What Nursing Students Say: AI Qualitative Analysis

The November 5, 2026 PLOS One study on nursing students’ practicum experiences found that supplementary open-ended responses added context to quantitative findings about nursing competency, learning stress, and clinical practice.

• The study analyzed 699 complete responses collected from nursing students in northern Taiwan between October and November 2023.
• All 699 participants answered both open-ended questions, but thematic coding produced 217 non-mutually-exclusive segment-to-theme assignments rather than prevalence estimates.
• Two researchers reached 92% initial percentage agreement before resolving coding differences through discussion and consensus.
• The study reported that nursing-process ratings were below sample grand means, while communication and biomedical-science classifications were unstable across 5, 000 bootstrap samples.
• The authors cautioned that the findings describe perceptions and exploratory associations, not observed competence, validated stress constructs, or causal effects.

The study found that open-ended practicum comments helped explain how nursing students experienced theory-practice integration, care-plan preparation, communication, nursing skills, and stress.

According to Tsai and Chen’s November 5, 2026 PLOS One article, the researchers invited all 730 eligible third-year nursing students, received 702 signed consent forms and questionnaires, excluded 3 incomplete questionnaires, and analyzed 699 participants.

The quantitative survey measured perceived importance and self-rated performance satisfaction across five competency domains. The study used sample grand means of 4.679 for importance and 4.503 for satisfaction as importance-performance crosshairs.

The qualitative component asked students, “What was your greatest gain during the practicum? ” and “What was your greatest difficulty during the practicum? ” The researchers coded meaningful response segments inductively, organized codes into themes, retained divergent cases, and maintained an audit trail.

Tsai and Chen reported that the qualitative findings partially converged with the survey results. Students described gains in communication and nursing skills, while written comments also highlighted nursing-process assignments, theory-practice integration, and stress.

The authors explicitly wrote that qualitative and quantitative findings should be interpreted without “forcing agreement between the two sources of data.”

Nursing education researchers should use qualitative analysis to explain survey patterns, not to convert self-reported experiences into claims about clinical competence.

The November 5, 2026 study demonstrates why researchers should separate three outputs: what students rated, what students described, and what the data can legitimately establish. Self-rated performance satisfaction is not the same as observed clinical performance, and cross-sectional stress associations do not establish causality.

• Treat coded theme counts as coding assignments when participants can contribute multiple segments or themes.
• Report the response denominator, the number of meaningful coded segments, and whether themes are mutually exclusive.
• Preserve negative or divergent cases instead of forcing every response into a dominant theme.
• Connect qualitative themes to quantitative measures through a joint display, while retaining contradictions between the two evidence sources.
• Use validated stress measures, objective competency assessments, and longitudinal or clustered designs before making intervention claims.

The study also shows why AI-assisted coding requires human review. Automated thematic analysis can accelerate organization and comparison, but researchers still need to define coding units, inspect ambiguous responses, document decisions, and distinguish descriptive patterns from causal evidence.

The November 5, 2026 PLOS One study shows that qualitative analysis can add important context to nursing education surveys, especially when students describe practicum gains, theory-practice difficulties, and stress.

The study also demonstrates why careful coding documentation matters: theme counts, self-ratings, stress scores, and importance-performance classifications each answer different research questions.

AI-enabled qualitative research can reduce the time required to organize open-ended responses and compare segments, while human researchers retain responsibility for interpretation, ethics, and methodological rigor.

Teams studying nursing education, clinical training, or student experience can try Evidano for free to analyze qualitative data alongside survey responses.