AI Thematic Analysis in Healthcare: MS Study

According to the PLOS One study protocol, the planned study will evaluate online mindfulness-based cognitive therapy for people with multiple sclerosis and mild-to-moderate depression through a mixed-methods design, not through qualitative evidence alone. The protocol demonstrates how AI thematic analysis in healthcare could help researchers manage interview transcripts, implementation frameworks, and cross-group comparisons while preserving human interpretation.

• The study protocol, published on November 13, 2026, plans a minimum randomized trial sample of 152 people with multiple sclerosis and mild-to-moderate depression.
• The protocol, registered on July 31, 2026, plans semi-structured interviews with 30 to 40 participants, healthcare professionals, mindfulness instructors, and multiple sclerosis decision makers.
• The planned intervention consists of eight weekly online sessions, and the protocol schedules quantitative data collection at baseline, immediately after treatment at week 8, and follow-up at week 21.
• The protocol specifies inductive thematic analysis followed by deductive analysis using the Consolidated Framework for Implementation Research.
• The study authors state that qualitative methods can explain not only whether the intervention works, but also "how the intervention is perceived and should be implemented."

According to Simpson and colleagues' 2026 protocol, the study is designed to test both the effectiveness and implementation of tailored online mindfulness-based cognitive therapy for people with multiple sclerosis and mild-to-moderate depression.

The protocol describes a type 1 hybrid effectiveness-implementation study conducted online through the University of Toronto. The design combines a waitlist randomized controlled trial, embedded qualitative interviews, and a process evaluation guided by the RE-AIM framework and informed by PRISM.

The protocol sets the primary quantitative outcome as change in depression measured by the Hospital Anxiety and Depression Scale, Depression subscale. The protocol also defines a 20% reduction in that measure as an exploratory minimally important difference.

The protocol states that interviews will examine motivations, acceptability, accessibility, perceived effects, and barriers and facilitators to implementation. The study authors write that qualitative research can provide "a meaningful platform for participants to share their own unique experiences" with the intervention.

The protocol is not a completed clinical trial report. According to the study timeline, recruitment was expected to begin on November 1, 2026, data collection was expected to finish in March 2028, and results were expected in spring 2028.

For healthcare researchers, the protocol shows that thematic analysis should answer implementation questions alongside outcome questions. Simpson and colleagues designed interviews to explore why participants join, what makes the intervention acceptable, which barriers affect participation, and how healthcare professionals and decision makers view delivery.

For mixed-methods teams, the protocol requires separate analysis of quantitative and qualitative evidence before integration through a joint display. That structure means researchers need a traceable path from transcript excerpts to codes, themes, stakeholder segments, and final meta-inferences.

For implementation teams, the protocol's use of RE-AIM, PRISM, and the Consolidated Framework for Implementation Research creates a practical need for both inductive and deductive coding. Inductive analysis can surface unexpected experiences, while framework-based coding can organize evidence around adoption, reach, implementation, and maintenance.

For healthcare organizations, the protocol emphasizes that online access does not automatically establish acceptability or scalability. The study authors note that tailoring, accessibility, community, and continued support are important considerations for digital interventions, but the planned study will provide the relevant evidence for this population.

Healthcare research involving depression requires an ethics-first workflow. AI-assisted analysis should support de-identified, research-focused interpretation and should not be used to diagnose individuals or replace clinical safety procedures.

The 2026 PLOS One protocol shows how qualitative interviews can explain the acceptability, accessibility, and implementation of an online intervention alongside randomized outcome data. AI thematic analysis in healthcare can make that evidence easier to organize across stakeholder groups, frameworks, and time points, while researchers retain responsibility for interpretation and ethics.

Evidano can help healthcare and implementation teams move from transcripts to structured themes, cross-segment comparisons, and evidence-backed research questions in one workspace. Try Evidano for free to explore an AI-assisted qualitative research workflow.