m-Path: an easy-to-use and highly tailorable platform for ecological momentary assessment and intervention in behavioral research and clinical practice.

In this paper, we present m-Path (www.m-Path.io), an online platform that provides an easy-to-use and highly tailorable framework for implementing smartphone-based ecological momentary assessment (EMA) and intervention (EMI) in both research and clinical practice in the context of blended care. Because real-time monitoring and intervention in people's everyday lives have unparalleled benefits compared to traditional data collection techniques (e.g., retrospective surveys or lab-based experiments), EMA and EMI have become popular in recent years. Although a surge in the use of these methods has led to a myriad of EMA and EMI applications, many existing platforms only focus on a single aspect of daily life data collection (e.g., assessment vs. intervention, active self-report vs. passive mobile sensing, research-dedicated vs. clinically-oriented tools). With m-Path, we aim to integrate all of these facets into a single platform, as it is exactly this all-in-one approach that fosters the clinical utility of accumulated scientific knowledge. To this end, we offer a comprehensive platform to set up complex and highly adjustable EMA and EMI designs with advanced functionalities, using an intuitive point-and click web interface that is accessible for researchers and clinicians with limited programming skills. We discuss the strengths of daily life data collection and intervention in general and m-Path in particular. We describe the regular workflow to set up an EMA or EMI design within the m-Path framework, and summarize both the basic functionalities and more advanced features of our software.

Usability of the Experience Sampling Method in Specialized Mental Health Care: Pilot Evaluation Study.

BACKGROUND: Mental health problems occur in interactions in daily life. Yet, it is challenging to bring contextual information into the therapy room. The experience sampling method (ESM) may facilitate this by assessing clients' thoughts, feelings, symptoms, and behaviors as they are experienced in everyday life. However, the ESM is still primarily used in research settings, with little uptake in clinical practice. One aspect that may facilitate clinical implementation concerns the use of ESM protocols, which involves providing practitioners with ready-to-use ESM questionnaires, sampling schemes, visualizations, and training. OBJECTIVE: This pilot study's objective was to evaluate the usability of an ESM protocol for using the ESM in a specialized mental health care setting. METHODS: We created the ESM protocol using the m-Path software platform and tested its usability in clinical practice. The ESM protocol consists of a dashboard for practitioners (ie, including the setup of the template and data visualizations) and an app for clients (ie, for completing the ESM questionnaires). A total of 8 practitioners and 17 clients used the ESM in practice between December 1, 2020, and July 31, 2021. Usability was assessed using questionnaires, ESM compliance rates, and semistructured interviews. RESULTS: The usability was overall rated reasonable to good by practitioners (mean scores of usability items ranging from 5.33, SD 0.91, to 6.06, SD 0.73, on a scale ranging from 1 to 7). However, practitioners expressed difficulty in personalizing the template and reported insufficient guidelines on how to use the ESM in clinical practice. On average, clients completed 55% (SD 25%) of the ESM questionnaires. They rated the usability as reasonable to good, but their scores were slightly lower and more variable than those of the practitioners (mean scores of usability items ranging from 4.18, SD 1.70, to 5.94, SD 1.50 on a scale ranging from 1 to 7). Clients also voiced several concerns over the piloted ESM template, with some indicating no interest in the continued use of the ESM. CONCLUSIONS: The findings suggest that using an ESM protocol may facilitate the implementation of the ESM as a mobile health assessment tool in psychiatry. However, additional adaptions should be made before further implementation. Adaptions include providing training on personalizing questionnaires, adding additional sampling scheme formats as well as an open-text field, and creating a dynamic data visualization interface. Future studies should also identify factors determining the suitability of the ESM for specific treatment goals among different client populations.

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.

Assessing the reliability of single-item momentary affective measurements in experience sampling.

Emotion researchers that use experience sampling methods (ESM) study how emotions fluctuate in everyday life. To reach valid conclusions, confirming the reliability of momentary emotion measurements is essential. However, to minimize participant burden, ESM researchers often use single-item measures, preventing a reliability assessment of people's emotion ratings. Furthermore, because emotions constantly change, checking reliability via conventional test-retest procedures is impractical, for it is impossible to separate measurement error from meaningful emotional variability. Here, drawing from classical test theory (CTT), we propose two time-varying test-retest adaptations to evaluate the reliability of single-item (emotion) measures in ESM. Following Method 1, we randomly repeat one emotion item within the same momentary survey and evaluate the discrepancy between test and retest ratings to determine reliability. Following Method 2, we introduce a subsequent, shortly delayed retest survey and extrapolate the size of test-retest discrepancies to the hypothetical instance where no time between assessments would exist. First, in an analytical study, we establish the mathematical relation between observed test-retest discrepancies and measurement error variance for both methods, based on common assumptions in the CTT literature. Second, in two empirical studies, we apply both methods to real-life emotion time series and find that the size of error in people's emotion ratings corresponds with almost a 10th of the scale, comprising around 27% of the total variability in participants' affective responses. Consequently, disregarding measurement error in ESM is problematic, and we encourage researchers to include a test-retest procedure in their future studies when relying on single-item measures. (PsycInfo Database Record (c) 2022 APA, all rights reserved).