Qualitative Analysis of mHealth App Usability

This post summarizes how to run a rapid, mixed-methods qualitative analysis of an mHealth diet app usability pilot (MyIBDDiet, July 2, 2026; n=40) and how Evidano supports transcription, AI-assisted coding, and linking themes to analytics to accelerate reproducible synthesis.

• MyIBDDiet is a 60-day, single-centre pilot randomized trial (published July 2, 2026) enrolling 40 participants that uses MAUQ, TFA, semi-structured interviews, and app analytics to assess usability.
• Pair validated acceptability scales (MAUQ, TFA) with interview themes and app analytics to distinguish usability problems from contextual engagement issues.
• Evidano ingests audio, performs verbatim transcription with custom dictionaries, supports PII redaction, provides AI-assisted auto-tagging of CFIR/TFA codebooks, and links themes to backend metrics for cross-segment analysis.
• A 7-step Evidano workflow can move a pilot from raw interviews to stakeholder-ready themes in roughly 10–14 days at pilot scale.

The MyIBDDiet protocol described a 60-day, single-centre pilot randomized trial (published July 2, 2026) of an anti-inflammatory diet app for people with IBD, enrolling 40 participants and using mixed-methods usability assessment.

Full protocol: PLOS One protocol.

• Primary outcome: usability (quantitative MAUQ plus qualitative interviews).
• Why this matters: co-design and qualitative interview data determine acceptability, implementation barriers, and refinement priorities before a larger RCT.

The protocol specified a mixed-methods approach: validated usability scales (MAUQ), the Theoretical Framework of Acceptability (TFA), and semi-structured interviews framed by CFIR, with verbatim transcription and analysis until thematic saturation.

• Interview framing: CFIR captured barriers and facilitators to adoption and implementation.
• Coding: two researchers independently coded transcripts with a third reviewer resolving conflicts, using thematic analysis per Braun and Clarke (2006).
• Triangulation: themes were compared with app analytics (usage patterns) and quantitative acceptability scores to prioritise features for iteration.

Follow these seven steps to move from raw interviews to stakeholder-ready themes in 10–14 days at pilot scale.

• 1) Import audio and metadata into Evidano; enable PII redaction and load a custom diet/IBD dictionary.
• 2) Auto-transcribe; review and correct high-priority segments.
• 3) Upload MAUQ and TFA survey CSVs for cross-linking to participant IDs.
• 4) Import the initial CFIR/TFA codebook and run AI-assisted auto-tagging.
• 5) Human review: adjudicate tags, merge duplicates, and finalise hierarchical themes.
• 6) Run cross-segment analyses (for example, by engagement quartile or disease activity) and generate co-occurrence networks.
• 7) Export a one-page decision brief and a quote library for product sprint planning.

Adopt a mixed-methods pipeline that links interview themes to usage data and validated acceptability scales for pilots like MyIBDDiet (published July 2, 2026; n=40; 60-day pilot).

Ready to compress weeks of analysis into days? See how Evidano integrates transcription, codebook import, AI-assisted thematic analysis, and cross-segment visualisations to produce reproducible deliverables, or Try Evidano for free.

Ethics note: this guidance is research-focused and non-diagnostic; follow local ethics and consent procedures when handling participant data.