Researchers and public health teams need reliable methods to examine how adolescent-led interventions challenge the fossil fuel industry. The primary keyword for this post is "qualitative analysis of youth climate interventions" and this post explains how to combine realist review methods with AI-enabled qualitative tools to speed synthesis, preserve nuance, and surface equity-relevant mechanisms for policy action. The Protocol by Deivanayagam et al., published in PLOS One on August 13, 2026, is the source text for this post and the practical steps below translate that protocol into AI-enabled qualitative research practice.
Key Takeaways
Deivanayagam et al., PLOS One (published August 13, 2026) set out a realist review protocol to identify how interventions involving adolescents can counter the fossil fuel industry and reduce health inequities, with a structural racism lens PLOS One.
- 1) Deivanayagam et al., PLOS One (published August 13, 2026) note an estimated 2.5 million deaths annually linked to outdoor air pollution from burning fossil fuels, underscoring the scale of harm.
- 2) Deivanayagam et al., PLOS One (published August 13, 2026) report that 67% of greenhouse gas emissions are attributable to fossil fuel combustion, situating interventions in a systems-level problem.
- 3) The review protocol began in October 2024 and aimed to complete evidence searches by April 2026, with results expected in July 2026 and dissemination through April 2027, showing a multi-year synthesis timetable.
- 4) The protocol uses realist review methods and the Context–Mechanism–Outcome framework to explain how adolescent involvement produces change, prioritising equity and participation.
What Happened / How the PLOS One protocol works
The PLOS One protocol describes a realist review to explain how interventions involving adolescents counter fossil fuel industry practices and reduce health inequities.
Deivanayagam et al., PLOS One (published August 13, 2026) define the review scope to include programmes, campaigns, litigation, and advocacy involving adolescents aged 10–19, and they will prioritise studies describing participation at Hart’s rung five and above.
Deivanayagam et al., PLOS One (published August 13, 2026) plan five realist stages: scoping, building initial programme theories, systematic evidence search, selection and appraisal, and extraction and synthesis, following RAMESES standards.
Deivanayagam et al., PLOS One (published August 13, 2026) explicitly apply a structural racism lens and examine corporate political activity, quoting the industry practice definition as “practices to secure preferential treatment and/or prevent, shape, circumvent or undermine public policies in ways that further corporate interests.”
Deivanayagam et al., PLOS One (published August 13, 2026) include youth involvement in study design, naming a Youth Advisory Board of six adolescents aged 14–17 from England and an expert steering group to refine program theories.
Findings Snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| August 13, 2026 | Protocol published | PLOS One realist review protocol | Methodological roadmap for analysing adolescent interventions |
| As cited in PLOS One (Aug 13, 2026) | Annual deaths from outdoor fossil fuel pollution | 2.5 million deaths per year | Frames public health urgency for interventions |
| As cited in PLOS One (Aug 13, 2026) | Share of greenhouse gases from fossil fuels | 67% of greenhouse gases | Positions interventions within climate mitigation priorities |
| 2022 and 2023 (as cited in PLOS One) | Health sector advocacy | 192 organisations in 2022; 46.3 million health workers represented in 2023 | Shows growing institutional support for fossil fuel phase-out |
| October 2024 → April 2027 (protocol timeline) | Project timeline | Start Oct 2024, evidence collection aimed Apr 2026, dissemination by Apr 2027 | Indicates staged synthesis and iterative stakeholder engagement |
Implications for qualitative researchers and evaluators
Use realist, equity-centred synthesis to explain not just whether youth interventions work but how and for whom they work.
Deivanayagam et al., PLOS One (published August 13, 2026) recommend Context–Mechanism–Outcome configurations, which means qualitative analysts should extract context (setting, power relations), mechanisms (why participants act), and outcomes (policy, behaviour, equity) from each source.
Deivanayagam et al., PLOS One (published August 13, 2026) emphasise grey literature and movement ecosystems, so researchers must include campaign reports, legal filings, social media archives, and youth testimony when building programme theories.
Deivanayagam et al., PLOS One (published August 13, 2026) stress prioritising racially minoritised adolescents’ perspectives, which requires sampling, translation, and analytic practices that surface epistemic injustice and participation quality.
How Evidano Helps
What is Evidano and why use it here?
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Realist reviews and equity-focused syntheses require indexing diverse documents, extracting CMO-relevant excerpts, and iterating programme theories; Evidano automates ingestion and coding to speed these steps while preserving context.
For protocols like Deivanayagam et al., PLOS One (published August 13, 2026), the ability to combine academic papers, NGO reports, legal documents, and youth transcripts makes large-scale CMO mapping feasible.
Problem: Large, mixed document sets slow synthesis → Solution: Thematic and cross-segment analysis
Problem: Realist reviews draw on academic, grey, and movement sources which are time-consuming to screen and code.
Solution: Evidano’s document ingestion and AI-assisted thematic extraction lets teams tag contexts, mechanisms, and outcomes across hundreds of files and then export CMO-aligned excerpts for stakeholder workshops.
See Evidano features for automated coding at Evidano features.
Problem: Interviews and youth inputs need careful transcription and privacy handling → Solution: Transcription and PII redaction
Problem: Youth testimony requires accurate transcription, correct names and organized excerpts without exposing personal data.
Solution: Evidano offers speech-to-text with a custom dictionary and PII redaction so transcripts from youth advisory boards can be safely included in synthesis.
Learn more at Evidano speech-to-text.
Problem: Iterative theory refinement needs rapid re-querying → Solution: AI chat and visualization
Problem: Teams need to re-run searches and visualise co-occurrence of mechanisms and contexts during workshops.
Solution: Evidano provides AI chat over your documents and visualisations such as hierarchical codes and co-occurrence networks to validate CMO configurations with youth and experts.
Ethics and data security
Evidano supports encrypted data storage and policies that ensure uploaded material is not used to train third-party models, aligning with research ethics for youth participation.
See Evidano data protections at Evidano data security.
FAQ: qualitative analysis of youth climate interventions
How can AI help realist reviews of youth climate interventions?
Answer: AI can accelerate document ingestion, extract candidate contexts, mechanisms, and outcomes, and surface patterns for iterative theory refinement.
Supporting detail: Deivanayagam et al., PLOS One (published August 13, 2026) call for broad searches across academic and grey literature, and AI tools reduce manual screening time while preserving source links for auditability.
What data should I prioritise when studying adolescent participation?
Answer: Prioritise records that document participation level, decision-making influence, and demographic context.
Supporting detail: Deivanayagam et al., PLOS One (published August 13, 2026) use Hart’s ladder and a structural racism lens to rate relevance, so include records that allow you to code power, inclusion, and equity outcomes.
Are transcripts from youth advisory boards safe to process with AI tools?
Answer: Yes, if the platform provides PII redaction, encryption, and clear data-use policies.
Supporting detail: Deivanayagam et al., PLOS One (published August 13, 2026) describe a Youth Advisory Board of six adolescents; platforms used in such projects must enable secure transcription and restricted access to comply with ethics.
How do I report CMO configurations so policymakers can act?
Answer: Report concise CMO statements with source citations, exemplar quotations, and visual summaries.
Supporting detail: Deivanayagam et al., PLOS One (published August 13, 2026) plan visual CMO summaries validated with youth and experts, which helps translate mechanisms into actionable policy recommendations.
Conclusion & Next Steps
Deivanayagam et al., PLOS One (published August 13, 2026) provide a realist protocol that makes qualitative, equity-centred synthesis of adolescent interventions feasible and policy-relevant.
Researchers should combine the protocol’s CMO focus with AI-enabled workflows to speed extraction, maintain traceability, and foreground racially minoritised adolescents’ perspectives.
If you are planning a realist review or youth-centred synthesis, consider tools that support transcription, secure document ingestion, thematic and cross-segment analysis, and stakeholder workshops.
To try an AI platform designed for qualitative synthesis, Try Evidano for free.
Topics
- qualitative analysis of youth climate interventions
- AI-enabled qualitative analysis
- youth climate interventions analysis
- realist review youth participation
- qualitative research AI tools
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