Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic Review

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence

BACKGROUND

This PRISMA systematic literature review examined the use of digital data collection methods (including ecological momentary assessment [EMA], experience sampling method [ESM], digital biomarkers, passive sensing, mobile sensing, ambulatory assessment, and time-series analysis), emphasizing on digital phenotyping (DP) to study depression. DP is defined as the use of digital data to profile health information objectively.

AIMS

Four distinct yet interrelated goals underpin this study: (a) to identify empirical research examining the use of DP to study depression; (b) to describe the different methods and technology employed; (c) to integrate the evidence regarding the efficacy of digital data in the examination, diagnosis, and monitoring of depression and (d) to clarify DP definitions and digital mental health records terminology.

RESULTS

Overall, 118 studies were assessed as eligible. Considering the terms employed, "EMA", "ESM", and "DP" were the most predominant. A variety of DP data sources were reported, including voice, language, keyboard typing kinematics, mobile phone calls and texts, geocoded activity, actigraphy sensor-related recordings (i.e., steps, sleep, circadian rhythm), and self-reported apps' information. Reviewed studies employed subjectively and objectively recorded digital data in combination with interviews and psychometric scales.

CONCLUSIONS

Findings suggest links between a person's digital records and depression. Future research recommendations include (a) deriving consensus regarding the DP definition and (b) expanding the literature to consider a person's broader contextual and developmental circumstances in relation to their digital data/records.

Don't Miss the Moment: A Systematic Review of Ecological Momentary Assessment in Suicide Research

Suicide and suicide-related behaviors are prevalent yet notoriously difficult to predict. Specifically, short-term predictors and correlates of suicide risk remain largely unknown. Ecological momentary assessment (EMA) may be used to assess how suicidal thoughts and behaviors (STBs) unfold in real-world contexts. We conducted a systematic literature review of EMA studies in suicide research to assess (1) how EMA has been utilized in the study of STBs (i.e., methodology, findings), and (2) the feasibility, validity and safety of EMA in the study of STBs. We identified 45 articles, detailing 23 studies. Studies mainly focused on examining how known longitudinal predictors of suicidal ideation perform within shorter (hourly, daily) time frames. Recent studies have explored the prospects of digital phenotyping of individuals with suicidal ideation. The results indicate that suicidal ideation fluctuates substantially over time (hours, days), and that individuals with higher mean ideation also have more fluctuations. Higher suicidal ideation instability may represent a phenotypic indicator for increased suicide risk. Few studies succeeded in establishing prospective predictors of suicidal ideation beyond prior ideation itself. Some studies show negative affect, hopelessness and burdensomeness to predict increased ideation within-day, and sleep characteristics to impact next-day ideation. The feasibility of EMA is encouraging: agreement to participate in EMA research was moderate to high (median = 77%), and compliance rates similar to those in other clinical samples (median response rate = 70%). More individuals reported suicidal ideation through EMA than traditional (retrospective) self-report measures. Regarding safety, no evidence was found of systematic reactivity of mood or suicidal ideation to repeated assessments of STBs. In conclusion, suicidal ideation can fluctuate substantially over short periods of time, and EMA is a suitable method for capturing these fluctuations. Some specific predictors of subsequent ideation have been identified, but these findings warrant further replication. While repeated EMA assessments do not appear to result in systematic reactivity in STBs, participant burden and safety remains a consideration when studying high-risk populations. Considerations for designing and reporting on EMA studies in suicide research are discussed.

Associations of three major physiological stress systems with suicidal ideation and suicide attempts in patients with a depressive and/or anxiety disorder

BACKGROUND

People with depressive and/or anxiety disorders are at increased risk of suicidal ideation and suicide attempts, but biological correlates signaling such risk remain unclear. Independent and cumulative dysregulations in physiological stress systems, in particular the hypothalamic-pituitaryadrenal axis (HPA-axis), immune-inflammatory system, and autonomous nervous system (ANS), may contribute to this risk. However, findings have either been heterogeneous or absent thus far.

METHODS

Associations between individual markers and cumulative indices of the HPA-axis (cortisol awakening response and evening cortisol), immune-inflammatory system (C-reactive protein, interleukin-6 (IL-6), and tumor necrosis factor-α), and the ANS (heart rate, respiratory sinus arrhythmia, and pre-ejection period) and the outcomes no suicide ideation with suicide attempt (SI-SA+), suicide ideation without suicide attempt (SI+SA-) and suicide ideation with suicide attempt (SI+SA+) were investigated in 1749 persons with depressive and/or anxiety disorders from the Netherlands Study of Depression and Anxiety (NESDA).

RESULTS

High levels of CRP and IL-6 were associated with SI-SA+ and SI+SA+ respectively when compared to non-suicidal patients after adjusting for confounders and multiple testing. Also, cumulative immune-inflammatory dysregulations were positively associated with SI+SA+, suggesting a dose-response effect. No significant associations were found between HPA-axis or ANS indicators and suicide-outcomes and between immune-inflammatory system markers or cumulative stress system dysregulations and SI+SA-.

CONCLUSION

Although stress system markers could not differentiate between SI+SA- and non-suicidal patients, findings indicate that dysregulations of individual and cumulative immune-inflammatory markers are associated with suicide attempts in depressive and/or anxiety patients. Thus, immune-inflammatory system dysregulation may be involved in the pathophysiology of suicidal behavior, supporting further examination of the effects of anti-inflammatory interventions on suicidality.

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.

Ecological momentary intervention to enhance emotion regulation in healthcare workers via smartphone: a randomized controlled trial protocol

BACKGROUND

CUIDA-TE is an APP that offers transdiagnostic cognitive behavioral therapy focused on enhancing emotion regulation. As a novelty, it incorporates ecological momentary interventions (EMI), which can provide psychological support in real time, when suffering arises. The main goal of the study is to evaluate the efficacy of CUIDA-TE to improve emotion regulation in healthcare workers, a population that has been particularly emotionally impacted by the COVID-19 pandemic.

METHODS

In this three-arm, randomized controlled trial (RCT) the study sample will be composed of a minimum of 174 healthcare workers. They will be randomly assigned to a 2-month EMI group (CUIDA-TE APP, n ≥ 58), a 2-month ecological momentary assessment (EMA) only group (MONITOR EMOCIONAL APP, n ≥ 58), or a wait-list control group (no daily monitoring nor intervention, n ≥ 58). CUIDA-TE will provide EMI if EMA reveals emotional problems, poor sleep quality/quantity, burnout, stress, or low perceived self-efficacy when regulating emotions. Depression will be the primary outcome. Secondary outcomes will include emotion regulation, quality of life, and resilience. Treatment acceptance and usability will also be measured. Primary and secondary outcomes will be obtained at pre- and post-intervention measurements, and at the 3-month follow-up for all groups.

DISCUSSION

To our knowledge, this is the first RCT that evaluates the efficacy of an APP-based EMI to improve emotion regulation skills in healthcare workers. This type of intervention might ultimately help disseminate treatments and reach a larger number of individuals than traditional face-to-face individual therapies.

TRIAL REGISTRATION

ClinicalTrial.gov : NCT04958941 Registered 7 Jun 2021.

STUDY STATUS

Participant recruitment has not started.

Suicide Prevention in Your Pocket: A Systematic Review of Ecological Momentary Interventions for the Management of Suicidal Thoughts and Behaviors

BACKGROUND

This study reviews the evidence on ecological momentary interventions (EMIs) for managing and preventing suicidal thoughts and behaviors.

METHODS

This review follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Its protocol was registered in the PROSPERO database. We conducted a systematic literature search of five databases: PubMed, EMBASE, Web of Science, PsycInfo, and Cochrane library. The most recent search date was 10 September 2021.

RESULTS

After screening and full-text review, 27 studies were included, totaling 19 different interventions. Many of the available interventions have not yet been clinically tested. Those that have undergone effectiveness evaluation (10 interventions) showed good rates of effectiveness and feasibility, with some exceptions. The most widely used intervention model is the safety plan, which allows the user to implement coping and distracting strategies in case of suicidal ideation.

CONCLUSIONS

Ecological momentary interventions provide certain advantages, such as their wide availability, versatility, and potential for customization. These interventions can be useful complements to traditional care, especially in situations in which face-to-face care is not possible. Evidence on the effectiveness of such interventions is still scarce. Furthermore, barriers limiting implementation in clinical practice remain. The constant advance of technology means that these interventions have great potential for improvement in the coming years.

Discriminating between patients with unipolar disorder, bipolar disorder, and healthy control individuals based on voice features collected from naturalistic smartphone calls

BACKGROUND

It is of crucial importance to be able to discriminate unipolar disorder (UD) from bipolar disorder (BD), as treatments, as well as course of illness, differ between the two disorders.

AIMS

To investigate whether voice features from naturalistic phone calls could discriminate between (1) UD, BD, and healthy control individuals (HC); (2) different states within UD.

METHODS

Voice features were collected daily during naturalistic phone calls for up to 972 days. A total of 48 patients with UD, 121 patients with BD, and 38 HC were included. A total of 115,483 voice data entries were collected (UD [n = 16,454], BD [n = 78,733], and HC [n = 20,296]). Patients evaluated symptoms daily using a smartphone-based system, making it possible to define illness states within UD and BD. Data were analyzed using random forest algorithms.

RESULTS

Compared with BD, UD was classified with a specificity of 0.84 (SD: 0.07)/AUC of 0.58 (SD: 0.07) and compared with HC with a sensitivity of 0.74 (SD: 0.10)/AUC = 0.74 (SD: 0.06). Compared with BD during euthymia, UD during euthymia was classified with a specificity of 0.79 (SD: 0.05)/AUC = 0.43 (SD: 0.16). Compared with BD during depression, UD during depression was classified with a specificity of 0.81 (SD: 0.09)/AUC = 0.48 (SD: 0.12). Within UD, compared with euthymia, depression was classified with a specificity of 0.70 (SD 0.31)/AUC = 0.65 (SD: 0.11). In all models, the user-dependent models outperformed the user-independent models.

CONCLUSIONS

The results from the present study are promising, but as reflected by the low AUCs, does not support that voice features collected during naturalistic phone calls at the current state of art can be implemented in clinical practice as a supplementary and assisting tool. Further studies are needed.

Study protocol for a randomised, double-blinded, placebo-controlled phase III trial examining the add-on efficacy, cost-utility and neurobiological effects of low-dose naltrexone (LDN) in patients with fibromyalgia (INNOVA study)

INTRODUCTION

There is evidence that low-dose naltrexone (LDN; <5.0 mg/day) reduces pain and improves the quality of life of people with fibromyalgia syndrome (FMS). However, no randomised controlled trials with long-term follow-ups have been carried out. The INNOVA study will evaluate the add-on efficacy, safety, cost-utility and neurobiological effects of LDN for reducing pain in patients with FMS, with a 1-year follow-up.

METHODS AND ANALYSIS

A single-site, prospective, randomised, double-blinded, placebo-controlled, parallel design phase III trial will be performed. Eligibility criteria include being adult, having a diagnosis of FMS and experiencing pain of 4 or higher on a 10-point numerical rating scale. Participants will be randomised to a LDN intervention group (4.5 mg/day) or to a placebo control group. Clinical assessments will be performed at baseline (T0), 3 months (T1), 6 months (T2) and 12 months (T3). The primary endpoint will be pain intensity. A sample size of 60 patients per study arm (120 in total), as calculated prior to recruitment for sufficient power, will be monitored between January 2022 and August 2024. Assessment will also include daily ecological momentary evaluations of FMS-related symptoms (eg, pain intensity, fatigue and sleep disturbance), and side effects via ecological momentary assessment through the Pain Monitor app during the first 3 months. Costs and quality-adjusted life years will be also calculated. Half of the participants in each arm will be scanned with MRI at T0 and T1 for changes in brain metabolites related to neuroinflammation and central sensitisation. Inflammatory biomarkers in serum will also be measured.

ETHICS AND DISSEMINATION

This study has been approved by the Ethics Committee of the Fundació Sant Joan de Déu. The results will be actively disseminated through peer-reviewed journals, conference presentations, social media and community engagement activities.

TRIAL REGISTRATION NUMBER

NCT04739995.

A Data-Driven Clustering Method for Discovering Profiles in the Dynamics of Major Depressive Disorder Using a Smartphone-Based Ecological Momentary Assessment of Mood

BACKGROUND

Although major depressive disorder (MDD) is characterized by a pervasive negative mood, research indicates that the mood of depressed patients is rarely entirely stagnant. It is often dynamic, distinguished by highs and lows, and it is highly responsive to external and internal regulatory processes. Mood dynamics can be defined as a combination of mood variability (the magnitude of the mood changes) and emotional inertia (the speed of mood shifts). The purpose of this study is to explore various distinctive profiles in real-time monitored mood dynamics among MDD patients in routine mental healthcare.

METHODS

Ecological momentary assessment (EMA) data were collected as part of the cross-European E-COMPARED trial, in which approximately half of the patients were randomly assigned to receive the blended Cognitive Behavioral Therapy (bCBT). In this study a subsample of the bCBT group was included (n = 287). As part of bCBT, patients were prompted to rate their current mood (on a 1-10 scale) using a smartphone-based EMA application. During the first week of treatment, the patients were prompted to rate their mood on three separate occasions during the day. Latent profile analyses were subsequently applied to identify distinct profiles based on average mood, mood variability, and emotional inertia across the monitoring period.

RESULTS

Overall, four profiles were identified, which we labeled as: (1) "very negative and least variable mood" (n = 14) (2) "negative and moderate variable mood" (n = 204), (3) "positive and moderate variable mood" (n = 41), and (4) "negative and highest variable mood" (n = 28). The degree of emotional inertia was virtually identical across the profiles.

CONCLUSIONS

The real-time monitoring conducted in the present study provides some preliminary indications of different patterns of both average mood and mood variability among MDD patients in treatment in mental health settings. Such varying patterns were not found for emotional inertia.

The prefrontal cortex, pathological anxiety, and anxiety disorders

Anxiety is experienced in response to threats that are distal or uncertain, involving changes in one's subjective state, autonomic responses, and behavior. Defensive and physiologic responses to threats that involve the amygdala and brainstem are conserved across species. While anxiety responses typically serve an adaptive purpose, when excessive, unregulated, and generalized, they can become maladaptive, leading to distress and avoidance of potentially threatening situations. In primates, anxiety can be regulated by the prefrontal cortex (PFC), which has expanded in evolution. This prefrontal expansion is thought to underlie primates' increased capacity to engage high-level regulatory strategies aimed at coping with and modifying the experience of anxiety. The specialized primate lateral, medial, and orbital PFC sectors are connected with association and limbic cortices, the latter of which are connected with the amygdala and brainstem autonomic structures that underlie emotional and physiological arousal. PFC pathways that interface with distinct inhibitory systems within the cortex, the amygdala, or the thalamus can regulate responses by modulating neuronal output. Within the PFC, pathways connecting cortical regions are poised to reduce noise and enhance signals for cognitive operations that regulate anxiety processing and autonomic drive. Specialized PFC pathways to the inhibitory thalamic reticular nucleus suggest a mechanism to allow passage of relevant signals from thalamus to cortex, and in the amygdala to modulate the output to autonomic structures. Disruption of specific nodes within the PFC that interface with inhibitory systems can affect the negative bias, failure to regulate autonomic arousal, and avoidance that characterize anxiety disorders.

Examining the Theoretical Framework of Behavioral Activation for Major Depressive Disorder: Smartphone-Based Ecological Momentary Assessment Study

BACKGROUND

Behavioral activation (BA), either as a stand-alone treatment or as part of cognitive behavioral therapy, has been shown to be effective for treating depression. The theoretical underpinnings of BA derive from Lewinsohn et al's theory of depression. The central premise of BA is that having patients engage in more pleasant activities leads to them experiencing more pleasure and elevates their mood, which, in turn, leads to further (behavioral) activation. However, there is a dearth of empirical evidence about the theoretical framework of BA.

OBJECTIVE

This study aims to examine the assumed (temporal) associations of the 3 constructs in the theoretical framework of BA.

METHODS

Data were collected as part of the "European Comparative Effectiveness Research on Internet-based Depression Treatment versus treatment-as-usual" trial among patients who were randomly assigned to receive blended cognitive behavioral therapy (bCBT). As part of bCBT, patients completed weekly assessments of their level of engagement in pleasant activities, the pleasure they experienced as a result of these activities, and their mood over the course of the treatment using a smartphone-based ecological momentary assessment (EMA) application. Longitudinal cross-lagged and cross-sectional associations of 240 patients were examined using random intercept cross-lagged panel models.

RESULTS

The analyses did not reveal any statistically significant cross-lagged coefficients (all P>.05). Statistically significant cross-sectional positive associations between activities, pleasure, and mood levels were identified. Moreover, the levels of engagement in activities, pleasure, and mood slightly increased over the duration of the treatment. In addition, mood seemed to carry over, over time, while both levels of engagement in activities and pleasurable experiences did not.

CONCLUSIONS

The results were partially in accordance with the theoretical framework of BA, insofar as the analyses revealed cross-sectional relationships between levels of engagement in activities, pleasurable experiences deriving from these activities, and enhanced mood. However, given that no statistically significant temporal relationships were revealed, no conclusions could be drawn about potential causality. A shorter measurement interval (eg, daily rather than weekly EMA reports) might be more attuned to detecting potential underlying temporal pathways. Future research should use an EMA methodology to further investigate temporal associations, based on theory and how treatments are presented to patients.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02542891, https://clinicaltrials.gov/ct2/show/NCT02542891; German Clinical Trials Register, DRKS00006866, https://tinyurl.com/ybja3xz7; Netherlands Trials Register, NTR4962, https://www.trialregister.nl/trial/4838; ClinicalTrials.Gov, NCT02389660, https://clinicaltrials.gov/ct2/show/NCT02389660; ClinicalTrials.gov, NCT02361684, https://clinicaltrials.gov/ct2/show/NCT02361684; ClinicalTrials.gov, NCT02449447, https://clinicaltrials.gov/ct2/show/NCT02449447; ClinicalTrials.gov, NCT02410616, https://clinicaltrials.gov/ct2/show/NCT02410616; ISRCTN registry, ISRCTN12388725, https://www.isrctn.com/ISRCTN12388725.

Smartphone-Delivered Ecological Momentary Interventions Based on Ecological Momentary Assessments to Promote Health Behaviors: Systematic Review and Adapted Checklist for Reporting Ecological Momentary Assessment and Intervention Studies

Background

Healthy behaviors are crucial for maintaining a person’s health and well-being. The effects of health behavior interventions are mediated by individual and contextual factors that vary over time. Recently emerging smartphone-based ecological momentary interventions (EMIs) can use real-time user reports (ecological momentary assessments [EMAs]) to trigger appropriate support when needed in daily life.

Objective

This systematic review aims to assess the characteristics of smartphone-delivered EMIs using self-reported EMAs in relation to their effects on health behaviors, user engagement, and user perspectives.

Methods

We searched MEDLINE, Embase, PsycINFO, and CINAHL in June 2019 and updated the search in March 2020. We included experimental studies that incorporated EMIs based on EMAs delivered through smartphone apps to promote health behaviors in any health domain. Studies were independently screened. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. We performed a narrative synthesis of intervention effects, user perspectives and engagement, and intervention design and characteristics. Quality appraisal was conducted for all included studies.

Results

We included 19 papers describing 17 unique studies and comprising 652 participants. Most studies were quasi-experimental (13/17, 76%), had small sample sizes, and great heterogeneity in intervention designs and measurements. EMIs were most popular in the mental health domain (8/17, 47%), followed by substance abuse (3/17, 18%), diet, weight loss, physical activity (4/17, 24%), and smoking (2/17, 12%). Of the 17 studies, the 4 (24%) included randomized controlled trials reported nonstatistically significant effects on health behaviors, and 4 (24%) quasi-experimental studies reported statistically significant pre-post improvements in self-reported primary outcomes, namely depressive (P<.001) and psychotic symptoms (P=.03), drinking frequency (P<.001), and eating patterns (P=.01). EMA was commonly used to capture subjective experiences as well as behaviors, whereas sensors were rarely used. Generally, users perceived EMIs to be helpful. Common suggestions for improvement included enhancing personalization, multimedia and interactive capabilities (eg, voice recording), and lowering the EMA reporting burden. EMI and EMA components were rarely reported and were not described in a standardized manner across studies, hampering progress in this field. A reporting checklist was developed to facilitate the interpretation and comparison of findings and enhance the transparency and replicability of future studies using EMAs and EMIs.

Conclusions

The use of smartphone-delivered EMIs using self-reported EMAs to promote behavior change is an emerging area of research, with few studies evaluating efficacy. Such interventions could present an opportunity to enhance health but need further assessment in larger participant cohorts and well-designed evaluations following reporting checklists. Future research should explore combining self-reported EMAs of subjective experiences with objective data passively collected via sensors to promote personalization while minimizing user burden, as well as explore different EMA data collection methods (eg, chatbots).

Trial Registration

PROSPERO CRD42019138739; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=138739

In Search of Digital Dopamine: How Apps Can Motivate Depressed Patients, a Review and Conceptual Analysis

INTRODUCTION

Depression is highly prevalent and causes considerable suffering and disease burden despite the existence of wide-ranging treatment options. Momentary assessment 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. Treating the motivational and hedonic aspects of depression is a key target reported in the literature, but it is time-consuming in terms of human resources. Digital Applications offer a major opportunity to indirectly regulate impaired motivational circuits through dopaminergic pathways.

OBJECTIVE

The main objective of this review was twofold: (1) propose a conceptual and critical review of the literature regarding the theoretical and technical principles of digital applications focused on motivation in depression, activating dopamine, and (2) suggest recommendations on the relevance of using these tools and their potential place in the treatment of depression.

MATERIAL AND METHODS

A search for words related to "dopamine", "depression", "smartphone apps", "digital phenotype" has been conducted on PubMed.

RESULTS

Ecological momentary interventions (EMIs) differ from traditional treatments by providing relevant, useful intervention strategies in the context of people's daily lives. EMIs triggered by ecological momentary assessment (EMA) are called "Smart-EMI". Smart-EMIs can mimic the "dopamine reward system" if the intervention is tailored for motivation or hedonic enhancement, and it has been shown that a simple reward (such as a digital badge) can increase motivation.

DISCUSSION

The various studies presented support the potential interest of digital health in effectively motivating depressed patients to adopt therapeutic activation behaviors. Finding effective ways to integrate EMIs with human-provided therapeutic support may ultimately yield the most efficient and effective intervention method. This approach could be a helpful tool to increase adherence and motivation.

CONCLUSION

Smartphone apps can motivate depressed patients by enhancing dopamine, offering the opportunity to enhance motivation and behavioral changes, although longer term studies are still needed.

Natural language processing for cognitive therapy: Extracting schemas from thought records

The cognitive approach to psychotherapy aims to change patients’ maladaptive schemas, that is, overly negative views on themselves, the world, or the future. To obtain awareness of these views, they record their thought processes in situations that caused pathogenic emotional responses. The schemas underlying such thought records have, thus far, been largely manually identified. Using recent advances in natural language processing, we take this one step further by automatically extracting schemas from thought records. To this end, we asked 320 healthy participants on Amazon Mechanical Turk to each complete five thought records consisting of several utterances reflecting cognitive processes. Agreement between two raters on manually scoring the utterances with respect to how much they reflect each schema was substantial (Cohen’s κ = 0.79). Natural language processing software pretrained on all English Wikipedia articles from 2014 (GLoVE embeddings) was used to represent words and utterances, which were then mapped to schemas using k-nearest neighbors algorithms, support vector machines, and recurrent neural networks. For the more frequently occurring schemas, all algorithms were able to leverage linguistic patterns. For example, the scores assigned to the Competence schema by the algorithms correlated with the manually assigned scores with Spearman correlations ranging between 0.64 and 0.76. For six of the nine schemas, a set of recurrent neural networks trained separately for each of the schemas outperformed the other algorithms. We present our results here as a benchmark solution, since we conducted this research to explore the possibility of automatically processing qualitative mental health data and did not aim to achieve optimal performance with any of the explored models. The dataset of 1600 thought records comprising 5747 utterances is published together with this article for researchers and machine learning enthusiasts to improve upon our outcomes. Based on our promising results, we see further opportunities for using free-text input and subsequent natural language processing in other common therapeutic tools, such as ecological momentary assessments, automated case conceptualizations, and, more generally, as an alternative to mental health scales.

Efficacy of an internet-based psychological intervention for problem gambling and gambling disorder: Study protocol for a randomized controlled trial

Gambling Disorder is a prevalent non-substance use disorder, which contrasts with the low number of people requesting treatment. Information and Communication Technologies (ICT) could help to enhance the dissemination of evidence-based treatments and considerably reduce the costs. The current study seeks to assess the efficacy of an online psychological intervention for people suffering from gambling problems in Spain. The proposed study will be a two-arm, parallel-group, randomized controlled trial. A total of 134 participants (problem and pathological gamblers) will be randomly allocated to a waiting list control group (N = 67) or an intervention group (N = 67). The intervention program includes 8 modules, and it is based on motivational interviewing, cognitive-behavioral therapy (CBT), and extensions and innovations of CBT. It includes several complementary tools that are present throughout the entire intervention. Therapeutic support will be provided once a week through a phone call with a maximum length of 10 min. The primary outcome measure will be gambling severity and gambling-related cognitions, and secondary outcome measures will be readiness to change, and gambling self-efficacy. Other variables that will be considered are depression and anxiety symptoms, positive and negative affect, difficulties in emotion regulation strategies, impulsivity, and quality of life. Individuals will be assessed at baseline, post-treatment, and 3-, 6-, and 12-month follow-ups. During the treatment, participants will also respond to a daily Ecological Momentary Intervention (EMI) in order to evaluate urges to gamble, self-efficacy to cope with gambling urges, gambling urge frequency, and whether gambling behaviour occurs. The EMI includes immediate automatic feedback depending on the participant's responses. Treatment acceptance and satisfaction will also be assessed. The data will be analysed both per protocol and by Intention-to-treat. As far as we know, this is the first randomized controlled trial of an online psychological intervention for gambling disorder in Spain. It will expand our knowledge about treatments delivered via the Internet and contribute to improving treatment dissemination, reaching people suffering from this problem who otherwise would not receive help.

TRIAL REGISTRATION

Clinicaltrials.gov as NCT04074681. Registered 22 July 2019.

Implementation of automatic speech analysis for early detection of psychiatric symptoms: What do patients want?

Psychiatry is in dire need of a method to aid early detection of symptoms. Recent developments in automatic speech analysis prove promising in this regard, and open avenues for implementation of speech-based applications to detect psychiatric symptoms. The current survey was conducted to assess positions with regard to speech recordings among a group (n = 675) of individuals who experience psychiatric symptoms. Overall, respondents are open to the idea of speech recordings in light of their mental welfare. Importantly, concerns with regard to privacy were raised. Given that speech recordings are privacy sensitive, this requires special attention upon implementation of automatic speech analysis techniques. Furthermore, respondents indicated a preference for speech recordings in the presence of a clinician, as opposed to a recording made at home without the clinician present. In developing a speech marker for psychiatry, close collaboration with the intended users is essential to arrive at a truly valid and implementable method.

Efficacité des applications mobiles et des messages textes comme intervention en cybersanté mentale pour les 3 blessures de stress opérationnel les plus fréquentes chez le personnel de la sécurité publique : une recension-cadre

Contexte La fréquence de diagnostic probable de trouble de santé mentale est beaucoup plus haute chez le personnel de la sécurité publique (PSP) que dans la population générale, ce qui s’explique entre autres par l’exercice des fonctions opérationnelles. Les blessures de stress opérationnelles (BSO) les plus fréquentes chez les PSP au Canada sont la dépression, le trouble de stress posttraumatique et le trouble d’anxiété généralisée. Par leur caractère confidentiel et accessible, les interventions en cybersanté mentale délivrées par des téléphones intelligents (interventions mobiles) offrent un fort potentiel chez les PSP. La Commission de la santé mentale du Canada a proposé des critères évaluatifs afin de faire un examen complet des interventions mobiles, qui dépasse l’examen scientifique de l’efficacité de l’outil.

Objectifs Cette recension-cadre vise d’abord à recenser les résultats des recensions systématiques et des méta-analyses qui portent sur l’évaluation des interventions mobiles visant à diminuer les symptômes reliés à au moins une BSO chez les PSP. Ensuite, nous évaluerons les interventions mobiles ayant été étudiées auprès de PSP à l’aide des critères évaluatifs proposés par la Commission de la santé mentale du Canada, afin d’établir si leur usage peut être recommandé.

Méthode Des termes en lien avec les BSO, les technologies mobiles et les interventions ont été utilisées dans les bases de données PubMed, PsycInfo et Embase. Les articles évaluant l’efficacité des interventions mobiles en lien avec au moins une BSO et desquels il était possible d’extraire les informations nécessaires à cette recension ont été retenus. Un examen des articles inclus dans les recensions retenues a été fait afin de repérer les études réalisées auprès d’un échantillon de PSP.

Résultats La recherche de la littérature n’a relevé aucune recension qui s’intéressait particulièrement aux PSP, ce pour quoi nous avons dû élargir notre recherche à la population générale. Neuf articles correspondent aux critères d’inclusion, lesquels ont été publiés entre 2016 et 2019. De manière générale, les interventions mobiles semblent réduire de manière significative les symptômes d’anxiété, de dépression et de stress posttraumatique. Deux interventions mobiles étudiées auprès de PSP ont été identifiées, et ces dernières remplissent la majorité des critères évaluatifs.

Conclusion Les interventions mobiles recensées dans la littérature offrent un fort potentiel auprès de la population générale et auprès des PSP. Toutefois, les méta-analyses et les recensions systématiques rapportent certaines limites importantes telles qu’une hétérogénéité entre les études et un taux d’abandon élevé. Les recherches futures sur les interventions mobiles destinées aux PSP gagneraient à investiguer davantage les aspects liés à l’ergonomie, la désirabilité pour l’utilisateur et la sécurité des renseignements personnels. Les échantillons devraient également inclure une plus grande variété de professions liées à la sécurité publique.

A cross-diagnostic study of Adherence to Ecological Momentary Assessment: Comparisons across study length and daily survey frequency find that early adherence is a potent predictor of study-long adherence

Background

Ecological momentary assessment (EMA) offers a highly valid strategy to assess everyday functioning in people with severe mental illness. Adherence is generally good, but several questions regarding the impact of study length, daily density of sampling, and symptom severity on adherence remain.

Methods

EMA adherence in two separate studies was examined. One sampled participants with schizophrenia (n=106) and healthy controls (n=76) 7 times per day for 7 days and the other sampled participants with schizophrenia (n=104) and participants with bipolar illness (n=76) 3 times per day for 30 days. Participants were asked where they were, who they were with, what they were doing and how they were feeling in both studies. The impact of rates of very early adherence on eventual adherence was investigated across the samples, and adherence rates were examined for associations with mood state and most common location when answering surveys.

Results

Median levels of adherence were over 80% across the samples, and the 10^th percentile for adherence was approximately 45% of surveys answered. Early adherence predicted study-long adherence quite substantially in every sample. Mood states did not correlate with adherence in the patient samples and being home correlated with adherence in only the bipolar sample.

Implications

Adherence was quite high and was not correlated with the length of the study or the density of sampling per study day. There was a tendency for bipolar participants who were more commonly away from home to answer fewer surveys but overall adherence for the bipolar patients was quite high. These data suggest that early nonadherence is a potential predictor of eventual nonadherence and study noncompletion.

An informatics approach to examine decision-making impairments in the daily life of individuals with depression

Mental health informatics studies methods that collect, model, and interpret a wide variety of data to generate useful information with theoretical or clinical relevance to improve mental health and mental health care. This article presents a mental health informatics approach that is based on the decision-making theory of depression, whereby daily life data from a natural sequential decision-making task are collected and modeled using a reinforcement learning method. The model parameters are then estimated to uncover specific aspects of decision-making impairment in individuals with depression. Empirical results from a pilot study conducted to examine decision-making impairments in the daily lives of university students with depression are presented to illustrate this approach. Future research can apply and expand on this approach to investigate a variety of daily life situations and psychiatric conditions and to facilitate new informatics applications. Using this approach in mental health research may generate useful information with both theoretical and clinical relevance and high ecological validity.

Screening for depression in older adults with cognitive impairment in the homecare setting: a systematic review

OBJECTIVE

Previous systematic reviews have examined depression screening in older adults with cognitive impairment (CI) in outpatient and inpatient clinics, nursing homes, and residential care. Despite an increasing number of older adults with CI receiving care in their homes, less is known about best depression screening practices in homecare. The objective of this review is to identify evidence-based practices for depression screening for individuals with CI receiving homecare by assessing tool performance and establishing the current evidence for screening practices in this setting.

METHODS

This review is registered under PROSPERO (ID: CRD42018110243). A systematic search was conducted using MEDLINE, EMBASE, Health and Psychosocial Abstracts, PsycINFO and CINAHL. The following criteria were used: assessment of depression at home in older adults (>55 years) with CI, where performance outcomes of the depression screening tool were reported.

RESULTS

Of 5,453 studies, only three met eligibility criteria. These studies evaluated the Patient Health Questionnaire (n = 236), the Geriatric Depression Scale (n = 79) and the Mental Health Index (n = 1,444) in older adults at home with and without CI. Psychometric evaluation demonstrated moderate performance in the subsamples of people with CI.

CONCLUSION

At present, there is insufficient evidence to support best practices in screening for depression in people with CI in homecare.

Discovering different profiles in the dynamics of depression based on real-time monitoring of mood: a first exploration

BACKGROUND

Although depression is typically characterized by a persistent depressed mood, mood dynamics do seem to vary across a depressed population. Heterogeneity of mood variability (magnitude of changes) and emotional inertia (speed at which mood shifts) is seen in clinical practice. However, studies investigating the heterogeneity of these mood dynamics are still scarce. The aim of the present study is to explore different distinctive profiles in real-time monitored mood dynamics among depressed persons.

METHODS

After completing baseline measures, mildly-to-moderately depressed persons (n = 37) were prompted to rate their current mood (1-10 scale) on their smartphones, 3 times a day for 7 consecutive days. Latent profile analyses were applied to identify profiles based on average mood, variability of mood and emotional inertia as reported by the participants.

RESULTS

Two profiles were identified in this sample. The overwhelming majority of the sample belonged to profile 1 (n = 31). Persons in profile 1 were characterized by a mood just above the cutoff for positive mood (M = 6.27), with smaller mood shifts (lower variability [SD = 1.05]) than those in profile 2 (n = 6), who displayed an overall negative mood (M = 4.72) and larger mood shifts (higher variability [SD = 1.95]) but at similar speed (emotional inertia) (AC = 0.19, AC = 0.26, respectively).

CONCLUSIONS

The present study provides preliminary indications for patterns of average mood and mood variability, but not emotional inertia, among mildly-to-moderately depressed persons.

Patients' experience of an ecological momentary intervention involving self-monitoring and personalized feedback for depression

Experts in clinical mental health research count on personalized approaches based on self-monitoring and self-management to improve treatment efficacy in psychiatry. Among other things, researchers expect that Ecological Momentary Interventions (EMI) based on self-monitoring and personalized feedback will reduce depressive symptoms. Clinical trial findings have, however, been conflicting. A recent trial (ZELF-i) investigated whether depression treatment might be enhanced by an add-on EMI with self-monitoring items and feedback focused on positive affect and activities (Do-module) or on negative affect and thinking patterns (Think-module). There was no statistical evidence that this EMI impacted clinical or functional outcomes beyond the effects of regular care, regardless of module content. In apparent contrast, 86% of the participants who completed the intervention indicated they would recommend it to others. In the present study, we used in-depth interviews (n = 20) to better understand the EMI's personal and clinical benefits and downsides. A thematic analysis of the interviews generated six areas of impact with various subthemes. In line with the trial results, few participants reported behavioral changes or symptom improvement over time; the self-assessments mainly amplified momentary mood, in either direction. The most often mentioned benefits were an increase in self-awareness, insight, and self-management (e.g., a stronger sense of control over complaints). Consistently, these domains received the highest ratings in our evaluation questionnaire (n = 89). Furthermore, the EMI instilled a routine into the days of individuals without regular jobs or other activities. Participants reported few downsides. The experiences were rather similar between the two modules. This study suggests that EMI might contribute to health by helping individuals deal with their symptoms, rather than reducing them. Measures on self-awareness, insight, and self-management should be more emphatically involved in future EMI research.

The Moderating Role of Emotion Regulation in the Recall of Negative Autobiographical Memories

When facing a negative event, people implement different strategies to regulate ongoing emotions. Although the previous literature has suggested that the emotional intensity of a negative episode is associated with the characteristics of the subsequent autobiographical memory, it is still unknown whether emotion regulation (ER) moderates this relationship. In the present study, we provided undergraduate students with a smartphone-based diary to report a negative episode immediately after its occurrence and rate the momentary use of two ER strategies: cognitive reappraisal and rumination. To explore autobiographical memory, two "surprise" recall tasks were performed one week and one month after the event. According to the results, cognitive reappraisal was linked with better memory performances, and a tendency to retrospectively underestimate the negativity of highly intense events was observed only in participants adopting high rates of this strategy. Conversely, intense rumination was found to be associated with less detailed memories of emotionally intense events, as well as with higher emotional involvement with negative episodes over time, regardless of their intensity. Together, our results support the maladaptive role of rumination and the adaptive influence of cognitive reappraisal on autobiographical memory.

Virtual reality for the enhancement of emotion regulation

In recent decades, a growing body of literature has focused on emotion regulation (ER), which refers to the ability to implement strategies in order to modulate emotional responses and reach desirable goals. To date, impaired ER (i.e., emotion dysregulation) has been identified as a transdiagnostic factor across a wide range of psychopathological conditions, which shows the importance of improving patients' ability to regulate negative and positive emotions in clinical practice. In addition to the increasing evidence showing its efficacy in the treatment of several clinical conditions, virtual reality (VR) has recently emerged as a potentially powerful tool for enhancing ER, thus breaking new ground in the development of cutting-edge transdiagnostic interventions. In the present narrative review, we will provide an overview of the existing evidence about VR-based interventions in the field of ER, emphasizing the promising findings and the barriers that still have to be addressed. To this aim, the available VR-based literature will be analysed in relation to four categories of ER strategies: situational strategies, attentional strategies, cognitive strategies, and response modulation strategies. Furthermore, new emerging fields of research targeting innovative aspects of ER will be highlighted, including the use of VR to promote positive emotions and interpersonal ER skills. Besides, its cost-effectiveness will be discussed, taking into account the costs for both developers (e.g., clinicians and researchers) and end-users. Finally, future directions in this promising field of research will be outlined.

Use of Ecological Momentary Assessment to Study Suicidal Thoughts and Behavior: a Systematic Review

PURPOSE OF REVIEW

Ecological momentary assessment (EMA) is a recently introduced approach to patient evaluation that consists of asking patients questions in real time and in their usual habitat. This method seeks to contribute to suicide prevention by providing psychiatrists with detailed information about suicidal thoughts and behavior, how these fluctuate over short periods of time, and the short-term risk factors presented by patients. We conducted a systematic review of published research using EMA to study suicidal thoughts and behavior.

RECENT FINDINGS

Several systematic reviews of EMA in mental health have been conducted to date, and the literature contains numerous theoretical papers and compilations on EMA and suicide phenomena. To date, however, no systematic reviews have explored the use of this tool to study suicidal thoughts and behavior. We performed a systematic review of five databases (i.e., PubMed, Embase, Scopus, Web of Science, and PsycINFO) to identify studies on EMA and suicidal thoughts and behavior. An initial search revealed 544 articles. Following the study selection process, 35 studies were included in the review. Almost three-quarters of the studies were published in the last 4 years. The studies reviewed concluded that EMA was generally feasible and well accepted. EMA findings correlated well with the results of a retrospective assessment, though tended to over-represent symptom severity. Our review points to important aspects of suicidal thoughts and behavior, such as its wide fluctuation over short periods of time. Negative affect and disturbed sleep, among others, emerged as short-term predictors of suicidal thoughts and behavior. Therefore, EMA is a potentially useful tool in clinical practice, although not without drawbacks, such as participant fatigue with questionnaires and ethical concerns.

Perceived Impacts, Acceptability, and Recommendations for Ecological Momentary Assessment Among Youth Experiencing Homelessness: Qualitative Study

BACKGROUND

The use of ecological momentary assessment (EMA) to study youth experiencing homelessness (YEH) behaviors is an emerging area of research. Despite high rates of participation and potential clinical utility, few studies have investigated the acceptability and recommendations for EMA from the YEH perspective.

OBJECTIVE

This study aimed to describe the perceived benefits, usability, acceptability, and barriers to the use of EMA from the homeless youth perspective.

METHODS

YEH were recruited from a larger EMA study. Semistructured exit interviews were performed using an interview guide that focused on the YEH experience with the EMA app, and included perceived barriers and recommendations for future studies. Data analyses used an inductive approach with thematic analysis to identify major themes and subthemes.

RESULTS

A total of 18 YEH aged 19-24 years participated in individual and group exit interviews. The EMA was highly acceptable to YEH and they found the app and EMA surveys easy to navigate. Perceived benefits included increased behavioral and emotional awareness with some YEH reporting a decrease in their high-risk behaviors as a result of participation. Another significant perceived benefit was the ability to use the phones for social support and make connections to family, friends, and potential employers. Barriers were primarily survey and technology related. Survey-related barriers included the redundancy of questions, the lack of customizable responses, and the timing of survey prompts. Technology-related barriers included the "freezing" of the app, battery charge, and connectivity issues. Recommendations for future studies included the need to provide real-time mental health support for symptomatic youth, to create individually customized questions, and to test the use of personalized motivational messages that respond to the EMA data in real time.

CONCLUSIONS

YEH are highly receptive to the use of EMA in studies. Further studies are warranted to understand the impact of EMA on YEH behaviors. Incorporating the YEH perspective into the design and implementation of EMA studies may help minimize barriers, increase acceptability, and improve participation rates in this hard-to-reach, disconnected population.

Ecological momentary interventions for mental health: A scoping review

BACKGROUND

The development of mobile computing technology has enabled the delivery of psychological interventions while people go about their everyday lives. The original visions of the potential of these "ecological momentary interventions" were presented over a decade ago, and the widespread adoption of smartphones in the intervening years has led to a variety of research studies exploring the feasibility of these aspirations. However, there is a dearth of research describing the different dimensions, characteristics, and features of these interventions, as constructed.

OBJECTIVE

To provide an overview of the definitions given for "ecological momentary interventions" in the treatment of common mental health disorders, and describe the set of technological and interaction possibilities which have been used in the design of these interventions.

METHODS

A systematic search identified relevant literature published between 2009 and 2020 in the PubMed, PsycInfo, and ACM Guide to the Computing Literature databases. Following screening, data were extracted from eligible articles using a standardized extraction worksheet. Selected articles were then thematically categorized.

RESULTS

The search identified 583 articles of which 64 met the inclusion criteria. The interventions target a range of mental health problems, with diverse aims, intervention designs and evaluation approaches. The studies employed a variety of features for intervention delivery, but recent research is overwhelmingly comprised of studies based on smartphone apps (30 of 42 papers that described an intervention). Twenty two studies employed sensors for the collection of data in order to provide just-in-time support or predict psychological states.

CONCLUSIONS

With the shift towards smartphone apps, the vision for EMIs has begun to be realised. Recent years have seen increased exploration of the use of sensors and machine learning, but the role of humans in the delivery of EMI is also varied. The variety of capabilities exhibited by EMIs motivates development of a more precise vocabulary for capturing both automatic and human tailoring of these interventions.

Predicting the Physical and Mental Health Status of Individuals With Chronic Musculoskeletal Pain From a Biopsychosocial Perspective: A Multivariate Approach

OBJECTIVES

Chronic pain is theoretically conceptualized from a biopsychosocial perspective. However, research into chronic pain still tends to focus on isolated, biological, psychological, or social variables. Simultaneous examination of these variables in the prediction of outcomes is important because communalities between predictors exist. Examination of unique contributions might help guide research and interventions in a more effective way.

METHODS

The participants were 114 individuals with chronic pain (mean age=58.81, SD=11.85; 58.8% women and 41.2% men) who responded to demographics (age and sex), pain characteristics (duration and sensory qualities), psychological (catastrophizing and perceived injustice), and social (marital adjustment) measures. Multivariate analyses were conducted to investigate their unique contributions to pain-related health variables pain severity, pain interference, disability, anxiety, and depressive symptoms.

RESULTS

Bivariate analyses evidenced significant associations between pain sensory qualities, catastrophizing, perceived injustice, and all health variables. In multivariate analyses, pain sensory qualities were associated with pain severity (β=0.10; 95% confidence interval [CI]=0.05, 0.14; t=4.28, P<0.001), while perceived injustice was associated with pain interference (β=0.08; 95% CI=0.03, 0.12; t=3.59, P<0.001), disability (β=0.25; 95% CI=0.08, 0.42; t=2.92, P=0.004), anxiety (β=0.18; 95% CI=0.08, 0.27; t=3.65, P<0.001), and depressive symptoms (β=0.14; 95% CI=0.05, 0.23; t=2.92, P=0.004). Age, sex, pain duration, and marital adjustment were not associated with health variables either in bivariate or in multivariate analyses (all P>0.010).

DISCUSSION

As expected, communalities between biopsychosocial variables exist, which resulted in a reduced number of unique contributions in multivariate analyses. Perceived injustice emerged as a unique contributor to variables, which points to this psychological construct as a potentially important therapeutic target in multidisciplinary treatment of pain.

Dropping the E: The potential for integrating e-mental health in psychotherapy

E-mental health, or the use of technology in mental healthcare, has been the focus of research for over two decades. Over that period, the evidence base for the potential of technology to improve psychotherapeutic practice has grown steadily. This sharply contrasts with the actual use of e-mental health by psychotherapists, which has remained limited. In this article, we aim to illustrate how and when different technological tools and applications can play a role in psychotherapy. At the same time, we also highlight current limitations and discuss challenges for future research. A specific, yet hypothetical case, is used to guide this narrative review and make proposed applications tangible and concrete.

Patient and physician perspectives of a smartphone application for depression: a qualitative study

BACKGROUND

Despite an increasing number of smartphone apps, such therapeutic tools have not yet consistently demonstrated their efficacy and many suffer from low retention rates. To ensure the development of efficient apps associated with high adherence, we aimed to identify, through a user-centred design approach, patient and physician expectations of a hypothetical app dedicated to depression.

METHODS

We conducted semi-structured interviews with physicians (psychiatrists and general practitioners) and patients who had experienced a major depressive episode during the last 12 months using the focus group method. The interviews were audio recorded, transcribed and analysed using qualitative content analysis to define codes, categories and emergent themes.

RESULTS

A total of 26 physicians and 24 patients were included in the study. The focus groups showed balanced sex and age distributions. Most participants owned a smartphone (83.3% of patients, 96.1% of physicians) and were app users (79.2% of patients and 96.1% of physicians). The qualitative content analysis revealed 3 main themes: content, operating characteristics and barriers to the use of the app. Expected content included the data collected by the app, aiming to provide information about the patient, data provided by the app, gathering psychoeducation elements, therapeutic tools and functionalities to help with the management of daily life and features expected for this tool. The "operating characteristics" theme gathered aims considered for the app, its potential target users, considered modalities of use and considerations around its accessibility and security of use. Finally, barriers to the use of the app included concerns about potential app users, its accessibility, safety, side-effects, utility and functioning. All themes and categories were the same for patients and physicians.

CONCLUSIONS

Physician and patient expectations of a hypothetical smartphone app dedicated to depression are high and confirmed the important role it could play in depression care. The key points expected by the users for such a tool are an easy and intuitive use and a personalised content. They are also waiting for an app that gives information about depression, offers a self-monitoring functionality and helps them in case of emergency.

Mood and Activity Measured Using Smartphones in Unipolar Depressive Disorder

Background: Smartphones comprise a promising tool for symptom monitoring in patients with unipolar depressive disorder (UD) collected as either patient-reportings or possibly as automatically generated smartphone data. However, only limited research has been conducted in clinical populations. We investigated the association between smartphone-collected monitoring data and validated psychiatric ratings and questionnaires in a well-characterized clinical sample of patients diagnosed with UD. Methods: Smartphone data, clinical ratings, and questionnaires from patients with UD were collected 6 months following discharge from psychiatric hospitalization as part of a randomized controlled study. Smartphone data were collected daily, and clinical ratings (i.e., Hamilton Depression Rating Scale 17-item) were conducted three times during the study. We investigated associations between (1) smartphone-based patient-reported mood and activity and clinical ratings and questionnaires; (2) automatically generated smartphone data resembling physical activity, social activity, and phone usage and clinical ratings; and (3) automatically generated smartphone data and same-day smartphone-based patient-reported mood and activity. Results: A total of 74 patients provided 11,368 days of smartphone data, 196 ratings, and 147 questionnaires. We found that: (1) patient-reported mood and activity were associated with clinical ratings and questionnaires (p < 0.001), so that higher symptom scores were associated with lower patient-reported mood and activity, (2) Out of 30 investigated associations on automatically generated data and clinical ratings of depression, only four showed statistical significance. Further, lower psychosocial functioning was associated with fewer daily steps (p = 0.036) and increased number of incoming (p = 0.032), outgoing (p = 0.015) and missed calls (p = 0.007), and longer phone calls (p = 0.012); (3) Out of 20 investigated associations between automatically generated data and daily patient-reported mood and activity, 12 showed statistical significance. For example, lower patient-reported activity was associated with fewer daily steps, shorter distance traveled, increased incoming and missed calls, and increased screen-time. Conclusion: Smartphone-based self-monitoring is feasible and associated with clinical ratings in UD. Some automatically generated data on behavior may reflect clinical features and psychosocial functioning, but these should be more clearly identified in future studies, potentially combining patient-reported and smartphone-generated data.

An evaluation of the efficacy of two add-on ecological momentary intervention modules for depression in a pragmatic randomized controlled trial (ZELF-i)

BACKGROUND

Depression treatment might be enhanced by ecological momentary interventions (EMI) based on self-monitoring and person-specific feedback. This study is the first to examine the efficacy of two different EMI modules for depression in routine clinical practice.

METHODS

Outpatients starting depression treatment at secondary mental health services (N = 161; MIDS-DEPRESSION = 35.9, s.d. = 10.7; MAGE = 32.8, s.d. = 12.1; 46% male) participated in a pragmatic randomized controlled trial with three arms. Two experimental groups engaged in 28 days of systematic self-monitoring (5 times per day), and received weekly feedback on either positive affect and activities (Do-module) or negative affect and thinking patterns (Think-module). The control group received no additional intervention. Participants completed questionnaires on depressive symptoms (primary outcome), social functioning, and empowerment before and after the intervention period, and at four measurements during a 6-month follow-up period.

RESULTS

Of the 90 (out of 110) participants who completed the intervention, 86% would recommend it. However, the experimental groups did not show significantly more or faster changes over time than the control group in terms of depressive symptoms, social functioning, and empowerment. Furthermore, the trajectories of the two EMI modules were very similar.

CONCLUSIONS

We did not find statistical evidence that this type of EMI augments the efficacy of regular depression treatment, regardless of module content. We cannot rule out that EMIs have a positive impact on other domains or provide a more efficient way of delivering care. Nonetheless, EMI's promise of effectiveness has not materialized yet.

A perspective on the use of ecological momentary assessment and intervention to promote stroke recovery and rehabilitation

Motivated by recent advances in technologies, ecological momentary assessment (EMA), and ecological momentary intervention (EMI) have seen a rise in behavioral medicine research that in real-time, informs the context for the behavior and prompts interventions to change that behavior in the natural setting when necessary. However, EMA and EMI have yet to be fully embraced in the field of stroke rehabilitation. Our objective is to provide a theoretically based perspective for the combined and synergistic use of EMA and EMI to promote person-centered, recovery-based durable changes in functional movement behaviors of stroke survivors. Research abounds for non-stroke populations with emerging evidence for the benefits of using real-time data capture techniques (i.e. EMA) coupled with EMI to better customize the content and timing of interventions to the inherent fluctuations in state and context that encompass the target behavior. We review existing EMA and EMI literature broadly in behavioral medicine and psychological science to identify how real-time repeated sampling technology has been used in the context of stroke rehabilitation and to delineate the pros and cons of this approach in general with non-stroke populations. We propose a coupled EMA and EMI strategy be used in conjunction with existing stroke recovery and rehabilitation practices. There is tremendous potential to effectively personalize recovery-promoting interventions to achieve durable behavior change, and importantly, shift the focus of rehabilitation practice from the health-care provider and clinical environment to the individual and their lived experience in the home and community.

Brief Acceptance and Commitment Therapy for Fibromyalgia: Feasibility and Effectiveness of a Replicated Single-Case Design

Objective

Overall, the literature on the effectiveness of psychological treatments in general and those for fibromyalgia in particular has been dominated by research designs that focus on large groups and explore changes on average, so the treatment impact at the individual level remains unclear. In this quasi-experimental, replicated single-case design, we will test the feasibility and effectiveness of a brief acceptance and committed therapy intervention using ecological momentary assessment supported by technology.

Methods

The sample comprised 7 patients (3 in the individual condition and 4 in the group condition) who received a brief, 5-week psychological treatment. Patient evolution was assessed one week prior to treatment onset and during the whole study with a smartphone app. Because ecological momentary assessment and the use of an app are not frequent practices in routine care, we also evaluated the feasibility of this assessment methodology (i.e., compliance with the app). Change was investigated with a nonoverlap of all pairs index. Outcomes were pain interference with sleep and social activities, fatigue, sadness, and pain intensity.

Results

Patient change was not uniform across outcomes. Four patients (two in each condition) showed relatively moderate levels of change (approximately 60% nonoverlap in several outcomes). The remaining patients showed more modest improvements which affected a reduced number of outcomes. Based on nonoverlapping indices, there was no clear evidence in favor of any treatment format.

Conclusions

An alternative design to large-scale trials, one that focuses on the individual change, exists and it can be implemented in pain research. The use of technology (e.g., smartphones) simplifies such designs by facilitating ecological momentary assessment. Based on our findings showing that changes were not homogeneous across patients or outcomes, more single-case designs and patient-centered analyses (e.g., responder and moderation analyses) are required.

Schema therapy versus cognitive behavioral therapy versus individual supportive therapy for depression in an inpatient and day clinic setting: study protocol of the OPTIMA-RCT

BACKGROUND

Major depressive disorder represents (MDD) a major cause of disability and disease burden. Beside antidepressant medication, psychotherapy is a key approach of treatment. Schema therapy has been shown to be effective in the treatment of psychiatric disorders, especially personality disorders, in a variety of settings and patient groups. Nevertheless, there is no evidence on its effectiveness for MDD in an inpatient nor day clinic setting and little is known about the factors that drive treatment response in such a target group.

METHODS

In the current protocol, we outline OPTIMA (OPtimized Treatment Identification at the MAx Planck Institute): a single-center randomized controlled trial of schema therapy as a treatment approach for MDD in an inpatient and day clinic setting. Over the course of 7 weeks, we compare schema therapy with cognitive behavioral therapy and individual supportive therapy, conducted in individual and group sessions and with no restrictions regarding concurrent antidepressant medication, thus approximating real-life treatment conditions. N = 300 depressed patients are included. All study therapists undergo a specific training and supervision and therapy adherence is assessed. Primary outcome is depressive symptom severity as self-assessment (Beck Depression Inventory-II) and secondary outcomes are clinical ratings of MDD (Montgomery-Asberg Depression Rating Scale), recovery rates after 7 weeks according to the Munich-Composite International Diagnostic Interview, general psychopathology (Brief Symptom Inventory), global functioning (World Health Organization Disability Assessment Schedule), and clinical parameters such as dropout rates. Further parameters on a behavioral, cognitive, psychophysiological, and biological level are measured before, during and after treatment and in 2 follow-up assessments after 6 and 24 months after end of treatment.

DISCUSSION

To our knowledge, the OPTIMA-Trial is the first to investigate the effectiveness of schema therapy as a treatment approach of MDD, to investigate mechanisms of change, and explore predictors of treatment response in an inpatient and day clinic setting by using such a wide range of parameters. Insights from OPTIMA will allow more integrative approaches of psychotherapy of MDD. Especially, the identification of intervention-specific markers of treatment response can improve evidence-based clinical decision for individualizing treatment.

TRIAL REGISTRATION

Identifier on clinicaltrials.gov : NCT03287362 ; September, 12, 2017.

The clinical characterization of the adult patient with depression aimed at personalization of management

Depression is widely acknowledged to be a heterogeneous entity, and the need to further characterize the individual patient who has received this diagnosis in order to personalize the management plan has been repeatedly emphasized. However, the research evidence that should guide this personalization is at present fragmentary, and the selection of treatment is usually based on the clinician's and/or the patient's preference and on safety issues, in a trial-and-error fashion, paying little attention to the particular features of the specific case. This may be one of the reasons why the majority of patients with a diagnosis of depression do not achieve remission with the first treatment they receive. The predominant pessimism about the actual feasibility of the personalization of treatment of depression in routine clinical practice has recently been tempered by some secondary analyses of databases from clinical trials, using approaches such as individual patient data meta-analysis and machine learning, which indicate that some variables may indeed contribute to the identification of patients who are likely to respond differently to various antidepressant drugs or to antidepressant medication vs. specific psychotherapies. The need to develop decision support tools guiding the personalization of treatment of depression has been recently reaffirmed, and the point made that these tools should be developed through large observational studies using a comprehensive battery of self-report and clinical measures. The present paper aims to describe systematically the salient domains that should be considered in this effort to personalize depression treatment. For each domain, the available research evidence is summarized, and the relevant assessment instruments are reviewed, with special attention to their suitability for use in routine clinical practice, also in view of their possible inclusion in the above-mentioned comprehensive battery of measures. The main unmet needs that research should address in this area are emphasized. Where the available evidence allows providing the clinician with specific advice that can already be used today to make the management of depression more personalized, this advice is highlighted. Indeed, some sections of the paper, such as those on neurocognition and on physical comorbidities, indicate that the modern management of depression is becoming increasingly complex, with several components other than simply the choice of an antidepressant and/or a psychotherapy, some of which can already be reliably personalized.

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

BACKGROUND

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

METHODS

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

RESULTS

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

LIMITATIONS

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

CONCLUSIONS

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

Ecological momentary assessment of daily drug use and harm reduction service utilization among people who inject drugs in non-urban areas: A concurrent mixed-method feasibility study

BACKGROUND

Ecological momentary assessments (EMA) can improve data accuracy and be useful for understanding the real-time co-occurrence of drug use and harm reduction service utilization among people who inject drugs (PWID); however, feasibility and acceptability of EMA in this population is unknown.

METHODS

We conducted qualitative interviews (n = 45) and EMA surveys (n = 38) with PWID in cities and towns outside of Massachusetts' and Rhode Island's capital cities to 1) assess EMA feasibility and acceptability and 2) examine day-level correlations between drug use and harm reduction service utilization.

RESULTS

Qualitative and quantitative data demonstrated that a 14-day EMA study was both feasible and acceptable. Interviews identified housing instability and related disruptions in cellphone access as challenges to consistent EMA participation. In the 14-day EMA study, EMA completion was high (mean = 10.1 days,SD = 5.3). High completion was associated with higher education (p = 0.005), receiving EMA via SMS text (vs. email, p = 0.017), and not having injected crack in the past month (p = 0.026). Of those who responded (n = 29), 100 % reported willingness to participate in a similar future study. Past 24 -h use of harm reduction services was positively associated with past 24 -h injection drug use (p = 0.013), but not past 24 -h syringe sharing (p = 0.197).

CONCLUSION

Findings support the acceptability, feasibility, and potential utility of EMA for understanding daily experiences of PWID. Future studies should explore strategies to overcome structural barriers to maximize EMA participation, and assess how injection practices, syringe sharing, and use of harm reduction services interact to impact health risks in larger and diverse samples of PWID.

Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health

This conceptual paper describes the current state of mental health services, identifies critical problems, and suggests how to solve them. I focus on the potential contributions of artificial intelligence and precision mental health to improving mental health services. Toward that end, I draw upon my own research, which has changed over the last half century, to highlight the need to transform the way we conduct mental health services research. I identify exemplars from the emerging literature on artificial intelligence and precision approaches to treatment in which there is an attempt to personalize or fit the treatment to the client in order to produce more effective interventions.

Biased Affective Forecasting: A Potential Mechanism That Enhances Resilience and Well-Being

According to a growing body of studies, people's ability to forecast future emotional experiences is generally biased. Nonetheless, the existing literature has mainly explored affective forecasting in relation to specific events, whereas little is still known about the ability to make general estimations of future emotional states. Based on existing evidence suggesting future-oriented disposition as a key factor for mental health, the aims of the current study were (1) to investigate the relationship between negative (NA) and positive (PA) affective forecasting biases and perceived psychological well-being, and (2) to explore whether positively biased predictions are associated with resilience and foster one's skills to cope with stressful events. To do so, we asked 85 undergraduate students to forecast PA and NA over 2 weeks, as well as to report their daily affect through a web-based Ecological Momentary Assessment. According to the results, positively biased PA forecasting (i.e., overestimating positive emotional states) was associated with greater perceived psychological well-being and higher resilience. When high levels of stress were experienced, participants holding an optimistic, yet biased, estimation of future PA were more likely to successfully manage stressors, thus maintaining lower levels of NA and higher levels of positive emotions. We suggest that positively biased PA forecasting is an adaptive cognitive distortion that boosts people's resilience and mental health, thus opening new avenues for the promotion of psychological well-being.

Affect Recall Bias: Being Resilient by Distorting Reality

Background

According to a growing body of literature, people are quite inaccurate in recalling past affective experiences. Nevertheless, the mechanism underlying this recall bias (i.e., the tendency to overestimate and/or underestimate positive or negative past emotional experiences) remains unclear, and its association with mental health has not been studied yet.

Methods

We adopted a smartphone-based Ecological Momentary Assessment to monitor daily affect (n = 92) and investigate the association between affect recall bias, mental health and resilience.

Results

While the tendency to overestimate negative affective experiences was observed in participants reporting mild depressive symptoms, positive affect (PA) overestimation as compared to PA underestimation was associated with better mental health (i.e. higher psychological well-being and lower depressive and anxiety symptoms) through the enhancement of resilience. Furthermore, positively biased participants (i.e. PA over estimators) benefited from greater well-being, even when compared to accurate individuals.

Conclusions

While people appear to use retrospective PA overestimation as a strategy to enhance well-being and resilience, they are not likely to underestimate past negative experiences to feel better. Accordingly, owning an optimistic vision of the past may represent an adaptive “distortion” of reality that fosters people’s mental health. The clinical implications of cultivating PA and learning strategies to regulate both negative and positive emotions are discussed.

The Use of a Virtual Reality Platform for the Assessment of the Memory Decline and the Hippocampal Neural Injury in Subjects with Mild Cognitive Impairment: The Validity of Smart Aging Serious Game (SASG)

Due to the lack of pharmacological treatment for dementia, timely detection of subjects at risk can be of seminal importance for preemptive rehabilitation interventions. The aim of the study was to determine the usability of the smart aging serious game (SASG), a virtual reality platform, in assessing the cognitive profile of an amnestic mild cognitive impairment (aMCI) population, its validity in discriminating aMCI from healthy controls (HC), and in detecting hippocampal degeneration, a biomarker of clinical progression towards dementia. Thirty-six aMCI and 107 HC subjects were recruited and administered the SASG together with a neuropsychological evaluation. All aMCI and 30 HC subjects performed also an MRI for hippocampal volume measurement. Results showed good usability of the SASG despite the low familiarity with technology in both groups. ROC curve analyses showed similar discriminating abilities for SASG and gold standard tests, and a greater discrimination ability compared to non-specific neuropsychological tests. Finally, linear regression analysis revealed that the SASG outperformed the Montreal cognitive assessment test (MoCA) in the ability to detect neuronal degeneration in the hippocampus on the right side. These data show that SASG is an ecological task, that can be considered a digital biomarker providing objective and clinically meaningful data about the cognitive profile of aMCI subjects.

Sensors Capabilities, Performance, and Use of Consumer Sleep Technology

Sleep is crucial for the proper functioning of bodily systems and for cognitive and emotional processing. Evidence indicates that sleep is vital for health, well-being, mood, and performance. Consumer sleep technologies (CSTs), such as multisensory wearable devices, have brought attention to sleep and there is growing interest in using CSTs in research and clinical applications. This article reviews how CSTs can process information about sleep, physiology, and environment. The growing number of sensors in wearable devices and the meaning of the data collected are reviewed. CSTs have the potential to provide opportunities to measure sleep and sleep-related physiology on a large scale.

mHealth in affective disorders: hype or hope? A focused narrative review

The constant growth and widespread availability of mobile technologies (i.e. smartphones and wearables) over the last decades have been a subject of intense interest and research in the affective disorders (AD) field. The potential of mHealth for collecting a new kind of passive and active information while providing cost-effective and tailored interventions have raised many hopes. However, until now, despite some encouraging results, research in the field has not been translated to reach real-world clinical settings or to develop additional evidence-based mHealth tools for people suffering from AD. Meanwhile, commercial untested apps and wearables are already being increasingly used and adopted by patients for the self-management of their illnesses. Hence, there is a latent need and demand from service users to integrate mHealth in their care, which the field cannot yet fulfil. In this article, through a focused narrative review, we discuss the evidence available for the use, validity and efficacy of mHealth tools in AD. Challenges in the academic field hampering the advancement of these technologies and its implementation into clinical practice are discussed. Lastly, we propose a framework to overcome these issues, which may facilitate mHealth solutions reaching service users.

Experienced Burden of and Adherence to Smartphone-Based Ecological Momentary Assessment in Persons with Affective Disorders

(1) Background: The use of smartphone-based ecological momentary assessment (EMA) questionnaires in affective disorder research has rapidly increased. Though, a thorough understanding of experienced burden of and adherence to EMA is crucial in determining the usefulness of EMA. (2) Methods: Persons with current affective disorders (n = 100), remitted persons (n = 190), and healthy controls (n = 94) participated in a smartphone-based EMA two-week monitoring period. Our primary outcomes were (momentary) perceived burden of and adherence to EMA. (3) Results: In the whole sample, lower positive and higher negative affect were associated with slightly higher levels of perceived momentary burden (B = -0.23 [95%CI = -0.27-0.19], B = 0.30 [95%CI = 0.24-0.37], respectively). The persons with current affective disorders reported slightly higher levels of experienced momentary burden (Mdn = 1.98 [IQR = 1.28-2.57]), than the remitted persons (Mdn = 1.64 [IQR = 1.11-2.24]) and healthy controls (Mdn = 1.28 [IQR = 1.04-1.92]). Nevertheless, the persons with current affective disorders still showed very high adherence rates (Mdn = 94.3% [IQR = 87.9-97.1]), at rates on a par with the remitted persons (Mdn = 94.3% [IQR = 90.0-97.1]) and healthy controls (Mdn = 94.3% [IQR = 90.0-98.6]). (4) Discussion: Frequent momentary questionnaires of mental well-being are slightly more burdensome to the persons with current affective disorders, but this does not seem to have a negative impact on adherence. Their high rate of adherence to EMA-which was similar to that in remitted persons and healthy controls -suggests that it is feasible to apply (short-duration) EMA.