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

M. Mestdagh, S. Verdonck, M. Piot, K. Niemeijer, G. Kilani, F. Tuerlinckx, P. Kuppens, E. Dejonckheere

Research output: Contribution to journalArticleScientificpeer-review

14 Citations (Scopus)
49 Downloads (Pure)

Abstract

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.
Original languageEnglish
Article number1182175
Number of pages11
JournalFrontiers in digital health
Volume5
Early online date2023
DOIs
Publication statusPublished - 2023

Keywords

  • ambulatory assessment
  • blended care
  • daily life
  • experience sampling
  • just-in-time adaptive interventions
  • mental health
  • mobile sensing
  • smartphones

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