Qualitative Analysis of Hearing Program (SOUND-BITES)

Evidano is an AI-powered qualitative data analysis platform that helps teams transform SOUND-BITES audio, surveys, and clinical outputs into reproducible themes and stakeholder-ready visuals.

The SOUND-BITES pilot embeds hearing checks into Meals on Wheels NSW, generating mixed-methods data ideal for AI-assisted synthesis and cross-segment analysis.

• Design and timeline: the protocol is published in PLoS One on 14 July 2026, with full data collection expected by 30 April 2027 and preliminary results anticipated on 01 September 2027.
• Scope and sample: the study recruits 60 volunteers and targets 600 clients or household members, combining Arclight otoscopy with the Sound Scouts tablet audiometry app.
• Analytic payoff: standardized interview guides, audio recordings, survey CSVs (HHIE‑S, SSQ‑12, EQ‑5D‑5L), and NVivo-ready transcripts make the data ideal for secure transcription, TDF-aligned coding, and cross-segment frequency analysis.

This section summarizes what the SOUND-BITES study offers researchers in one sentence: the program embeds hearing checks into Meals on Wheels NSW deliveries and pairs Arclight otoscopy with the Sound Scouts tablet audiometry app to collect mixed-methods data.

The protocol is published in PLoS One.

• Design: mixed-methods pilot testing acceptability and feasibility; qualitative interviews + pre/post surveys + clinical screening data.
• Why it matters: task-shifted hearing checks can surface undiagnosed loss in a trusted community service and generate rich qualitative data on barriers and uptake.
• Quick payoff for analysts: standardized interview guides, audio recordings, survey CSVs, and NVivo-ready transcripts, ideal inputs for AI-assisted synthesis.

The SOUND-BITES pilot pairs low-cost clinical tools (Arclight otoscope and the Sound Scouts app) with Meals on Wheels NSW volunteers and Master of Clinical Audiology students to deliver in-home hearing checks and education.

The protocol describes the clinical flow, data collected, and the qualitative plan for transcripts and thematic coding.

• Clinical flow: otoscopy (Arclight) → 8–10 minute Sound Scouts screening (iPad + Sennheiser headphones) → feedback and referral materials.
• Data collected: audiometric outputs (hearing numbers, pass/refer), structured otoscopy observations, baseline + 6-month surveys (HHIE‑S, SSQ‑12, EQ‑5D‑5L), and optional recorded interviews at ~4 weeks.
• Qualitative plan: audio-recorded interviews transcribed (intelligent verbatim), accuracy-checked, participant-validated, then coded in NVivo using the Theoretical Domains Framework (TDF) with dual coders and consensus processes.

This checklist describes the seven steps to go from recordings to recommendations using the protocol’s materials and Evidano capabilities.

• 1) Collect audio and screening outputs and label metadata (site, date, hearing pass/refer, volunteer ID).
• 2) Upload audio and CSV surveys to Evidano; enable a custom dictionary with local clinical terms and service names.
• 3) Run secure transcripts with PII redaction; send transcripts back to participants for the two-week validation window (per protocol).
• 4) Import transcripts and the TDF codebook into Evidano; run automated pre-coding and review dual-coder disagreements.
• 5) Generate thematic summaries, quote atlases, and co-occurrence networks; filter by segment (age group, pass/refer, geography).
• 6) Merge survey outcomes (HHIE‑S change, help-seeking) for cross-segment analysis and simple GLM-ready exports.
• 7) Produce a stakeholder brief (visuals and a 1‑page decision memo) and schedule a Q&A with operational partners.

This section summarises the study and next steps: SOUND-BITES (Tang et al., PLoS One, 14 July 2026) is a timely, well-documented pilot that pairs accessible mHealth tools with a trusted community service to reach older adults and creates a strong basis for AI-enabled qualitative synthesis.

• Try a secure pilot: upload a small set (5–10) of interviews and the associated survey CSV to Evidano to validate code mapping and theme recovery before scaling.
• Security note: this research-focused analysis is non-diagnostic; follow local ethics and consent processes for any clinical recommendations.

Ready to test these steps with your own SOUND-BITES-style data? Try Evidano for free and we will help you map transcripts, codes, and survey merges into a reproducible analysis pipeline.