A Systematic Scoping Review of Fully Idiographic Network Analysis in Mental Health

Psychometric validation of the pictorial ecological momentary well-being instrument.

In this editorial, we discuss how mobile phone technology has the potential to move the field forward in terms of understanding suicide risk as well as laying foundations for the development of effective treatments/interventions. We have focused on mobile health technology given the rapid growth of mobile health approaches in suicide prevention (De Jaegere & Portzky, 2014; Mishara & Kerkhof, 2013) and psychological research more generally (Myin-Germeys et al., 2009; Nock, Prinstein, & Sterba, 2009; Palmier-Claus et al., 2011) and because mobile phone use is ubiquitous, with 75% of the world having access to a mobile phone (Kay, 2011). (aut. ref.)

Open Science in Suicide Research Is Open for Business.

Multidisciplinary research priorities for the COVID-19 pandemic

BackgroundDigital media has made screen time more available across multiple contexts, but our understanding of the ways children and families use digital media has lagged behind the rapid adoption of this technology.ObjectiveThis study evaluated the feasibility of an intensive longitudinal data collection protocol to objectively measure digital media use, physical activity, sleep, sedentary behavior, and socioemotional context among caregiver-child dyads. This paper also describes preliminary convergent validity of ecological momentary assessment (EMA) measures and preliminary agreement between caregiver self-reported phone use and phone use collected from passive mobile sensing.MethodsCaregivers and their preschool-aged child (3-5 years) were recruited to complete a 30-day assessment protocol. Within 30-days, caregivers completed 7 days of EMA to measure child behavior problems and caregiver stress. Caregivers and children wore an Axivity AX3 (Newcastle Upon Tyne) accelerometer to assess physical activity, sedentary behavior, and sleep. Phone use was assessed via passive mobile sensing; we used Chronicle for Android users and screenshots of iOS screen time metrics for iOS users. Participants were invited to complete a second 14-day protocol approximately 3-12 months after their first assessment. We used Pearson correlations to examine preliminary convergent validity between validated questionnaire measures of caregiver psychological functioning, child behavior, and EMA items. Root mean square errors were computed to examine the preliminary agreement between caregiver self-reported phone use and objective phone use.ResultsOf 110 consenting participants, 105 completed all protocols (105/110, 95.5% retention rate). Compliance was defined a priori as completing ≥70%-75% of each protocol task. There were high compliance rates for passive mobile sensing for both Android (38/40, 95%) and iOS (64/65, 98%). EMA compliance was high (105/105, 100%), but fewer caregivers and children were compliant with accelerometry (62/99, 63% and 40/100, 40%, respectively). Average daily phone use was 383.4 (SD 157.0) minutes for Android users and 354.7 (SD 137.6) minutes for iOS users. There was poor agreement between objective and caregiver self-reported phone use; root mean square errors were 157.1 and 81.4 for Android and iOS users, respectively. Among families who completed the first assessment, 91 re-enrolled to complete the protocol a second time, approximately 7 months later (91/105, 86.7% retention rate).ConclusionsIt is feasible to collect intensive longitudinal data on objective digital media use simultaneously with accelerometry and EMA from an economically and racially diverse sample of families with preschool-aged children. The high compliance and retention of the study sample are encouraging signs that these methods of intensive longitudinal data collection can be completed in a longitudinal cohort study. The lack of agreement between self-reported and objectively measured mobile phone use highlights the need for additional research using objective methods to measure digital media use.International Registered Report Identifier (IRRID)RR2-36240

Understanding mental well-being in the face of adversity: a scientific exploration in eating disorder patients

Opportunities in mental health services research.

Mobile technologies present new opportunities to develop personalized health interventions that respond to changes in behaviors and states. Such interventions are powered by computational models that need information on health behaviors in the real world. Ideally, sensors embedded on mobile devices could measure these behaviors. But we currently need self-report to capture subjective experiences that sensors cannot measure directly (e.g., fatigue and pain). Ecological momentary assessment (EMA) is one such approach that enables in-situ self-report data collection using smartphones. In EMA, participants are prompted several times a day on their phones to answer sets of multiple-choice questions. While the repeated nature of EMA reduces recall bias, it may induce user-burden. Thus, there is a need to explore methods complementary to EMA that are less burdensome yet provide comprehensive information on an individual's experiences. In this work, I present microinteraction ecological momentary assessment (μEMA). The μEMA method restricts EMA interruptions to single, cognitively simple questions that can be answered on a smartwatch with a single tap - a quick, glanceable microinteraction. Because all interactions are limited to this microinteraction, μEMA permits substantially higher interruption than EMA without as much burden. This work is motivated by the overarching question - can we rethink how we capture self-report at a high frequency without burdening users and yet gain a comprehensive understanding of one's behavior? To that end, my work evaluates the sustainability, compliance biases, and data validity of μEMA using data from a longitudinal study. In this study, participants answered μEMA questions (on smartwatch) and EMA questions (on smartphone) on different days, for a period of 12 months. In addition to self-report surveys, sensor data from both smartwatches and smartphones such as raw acceleration, location, and device use were collected. At the end of the study, participants self-reported their perceived burden of answering questions using μEMA and participated in a semi-structured interview describing their experience in the study. Properties of μEMA are explored using the data from the longitudinal study. First, when comparing μEMA with EMA, μEMA yielded significantly higher response rates and lower perceived burden at the end of 12 months - suggesting μEMA's sustainability. Qualitative data revealed that participants experienced burden via interruption burden and response burden, yet underlying motivators enabled them to answer questions continuously on μEMA and EMA. Second, we identified that contextual factors such as temporal variables (e.g., time of the day, day of the week, and days in study), device usage variables (e.g., media usage, battery state, and charging state), and activity/mobility variables (e.g., wrist motion and location) had a statistically significant association with momentary μEMA non-response - highlighting μEMA's compliance biases. Third, qualitative evaluation of exit interviews revealed mechanisms participants use to answer short-yet-frequent μEMA questions at the moment - providing information on μEMA's data validity and threats to its ecological validity. Finally, design opportunities for observation/intervention studies that might use μEMA for the intensive longitudinal data collection on smartwatches were identified.--Author's abstract

BackgroundDigital tools assessing momentary parameters and offering interventions in people’s daily lives play an increasingly important role in mental health research and treatment. Ecological momentary assessment (EMA) makes it possible to assess transient mental health states and their parameters. Ecological momentary interventions (EMIs) offer mental health interventions that fit well into individuals’ daily lives and routines. Self-efficacy is a transdiagnostic construct that is commonly associated with positive mental health outcomes.ObjectiveThe aim of our study assessing mood, specific self-efficacy, and other parameters using EMA was 2-fold. First, we wanted to determine the effects of daily assessed moods and dissatisfaction with social contacts as well as the effects of baseline variables, such as depression, on specific self-efficacy in the training group (TG). Second, we aimed to explore which variables influenced both groups’ positive and negative moods during the 7-day study period.MethodsIn this randomized controlled trial, we applied digital self-efficacy training (EMI) to 93 university students with elevated self-reported stress levels and daily collected different parameters, such as mood, dissatisfaction with social contacts, and specific self-efficacy, using EMA. Participants were randomized to either the TG, where they completed the self-efficacy training combined with EMA, or the control group, where they completed EMA only.ResultsIn total, 93 university students participated in the trial. Positive momentary mood was associated with higher specific self-efficacy in the evening of the same day (b=0.15, SE 0.05, P=.005). Higher self-efficacy at baseline was associated with reduced negative mood during study participation (b=–0.61, SE 0.30, P=.04), while we could not determine an effect on positive mood. Baseline depression severity was significantly associated with lower specific self-efficacy over the week of the training (b=–0.92, SE 0.35, P=.004). Associations between higher baseline anxiety with higher mean negative mood (state anxiety: b=0.78, SE 0.38, P=.04; trait anxiety: b=0.73, SE 0.33, P=.03) and lower mean positive mood (b=–0.64, SE 0.28, P=.02) during study participation were found. Emotional flexibility was significantly enhanced in the TG. Additionally, dissatisfaction with social contacts was associated with both a decreased positive mood (b=–0.56, SE 0.15, P<.001) and an increased negative mood (b=0.45, SE 0.12, P<.001).ConclusionsThis study showed several significant associations between mood and self-efficacy as well as those between mood and anxiety in students with elevated stress levels, for example, suggesting that improving mood in people with low mood could enhance the effects of digital self-efficacy training. In addition, engaging in 1-week self-efficacy training was associated with increased emotional flexibility. Future work is needed to replicate and investigate the training’s effects in other groups and settings.Trial RegistrationClinicalTrials.gov NCT05617248; https://clinicaltrials.gov/study/NCT05617248

Intensive longitudinal data (ILD) collection methods have gained popularity in social and behavioral research as a tool to better understand behavior and experiences over time with reduced recall bias. Engaging participants in these studies over multiple months and ensuring high data quality are crucial but challenging due to the potential burden of repeated measurements. It is suspected that participants may engage in inattentive responding (IR) behavior to combat burden, but the processes underlying this behavior are unclear as previous studies have focused on the barriers to compliance rather than the barriers to providing high-quality data. This study aims to broaden researchers' knowledge about IR during ILD studies using qualitative analysis and uncover the underlying IR processes to aid future hypothesis generation. We explored the process of IR by conducting semistructured qualitative exit interviews with 31 young adult participants (aged 18-29 years) who completed a 12-month ILD health behavior study with daily evening smartphone-based ecological momentary assessment (EMA) surveys and 4-day waves of hourly EMA surveys. The interviews assessed participants' motivations, the impact of time-varying contexts, changes in motivation and response patterns over time, and perceptions of attention check questions (ACQs) to understand participants' response patterns and potential factors leading to IR. Thematic analysis revealed 5 overarching themes on factors that influence participant engagement: (1) friends and family also had to tolerate the frequent surveys, (2) participants tried to respond to surveys quickly, (3) the repetitive nature of surveys led to neutral responses, (4) ACQs within the surveys helped to combat overly consistent response patterns, and (5) different motivations for answering the surveys may have led to different levels of data quality. This study aimed to examine participants' perceptions of the quality of data provided in an ILD study to contribute to the field's understanding of engagement. These findings provide insights into the complex process of IR and participant engagement in ILD studies with EMA. The study identified 5 factors influencing IR that could guide future research to improve EMA survey design. The identified themes offer practical implications for researchers and study designers, including the importance of considering social context, the consideration of dynamic motivations, and the potential benefit of including ACQs as a technique to reduce IR and leveraging the intrinsic motivators of participants. By incorporating these insights, researchers might maximize the scientific value of their multimonth ILD studies through better data collection protocols. RR2-10.2196/36666.

Ecological momentary assessment (EMA) is a method of data collection that entails prompting individuals to report their experiences (e.g., thoughts, feelings, and behaviors) in real time over the course of their day-to-day lives. By providing rich information about how these experiences unfold over time within an individual, EMA has the potential to substantially advance our understanding of grief. However, there is uncertainty about how bereaved adults will respond to EMA, especially among those with high prolonged grief symptom severity. Accordingly, we evaluated the feasibility and acceptability of an EMA protocol in bereaved adults with low and high prolonged grief severity. Participants completed six 12-item EMA surveys per day on their smartphones for 17 days. Adherence was high (mean survey completion = 90%, median = 96%), and only 6% of participants withdrew. Adherence remained high in those with high prolonged grief symptom severity (mean = 86%; median = 96%). On average, participants reported agreement that survey frequency and length were acceptable. There was no evidence for systematic worsening of symptoms during EMA data collection. Together, these findings suggest that EMA is feasible, acceptable, and safe for bereaved adults, including those with high prolonged grief symptom severity.

Feasibility and utility of ecological momentary assessment to measure mental health issues in perinatal women: Scoping review.

BackgroundThere are significant racial disparities in pregnancy and postpartum health outcomes, including postpartum weight retention and cardiometabolic risk. These racial disparities are a result of a complex interplay between contextual, environmental, behavioral, and psychosocial factors.ObjectiveThis protocol provides a description of the development and infrastructure for the Postpartum Mothers Mobile Study (PMOMS), designed to better capture women’s daily experiences and exposures from late pregnancy through 1 year postpartum. The primary aims of PMOMS are to understand the contextual, psychosocial, and behavioral factors contributing to racial disparities in postpartum weight and cardiometabolic health, with a focus on the daily experiences of stress and racism, as well as contextual forms of stress (eg, neighborhood stress and structural racism).MethodsPMOMS is a longitudinal observation study that is ancillary to an existing randomized control trial, GDM2 (Comparison of Two Screening Strategies for Gestational Diabetes). PMOMS uses an efficient and cost-effective approach for recruitment by leveraging the infrastructure of GDM2, facilitating enrollment of participants while consolidating staff support from both studies. The primary data collection method is ecological momentary assessment (EMA) and through smart technology (ie, smartphones and scales). The development of the study includes: (1) the pilot phase and development of the smartphone app; (2) feedback and further development of the app including selection of key measures; and (3) implementation, recruitment, and retention.ResultsPMOMS aims to recruit 350 participants during pregnancy, to be followed through the first year after delivery. Recruitment and data collection started in December 2017 and are expected to continue through September 2020. Initial results are expected in December 2020. As of early May 2019, PMOMS recruited a total of 305 participants. Key strengths and features of PMOMS have included data collection via smartphone technology to reduce the burden of multiple on-site visits, low attrition rate because of participation in an ongoing trial in which women are already motivated and enrolled, high EMA survey completion and the use of EMA as a unique data collection method to understand daily experiences, and shorter than expected timeframe for enrollment because of the infrastructure of the GDM2 trial.ConclusionsThis protocol outlines the development of the PMOMS, one of the first published studies to use an ongoing EMA and mobile technology protocol during pregnancy and throughout 1 year postpartum to understand the health of childbearing populations and enduring racial disparities in postpartum weight and cardiometabolic health. Our findings will contribute to the improvement of data collection methods, particularly the role of EMA in capturing multiple exposures and knowledge in real time. Furthermore, the results of the study will inform future studies investigating weight and cardiometabolic health during pregnancy and the postpartum period, including how social determinants produce population disparities in these outcomes.International Registered Report Identifier (IRRID)DERR1-10.2196/13569

Ecological momentary assessment (EMA) is a promising method to gain insight into the daily lives of people with mental disorders. EMA can be used to monitor mood, symptoms, and experiences multiple times per day. Using advanced statistical methods, such as network analysis, as EMA feedback might result in novel insights that are relevant to psychiatric care.To investigate the promise, pitfalls, and possibilities of EMA and network analysis for psychiatric care.Empirical network studies, reviews, and qualitative research were employed to investigate the state of research and the perspectives of patients and clinicians on EMA and network analysis. Furthermore, an empirical study will be discussed, in which twenty patients with bipolar disorders completed five EMA diaries per day for four months within treatment.Studies using network analysis demonstrated conflicting results. Qualitative research indicated that bipolar patients and clinicians are aware of the added benefit of EMA for psychiatric care, especially for improving insight and self-management. At the same time, EMA was seen as burdensome. Personalization and integration with existing treatment protocols emerged as necessary requirements for adequate implementation of EMA in psychiatric care.EMA can have added value for psychiatric care, provided it is adequately implemented.Ecological momentary assessment (EMA) is a promising method to gain insight into the daily lives of people with mental disorders. EMA can be used to monitor mood, symptoms, and experiences multiple times per day. Using advanced statistical methods, such as network analysis, as EMA feedback might result in novel insights that are relevant to psychiatric care.To investigate the promise, pitfalls, and possibilities of EMA and network analysis for psychiatric care.Empirical network studies, reviews, and qualitative research were employed to investigate the state of research and the perspectives of patients and clinicians on EMA and network analysis. Furthermore, an empirical study will be discussed, in which twenty patients with bipolar disorders completed five EMA diaries per day for four months within treatment.Studies using network analysis demonstrated conflicting results. Qualitative research indicated that bipolar patients and clinicians are aware of the added benefit of EMA for psychiatric care, especially for improving insight and self-management. At the same time, EMA was seen as burdensome. Personalization and integration with existing treatment protocols emerged as necessary requirements for adequate implementation of EMA in psychiatric care.EMA can have added value for psychiatric care, provided it is adequately implemented.

Irritability presents transdiagnostically, commonly occurring with anxiety and other mood symptoms. However, little is known about the temporal and dynamic interplay among irritability-related clinical phenomena. Using a novel network analytic approach with smartphone-based ecological momentary assessment (EMA), we examined how irritability and other anxiety and mood symptoms were connected. Sample included 152 youth ages 8-18 years (M ± SD = 12.28 ± 2.53; 69.74% male; 65.79% White) across several diagnostic groups enriched for irritability including disruptive mood dysregulation disorder (n = 34), oppositional defiant disorder (n = 9), attention-deficit/hyperactivity disorder (n = 47), anxiety disorder (n = 29), and healthy comparisons (n = 33). Participants completed EMA on irritability-related constructs and other mood and anxiety symptoms three times a day for 7 days. EMA probed symptoms on two timescales: "since the last prompt" (between-prompt) versus "at the time of the prompt" (momentary). Irritability was also assessed using parent-, child- and clinician-reports (Affective Reactivity Index; ARI), following EMA. Multilevel vector autoregressive (mlVAR) models estimated a temporal, a contemporaneous within-subject and a between-subject network of symptoms, separately for between-prompt and momentary symptoms. For between-prompt symptoms, frustration emerged as the most central node in both within- and between-subject networks and predicted more mood changes at the next timepoint in the temporal network. For momentary symptoms, sadness and anger emerged as the most central node in the within- and between-subject network, respectively. While anger was positively related to sadness within individuals and measurement occasions, anger was more broadly positively related to sadness, mood lability, and worry between/across individuals. Finally, mean levels, not variability, of EMA-indexed irritability were strongly related to ARI scores. This study advances current understanding of symptom-level and temporal dynamics of irritability. Results suggest frustration as a potential clinically relevant treatment target. Future experimental work and clinical trials that systematically manipulate irritability-related features (e.g. frustration, unfairness) will elucidate the causal relations among clinical variables.