Related Experiment Video
Updated: Jan 29, 2026

Measuring Engagement of Spectators of Social Digital Games
Published on: July 3, 2021
A Framework for Analyzing and Measuring Usage and Engagement Data (AMUsED) in Digital Interventions: Viewpoint
Sascha Miller1, Ben Ainsworth2, Lucy Yardley1,3
1Center for Clinical and Community Applications of Health Psychology, Department of Psychology, University of Southampton, Southampton, United Kingdom.
Abstract:
Trials of digital interventions can yield extensive, in-depth usage data, yet usage analyses tend to focus on broad descriptive summaries of how an intervention has been used by the whole sample. This paper proposes a novel framework to guide systematic, fine-grained usage analyses that better enables understanding of how an intervention works, when, and for whom. The framework comprises three stages to assist in the following: (1) familiarization with the intervention and its relationship to the captured data, (2) identification of meaningful measures of usage and specifying research questions to guide systematic analyses of usage data, and (3) preparation of datasheets and consideration of available analytical methods with which to examine the data. The framework can be applied to inform data capture during the development of a digital intervention and/or in the analysis of data after the completion of an evaluation trial. We will demonstrate how the framework shaped preparation and aided efficient data capture for a digital intervention to lower transmission of cold and flu viruses in the home, as well as how it informed a systematic, in-depth analysis of usage data collected from a separate digital intervention designed to promote self-management of colds and flu. The Analyzing and Measuring Usage and Engagement Data (AMUsED) framework guides systematic and efficient in-depth usage analyses that will support standardized reporting with transparent and replicable findings. These detailed findings may also enable examination of what constitutes effective engagement with particular interventions.
More Related Videos
08:04Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
Published on: December 4, 2013
12:22Mindfulness in Motion MIM: An Onsite Mindfulness Based Intervention MBI for Chronically High Stress Work Environments to Increase Resiliency and Work Engagement
Published on: July 1, 2015
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Statistical Methods to Analyze Parametric Data: ANOVA
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
Nursing Interventions I: Taxonomy of Nursing Interventions
A nursing intervention is a treatment or action based on scientific concepts and knowledge from the nursing, behavioral, and physical sciences. Identifying and prioritizing nursing interventions based on the desired outcome...
Nursing Interventions II: Selecting and Classifying the Nursing Interventions
Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with...
Community Based Intervention
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...