Qualitative Analysis of Clinical Supervision in Lesotho

According to the Clinical supervision in public hospitals in Lesotho: Nurse managers’ support for registered nurses, clinical supervision combines performance monitoring, quality assurance, resource management, professional development, conflict management, and psychosocial support.

The November 5, 2026 PLOS One study found that nurse managers supported registered nurses through structured supervisory practices, but faced challenges involving staff attitudes, skill gaps, limited preparation, and the absence of standardized supervision frameworks.

• Researchers conducted eight face-to-face interviews with nurse managers across eight public hospitals in Lesotho between May 1 and July 31, 2024.
• The qualitative analysis identified three main themes and eight sub-themes using thematic analysis based on Braun and Clarke’s six-step approach.
• The interviews lasted between 45 and 60 minutes, and the researchers considered data saturation achieved after the eighth interview.
• The study found that supervision included human resource support, equipment and supply monitoring, clinical guideline access, performance appraisal, quality audits, mentoring, and emotional support.
• The study reported that nurse managers needed additional capacity-building and structured supervision tools to address knowledge limitations and inconsistent supervisory practice.

The Lesotho study used an exploratory descriptive qualitative design to understand nurse managers’ experiences in their natural hospital settings. According to the November 5, 2026 PLOS One article, purposive sampling selected nurse managers who were registered with the Lesotho Nursing Council and had at least six months of experience in a public hospital.

The research team collected data through recorded, verbatim, face-to-face interviews conducted from May 1 to July 31, 2024. According to the study, the central interview question was, “What support do you provide to registered nurses during clinical supervision? ”

The researcher and an independent co-coder analyzed the transcripts using the six steps of thematic analysis: familiarization, initial coding, theme development, theme review, theme definition, and reporting. According to the study, the researchers compared codes, resolved discrepancies through consensus, revisited transcripts, and used participant quotations to connect findings to the original data.

The study’s design provides a useful model for AI-enabled qualitative research because the dataset was small but conceptually rich. AI can accelerate transcript organization, code discovery, theme comparison, and retrieval of supporting quotations, while researchers remain responsible for interpretation, reflexivity, ethics, and contextual judgment.

The Lesotho study demonstrates how qualitative research can reveal the full scope of clinical supervision, from quality audits and resource management to mentoring and psychosocial support. The study’s eight interviews produced three themes and eight sub-themes, showing why careful coding and contextual interpretation matter even in a small dataset. AI-enabled qualitative analysis can help healthcare researchers process transcripts faster, retrieve evidence, and compare supervisory experiences without removing human oversight. Teams analyzing nursing interviews or other sensitive healthcare data can try Evidano for free and build a more efficient, auditable research workflow.