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

Evaluation of completely online psychotherapy with app-support versus therapy as usual for clients with depression or anxiety disorder: A retrospective matched cohort study investigating the effectiveness, efficiency, client satisfaction, and costs

INTRODUCTION

Depressive and anxiety disorders are common mental disorders ranking among the leading causes of global disease burden. Not all clients currently benefit from therapy and clients are looking for modern ways of therapy. Online psychotherapy is a promising option for better meeting clients' needs. Recently, a new psychotherapy concept has emerged that combines videoconferencing sessions with support through a mobile application. The latter allows for ecological momentary assessments and interventions, facilitates communication between patients and therapists in between sessions through chat, and allows for incorporating feedback-informed treatment principles.

MATERIAL AND METHODS

The study was a retrospective observational matched cohort study, comparing online psychotherapy with Therapy As Usual (TAU) for clients with depressive or anxiety disorders. Data were obtained via questionnaires, which are part of standard clinical care. Primary outcomes included general mental functioning, and symptoms of depression and anxiety. Secondary outcomes were efficiency, client satisfaction, and therapy costs. Primary endpoints were analyzed using linear mixed models analysis, with an interaction term between time and group. Secondary outcomes were analyzed using linear regression.

RESULTS

Larger improvements were observed in the online compared to the TAU group for general mental functioning and depressive disorder (i.e., General mental functioning: B = -8.50, 95 CI: -15.01 - -1.97, p = 0.011; Depressive disorder: B = - 3.66, 95 % CI: -5.79 - -1.54p < 0.01). No significant differences in change over time between the two groups were observed for anxiety disorder (B = -3.64, 95 % CI: (-13.10 - 5.82) p = 0.447). The total number of sessions was significantly higher in the online psychotherapy group than in TAU (B = 3.71, p < 0.01), although clients were matched on treatment time in weeks. Treatment session duration in minutes was comparable across the groups.

DISCUSSION

Online psychotherapy with app support showed to be a promising alternative to TAU for depressive and anxiety disorders. More research is needed to evaluate the effectiveness, cost-effectiveness and client satisfaction of online psychotherapy compared to TAU, such as randomized controlled trials or studies multiple baseline series designs, and in-depth qualitative research.

Differential effects of everyday-life social support on chronic pain

BACKGROUND

Social support is a multidimensional construct encompassing emotional support as well as pain-focused care and attention, also known as solicitous support. One the one hand, social support is widely believed to positively influence pain symptoms, their intensity, and the ability to cope and influence pain. On the other hand, social support can be negative if it conflicts with the patient's needs or even causes discomfort. How different types of social support influence pain is not very well understood especially because most of the present research originates from laboratory studies, raising uncertainties about its generalizability to the everyday life of individuals with chronic pain.

METHODS

Here, we tested the effects of emotional, solicitous, and negative social support on pain intensity cross-sectionally in everyday life. We collected data from 20 patients with acute complex regional pain syndrome using a smartphone-based Ecological Momentary Assessment with up to 30 survey prompts over a period of five consecutive days.

RESULTS

Our results showed that solicitous social support decreased pain, in particular in male patients. Emotional support was beneficial on pain in women but not in men.

CONCLUSIONS

Taken together, these findings highlight the differential effects of social support in every-day life on chronic pain.

The integration of geographic methods and ecological momentary assessment in public health research: A systematic review of methods and applications

With the widespread prevalence of mobile devices, ecological momentary assessment (EMA) can be combined with geospatial data acquired through geographic techniques like global positioning system (GPS) and geographic information system. This technique enables the consideration of individuals' health and behavior outcomes of momentary exposures in spatial contexts, mostly referred to as "geographic ecological momentary assessment" or "geographically explicit EMA" (GEMA). However, the definition, scope, methods, and applications of GEMA remain unclear and unconsolidated. To fill this research gap, we conducted a systematic review to synthesize the methodological insights, identify common research interests and applications, and furnish recommendations for future GEMA studies. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines to systematically search peer-reviewed studies from six electronic databases in 2022. Screening and eligibility were conducted following inclusion criteria. The risk of bias assessment was performed, and narrative synthesis was presented for all studies. From the initial search of 957 publications, we identified 47 articles included in the review. In public health, GEMA was utilized to measure various outcomes, such as psychological health, physical and physiological health, substance use, social behavior, and physical activity. GEMA serves multiple research purposes: 1) enabling location-based EMA sampling, 2) quantifying participants' mobility patterns, 3) deriving exposure variables, 4) describing spatial patterns of outcome variables, and 5) performing data linkage or triangulation. GEMA has advanced traditional EMA sampling strategies and enabled location-based sampling by detecting location changes and specified geofences. Furthermore, advances in mobile technology have prompted considerations of additional sensor-based data in GEMA. Our results highlight the efficacy and feasibility of GEMA in public health research. Finally, we discuss sampling strategy, data privacy and confidentiality, measurement validity, mobile applications and technologies, and GPS accuracy and missing data in the context of current and future public health research that uses GEMA.

Using Multimodal Assessments to Reevaluate Depression Designations for Spine Surgery Candidates

BACKGROUND

Depression is common in spine surgery candidates and may influence postoperative outcomes. Ecological momentary assessments (EMAs) can overcome limitations of existing depression screening methods (e.g., recall bias, inaccuracy of historical diagnoses) by longitudinally monitoring depression symptoms in daily life. In this study, we compared EMA-based depression assessment with retrospective self-report (a 9-item Patient Health Questionnaire [PHQ-9]) and chart-based depression diagnosis in lumbar spine surgery candidates. We further examined the associations of each depression assessment method with surgical outcomes.

METHODS

Adult patients undergoing lumbar spine surgery (n = 122) completed EMAs quantifying depressive symptoms up to 5 times daily for 3 weeks preoperatively. Correlations (rank-biserial or Spearman) among EMA means, a chart-based depression history, and 1-time preoperative depression surveys (PHQ-9 and Psychache Scale) were analyzed. Confirmatory factor analysis was used to categorize PHQ-9 questions as somatic or non-somatic; subscores were compared with a propensity score-matched general population cohort. The associations of each screening modality with 6-month surgical outcomes (pain, disability, physical function, pain interference) were analyzed with multivariable regression.

RESULTS

The association between EMA Depression scores and a depression history was weak (rrb = 0.34 [95% confidence interval (CI), 0.14 to 0.52]). Moderate correlations with EMA-measured depression symptoms were observed for the PHQ-9 (rs = 0.51 [95% CI, 0.37 to 0.63]) and the Psychache Scale (rs = 0.68 [95% CI, 0.57 to 0.76]). Compared with the matched general population cohort, spine surgery candidates endorsed similar non-somatic symptoms but significantly greater somatic symptoms on the PHQ-9. EMA Depression scores had a stronger association with 6-month surgical outcomes than the other depression screening modalities did.

CONCLUSIONS

A history of depression in the medical record is not a reliable indication of preoperative depression symptom severity. Cross-sectional depression assessments such as PHQ-9 have stronger associations with daily depression symptoms but may conflate somatic depression symptoms with spine-related disability. As an alternative to these methods, mobile health technology and EMAs provide an opportunity to collect real-time, longitudinal data on depression symptom severity, potentially improving prognostic accuracy.

LEVEL OF EVIDENCE

Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Linguistic style as a digital marker for depression severity: An ambulatory assessment pilot study in patients with depressive disorder undergoing sleep deprivation therapy

BACKGROUND

Digital phenotyping and monitoring tools are the most promising approaches to automatically detect upcoming depressive episodes. Especially, linguistic style has been seen as a potential behavioral marker of depression, as cross-sectional studies showed, for example, less frequent use of positive emotion words, intensified use of negative emotion words, and more self-references in patients with depression compared to healthy controls. However, longitudinal studies are sparse and therefore it remains unclear whether within-person fluctuations in depression severity are associated with individuals' linguistic style.

METHODS

To capture affective states and concomitant speech samples longitudinally, we used an ambulatory assessment approach sampling multiple times a day via smartphones in patients diagnosed with depressive disorder undergoing sleep deprivation therapy. This intervention promises a rapid change of affective symptoms within a short period of time, assuring sufficient variability in depressive symptoms. We extracted word categories from the transcribed speech samples using the Linguistic Inquiry and Word Count.

RESULTS

Our analyses revealed that more pleasant affective momentary states (lower reported depression severity, lower negative affective state, higher positive affective state, (positive) valence, energetic arousal and calmness) are mirrored in the use of less negative emotion words and more positive emotion words.

CONCLUSION

We conclude that a patient's linguistic style, especially the use of positive and negative emotion words, is associated with self-reported affective states and thus is a promising feature for speech-based automated monitoring and prediction of upcoming episodes, ultimately leading to better patient care.

Mixed-Methods Assessment of Maternal Anxiety During the First 8 Weeks After Birth

OBJECTIVE

To describe and compare the experiences of postpartum anxiety among women with generalized anxiety and postpartum-specific anxiety.

DESIGN

Prospective, longitudinal, mixed methods.

SETTING

Academic tertiary center in the mid-Atlantic United States. Study activities were remote.

PARTICIPANTS

Women at 1 to 8 weeks after birth (N = 34).

METHODS

We used mobile surveys to measure daily anxiety ratings and responses to open-ended, theory-driven questions about anxiety. We used the cutoff scores on the State-Trait Anxiety Inventory and Postpartum Specific Anxiety Scale administered 8 weeks after birth to determine the presence of generalized and postpartum-specific anxiety. Participants' responses were analyzed with qualitative description and sorted by anxiety questionnaire scores at 8 weeks after birth. We compared qualitative findings between participants with generalized anxiety and postpartum-specific anxiety.

RESULTS

Participants with generalized anxiety had high levels of overwhelm and felt ill-equipped to handle daily stressors, whereas those with postpartum-specific anxiety felt adept at coping. Participants with generalized anxiety lacked emotional and physical support, and those with postpartum-specific anxiety reported more physical but variable emotional support. Sources of daily anxiety in participants with postpartum-specific anxiety were infant-centric (e.g., infant health, end of maternity leave, breastfeeding), whereas anxiety sources for participants with generalized anxiety were varied (e.g., self-health, partner concerns). Participants with generalized anxiety versus postpartum-specific anxiety were more likely to be multiparous and have comorbid depression symptoms.

CONCLUSION

Symptoms, levels of perceived support, and sources of anxiety differed between participants with generalized versus postpartum-specific anxiety. Our findings can inform postpartum anxiety screening strategies and support interventions.

Heart rate vARiability and physical activity in inpatient treatMent of burnOut and DepressIon (HARMODI): protocol of a cross-sectional study with up to 8-week follow up

INTRODUCTION

Chronic stress can cause an imbalance within the autonomic nervous system, thereby affecting cardiovascular and mental health. Physical activity (PA) may have a positive effect on the autonomic nervous system and stress-related disorders, such as depression and burnout. Heart rate variability (HRV) is a non-invasive marker of the autonomic nervous system. However, limited and inconsistent data exist on the exact relationship between HRV, PA and depression and burnout symptoms. The HARMODI study aims to explore whether HRV is a feasible marker of depression and burnout symptoms and aims to evaluate the role of PA in the treatment of stress-related disorders.

METHODS AND ANALYSES

This is an observational study with a cross-sectional up to 8 week follow-up study design. A total of 153 patients, undergoing psychiatric inpatient treatment with burnout syndrome (Z73) and depressive episode (F32 or F33) or adjustment disorder (F43.2), will be recruited. Data on depression and burnout symptoms, HRV recordings (24-hour, supine, standing and exercise stress test), cognitive function, cardiorespiratory fitness, cardiovascular health, balance and strength will be collected at baseline (T1) and after up to 8 weeks (T2). Continuous data on PA and Ecological Momentary Assessments of exhaustion, mood and tension will be monitored daily throughout inpatient treatment. Multiple regression models, adjusted for potential confounders, will assess the association between HRV as the primary outcome, PA and depression and burnout severity score.

ETHICS AND DISSEMINATION

The protocol has been approved by Swiss Ethics Committee, Cantonal Ethics Committee Zürich. Results of HARMODI will be disseminated through peer-reviewed journals and conference presentations.

TRIAL REGISTRATION NUMBER

NCT05874856.

Working mechanisms of the use and acceptability of ecological momentary interventions: a realist evaluation of a guided self-help ecological momentary intervention targeting self-esteem

BACKGROUND

Technology improves accessibility of psychological interventions for youth. An ecological momentary intervention (EMI) is a digital intervention geared toward intervening in daily life to enhance the generalizability and ecological validity, and to be able to intervene in moments most needed. Identifying working mechanisms of the use of ecological momentary interventions might generate insights to improve interventions.

METHODS

The present study investigates the working mechanisms of the use and acceptability of an ecological momentary intervention, named SELFIE, targeting self-esteem in youth exposed to childhood trauma, and evaluates under what circumstances these mechanisms of use and acceptability do or do not come into play. A realist evaluation approach was used for developing initial program theories (data: expert interviews and a stakeholders focus group), and subsequently testing (data: 15 interviews with participants, a focus group with therapists, debriefing questionnaire), and refining them.

RESULTS

The SELFIE intervention is offered through a smartphone application enabling constant availability of the intervention and thereby increasing accessibility and feasibility. When the intervention was offered on their personal smartphone, this enhanced a sense of privacy and less hesitance in engaging with the app, leading to increased disclosure and active participation. Further, the smartphone application facilitates the practice of skills in daily life, supporting the repeated practice of exercises in different situations leading to the generalizability of the effect. Buffering against technical malfunction seemed important to decrease its possible negative effects.

CONCLUSIONS

This study enhanced our understanding of possible working mechanisms in EMIs, such as the constant availability supporting increased accessibility and feasibility, for which the use of the personal smartphone was experienced as a facilitating context. Hereby, the current study contributes to relatively limited research in this field. For the field to move forward, mechanisms of use, and acceptability of EMIs need to be understood. It is strongly recommended that alongside efficacy trials of an EMI on specific target mechanisms, a process evaluation is conducted investigating the working mechanisms of use.

TRIAL REGISTRATION

The current paper reports on a realist evaluation within the SELFIE trial (Netherlands Trial Register NL7129 (NTR7475)).

STROBE-GEMA: a STROBE extension for reporting of geographically explicit ecological momentary assessment studies

CONTEXT

While a growing body of research has been demonstrating how exposure to social and built environments relate to various health outcomes, specific pathways generally remain poorly understood. But recent technological advancements have enabled new study designs through continuous monitoring using mobile sensors and repeated questionnaires. Such geographically explicit momentary assessments (GEMA) make it possible to link momentary subjective states, behaviors, and physiological parameters to momentary environmental conditions, and can help uncover the pathways linking place to health. Despite its potential, there is currently no review of GEMA studies detailing how location data is used to measure environmental exposure, and how this in turn is linked to momentary outcomes of interest. Moreover, a lack of standard reporting of such studies hampers comparability and reproducibility.

AIMS

The objectives of this research were twofold: 1) conduct a systematic review of GEMA studies that link momentary measurement with environmental data obtained from geolocation data, and 2) develop a STROBE extension guideline for GEMA studies.

METHOD

The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Inclusion criteria consisted of a combination of repeated momentary measurements of a health state or behavior with GPS coordinate collection, and use of these location data to derive momentary environmental exposures. To develop the guideline, the variables extracted for the systematic review were compared to elements of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and CREMAS (CRedibility of Evidence from Multiple Analyses of the Same data) checklists, to provide a new guideline for GEMA studies. An international panel of experts participated in a consultation procedure to collectively develop the proposed checklist items. RESULTS AND DEVELOPED TOOLS: A total of 20 original GEMA studies were included in the review. Overall, several key pieces of information regarding the GEMA methods were either missing or reported heterogeneously. Our guideline provides a total of 27 categories (plus 4 subcategories), combining a total of 70 items. The 22 categories and 32 items from the original STROBE guideline have been integrated in our GEMA guideline. Eight categories and 6 items from the CREMAS guideline have been included to our guideline. We created one new category (namely "Consent") and added 32 new items specific to GEMA studies.

CONCLUSIONS AND RECOMMENDATIONS

This study offers a systematic review and a STROBE extension guideline for the reporting of GEMA studies. The latter will serve to standardize the reporting of GEMA studies, as well as facilitate the interpretation of results and their generalizability. In short, this work will help researchers and public health professionals to make the most of this method to advance our understanding of how environments influence health.

Exploring biologically oriented precision mental health initiatives for the care of patients with eating disorders: A narrative review

OBJECTIVE

Eating disorders (EDs) represent a major public health burden. Increasingly, studies suggest mental health (MH) fields are failing to improve the effectiveness of treatments and that alternative models of care must be considered. Precision mental health (PMH) seeks to tailor treatment to individual needs and relies on a comprehensive understanding of the neurobiological and physiological underpinnings of mental illness.

METHODS

In this narrative review, published literature with focus on biological application of PMH strategies for EDs is reviewed and summarised.

RESULTS

A total of 39 articles were retained for the review covering a variety of themes with relevance to PMH. Many studies of biological markers with PMH applicability focused on anorexia nervosa. Although a variety of potential PMH research applications were identified, the review failed to identify any evidence of implementation into routine ED practice.

CONCLUSIONS

Despite the theoretical merit of biological application of PMH in ED treatment, clinical applications for standard practice are lacking. There is a need to invest further in studies that seek to identify biological markers and investigate neurobiological underpinnings of disease in hopes of targeting and developing treatments that can be better tailored to the individualised needs of patients.

Characterizing Longitudinal Patterns in Cognition, Mood, And Activity in Depression With 6-Week High-Frequency Wearable Assessment: Observational Study

BACKGROUND

Cognitive symptoms are an underrecognized aspect of depression that are often untreated. High-frequency cognitive assessment holds promise for improving disease and treatment monitoring. Although we have previously found it feasible to remotely assess cognition and mood in this capacity, further work is needed to ascertain the optimal methodology to implement and synthesize these techniques.

OBJECTIVE

The objective of this study was to examine (1) longitudinal changes in mood, cognition, activity levels, and heart rate over 6 weeks; (2) diurnal and weekday-related changes; and (3) co-occurrence of fluctuations between mood, cognitive function, and activity.

METHODS

A total of 30 adults with current mild-moderate depression stabilized on antidepressant monotherapy responded to testing delivered through an Apple Watch (Apple Inc) for 6 weeks. Outcome measures included cognitive function, assessed with 3 brief n-back tasks daily; self-reported depressed mood, assessed once daily; daily total step count; and average heart rate. Change over a 6-week duration, diurnal and day-of-week variations, and covariation between outcome measures were examined using nonlinear and multilevel models.

RESULTS

Participants showed initial improvement in the Cognition Kit N-Back performance, followed by a learning plateau. Performance reached 90% of individual learning levels on average 10 days after study onset. N-back performance was typically better earlier and later in the day, and step counts were lower at the beginning and end of each week. Higher step counts overall were associated with faster n-back learning, and an increased daily step count was associated with better mood on the same (P<.001) and following day (P=.02). Daily n-back performance covaried with self-reported mood after participants reached their learning plateau (P=.01).

CONCLUSIONS

The current results support the feasibility and sensitivity of high-frequency cognitive assessments for disease and treatment monitoring in patients with depression. Methods to model the individual plateau in task learning can be used as a sensitive approach to better characterize changes in behavior and improve the clinical relevance of cognitive data. Wearable technology allows assessment of activity levels, which may influence both cognition and mood.

Feasibility of a novel blended-care intervention for fatigue after acquired brain injury: a pilot study of the Tied by Tiredness intervention

PURPOSE

Evidence-based treatments for fatigue after brain injury are scarce and often not personalized. An approach to foster personalization is Experience Sampling Methodology (ESM), consisting of repeated daily measurements of fatigue and related factors in daily life. We investigated the feasibility and usability of a novel six-week ESM-based intervention for fatigue after brain injury.

MATERIALS AND METHODS

Ten individuals with acquired brain injury (six men; four women) aged between 36-70 years (M = 53.3, SD = 12.9) used a mHealth application for three days each week during six-weeks; seven completed the intervention. Momentary fatigue, activities, mood, worrying, and social context were assessed with ESM and participants received weekly personalized feedback by a therapist..

RESULTS

56% of ESM-questionnaires (568/1008) were completed, providing detailed insights into individual fatigue patterns. No statistically significant decrease in response rate was found over the course of treatment. Qualitative feedback from participants revealed increased insight into factors underlying fatigue, and no problems with treatment duration or difficulties using the app. Five participants showed a decline in fatigue level during treatment.

CONCLUSIONS

This pilot study provides initial support for the feasibility and usability of this novel blended-care intervention, aimed at alleviating fatigue through personalized feedback and treatment strategies.

The Effect of Everyday-Life Social Contact on Pain

Pain is a biopsychosocial phenomenon, resulting from the interplay between physiological and psychological processes and social factors. Given that humans constantly interact with others, the effect of social factors is particularly relevant. Documenting the significance of the social modulation of pain, an increasing number of studies have investigated the effect of social contact on subjective pain intensity and pain-related physiological changes. While evidence suggests that social contact can alleviate pain, contradictory findings indicate an increase in pain intensity and a deterioration of pain coping strategies. This evidence primarily stems from studies examining the effect of social contact on pain within highly controlled laboratory conditions. Moreover, pain assessments often rely on one-time subjective reports of average pain intensity across a predefined period. Ecological momentary assessments (EMAs) can circumvent these problems, as they can capture diverse aspects of behavior and experiences multiple times a day, in real time, with high resolution, and within naturalistic and ecologically valid settings. These multiple measures allow for the examination of fluctuations of pain symptoms throughout the day in relation to affective, cognitive, behavioral, and social factors. In this opinion paper, we review the current state and future relevance of EMA-based social pain research in daily life. Specifically, we examine whether everyday-life social support reduces or enhances pain. The first part of the paper provides a comprehensive overview of the use of EMA in pain research and summarizes the main findings. The review of the relatively limited number of existing EMA studies shows that the association between pain and social contact in everyday life depends on numerous factors, including pain syndromes, temporal dynamics, the nature of social interactions, and characteristics of the interaction partners. In line with laboratory research, there is evidence that everyday-life social contact can alleviate, but also intensify pain, depending on the type of social support. Everyday-life emotional support seems to reduce pain, while extensive solicitous support was found to have opposite effects. Moreover, positive short-term effects of social support can be overshadowed by other symptoms such as fatigue. Overall, gathering and integrating experiences from a patient's social environment can offer valuable insights. These insights can help interpret dynamics in pain intensity and accompanying symptoms such as depression or fatigue. We conclude that factors determining the reducing versus enhancing effects of social contact on pain need to be investigated more thoroughly. We advocate EMA as the assessment method of the future and highlight open questions that should be addressed in future EMA studies on pain and the potential of ecological momentary interventions for pain treatment.

Comparisons of Self-Report With Objective Measurements Suggest Faster Responding but Little Change in Response Quality Over Time in Ecological Momentary Assessment Studies

Response times (RTs) to ecological momentary assessment (EMA) items often decrease after repeated EMA administration, but whether this is accompanied by lower response quality requires investigation. We examined the relationship between EMA item RTs and EMA response quality. In one data set, declining response quality was operationalized as decreasing correspondence over time between subjective and objective measures of blood glucose taken at the same time. In a second EMA study data set, declining response quality was operationalized as decreasing correspondence between subjective ratings of memory test performance and objective memory test scores. We assumed that measurement error in the objective measures did not increase across time, meaning that decreasing correspondence across days within a person could be attributed to lower response quality. RTs to EMA items decreased across study days, while no decrements in the mean response quality were observed. Decreasing EMA item RTs across study days did not appear problematic overall.

The use of ecological momentary assessment for family caregivers of adults with chronic conditions: A systematic review

Background

Ecological momentary assessment (EMA) as a real-time data collection method can provide insight into the daily experiences of family caregivers.

Purpose

This systematic review aimed to synthesize studies involving EMA completed by family caregivers of adults with chronic conditions.

Methods

A systematic search was conducted within six databases for articles published from the inception of the database through September 2023. We extracted the characteristics of the included studies and data on EMA-specific methods to determine the quality of the included studies.

Results

A total of 12 studies involving EMA completed by family caregivers of adults with chronic conditions were identified, with almost all studies focused on caregivers of persons with Alzheimer's or dementia-related conditions. The average compliance rate across the included studies was 75%, below the recommended rate. In addition, most of the included studies did not collect the family caregivers' daily activities and care contexts in their responses (i.e., affect, stress, well-being, care demand, and fatigue) to the EMA prompts.

Discussion

This review showed that using EMA to collect information on family caregivers of adults with chronic health conditions appeared feasible and acceptable. However, the methodology or design of using EMA to collect caregiver information in this population is still preliminary. The limited number of existing studies that have used EMA to capture the daily experiences of family caregivers does not provide key information that could improve understanding of caregivers' emotional experiences and well-being in real-life situations. We identified gaps in the literature that warrant additional EMA studies for this population.

If it Ain't Broke, Don't Fix it: Positive Versus Negative Emotion Regulation in Daily Life and Depressive Symptoms

BACKGROUND

Despite the importance of positive emotions for affective psychopathology, prior research primarily focused on negative emotion regulation. To address this gap, this ecological momentary assessment study compared a broad set of emotion regulation strategies in the context of positive versus negative emotions regarding their effectiveness and associations with depressive symptoms.

METHODS

We analyzed data from 1066 participants who were notified five times daily for seven consecutive days to complete a smartphone survey assessing their predominant emotions, strategies to regulate them, and subsequent emotional outcomes.

RESULTS

Findings show that the effectiveness of most regulation strategies depended on whether the emotional context was positive or negative. While acceptance and savoring predicted improved emotional outcomes across emotional contexts, reappraisal and problem-solving were associated with deteriorated emotional outcomes and increased depressive symptoms when regulating positive but not negative emotions.

LIMITATIONS

Future studies should replicate our findings in demographically and culturally diverse clinical samples to improve generalizability.

CONCLUSION

These results emphasize that strategies effective for regulating negative emotions may be less helpful in the context of positive emotions. Thus, context-specific interventions may be a promising approach to improve the treatment of affective disorders.

Mobile-based ecological momentary assessment and intervention: bibliometric analysis

Objective

The aim of this article was to review existing documents in the field of mobile-based EMA and EMI, provide an overview of current hot topics, and predict future development trends.

Methods

We conducted a bibliometric study on mobile-based EMA and EMI publications that were collected from the Web of Science Core Collection database. Biblioshiny and CiteSpace were utilized to analyze scientific productions, leading sources, authors, affiliations, documents, research hot topics, keywords, and trend topics.

Results

A total of 2222 documents related to EMA and EMI published between 1992 and 2023 were retrieved. In recent years, scholarly publications have generally increased in mobile-based EMA and EMI research, particularly in the last decade. JMIR mHealth and uHealth (n=86), as well as JMIR (n=73), showed the highest number of publications. The United States (n=1038), Germany (n=218) and Netherlands (n=175) were leading countries. Regarding keyword co-occurrence and trend topics analysis, mental health, health behaviors, and feasibility were hot topics in mobile-based EMA and EMI research. Future research trends included using EMA for tailoring EMI, just-in-time adaptive interventions (JITAI), and digital phenotyping.

Conclusion

This bibliometric study on mobile-based EMA and EMI is a valuable resource for understanding the field's evolution and future trends. Our analysis indicates that EMA and EMI have great potential in health behaviors and mental health, but implementation should consider feasibility and reactivity issues carefully. Emerging trends include EMA-tailored EMI, JITAI, and digital phenotyping. In the future, strengthening multidisciplinary cooperation will be necessary to promote the continued development of the field.

Affect dimensions and variability during major depressive episodes: Ecological momentary assessment of unipolar, bipolar, and borderline patients and healthy controls

Differentiating major depressive episodes (MDEs) of major depressive disorder (MDD), bipolar disorder (MDE/BD) and the MDEs comorbid with borderline personality disorder (MDE/BPD) is crucial for appropriate treatment, and knowledge of phenomenological differences may aid this. However, studies comparing affect experiences of these three patient groups and healthy subjects are scarce. In our study, participants (N = 114), including patients with MDD (n = 34), MDE/BD (n = 27), and MDE/BPD (n = 24), and healthy controls (HC, n = 29) responded to ecological momentary assessment (EMA) with ten circumplex model affect items ten times daily for seven days (7709 recordings). Explorative factor analysis resulted in two affect dimensions. The positive dimension included active, excited, cheerful (high arousal), and content (low arousal) affects, and the negative dimension irritated, angry, and nervous (high arousal) affects. Relative to HC, patients reported 3.5-fold negative affects (mean MDD 1.36 (SD 0.92), MDE/BD 1.43 (0.76), MDE/BPD 1.81 (0.95) vs. HC 0.44 (0.49) (p < 0.01)) but 0.5-fold positive affects (2.01 (0.90), 1.95 (0.89), 2.24 (1.03), vs. 3.2 (0.95), respectively (p < 0.01)). We used multilevel modelling. Negative-affect within-individual stability was lowest in MDE/BPD and highest in MDD. Negative affect predicted concurrent positive affect more in MDE/BPD than in MDD. Moderate size of subcohorts and no inpatients were limitations. Despite apparently similar MDEs, affective experiences may differ between BPD, BD, and MDD patients. Clinical subgroups of patients with depression may vary in affective instability and concurrent presence of negative and positive affects during depression.

Trial Participants' Perceptions of the Impact of Ecological Momentary Assessment on Smoking Behaviors: Qualitative Analysis

Background

Ecological momentary assessment (EMA) is an increasingly used tool for data collection in behavioral research, including smoking cessation studies. As previous addiction research suggests, EMA has the potential to elicit cue reactivity by triggering craving and increasing behavioral awareness. However, there has been limited evaluation of its potential influence on behavior.

Objective

By examining the perspectives of research participants enrolled in a tobacco treatment intervention trial, this qualitative analysis aims to understand the potential impact that EMA use may have had on smoking behaviors that may not have otherwise been captured through other study measures.

Methods

We performed a qualitative analysis of in-depth interviews with participants enrolled in a pilot randomized controlled trial of a tobacco treatment intervention that used SMS text messaging to collect EMA data on smoking behaviors. In the pilot randomized controlled trial, combustible cigarette and e-cigarette use and smoking-related cravings were measured as part of an EMA protocol, in which SMS text messaging served as a smoking diary. SMS text messaging was intended for data collection only and not designed to serve as part of the intervention. After a baseline assessment, participants were asked to record daily nicotine use for 12 weeks by responding to text message prompts that they received 4 times per day. Participants were prompted to share their experiences with the EMA text messaging component of the trial but were not directly asked about the influence of EMA on their behaviors. Transcripts were coded according to the principles of the framework for applied research. The codes were then examined, summarized, and grouped into themes based on the principles of grounded theory.

Results

Interviews were analyzed for 26 participants. The themes developed from the analysis suggested the potential for EMA, in the form of an SMS text messaging smoking diary, to influence participants' smoking behaviors. The perceived impacts of EMA text messaging on smoking behaviors were polarized; some participants emphasized the positive impacts of text messages on their efforts to reduce smoking, while others stressed the ways that text messaging negatively impacted their smoking reduction efforts. These contrasting experiences were captured by themes reflecting the positive impacts on smoking behaviors, including increased awareness of smoking behaviors and a sense of accountability, and the negative impacts on emotions and smoking behaviors, including provoking a sense of guilt and triggering smoking behaviors.

Conclusions

The collection of EMA smoking behavior data via SMS text messaging may influence the behaviors and perceptions of participants in tobacco treatment interventions. More research is needed to determine the magnitude of impact and mechanisms, to account for the potential effects of EMA. A broader discussion of the unintended effects introduced by EMA use is warranted among the research community.

Selecting an Ecological Momentary Assessment Platform: Tutorial for Researchers

BACKGROUND

Although ecological momentary assessment (EMA) has been applied in psychological research for decades, delivery methods have evolved with the proliferation of digital technology. Technological advances have engendered opportunities for enhanced accessibility, convenience, measurement precision, and integration with wearable sensors. Notwithstanding, researchers must navigate novel complexities in EMA research design and implementation.

OBJECTIVE

In this paper, we aimed to provide guidance on platform selection for clinical scientists launching EMA studies.

METHODS

Our team includes diverse specialties in child and adolescent behavioral and mental health with varying expertise on EMA platforms (eg, users and developers). We (2 research sites) evaluated EMA platforms with the goal of identifying the platform or platforms with the best fit for our research. We created a list of extant EMA platforms; conducted a web-based review; considered institutional security, privacy, and data management requirements; met with developers; and evaluated each of the candidate EMA platforms for 1 week.

RESULTS

We selected 2 different EMA platforms, rather than a single platform, for use at our 2 research sites. Our results underscore the importance of platform selection driven by individualized and prioritized laboratory needs; there is no single, ideal platform for EMA researchers. In addition, our project generated 11 considerations for researchers in selecting an EMA platform: (1) location; (2) developer involvement; (3) sample characteristics; (4) onboarding; (5) survey design features; (6) sampling scheme and scheduling; (7) viewing results; (8) dashboards; (9) security, privacy, and data management; (10) pricing and cost structure; and (11) future directions. Furthermore, our project yielded a suggested timeline for the EMA platform selection process.

CONCLUSIONS

This study will guide scientists initiating studies using EMA, an in vivo, real-time research tool with tremendous promise for facilitating advances in psychological assessment and intervention.

Digitally managing depression: A fully remote randomised attention-placebo controlled trial

Background

Depression is a common and disabling condition. Digital apps may augment or facilitate care, particularly in under-served populations. We tested the efficacy of juli, a digital self-management app for depression in a fully remote randomised controlled trial.

Methods

A pragmatic randomised controlled trial that included participants aged > 18 who self-identified as having depression and scored > 5 on the Patient Health Questionnaire-8. Participants were randomly assigned (1:1) to receive juli for 8 weeks or a limited attention-placebo control app. Our primary outcome was the difference in Patient Health Questionnaire-8 scores at 8 weeks. Secondary outcomes were remission, minimal clinically important difference, worsening of depression, and health-related quality of life. Analyses were per-protocol (primary), and modified and full intention-to-treat (secondary). The trial was registered at ISRCTN (ISRCTN12329547).

Results

Between May 2021 and January 2023, we randomised 908 participants. 662 completed the week 2 outcome assessment and were included in the modified intention-to-treat analysis, and 456 completed the week 8 outcome assessments (per-protocol). In the per-protocol analysis, the juli group had a greater reduction in Patient Health Questionnaire-8 score (10.78, standard deviation 6.26) than the control group (11.88, standard deviation 5.73) by week 8 (baseline adjusted β-coefficient -0.94, 95% CI: -1.87 to -0.22, p = 0.045). Achieving remission and a minimal clinically important difference was more likely in the juli group at 8 weeks (adjusted odds ratios 2.22, 95% CI: 1.45-3.39, p < 0.001 and 1.56, 95% CI: 1.08-2.27, p = 0.018, respectively). There were no between-group differences in health-related quality of life or worsening of depression. Modified and full intention-to-treat analyses found similar results, but the primary outcome was non-significant.

Conclusion

The use of juli for 8 weeks resulted in a small reduction in symptoms of depression compared with an attention-placebo control. The juli app is a digital self-management tool that could increase the accessibility of evidence-based depression treatments.

The Promise of Ecological Momentary Assessment to Improve Depression Management for Older Adults in Primary Care

Among older adults, depression is a common, morbid, and costly disorder. Older adults with depression are overwhelmingly treated by primary care providers with poor rates of remission and treatment response, despite attempts to improve care delivery through behavioral health integration and care management models. Given one in 10 older adults in primary care settings meet criteria for depression, there is a pressing need to improve the efficacy of depression treatment among affected individuals. Measurement-based care (i.e., the incorporation of systematic measurement of patient outcomes into treatment) for depressed older adults in primary care has had poor uptake, which at least partly underlies the limited efficacy of depression treatments. In this perspective, we discuss the proposal that ecological momentary assessment (EMA) may increase uptake of measurement-based care for depression in primary care, enhance the quality of clinical depression data, and lead to improvements in treatment efficacy without adding to providers' burden. We describe key issues related to EMA implementation and application in routine settings for depressed older adults, along with potential pitfalls and future research directions.

Time Effect on Acute Postoperative Pain After Total Knee Replacement Surgery: An Exploratory Study Using the Experience Sampling Method

OBJECTIVES

Acute postoperative pain (APP) is the main cause of postoperative dissatisfaction; however, traditional methods of pain assessment provide limited insights into the dynamics and development of APP. This study used the experience sampling method to understand the dynamics of APP over time in relation to various patient factors.

MATERIALS AND METHODS

Forty patients scheduled to undergo total knee replacement surgery were recruited in this study. Following an initial assessment, a short report questionnaire was sent to the patients through 10 digital alerts per day to assess the pain levels during 2 preoperative and the first 6 postoperative days. The data were analyzed using multilevel regression, including random intercept and slope.

RESULTS

Thirty-two patients submitted the prespecified minimum of 30% of their short reports, yielding 1217 records. The analysis revealed significant ( P <0.001) linear and quadratic decreases in APP and a quadratic time effect. The lowest between-day and within-day pain levels were observed on postoperative day 4.8 and during the time slot 3.8 or ~19:15, respectively. Significant random intercepts and slopes were noted, indicating variations in the mean pain level between patients and a decrease in pain. None of the 10 patient factors had any confounding effect.

DISCUSSION

Using the experience sampling method data combined with multilevel analysis, we were able to evaluate the postoperative pain course while considering inter-individual differences in the baseline pain level and nonlinear pain course over time. The findings of this study could aid clinicians in personalizing the treatment for APP.

An Evidence-Based Framework for Creating Inclusive and Personalized mHealth Solutions-Designing a Solution for Medicaid-Eligible Pregnant Individuals With Uncontrolled Type 2 Diabetes

Mobile health (mHealth) apps can be an evidence-based approach to improve health behavior and outcomes. Prior literature has highlighted the need for more research on mHealth personalization, including in diabetes and pregnancy. Critical gaps exist on the impact of personalization of mHealth apps on patient engagement, and in turn, health behaviors and outcomes. Evidence regarding how personalization, engagement, and health outcomes could be aligned when designing mHealth for underserved populations is much needed, given the historical oversights with mHealth design in these populations. This viewpoint is motivated by our experience from designing a personalized mHealth solution focused on Medicaid-enrolled pregnant individuals with uncontrolled type 2 diabetes, many of whom also experience a high burden of social needs. We describe fundamental components of designing mHealth solutions that are both inclusive and personalized, forming the basis of an evidence-based framework for future mHealth design in other disease states with similar contexts.

Ecological momentary interventions for smoking cessation: a systematic review and meta-analysis

BACKGROUND AND OBJECTIVES

Tobacco use is an important cause of preventable mortality and morbidity worldwide. Only 7% of smokers successfully quit annually, despite numerous evidence-based smoking cessation treatments. An important reason for failure is barriers to accessing appropriate smoking cessation interventions, which can be minimized by technology-delivered interventions, such as ecological momentary interventions. Ecological momentary interventions provide the right type and intensity of treatment in real time, based on ecological momentary assessments of relevant variables. The aim of this review was to assess the effectiveness of ecological momentary interventions in smoking cessation.

METHODS

We searched MEDLINE, Scopus, CENTRAL, psychINFO, and ProQuest without applying any filters on 19 September, 2022. One author screened search results for obvious irrelevant and duplicate studies. The remaining studies were independently reviewed by two authors to exclude irrelevant studies, and then they extracted data from the included studies. We collated study findings, transformed data into a common rubric, and calculated a weighted treatment effect across studies using Review Manager 5.

FINDINGS

We analyzed 10 studies with a total of 2391 participants. Assessment methods included exhaled CO analyzers, bidirectional SMS, data input in apps, and hand movement detection. Interventions were based on acceptance and commitment therapy and cognitive behavioral therapy. Smoking abstinence was significantly higher in participants of intervention groups compared to control groups (RR = 1.24; 95% CI 1.07-1.44, P = 0.004; I2 = 0%).

CONCLUSION

Ecological momentary intervention is a novel area of research in behavioral science. The results of this systematic review based on the available literature suggest that these interventions could be beneficial for smoking cessation.

Decision Trade-Offs in Ecological Momentary Assessments and Digital Wearables Uptake: Protocol for a Discrete Choice Experiment

BACKGROUND

Ecological momentary assessments (EMAs) and digital wearables (DW) are commonly used remote monitoring technologies that capture real-time data in people's natural environments. Real-time data are core to personalized medical care and intensively adaptive health interventions. The utility of such personalized care is contingent on user uptake and continued use of EMA and DW. Consequently, it is critical to understand user preferences that may increase the uptake of EMA and DW.

OBJECTIVE

The study aims to quantify users' preferences of EMA and DW, examine variations in users' preferences across demographic and behavioral subgroups, and assess the association between users' preferences and intentions to use EMA and DW.

METHODS

We will administer 2 discrete choice experiments (DCEs) paired with self-report surveys on the internet to a total of 3260 US adults through Qualtrics. The first DCE will assess participants' EMA preferences using a choice-based conjoint design that will ask participants to compare the relative importance of prompt frequency, number of questions per prompt, prompt type, health topic, and assessment duration. The second DCE will measure participants' DW preferences using a maximum difference scaling design that will quantify the relative importance of device characteristics, effort expectancy, social influence, and facilitating technical, health care, and market factors. Hierarchical Bayesian multinomial logistic regression models will be used to generate subject-specific preference utilities. Preference utilities will be compared across demographic (ie, sex, age, race, and ethnicity) and behavioral (ie, substance use, physical activity, dietary behavior, and sleep duration) subgroups. Regression models will determine whether specific utilities are associated with attitudes toward or intentions to use EMA and DW. Mixture models will determine the associations of attitudes toward and intentions to use EMA and DW with latent profiles of user preferences.

RESULTS

The institutional review board approved the study on December 19, 2022. Data collection started on January 20, 2023, and concluded on May 4, 2023. Data analysis is currently underway.

CONCLUSIONS

The study will provide evidence on users' preferences of EMA and DW features that can improve initial uptake and potentially continued use of these remote monitoring tools. The sample size and composition allow for subgroup analysis by demographics and health behaviors and will provide evidence on associations between users' preferences and intentions to uptake EMA and DW. Limitations include the cross-sectional nature of the study, which limits our ability to measure direct behavior. Rather, we capture behavioral intentions for EMA and DW uptake. The nonprobability sample limits the generalizability of the results and introduces self-selection bias related to the demographic and behavioral characteristics of participants who belong to web-based survey panels.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47567.

Reactivity toward daily events: Intraindividual variability and change in recurrent depression - A measurement burst study

In Major Depressive Disorder, first evidence shows heightened mood-reactivity toward daily events. Related longitudinal studies in remitted patients with recurrent major depression are lacking. Long-term changes in such short-term within-person associations can be analysed via measurement burst designs. Two bursts, separated by approximately 4.4 years, consisted of a baseline session and an Ambulatory Assessment (burst-1: 3 days, burst-2: 5 days). Via smartphone, 54 initially remitted patients with recurrent major depression indicated their negative and positive affect, rumination, self-acceptance, and the occurrence of negative and positive daily events ten times and collected saliva cortisol samples five times per day. In bursts with higher depression levels, patients showed blunted negative affect- and cortisol-reactivity and stronger decreases in positive affect and self-acceptance toward negative daily events, as well as stronger increases in self-acceptance following positive daily events. However, patients with higher depression levels demonstrated stronger ruminative stress-reactivity within bursts. Furthermore, patients with higher depression levels showed an increase of affective stress-reactivity over bursts, such that negative affect more strongly increased and positive affect more strongly decreased following negative daily events over bursts. Following positive daily events, patients with higher depression levels showed stronger decreases in negative affect within bursts and a decrease of self-acceptance-reactivity over bursts. To conclude, measurement burst designs enable to examine intraindividual variability and change of micro-level processes, and possible moderators thereof, potentially providing prognostic information for the course of recurrent major depression.

Using machine learning with intensive longitudinal data to predict depression and suicidal ideation among medical interns over time

BACKGROUND

Use of intensive longitudinal methods (e.g. ecological momentary assessment, passive sensing) and machine learning (ML) models to predict risk for depression and suicide has increased in recent years. However, these studies often vary considerably in length, ML methods used, and sources of data. The present study examined predictive accuracy for depression and suicidal ideation (SI) as a function of time, comparing different combinations of ML methods and data sources.

METHODS

Participants were 2459 first-year training physicians (55.1% female; 52.5% White) who were provided with Fitbit wearable devices and assessed daily for mood. Linear [elastic net regression (ENR)] and non-linear (random forest) ML algorithms were used to predict depression and SI at the first-quarter follow-up assessment, using two sets of variables (daily mood features only, daily mood features + passive-sensing features). To assess accuracy over time, models were estimated iteratively for each of the first 92 days of internship, using data available up to that point in time.

RESULTS

ENRs using only the daily mood features generally had the best accuracy for predicting mental health outcomes, and predictive accuracy within 1 standard error of the full 92 day models was attained by weeks 7-8. Depression at 92 days could be predicted accurately (area under the curve >0.70) after only 14 days of data collection.

CONCLUSIONS

Simpler ML methods may outperform more complex methods until passive-sensing features become better specified. For intensive longitudinal studies, there may be limited predictive value in collecting data for more than 2 months.

Evidence for positive long- and short-term effects of vaccinations against COVID-19 in wearable sensor metrics

Vaccines are among the most powerful tools to combat the COVID-19 pandemic. They are highly effective against infection and substantially reduce the risk of severe disease, hospitalization, ICU admission, and death. However, their potential for attenuating long-term changes in personal health and health-related wellbeing after a SARS-CoV-2 infection remains a subject of debate. Such effects can be effectively monitored at the individual level by analyzing physiological data collected by consumer-grade wearable sensors. Here, we investigate changes in resting heart rate, daily physical activity, and sleep duration around a SARS-CoV-2 infection stratified by vaccination status. Data were collected over a period of 2 years in the context of the German Corona Data Donation Project with around 190,000 monthly active participants. Compared to their unvaccinated counterparts, we find that vaccinated individuals, on average, experience smaller changes in their vital data that also return to normal levels more quickly. Likewise, extreme changes in vitals during the acute phase of the disease occur less frequently in vaccinated individuals. Our results solidify evidence that vaccines can mitigate long-term detrimental effects of SARS-CoV-2 infections both in terms of duration and magnitude. Furthermore, they demonstrate the value of large-scale, high-resolution wearable sensor data in public health research.

Evaluating the Modified Patient Health Questionnaire-2 and Insomnia Severity Index-2 for Daily Digital Screening of Depression and Insomnia: Validation Study

BACKGROUND

The Patient Health Questionnaire-2 (PHQ-2) and Insomnia Severity Index-2 (ISI-2) are screening assessments that reflect the past 2-week experience of depression and insomnia, respectively. Retrospective assessment has been associated with reduced accuracy owing to recall bias.

OBJECTIVE

This study aimed to increase the reliability of responses by validating the use of the PHQ-2 and ISI-2 for daily screening.

METHODS

A total of 167 outpatients from the psychiatric department at the Yongin Severance Hospital participated in this study, of which 63 (37.7%) were male and 104 (62.3%) were female with a mean age of 35.1 (SD 12.1) years. Participants used a mobile app ("Mental Protector") for 4 weeks and rated their depressive and insomnia symptoms daily on the modified PHQ-2 and ISI-2 scales. The validation assessments were conducted in 2 blocks, each with a fortnight response from the participants. The modified version of the PHQ-2 was evaluated against the conventional scales of the Patient Health Questionnaire-9 and the Korean version of the Center for Epidemiologic Studies Depression Scale-Revised.

RESULTS

According to the sensitivity and specificity analyses, an average score of 3.29 on the modified PHQ-2 was considered valid for screening for depressive symptoms. Similarly, the ISI-2 was evaluated against the conventional scale, Insomnia Severity Index, and a mean score of 3.50 was determined to be a valid threshold for insomnia symptoms when rated daily.

CONCLUSIONS

This study is one of the first to propose a daily digital screening measure for depression and insomnia delivered through a mobile app. The modified PHQ-2 and ISI-2 were strong candidates for daily screening of depression and insomnia, respectively.

Speech as a promising biosignal in precision psychiatry

Health research and health care alike are presently based on infrequent assessments that provide an incomplete picture of clinical functioning. Consequently, opportunities to identify and prevent health events before they occur are missed. New health technologies are addressing these critical issues by enabling the continual monitoring of health-related processes using speech. These technologies are a great match for the healthcare environment because they make high-frequency assessments non-invasive and highly scalable. Indeed, existing tools can now extract a wide variety of health-relevant biosignals from smartphones by analyzing a person's voice and speech. These biosignals are linked to health-relevant biological pathways and have shown promise in detecting several disorders, including depression and schizophrenia. However, more research is needed to identify the speech signals that matter most, validate these signals against ground-truth outcomes, and translate these data into biomarkers and just-in-time adaptive interventions. We discuss these issues herein by describing how assessing everyday psychological stress through speech can help both researchers and health care providers monitor the impact that stress has on a wide variety of mental and physical health outcomes, such as self-harm, suicide, substance abuse, depression, and disease recurrence. If done appropriately and securely, speech is a novel digital biosignal that could play a key role in predicting high-priority clinical outcomes and delivering tailored interventions that help people when they need it most.

AwarNS: A framework for developing context-aware reactive mobile applications for health and mental health

In recent years, interest and investment in health and mental health smartphone apps have grown significantly. However, this growth has not been followed by an increase in quality and the incorporation of more advanced features in such applications. This can be explained by an expanding fragmentation of existing mobile platforms along with more restrictive privacy and battery consumption policies, with a consequent higher complexity of developing such smartphone applications. To help overcome these barriers, there is a need for robust, well-designed software development frameworks which are designed to be reliable, power-efficient and ethical with respect to data collection practices, and which support the sense-analyse-act paradigm typically employed in reactive mHealth applications. In this article, we present the AwarNS Framework, a context-aware modular software development framework for Android smartphones, which facilitates transparent, reliable, passive and active data sampling running in the background (sense), on-device and server-side data analysis (analyse), and context-aware just-in-time offline and online intervention capabilities (act). It is based on the principles of versatility, reliability, privacy, reusability, and testability. It offers built-in modules for capturing smartphone and associated wearable sensor data (e.g. IMU sensors, geolocation, Wi-Fi and Bluetooth scans, physical activity, battery level, heart rate), analysis modules for data transformation, selection and filtering, performing geofencing analysis and machine learning regression and classification, and act modules for persistence and various notification deliveries. We describe the framework's design principles and architecture design, explain its capabilities and implementation, and demonstrate its use at the hand of real-life case studies implementing various mobile interventions for different mental disorders used in clinical practice.

A nurse-led mHealth intervention to alleviate depressive symptoms in older adults living alone in the community: A quasi-experimental study

BACKGROUND

The prevalence of geriatric depression has increased worldwide, becoming a major contributor to the burden of health care costs. Geriatric depression is difficult to detect in daily life because of its atypical presentation for each person. Therefore, there is an emerging need to develop personalised mHealth interventions for older adults with depression based on data from an ecological momentary assessment.

OBJECTIVE

To develop and evaluate the effect of a nurse-led mHealth intervention of geriatric depression in older adults living alone.

DESIGN

A quasi-experimental research design was used, and the study followed the transparent reporting of evaluations with a nonrandomised design statement.

SETTING

The nurse-led mHealth intervention was developed and evaluated in a community senior centre in Seoul, Korea.

PARTICIPANTS

Sixty-four older adults living alone with depressive symptoms were recruited between 1 October 2018 and 1 October 2019.

METHODS

Study participants were randomly assigned to the intervention or control groups by drawing lots. In the intervention group, nurses repeatedly assessed older adults' depressive symptoms using an ecological momentary assessment via a mobile tablet. The intervention consisted of weekly sessions, which included (1) standardised mHealth device training, (2) a nurse-led mHealth programme, and (3) art activities. The control group received care as usual. Intra- and inter-group differences were evaluated using paired t-tests and analysis of covariance was used to assess subjective depression symptoms. A linear mixed-model was used to analyse the relationship between groups and momentary scores over time.

RESULTS

The average age of the final sample was 76.2 years (SD = 6.06), 63.6 % (28/44) of whom were female. Compared with the control group (n = 23), the intervention group (n = 21) showed a decreased depression score (t = 4.041, p = .027). There was no statistical difference between the intervention and control groups based on traditional scales and the ecological momentary assessment. However, our data from the ecological momentary assessment captures clear fluctuating patterns across the days during the study, which traditional scales could not measure.

CONCLUSIONS

Most of the older adults successfully participated in a nurse-led mHealth intervention that included multiple components of a non-pharmacological approach to address depression. Mental health nurses should perform critical roles to personalise mHealth activities considering the older adult's autonomy and supportive decision-making, specifically when using high-technological intervention. Future research should maximise the methodological and clinical advantage of an ecological momentary assessment of geriatric depression.

REGISTRATION

Clinical Research Information Service number KCT0005073.

Cannabis use and sleep quality in daily life: An electronic daily diary study of adults starting cannabis for health concerns

BACKGROUND

Real world patterns of cannabis use for health concerns are highly variable and rarely overseen by a physician. Pragmatic effectiveness studies with electronic daily diaries that capture person-specific patterns of cannabis use and health symptoms may help clarify risks and benefits.

METHODS

As part of a larger, randomized trial (NCT03224468), adults (N = 181) seeking cannabis for insomnia, pain, or anxiety or depressive symptoms were randomized to obtain a medical cannabis card immediately (MCC) or a waitlist control (WLC) and completed 12-weeks of daily web-based surveys on cannabis use and sleep, pain, and depressive symptoms.

RESULTS

Completion rates of daily surveys were moderate to high (median completed: 72 out of 90 days). Daily reports of cannabis use were consistent with monthly interview assessments and urinalysis. The MCC group increased cannabis use frequency in the 12 weeks following randomization, while WLC did not. Among the MCC group, self-reported sleep quality was significantly higher on cannabis use days, compared to nonuse days. The MCC group displayed long-term sleep improvements, consistent with increasing cannabis frequency. No improvements were found for pain or depressive symptoms.

CONCLUSION

Cannabis use is associated with same day improvements in self-reported sleep quality, but not pain or depressive symptoms, although sleep improvements occurred in the context of increased frequency of cannabis use, raising the risk for cannabis use disorder. Daily web-based assessments of cannabis appear valid and feasible in adults seeking cannabis for health concerns, providing a flexible, complementary method for future real-world effectiveness studies with expanded and objective measures.

Telepsychiatry: The future is already present

This review paper analyzes the state of knowledge on Telepsychiatry (TP) after the crisis caused by COVID and the resulting need to use new modalities of care. Six essential aspects of TP are addressed: patient's and mental health staff satisfaction, diagnostic reliability, effectiveness of TP interventions, cost-effectiveness in terms of opportunity cost (or efficiency), legal aspects inherent to confidentiality and privacy in particular and the attitude of professionals toward TP. Satisfaction with TP is acceptable among both patients and professionals, the latter being the most reluctant. Diagnostic reliability has been demonstrated, but requires further studies to confirm this reliability in different diagnoses and healthcare settings. The efficacy of TP treatments is not inferior to face-to-face care, as has been proven in specific psychotherapies. Finally, it should be noted that the attitude of the psychiatrist is the most decisive element that limits or facilitates the implementation of TP.

Descriptive Exploratory Study to Understand Postpartum Anxiety Using Multiple Measures

OBJECTIVE

To compare a general anxiety instrument plus a depression instrument with a specific postpartum anxiety instrument plus a depression instrument to detect postpartum anxiety and to explore trends in daily postpartum anxiety.

DESIGN

Prospective, longitudinal cohort study.

SETTING

Academic tertiary center in the mid-Atlantic United States. Study activities were remote.

PARTICIPANTS

Pregnant women (N = 73) in the third trimester of pregnancy.

METHODS

We administered the State-Trait Anxiety Inventory (STAI), Postpartum Specific Anxiety Scale (PSAS), and Edinburgh Postnatal Depression Scale (EPDS) at 1 and 8 weeks after birth. We used mobile ecological momentary assessment prompts to measure daily anxiety levels (0-10) from 1 to 8 weeks after birth. We defined the presence of anxiety and depression by using the established instrument cutoff scores. We used repeated-measures analysis of variance and dependent-samples t tests to determine the stability of the determined anxiety instruments during the study time frame. We used linear mixed modeling to explore mobile ecological momentary assessment anxiety trends.

RESULTS

The PSAS and EPDS detected more participants with anxiety and/or depression (26.8%, 19/71) than the STAI and EPDS (23.9%, 17/71) at 8 weeks after birth. PSAS scores increased from 1 to 8 weeks after birth (p = .003); STAI scores decreased (p = .01). Daily anxiety ratings changed nonlinearly during the study period, were greatest at 2 weeks, declined and stabilized, and then trended upward toward Week 8.

CONCLUSION

Detection of postpartum anxiety in clinical settings can be improved through addition of the PSAS in routine screening. Timing of anxiety assessment should be considered between 6 to 8 weeks after birth.

Understanding health behaviours in context: A systematic review and meta-analysis of ecological momentary assessment studies of five key health behaviours

Ecological Momentary Assessment (EMA) involves repeated, real-time sampling of health behaviours in context. We present the state-of-knowledge in EMA research focused on five key health behaviours (physical activity and sedentary behaviour, dietary behaviour, alcohol consumption, tobacco smoking, sexual health), summarising theoretical (e.g., psychological and contextual predictors) and methodological aspects (e.g., study characteristics, EMA adherence). We searched Ovid MEDLINE, Embase, PsycINFO and Web of Science until February 2021. We included studies focused on any of the aforementioned health behaviours in adult, non-clinical populations that assessed ≥1 psychological/contextual predictor and reported a predictor-behaviour association. A narrative synthesis and random-effects meta-analyses of EMA adherence were conducted. We included 633 studies. The median study duration was 14 days. The most frequently assessed predictors were 'negative feeling states' (21%) and 'motivation and goals' (16.5%). The pooled percentage of EMA adherence was high at 81.4% (95% CI = 80.0%, 82.8%, k = 348) and did not differ by target behaviour but was somewhat higher in student (vs. general population) samples, when EMAs were delivered via mobile phones/smartphones (vs. handheld devices), and when event contingent (vs. fixed) sampling was used. This review showcases how the EMA method has been applied to improve understanding and prediction of health behaviours in context.

The feasibility of using Apple's ResearchKit for recruitment and data collection: Considerations for mental health research

In 2015, Apple launched an open-source software framework called ResearchKit. ResearchKit provides an infrastructure for conducting remote, smartphone-based research trials through the means of Apple's App Store. Such trials may have several advantages over conventional trial methods including the removal of geographic barriers, frequent assessments of participants in real-life settings, and increased inclusion of seldom-heard communities. The aim of the current study was to explore the feasibility of participant recruitment and the potential for data collection in the non-clinical population in a smartphone-based trial using ResearchKit. As a case example, an app called eMovit, a behavioural activation (BA) app with the aim of helping users to build healthy habits was used. The study was conducted over a 9-month period. Any iPhone user with access to the App Stores of The Netherlands, Belgium, and Germany could download the app and participate in the study. During the study period, the eMovit app was disseminated amongst potential users via social media posts (Twitter, Facebook, LinkedIn), paid social media advertisements (Facebook), digital newsletters and newspaper articles, blogposts and other websites. In total, 1,788 individuals visited the eMovit landing page. A total of 144 visitors subsequently entered Apple's App Store through that landing page. The eMovit product page was viewed 10,327 times on the App Store. With 79 installs, eMovit showed a conversion rate of 0.76% from product view to install of the app. Of those 79 installs, 53 users indicated that they were interested to participate in the research study and 36 subsequently consented and completed the demographics and the participants quiz. Fifteen participants completed the first PHQ-8 assessment and one participant completed the second PHQ-8 assessment. We conclude that from a technological point of view, the means provided by ResearchKit are well suited to be integrated into the app process and thus facilitate conducting smartphone-based studies. However, this study shows that although participant recruitment is technically straightforward, only low recruitment rates were achieved with the dissemination strategies applied. We argue that smartphone-based trials (using ResearchKit) require a well-designed app dissemination process to attain a sufficient sample size. Guidelines for smartphone-based trial designs and recommendations on how to work with challenges of mHealth research will ensure the quality of these trials, facilitate researchers to do more testing of mental health apps and with that enlarge the evidence-base for mHealth.

Emotion Dynamics and Emotion Regulation in Anorexia Nervosa: A Systematic Review of Ecological Momentary Assessment Studies

Altered emotion dynamics and emotion regulation (ER) have been indicated in theoretical descriptions of abnormal emotional functioning, which contributes to the development and maintenance of anorexia nervosa (AN). Ecological momentary assessment (EMA) has recently become popular in research on eating disorders. It is a source of new insights into the psychopathology of AN as it enables intensive long-term tracking of everyday experiences and behaviours of individuals through repeated self-reports. The following systematic review aims to synthesize research on the use of EMA when evaluating emotion dynamics and ER in AN. Specific studies were identified with the use of MEDLINE, PsycINFO, and Scopus databases. A supplemental search was performed in reference lists of the relevant publications. As a result, 27 publications were identified and included in the systematic review. The findings from the reviewed studies point to various disturbed components of emotion dynamics as well as to unique associations of maladaptive ER strategies with specific abnormalities in emotion dynamics in AN. Limitations of the studies were discussed as well. An outlook for further research in the field was provided in the last section of the paper.

Negative expectations regarding interpersonal interactions in daily life are associated with subclinical depressive symptoms in a student sample: A prospective experience sampling study

Dysfunctional expectations and interpersonal problems are associated with depression, so we measured expected emotions towards interaction partners and compared them with actual emotions. We hypothesized that, between persons, individuals with higher subclinical depression would display stronger, more stable, and less accurate negative expectations. Within persons, we hypothesized that momentary negative expectations would predict subsequent negative affect. Fifty-three students completed 6 days of Experience Sampling, consisting of one morning expectation-assessment (9 am), three assessments on actual interpersonal emotions (1 pm, 5 pm, 9 pm), and six random affect-assessments. We regressed expected emotions, experienced emotions, expectation fluctuations, and expectation violations on subclinical depression. Using mixed model analyses, we further examined whether negative expectations preceded negative affect, and whether expectation violations preceded adjustments of expectations. Higher subclinical depression predicted more negative expectations. Within persons, worse-than-expected interpersonal interactions preceded negative affect whereas better-than-expected interactions preceded reductions of negative expectations. Despite problems with skewed data, our approach appears well-suited to examine interpersonal expectations in vivo.

The Use of Smart Devices for Mental Health Diagnosis and Care

In 2019, more than 970 million people worldwide suffered from a mental disorder, with anxiety and depressive disorders as the leading culprits [...]

The association of momentary sad moods, concurrent productive behaviour, and global functional outcomes: a 30-day ecological momentary assessment study of people with bipolar illness

BACKGROUND

Previous weekly sampling studies found that persistent sad moods are associated with disability in bipolar illness. However, those data were collected retrospectively. We examined the momentary quality of activities (productive, unproductive, and passive recreation) in an ecological momentary assessment (EMA) study and related sadness at each survey to quality of momentary activities and overall everyday functioning.

METHODS

Participants with bipolar illness (N = 91) were sampled three times per day for 30 days. Each survey queried participants as to where they were, with whom, what they were doing, and their mood state. Activities were characterised according to predetermined criteria and related to momentary sadness. Observer ratings of everyday functioning were related to daily reports of sadness and activities.

RESULTS

Sadness was associated with the quality of activities. Momentary reports of unproductive activities were associated with the most sadness (p < .001), followed by passive recreation, and productive activities. Momentary sadness and momentary unproductive activities correlated with observer ratings of competence in work, everyday activities, and social outcomes (p < .001). Using both predictors led to the best model.

CONCLUSIONS

This study on the course of sad moods in people with bipolar illness to EMA found that momentary sadness correlatesdwith the quality of concurrent activities and that both sadness and the quality of everyday activities predicted observer ratings of everyday functioning. Although we cannot determine the causal direction, these findings support the hypothesis that momentary sadness leads to reductions in productive activities and impairments in everyday functioning.

Ecological momentary assessment of affect in depression-prone and control samples: Survey compliance and affective yield

BACKGROUND

Ecological momentary assessment (EMA) is a high-frequency ambulatory data collection approach that has come to be widely used in emotion research. It therefore is timely to examine two features of EMA needed for a successful study: compliance with survey prompts and high affective yield (survey prompts that capture affect experience). We posit that compliance may be subject to temporal variation (time-of-day, days in study) and individual differences (depression history), and that affective yield may also differ by social context.

METHODS

We examined these issues in a sample of 318 young adults (Mage = 24.7 years, SD = 2.7), including those with current depression (n = 28), remitted depression (n = 168) and never-depressed controls (n = 122) who participated in a 7-day EMA protocol of negative and positive affect (NA and PA, respectively).

RESULTS

The overall compliance rate was 91% and remained stable across the survey week. However, subjects were significantly less likely to respond to the first daily prompt compared to those that followed. The likelihood of capturing NA and PA decreased with each EMA protocol day, and affective yield across social contexts differed by participants' depression status.

LIMITATIONS

The sample was largely comprised of White young adults. Relative to the remitted and control groups, the sample size for the currently depressed was unbalanced.

CONCLUSION

Researchers can optimize compliance and affective yield within EMA by considering depression, time-of-day, study duration, and social context. Clinicians using EMA to monitor affect may benefit from considering these parameters.

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.