Momentary assessment technology as a tool to help patients with depression help themselves

An Ecological Mobile Momentary Intervention to Support Dynamic Goal Pursuit: Feasibility and Acceptability Study

BACKGROUND

Individuals can experience difficulties pursuing their goals amid multiple competing priorities in their environment. Effective goal dynamics require flexible and generalizable pursuit skills. Supporting successful goal pursuit requires a perpetually adapting intervention responsive to internal states.

OBJECTIVE

The purpose of this study was to (1) develop a flexible intervention that can adapt to an individual's changing short to medium-term goals and be applied to their daily life and (2) examine the feasibility and acceptability of the just-in-time adaptive intervention for goal pursuit.

METHODS

This study involved 3 iterations to test and systematically enhance all aspects of the intervention. During the pilot phase, 73 participants engaged in an ecological momentary assessment (EMA) over 1 month. After week 1, they attended an intervention training session and received just-in-time intervention prompts during the following 3 weeks. The training employed the Capability, Opportunity, Motivation, and Behavior (COM-B) framework for goal setting, along with mental contrasting with implementation intentions (MCII). Subsequent prompts, triggered by variability in goal pursuit, guided the participants to engage in MCII in relation to their current goal. We evaluated feasibility and acceptability, efficacy, and individual change processes by combining intensive (single-case experimental design) and extensive methods.

RESULTS

The results suggest that the digital intervention was feasible and acceptable to participants. Compliance with the intervention was high (n=63, 86%). The participants endorsed high acceptability ratings relating to both the study procedures and the intervention. All participants (N=73, 100%) demonstrated significant improvements in goal pursuit with an average difference of 0.495 units in the outcome (P<.001). The results of the dynamic network modeling suggest that self-monitoring behavior (EMA) and implementing the MCII strategy may aid in goal reprioritization, where goal pursuit itself is a driver of further goal pursuit.

CONCLUSIONS

This pilot study demonstrated the feasibility and acceptability of a just-in-time adaptive intervention among a nonclinical adult sample. This intervention used self-monitoring of behavior, the COM-B framework, and MCII strategies to improve dynamic goal pursuit. It was delivered via an Ecological Momentary Intervention (EMI) procedure. Future research should consider the utility of this approach as an additional intervention element within psychological interventions to improve goal pursuit. Sustaining goal pursuit throughout interventions is central to their effectiveness and warrants further evaluation.

The 'discontinuity hypothesis' of depression in later life-clinical and research implications

The term depression is overused as an umbrella term for a variety of conditions, including depressed mood and various psychiatric disorders. According to psychiatric diagnostic criteria, depressive disorders impact nearly all aspects of human life and are a leading cause of disability worldwide. The widespread assumption that different types of depression lie on a continuum of severity has stimulated important research on subthreshold depression in later life. This view assumes that depressed mood is a precursor of a depressive disorder. The present narrative review argues why in later life depressed mood might either (i) lie on a continuum with depressive disorders among people vulnerable for a depressive disorder or (ii) be an ageing-related epiphenomenon of underlying physical illnesses in people who are resilient to depressive disorders ('discontinuity hypothesis'). Three arguments are discussed. First, the course of depressed mood and depressive disorders differs across the life span. Second, screening instruments for depression have low predictive value for depressive disorders in later life. Third, a dose-response relationship has not been consistently found across different types of depression and detrimental health outcomes. Using the umbrella term depression may partly explain why pharmacological treatment is less effective with increasing age, and negative health-related outcomes might be overestimated. The discontinuity hypothesis may prevent pharmacological overtreatment of milder subtypes of depression and may stimulate comprehensive multidisciplinary assessment as well as the development of separate treatment algorithms for depressed mood and depressive disorders.

Effects of a Novel, Transdiagnostic Ecological Momentary Intervention for Prevention, and Early Intervention of Severe Mental Disorder in Youth (EMIcompass): Findings From an Exploratory Randomized Controlled Trial

BACKGROUND/HYPOTHESIS

Digital interventions targeting transdiagnostic mechanisms in daily life may be a promising translational strategy for prevention and early intervention of psychotic and other severe mental disorders. We aimed to investigate the feasibility and initial signals of efficacy of a transdiagnostic, compassion-focused, hybrid ecological momentary intervention for improving resilience (ie, EMIcompass) in youth with early mental health problems.

STUDY DESIGN

In an exploratory, assessor-blind randomized controlled trial, youth aged 14-25 with current distress, broad at-risk mental state, or first episode of severe mental disorder were randomly allocated to experimental (EMIcompass+treatment as usual [TAU]) or control condition (TAU). Data on primary (stress reactivity) and secondary candidate mechanisms as well as candidate primary (psychological distress) and secondary outcomes were collected.

STUDY RESULTS

Criteria for the feasibility of trial methodology and intervention delivery were met (n = 92 randomized participants). No serious adverse events were observed. Initial outcome signals were evident for reduced momentary stress reactivity (stress×time×condition, B = -0.10 95%CI -0.16--0.03, d = -0.10), aberrant salience (condition, B = -0.38, 95%CI -0.57--0.18, d = -0.56) as well as enhanced momentary resilience (condition, B = 0.55, 95%CI 0.18-0.92, d = 0.33) and quality of life (condition, B = 0.82, 95%CI 0.10-1.55, d = 0.60) across post-intervention and 4-week follow-up. No outcome signals were observed for self-reported psychological distress (condition, B = 0.57, 95%CI -1.59-2.72, d = 0.09), but there was suggestive evidence of reduced observer-rated symptoms at the 4-week follow-up (B = -1.41, 95%CI -2.85-0.02, d = -0.41).

CONCLUSIONS

Our findings provide evidence of feasibility and initial signals that EMIcompass may reduce stress reactivity and improve quality of life. A definitive trial is now warranted.

Integrating personalized experience sampling in psychotherapy: A case illustration of the Therap-i module

Background

The experience sampling methodology (ESM) is increasingly being suggested as a clinical tool in mental health care, as it offers ecologically valid, microlevel information on psychopathological processes. Patients and clinicians have recommended that applications of ESM should be personalized and integrated into the existing clinical process, but there is still much uncertainty about how implementation may look like.

Objective

To provide an example of personalized ESM assessment and feedback being integrated into psychotherapy for depression, specifically looking at the collaborative use of ESM in case conceptualization.

Methods

George, a 27-year-old man diagnosed with depression, and his therapist participated in the Therap-i randomized controlled trial, which investigates the efficacy of a personalized ESM module added to psychotherapy. Together, they created a personalized ESM questionnaire, aiming to capture their hypotheses and questions regarding George's case conceptualization. George then filled out his ESM questionnaire five times per day, for 8 weeks. During this period, ESM data were discussed and interpreted by George, his therapist, and a researcher, in three feedback sessions. In these sessions, data were visualized in a flexible feedback interface that allowed for collaborative exploration of George's data. Both patient and therapist evaluated the module through questionnaires and George also participated in a semi-structured evaluation interview.

Results

George's ESM questionnaire included personalized items on the topics of self-esteem and open versus withdrawn behavior. He completed 241 (89.3%) assessments. Discussions during the feedback sessions focused on two core themes: First, George's low energy level, which was further explored with regard to his sleep, medication, and activity patterns. Second, his low sense of self-esteem, which led to an in-depth exploration of his thinking patterns and social interactions. The ESM module was seen as useful and insightful by both George and therapist.

Conclusions

This case shows how ESM and ESM-based feedback can stimulate the collaborative exploration of the patient's complaints, and how it can provide useful insights for treatment. We discuss how our personalized ESM module relates to current clinical principles and practices, and make suggestions for further implementation.

Using an ecological momentary assessment protocol to understand problem anger in veterans

BACKGROUND AND OBJECTIVES

Problem anger is highly destructive, and is one of the most commonly reported issues in military and veteran populations. The goal of this study was to use ecological momentary assessment (EMA) to explore and characterize moment-to-moment experiences of problem anger in a sample of Australian veterans.

METHODS

Sixty veterans with problem anger (measured on the Dimensions of Anger Reactions Scale) completed measures of anger and anger rumination, before and after a 10-day EMA period which assessed the frequency, intensity, and expression of momentary anger experiences.

RESULTS

Findings showed that 75% of respondents indicated some level of anger during EMA monitoring. In 25% of cases, anger was reported as severe. Moreover, anger was expressed verbally in 43% of cases, and expressed physically in 27% of cases. While anger fluctuated frequently during the day, more severe anger was more likely to be reported in the late afternoon/early evening. Problem anger symptoms decreased significantly over time, from pre-EMA to post EMA (p < .001).

LIMITATIONS

The generalizability of findings is limited to a predominantly male sample, with low levels of risk of harm or violence. The study was also limited in the selection of outcome variables assessed and the lack of a control group; other momentary factors could influence experience of problem anger and provide further explanation of study results.

CONCLUSIONS

EMA is a valuable assessment tool for individuals with problem anger, and the potential for EMA as an intervention needs to be explored further.

A Web-Based Application for Personalized Ecological Momentary Assessment in Psychiatric Care: User-Centered Development of the PETRA Application

BACKGROUND

Smartphone self-monitoring of mood, symptoms, and contextual factors through ecological momentary assessment (EMA) provides insights into the daily lives of people undergoing psychiatric treatment. Therefore, EMA has the potential to improve their care. To integrate EMA into treatment, a clinical tool that helps clients and clinicians create personalized EMA diaries and interpret the gathered data is needed.

OBJECTIVE

This study aimed to develop a web-based application for personalized EMA in specialized psychiatric care in close collaboration with all stakeholders (ie, clients, clinicians, researchers, and software developers).

METHODS

The participants were 52 clients with mood, anxiety, and psychotic disorders and 45 clinicians (psychiatrists, psychologists, and psychiatric nurses). We engaged them in interviews, focus groups, and usability sessions to determine the requirements for an EMA web application and repeatedly obtained feedback on iteratively improved high-fidelity EMA web application prototypes. We used human-centered design principles to determine important requirements for the web application and designed high-fidelity prototypes that were continuously re-evaluated and adapted.

RESULTS

The iterative development process resulted in Personalized Treatment by Real-time Assessment (PETRA), which is a scientifically grounded web application for the integration of personalized EMA in Dutch clinical care. PETRA includes a decision aid to support clients and clinicians with constructing personalized EMA diaries, an EMA diary item repository, an SMS text message-based diary delivery system, and a feedback module for visualizing the gathered EMA data. PETRA is integrated into electronic health record systems to ensure ease of use and sustainable integration in clinical care and adheres to privacy regulations.

CONCLUSIONS

PETRA was built to fulfill the needs of clients and clinicians for a user-friendly and personalized EMA tool embedded in routine psychiatric care. PETRA is unique in this codevelopment process, its extensive but user-friendly personalization options, its integration into electronic health record systems, its transdiagnostic focus, and its strong scientific foundation in the design of EMA diaries and feedback. The clinical effectiveness of integrating personalized diaries via PETRA into care requires further research. As such, PETRA paves the way for a systematic investigation of the utility of personalized EMA for routine mental health care.

Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas

Contemporarily, depression has become a common psychiatric disorder that influences people's life quality and mental state. This study presents a systematic review analysis of depression based on a hierarchical structure approach. This research provides a rich theoretical foundation for understanding the hot spots, evolutionary trends, and future related research directions and offers further guidance for practice. This investigation contributes to knowledge by combining robust methodological software for analysis, including Citespace, Ucinet, and Pajek. This paper employed the bibliometric methodology to analyze 5,000 research articles concerning depression. This current research also employed the BibExcel software to bibliometrically measure the keywords of the selected articles and further conducted a co-word matrix analysis. Additionally, Pajek software was used to conduct a co-word network analysis to obtain a co-word network diagram of depression. Further, Ucinet software was utilized to calculate K-core values, degree centrality, and mediated centrality to better present the research hotspots, sort out the current status and reveal the research characteristics in the field of depression with valuable information and support for subsequent research. This research indicates that major depressive disorder, anxiety, and mental health had a high occurrence among adolescents and the aged. This present study provides policy recommendations for the government, non-governmental organizations and other philanthropic agencies to help furnish resources for treating and controlling depression orders.

Digital phenotyping in depression diagnostics: Integrating psychiatric and engineering perspectives

Depression is a serious medical condition and is a leading cause of disability worldwide. Current depression diagnostics and assessment has significant limitations due to heterogeneity of clinical presentations, lack of objective assessments, and assessments that rely on patients' perceptions, memory, and recall. Digital phenotyping (DP), especially assessments conducted using mobile health technologies, has the potential to greatly improve accuracy of depression diagnostics by generating objectively measurable endophenotypes. DP includes two primary sources of digital data generated using ecological momentary assessments (EMA), assessments conducted in real-time, in subjects' natural environment. This includes active EMA, data that require active input by the subject, and passive EMA or passive sensing, data passively and automatically collected from subjects' personal digital devices. The raw data is then analyzed using machine learning algorithms to identify behavioral patterns that correlate with patients' clinical status. Preliminary investigations have also shown that linguistic and behavioral clues from social media data and data extracted from the electronic medical records can be used to predict depression status. These other sources of data and recent advances in telepsychiatry can further enhance DP of the depressed patients. Success of DP endeavors depends on critical contributions from both psychiatric and engineering disciplines. The current review integrates important perspectives from both disciplines and discusses parameters for successful interdisciplinary collaborations. A clinically-relevant model for incorporating DP in clinical setting is presented. This model, based on investigations conducted by our group, delineates development of a depression prediction system and its integration in clinical setting to enhance depression diagnostics and inform the clinical decision making process. Benefits, challenges, and opportunities pertaining to clinical integration of DP of depression diagnostics are discussed from interdisciplinary perspectives.

A New Digital Assessment of Mental Health and Well-being in the Workplace: Development and Validation of the Unmind Index

BACKGROUND

Unmind is a workplace, digital, mental health platform with tools to help users track, maintain, and improve their mental health and well-being (MHWB). Psychological measurement plays a key role on this platform, providing users with insights on their current MHWB, the ability to track it over time, and personalized recommendations, while providing employers with aggregate information about the MHWB of their workforce.

OBJECTIVE

Due to the limitations of existing measures for this purpose, we aimed to develop and validate a novel well-being index for digital use, to capture symptoms of common mental health problems and key aspects of positive well-being.

METHODS

In Study 1A, questionnaire items were generated by clinicians and screened for face validity. In Study 1B, these items were presented to a large sample (n=1104) of UK adults, and exploratory factor analysis was used to reduce the item pool and identify coherent subscales. In Study 2, the final measure was presented to a new nationally representative UK sample (n=976), along with a battery of existing measures, with 238 participants retaking the Umind Index after 1 week. The factor structure and measurement invariance of the Unmind Index was evaluated using confirmatory factor analysis, convergent and discriminant validity by estimating correlations with existing measures, and reliability by examining internal consistency and test-retest intraclass correlations.

RESULTS

Studies 1A and 1B yielded a 26-item measure with 7 subscales: Calmness, Connection, Coping, Happiness, Health, Fulfilment, and Sleep. Study 2 showed that the Unmind Index is fitted well by a second-order factor structure, where the 7 subscales all load onto an overall MHWB factor, and established measurement invariance by age and gender. Subscale and total scores correlate well with existing mental health measures and generally diverge from personality measures. Reliability was good or excellent across all subscales.

CONCLUSIONS

The Unmind Index is a robust measure of MHWB that can help to identify target areas for intervention in nonclinical users of a mental health app. We argue that there is value in measuring mental ill health and mental well-being together, rather than treating them as separate constructs.

The Importance of Context: An ESM Study in Forensic Psychiatry

Experience Sampling Method (ESM) is a structured diary technique assessing variations in thoughts, mood, and psychiatric symptoms in everyday life. Research has provided ample evidence for the efficacy of the use of ESM in general psychiatry but its use in forensic psychiatry has been limited. Twenty forensic psychiatric patients participated. The PsyMate™ Device emitted a signal 10 times a day on six consecutive days, at unpredictable moments. After each "beep," the patients completed ESM forms assessing current context, thoughts, positive and negative affect, and psychotic experiences. Stress was measured using the average scores of the stress related items. Compliance rate was high (85% beeps responded). Activity stress was related to more negative affect, lower positive affect, and more psychotic symptoms. This finding was restricted to moments when a team member was present; not when patients were alone or with other patients. ESM can be useful in forensic psychiatry and give insights into the relationships between symptoms and mood in different contexts. In this study activity-related stress was contextualized. These findings can be used to personalize interventions.

Using network models in person-centered care in psychiatry: How perspectivism could help to draw boundaries

In this paper, we explore the conceptual problems that arise when using network analysis in person-centered care (PCC) in psychiatry. Personalized network models are potentially helpful tools for PCC, but we argue that using them in psychiatric practice raises boundary problems, i.e., problems in demarcating what should and should not be included in the model, which may limit their ability to provide clinically-relevant knowledge. Models can have explanatory and representational boundaries, among others. We argue that perspectival reasoning can make more explicit what questions personalized network models can address in PCC, given their boundaries.

A Review of Explicit and Implicit Assumptions When Providing Personalized Feedback Based on Self-Report EMA Data

Ecological Momentary Assessment (EMA) in which participants report on their moment-to-moment experiences in their natural environment, is a hot topic. An emerging field in clinical psychology based on either EMA, or what we term Ecological Retrospective Assessment (ERA) as it requires retrospectivity, is the field of personalized feedback. In this field, EMA/ERA-data-driven summaries are presented to participants with the goal of promoting their insight in their experiences. Underlying this procedure are some fundamental assumptions about (i) the relation between true moment-to-moment experiences and retrospective evaluations of those experiences, (ii) the translation of these experiences and evaluations to different types of data, (iii) the comparison of these different types of data, and (iv) the impact of a summary of moment-to-moment experiences on retrospective evaluations of those experiences. We argue that these assumptions deserve further exploration, in order to create a strong evidence-based foundation for the personalized feedback procedure.

Effects of a Novel, Transdiagnostic, Hybrid Ecological Momentary Intervention for Improving Resilience in Youth (EMIcompass): Protocol for an Exploratory Randomized Controlled Trial

BACKGROUND

Most mental disorders first emerge in youth and, in their early stages, surface as subthreshold expressions of symptoms comprising a transdiagnostic phenotype of psychosis, mania, depression, and anxiety. Elevated stress reactivity is one of the most widely studied mechanisms underlying psychotic and affective mental health problems. Thus, targeting stress reactivity in youth is a promising indicated and translational preventive strategy for adverse mental health outcomes that could develop later in life and for improving resilience. Compassion-focused interventions offer a wide range of innovative therapeutic techniques that are particularly amenable to being implemented as ecological momentary interventions (EMIs), a specific type of mobile health intervention, to enable youth to access interventions in a given moment and context in daily life. This approach may bridge the current gap in youth mental health care.

OBJECTIVE

This study aims to investigate the clinical feasibility, candidate underlying mechanisms, and initial signals of the efficacy of a novel, transdiagnostic, hybrid EMI for improving resilience to stress in youth-EMIcompass.

METHODS

In an exploratory randomized controlled trial, youth aged between 14 and 25 years with current distress, a broad Clinical High At-Risk Mental State, or the first episode of a severe mental disorder will be randomly allocated to the EMIcompass intervention (ie, EMI plus face-to-face training sessions) in addition to treatment as usual or a control condition of treatment as usual only. Primary (stress reactivity) and secondary candidate mechanisms (resilience, interpersonal sensitivity, threat anticipation, negative affective appraisals, and momentary physiological markers of stress reactivity), as well as primary (psychological distress) and secondary outcomes (primary psychiatric symptoms and general psychopathology), will be assessed at baseline, postintervention, and at the 4-week follow-up.

RESULTS

The first enrollment was in August 2019, and as of May 2021, enrollment and randomization was completed (N=92). We expect data collection to be completed by August 2021.

CONCLUSIONS

This study is the first to establish feasibility, evidence on underlying mechanisms, and preliminary signals of the efficacy of a compassion-focused EMI in youth. If successful, a confirmatory randomized controlled trial will be warranted. Overall, our approach has the potential to significantly advance preventive interventions in youth mental health provision.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00017265; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00017265.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/27462.

Psychopathological networks: Theory, methods and practice

In recent years, network approaches to psychopathology have sparked much debate and have had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there are many important challenges in moving from theory to empirical research and clinical practice and vice versa. Therefore, in this article, we bring together different points of view on psychological networks by methodologists and clinicians to give a critical overview on these challenges, and to present an agenda for addressing these challenges. In contrast to previous reviews, we especially focus on methodological issues related to temporal networks. This includes topics such as selecting and assessing the quality of the nodes in the network, distinguishing between- and within-person effects in networks, relating items that are measured at different time scales, and dealing with changes in network structures. These issues are not only important for researchers using network models on empirical data, but also for clinicians, who are increasingly likely to encounter (person-specific) networks in the consulting room.

Personalizing Psychological Care for Chronic Cancer-Related Fatigue: A Case Study on Symptom Dynamics

Approximately 25% of cancer patients suffer from chronic cancer-related fatigue (CCRF), which is a complex, multifactorial condition. While there are evidence-based interventions, it remains unclear what treatment works best for the individual patient. Psychological network models can offer a schematic representation of interrelations among fatigue and protective and perpetuating factors for the individual patient. We explored whether feedback based on these individual fatigue networks can help personalize psychological care for CCRF. A 34-year old woman with CCRF was referred to our mental healthcare institute for psycho-oncology. During the waitlist period, she filled out an experience sampling app for 101 days, including five daily assessments of fatigue, pain, mood, activity and fatigue coping. The interplay between items was visualized in network graphs at the moment-level and day-level, which were discussed with the patient. For example, acceptance of fatigue in the past three hours was associated with less hopelessness and less fatigue in the following moment. At the day-level, acceptance was also being associated with less fatigue, less hopelessness, a better mood, and more motivation to do things. The patient recognized these patterns and explained how unexpected waves of fatigue can make her feel hopeless. This started a dialogue on how cultivating acceptance could potentially help her handle the fatigue. The patient would discuss this with her therapist. Feedback based on individual fatigue networks can provide direct insight into how one copes with CCRF and subsequently offer directions for treatment. Further research is needed in order to implement this in clinical practice.

Ecological Momentary Assessment Using Smartphones in Patients With Depression: Feasibility Study

Background

Ecological momentary assessment (EMA) is a promising tool in the management of psychiatric disorders and particularly depression. It allows for a real-time evaluation of symptoms and an earlier detection of relapse or treatment efficacy. The generalization of the smartphone in the modern world offers a new, large-scale support for EMA.

Objective

The main objective of this study was twofold: (1) to assess patients’ compliance with an EMA smartphone app defined by the number of EMAs completed, and (2) to estimate the external validity of the EMA using a correlation between self-esteem/guilt/mood variables and Hamilton Depression Rating Scale (HDRS) score.

Methods

Eleven patients at the Pitié-Salpêtrière Hospital, Paris, France, were monitored for 28 days by means of a smartphone app. Every patient enrolled in the study had two types of assessment: (1) three outpatient consultations with a psychiatrist at three different time points (days 1, 15, and 28), and (2) real-time data collection using an EMA smartphone app with a single, fixed notification per day at 3 pm for 28 days. The results of the real-time data collected were reviewed during the three outpatient consultations by a psychiatrist using a dashboard that aggregated all of the patients’ data into a user-friendly format.

Results

Of the 11 patients in the study, 6 patients attended the 3 outpatient consultations with the psychiatrist and completed the HDRS at each consultation. We found a positive correlation between the HDRS score and the variables of self-esteem, guilt, and mood (Spearman correlation coefficient 0.57). Seven patients completed the daily EMAs for 28 days or longer, with an average response rate to the EMAs of 62.5% (175/280). Furthermore, we observed a positive correlation between the number of responses to EMAs and the duration of follow-up (Spearman correlation coefficient 0.63).

Conclusions

This preliminary study with a prolonged follow-up demonstrates significant patient compliance with the smartphone app. In addition, the self-assessments performed by patients seemed faithful to the standardized measurements performed by the psychiatrist. The results also suggest that for some patients it is more convenient to use the smartphone app than to attend outpatient consultations.

Feasibility of ecological momentary assessment to study depressive symptoms among cancer caregivers

OBJECTIVE

Ecological momentary assessment (EMA) may help with the development of more targeted interventions for caregivers' depression, yet the use of this method has been limited among cancer caregivers. This study aimed to demonstrate the feasibility of EMA among cancer caregivers and the use of EMA data to understand affective correlates of caregiver depressive symptoms.

METHODS

Caregivers (N = 25) completed a depressive symptom assessment (Patient Health Questionnaire-8) and then received eight EMA survey prompts per day for 7 days. EMA surveys assessed affect on the orthogonal dimensions of valence and arousal. Participants completed feedback surveys regarding the EMA protocol at the conclusion of the week-long study.

RESULTS

Of 32 caregivers approached, 25 enrolled and participated (78%), which exceeded the a priori feasibility cutoff of 55%. The prompt completion rate (59%, or 762 of 1,286 issued) did not exceed the a priori cutoff of 65%, although completion was not related to caregivers' age, employment status, physical health quality of life, caregiving stress, or depressive symptoms or the patients' care needs (ps > 0.22). Caregivers' feedback about their study experience was generally positive. Mixed-effects location scale modeling showed caregivers' higher depressive symptoms were related to overall higher reported negative affect and lower positive affect, but not to affective variability.

CONCLUSIONS

Findings from this feasibility study refute potential concerns that an EMA design is too burdensome for distressed caregivers. Clinically, findings suggest the potential importance of not only strategies to reduce overall levels of negative affect, but also to increase opportunities for positive affect.

Recommendations for the use of long-term experience sampling in bipolar disorder care: a qualitative study of patient and clinician experiences

Background

Self-monitoring has been shown to improve the self-management and treatment of patients with bipolar disorder. However, current self-monitoring methods are limited to once-daily retrospectively assessed mood, which may not suit the rapid mood fluctuations in bipolar disorder. The experience sampling method (ESM), which assesses mood in real-time several times a day, may overcome these limitations. This study set out to assess the experiences of patients and clinicians with the addition of ESM monitoring, real-time alerts, and personalized feedback to clinical care. Participants were twenty patients with bipolar disorder type I/II and their clinicians. For four months, patients completed five ESM assessments per day on mood, symptoms, and activities. Weekly symptom questionnaires alerted patients and clinicians to potential episodes. After the monitoring, a personalized feedback report based on the patient’s data was discussed between patient and clinician. Three months later, patient and clinician were both interviewed.

Results

Thematic analysis of the transcripts resulted in four themes: perceived effects of the monitoring, alerts, and feedback, and recommendations for implementation of ESM. ESM was perceived as helping patients to cope better with their disorder by increasing awareness, offering new insights, and encouraging life style adjustments. ESM was further believed to facilitate communication between patient and clinician and to lead to new treatment directions. However, high assessment burden and pre-occupation with negative mood and having a disorder were also described. Patients and clinicians advocated for increased personalization and embedding of ESM in care.

Conclusions

This study demonstrates that long-term ESM monitoring, alerts, and personalized feedback are perceived as beneficial to the treatment and self-management of patients with bipolar disorder. Future research should further test the clinical utility of ESM. Clinically relevant feedback and technology need to be developed to enable personalized integration of ESM in clinical care.

ESMvis: a tool for visualizing individual Experience Sampling Method (ESM) data

Purpose

The experience sampling method (ESM) is used for intensive longitudinal time-series data collection during normal daily life. ESM data give information on momentary affect, activities and (social) context of, for example, patients suffering from mental disorders, and allows for person-specific feedback reports. However, current personalized feedback reports only display a selection of measured variables, and typically involve only summary statistics, thus not reflecting the dynamic fluctuations in affect and its influencing factors. To address this shortcoming, we developed a tool for dynamically visualizing ESM data.

Methods

We introduce a new framework, ESMvis, for giving descriptive feedback, focusing on direct visualization of the dynamic nature of raw data. In this ESM feedback approach, raw ESM data are visualized using R software. We applied ESMvis to data collected for over 52 weeks on a patient diagnosed with an obsessive–compulsive disorder with comorbid depression.

Results

We provided personalized feedback, in which both the overall trajectory and specific time moments were captured in a movie format. Two relapses during the study period could be visually determined, and subsequently confirmed by the therapist. The therapist and patient evaluated ESMvis as an insightful add-on tool to care-as-usual.

Conclusion

ESMvis is a showcase on providing personalized feedback by dynamic visualization of ESM time-series data. Our tool is freely available and adjustable, making it widely applicable. In addition to potential applications in clinical practice, ESMvis can work as an exploratory tool that can lead to new hypotheses and inform more complex statistical techniques.

Electronic supplementary material

The online version of this article (10.1007/s11136-020-02701-4) contains supplementary material, which is available to authorized users.

Psychometric Properties of the Korean Version of the PsyMate Scale Using a Smartphone App: Ecological Momentary Assessment Study

BACKGROUND

Ecological momentary assessment (EMA) is a method for capturing the changes in the variables in daily life with increased accuracy and decreased recall bias. The PsyMate scale assesses momentary moods in daily life and can be used in various settings.

OBJECTIVE

The aim of this study was to develop a Korean version of the PsyMate (K-PsyMate) scale and evaluate its psychometric properties by using the EMA method in patients with moyamoya disease (MMD) in South Korea.

METHODS

Patients with MMD aged over 18 years were recruited from July 2018 to January 2019 at the inpatient and outpatient departments of a university hospital in South Korea. The K-PsyMate scale comprising 13 items was developed following a translation/back translation approach of the English version and loaded onto a mobile app. Participants were instructed to enter their moods 4 times a day for 7 consecutive days. Content validity index, factor analysis, and Pearson's correlation were performed for validity analysis. For reliability, intraclass correlation coefficients between the first and last measurements were estimated by mean rating, absolute agreement, and a 2-way mixed-effects model. Usability was analyzed through a descriptive analysis, 2-tailed t test, and analysis of variance, and the results were confirmed by Mann-Whitney U test and the Kruskal-Wallis test, as the dependent variable was not normally distributed.

RESULTS

In total, 1929 assessments from 93 patients were analyzed. The mean age of the participants was 40.59 (SD 10.06) years, and 66 (71%) of the 93 participants were women. Content validity was excellent as content validity index was 0.99, and 2 factors, negative affect and positive affect, were derived by an exploratory factor analysis. The correlations between the subdomains of the K-PsyMate scale and Hospital Anxiety and Depression Scale were significant (P<.001). The agreement between the first and last measurements was poor to moderate according to the obtained intraclass correlation coefficient values. Usability was evaluated by 67 (72%) out of the 93 participants. The participants rated the accuracy of assessing their momentary moods on the app at 4.13 (SD 0.97), easiness in understanding questions, operating, and inputting answers at 4.12 (SD 0.88), and interruption by the survey alarms at 2.48 (SD 1.02) out of 5.

CONCLUSIONS

The K-PsyMate scale has good validity but poor to moderate agreement, which reflects the characteristics of the EMA data collected in real and natural living environments without control. The findings of our study show that the K-PsyMate scale uploaded in a mobile app can be a valid and reliable tool for evaluating the momentary mood of patients with MMD because using a mobile app is convenient and patients are familiar with their own smartphones, which they use in their daily lives.

Mood and Stress Evaluation of Adult Patients With Moyamoya Disease in Korea: Ecological Momentary Assessment Method Using a Mobile Phone App

Background

Moyamoya disease (MMD) is a known progressive obstructive cerebrovascular disorder. Monitoring and managing mood and stress are critical for patients with MMD, as they affect clinical outcomes. The ecological momentary assessment (EMA) method is a longitudinal study design by which multiple variable assessments can be performed over time to detect momentary fluctuations and changes in psychological dimensions such as mood and stress over time.

Objective

This study aimed to identify predicting factors associated with momentary mood and stress at both the within-person and between-person levels and to examine individual fluctuation of mood over time in the short term using an EMA method combined with a mobile phone app.

Methods

Participants aged older than 18 years were recruited from a tertiary hospital in Seoul, Korea, between July 2018 and January 2019. The PsyMate scale for negative affect (NA) and positive affect (PA) and the Trier Inventory for Chronic Stress Scale were uploaded on patient mobile phones. Using a mobile app, data were collected four times a day for 7 days. Pearson correlations and mixed modeling were used to predict relationships between repeatedly measured variables at both the between-person and within-person levels.

Results

The mean age of the 93 participants was 40.59 (SD 10.06) years, 66 (71%) were female, and 71 (76%) were married. Participants provided 1929 responses out of a possible 2604 responses (1929/2604, 74.08%). The mean momentary NA and PA values were 2.15 (SD 1.12) and 4.70 (SD 1.31) out of 7, respectively. The momentary stress value was 2.03 (SD 0.98) out of 5. Momentary NA, PA, and stress were correlated (P<.001) and varied over time in relation to momentary variables. Common momentary variables associated with momentary mood and stress at both the within-person (level 1) and between-person (level 2) levels were identified. Momentary NA increased when being alone and being at the hospital at both levels, whereas momentary PA increased when eating or drinking, resting, being at a café, restaurant or a public place but decreased when being alone at both levels. Momentary stress increased when being at the office, at a public place, or as the time of the day went by but decreased when resting or during the weekend. Different factors affecting mood and stress at different levels were identified. Fluctuations in individual momentary mood over time at the within-person level were captured.

Conclusions

The EMA method using a mobile phone app demonstrated its ability to capture changes in mood and stress in various environmental contexts in patients with MMD. The results could provide baseline information for developing interventions to manage negative mood and stress of patients with MMD based on the identified predictors affecting mood and stress at two different levels.

Personal information and public health: Design tensions in sharing and monitoring wellbeing in pregnancy

Mobile technologies are valuable tools for the self-report of mental health and wellbeing. These systems pose many unique design challenges which have received considerable attention within HCI, including the engagement of users. However, less attention has been paid to the use of personal devices in public health. Integrating self-reported data within the context of clinical care suggests the need to design interfaces to support data management, sense-making, risk-assessment, feedback and patient-provider relationships. This paper reports on a qualitative design study for the clinical interface of a mobile application for the self-report of psychological wellbeing and depression during pregnancy. We examine the design tensions which arise in managing the expectations and informational needs of pregnant women, midwives, clinical psychologists, GPs and other health professionals with respect to a broad spectrum of wellbeing. We discuss strategies for managing these tensions in the design of technologies required to balance personal information with public health.

Insights of Patients and Clinicians on the Promise of the Experience Sampling Method for Psychiatric Care

OBJECTIVE

This qualitative study aimed to map the relevance of the experience sampling method (ESM) for psychiatric practice and identify barriers and facilitators for implementation, as perceived by patients and clinicians.

METHODS

Participants were 22 patients with various diagnoses and 21 clinicians (e.g., psychiatrists, psychologists) who participated in interviews or focus groups. Using Atlas.TI, the authors conducted qualitative thematic analysis to analyze the transcripts, resulting in four themes: applications, advantages, undesirable effects, and requirements for implementation of ESM in care.

RESULTS

Clinicians and patients believed ESM could be relevant in every phase of care to increase patients' awareness, insight, and self-management; personalize interventions; and alert patients to rising symptoms. Further, ESM was expected to improve the patient-clinician relationship; lead to objective, personalized, reliable and visual data; and increase efficiency of care. However, participants warned against high assessment burden and potential symptom worsening.

CONCLUSIONS

This study provides first evidence that the potential of ESM is recognized by both patients and clinicians. Key recommendations for optimal implementation of ESM in psychiatric care include flexible application of ESM, collaboration between patient and clinician, regular evaluation, awareness of negative reactivity, availability to patients with different psychiatric syndromes, and implementation by an interdisciplinary team of patients, clinicians, researchers, and information technology specialists.

Validation of an mHealth App for Depression Screening and Monitoring (Psychologist in a Pocket): Correlational Study and Concurrence Analysis

Background

Mobile health (mHealth) is a fast-growing professional sector. As of 2016, there were more than 259,000 mHealth apps available internationally. Although mHealth apps are growing in acceptance, relatively little attention and limited efforts have been invested to establish their scientific integrity through statistical validation. This paper presents the external validation of Psychologist in a Pocket (PiaP), an Android-based mental mHealth app which supports traditional approaches in depression screening and monitoring through the analysis of electronic text inputs in communication apps.

Objective

The main objectives of the study were (1) to externally validate the construct of the depression lexicon of PiaP with standardized psychological paper-and-pencil tools and (2) to determine the comparability of PiaP, a new depression measure, with a psychological gold standard in identifying depression.

Methods

College participants downloaded PiaP for a 2-week administration. Afterward, they were asked to complete 4 psychological depression instruments. Furthermore, 1-week and 2-week PiaP total scores (PTS) were correlated with (1) Beck Depression Index (BDI)-II and Center for Epidemiological Studies–Depression (CES-D) Scale for congruent construct validation, (2) Affect Balance Scale (ABS)–Negative Affect for convergent construct validation, and (3) Satisfaction With Life Scale (SWLS) and ABS–Positive Affect for divergent construct validation. In addition, concordance analysis between PiaP and BDI-II was performed.

Results

On the basis of the Pearson product-moment correlation, significant positive correlations exist between (1) 1-week PTS and CES-D Scale, (2) 2-week PTS and BDI-II, and (3) PiaP 2-week PTS and SWLS. Concordance analysis (Bland-Altman plot and analysis) suggested that PiaP’s approach to depression screening is comparable with the gold standard (BDI-II).

Conclusions

The evaluation of mental health has historically relied on subjective measurements. With the integration of novel approaches using mobile technology (and, by extension, mHealth apps) in mental health care, the validation process becomes more compelling to ensure their accuracy and credibility. This study suggests that PiaP’s approach to depression screening by analyzing electronic data is comparable with traditional and well-established depression instruments and can be used to augment the process of measuring depression symptoms.

Response Time as an Implicit Self-Schema Indicator for Depression Among Undergraduate Students: Preliminary Findings From a Mobile App-Based Depression Assessment

Background

Response times to depressive symptom items in a mobile-based depression screening instrument has potential as an implicit self-schema indicator for depression but has yet to be determined; the instrument was designed to readily record depressive symptoms experienced on a daily basis. In this study, the well-validated Korean version of the Center for Epidemiologic Studies Depression Scale-Revised (K-CESD-R) was adopted.

Objective

The purpose of this study was to investigate the relationship between depression severity (ie, explicit measure: total K-CESD-R Mobile scores) and the latent trait of interest in schematic self-referent processing of depressive symptom items (ie, implicit measure: response times to items in the K-CESD-R Mobile scale). The purpose was to investigate this relationship among undergraduate students who had never been diagnosed with, but were at risk for, major depressive disorder (MDD) or comorbid MDD with other neurological or psychiatric disorders.

Methods

A total of 70 participants—36 males (51%) and 34 females (49%)—aged 19-29 years (mean 22.66, SD 2.11), were asked to complete both mobile and standard K-CESD-R assessments via their own mobile phones. The mobile K-CESD-R sessions (binary scale: yes or no) were administered on a daily basis for 2 weeks. The standard K-CESD-R assessment (5-point scale) was administered on the final day of the 2-week study period; the assessment was delivered via text message, including a link to the survey, directly to participants’ mobile phones.

Results

A total of 5 participants were excluded from data analysis. The result of polynomial regression analysis showed that the relationship between total K-CESD-R Mobile scores and the reaction times to the depressive symptom items was better explained by a quadratic trend—F (2, 62)=21.16, P<.001, R²=.41—than by a linear trend—F (1, 63)=25.43, P<.001, R²=.29. It was further revealed that the K-CESD-R Mobile app had excellent internal consistency (Cronbach alpha=.94); at least moderate concurrent validity with other depression scales, such as the Korean version of the Quick Inventory for Depressive Symptomatology-Self Report (ρ=.38, P=.002) and the Patient Health Questionnaire-9 (ρ=.48, P<.001); a high adherence rate for all participants (65/70, 93%); and a high follow-up rate for 10 participants whose mobile or standard K-CESD-R score was 13 or greater (8/10, 80%).

Conclusions

As hypothesized, based on a self-schema model for depression that represented both item and person characteristics, the inverted U-shaped relationship between the explicit and implicit self-schema measures for depression showed the potential of an organizational breakdown; this also showed the potential for a subsequent return to efficient processing of schema-consistent information along a continuum, ranging from nondepression through mild depression to severe depression. Further, it is expected that the updated K-CESD-R Mobile app can play an important role in encouraging people at risk for depression to seek professional follow-up for mental health care.

Unraveling the Black Box: Exploring Usage Patterns of a Blended Treatment for Depression in a Multicenter Study

BACKGROUND

Blended treatments, combining digital components with face-to-face (FTF) therapy, are starting to find their way into mental health care. Knowledge on how blended treatments should be set up is, however, still limited. To further explore and optimize blended treatment protocols, it is important to obtain a full picture of what actually happens during treatments when applied in routine mental health care.

OBJECTIVE

The aims of this study were to gain insight into the usage of the different components of a blended cognitive behavioral therapy (bCBT) for depression and reflect on actual engagement as compared with intended application, compare bCBT usage between primary and specialized care, and explore different usage patterns.

METHODS

Data used were collected from participants of the European Comparative Effectiveness Research on Internet-Based Depression Treatment project, a European multisite randomized controlled trial comparing bCBT with regular care for depression. Patients were recruited in primary and specialized routine mental health care settings between February 2015 and December 2017. Analyses were performed on the group of participants allocated to the bCBT condition who made use of the Moodbuster platform and for whom data from all blended components were available (n=200). Included patients were from Germany, Poland, the Netherlands, and France; 64.5% (129/200) were female and the average age was 42 years (range 18-74 years).

RESULTS

Overall, there was a large variability in the usage of the blended treatment. A clear distinction between care settings was observed, with longer treatment duration and more FTF sessions in specialized care and a more active and intensive usage of the Web-based component by the patients in primary care. Of the patients who started the bCBT, 89.5% (179/200) also continued with this treatment format. Treatment preference, educational level, and the number of comorbid disorders were associated with bCBT engagement.

CONCLUSIONS

Blended treatments can be applied to a group of patients being treated for depression in routine mental health care. Rather than striving for an optimal blend, a more personalized blended care approach seems to be the most suitable. The next step is to gain more insight into the clinical and cost-effectiveness of blended treatments and to further facilitate uptake in routine mental health care.

Do daily dynamics in rumination and affect predict depressive symptoms and trait rumination? An experience sampling study

BACKGROUND AND OBJECTIVES

Rumination has been shown to prospectively predict the onset of depression. However, it is unclear how rumination and affect in daily life influence the development of depressive symptoms. The present study examined whether the structure of dynamics in rumination and affect could prospectively predict depressive symptoms and trait rumination in an undergraduate sample (n = 63).

METHODS

The main index used was entropy, which reflects the instability of a system's structure. Momentary rumination and affect were assessed eight times per day for a period of seven days. Additionally, depressive symptoms and trait rumination were measured at the beginning of the experiment and at six weeks follow-up.

RESULTS

The results showed that entropy significantly predicted trait rumination at follow-up (and depressive symptoms at trend level) while taking into account baseline depressive symptoms and trait rumination.

LIMITATIONS

The follow-up measurements conducted six weeks after the baseline were relatively short. Further research may test the predictive effect of the structure over a longer period and confirm its effect by using different indices that describe the structure.

CONCLUSIONS

These findings indicate that examining the structure of the dynamics in momentary rumination and affect holds promise for understanding the risk for depression.

Methodological Strategies for Ecological Momentary Assessment to Evaluate Mood and Stress in Adult Patients Using Mobile Phones: Systematic Review

Background

Ecological momentary assessment (EMA) has utility for measuring psychological properties in daily life. EMA has also allowed researchers to collect data on diverse experiences and symptoms from various subjects.

Objective

The aim of this study was to review methodological strategies and useful related information for EMA using mobile phones to capture changes of mood and stress in adult patients seeking health care.

Methods

We searched PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, the Cochrane Library, PsycINFO, and Web of Science. This review included studies published in peer-reviewed journals in English between January 2008 and November 2017 that used basic- or advanced-feature mobile phones to measure momentary mood or stress in adult patients seeking health care in outpatient departments. We excluded studies of smoking and substance addictions and studies of mental disorder patients who had been diagnosed by physicians.

Results

We reviewed 12 selected articles that used EMA via mobile phones to measure momentary mood and stress and other related variables from various patients with chronic fatigue syndrome, breast cancer, migraine, HIV, tinnitus, temporomandibular disorder, end-stage kidney disease, and traumatic brain injury. Most of the selected studies (11/12, 92%) used signal contingency and in 8 of the 12 studies (67%) alarms were sent at random or semirandom intervals to prompt the momentary measurement. Out of 12 studies, 7 (58%) used specific apps directly installed on mobile phones, 3 (25%) used mobile phones to link to Web-based survey programs, and 2 (17%) used an interactive voice-response system.

Conclusions

This study provides researchers with useful information regarding methodological details for utilizing EMA to measure mood and stress in adult patients. This review shows that EMA methods could be effective and reasonable for measuring momentary mood and stress, given that basic- and advanced-feature mobile phones are ubiquitous, familiar, and easy to approach. Therefore, researchers could adopt and utilize EMA methods using mobile phones to measure psychological health outcomes, such as mood and stress, in adult patients.

Improving Access to Trauma-Informed Adoption Services: Applying a Developmental Trauma Framework

Foster and adopted children often experience multiple traumatic and adverse experiences. A growing body of literature indicates the negative impact of trauma on developmental milestones and brain development, which supports the need to address complex trauma among this vulnerable population of foster and adopted youth. This paper presents an overview of the unique needs of children adopted from the foster care system from the perspective of adverse childhood experiences (ACEs), complex trauma, and developmental trauma disorder (DTD). There is an increasing number of evidence-based trauma-focused services and interventions for children and youth. However, many adoptive parents have limited trauma-informed training and limited access to trauma-informed and adoption-competent professionals, particularly long-term supports across developmental stages, making them ill-prepared to meet the needs of children in their care. This paper contributes to the understanding of how access to these trauma-focused services can be increased through new technologies, to better prepare and empower adoptive parents to deal effectively with difficult adoption issues when they arise and to improve outcomes for children and youth adopted from the public child welfare system. Several innovative approaches toward this end include harnessing technology to: (1) improve access to suitable adoption resources, (2) improve mechanisms to track critical events, behaviors, emotions, functional abilities, strengths, etc., in order to determine timely, on-demand contextual services, and (3) extend professional, supportive environments beyond the adoptive family context by proposing the use of technology to build interdisciplinary, virtual community partners.

An Experience Sampling Method Intervention for Dementia Caregivers: Results of a Randomized Controlled Trial

OBJECTIVE

Ecological momentary interventions integrated with real-life assessments using the experience sampling method (ESM) could be promising to effectively support dementia caregivers in daily life. This study reports on the effectiveness of the ESM-based intervention "Partner in Sight."

DESIGN, SETTING, PARTICIPANTS

A randomized controlled trial with 76 dementia caregivers was performed. Participants were randomly assigned to the intervention group ("Partner in Sight": ESM self-monitoring and personalized feedback), the pseudo-intervention group (ESM self-monitoring without feedback), or the control group (usual care).

MEASUREMENTS

Effects were evaluated pre- and postintervention and at 2-month follow-up. Primary outcomes were retrospective measures of caregiver sense of competence and mastery. Secondary outcomes were retrospective measures of depression, anxiety, and perceived stress. Complementary ESM measures of positive and negative affect were collected pre- and postintervention.

RESULTS

Both the experimental and pseudo-experimental groups showed an increase in retrospective sense of competence and a decrease in perceived stress at 2-month follow-up. At postintervention, the experimental group showed a decrease in momentary negative affect compared with the pseudo-experimental and control groups. No effects were found for retrospective mastery, depression, anxiety, and momentary positive affect.

CONCLUSIONS

ESM interventions could be an important asset for increasing caregiver resources and could help caregivers to better adapt and manage difficult situations and to protect against negative emotions.

A Mobile App for the Self-Report of Psychological Well-Being During Pregnancy (BrightSelf): Qualitative Design Study

BACKGROUND

Maternal mental health impacts both parental well-being and childhood development. In the United Kingdom, 15% of women are affected by depression during pregnancy or within 1 year of giving birth. Suicide is a leading cause of perinatal maternal mortality, and it is estimated that >50% of perinatal depression cases go undiagnosed. Mobile technologies are potentially valuable tools for the early recognition of depressive symptoms, but complex design challenges must be addressed to enable their use in public health screening.

OBJECTIVE

The aim of this study was to explore the issues and challenges surrounding the use of mobile phones for the self-report of psychological well-being during pregnancy.

METHODS

This paper presents design research carried out as part of the development of BrightSelf, a mobile app for the self-report of psychological well-being during pregnancy. Design sessions were carried out with 38 participants, including pregnant women, mothers, midwives, and other health professionals. Overall, 19 hours of audio were fully transcribed and used as the basis of thematic analysis.

RESULTS

The study highlighted anxieties concerning the pregnancy journey, challenges surrounding current approaches to the appraisal of well-being in perinatal care, and the midwife-patient relationship. Designers should consider the framing of perinatal mental health technologies, the experience of self-report, supporting self-awareness and disclosure, providing value to users through both self-report and supplementary features, and designing for longitudinal engagement.

CONCLUSIONS

This study highlights the needs, motivations, and anxieties of women with respect to technology use in pregnancy and implications for the design of mobile health technologies.

Predictive modeling in e-mental health: A common language framework

Recent developments in mobile technology, sensor devices, and artificial intelligence have created new opportunities for mental health care research. Enabled by large datasets collected in e-mental health research and practice, clinical researchers and members of the data mining community increasingly join forces to build predictive models for health monitoring, treatment selection, and treatment personalization. This paper aims to bridge the historical and conceptual gaps between the distant research domains involved in this new collaborative research by providing a conceptual model of common research goals. We first provide a brief overview of the data mining field and methods used for predictive modeling. Next, we propose to characterize predictive modeling research in mental health care on three dimensions: 1) time, relative to treatment (i.e., from screening to post-treatment relapse monitoring), 2) types of available data (e.g., questionnaire data, ecological momentary assessments, smartphone sensor data), and 3) type of clinical decision (i.e., whether data are used for screening purposes, treatment selection or treatment personalization). Building on these three dimensions, we introduce a framework that identifies four model types that can be used to classify existing and future research and applications. To illustrate this, we use the framework to classify and discuss published predictive modeling mental health research. Finally, in the discussion, we reflect on the next steps that are required to drive forward this promising new interdisciplinary field.

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 .

Demonstrating the reliability of transdiagnostic mHealth Routine Outcome Monitoring in mental health services using experience sampling technology

Background

Routine Outcome Monitoring (ROM) should provide a dynamic, within-treatment forward feedback loop to guide individual treatment decisions across diagnostic categories. It has been suggested that the Experience Sampling Method (ESM), capturing the film of daily life adaptive processes, offers a flexible, personalised and transdiagnostic feedback system for monitoring and adapting treatment strategies. This is the first study that uses an ESM application (the PsyMate™) as a routine mobile-ROM (mROM) tool in an ambulatory mental health setting.

Objective

To demonstrate adequate psychometric properties of the PsyMate™ app assessing both symptom severity levels as well as daily life functioning.

Method

In a transdiagnostic sample of 64 outpatients, an mROM protocol (ESM for 6 days, at 10 semi-random moments a day) and a standard ROM instrument (HADS) were administered at baseline and at three-month follow-up. We measured positive affect (PA), negative affect (NA), quality of sleep, positive social interaction, activity-related stress, tiredness, and feeling unwell.

Results

Subjects completed 53% of the measurements at baseline (N = 64) and 48% at follow-up (N = 29). Factor analysis and subsequent reliability analysis of PA and NA confirmed the two constructs. Significant and meaningful correlations were found between PA, NA and HADS scores (ranging from r = .4 to r = .7). Multilevel analyses yielded significant change scores for all measures.

Conclusion

The ESM-based, transdiagnostic mROM tool can be used reliably in clinical settings: it shows adequate psychometric properties, as well as concurrent validity and sensitivity to change over time with respect to relevant ROM constructs. Person-tailored items can be added. In addition, mROM offers added value over standard symptom-based ROM, as it provides information on adaptive functioning in the daily environment of patients.

Supportive Mental Health Self-Monitoring among Smartphone Users with Psychological Distress: Protocol for a Fully Mobile Randomized Controlled Trial

Mobile health (mHealth) could be widely used in the population to improve access to psychological treatment. In this paper, we describe the development of a mHealth intervention on the basis of supportive self-monitoring and describe the protocol for a randomized controlled trial to evaluate its effectiveness among smartphone users with psychological distress. Based on power analysis, a representative quota sample of N = 186 smartphone users will be recruited, with an over-sampling of persons with moderate to high distress. Over a 4-week period, the intervention will be compared to a self-monitoring without intervention group and a passive control group. Telephone interviews will be conducted at baseline, post-intervention (4 weeks), and 12-week follow-up to assess study outcomes. The primary outcome will be improvement of mental health. Secondary outcomes will include well-being, intentions toward help-seeking and help-seeking behavior, user activation, attitudes toward mental-health services, perceived stigmatization, smartphone app quality, user satisfaction, engagement, and adherence with the intervention. Additionally, data from the user's daily life as collected during self-monitoring will be used to investigate risk and protective factors of mental health in real-world settings. Therefore, this study will allow us to demonstrate the effectiveness of a smartphone application as a widely accessible and low-cost intervention to improve mental health on a population level. It also allows to identify new assessment approaches in the field of psychiatric epidemiology.

Using game authoring platforms to develop screen-based simulated functional assessments in persons with executive dysfunction following traumatic brain injury

The assessment of functional status is a critical component of clinical neuropsychological evaluations used for both diagnostic and therapeutic purposes in patients with cognitive brain disorders. There are, however, no widely adopted neuropsychological tests that are both ecologically valid and easily administered in daily clinical practice. This discrepancy is a roadblock to the widespread adoption of functional assessments. In this paper, we propose a novel approach using a serious game authoring platform (eAdventure) for creating screen-based simulated functional assessments. We created a naturalistic functional task that consisted of preparing a cup of tea (SBS-COT) and applied the assessment in a convenience sample of eight dyads of therapists/patients with mild executive dysfunction after traumatic brain injury. We had three main aims. First, we performed a comprehensive review of executive function assessment in activities of daily living. Second, we were interested in measuring the feasibility of this technology with respect to staffing, economic and technical requirements. Third, a serious game was administered to patients to study the feasibility of this technology in the clinical context (pre-screening test). In addition, quantitative (Technology Acceptance Model (TAM) questionnaires) and qualitative (semistructured interviews) evaluations were applied to obtain user input. Our results suggest that the staffing, economic and technical requirements of the SBS-COT are feasible. The outcomes of the pre-screening test provide evidence that this technology is useful in the functional assessment of patients with executive dysfunction. In relation to subjective data, the TAM questionnaire showed good user acceptability from a professional perspective. Interview analyses with professionals and patients showed positive experiences related to the use of the SBS-COT. Our work indicates that the use of these types of authoring platforms could have positive long-term implications for neuropsychological research, opening the door to more reproducible, cooperative and efficient research by allowing the facilitated production, reuse and sharing of neuropsychological assessment tools.

Dealing with Daily Challenges in Dementia (Deal-id Study): An Experience Sampling Study to Assess Caregivers' Sense of Competence and Experienced Positive Affect in Daily Life

OBJECTIVE

Positive emotions and feelings of competence seem to play an important role in the well-being of caregivers of people with dementia. Both are likely to fluctuate constantly throughout the caretaking process. Unlike standard retrospective methods, momentary assessments in daily life can provide insight into these moment-to-moment fluctuations. Therefore, in this study both retrospective and momentary assessments were used to examine the relationship between caregivers' sense of competence and their experienced positive affect (PA) in daily life.

METHODS

Thirty Dutch caregivers provided momentary data on PA and daily sense of competence ratings for 6 consecutive days using the experience sampling methodology. Additionally, they reported retrospectively on their sense of competence with a traditional questionnaire.

RESULTS

A positive association was found between retrospective and daily measured sense of competence. Caregivers reported corresponding levels of sense of competence on both measures. Both daily and retrospective sense of competence were positively associated with the experienced levels of PA. However, daily sense of competence appeared to be the strongest predictor. Regarding the variability in PA, only daily sense of competence showed a significant association, with a higher daily sense of competence predicting a more stable PA pattern.

CONCLUSION

This study provides support for redirecting caregiver support interventions toward enhancement of positive rather than negative experiences and focusing more on caregivers' momentary emotional experiences. Momentary assessments are a valuable addition to standard retrospective measures and provide a more comprehensive and dynamic view of caregiver functioning.

The fading affect bias shows positive outcomes at the general but not the individual level of analysis in the context of social media

Unpleasant affect fades faster than pleasant affect (e.g., Walker, Vogl, & Thompson, 1997); this effect is referred to as the Fading Affect Bias (FAB; Walker, Skowronski, Gibbons, Vogl, & Thompson, 2003a). Research shows that the FAB is consistently related to positive/healthy outcomes at a general but not at a specific level of analysis based on event types and individual differences (e.g., Gibbons et al., 2013). Based on the positive outcomes for FAB and negative outcomes for social media (Bolton et al., 2013; Huang, 2010), the current study examined FAB in the context of social media events along with related individual differences. General positive outcomes were shown in the form of robust FAB effects across social media and non-social media events, a larger FAB for non-social media events than for social media events, negative correlations of FAB with depression, anxiety, and stress as well as a positive correlation of FAB with self-esteem. However, the lack of a negative correlation between FAB and anxiety for social media events in a 3-way interaction did not show positive outcomes at a specific level of analysis. Rehearsal ratings mediated the 3-way interaction. Implications are discussed.

Use of Computer and Mobile Technologies in the Treatment of Depression

Major depression (MDD) is a common and disabling disorder. Research has shown that most people with MDD receive either no treatment or inadequate treatment. Computer and mobile technologies may offer solutions for the delivery of therapies to untreated or inadequately treated individuals with MDD. The authors review currently available technologies and research aimed at relieving symptoms of MDD. These technologies include computer-assisted cognitive-behavior therapy (CCBT), web-based self-help, Internet self-help support groups, mobile psychotherapeutic interventions (i.e., mobile applications or apps), technology enhanced exercise, and biosensing technology.

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.

Exploring the feasibility and usability of the experience sampling method to examine the daily lives of patients with acquired brain injury

The experience sampling method (ESM) is a structured diary method with high ecological validity, in that it accurately captures the everyday context of individuals through repeated measurements in naturalistic environments. Our main objective was to investigate the feasibility of using ESM in individuals with acquired brain injury (ABI). A second goal was to explore the usability of ESM data on a clinical level, by illustrating the interactions between person, environment, and affect. The PsyMate device provided ABI patients (N = 17) with ten signals (beeps) per day during six consecutive days. Each beep was followed by a digital questionnaire assessing mood, location, activities, social context, and physical well-being. Results demonstrated high feasibility with a 71% response rate and a 99% completion rate of the questionnaires. There were no dropouts and the method was experienced as user-friendly. Time-lagged multilevel analysis showed that higher levels of physical activity and fatigue predicted higher levels of negative affect at the same point in time, but not at later time points. This study illustrates the potential of ESM to identify complex person-environment dynamics after ABI, while generating understandable and easy to use graphical feedback.

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

An Exploratory Randomized Controlled Trial of Personalized Lifestyle Advice and Tandem Skydives as a Means to Reduce Anhedonia

Anhedonia is a major public health concern and has proven particularly difficult to counteract. It has been hypothesized that anhedonia can be deterred by engagement in rewarding social and physical events. The aims of the present study were to examine (1) the effects of personalized lifestyle advice based on observed individual patterns of lifestyle factors and experienced pleasure in anhedonic young adults; and (2) whether a tandem skydive can enhance the motivation to carry out the recommended lifestyle changes. Participants (N = 69; M_age = 21.5, SD = 2.0; 79.7% female) were selected through an online screening survey among young adults. Inclusion criteria were persistent anhedonia and willingness to perform a tandem skydive. Participants filled out questionnaires on their smartphones for 2 consecutive months (3 times per day). After the first month, they were randomly assigned to one of three groups: (1) no intervention, (2) lifestyle advice, and (3) lifestyle advice and tandem skydive. The momentary questionnaire data were analyzed using interrupted time series analyses (ITSA) in a multilevel model and monthly pleasure and depression questionnaires by repeated measures ANOVA. No group differences were found in monthly depression and pleasure scores, but the momentary data showed higher positive affect (PA) and pleasure ratings in the month following the intervention in the two intervention groups than in the control group. The tandem skydive did not have any effects above the effects of the lifestyle advice. Our results indicate that providing personalized lifestyle advice to anhedonic young adults can be an effective way to increase PA and pleasure.

Reactivity to smartphone-based ecological momentary assessment of depressive symptoms (MoodMonitor): protocol of a randomised controlled trial

BACKGROUND

Ecological momentary assessment (EMA) of mental health symptoms may influence the symptoms that it measures, i.e. assessment reactivity. In the field of depression, EMA reactivity has received little attention. We aim to investigate whether EMA of depressive symptoms induces assessment reactivity. Reactivity will be operationalised as an effect of EMA on depressive symptoms measured by a retrospective questionnaire, and, secondly, as a change in response rate and variance of the EMA ratings.

METHODS

This study is a 12-week randomised controlled trial comprising three groups: group 1 carries out EMA of mood and completes a retrospective questionnaire, group 2 carries out EMA of how energetic they feel and completes a retrospective questionnaire, group 3 is the control group, which completes only the retrospective questionnaire. The retrospective questionnaire (Centre for Epidemiologic Studies Depression scale; CES-D) assesses depressive symptoms and is administered at baseline, 6 weeks after baseline and 12 weeks after baseline. We aim to recruit 160 participants who experience mild to moderate depressive symptoms, defined as a Patient Health Questionnaire (PHQ-9) score of 5 to 15. This study is powered to detect a small between-groups effect, where no clinically relevant effect is defined as the effect size margin -0.25< d <0.25.

DISCUSSION

To our knowledge, this is the first study to investigate whether self-rated EMA of depressive symptoms could induce assessment reactivity among mildly depressed individuals.

TRIAL REGISTRATION

Netherlands Trial Register NTR5803. Registered 12 April 2016. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5803 .

Piloting the use of experience sampling method to investigate the everyday social experiences of children with Asperger syndrome/high functioning autism

OBJECTIVE

This pilot study explored the nature and quality of social experiences of children with Asperger Syndrome/High Functioning Autism (AS/HFA) through experience sampling method (ESM) while participating in everyday activities.

METHODS

ESM was used to identify the contexts and content of daily life experiences. Six children with AS/HFA (aged 8-12) wore an iPod Touch on seven consecutive days, while being signalled to complete a short survey.

RESULTS

Participants were in the company of others 88.3% of their waking time, spent 69.0% of their time with family and 3.8% with friends, but only conversed with others 26.8% of the time. Participants had more positive experiences and emotions when they were with friends compared with other company. Participating in leisure activities was associated with enjoyment, interest in the occasion, and having positive emotions.

CONCLUSIONS

ESM was found to be helpful in identifying the nature and quality of social experiences of children with AS/HFA from their perspective.

An n=1 Clinical Network Analysis of Symptoms and Treatment in Psychosis

INTRODUCTION

Dynamic relationships between the symptoms of psychosis can be shown in individual networks of psychopathology. In a single patient, data collected with the Experience Sampling Method (ESM-a method to construct intensive time series of experience and context) can be used to study lagged associations between symptoms in relation to illness severity and pharmacological treatment.

METHOD

The patient completed, over the course of 1 year, for 4 days per week, 10 daily assessments scheduled randomly between 10 minutes and 3 hours apart. Five a priori selected symptoms were analysed: 'hearing voices', 'down', 'relaxed', 'paranoia' and 'loss of control'. Regression analysis was performed including current level of one symptom as the dependent variable and all symptoms at the previous assessment (lag) as the independent variables. Resulting regression coefficients were printed in graphs representing a network of symptoms. Network graphs were generated for different levels of severity: stable, impending relapse and full relapse.

RESULTS

ESM data showed that symptoms varied intensely from moment to moment. Network representations showed meaningful relations between symptoms, e.g. 'down' and 'paranoia' fuelling each other, and 'paranoia' negatively impacting 'relaxed'. During relapse, symptom levels as well as the level of clustering between symptoms markedly increased, indicating qualitative changes in the network. While 'hearing voices' was the most prominent symptom subjectively, the data suggested that a strategic focus on 'paranoia', as the most central symptom, had the potential to bring about changes affecting the whole network.

CONCLUSION

Construction of intensive ESM time series in a single patient is feasible and informative, particularly if represented as a network, showing both quantitative and qualitative changes as a function of relapse.