This post shows how AI-enabled qualitative analysis can accelerate and deepen evaluations of leadership programmes, aimed at evaluation teams and qualitative researchers. The primary keyword for this post is ai qualitative analysis leadership programmes. According to the PLOS One study, the six-month person-centred leadership programme under study enrolled 80 leaders in 2022 and produced interview data that illuminated changes in self-leadership, team leadership, and workforce development, as reported in PLOS One.
Key Takeaways
The PLOS One study found that a six-month person-centred leadership programme influenced leaders’ self-leadership, team-leadership, and workforce development, according to PLOS One.
- 80 leaders were admitted to the programme in 2022, according to PLOS One.
- 13 leaders were purposefully interviewed between 27/01/2023 and 16/03/2023, with interviews lasting 40–65 minutes (mean 52 minutes), as reported in PLOS One.
- The study published on 22 July 2026 concluded that workplace-based assignments, reflective practices, and managerial support were key preconditions for sustaining person-centred leadership, according to PLOS One.
What happened and how the study worked
The PLOS One article documents a six-month educational programme on person-centred leadership delivered in 2022, and the paper evaluated leaders’ experiences through qualitative interviews, according to PLOS One.
According to PLOS One, the programme combined a flipped-classroom pedagogy, six modules, workplace assignments, and reflective journals to anchor learning in practice.
According to PLOS One, the researchers conducted 13 individual interviews between 27 January and 16 March 2023, transcribed them verbatim, and analysed them using conventional content analysis with three analytical tracks: self-leadership, team-leadership, and workforce development.
According to PLOS One, the final interpretation produced an overarching theme, three visions (Live as you learn, Strive for equal relations, Enable co-creation), and nine sub-categories that described behavioural and cultural shifts.
Findings snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| 2022 | Programme admissions | 80 leaders admitted | Programme scale supports workplace-based learning cohorts |
| 27/01/2023–16/03/2023 | Interviews | 13 leaders interviewed | Purposeful sampling across settings yields diverse leadership perspectives |
| Jan–Mar 2023 | Interview length | 40–65 minutes, mean 52 minutes | Depth of interviews supports rich thematic analysis |
| 22 July 2026 | Publication | PLOS One article published | Peer-reviewed evidence base for programme effects |
Implications for qualitative researchers evaluating leadership programmes
For qualitative researchers, the PLOS One study shows that embedding learning in workplace tasks and collecting in-depth interviews yields change narratives that link individual reflection to team and organisational outcomes, according to PLOS One.
- Design sampling to capture heterogeneity: the PLOS One study purposefully sampled 13 leaders across sectors to reflect diverse roles, according to PLOS One.
- Use workplace-based assignments as data sources: the study found that workplace assignments and reflective journals strengthened transfer of learning to practice, according to PLOS One.
- Triangulate perspectives: the study recommends including employees, patients, and relatives to validate whether care has become more person-centred, according to PLOS One.
How Evidano Helps
Problem: rich interview data but slow synthesis
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Solution: Evidano automates thematic clustering and extracts illustrative quotes so teams can move from 13 long interviews to a coded synthesis in hours rather than weeks, preserving traceability to verbatim source text.
Problem: inconsistent terminology and multi-site programmes
Solution: Evidano supports custom dictionaries and translation controls so researchers can normalise terms like “person-centred leadership” across transcripts and sites, which mirrors the PLOS One study’s emphasis on adopting a shared language, according to PLOS One.
See feature details at the Evidano features page: Evidano features.
Problem: interview audio to transcript quality and privacy
Solution: Evidano offers accurate transcription with custom dictionaries and PII redaction and a dedicated speech-to-text pipeline for interview audio, which speeds preparation for coding while protecting sensitive data.
Solution: Evidano encrypts project data and does not use customer data to train third-party models, supporting ethics and confidentiality for studies under approvals like the Swedish Ethical Review Authority described in PLOS One.
Problem: need to compare segments (self-leadership vs team-leadership)
Solution: Evidano produces cross-segment analyses and visualizations so evaluators can quantify how many participants mention themes like “reflective practice” and link those mentions to excerpts and dates, supporting the mixed interpretive approach used in the PLOS One study.
FAQ: AI qualitative analysis of leadership programmes
How can AI accelerate analysis of interview data from leadership programmes?
AI can accelerate coding and clustering so analysts reach thematic saturation faster.
For example, the PLOS One study collected 13 interviews averaging 52 minutes each, and AI-enabled tools can pre-code transcripts to highlight the self-leadership, team-leadership, and workforce development tracks used by the authors, according to PLOS One.
Will AI change the interpretive quality of qualitative research?
AI augments but does not replace researcher interpretation, it speeds routine tasks and surfaces patterns for human analysts.
Researchers should maintain reflexive practices, as the PLOS One authors did, and use AI outputs as starting points for negotiated consensus in coding and interpretation, according to PLOS One.
Can AI tools preserve participant confidentiality in sensitive studies?
Yes, when platforms provide PII redaction and project-level encryption.
For studies governed by ethical approvals such as the Swedish Ethical Review Authority referenced in PLOS One, researchers must ensure storage and access controls; Evidano provides PII redaction and encryption features to support compliance.
What concrete outputs should evaluators aim to deliver after reanalyzing a leadership programme?
Evaluators should deliver a themed codebook, frequency counts by segment, illustrative quotations, and a synthesis linking activities to outcomes.
The PLOS One study exemplifies this by reporting themed visions and sub-categories alongside participant quotations and context, a format that AI-assisted reports can replicate and expand with cross-segment tables.
Conclusion & Next Steps
The PLOS One evaluation shows that workplace-based learning, reflective practice, and managerial support shape person-centred leadership, according to PLOS One.
For qualitative teams, combining careful sampling and reflexive analysis with AI-enabled synthesis reduces time to insight and makes it practical to include additional perspectives such as employees and patients.
If you want to prototype AI-assisted reanalysis of leadership programme data, Try Evidano for free to upload transcripts, run thematic and cross-segment analyses, and export quotation-backed reports.