This post explains how strategy mapping software was used to run a participatory evaluation of crisis management and how AI-enabled qualitative research can scale and sharpen similar evaluations. The primary keyword strategy mapping software refers to collaborative causal-mapping tools such as the browser-based application evaluated in the PLOS ONE case study. The intended audience is evaluation leads, qualitative researchers, and crisis preparedness teams who want practical steps to convert workshop conversations into actionable recommendations and measurable follow up.
Key Takeaways
According to the PLOS ONE article (Björnqvist et al., published 20 August 2026) the strategy mapping software supported a four-workshop participatory evaluation that produced ten participant-developed recommendations and measurable follow-up one year later: "Yes, I would say that it absolutely has been started" (Interviewee 2, quoted in PLOS ONE).
- 15 healthcare professionals participated in the workshops between 3 April 2023 and 12 June 2023, according to PLOS ONE (Björnqvist et al., 20 August 2026).
- The study reports ten recommendations were produced in the workshops and ten of the 15 participants were interviewed in spring 2024 to assess perceived use, according to PLOS ONE (Björnqvist et al., 20 August 2026).
- Participants rated and validated risks and recommendations in real time using the strategy mapping software, and many interviewees said the process produced "helpful, easy to understand, and timely" recommendations (Interviewee comments quoted in PLOS ONE).
- PLOS ONE (Björnqvist et al., 20 August 2026) also found limits: several participants described recommendations as sometimes "too vague" or dependent on other organizations, which reduced immediate actionability.
What happened and how the study measured impact
Answer: The PLOS ONE case study used a four-stage participatory evaluation guided by strategy mapping software to evaluate a unit's COVID-19 crisis management and then measured perceived impact with follow-up interviews.
According to PLOS ONE (Björnqvist et al., 20 August 2026), the evaluation involved 15 employees from a unit for communicable disease and infection control and ran four workshops: 3 April 2023, 6 April 2023, 24 April 2023, and 12 June 2023.
According to PLOS ONE (Björnqvist et al., 20 August 2026), workshop steps followed the strategy mapping four subtasks: brainstorm statements, cluster statements, causally link statements into maps, and derive recommendations targeting central risks using software analytical tools.
According to PLOS ONE (Björnqvist et al., 20 August 2026), the study then interviewed ten of the original 15 participants in spring 2024 to assess whether recommendations were used, how participants perceived clarity and feasibility, and whether the participatory process itself produced learning.
According to PLOS ONE (Björnqvist et al., 20 August 2026), the evaluation produced ten recommendations, several of which participants reported had been started, incorporated into projects, or used to prioritize changes; the authors also archived analytic materials in Zenodo with restricted access per participant consent.
Findings snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| 3 Apr 2023 – 12 Jun 2023 | Workshops run | 4 workshops with 15 participants | Drawn-out, reflective process that enabled individual then collective mapping (PLOS ONE, 20 Aug 2026) |
| 24 Apr 2023 | Recommendation development | 10 participant-developed recommendations | Produced actionable ideas but several were later described as vague or dependent (PLOS ONE, 20 Aug 2026) |
| Spring 2024 | Follow-up interviews | 10 of 15 participants interviewed (~1 year later) | Majority reported partial use or projects started, but perceptions varied (PLOS ONE, 20 Aug 2026) |
| 20 Aug 2026 | Publication | PLOS ONE peer-reviewed article (Björnqvist et al.) | Provides documented case and recommendations for future participatory evaluations |
Implications for evaluators and qualitative researchers
Answer: Evaluators should treat strategy mapping software as a method to increase stakeholder ownership while planning explicit facilitator steps to boost recommendation clarity and follow-up.
According to PLOS ONE (Björnqvist et al., 20 August 2026), stakeholder involvement increased perceived impact and produced individual and collective learning, but some interviewees described recommendations as "too vague" and recommended more facilitator polishing before dissemination.
According to PLOS ONE (Björnqvist et al., 20 August 2026), the study authors propose shortening or redesigning sessions (for example reducing from four workshops to two) if time constraints or motivation are limiting factors, but they caution that fewer sessions could weaken ownership.
Practical guidance for evaluators based on PLOS ONE (Björnqvist et al., 20 August 2026): define what "use" means before follow-up, set expectations for facilitator edits, and use participant rating features (importance, feasibility, effectiveness) during the workshop to prioritize implementable recommendations.
How Evidano helps convert participatory workshops into rigorous qualitative evidence
Problem: workshop notes and transcripts are fragmented → Solution: thematic synthesis and traceability
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Problem: PLOS ONE (Björnqvist et al., 20 August 2026) shows workshops create maps, ratings, and free-text recommendations that need synthesis; evaluators in that study used manual transcription cleanup and directed content analysis.
Solution: Evidano ingests workshop transcripts, maps, and survey-style ratings to produce thematic coding, frequency counts, and cross-segment comparisons to identify which recommendations are most mentioned, who supports them, and which roles report use.
Problem: participant-developed recommendations are actionable but sometimes vague → Solution: AI-assisted recommendation sharpening
Problem: The PLOS ONE study found several recommendations were described by participants as "too vague" or dependent on external organizations (Björnqvist et al., 20 August 2026).
Solution: Evidano can summarize participant recommendations, propose specificity (actors, timelines, dependencies) and generate a facilitator-ready draft for validation with participants, preserving provenance and participant phrasing while improving actionability. See Evidano features for analytics and traceability.
Problem: follow-up measurement is uneven → Solution: structured follow-up and AI chat over evidence
Problem: PLOS ONE measured impact via interviews one year later with varied perceptions of use (Björnqvist et al., 20 August 2026).
Solution: Evidano supports survey imports and scripted follow-up interviews, automatic transcription with PII redaction, and an AI chat over your documents to ask, "Which recommendations were implemented by June 2024? " and produce reproducible usage tallies for management and publication.
FAQ: strategy mapping software
What is strategy mapping software and why use it for participatory evaluation?
Answer: Strategy mapping software is a collaborative causal-mapping tool that supports stakeholder brainstorming, clustering, causal linking, and prioritization, and it helps structure participatory evaluations.
Support: The PLOS ONE case study used Strategyfinder-style software to run live anonymous and open gathers, link risks causally, and let participants rate importance and feasibility, which participants described as an "innovative and useful method" (Björnqvist et al., PLOS ONE, 20 August 2026).
How do I ensure recommendations from a participatory workshop are actionable?
Answer: Define actionability criteria in advance, use facilitator editing with participant validation, and capture dependencies explicitly.
Support: The authors of PLOS ONE (Björnqvist et al., 20 August 2026) recommend greater facilitator involvement in clarifying recommendations and suggest a follow-up validation session so edits do not erode participant ownership.
Can AI be used ethically in translating and reproducing workshop maps?
Answer: Yes, when AI is used for translation and reproduction under researcher verification and not for analysis without disclosure.
Support: PLOS ONE (Björnqvist et al., 20 August 2026) used a large language model (M365 Copilot, GPT-5 architecture) to translate and recreate strategy maps and explicitly verified outputs against originals; the authors noted the model was not used for data generation or interpretation.
How do I measure whether recommendations were used after one year?
Answer: Use a predefined definition of "use", combine structured surveys with targeted interviews, and triangulate with document or project logs.
Support: PLOS ONE (Björnqvist et al., 20 August 2026) found varied responses in one-year follow-up interviews and recommends predefining what counts as implementation to reduce interpretive variance across roles.
Conclusion & Next Steps
Answer: The PLOS ONE case study (Björnqvist et al., published 20 August 2026) demonstrates that strategy mapping software can produce stakeholder-owned recommendations and measurable learning, but facilitators should plan edits and follow-up to increase clarity and implementation.
If you run participatory evaluations, define use criteria before follow-up, capture ratings and causal links during workshops, and plan a short facilitator validation step to sharpen recommendations without eroding ownership, as recommended by the PLOS ONE authors (Björnqvist et al., 20 August 2026).
Evidano can automate transcription cleanup, thematic coding, and recommendation traceability and provide AI-assisted drafting and validation workflows to speed the path from workshop maps to implemented change; learn more on our features page.
Next step: bring your workshop transcripts, maps, and rating sheets into a reproducible qualitative pipeline and measure change over time. Try Evidano for free.
Topics
- strategy mapping software
- participatory evaluation
- AI-enabled qualitative analysis
- qualitative evaluation software
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