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

Which client with generalized anxiety disorder benefits from a mindfulness ecological momentary intervention versus a self-monitoring app? Developing a multivariable machine learning predictive model

Precision medicine methods (machine learning; ML) can identify which clients with generalized anxiety disorder (GAD) benefit from mindfulness ecological momentary intervention (MEMI) vs. self-monitoring app (SM). We used randomized controlled trial data of MEMI vs. SM for GAD (N = 110) and tested three ML models to predict one-month follow-up reliable improvement in GAD severity, perseverative cognitions (PC), trait mindfulness (TM), and executive function (EF). Eleven baseline predictors were tested regarding differential reliable change from MEMI vs. SM (age, sex, race, EF errors, inhibitory dyscontrol, set-shifting deficits, verbal fluency, working memory, GAD severity, TM, PC). The final top five prescriptive predictor models of all outcomes performed well (AUC = .752 .886). The following variables predicted better outcome from MEMI vs. SM: Higher GAD severity predicted more GAD improvement but less EF improvement. Elevated PC, inhibitory dyscontrol, and verbal dysfluency predicted better improvement in most outcomes. Greater set-shifting and TM predicted stronger improvements in GAD symptoms and TM. Older age predicted more alleviation of GAD and PC symptoms. Women exhibited more enhancements in trait mindfulness and EF than men. White individuals benefitted more than non-White. PC, TM, EF, and sociodemographic data might help predictive models optimize intervention selection for GAD.

Traditional surveys versus ecological momentary assessments: Digital citizen science approaches to improve ethical physical activity surveillance among youth

The role of physical activity (PA) in minimizing non-communicable diseases is well established. Measurement bias can be reduced via ecological momentary assessments (EMAs) deployed via citizen-owned smartphones. This study aims to engage citizen scientists to understand how PA reported digitally by retrospective and prospective measures varies within the same cohort. This study used the digital citizen science approach to collaborate with citizen scientists, aged 13-21 years over eight consecutive days via a custom-built app. Citizen scientists were recruited through schools in Regina, Saskatchewan, Canada in 2018 (August 31-December 31). Retrospective PA was assessed through a survey, which was adapted from three validated PA surveys to suit smartphone-based data collection, and prospective PA was assessed through time-triggered EMAs deployed consecutively every day, from day 1 to day 8, including weekdays and weekends. Data analyses included paired t-tests to understand the difference in PA reported retrospectively and prospectively, and linear regressions to assess contextual and demographic factors associated with PA reported retrospectively and prospectively. Findings showed a significant difference between PA reported retrospectively and prospectively (p = 0.001). Ethnicity (visible minorities: β = - 0.911, 95% C.I. = -1.677, -0.146), parental education (university: β = 0.978, 95% C.I. = 0.308, 1.649), and strength training (at least one day: β = 0.932, 95% C.I. = 0.108, 1.755) were associated with PA reported prospectively. In contrast, the number of active friends (at least one friend: β = 0.741, 95% C.I. = 0.026, 1.458) was associated with retrospective PA. Physical inactivity is the fourth leading cause of mortality globally, which requires accurate monitoring to inform population health interventions. In this digital age, where ubiquitous devices provide real-time engagement capabilities, digital citizen science can transform how we measure behaviours using citizen-owned ubiquitous digital tools to support prevention and treatment of non-communicable diseases.

Acceptability and feasibility of ecological momentary assessment with augmentation of passive sensor data in young adults at high risk for suicide

Ecological Momentary Assessment (EMA) and wearable sensor data have the potential to enhance prediction of suicide risk in real-world conditions. However, the feasibility of this methodology with high-risk populations, including over extended periods, warrants closer attention. This study examined the feasibility and acceptability of concurrent EMA and wearable sensor monitoring in young adults after emergency department (ED) care for suicide risk-related concerns. For 2 months after ED discharge, 106 participants (ages 18-25; 81.1% female) took part in EMA surveys (4x per day) and passive sensor (Fitbit) monitoring and completed an end-of-study phone interview. Overall adherence to EMA (62.1%) and wearable sensor (53.6%) was moderate and comparable to briefer protocols. Relative to EMAs (81%), fewer participants completed the full 8 weeks of Fitbit (63%). While lower initial hopelessness was linked to reduced EMA adherence, previous-day suicidal ideation predicted lower Fitbit adherence on the next day. Self-endorsed barriers to EMA and wearable sensor adherence were also examined. Participants tended to report positive experience with the protocol, with majority indicating EMAs were minimally burdensome, reporting that the Fitbit was generally comfortable, and expressing interest in participating in a similar study again. Findings provide support for the feasibility and acceptability of concurrent intensive self-report and wearable sensor data during a high-risk period. Implications and future directions are discussed.

Promoting Daily Well-being in Adolescents using mHealth

Adolescents are at increased risk for developing mental health problems. The Grow It! app is an mHealth intervention aimed at preventing mental health problems through improving coping by cognitive behavioral therapy (CBT)-inspired challenges as well as self-monitoring of emotions through Experience Sampling Methods (ESM). Yet, little is known about daily changes in well-being and coping during a stressful period, like the COVID-19 pandemic. The current study aimed to elucidate daily changes in positive and negative affect, and adaptive coping, and to better understand the within-person's mechanisms of the Grow It! app. The sample consisted of 12-25-year old Dutch adolescents in two independent cohorts (cohort 1: N = 476, Mage = 16.24, 76.1% female, 88.7% Dutch; cohort 2: N = 814, Mage = 18.45, 82.8% female, 97.2% Dutch). ESM were used to measure daily positive and negative affect and coping (cohort 1: 42 days, 210 assessments per person; cohort 2: 21 days, 105 assessments). The results showed that, on average, adolescents decreased in daily positive affect and adaptive coping, and increased in their experienced negative affect. A positive relation between adaptive coping and positive affect was found, although independent of the CBT-based challenges. Latent class analysis identified two heterogeneous trajectories for both positive and negative affect, indicating that the majority of participants with low to moderate-risk on developing mental health problems were likely to benefit from the Grow It! app.

Practitioner and researcher perspectives on the utility of ecological momentary assessment in mental health care: A survey study

BACKGROUND

Ecological momentary assessment (EMA) is a scientific self-monitoring method to capture individuals' daily life experiences. Early on, EMA has been suggested to have the potential to improve mental health care. However, it remains unclear if and how EMA should be implemented. This requires an in-depth investigation of how practitioners and researchers view the implementation of EMA.

OBJECTIVE

Explore the perspectives of mental health practitioners and EMA researchers on the utility of EMA for mental health care.

METHODS

Practitioners (n = 89; psychiatrists, psychologists, psychiatric nurses) and EMA researchers (n = 62) completed a survey about EMA in clinical practice. This survey addressed EMA goals for practitioner and patient, requirements regarding clinical use of EMA, and (dis)advantages of EMA compared to treatment-as-usual. t-Tests were used to determine agreement with each statement and whether practitioners' and researchers' views differed significantly. Linear regression was used to explore predictors of goals and preferences (e.g., EMA experience).

RESULTS

Practitioners and researchers considered EMA to be a useful clinical tool for diverse stages of care. They indicated EMA to be most useful for gaining insight into the context specificity of symptoms (55.0 %), whereas receiving alerts when symptoms increase was rated the least useful (11.3 %, alerts is in 95 % of bootstrap iterations between rank 8 and 10). Compared to treatment-as-usual, EMA was considered easier to use (M = 4.87, t = 5.30, p < .001) and interpret (M = 4.52, t = 3.61, p < .001), but also more burdensome for the patient (M = 4.48, t = 3.17, p < .001). Although participants preferred personalization of the EMA diary, they also suggested that EMA should cost practitioners and patients limited time. The preference for creating personalized EMA was related to the level of experience with EMA. Finally, they highlighted the need for practitioner training and patient full-time access to the EMA feedback.

CONCLUSIONS

This survey study demonstrated that practitioners and researchers expect EMA to have added value for mental health care. Concrete recommendations for implementation of EMA are formulated. This may inform the development of specific clinical applications and user-friendly EMA software.

Using smartphone-based ecological momentary assessment and personalized feedback for patients with chronic cancer-related fatigue: A proof-of-concept study

INTRODUCTION

Chronic cancer-related fatigue (CCRF) is a complex multidimensional problem warranting person-centered care. Providing patients and therapists personalized feedback based on network analysis applied to ecological momentary assessment (EMA) data could facilitate case conceptualization in psycho-oncological care. The aim was to explore patients' and therapists' experiences of using an EMA app and personalized feedback based on network theory to aid case conceptualization in psycho-oncological care.

METHODS

A n = 5 proof-of-concept study was implemented in routine psycho-oncological care. We purposively selected adult cancer patients suffering from severe CCRF who were on the waitlist for psycho-oncological care. During a 3-week period participants filled out the EMA app Energy InSight (fatigue, mood, activity, responding, and context) five times a day. Participants received a descriptive and network feedback report, which they reflected upon during the first therapy sessions. Thematic analysis was used to analyze user experiences.

RESULTS

Patients experienced that filling out the Energy InSight app, as well as receiving descriptive and network-based personalized feedback provided them with insight into their CCRF. Although therapists experienced the discussion of network feedback as challenging, it facilitated the case conceptualization.

DISCUSSION

Using EMA during waitlist for psychological care seemed feasible. Patients experienced beneficial effects from filling out the EMA app and talking over the personalized feedback reports, which in turn aided case conceptualization and personalized care. Based on this evaluation, an improved version of the Energy InSight app and a therapist training for providing network feedback is developed for implementation in psycho-oncological care.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Understanding self-monitoring to inform a mobile intervention for binge eating and weight management: A proof-of-concept randomized trial

OBJECTIVE

This study explored consumers' perspectives on self-monitoring, a common feature in behavioral interventions that helps inform consumers' progress and answer their questions, to learn what outcome metrics matter to consumers and whether self-selection of these metrics leads to greater engagement (i.e., compliance, satisfaction) in self-monitoring than monitoring only default options.

METHODS

In a proof-of-concept randomized trial, 48 adult participants were randomly assigned to "clinician-determined monitoring" or "clinician + self-determined monitoring" conditions. Before starting monitoring, all participants shared outcomes that would matter to them in a mobile intervention for binge eating and weight management. Then, for 3 weeks, participants in the "clinician-determined" condition monitored their weight and binge-eating episodes, and participants in the "clinician + self-determined" condition monitored these and another metric of their choosing. After, satisfaction and compliance were assessed.

RESULTS

Participants identified 116 metrics, grouped into 12 themes, that mattered to them. During monitoring, participants in the "clinician + self-determined" condition monitored 41 metrics. Surprisingly, participants in the "clinician-determined" condition also monitored metrics besides weight and binge eating. This resulted in a failure of our experimental manipulation, which represents a significant limitation of this research. No significant differences emerged in satisfaction or compliance between conditions.

DISCUSSION

Although our proof-of-concept trial yielded null quantitative results, findings also suggested binge eating and weight management interventions may benefit from including an individually customizable monitoring option in addition to default metrics, warranting testing in future research.

PUBLIC SIGNIFICANCE

Examining consumers' self-monitoring preferences for a mobile intervention for binge eating and weight management revealed a variety of metrics that matter to consumers, although binge eating and weight were still most valued. Findings from our proof-of-concept trial suggest design implications of encouraging an individually customizable monitoring option, in addition to default metrics, which needs to be tested in future research over a longer period and during actual mobile intervention delivery.