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

Developing a qualitative and quantitative ambulatory assessment-based feedback system within cognitive behavioural interventions for people with persecutory beliefs

Background

Although the application of self-monitoring (ambulatory assessment) and visual feedback in psychological interventions has yielded promising results, there are currently no reports on using self-monitoring and feedback during a complete therapy. The online m-Path platform provides a tailorable framework for integrating self-monitoring and visual feedback within different psychological interventions.

Methods

Therapy-specific questionnaires and visual feedback were developed within the online m-Path platform as part of the Feeling Safe-NL trial (registration number: ISRCTN25766661) for regular CBT for psychosis (CBTp) and the Feeling Safe Programme combined with peer counselling (the Feeling Safe-NL Programme). The design process involved people with lived experience, psychologists, peer counsellors, researchers, and software developers. The design principles included that the system should be 1) easy to use, 2) suitable for use during a six-month therapy, 3) focussed on positive and goal-aligned outcomes, 4) understandable by patients and professionals, and 5) informing, guiding, and promoting therapy. Design principles were evaluated using compliance data and a patient questionnaire.

Results

The system was used by 21 patients, of which nine completed the questionnaires for the full therapy period, 168 days on average. Usability data from patients revealed that the system was easy to use, well-explained, and suitable for use over six months of therapy. The patients also reported that the questions overall positively affected their emotions and that the feedback was insightful.

Conclusion

The results support the successful application of the design principles to promote the integration of the self-monitoring and visual feedback system within specific CBTp interventions.

Ecological Momentary Assessment in psychotherapy research: A systematic review

Ecological Momentary Assessment (EMA) stands as a valuable method to capture real-time data on individuals' daily experiences and behaviors. In recent years, the utilization of EMA as a measurement method has substantially increased with the majority of studies emphasizing its clinical utility. However, a comprehensive overview of its use in psychotherapy research is lacking. This study addresses that gap by systematically reviewing EMA's application in psychotherapy research. In total, 168 studies met the inclusion criteria and were classified according to clinical utilization. Six areas of clinical EMA application were identified: prediction of therapy outcome (n = 8), prediction of psychopathology (n = 40), prediction of biopsychosocial states (n = 44), evaluation of therapy outcome (n = 21), acquisition of further clinical insights into specific disorders (n = 68) and adaptation of treatment processes (n = 18). Despite studies consistently highlighting EMA's potential in tailoring psychotherapeutic treatments, its limited use in this area warrants further research. Drawing from our findings, we discuss future research directions for the direct application of EMA in psychotherapeutic settings.

The Association Between Cognitive Functioning and Depression Severity: A Multiwave Longitudinal Remote Assessment Study

Cognitive difficulties are prevalent in depression and are linked to various negative life outcomes such as psychosocial impairment, absenteeism, lower chance of recovery or remission, and overall poor quality of life. Thus, assessing cognitive functioning over time is key to expanding our understanding of depression. Recent methodological advances and the ubiquity of smartphones enable remote assessment of cognitive functioning through smartphone-based tasks and surveys. However, the association of smartphone-based assessments of cognitive functioning to depression severity remains underexplored. Using a dedicated mobile application for assessing cognitive functioning (THINC-it), we investigate within- and between-person associations between performance-based (attention, working memory, processing speed, attention switching) and self-report measures of cognitive functioning with depression severity in 475 participants from the RADAR-MDD (Remote Assessment of Disease and Relapse-Major Depressive Disorder) cohort study (t = 2036 observations over an average of 14 months of follow-up). At the between-person level, we found stronger negative associations between the self-reported cognitive functioning measure and depression severity (β = -0.649, p  < 0.001) than between the performance-based measures and depression severity (βs = -0.220 to -0.349, p s  < 0.001). At the within-person level, we found negative associations between depression severity and the self-reported measure (β = -0.223, p  < 0.001), processing speed (β = -0.026, p=0.032) and attention (β = -0.037, p=0.003). These findings suggest that although THINC-it could adequately and remotely detect poorer cognitive performance in people with higher depressive symptoms, it was not capable of tracking within-person change over time. Nonetheless, repeatedly measuring self-reports of cognitive functioning showed more potential in tracking within-person changes in depression severity, underscoring their relevance for patient monitoring.

Assessing and accounting for measurement in intensive longitudinal studies: current practices, considerations, and avenues for improvement

PURPOSE

Intensive longitudinal studies, in which participants complete questionnaires multiple times a day over an extended period, are increasingly popular in the social sciences in general and quality-of-life research in particular. The intensive longitudinal methods allow for studying the dynamics of constructs (e.g., how much patient-reported outcomes vary across time). These methods promise higher ecological validity and lower recall bias than traditional methods that question participants only once, since the high frequency means that participants complete questionnaires in their everyday lives and do not have to retrospectively report about a large time interval. However, to ensure the validity of the results obtained from analyzing the intensive longitudinal data (ILD), greater awareness and understanding of appropriate measurement practices are needed.

METHOD

We surveyed 42 researchers experienced with ILD regarding their measurement practices and reasons for suboptimal practices.

RESULTS

Results showed that researchers typically do not use measures validated specifically for ILD. Participants assessing the psychometric properties and invariance of measures in their current studies was even less common, as was accounting for these properties when analyzing dynamics. This was mainly because participants did not have the necessary knowledge to conduct these assessments or were unaware of their importance for drawing valid inferences. Open science practices, in contrast, appear reasonably well ingrained in ILD studies.

CONCLUSION

Measurement practices in ILD still need improvement in some key areas; we provide recommendations in order to create a solid foundation for measuring and analyzing psychological constructs.

The experience sampling methodology as a digital clinical tool for more person-centered mental health care: an implementation research agenda

This position paper by the international IMMERSE consortium reviews the evidence of a digital mental health solution based on Experience Sampling Methodology (ESM) for advancing person-centered mental health care and outlines a research agenda for implementing innovative digital mental health tools into routine clinical practice. ESM is a structured diary technique recording real-time self-report data about the current mental state using a mobile application. We will review how ESM may contribute to (1) service user engagement and empowerment, (2) self-management and recovery, (3) goal direction in clinical assessment and management of care, and (4) shared decision-making. However, despite the evidence demonstrating the value of ESM-based approaches in enhancing person-centered mental health care, it is hardly integrated into clinical practice. Therefore, we propose a global research agenda for implementing ESM in routine mental health care addressing six key challenges: (1) the motivation and ability of service users to adhere to the ESM monitoring, reporting and feedback, (2) the motivation and competence of clinicians in routine healthcare delivery settings to integrate ESM in the workflow, (3) the technical requirements and (4) governance requirements for integrating these data in the clinical workflow, (5) the financial and competence related resources related to IT-infrastructure and clinician time, and (6) implementation studies that build the evidence-base. While focused on ESM, the research agenda holds broader implications for implementing digital innovations in mental health. This paper calls for a shift in focus from developing new digital interventions to overcoming implementation barriers, essential for achieving a true transformation toward person-centered care in mental health.

Feedback About a Person's Social Context - Personal Networks and Daily Social Interactions

The social context of a person, meaning their social relationships and daily social interactions, is an important factor for understanding their mental health. However, personalised feedback approaches to psychotherapy do not consider this factor sufficiently yet. Therefore, we developed an interactive feedback prototype focusing specifically on a person's social relationships as captured with personal social networks (PSN) and daily social interactions as captured with experience sampling methodology (ESM). We describe the development of the prototype as well as two evaluation studies: Semi-structured interviews with students (N = 23) and a focus group discussion with five psychotherapy patients. Participants from both studies considered the prototype useful. The students considered participation in our study, which included social context assessment via PSN and ESM as well as a feedback session, insightful. However, it remains unclear how much insight the feedback procedure generated for the students beyond the insights they already gained from the assessments. The focus group patients indicated that in a clinical context, (social context) feedback may be especially useful to generate insight for the clinician and facilitate collaboration between patient and clinician. Furthermore, it became clear that the current feedback prototype requires explanations by a researcher or trained clinician and cannot function as a stand-alone intervention. As such, we discuss our feedback prototype as a starting point for future research and clinical implementation.

Introducing FRED: Software for Generating Feedback Reports for Ecological Momentary Assessment Data

Ecological Momentary Assessment (EMA) is a data collection approach utilizing smartphone applications or wearable devices to gather insights into daily life. EMA has advantages over traditional surveys, such as increasing ecological validity. However, especially prolonged data collection can burden participants by disrupting their everyday activities. Consequently, EMA studies can have comparably high rates of missing data and face problems of compliance. Giving participants access to their data via accessible feedback reports, as seen in citizen science initiatives, may increase participant motivation. Existing frameworks to generate such reports focus on single individuals in clinical settings and do not scale well to large datasets. Here, we introduce FRED (Feedback Reports on EMA Data) to tackle the challenge of providing personalized reports to many participants. FRED is an interactive online tool in which participants can explore their own personalized data reports. We showcase FRED using data from the WARN-D study, where 867 participants were queried for 85 consecutive days with four daily and one weekly survey, resulting in up to 352 observations per participant. FRED includes descriptive statistics, time-series visualizations, and network analyses on selected EMA variables. Participants can access the reports online as part of a Shiny app, developed via the R programming language. We make the code and infrastructure of FRED available in the hope that it will be useful for both research and clinical settings, given that it can be flexibly adapted to the needs of other projects with the goal of generating personalized data reports.

Studies of Social Anxiety Using Ambulatory Assessment: Systematic Review

BACKGROUND

There has been an increased interest in understanding social anxiety (SA) and SA disorder (SAD) antecedents and consequences as they occur in real time, resulting in a proliferation of studies using ambulatory assessment (AA). Despite the exponential growth of research in this area, these studies have not been synthesized yet.

OBJECTIVE

This review aimed to identify and describe the latest advances in the understanding of SA and SAD through the use of AA.

METHODS

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic literature search was conducted in Scopus, PubMed, and Web of Science.

RESULTS

A total of 70 articles met the inclusion criteria. The qualitative synthesis of these studies showed that AA permitted the exploration of the emotional, cognitive, and behavioral dynamics associated with the experience of SA and SAD. In line with the available models of SA and SAD, emotion regulation, perseverative cognition, cognitive factors, substance use, and interactional patterns were the principal topics of the included studies. In addition, the incorporation of AA to study psychological interventions, multimodal assessment using sensors and biosensors, and transcultural differences were some of the identified emerging topics.

CONCLUSIONS

AA constitutes a very powerful methodology to grasp SA from a complementary perspective to laboratory experiments and usual self-report measures, shedding light on the cognitive, emotional, and behavioral antecedents and consequences of SA and the development and maintenance of SAD as a mental disorder.

Planning Individual and Population-Based Interventions in Global Health: Applying the DEA-A Framework to Promote Behavioral, Emotional, and/or Cognitive Change among Stakeholders

Addressing health challenges that impact human well-being requires a comprehensive, interdisciplinary approach that would be at the crossroad of population-based prevention and individual-level clinical care, which is in line with a Global Health perspective. In the absence of a unifying theoretical framework to guide such interventions, a Dynamic Ecosystem Adaptation through the Allostasis (DEA-A) framework has been proposed, emphasizing the functional adaptation of individuals and organizations in symbiosis with their living ecosystem. While a conceptual model has been presented, this methodological contribution aims at illustrating the practical application of the DEA-A framework for planning Global Health interventions. The methodology combines Intervention Mapping and Cognitive and Behavioral Theory, extended to the ecosystem. Practical guidelines and supporting tools are provided to help public health providers and clinicians in establishing a functional ecosystem diagnosis of the issue; defining not only behavioral, but also emotional and cognitive change objectives (allostasis targets) expected for each stakeholder; and designing intervention plans targeting determinants of these allostasis. The discussion addresses implementation and evaluation perspectives of interventions based on the DEA-A framework, emphasizing the importance of considering change in its processual and ecosystem complexity. Lastly, encouragements for a deeper understanding of individual and ecosystem homeostasis/allostasis processes are made in order to promote more functional interventions.

Using the experience sampling method to support clinical practice: An illustration with problematic cannabis use

The experience sampling method (ESM) has been frequently used in clinical research; however, there is low translational uptake in clinical practice. This may be due to challenges with interpreting individual-level data at granular intervals. We provide an illustrative example of how ESM can be leveraged to generate personalized cognitive-behavioral strategies for problematic cannabis use.

We conducted a descriptive case series analysis using ESM data from 30 individuals reporting on problematic cannabis use, craving, affect, and coping four times daily for 16-days (t = 64, T = 1,920).

Analyzing ESM data using descriptive statistics and visualizations from individuals with similar clinical and demographic profiles supported a diverse array of personalized clinical insights and recommendations for each case. These recommendations included psychoeducation regarding affect- and boredom-regulation strategies, functional analyses of occasions during which cannabis was not used, and discussions on how cannabis use intersects with one's personal values.

While many clinicians utilize measurement-based care, barriers have limited the incorporation of ESM towards personalized, data-informed approaches to treatment. We provide an illustrative example of how ESM data can be used to generate actionable treatment strategies for problematic cannabis use and highlight continued challenges with interpreting time-series data.

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.

Feedback based on experience sampling data: Examples of current approaches and considerations for future research

Methodologies such as the Experience Sampling Method (ESM) or Ecological Momentary Assessment allow the gathering of fine-graded, dynamic, personal data within a patient's daily life. Currently, it is studied whether feedback based on experience sampling data (ESM-based feedback) can be used as a clinical tool to inform shared decision-making in clinical practice. Although the potential of feedback is recognized, little is known on how to generate, use, and implement it. This article (i) presents n = 15 ongoing ESM projects within the Belgian-Dutch network for ESM research wherein ESM-based feedback is provided to various patient populations, and (ii) summarizes qualitative data on experiences with ESM-based feedback of researchers (n = 8) with extensive expertise with ESM (average of 10 years) involved in these ongoing studies. The following aspects appear to be of relevance when providing ESM-based feedback: training for healthcare professionals and researchers, the use of online interfaces and graphical visualizations to present data, and interacting with patients in a face-to-face setting when discussing the contextual relevance and potential implications. Prospectively, research may build on these aspects and create coherent consensus-based guidelines for the use of ESM-based feedback.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

A digital patient-reported outcome (electronic patient-reported outcome) system for patients with severe psychiatric disorders: User-centered development study and study protocol of a multicenter-controlled trial

Background

The effective treatment of patients with severe psychiatric disorders primarily relies on subjective reporting of symptoms and side-effects. This information is crucial for a clinician's decision regarding medication adjustment. Treatment adjustment usually happens at a low frequency (∼4-8 weeks). In between points of care, patients are left alone with their symptoms and side-effects. This leads to uncertainty regarding the treatment, non-adherence, possible relapse, and rehospitalization.

Objectives

We aim to design a flexible electronic patient-reported outcome (ePRO) system, which allows patients with severe psychiatric disorders to: (a) record their symptoms using an app; (b) share the data with the clinical team at points of care; and (c) utilize the data to support therapy decisions.

Methods

In this article, we describe the development process which included the following steps: (a) formation of a co-design team; (b) stakeholder interviews with patients, practitioners, and digital health experts to access needs, requirements, and barriers; (c) prototype conceptualization and design; (d) user acceptance testing and refinement; and (e) finalization of the system for testing in a pilottrial.

Results

We included input from patients with lived experience of psychiatric disorders, clinical team members, software engineers, and researchers. A prototype system was refined, and iterative changes were made before finalization during a series of operational meetings. The system allows patients to digitally self-report their symptoms and provides longitudinal ePRO symptom data for export into the electronic health record.

Conclusions

Routine ePRO collection has the potential to improve outcomes and hereby also reduce health service costs. We have successfully developed a trial-ready ePRO system for severe psychiatric disorders. The findings were incorporated in the planning of a feasibility pilot trial. Assuming feasibility will be established, the system might be subjected to a certification process evaluation of safety and efficacy including a randomized controlled trial.

Examining Stress and Residual Symptoms in Remitted and Partially Remitted Depression Using a Wearable Electrodermal Activity Device: A Pilot Study

Consistent evidence suggests residual symptoms and stress are the most reliable predictors of relapse in remitted depression. Prevailing methodologies often do not enable continuous real-time sampling of stress. Thus, little is known about day-to-day interactions between residual symptoms and stress in remitted depression. In preparation for a full-scale trial, this study aimed to pilot a wrist-worn wearable electrodermal activity monitor: ADI (Analog Devices, Inc.) Study Watch for assessing interactions between physiological stress and residual depressive symptoms following depression remission. 13 individuals remitted from major depression completed baseline, daily diary, and post-daily diary assessments. Self-reported stress and residual symptoms were measured at baseline and post-daily diary. Diary assessments required participants to wear ADI's Study Watch during waking hours and complete self-report questionnaires every evening over one week. Sleep problems, fatigue, energy loss, and agitation were the most frequently reported residual symptoms. Average skin conductance responses (SCRs) were 16.09 per-hour, with an average of 11.30 hours of wear time per-day. Increased residual symptoms were associated with enhanced self-reported stress on the same day. Increased SCRs on one day predicted increased residual symptoms on the next day. This study showed a wearable electrodermal activity device can be recommended for examining stress as a predictor of remitted depression. This study also provides preliminary work on relationships between residual symptoms and stress in remitted depression. Importantly, significant findings from the small sample of this pilot are preliminary with an aim to follow up with a 3-week full-scale study to draw conclusions about psychological processes explored. Clinical and Translational Impact Statemen-ADI's wearable electrodermal activity device enables a continuous measure of physiological stress for identifying its interactions with residual depressive symptoms following remission. This novel procedure is promising for future studies.

Common methods of determining meaningful change in clinical practice: implications for precision patient-reported outcomes

PURPOSE

Patient-reported outcomes (PROs) are used in clinical practice for several purposes, including to monitor whether a treatment is working or whether a patient is experiencing adverse events from treatment. This study surveyed oncology providers (OP) and mental health providers (MHP) to determine how clinicians from different disciplines determine individual-level meaningful change on PROs. Understanding how clinicians determine change on PROs could help inform methods for individualizing meaningful change definitions, an approach we have dubbed "Precision PROs".

METHODS

Three hundred and forty-seven providers utilizing PROs completed an online survey about PRO use to monitor patients in clinical practice. A question on methods used to determine individual-level meaningful change on PROs was developed with input from clinicians. Multivariate logistic regression analyses were used to assess whether specific methods were associated with clinician characteristics.

RESULTS

The most commonly reported method was comparing the previous score to the current score (65%). Other methods included examining the numerical scores without a visual aid (59%), considering other factors affecting scores (42%), comparing scores to norms (31%) and using a graph of scores (29%). Provider age was negatively associated with odds of using a graph (OR = 0.95, 95% CI 0.91, 1.0) but no other method. Provider gender, hours per week in clinical practice and years in practice were not associated with odds of using a specific method.

CONCLUSIONS

Most providers determined individual-level meaningful change without a visual aid and used only the previous score and current score, the minimum number (2 scores) to determine change. Consistent with current practice, future research on methods of determining within-individual meaningful change for clinical use should focus on methods requiring two rather than three or more scores. When attempting to personalize within-individual change definitions (Precision PROs), methods examining a baseline and single follow-up may be most useful for clinical practice.

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.

Measurement-Based and Data-Informed Psychological Therapy

Outcome measurement in the field of psychotherapy has developed considerably in the last decade. This review discusses key issues related to outcome measurement, modeling, and implementation of data-informed and measurement-based psychological therapy. First, an overview is provided, covering the rationale of outcome measurement by acknowledging some of the limitations of clinical judgment. Second, different models of outcome measurement are discussed, including pre-post, session-by-session, and higher-resolution intensive outcome assessments. Third, important concepts related to modeling patterns of change are addressed, including early response, dose-response, and nonlinear change. Furthermore, rational and empirical decision tools are discussed as the foundation for measurement-based therapy. Fourth, examples of clinical applications are presented, which show great promise to support the personalization of therapy and to prevent treatment failure. Finally, we build on continuous outcome measurement as the basis for a broader understanding of clinical concepts and data-driven clinical practice in the future. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Some socially poor but also some socially rich adolescents feel closer to their friends after using social media

Who benefits most from using social media is an important societal question that is centered around two opposing hypotheses: the rich-get-richer versus the poor-get-richer hypothesis. This study investigated the assumption that both hypotheses may be true, but only for some socially rich and some socially poor adolescents and across different time intervals. We employed a state-of-the-art measurement burst design, consisting of a three-week experience sampling study and seven biweekly follow-up surveys. Person-specific analyses of more than 70,000 observations from 383 adolescents revealed that 12% of the socially rich adolescents (high in friendship support or low in loneliness) felt closer to their friends after using social media, as opposed to about 25% of the socially poor adolescents (low in friendship support or high in loneliness). However, only 1 to 6% of all adolescents (socially rich and poor) felt closer both in the short- and longer-term. These results indicate that the rich-get-richer and the poor-get-richer hypotheses can hold both, but for different adolescents.