ArticleInternational journal of qualitative methods
A Comparison of Leximancer Semi-automated Content Analysis to Manual Content Analysis: A Healthcare Exemplar Using Emotive Transcripts of COVID-19 Hospital Staff Interactive Webcasts.
Article in International journal of qualitative methods. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Impact of Digital Hospitals on Patient and Clinician Experience: Systematic Review and Qualitative Evidence Synthesis.Journal of medical Internet research · 2024Pooled it
- Reflecting on LLM Support in Reflexive Thematic Analysis: An Exploratory Study.Qualitative health research · 2026Article
- Establishing research and translation priorities and care pathways for families where a parent lives with mental ill health.PLOS mental health · 2026Article
- Artificial intelligence after the bedside: co-design of AI-based clinical informatics workflows to routinely analyse patient-reported experience measures in hospitals.BMJ health & care informatics · 2024Article
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4 authors.
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Abstract
Effective consumer centred healthcare incorporates consumer and clinician perspectives into decision making, in addition to traditional quantitative measures. This information is usually captured in qualitative data that requires manual analysis. Healthcare systems often lack resources to systematically incorporate qualitative feedback into decision making. Semi-automated content analysis tools, such as Leximancer, provide an efficient and objective alternative to time consuming manual content analysis (MCA). Literature on the validity of Leximancer in healthcare is sparse. This study seeks to validate Leximancer against MCA on a broad emotive conversational dataset gathered in a healthcare setting. At the outset of the COVID-19 pandemic, a large Australian hospital and health service conducted interactive webcasts with staff to provide updates and answer questions. A manual thematic analysis and a Leximancer content analysis were conducted independently on 20 webcast transcripts. The findings were compared, along with the time required to the complete each analysis. The Leximancer analysis identified nine concepts, while the manual analysis identified 12 concepts. The Leximancer concepts mapped to five of the concepts identified in the manual analysis, which accounted for 74% of mentions tagged in the text through the manual analysis. Leximancer missed concepts which required an emotional or contextual interpretation. The Leximancer analysis took 21 hours (excluding time to learn the program), compared to 73 hours for the manual analysis. Semi-automated content analysis provides an efficient alternative to manual qualitative data analysis, shifting it from a small-scale research activity to a more routine operational activity, albeit with some limitations. This is critical to be able to utilise at scale the rich narratives from consumers and clinicians in healthcare decision making.
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