Qualitative researchers and organisational learning teams need reliable, fast methods to extract themes, quotations, and contextual preconditions from leadership-training studies. The primary keyword for this post, qualitative analysis person-centred leadership, describes the task: synthesising interview data about how leaders change when trained in person-centred leadership. According to the PLOS One study by Klinga et al. (2026), a six-month educational programme run in 2022 enrolled 80 admitted leaders and produced 13 in-depth interviews analysed in early 2023. This post refracts those findings through the lens of AI-enabled qualitative research, showing how automated ingestion, thematic coding, frequency counts, and extractable quotations speed synthesis while preserving traceability to original transcripts.
Key Takeaways
According to the PLOS One study by Klinga et al. (2026), participation in a six-month person-centred leadership programme in 2022 was experienced to change leaders’ practices at three levels: self-leadership, team-leadership, and workforce development. PLOS One
- 13 leaders were interviewed between 27 January 2023 and 16 March 2023, and the interviews averaged 52 minutes each, according to PLOS One (Klinga et al., 2026).
- The programme admitted 80 leaders in 2022 and ran six modules combining flipped-classroom digital content, in-person workshops, and workplace-based assignments, according to PLOS One (Klinga et al., 2026).
- Participants reported three development visions ("Live as you learn, " "Strive for equal relations, " and "Enable co-creation") that map to concrete actions leaders used to translate person-centred ethics into practice, as reported by PLOS One (Klinga et al., 2026).
What happened and how it was measured
Answer: The PLOS One study used purposive sampling and conventional content analysis to explore leaders’ experiences after a six-month programme offered in 2022. According to PLOS One (Klinga et al., 2026), the authors purposefully selected 13 participants from the cohort of 80 admitted leaders in 2022 and conducted individual digital interviews between 27 January 2023 and 16 March 2023.
According to PLOS One (Klinga et al., 2026), interviews lasted 40 to 65 minutes (mean 52 minutes), were transcribed verbatim, and were analysed using conventional content analysis with an interpretative step that linked categories to an overarching theme using three leadership concepts.
According to PLOS One (Klinga et al., 2026), the programme curriculum included six modules (foundations, communication, implementation strategies, being person-centred, ethics, and leading future care) and required workplace assignments and reflective journals to ground learning in practice.
Findings snapshot
| Date / Period | Metric | Value (from study) | Implication for qualitative synthesis |
|---|---|---|---|
| 2022 | Programme admissions | 80 leaders admitted | Provides population frame for purposive sampling and transferability notes |
| 27 Jan–16 Mar 2023 | Interviews conducted | 13 interviews, mean 52 min | Rich transcripts for thematic and quotation extraction |
| July 22, 2026 | Publication date | PLOS One article published | Peer-reviewed source to cite when reporting synthesis and recommendations |
Implications for qualitative researchers and health care evaluators
Answer: The PLOS One findings show that leadership changes are multi-level and context-dependent, so qualitative analyses must preserve participant voice and organisational preconditions. According to PLOS One (Klinga et al., 2026), leaders described development across self, team, and workforce levels and emphasised organisational preconditions such as managerial support and time to coach teams.
Researchers should therefore prioritise coding schemes that 1) separate self-leadership, team-leadership, and workforce-development codes, 2) tag quotations with timestamps and interview IDs, and 3) capture preconditions and barriers as distinct analytic categories, as suggested by the PLOS One study (Klinga et al., 2026).
Practitioners and evaluators should note that the study reported variable uptake: some participants described rapid mindset shifts while others cited insufficient organisational preconditions, which implies that programme effect sizes are likely heterogeneous and warrant mixed-methods follow-up, according to PLOS One (Klinga et al., 2026).
Ethics note: This post summarises non-diagnostic, research-focused findings; the original study restricted data access for confidentiality via the Swedish Ethical Review Authority, according to PLOS One (Klinga et al., 2026).
How Evidano Helps
Evidano: what it is
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Evidano’s platform preserves traceability, so quotations like "You get the chance to pause and reflect in a way that you don’t usually do" (Interview 10, PLOS One, 2026) can be linked back to timestamped transcripts and source IDs.
Problem: manual synthesis is slow → Solution: thematic + frequency analysis
Problem statement: Manual coding of 13 long interviews (mean 52 minutes) and related workplace assignments is time-consuming and error prone, as indicated by the workload described in PLOS One (Klinga et al., 2026).
Evidano feature: Automated thematic extraction and code co-occurrence networks identify the three development tracks (self-leadership, team-leadership, workforce development) within minutes, with frequency counts and exportable codebooks. See Evidano features.
Problem: quotations need verbatim accuracy → Solution: transcription + redaction
Problem statement: Quotation accuracy and privacy matter when reporting interview excerpts such as "It’s about using words without defining what we mean by those words" (Interview 5, PLOS One, 2026).
Evidano feature: Integrated transcription with custom dictionaries and PII redaction preserves verbatim quotes and enables audit-ready provenance; learn more at Evidano speech-to-text.
Problem: linking participant-level context to themes → Solution: cross-segment analysis
Problem statement: The PLOS One authors linked codes to preconditions and organisational context, a task that benefits from cross-segment comparison (e.g., leaders with 3–20 years of experience), according to PLOS One (Klinga et al., 2026).
Evidano feature: Cross-segment analysis lets researchers filter themes by leadership experience, region, or role and generate visualizations that show whether themes like "Enable co-creation" cluster by context, with downloadable tables for reporting. See Evidano features.
FAQ: qualitative analysis person-centred leadership
What methods did the PLOS One study use to analyze leaders’ experiences?
Answer: The study used conventional content analysis of verbatim interview transcripts, with iterative coding and an interpretative step connecting categories to an overarching theme, according to PLOS One (Klinga et al., 2026).
Supporting detail: The authors applied three analytical tracks (self-leadership, team-leadership, workforce development) to structure interpretation and used negotiated consensus coding among authors to enhance trustworthiness, according to PLOS One (Klinga et al., 2026).
How can AI preserve the nuance of person-centred quotations?
Answer: AI can preserve nuance by aligning automated transcripts with original audio timestamps and surfacing verbatim quotations for human validation.
Supporting detail: For example, the PLOS One study includes verbatim quotes such as "You get the chance to pause and reflect in a way that you don’t usually do" (Interview 10, PLOS One, 2026); AI workflows should show both the extracted quote and its transcript context for reviewer confirmation.
How many participants are typical for this kind of qualitative evaluation?
Answer: Small purposive samples are common; the PLOS One study analysed 13 interviews from a 2022 cohort of 80 admitted leaders, which the authors considered sufficient using information power guidelines, according to PLOS One (Klinga et al., 2026).
Supporting detail: The study cites Malterud et al. (2016) on information power to justify sample size decisions and reports interviews conducted between 27 January 2023 and 16 March 2023, according to PLOS One (Klinga et al., 2026).
Conclusion & Next Steps
Answer: The PLOS One study (Klinga et al., 2026) documents that a structured six-month person-centred leadership programme produced multi-level changes in leaders’ practices when organisational preconditions were present.
Researchers who need to reproduce or extend that synthesis should preserve interview provenance, tag preconditions as distinct codes, and extract representative quotations for transparent reporting, following the methods described in PLOS One (Klinga et al., 2026).
If you run qualitative evaluations of leadership programmes and want faster thematic synthesis, traceable quotations, and cross-segment charts, Evidano can ingest transcripts and deliver codebooks and visualisations ready for publication; learn more at Evidano features.
Next step: Try Evidano for free.