ESMAC: A Web-Based Configurator for Context-Aware Experience Sampling Apps in Ambulatory Assessment

Abstract

In ambulatory assessment, psychologists apply experience sampling methods (ESM) on mobile devices to assess self-reports from subjects. One major challenge is to support domain experts to create ESM apps themselves without prior programming knowledge. When running ESM apps, subjects are prompted to answer self-reports time-triggered at fixed points in time or randomly. The compliance of the subjects often drops due to a high frequency of prompts or a high number of questions to be answered. We propose ESMAC, an open-source ESM app configuration system that is easy to use by non-programmers and able to create context-aware apps. Leveraging context-awareness can counteract a drop in compliance by prompting event-based only in situations of relevance (reducing the frequency) and by automatically assessing information (decreasing the number of questions). The ESMAC web interface for configuring ESM apps was evaluated with two psychologists. One of their configurations was deployed and evaluated in a preliminary user study with ESM subjects. Both experiments yielding good results using SUS and UEQ benchmarks. In addition, we analyzed the share of triggers and identified that 84% of all prompts were event- and not time-based. This emphasizes the relevance of event-triggers.

Keywords

• mobile sensing
• context awareness
• experience sampling
• ambulatory assessment