone on fatigue in patients with secondary adrenal insufficiency. The trial will include 30 participants. After 5 weeks on their usual hydrocortisone treatment, patients will be shifted to Plenadren for 16 weeks. Fatigue will be assessed using momentary versions of the Multidimensional Fatigue Inventory (MFI-20). Items will be administered to participants via a smartphone application four times daily during 20 days. Assessments will be performed before treatment shift and repeated after 12.5 weeks on Plenadren. The study will identify the best suited outcome for future randomised clinical trials, and in addition, estimate the variability and difference in fatigue between the two treatments to perform power calculations.

ETHICS AND DISSEMINATION

The trial will be conducted in accordance with the Declaration of Helsinki and has been approved by the Regional Scientific Ethical Committee in Copenhagen (ID: H-1-2014-073). All patients will receive written and verbal information about the trial and will give informed consent before enrolment. Findings will be published in peer-reviewed journals and presented at international conferences.

TRIAL REGISTRATION NUMBER

EudraCT201400203932.

Innovative approaches to bipolar disorder and its treatment

All psychiatric disorders have suffered from a dearth of truly novel pharmacological interventions. In bipolar disorder, lithium remains a mainstay of treatment, six decades since its effects were serendipitously discovered. The lack of progress reflects several factors, including ignorance of the disorder's pathophysiology and the complexities of the clinical phenotype. After reviewing the current status, we discuss some ways forward. First, we highlight the need for a richer characterization of the clinical profile, facilitated by novel devices and new forms of data capture and analysis; such data are already promoting a reevaluation of the phenotype, with an emphasis on mood instability rather than on discrete clinical episodes. Second, experimental medicine can provide early indications of target engagement and therapeutic response, reducing the time, cost, and risk involved in evaluating potential mood stabilizers. Third, genomic data can inform target identification and validation, such as the increasing evidence for involvement of calcium channel genes in bipolar disorder. Finally, new methods and models relevant to bipolar disorder, including stem cells and genetically modified mice, are being used to study key pathways and drug effects. A combination of these approaches has real potential to break the impasse and deliver genuinely new treatments.

There is an app for that! The current state of mobile applications (apps) for DSM-5 obsessive-compulsive disorder, posttraumatic stress disorder, anxiety and mood disorders

Mental health apps are viewed as a promising modality to extend the reach of mental health care beyond the clinic. They do so by providing a means of assessment, tracking, and treatment through a smartphone. Given that nearly 2/3 of the American population owns a smartphone, mental health apps offer the possibility of overcoming treatment barriers such as geographic location or financial barriers. Unfortunately, the excitement surrounding mental health apps may be premature as the current supporting literature regarding their efficacy is limited. The app marketplace is littered with apps claiming to treat or assess symptoms, but even those created by reputable organizations or those incorporating components of evidence-based treatments have not yet been validated in terms of their efficacy. This review aims to provide a comprehensive review of the current state of the mental health app literature by examining published reports of apps designed for DSM-5 anxiety and mood disorders, OCD, and PTSD. The breadth of apps reviewed includes those oriented around assessment, symptom tracking, and treatment as well as "multipurpose" apps, which incorporate several of these components. This review will also present some of the most popular mental health apps which may have clinical utility and could be prescribed to clients. While we discuss many potential benefits of mental health apps, we focus on a number of issues that the current state of the app literature presents. Overall there is a significant disconnect between app developers, the scientific community and health care, leaving the utility of existing apps questionable.

Clinical Insight Into Latent Variables of Psychiatric Questionnaires for Mood Symptom Self-Assessment

BACKGROUND

We recently described a new questionnaire to monitor mood called mood zoom (MZ). MZ comprises 6 items assessing mood symptoms on a 7-point Likert scale; we had previously used standard principal component analysis (PCA) to tentatively understand its properties, but the presence of multiple nonzero loadings obstructed the interpretation of its latent variables.

OBJECTIVE

The aim of this study was to rigorously investigate the internal properties and latent variables of MZ using an algorithmic approach which may lead to more interpretable results than PCA. Additionally, we explored three other widely used psychiatric questionnaires to investigate latent variable structure similarities with MZ: (1) Altman self-rating mania scale (ASRM), assessing mania; (2) quick inventory of depressive symptomatology (QIDS) self-report, assessing depression; and (3) generalized anxiety disorder (7-item) (GAD-7), assessing anxiety.

METHODS

We elicited responses from 131 participants: 48 bipolar disorder (BD), 32 borderline personality disorder (BPD), and 51 healthy controls (HC), collected longitudinally (median [interquartile range, IQR]: 363 [276] days). Participants were requested to complete ASRM, QIDS, and GAD-7 weekly (all 3 questionnaires were completed on the Web) and MZ daily (using a custom-based smartphone app). We applied sparse PCA (SPCA) to determine the latent variables for the four questionnaires, where a small subset of the original items contributes toward each latent variable.

RESULTS

We found that MZ had great consistency across the three cohorts studied. Three main principal components were derived using SPCA, which can be tentatively interpreted as (1) anxiety and sadness, (2) positive affect, and (3) irritability. The MZ principal component comprising anxiety and sadness explains most of the variance in BD and BPD, whereas the positive affect of MZ explains most of the variance in HC. The latent variables in ASRM were identical for the patient groups but different for HC; nevertheless, the latent variables shared common items across both the patient group and HC. On the contrary, QIDS had overall very different principal components across groups; sleep was a key element in HC and BD but was absent in BPD. In GAD-7, nervousness was the principal component explaining most of the variance in BD and HC.

CONCLUSIONS

This study has important implications for understanding self-reported mood. MZ has a consistent, intuitively interpretable latent variable structure and hence may be a good instrument for generic mood assessment. Irritability appears to be the key distinguishing latent variable between BD and BPD and might be useful for differential diagnosis. Anxiety and sadness are closely interlinked, a finding that might inform treatment effects to jointly address these covarying symptoms. Anxiety and nervousness appear to be amongst the cardinal latent variable symptoms in BD and merit close attention in clinical practice.

Immediate Mood Scaler: Tracking Symptoms of Depression and Anxiety Using a Novel Mobile Mood Scale

BACKGROUND

Mood disorders are dynamic disorders characterized by multimodal symptoms. Clinical assessment of symptoms is currently limited to relatively sparse, routine clinic visits, requiring retrospective recollection of symptoms present in the weeks preceding the visit. Novel advances in mobile tools now support ecological momentary assessment of mood, conducted frequently using mobile devices, outside the clinical setting. Such mood assessment may help circumvent problems associated with infrequent reporting and better characterize the dynamic presentation of mood symptoms, informing the delivery of novel treatment options.

OBJECTIVES

The aim of our study was to validate the Immediate Mood Scaler (IMS), a newly developed, iPad-deliverable 22-item self-report tool designed to capture current mood states.

METHODS

A total of 110 individuals completed standardized questionnaires (Patient Health Questionnaire, 9-item [PHQ-9]; generalized anxiety disorder, 7-Item [GAD-7]; and rumination scale) and IMS at baseline. Of the total, 56 completed at least one additional session of IMS, and 17 completed one additional administration of PHQ-9 and GAD-7. We conducted exploratory Principal Axis Factor Analysis to assess dimensionality of IMS, and computed zero-order correlations to investigate associations between IMS and standardized scales. Linear Mixed Model (LMM) was used to assess IMS stability across time and to test predictability of PHQ-9 and GAD-7 score by IMS.

RESULTS

Strong correlations were found between standard mood scales and the IMS at baseline (r=.57-.59, P<.001). A factor analysis revealed a 12-item IMS ("IMS-12") with two factors: a "depression" factor and an "anxiety" factor. IMS-12 depression subscale was more strongly correlated with PHQ-9 than with GAD-7 (z=1.88, P=.03), but the reverse pattern was not found for IMS-12 anxiety subscale. IMS-12 showed less stability over time compared with PHQ-9 and GAD-7 (.65 vs .91), potentially reflecting more sensitivity to mood dynamics. In addition, IMS-12 ratings indicated that individuals with mild to moderate depression had greater mood fluctuations compared with individuals with severe depression (.42 vs .79; P=.04). Finally, IMS-12 significantly contributed to the prediction of subsequent PHQ-9 (beta=1.03, P=.02) and GAD-7 scores (beta =.93, P=.01).

CONCLUSIONS

Collectively, these data suggest that the 12-item IMS (IMS-12) is a valid tool to assess momentary mood symptoms related to anxiety and depression. Although IMS-12 shows good correlation with standardized scales, it further captures mood fluctuations better and significantly adds to the prediction of the scales. Results are discussed in the context of providing continuous symptom quantification that may inform novel treatment options and support personalized treatment plans.

Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies

Digital footprints, the automatically accumulated by-products of our technology-saturated lives, offer an exciting opportunity for psychiatric research. The commercial sector has already embraced the electronic trails of customers as an enabling tool for guiding consumer behaviour, and analogous efforts are ongoing to monitor and improve the mental health of psychiatric patients. The untargeted collection of digital footprints that may or may not be health orientated comprises a large untapped information resource for epidemiological scale research into psychiatric disorders. Real-time monitoring of mood, sleep and physical and social activity in a substantial portion of the affected population in a naturalistic setting is unprecedented in psychiatry. We propose that digital footprints can provide these measurements from real world setting unobtrusively and in a longitudinal fashion. In this perspective article, we outline the concept of digital footprints and the services and devices that create them, and present examples where digital footprints have been successfully used in research. We then critically discuss the opportunities and fundamental challenges associated digital footprints in psychiatric research, such as collecting data from different sources, analysis, ethical and research design challenges.

Daily longitudinal self-monitoring of mood variability in bipolar disorder and borderline personality disorder

BACKGROUND

Traditionally, assessment of psychiatric symptoms has been relying on their retrospective report to a trained interviewer. The emergence of smartphones facilitates passive sensor-based monitoring and active real-time monitoring through time-stamped prompts; however there are few validated self-report measures designed for this purpose.

METHODS

We introduce a novel, compact questionnaire, Mood Zoom (MZ), embedded in a customised smart-phone application. MZ asks participants to rate anxiety, elation, sadness, anger, irritability and energy on a 7-point Likert scale. For comparison, we used four standard clinical questionnaires administered to participants weekly to quantify mania (ASRM), depression (QIDS), anxiety (GAD-7), and quality of life (EQ-5D). We monitored 48 Bipolar Disorder (BD), 31 Borderline Personality Disorders (BPD) and 51 Healthy control (HC) participants to study longitudinal (median±iqr: 313±194 days) variation and differences of mood traits by exploring the data using diverse time-series tools.

RESULTS

MZ correlated well (|R|>0.5,p<0.0001) with QIDS, GAD-7, and EQ-5D. We found statistically strong (|R|>0.3,p<0.0001) differences in variability in all questionnaires for the three cohorts. Compared to HC, BD and BPD participants exhibit different trends and variability, and on average had higher self-reported scores in mania, depression, and anxiety, and lower quality of life. In particular, analysis of MZ variability can differentiate BD and BPD which was not hitherto possible using the weekly questionnaires.

LIMITATIONS

All reported scores rely on self-assessment; there is a lack of ongoing clinical assessment by experts to validate the findings.

CONCLUSIONS

MZ could be used for efficient, long-term, effective daily monitoring of mood instability in clinical psychiatric practice.