Supporting Systematic Assessment of Digital Interventions: A Framework for Analysing and Measuring Usage and Engagement Data (AMUsED)

Sascha Miller, Benjamin Ainsworth, Lucy Yardley, Alexander Milton, Mark Weal, Peter Smith, Leanne Morrison

Research output: Contribution to journalArticle

6 Citations (Scopus)


Introduction: Trials of digital interventions (DIs) 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.
Framework for Analysing and Measuring Usage and Engagement Data description: The framework comprises three stages to assist: 1) familiarisation 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; 3) preparation of datasheets, and consideration of available analytical methods with which to examine the data.
Framework application: The framework can be applied to inform data capture during the development of a DI 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 DI to lower transmission of cold and flu viruses in the home, and informed a systematic in-depth analysis of usage data collected from a separate DI designed to promote self-management of colds and flu.
Conclusions: The 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.
Original languageEnglish
Article numbere10966
JournalJournal of Medical Internet Research
Issue number2
Publication statusPublished - 15 Feb 2019


  • behavioral research; internet; health; patient engagement; data analysis

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