Person-centred leadership analysis: lessons from PLOS One

According to the PLOS One article by Klinga et al. (published July 22, 2026), a six-month blended educational programme was experienced by participants to influence leadership at three levels: self-leadership, team-leadership, and workforce development.

• 80 leaders were admitted to the programme in 2022, reported by Klinga et al. in PLOS One (2026).
• 13 leaders were purposefully interviewed between 27 January 2023 and 16 March 2023, three to five months after programme completion, with interviews lasting 40–65 minutes (mean 52 minutes), as reported in PLOS One (Klinga et al., 2026).
• When preconditions such as managerial support and time for coaching were present, participants reported measurable changes in practice across the three development tracks in July 2026, according to Klinga et al., PLOS One.
• A participant in Klinga et al., PLOS One (2026) put it plainly, “You get the chance to pause and reflect in a way that you don’t usually do” (participant, Interview 10, Klinga et al., PLOS One, July 22, 2026).

Answer: Klinga et al. evaluated leader experiences after a six-month educational programme using individual interviews and conventional content analysis.

According to the PLOS One article (Klinga et al., 2026), the programme combined six modules, a flipped-classroom pedagogy, workplace assignments, and workshops designed to operationalise the GPCC framework for person-centred care.

According to Klinga et al. (PLOS One, 2026), 80 leaders entered the 2022 cohort, 13 were interviewed between 27 January and 16 March 2023, and interviews were transcribed verbatim and analysed with an abductive, conventional content analysis approach to produce three analytical tracks: self-leadership, team-leadership, and workforce development.

Answer: The PLOS One study demonstrates best practices for programme-focused qualitative evaluation that AI-enabled methods can accelerate without sacrificing rigor.

According to Klinga et al., PLOS One (2026), embedding assignments in workplace settings and interviewing participants three to five months post-programme produced rich behavioural accounts that captured implementation conditions and barriers.

According to the PLOS One article (Klinga et al., 2026), credible qualitative inference depended on transparent coding, negotiated consensus among multiple analysts, and careful reflexivity; AI tools should augment rather than replace these steps by streamlining transcription, code suggestion, and audit-trail generation.

Klinga et al.’s PLOS One study (published July 22, 2026) shows that a six-month, blended person-centred leadership programme can produce self-reported changes in self-leadership, team-leadership, and workforce development when organisational preconditions are met.

For qualitative researchers, the study underscores the value of workplace-embedded assignments, delayed interviews (three to five months), and transparent analytic procedures that AI can accelerate without replacing human interpretation.

If you evaluate leadership programmes and want to compress transcription-to-insights time while keeping auditability, consider tools that combine accurate speech-to-text, hierarchical coding, and collaborative audit trails.

Get started with an AI workflow designed for qualitative researchers, or Try Evidano for free.