Cut Usability Time: qualitative analysis of app usability

Evidano is an AI-powered qualitative data analysis platform that ingests interview transcripts, questionnaires, ASA24 exports, and app analytics, then produces thematic coding, cross-tabs, and secure, reproducible reports.

Evidano can accelerate synthesis for MyIBDDiet-style mixed-methods pilots by automating transcription, AI-assisted coding, cross-segmentation, and stakeholder-ready exports.

• The MyIBDDiet pilot protocol was published 2 July 2026 in PLoS One and defines a 60-day randomized pilot with n = 40 and a 30-day crossover.
• Primary outcomes are mixed-methods usability measures (MAUQ, TFA) combined with semi-structured interviews, backend app analytics, ASA24 dietary recalls, and biomarkers.
• A two-week Evidano runbook moves raw audio, CSVs, and analytics to validated transcripts, AI-assisted coding, cross-tabs, and an exportable recommendation report.

The MyIBDDiet pilot (published 2 July 2026) tests usability and acceptability of a Mediterranean-style diet app for people with IBD, using mixed quantitative scales and semi-structured interviews. Full protocol: PLoS One.

• Primary outcome: usability measured with MAUQ and TFA, plus qualitative interviews.
• Design: a 60-day single-centre randomized pilot with n = 40 (20 per arm) and a 30-day crossover.
• Why researchers care: the pilot yields interview transcripts, app analytics, dietary recalls (ASA24), and biomarkers, a rich dataset for AI-enabled qualitative synthesis.

MyIBDDiet is a co-designed nutrition app that tracks foods (Canadian Nutrient File, USDA, and other regional DBs), flags ultra-processed items via NOVA, and links symptom logs to meals. The pilot randomizes 40 adults with IBD to immediate app access or usual care with a 30-day delayed crossover.

• Usability is measured quantitatively with MAUQ scores and TFA constructs, and qualitatively through semi-structured interviews until thematic saturation.
• Secondary data include ASA24 dietary recalls, spot urine sodium/chloride (processed food biomarkers), CRP and fecal calprotectin, and exploratory microbiome/metabolome profiles.
• App analytics (engagement logs, barcode scans, processing-level tags) are captured at the backend, a source for mixed-method triangulation.

Qualitative researchers and UX teams should combine validated usability scales with semi-structured interviews and backend analytics to capture behavior, perception, and objective use. The MyIBDDiet protocol provides a practical template for that mix.

• Use paired MAUQ and TFA to quantify acceptability domains and link those numeric constructs to interview themes (for example, link burden to login friction).
• Triangulate app logs with interview claims to prioritize UX fixes, for example compare claimed daily use with actual session counts.
• Collect diet recalls and simple biomarkers to test whether behavior-change claims map to objective signals when product claims touch clinical outcomes.

A two-week runbook converts raw files into stakeholder-ready insight using Evidano.

• Day 1–2: Ingest files, upload interview audio, MAUQ and TFA CSVs, ASA24 exports, and app analytics CSVs. Use a custom dictionary to normalize food terms and IBD jargon.
• Day 3–5: Auto-transcribe audio with PII redaction if needed; review and approve transcripts.
• Day 6–8: Auto-code with an initial codebook (MAUQ domains and CFIR constructs); run thematic extraction and a co-occurrence network to reveal dominant theme clusters.
• Day 9–11: Cross-segment analysis, compare themes by engagement quartile, MAUQ score bands, or biomarker change (for example, sodium delta).
• Day 12–14: Export a stakeholder-ready report with top themes, representative quotes, word clouds, and a recommendation checklist for UX and clinical teams.

The MyIBDDiet pilot (protocol published 2 July 2026 in PLoS One) is a concise example of rigorous mixed-methods evaluation for a diet-focused mHealth app: combine validated usability scales, semi-structured interviews, and backend analytics to capture perception and behavior.

• Start by prescribing the same data collection mix used in the pilot: validated usability scales (MAUQ and TFA), semi-structured interviews, and backend analytics.
• Use Evidano to ingest, code, cross-tab, and visualize themes securely, then export reproducible reports for clinicians and product owners.
• See the protocol in PLoS One.

Learn how to run a pilot-to-insight pipeline on Evidano and start a secure trial with your transcripts and analytics. Try Evidano for free.