Mood disorders in everyday life: a systematic review of experience sampling and ecological momentary assessment studies

Honoring the Past, Envisioning the Future: ABCT's 50th Anniversary Presidential Address

The theme of the Association for Behavioral and Cognitive Therapies (ABCT) 50^th Anniversary was to honor the past and envision the future. From the wisdom, foresight, and determination of the pioneers of our organization, and the continuous upholding of the scientific method over the last 50 years, cognitive behavioral therapy (CBT) has become the most empirically supported psychological treatment for a wide array of mental health problems. Yet, we still have a long way to go. This address outlines a vision for the future of CBT, which involves greater collaborative science, with all minds working together on the same problem, and greater attention to the risk factors and critical processes that underlie psychopathology and explain treatment change. Such knowledge generation can inform the development of new, more efficient and more effective therapies that are tailored with more precision to the needs of each person. Latest technologies provide tools for a precision focus while at the same time increasing the reach of our treatments to the many for whom traditional therapies are unavailable. Our impact will be greatly enhanced by large samples with common methods and measures that inform a precision approach. We have come a long way since ABCT was founded in 1966, and we are poised to make even larger strides in our mission to enhance health and well-being by harnessing science, our major guiding principle.

Ambulatory Assessment

In recent years, significant technological advances have changed our understanding of dynamic processes in clinical psychology. A particularly important agent of change has been ambulatory assessment (AA). AA is the assessment of individuals in their daily lives, combining the twin benefits of increased ecological validity and minimized retrospective biases. These benefits make AA particularly well-suited to the assessment of dynamic processes, and recent advancements in technology are providing exciting new opportunities to understand these processes in new ways. In the current article, we briefly detail the capabilities currently offered by smartphones and mobile physiological devices, as well as some of the practical and ethical challenges of incorporating these new technologies into AA research. We then provide several examples of recent innovative applications of AA methodology in clinical research, assessment, and intervention and provide a case example of AA data generated from a study utilizing multiple mobile devices. In this way, we aim to provide a sense of direction for researchers planning AA studies of their own.

Assessing Temporal Emotion Dynamics Using Networks

Multivariate psychological processes have recently been studied, visualized, and analyzed as networks. In this network approach, psychological constructs are represented as complex systems of interacting components. In addition to insightful visualization of dynamics, a network perspective leads to a new way of thinking about the nature of psychological phenomena by offering new tools for studying dynamical processes in psychology. In this article, we explain the rationale of the network approach, the associated methods and visualization, and illustrate it using an empirical example focusing on the relation between the daily fluctuations of emotions and neuroticism. The results suggest that individuals with high levels of neuroticism had a denser emotion network compared with their less neurotic peers. This effect is especially pronounced for the negative emotion network, which is in line with previous studies that found a denser network in depressed subjects than in healthy subjects. In sum, we show how the network approach may offer new tools for studying dynamical processes in psychology.

Smartphone-based objective monitoring in bipolar disorder: status and considerations

In 2001, the WHO stated that: "The use of mobile and wireless technologies to support the achievement of health objectives (mHealth) has the potential to transform the face of health service delivery across the globe". Within mental health, interventions and monitoring systems for depression, anxiety, substance abuse, eating disorder, schizophrenia and bipolar disorder have been developed and used. The present paper presents the status and findings from studies using automatically generated objective smartphone data in the monitoring of bipolar disorder, and addresses considerations on the current literature and methodological as well as clinical aspects to consider in the future studies.

Cognitive and Behavioral Skills Exercises Completed by Patients with Major Depression During Smartphone Cognitive Behavioral Therapy: Secondary Analysis of a Randomized Controlled Trial

BACKGROUND

A strong and growing body of evidence has demonstrated the effectiveness of cognitive behavioral therapy (CBT), either face-to-face, in person, or as self-help via the Internet, for depression. However, CBT is a complex intervention consisting of several putatively effective components, and how each component may or may not contribute to the overall effectiveness of CBT is poorly understood.

OBJECTIVE

The aim of this study was to investigate how the users of smartphone CBT use and benefit from various components of the program.

METHODS

This is a secondary analysis from a 9-week, single-blind, randomized controlled trial that has demonstrated the effectiveness of adjunctive use of smartphone CBT (Kokoro-App) over antidepressant pharmacotherapy alone among patients with drug-resistant major depressive disorder (total n=164, standardized mean difference in depression severity at week 9=0.40, J Med Internet Res). Kokoro-App consists of three cognitive behavioral skills of self-monitoring, behavioral activation, and cognitive restructuring, with corresponding worksheets to fill in. All activities of the participants learning each session of the program and completing each worksheet were uploaded onto Kokoro-Web, which each patient could use for self-check. We examined what use characteristics differentiated the more successful users of the CBT app from the less successful ones, split at the median of change in depression severity.

RESULTS

A total of 81 patients with major depression were allocated to the smartphone CBT. On average, they completed 7.0 (standard deviation [SD] 1.4) out of 8 sessions of the program; it took them 10.8 (SD 4.2) days to complete one session, during which they spent 62 min (SD 96) on the app. There were no statistically significant differences in the number of sessions completed, time spent for the program, or the number of completed self-monitoring worksheets between the beneficiaries and the nonbeneficiaries. However, the former completed more behavioral activation tasks, engaged in different types of activities, and also filled in more cognitive restructuring worksheets than the latter. Activities such as "test-drive a new car," "go to a coffee shop after lunch," or "call up an old friend" were found to be particularly rewarding. All cognitive restructuring strategies were found to significantly decrease the distress level, with "What would be your advice to a friend who has a similar problem?" found more helpful than some other strategies.

CONCLUSIONS

The CBT program offered via smartphone and connected to the remote server is not only effective in alleviating depression but also opens a new avenue in gathering information of what and how each participant may utilize the program. The activities and strategies found useful in this analysis will provide valuable information in brush-ups of the program itself and of mobile health (mHealth) in general.

TRIAL REGISTRATION

Japanese Clinical Trials Registry UMIN CTR 000013693; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ ctr_view.cgi?recptno=R000015984 (Archived by WebCite at http://www.webcitation.org/6u6pxVwik).

Economic evaluation of an experience sampling method intervention in depression compared with treatment as usual using data from a randomized controlled trial

BACKGROUND

Experience sampling, a method for real-time self-monitoring of affective experiences, holds opportunities for person-tailored treatment. By focussing on dynamic patterns of positive affect, experience sampling method interventions (ESM-I) accommodate strategies to enhance personalized treatment of depression-at potentially low-costs. This study aimed to investigate the cost-effectiveness of an experience sampling method intervention in patients with depression, from a societal perspective.

METHODS

Participants were recruited between January 2010 and February 2012 from out-patient mental health care facilities in or near the Dutch cities of Eindhoven and Maastricht, and through local advertisements. Out-patients diagnosed with major depression (n = 101) receiving pharmacotherapy were randomized into: (i) ESM-I consisting of six weeks of ESM combined with weekly feedback regarding the individual's positive affective experiences, (ii) six weeks of ESM without feedback, or (iii) treatment as usual only. Alongside this randomised controlled trial, an economic evaluation was conducted consisting of a cost-effectiveness and a cost-utility analysis, using Hamilton Depression Rating Scale (HDRS) and quality adjusted life years (QALYs) as outcome, with willingness-to-pay threshold for a QALY set at €50,000 (based on Dutch guidelines for moderate severe to severe illnesses).

RESULTS

The economic evaluation showed that ESM-I is an optimal strategy only when willingness to pay is around €3000 per unit HDRS and around €40,500 per QALY. ESM-I was the least favourable treatment when willingness to pay was lower than €30,000 per QALY. However, at the €50,000 willingness-to-pay threshold, ESM-I was, with a 46% probability, the most favourable treatment (base-case analysis). Sensitivity analyses confirmed the robustness of these results.

CONCLUSIONS

We may tentatively conclude that ESM-I is a cost-effective add-on intervention to pharmacotherapy in outpatients with major depression.

TRIAL REGISTRATION

Netherlands Trial register, NTR1974 .

Associations Between Daily Affective Instability and Connectomics in Functional Subnetworks in Remitted Patients with Recurrent Major Depressive Disorder

Remitted patients with major depressive disorder (rMDD) often report more fluctuations in mood as residual symptomatology. It is unclear how this affective instability is associated with information processing related to the default mode (DMS), salience/reward (SRS), and frontoparietal (FPS) subnetworks in rMDD patients at high risk of recurrence (rrMDD). Sixty-two unipolar, drug-free rrMDD patients (⩾2 MDD episodes) and 41 healthy controls (HCs) were recruited. We used experience sampling methodology to monitor mood/cognitions (10 times a day for 6 days) and calculated affective instability using the mean adjusted absolute successive difference. Subsequently, we collected resting-state functional magnetic resonance imaging data and performed graph theory to obtain network metrics of integration within (local efficiency) the DMS, SRS, and FPS, and between (participation coefficient) these subnetworks and others. In rrMDD patients compared with HCs, we found that affective instability was increased in most negative mood/cognition variables and that the DMS had less connections with other subnetworks. Furthermore, we found that rrMDD patients, who showed more instability in feeling down and irritated, had less connections between the SRS and other subnetworks and higher local efficiency coefficients in the FPS, respectively. In conclusion, rrMDD patients, compared with HCs, are less stable in their negative mood and these dynamics are related to differences in information processing within- and between-specific functional subnetworks. These results are a first step to gain a better understanding of how mood fluctuations in real life are represented in the brain and provide insights into the vulnerability profile of MDD.

Technology to assess and support self-management in serious mental illness

The functional impairment associated with serious mental illness (SMI) places an immense burden on individuals and society, and disability often persists even after efficacious treatment of psychopathologic symptoms. Traditional methods of measuring functioning have limitations, and numerous obstacles reduce the reach and impact of evidence-based interventions developed to improve functioning in SMI. This review describes the potential of technological innovations for overcoming the challenges involved in both functional assessment and intervention in people with SMI. Ecological momentary assessment (EMA), which involves the repeated sampling of naturalistic behaviors and experiences while individuals carry out their daily lives, has provided a new window through which the determinants of day-to-day function in SMI can be observed. EMA has several advantages over traditional assessment methods and has in recent years evolved to use mobile-based platforms, such as text messaging and smartphone applications, for both assessment and promotion of self-management in people with SMI. We will review promising data regarding the acceptability, adherence, and efficacy of EMA-based mobile technologies; explore ways in which these technologies can extend the reach and impact of evidence-based psychosocial rehabilitative interventions in SMI; and outline future directions for research in this important area.

Evaluation of Ecological Momentary Assessment for Tinnitus Severity

Importance

Existing patient-reported outcome measures of tinnitus assess the severity and disability retrospectively, which may result in adequate reliability, but cannot capture the fluctuating and individualized nature of tinnitus. Experience sampling may provide an alternative.

Objective

To use an ecological momentary assessment (EMA) to measure tinnitus disability and associated constructs.

Design, Setting, and Participants

Forty adults with tinnitus provided self-report of their tinnitus bother using 5 questions measured by EMA, as well as standard retrospective outcome measures. In this 6-week longitudinal observational study conducted from July 15 to December 22, 2014, participants provided EMA data for 2 weeks (part 1); then after a 2-week break, they provided EMA data for an additional 2 weeks (part 2). A text message with a link to the EMA survey was sent for a total of 56 assessments during each 2-week assessment period. Ecological momentary assessment responses were evaluated using multilevel confirmatory factor analysis to assess the fluctuating nature of bothersome tinnitus across the group and within the pool of individuals over time.

Main Outcomes and Measures

Ecological momentary assessment questions measured tinnitus disability and associated constructs. Compliance in each study part was assessed based on response rates. The Tinnitus Functional Index and the Overall Global Rating of Bother Scale were assessed at the beginning and end of each 2-week assessment period to explore the effect of the frequent EMAs on the perceived level of bother from tinnitus.

Results

Of the 40 participants in the study (10 women and 30 men; mean [SD] age, 60.0 [10.5] years), the median survey response rate was high (49 responses to 56 surveys sent [88%] for part 1 and 47 responses of 56 surveys sent [84%] for part 2). The latent factor identified by the 2-level confirmatory factor analysis models demonstrates that within-individual tinnitus bother, loudness, and stress vary together over time. In addition, tinnitus bother, feeling, and stress symptoms all vary together across individuals, which means that bother and stress covary strongly both across time and across individuals.

Conclusions and Relevance

Ecological momentary assessment evaluates the moment-to-moment perception of tinnitus and the effect of emotional and environmental factors, which suggests that it is a superior tool to measure tinnitus outcomes compared with standard retrospective self-reports. Taken together, information from emotional and environmental factors can be summarized in an underlying (latent) factor that represents a vulnerability to bothersome tinnitus and that can be used to comprehensively describe the tinnitus experience. Momentary variability in tinnitus bother is strongly associated with levels of perceived stress.

Physiological Markers of Interpersonal Stress Generation in Depression

Abnormalities in parasympathetic nervous system activity have been linked to depression, but less is known about processes underlying this relationship. The present study evaluated resting and stress-reactive respiratory sinus arrhythmia (RSA) to a laboratory stressor as predictors of daily interpersonal stress generation and depressive symptoms, whether stress generation mediated the relationship between RSA and depressive symptoms, and potential sex differences. A sample of formerly depressed 102 emerging adults (18-22 years; 78% female) completed a laboratory stressor and daily assessments of stressors and depressive symptoms over two weeks. Multilevel modeling revealed that: 1) lower resting RSA predicted daily depressive symptoms; 2) less RSA reactivity predicted interpersonal stress generation, 3) interpersonal dependent stressors mediated the relationship between RSA reactivity and daily depressive symptoms, and 4) sex differences occurred in the resting RSA-depression relationship. These findings highlight the importance of resting RSA and RSA reactivity in the examination of depression and interpersonal processes.

The Lausanne-Geneva cohort study of offspring of parents with mood disorders: methodology, findings, current sample characteristics, and perspectives

PURPOSE

Studies focusing on the offspring of affected parents utilize the well-established familial aggregation of mood disorders as a powerful tool for the identification of risk factors, early clinical manifestations, and prodromes of mood disorders in these offspring. The major goals of the Lausanne-Geneva mood cohort study are to: (1) assess the familial aggregation of bipolar and unipolar mood disorders; (2) prospectively identify risk factors for mood disorders as well as their early signs and prodromes; (3) identify their endophenotypes including cognitive features, alterations in brain structure, HPA-axis dysregulation, and abnormalities of the circadian rhythm of activity.

METHODS

Probands with bipolar disorders, major depressive disorder, and controls with at least one child aged from 4 to 17.9 years at study intake, their offspring, as well as their spouses are invited to take part in follow-up assessments at predetermined ages of the offspring. Direct semi-structured diagnostic interviews have been used for all participants. Probands, spouses, and adult offspring also undergo neurocognitive testing, anthropomorphic measures and biochemical exams, structural Magnetic Resonance Imaging, as well as objective assessments of physical activity using accelerometers in combination with ecological momentary assessments.

RESULTS

Currently, our study has up to seven follow-up assessments extending over a period of 20 years. There are 214 probands and 389 offspring with one direct interview before age 18 as well as a second assessment over follow-up. Data on 236 co-parents are also available from whom 55% have been directly interviewed. First publications support the specificity of the familial aggregation of BPD and the strong influence of an early onset of the parental BPD, which amplifies the risk of developing this disorder in offspring.

CONCLUSIONS

Information from clinical, biological, cognitive, and behavioral measures, based on contemporary knowledge, should further enhance our understanding of mood disorder psychopathology, its consequences, and underlying mechanisms.

Combining Standard Conventional Measures and Ecological Momentary Assessment of Depression, Anxiety and Coping Using Smartphone Application in Minor Stroke Population: A Longitudinal Study Protocol

Context: Stroke has several consequences on survivors’ daily life even for those who experience short-lasting neurological symptoms with no functional disability. Depression and anxiety are common psychological disorders occurring after a stroke. They affect long-term outcomes and quality of life but they are difficult to diagnose because of the neurobiological consequences of brain lesions. Current research priority is given to the improvement of the detection and prevention of those post-stroke psychological disorders. Although previous studies have brought promising perspectives, their designs based on retrospective tools involve some limits regarding their ecological validity. Ecological Momentary Assessment (EMA) is an alternative to conventional instruments that could be a key in research for understanding processes that underlined post-stroke depression and anxiety onset. We aim to evaluate the feasibility and validity of anxiety, depression and coping EMA for minor stroke patients.

Methods: Patients hospitalized in an Intensive Neuro-vascular Care Unit between April 2016 and January 2017 for a minor stroke is involved in a study based on an EMA methodology. We use a smartphone application in order to assess anxiety and depression symptoms and coping strategies four times a day during 1 week at three different times after stroke (hospital discharge, 2 and 4 months). Participants’ self-reports and clinician-rates of anxiety, depression and coping are collected simultaneously using conventional and standard instruments. Feasibility of the EMA method will be assessed considering the participation and compliance rate. Validity will be the assessed by comparing EMA and conventional self-report and clinician-rated measures.

Discussion: We expect this study to contribute to the development of EMA using smartphone in minor stroke population. EMA method offers promising research perspective in the assessment and understanding of post-stroke psychological disorders. The development of EMA in stroke population could lead to clinical implications such as remotely psychological follow-ups during early supported discharge.

Trial registration: European Clinical Trials Database Number 2014-A01937-40

What can daily life assessment tell us about the bipolar spectrum?

Evidence suggests that bipolar psychopathology is better characterized as a spectrum than by categorical diagnoses. The examination of symptoms and impairment associated with bipolar spectrum psychopathology is important and can be enhanced by methods that examine affect, thoughts, and behavior in daily life. The present study extended findings that provide validation of a continuum of bipolar psychopathology in daily life. Young adults (n=294) completed the Hypomanic Personality Scale (HPS) and experience sampling using smartphones. Participants were signaled eight times daily for one week to complete surveys in their normal daily environment. Bipolar spectrum psychopathology was characterized by increased positive and negative affect, confidence, racing thoughts, energy, and impulsivity in daily life. The HPS moderated the association of stress with trouble concentrating, irritability with dysphoria and impulsivity, and confidence with feeling like one's emotions were out of control. This study demonstrated that bipolar spectrum psychopathology is associated with disruptions in affect, thoughts, and behaviors and provided further evidence for a continuum of bipolar psychopathology. ESM is a promising method for examining dynamic constructs such as bipolar spectrum psychopathology and has the potential to be a strong research and clinical tool.

The experience sampling method as an mHealth tool to support self-monitoring, self-insight, and personalized health care in clinical practice

BACKGROUND

The experience sampling method (ESM) builds an intensive time series of experiences and contexts in the flow of daily life, typically consisting of around 70 reports, collected at 8-10 random time points per day over a period of up to 10 days.

METHODS

With the advent of widespread smartphone use, ESM can be used in routine clinical practice. Multiple examples of ESM data collections across different patient groups and settings are shown and discussed, varying from an ESM evaluation of a 6-week randomized trial of mindfulness, to a twin study on emotion dynamics in daily life.

RESULTS

Research shows that ESM-based self-monitoring and feedback can enhance resilience by strengthening the capacity to use natural rewards. Personalized trajectories of starting or stopping medication can be more easily initiated and predicted if sensitive feedback data are available in real time. In addition, personalized trajectories of symptoms, cognitive abilities, symptoms impacting on other symptoms, the capacity of the dynamic system of mental health to "bounce back" from disturbance, and patterns of environmental reactivity yield uniquely personal data to support shared decision making and prediction in clinical practice. Finally, ESM makes it possible to develop insight into previous implicit patterns of thought, experience, and behavior, particularly if rapid personalized feedback is available.

CONCLUSIONS

ESM enhances clinical practice and research. It is empowering, providing co-ownership of the process of diagnosis, treatment evaluation, and routine outcome measurement. Blended care, based on a mix of face-to-face and ESM-based outside-the-office treatment, may reduce costs and improve outcomes.

Worry and cognitive control predict course trajectories of anxiety in older adults with late-life depression

BACKGROUND

Many older adults with depressive disorder manifest anxious distress. This longitudinal study examines the predictive value of worry as a maladaptive cognitive emotion regulation strategy, and resources necessary for successful emotion regulation (i.e., cognitive control and resting heart rate variability [HRV]) for the course of anxiety symptoms in depressed older adults. Moreover, it examines whether these emotion regulation variables moderate the impact of negative life events on severity of anxiety symptoms.

METHODS

Data of 378 depressed older adults (CIDI) between 60 and 93 years (of whom 144 [41%] had a comorbid anxiety disorder) from the Netherlands Study of Depression in Older Adults (NESDO) were used. Latent Growth Mixture Modeling was used to identify different course trajectories of six-months BAI scores. Univariable and multivariable longitudinal associations of worry, cognitive control and HRV with symptom course trajectories were assessed.

RESULTS

We identified a course trajectory with low and improving symptoms (57.9%), a course trajectory with moderate and persistent symptoms (33.5%), and a course trajectory with severe and persistent anxiety symptoms (8.6%). Higher levels of worry and lower levels of cognitive control predicted persistent and severe levels of anxiety symptoms independent of presence of anxiety disorder. However, worry, cognitive control and HRV did not moderate the impact of negative life events on anxiety severity.

CONCLUSIONS

Worry may be an important and malleable risk factor for persistence of anxiety symptoms in depressed older adults. Given the high prevalence of anxious depression in older adults, modifying worry may constitute a viable venue for alleviating anxiety levels.

Interpersonal problems and negative affect in Borderline Personality and Depressive Disorders in daily life

Theories of Borderline Personality Disorder (BPD) suggest that interpersonal problems in BPD act as triggers for negative affect and, at the same time, are a possible result of affective dysregulation. Therefore, we assessed the relations between momentary negative affect (hostility, sadness, fear) and interpersonal problems (rejection, disagreement) in a sample of 80 BPD and 51 depressed outpatients at 6 time-points over 28 days. Data were analyzed using multivariate multi-level modeling to separate momentary-, day-, and person-level effects. Results revealed a mutually reinforcing relationship between disagreement and hostility, rejection and hostility, and between rejection and sadness in both groups, at the momentary and day level. The mutual reinforcement between hostility and rejection/disagreement was significantly stronger in the BPD group. Moreover, the link between rejection and sadness was present at all three levels of analysis for the BPD group, while it was localized to the momentary level in the depressed group.

Treating major depression with yoga: A prospective, randomized, controlled pilot trial

Background

Conventional pharmacotherapies and psychotherapies for major depression are associated with limited adherence to care and relatively low remission rates. Yoga may offer an alternative treatment option, but rigorous studies are few. This randomized controlled trial with blinded outcome assessors examined an 8-week hatha yoga intervention as mono-therapy for mild-to-moderate major depression.

Methods

Investigators recruited 38 adults in San Francisco meeting criteria for major depression of mild-to-moderate severity, per structured psychiatric interview and scores of 14–28 on Beck Depression Inventory-II (BDI). At screening, individuals engaged in psychotherapy, antidepressant pharmacotherapy, herbal or nutraceutical mood therapies, or mind-body practices were excluded. Participants were 68% female, with mean age 43.4 years (SD = 14.8, range = 22–72), and mean BDI score 22.4 (SD = 4.5). Twenty participants were randomized to 90-minute hatha yoga practice groups twice weekly for 8 weeks. Eighteen participants were randomized to 90-minute attention control education groups twice weekly for 8 weeks. Certified yoga instructors delivered both interventions at a university clinic. Primary outcome was depression severity, measured by BDI scores every 2 weeks from baseline to 8 weeks. Secondary outcomes were self-efficacy and self-esteem, measured by scores on the General Self-Efficacy Scale (GSES) and Rosenberg Self-Esteem Scale (RSES) at baseline and at 8 weeks.

Results

In intent-to-treat analysis, yoga participants exhibited significantly greater 8-week decline in BDI scores than controls (p-value = 0.034). In sub-analyses of participants completing final 8-week measures, yoga participants were more likely to achieve remission, defined per final BDI score ≤ 9 (p-value = 0.018). Effect size of yoga in reducing BDI scores was large, per Cohen’s d = -0.96 [95%CI, -1.81 to -0.12]. Intervention groups did not differ significantly in 8-week change scores for either the GSES or RSES.

Conclusion

In adults with mild-to-moderate major depression, an 8-week hatha yoga intervention resulted in statistically and clinically significant reductions in depression severity.

Trial registration

ClinicalTrials.gov NCT01210651

Bipolar disorder recurrence prevention using self-monitoring daily mood charts: case reports from a 5 year period

Mood symptoms in bipolar disorders are significantly related to psychosocial events, and the personalized identification of symptom triggers is important. Ecological momentary assessments have been used in paper-and-pencil form to explore emotional reactivity to daily life stress in patients with bipolar disorder. However, there are few data on long-term recurrence prevention effects using ecological momentary assessments. Subjects were three outpatients with bipolar disorder who had a history of at least one admission. They recorded self-monitoring daily mood charts using a 5-point Likert scale. Paper-and-pencil mood charts included mood, motivation, thinking speed, and impulsivity. Additionally, they recorded waking time, bedtime, and medication compliance. Fewer manic or depressive episodes including admissions occurred after self-monitoring daily mood charts compared to patients' admissions in the past 3 years. This study suggests that self-monitoring daily mood in addition to mood stabilizing medication has some effect on recurrence prevention in follow-up periods of at least 5 years. Further studies with rigorous designs and large sample sizes are needed.

Mental disorders as networks of problems: a review of recent insights

PURPOSE

The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years.

METHODS

This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three main themes: comorbidity, prediction, and clinical intervention.

RESULTS

Pertaining to comorbidity, the network approach provides a powerful new framework to explain why certain disorders may co-occur more often than others. For prediction, studies have consistently found that symptom networks of people with mental disorders show different characteristics than that of healthy individuals, and preliminary evidence suggests that networks of healthy people show early warning signals before shifting into disordered states. For intervention, centrality-a metric that measures how connected and clinically relevant a symptom is in a network-is the most commonly studied topic, and numerous studies have suggested that targeting the most central symptoms may offer novel therapeutic strategies.

CONCLUSIONS

We sketch future directions for the network approach pertaining to both clinical and methodological research, and conclude that network analysis has yielded important insights and may provide an important inroad towards personalized medicine by investigating the network structures of individual patients.

Advances in Scientific Possibilities Offered by Real-Time Monitoring Technology

There has been a marked increase in research aimed at studying dynamic (e.g., day-to-day, moment-to-moment) changes in mental disorders and related behavior problems. Indeed, the number of scientific papers published that focus on real-time monitoring has been nearly doubling every five years for the past several decades. These methods allow for a more fine-grained description of phenomena of interest as well as for real-world tests of theoretical models of human behavior. Here we comment on the recent study by van Winkel and colleagues (this issue)as an excellent example of the use of real-time monitoring methods to better understand mental disorders. We also discuss the expanding universe of new technologies (e.g., smartphones, wearable biosensors) that can be used to make discoveries about psychopathology and related constructs and describe what we perceive to be some of the most exciting scientific possibilities that can be achieved in the near term by taking advantage of these new and rapidly developing tools.

Repeated self-evaluations may involve familiarization: An exploratory study related to Ecological Momentary Assessment designs in patients with major depressive disorder

A growing body of research in clinical psychology is now relying on Ecological Momentary Assessment (EMA). EMA is fitted to investigate fluctuating processes and as such, it is of particular interest in a clinical context in which patients are often characterized by fluctuating behaviors and affective states or symptoms. EMA typically involves frequent self-evaluations over long periods, which may influence patient response. The present study aimed to determine whether EMA follow-ups could influence the participants' self-evaluations over time. The sample comprised 24 outpatients suffering from a Major Depressive Disorder (15 women, age = 51.4 ± 9.6). This study relied on an EMA protocol involving self-evaluations of seven depressive symptoms twice a day over 5 months. Patients did not show any clinical improvement following the clinical screening and the level of depressive symptoms during the follow-up. As a novel finding, significant moderate to large effects were observed for decreased variability and instability of psychological states over time. The main difference in temporal properties of psychological states was found after the first two weeks of the follow-up. This study characterized early changes in patients' self-evaluations, suggesting the idea of a valuable familiarization period during the first two weeks of an EMA follow-up.

Development of a Mobile Phone App to Support Self-Monitoring of Emotional Well-Being: A Mental Health Digital Innovation

BACKGROUND

Emotional well-being is a primary component of mental health and well-being. Monitoring changes in emotional state daily over extended periods is, however, difficult using traditional methodologies. Providing mental health support is also challenging when approximately only 1 in 2 people with mental health issues seek professional help. Mobile phone technology offers a sustainable means of enhancing self-management of emotional well-being.

OBJECTIVE

This paper aims to describe the development of a mobile phone tool designed to monitor emotional changes in a natural everyday context and in real time.

METHODS

This evidence-informed mobile phone app monitors emotional mental health and well-being, and it provides links to mental health organization websites and resources. The app obtains data via self-report psychological questionnaires, experience sampling methodology (ESM), and automated behavioral data collection.

RESULTS

Feedback from 11 individuals (age range 16-52 years; 4 males, 7 females), who tested the app over 30 days, confirmed via survey and focus group methods that the app was functional and usable.

CONCLUSIONS

Recommendations for future researchers and developers of mental health apps to be used for research are also presented. The methodology described in this paper offers a powerful tool for a range of potential mental health research studies and provides a valuable standard against which development of future mental health apps should be considered.

Tablet-based support for older adults with severe mood disorders treated in an ambulatory geriatric psychiatry setting: Protocol of a feasibility study of the eCare@Home platform

INTRODUCTION

Although older adults are just as likely to benefit from e-mental health as their younger counterparts, there are virtually no applications specifically designed to accommodate the needs of older adults with recurrent depression or bipolar disorder. Recurrent mood disorders constitute a large and rising proportion of the global disease in older populations, indicating a need for more e-mental health applications targeting this group. This paper describes the theoretical background and methodology of a study examining the feasibility of a tablet-based self-management platform for older adults with recurrent mood disorders. The eCare@Home platform was designed to 1) improve patients' awareness and knowledge of recurrent mood disorders and their treatment, 2) promote self-management through the use of a simple daily monitoring tool, and 3) facilitate online contact with their clinician through videoconferencing.

METHODS

The design involves a single-group four-month pilot study, with measurements at baseline (T0), and at weeks 8 and 16 (T1 and T2). The target group consists of older outpatients (aged 60 or above) who are undergoing treatment for recurrent depressive or bipolar disorder (N = 50), and their clinicians (N = 10). Primary feasibility endpoints will be system acceptability, system usability, and client satisfaction with the platform. In addition, qualitative data from semi-structured interviews in N = 10 patients and N = 5 clinicians will be gathered to provide more insight into user experiences and evaluations of the platform's added value.

DISCUSSION

To the best of our knowledge, this is the first study to evaluate the feasibility and acceptability of a tablet-based e-mental health platform for older adults with severe mood disorders. If tablet-based support for this group is shown to be feasible, the intention is to proceed with the design of a large-scale process and outcome evaluation. The strengths and limitations of the methodology used are addressed in this article.Trial Registration: registration is pending.

Smartphone-based ecological momentary assessment for Chinese patients with depression: An exploratory study in Taiwan

Mobile mental health has a potential to improve the recognition and management of Chinese patients with depression. Currently, evidence regarding ecological momentary assessment (EMA) for depressive disorder mostly originates from Western studies. Herein, we examined the validity of smartphone-based EMA for depression in Chinese patients and explored the determinants of use. A smartphone application, iHOPE, was used to perform daily EMA of depression, anxiety, sleep and cognitive performance. Outpatients with depressive disorder were recruited to use iHOPE for 8 weeks. Clinical characteristics and smartphone use patterns were assessed at baseline. We enrolled 59 Chinese patients with depression. In 8 weeks, participants interacted with iHOPE for an average of 10.8 (SD=12.3) days; a trend of decreased frequency of use (p=0.03) was observed. Scores of HAM-D at baseline was associated with, of the first 2 weeks, scores of PHQ-9 (p=0.005), EMA of depression (p=0.003) and anxiety (p<0.001), and poorer sleep quality (p=0.023). Among the demographic, clinical and smartphone-use variables examined, only limited internet package for smartphone (<500M per month) predicted higher use of iHOPE (p=0.04). The present study provides initial evidence for the feasibility of smartphone-based EMA in Chinese patients with depression. Level of engagement needs to be improved before determining its clinical usefulness.

Experience Sampling of Positive Affect in Adolescents with Autism: Feasibility and Preliminary Findings

BACKGROUND

Experience sampling is a powerful method for obtaining ecologically valid data from research participants in real-world contexts. Given the urgent need for innovative and sensitive outcome measures in autism spectrum disorder (ASD) research, the present study sought to examine the feasibility of using experience sampling of positive affect and behavior in adolescents with ASD.

METHOD

Nineteen high functioning adolescents with ASD and 20 sex and age matched controls completed smartphone- and Qualtrics® -based experience sampling of positive affect and behavior six times over four days.

RESULTS

Adherence was excellent: adolescents with ASD completed 85% of the assessments, compared to 93% in controls, and response rates were not impacted by age or IQ. Groups did not differ in positive affect overall or as a function of activities, nor did groups differ in the proportion of assessments completed during social or nonsocial activities. However, groups did differ in the proportion of assessments completed during preferred activities.

CONCLUSIONS

Results suggest that smartphone- and Qualtrics® -based experience sampling with high functioning adolescents with ASD is feasible and captures real-world behaviors that would not be possible using laboratory-based measures.

Factors contributing to depressive mood states in everyday life: A systematic review

BACKGROUND

Although accumulated evidence suggests that fluctuations in depressed mood are common among individuals with depression, and may be associated with onset, duration, and severity of illness, a systematic appraisal of putative predictors of depressed mood is lacking.

METHODS

A systematic search for relevant studies in the literature was conducted using PsycInfo and PubMed databases via EbscoHost in February 2016. The search was limited to articles using the experience sampling method, an approach suitable for capturing in situ fluctuations in mood states.

RESULTS

Forty-two studies met inclusion criteria for the review, from which three key risk factors (poor sleep, stress, and significant life events) and two protective factors (physical activity and quality of social interactions) were identified. The majority of papers supported concurrent and lagged associations between these putative protective/risk factors and depressed mood.

LIMITATIONS

Despite support for each of the proposed protective/risk factors, few studies evaluated multiple factors in the same study. Moreover, the time course for the effects of these predictors on depressed mood remains largely unknown.

CONCLUSIONS

The present review identified several putative risk and protective factors for depressed mood. A review of the literature suggests that poor sleep, negative social interactions, and stressful negative events may temporally precede spikes in depressed mood. In contrast, exercise and positive social interactions have been shown to predict subsequent declines in depressed mood. However, the lack of multivariate models in which the unique contributions of various predictors could be evaluated means that the current state of knowledge prevents firm conclusions about which factors are most predictive of depressed mood. More complex modeling of these effects is necessary in order to provide insights useful for clinical treatment in daily life of the depressed mood component of depressive disorders.

Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening

Background

Language reflects the state of one’s mental health and personal characteristics. It also reveals preoccupations with a particular schema, thus possibly providing insights into psychological conditions. Using text or lexical analysis in exploring depression, negative schemas and self-focusing tendencies may be depicted. As mobile technology has become highly integrated in daily routine, mobile devices have the capacity for ecological momentary assessment (EMA), specifically the experience sampling method (ESM), where behavior is captured in real-time or closer in time to experience in one’s natural environment. Extending mobile technology to psychological health could augment initial clinical assessment, particularly of mood disturbances, such as depression and analyze daily activities, such as language use in communication. Here, we present the process of lexicon generation and development and the initial validation of Psychologist in a Pocket (PiaP), a mobile app designed to screen signs of depression through text analysis.

Objective

The main objectives of the study are (1) to generate and develop a depressive lexicon that can be used for screening text-input in mobile apps to be used in the PiaP; and (2) to conduct content validation as initial validation.

Methods

The first phase of our research focused on lexicon development. Words related to depression and its symptoms based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) and in the ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines classification systems were gathered from focus group discussions with Filipino college students, interviews with mental health professionals, and the review of established scales for depression and other related constructs.

Results

The lexicon development phase yielded a database consisting of 13 categories based on the criteria depressive symptoms in the DSM-5 and ICD-10. For the draft of the depression lexicon for PiaP, we were able to gather 1762 main keywords and 9655 derivatives of main keywords. In addition, we compiled 823,869 spelling variations. Keywords included negatively-valenced words like “sad”, “unworthy”, or “tired” which are almost always accompanied by personal pronouns, such as “I”, “I’m” or “my” and in Filipino, “ako” or “ko”. For the content validation, only keywords with CVR equal to or more than 0.75 were included in the depression lexicon test-run version. The mean of all CVRs yielded a high overall CVI of 0.90. A total of 1498 main keywords, 8911 derivatives of main keywords, and 783,140 spelling variations, with a total of 793, 553 keywords now comprise the test-run version.

Conclusions

The generation of the depression lexicon is relatively exhaustive. The breadth of keywords used in text analysis incorporates the characteristic expressions of depression and its related constructs by a particular culture and age group. A content-validated mobile health app, PiaP may help augment a more effective and early detection of depressive symptoms.

Very early social support following mild stroke is associated with emotional and behavioral outcomes three months later

OBJECTIVE

To investigate whether social contact and support received during hospitalization for acute ischemic stroke predict depression and daily life functioning three months later.

DESIGN

Prospective observational study using Ecological Momentary Assessments to evaluate the number of social contacts as well as social support received from family, friends and medical staff within 24 hours following admission for stroke. Patients also monitored depression symptoms and behavior in real-time and in daily life contexts three months later.

SETTING

A university hospital acute stroke unit.

SUBJECTS

Thirty-four mild ischemic stroke patients.

INTERVENTIONS

None.

MAIN MEASURES

One-day Ecological Momentary Assessments immediately following stroke collected information concerning perceived social support, number of social contacts and depression symptoms. Ecological Momentary Assessments was repeated three months later and addressed depression levels as well as activities of daily living, such as working, cooking, shopping and housework.

RESULTS

The number of social interactions received at hospitalization did not predict three-month outcomes. However, a better quality of moral support from friends and family immediately after stroke was associated with decreases in later depression levels ( p = 0.041) and increases in activities of daily living ( p = 0.011). Material support from friends and family was associated with increases in activities of daily living ( p = 0.012). No effect was observed for support received from medical staff.

CONCLUSIONS

Patient perceptions of better support quality, and not quantity, immediately following mild stroke, are associated with better behavioral and emotional outcomes three months later.

Restoration in Its Natural Context: How Ecological Momentary Assessment Can Advance Restoration Research

More and more people use self-tracking technologies to track their psychological states, physiology, and behaviors to gain a better understanding of themselves or to achieve a certain goal. Ecological Momentary Assessment (EMA) also offers an excellent opportunity for restorative environments research, which examines how our physical environment (especially nature) can positively influence health and wellbeing. It enables investigating restorative health effects in everyday life, providing not only high ecological validity but also opportunities to study in more detail the dynamic processes playing out over time on recovery, thereby bridging the gap between laboratory (i.e., short-term effects) and epidemiological (long-term effects) research. We have identified four main areas in which self-tracking could help advance restoration research: (1) capturing a rich set of environment types and restorative characteristics; (2) distinguishing intra-individual from inter-individual effects; (3) bridging the gap between laboratory and epidemiological research; and (4) advancing theoretical insights by measuring a more broad range of effects in everyday life. This paper briefly introduces restorative environments research, then reviews the state of the art of self-tracking technologies and methodologies, discusses how these can be implemented to advance restoration research, and presents some examples of pioneering work in this area.

Ambulatory and diary methods can facilitate the measurement of patient-reported outcomes

PURPOSE

Ambulatory and diary methods of self-reported symptoms and well-being have received increasing interest in recent years. These methods are a valuable addition to traditional strategies for the assessment of patient-reported outcomes (PROs) in that they capture patients' recent symptom experiences repeatedly in their natural environments. In this article, we review ways that incorporating diary methods into PRO measurement can facilitate research on quality of life.

METHODS

Several diary methods are currently available, and they include "real-time" (Ecological Momentary Assessment) and "near-real-time" (end-of-day assessments, Day Reconstruction Method) formats. We identify the key benefits of these methods for PRO research.

RESULTS

(1) In validity testing, diary assessments can serve as a standard for evaluating the ecological validity and for identifying recall biases of PRO instruments with longer-term recall formats. (2) In research and clinical settings, diaries have the ability to closely capture variations and dynamic changes in quality of life that are difficult or not possible to obtain from traditional PRO assessments. (3) In test construction, repeated diary assessments can expand understanding of the measurement characteristics (e.g., reliability, dimensionality) of PROs in that parameters for differences between people can be compared with those for variation within people.

CONCLUSIONS

Diary assessment strategies can enrich the repertoire of PRO assessment tools and enhance the measurement of patients' quality of life.

Modeling BAS Dysregulation in Bipolar Disorder

Time series analysis is a technique that can be used to analyze the data from a single subject and has great potential to investigate clinically relevant processes like affect regulation. This article uses time series models to investigate the assumed dysregulation of affect that is associated with bipolar disorder. By formulating a number of alternative models that capture different kinds of theoretically predicted dysregulation, and by comparing these in both bipolar patients and controls, we aim to illustrate the heuristic potential this method of analysis has for clinical psychology. We argue that, not only can time series analysis elucidate specific maladaptive dynamics associated with psychopathology, it may also be clinically applied in symptom monitoring and the evaluation of therapeutic interventions.

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

BACKGROUND

Personal device technology has facilitated gathering data in real-time using Ecological momentary assessment (EMA). We hypothesized that using smartphones to measure symptoms in auto-generated surveys twice a day would be feasible in a group with bipolar disorder (BD). A second exploratory objective of this study was to compare potential differences in core symptoms between BD and healthy control (HC) groups.

METHODS

A two-arm, parallel group, observational study was designed to measure completion rates of surveys of symptoms of mood, energy, speed of thought, impulsivity, and social stress in BD (N=10) and HC (N=10) participants. The surveys were auto-generated twice a day for fourteen days, and subjects could also perform self-generated surveys. Completion rates were compared between BD and HC groups. Scores were averaged for each participant over the 14 day period, and group medians were compared.

RESULTS

Median completion rates did not differ between groups: 95% in BD, 88% in HC (p=0.68); the median completion rate of auto-generated surveys in the BD group was 79% and in the HC group was 71% (p=0.22). The BD group had significantly lower median mood score (p=0.043) and energy score (p=0.007) than the HC group. Median scores of speed of thoughts (p=0.739), impulsivity (p=0.123) and social stress (p=0.056) did not significantly differ between BD and HC. The BD group had significantly higher range of variability of group median mood (p=0.043), speed of thoughts (p=0.002) and impulsivity (p=0.005) scores over the course of 14 days than HC, while range of variability of energy (p=0.218) and social stress (p=0.123) scores did not differ. Results were not significantly different between auto-generated and self-generated surveys for BD or HC.

LIMITATIONS

This pilot study was conducted for a short time and with a small sample.

CONCLUSIONS

This study demonstrates feasibility of using EMA with a smartphone to gather data on BD symptoms.

Using Smartphones to Monitor Bipolar Disorder Symptoms: A Pilot Study

BACKGROUND

Relapse prevention in bipolar disorder can be improved by monitoring symptoms in patients' daily life. Smartphone apps are easy-to-use, low-cost tools that can be used to assess this information. To date, few studies have examined the usefulness of smartphone data for monitoring symptoms in bipolar disorder.

OBJECTIVE

We present results from a pilot test of a smartphone-based monitoring system, Social Information Monitoring for Patients with Bipolar Affective Disorder (SIMBA), that tracked daily mood, physical activity, and social communication in 13 patients. The objective of this study was to investigate whether smartphone measurements predicted clinical symptoms levels and clinical symptom change. The hypotheses that smartphone measurements are (1) negatively related to clinical depressive symptoms and (2) positively related to clinical manic symptoms were tested.

METHODS

Clinical rating scales were administered to assess clinical depressive and manic symptoms. Patients used a smartphone with the monitoring app for up to 12 months. Random-coefficient multilevel models were computed to analyze the relationship between smartphone data and externally rated manic and depressive symptoms. Overall clinical symptom levels and clinical symptom changes were predicted by separating between-patient and within-patient effects. Using established clinical thresholds from the literature, marginal effect plots displayed clinical relevance of smartphone data.

RESULTS

Overall symptom levels and change in clinical symptoms were related to smartphone measures. Higher overall levels of clinical depressive symptoms were predicted by lower self-reported mood measured by the smartphone (beta=-.56, P<.001). An increase in clinical depressive symptoms was predicted by a decline in social communication (ie, outgoing text messages: beta=-.28, P<.001) and a decline in physical activity as measured by the smartphone (ie, cell tower movements: beta=-.11, P=.03). Higher overall levels of clinical manic symptoms were predicted by lower physical activity on the smartphone (ie, distance travelled: beta=-.37, P<.001), and higher social communication (beta=.48, P=.03). An increase in clinical manic symptoms was predicted by a decrease in physical activity on the smartphone (beta=-.17, P<.001).

CONCLUSIONS

Clinical symptoms were related to some objective and subjective smartphone measurements, but not all smartphone measures predicted the occurrence of bipolar symptoms above clinical thresholds. Thus, smartphones have the potential to monitor bipolar disorder symptoms in patients' daily life. Further validation of monitoring tools in a larger sample is needed. Conclusions are limited by the low prevalence of manic and depressive symptoms in the study sample.

TRIAL REGISTRATION

International Standard Randomized Controlled Trial Number (ISRCTN): 05663421; http://www.controlled-trials.com/ISRCTN05663421 (Archived by WebCite at http://www.webcitation.org/6d9wsibJB).

Daily symptom ratings for studying premenstrual dysphoric disorder: A review

BACKGROUND

To review how daily symptom ratings have been used in research into premenstrual dysphoric disorder (PMDD), and to discuss opportunities for the future.

METHODS

PsycINFO and Medline were systematically searched, resulting in the inclusion of 75 studies in which (1) participants met the diagnostic criteria for late luteal phase dysphoric disorder (LLPDD) or PMDD and (2) diaries were used to study LLPDD/PMDD.

RESULTS

To date, diaries have been used to gain insight into the aetiology and phenomenology of PMDD, to examine associated biological factors, and to assess treatment efficacy. We found low consistency among the diaries used, and often only part of the menstrual cycle was analysed instead of the whole menstrual cycle. We also observed that there was substantial variability in diagnostic procedures and criteria.

LIMITATIONS

This review excluded diary studies conducted in women with premenstrual syndrome, women seeking help for premenstrual complaints without a clear diagnosis, and women without premenstrual complaints.

CONCLUSIONS

Prospective daily ratings of symptoms and related variables provide a valuable and important tool in the study of PMDD. This paper addresses some options for improving the use of diaries and proposes the use of experience sampling and ecological momentary assessment to investigate within-person variability in symptoms in more detail.

Ecological Momentary Assessment and Smartphone Application Intervention in Adolescents with Substance Use and Comorbid Severe Psychiatric Disorders: Study Protocol

CONTEXT

Substance use disorders (SUDs) are highly prevalent among inpatient adolescents with psychiatric disorders. In this population, substance use and other psychiatric outcomes can reinforce one another. Despite the need for integrated interventions in youths with dual diagnoses, few specific instruments are available. App-based technologies have shown promising results to help reduce substance use in adolescents, but their applicability in youths with associated severe psychiatric disorders is poorly documented. We aim to evaluate the feasibility of an ecological momentary assessment (EMA) intervention for all substance users, and of a smartphone application for cannabis users (Stop-Cannabis), for outpatient treatment after hospital discharge.

METHODS AND ANALYSIS

All inpatient adolescents with psychiatric disorders hospitalized between 2016 and 2018 in a university hospital will be systematically screened for SUD and, if positive, will be assessed by an independent specialist addiction team. Participants with confirmed SUDs will be invited and helped to download an EMA app and, if required, the Stop-Cannabis app, the week preceding hospital discharge. Information about the acceptability and use of both apps and the validity of EMA data in comparison to clinical assessments will be assessed after 6 months and 1 year.

DISCUSSION

This research has been designed to raise specific issues for consideration regarding the sequence between substance use, contextual factors, and other psychiatric symptoms among adolescents with comorbid severe psychiatric disorders. A better understanding of the mechanisms involved will inform the development of integrated treatment for dual disorders at that age.

ETHICS AND DISSEMINATION

The study has already been approved and granted. Dissemination will include presentations at international congresses as well as publications in peer-reviewed journals.

TRIAL REGISTRATION

European Clinical Trials Database: Number 2016-001999-30.

Emotions in Everyday Life

Despite decades of research establishing the causes and consequences of emotions in the laboratory, we know surprisingly little about emotions in everyday life. We developed a smartphone application that monitored real-time emotions of an exceptionally large (N = 11,000+) and heterogeneous participants sample. People's everyday life seems profoundly emotional: participants experienced at least one emotion 90% of the time. The most frequent emotion was joy, followed by love and anxiety. People experienced positive emotions 2.5 times more often than negative emotions, but also experienced positive and negative emotions simultaneously relatively frequently. We also characterized the interconnections between people's emotions using network analysis. This novel approach to emotion research suggests that specific emotions can fall into the following categories 1) connector emotions (e.g., joy), which stimulate same valence emotions while inhibiting opposite valence emotions, 2) provincial emotions (e.g., gratitude), which stimulate same valence emotions only, or 3) distal emotions (e.g., embarrassment), which have little interaction with other emotions and are typically experienced in isolation. Providing both basic foundations and novel tools to the study of emotions in everyday life, these findings demonstrate that emotions are ubiquitous to life and can exist together and distinctly, which has important implications for both emotional interventions and theory.

Experience sampling and ecological momentary assessment studies in psychopharmacology: A systematic review

Experience sampling methods (ESM) and ecological momentary assessment (EMA) offer insight into daily life experiences, including symptoms of mental disorders. The application of ESM/EMA in psychopharmacology can be a valuable addition to more traditional measures such as retrospective self-report questionnaires because they may help reveal the impact of psychotropic medication on patients' actual experiences. In this paper we systematically review the existing literature on the use of ESM/EMA in psychopharmacology research. To this end, we searched the PsycInfo and Medline databases for all available ESM/EMA studies on the use of psychotropic medication in patients with DSM-III-R and DSM-IV disorders. Dissertations were excluded. We included 18 studies that applied ESM/EMA to study the effects of medication on patients with major depressive disorder, substance use disorder, attention-deficit hyperactivity disorder, psychotic disorder, and anxiety disorder. We found that ESM/EMA may allow researchers and clinicians to track patients during different phases of treatment: before treatment to predict outcome, during treatment to examine the effects of treatment on symptoms and different aspects of daily life experience, and after treatment to detect vulnerability for relapse. Moreover, ESM/EMA can potentially help determine how long and in what contexts medications are effective. Thus, ESM/EMA may benefit both researchers and clinicians and might prove to be an effective tool for improving the treatment of psychiatric patients.

Effects of momentary self-monitoring on empowerment in a randomized controlled trial in patients with depression

Background

Interventions based on the experience sampling method (ESM) are ideally suited to provide insight into personal, contextualized affective patterns in the flow of daily life. Recently, we showed that an ESM-intervention focusing on positive affect was associated with a decrease in symptoms in patients with depression. The aim of the present study was to examine whether ESM-intervention increased patient empowerment.

Methods

Depressed out-patients (n = 102) receiving psychopharmacological treatment who had participated in a randomized controlled trial with three arms: (i) an experimental group receiving six weeks of ESM self-monitoring combined with weekly feedback sessions, (ii) a pseudo-experimental group participating in six weeks of ESM self-monitoring without feedback, and (iii) a control group (treatment as usual only). Patients were recruited in the Netherlands between January 2010 and February 2012. Self-report empowerment scores were obtained pre- and post-intervention.

Results

There was an effect of group × assessment period, indicating that the experimental (B = 7.26, P = 0.061, d = 0.44, statistically imprecise) and pseudo-experimental group (B = 11.19, P = 0.003, d = 0.76) increased more in reported empowerment compared to the control group. In the pseudo-experimental group, 29% of the participants showed a statistically reliable increase in empowerment score and 0% reliable decrease compared to 17% reliable increase and 21% reliable decrease in the control group. The experimental group showed 19% reliable increase and 4% reliable decrease.

Conclusions

These findings tentatively suggest that self-monitoring to complement standard antidepressant treatment may increase patients’ feelings of empowerment. Further research is necessary to investigate long-term empowering effects of self-monitoring in combination with person-tailored feedback.

The application of mHealth to mental health: opportunities and challenges

Advances in smartphones and wearable biosensors enable real-time psychological, behavioural, and physiological data to be gathered in increasingly precise and unobtrusive ways. Thus, moment-to-moment information about an individual's moods, cognitions, and activities can be collected, in addition to automated data about their whereabouts, behaviour, and physiological states. In this report, we discuss the potential of these new mobile digital technologies to transform mental health research and clinical practice. By drawing on results from the INSIGHT research project, we show how traditional boundaries between research and clinical practice are becoming increasingly blurred and how, in turn, this is leading to exciting new developments in the assessment and management of common mental disorders. Furthermore, we discuss the potential risks and key challenges associated with applying mobile technology to mental health.

Major depressive disorder as a nonlinear dynamic system: bimodality in the frequency distribution of depressive symptoms over time

BACKGROUND

A defining characteristic of Major Depressive Disorder (MDD) is its episodic course, which might indicate that MDD is a nonlinear dynamic phenomenon with two discrete states. We investigated this hypothesis using the symptom time series of individual patients.

METHODS

In 178 primary care patients with MDD, the presence of the nine DSM-IV symptoms of depression was recorded weekly for two years. For each patient, the time-series plots as well as the frequency distributions of the symptoms over 104 weeks were inspected. Furthermore, two indicators of bimodality were obtained: the bimodality coefficient (BC) and the fit of a 1- and a 2-state Hidden Markov Model (HMM).

RESULTS

In 66% of the sample, high bimodality coefficients (BC>.55) were found. These corresponded to relatively sudden jumps in the symptom curves and to highly skewed or bimodal frequency distributions. The results of the HMM analyses classified 90% of the symptom distributions as bimodal.

CONCLUSIONS

A two-state pattern can be used to describe the course of depression symptoms in many patients. The BC seems useful in differentiating between subgroups of MDD patients based on their life course data.

Next-generation psychiatric assessment: Using smartphone sensors to monitor behavior and mental health

OBJECTIVE

Optimal mental health care is dependent upon sensitive and early detection of mental health problems. We have introduced a state-of-the-art method for the current study for remote behavioral monitoring that transports assessment out of the clinic and into the environments in which individuals negotiate their daily lives. The objective of this study was to examine whether the information captured with multimodal smartphone sensors can serve as behavioral markers for one's mental health. We hypothesized that (a) unobtrusively collected smartphone sensor data would be associated with individuals' daily levels of stress, and (b) sensor data would be associated with changes in depression, stress, and subjective loneliness over time.

METHOD

A total of 47 young adults (age range: 19-30 years) were recruited for the study. Individuals were enrolled as a single cohort and participated in the study over a 10-week period. Participants were provided with smartphones embedded with a range of sensors and software that enabled continuous tracking of their geospatial activity (using the Global Positioning System and wireless fidelity), kinesthetic activity (using multiaxial accelerometers), sleep duration (modeled using device-usage data, accelerometer inferences, ambient sound features, and ambient light levels), and time spent proximal to human speech (i.e., speech duration using microphone and speech detection algorithms). Participants completed daily ratings of stress, as well as pre- and postmeasures of depression (Patient Health Questionnaire-9; Spitzer, Kroenke, & Williams, 1999), stress (Perceived Stress Scale; Cohen et al., 1983), and loneliness (Revised UCLA Loneliness Scale; Russell, Peplau, & Cutrona, 1980).

RESULTS

Mixed-effects linear modeling showed that sensor-derived geospatial activity (p < .05), sleep duration (p < .05), and variability in geospatial activity (p < .05), were associated with daily stress levels. Penalized functional regression showed associations between changes in depression and sensor-derived speech duration (p < .05), geospatial activity (p < .05), and sleep duration (p < .05). Changes in loneliness were associated with sensor-derived kinesthetic activity (p < .01).

CONCLUSIONS AND IMPLICATIONS FOR PRACTICE

Smartphones can be harnessed as instruments for unobtrusive monitoring of several behavioral indicators of mental health. Creative leveraging of smartphone sensing could provide novel opportunities for close-to-invisible psychiatric assessment at a scale and efficiency that far exceeds what is currently feasible with existing assessment technologies.

Ecological momentary assessment (EMA) of depression-related phenomena

Ecological momentary assessment (EMA) is one research method increasingly employed to better understand the processes that underpin depression and related phenomena. In particular, EMA is well suited to the study of affect (e.g., positive and negative affect), affective responses to stress (e.g., emotion reactivity), and behaviors (e.g., activity level, sleep) that are associated with depression. Additionally, EMA can provide insights into self-harm behavior (i.e. suicide and non-suicidal self-injury), and other mood disorders (e.g. bipolar disorder) commonly associated with depressive episodes. Given the increasing availability and affordability of handheld computing devices such as smartphones, EMA is likely to play an increasingly important role in the study of depression and related phenomena in the future.