This post explains how to run a reproducible qualitative analysis of child poverty in African conflict zones using the Raja et al. scoping review protocol (PLOS ONE, published 29 June 2026) and where AI-enabled workflows can shorten screening, translation, and thematic synthesis time while preserving reproducibility and audit trails.
Key Takeaways
This post shows how the Raja et al. protocol (PLOS ONE, 29 June 2026) maps multidimensional child poverty in African conflict settings and how an AI-enabled workflow can accelerate multilingual screening, coding, and evidence mapping while preserving reproducibility.
- The protocol focuses on children birth–18 in African conflict settings, includes English, French, and Portuguese sources, and was published 29 June 2026.
- Extraction was planned to finish in 2026 with synthesis expected in 2027, and the protocol follows Joanna Briggs Institute methods with OSF registration and PRISMA-ScR reporting.
- The protocol documents context-level statistics cited in June 2026, for example ~246 million children in conflict-lethal environments and a high multidimensional poverty signal in sub-Saharan conflict settings.
- AI-enabled workflows can centralize heterogeneous sources, run multilingual preprocessing, auto-code with reviewer validation, and produce reproducible exports such as evidence maps and PRISMA-ScR flowcharts.
Fast take: Why this protocol matters
The protocol matters because it will map multidimensional aspects of child poverty specific to African armed conflict settings and highlight underrepresented domains.
A new scoping review protocol (Raja et al., published 29 June 2026) will map the multidimensional aspects of child poverty in African armed conflict settings and identify underrepresented domains, full protocol at PLOS ONE.
- Scope: children birth–18 in African conflict settings; includes English, French, Portuguese sources.
- Rationale: existing tools (Global MPI, UNICEF MODA) miss conflict-specific domains such as safety, legal status, and psychosocial distress.
- Practical payoff: the protocol documents JBI methodology, Covidence/Zotero screening, Google Translate for preliminary translations, and OSF registration, providing ideal inputs for an AI-enabled synthesis pipeline.
Findings snapshot
| Item | Value | Source / Note |
|---|---|---|
| Publication | PLOS ONE protocol, published 29 June 2026 | Raja et al., 2026 |
| Review window / timeline | Screening & extraction completed in 2026; results expected 2027 | Protocol text |
| Geographic scope | All African countries (54 + islands) | Protocol inclusion criteria |
| Languages included | English, French, Portuguese | Authors use Google Translate for preliminary translations |
| Key context stats | ~246 million children live in conflict-lethal environments; Africa >35 active NIACs; 1 in 4 African children face significant deprivation | Protocol references (June 2026) |
| Prevalence signal | Multidimensional poverty affects ~6 in 10 children in sub‑Saharan conflict settings | Protocol literature summary |
What the protocol does (plain English)
The protocol maps literature on child poverty in armed conflict zones using JBI scoping-review methods to capture quantitative, qualitative, mixed-methods studies, and grey literature.
The authors follow Joanna Briggs Institute (JBI) scoping-review methods to map literature on child poverty in armed conflict zones across quantitative, qualitative, and mixed-methods studies, plus grey literature and theses.
- Screening & review workflow: two independent reviewers use Covidence, citations are managed in Zotero, and extraction is iterative to capture standard and conflict-specific dimensions.
- Dimensions captured: health, education, living standards, and conflict-specific domains such as safety, legal status, and psychosocial well-being.
- Search plan: Medline, Embase, CINAHL, Scopus, WHO AIM, ProQuest, OATD, and NGO and UN reports are included.
- Translation & languages: English, French, Portuguese are included; Google Translate is used for preliminary reads, with author contact where necessary.
- Outputs: the review will produce a mapped multidimensional framework, tabulated results, and a PRISMA-ScR flowchart, with extraction complete in 2026 and synthesis in 2027.
So what for qualitative researchers and policy teams?
Speed & coverage
The protocol’s multilingual, multi-source search increases coverage but requires significant time for manual triage and screening.
The protocol’s multilingual, multi-source search is necessary but time-consuming, generating thousands of hits across databases and NGO reports that create manual triage delays and potential inconsistency.
Validity & nuance
Conflict-specific dimensions require qualitative coding and contextual notes because standard MPI grids will not capture them adequately.
Conflict-specific dimensions such as legal status, protection, psychosocial stress, and mobility constraints require qualitative coding and contextual notes; a standard MPI grid will not capture these nuances.
Transparency & reproducibility
The protocol’s use of JBI methods, OSF registration, and PRISMA-ScR charting supports reproducibility, but thorough documentation of search strings, translations, and codebooks remains essential.
The protocol’s JBI approach, OSF registration, and PRISMA-ScR charting make the review reproducible, but rigorous documentation of search terms, translation choices, and codebooks is essential for stakeholder trust.
Do more, faster with Evidano
Ingest heterogeneous sources
Evidano is an AI-powered qualitative data analysis platform that ingests PDFs, interview transcripts, NGO reports, and spreadsheets so teams can centralize the protocol’s planned inputs without manual copy-paste.
Evidano ingests PDFs, interview transcripts, NGO reports, and spreadsheets (survey results) so you can centralize the protocol’s planned inputs (Medline PDFs, ProQuest theses, NGO Word/PDF reports) without manual copy-paste.
Multilingual preprocessing
Evidano supports custom translation dictionaries and workflows for French and Portuguese to preserve domain terms during preprocessing.
Evidano offers translation with a custom dictionary and supports French/Portuguese workflows described in the protocol, preserving domain terms such as 'unaccompanied minors' and 'CBOW' rather than relying solely on noisy machine translations.
Qualitative coding at scale
Evidano enables import of a draft codebook and AI-assisted coding, producing hierarchical themes and subcodes that map to Global MPI, MODA, and conflict-specific dimensions.
Use Evidano to import a draft codebook, run AI-assisted coding across documents, and generate hierarchical themes and subcodes that map to Global MPI, MODA, and conflict-specific dimensions mentioned in the protocol.
Thematic + cross-segment analysis
Evidano generates frequency tables, co-occurrence networks, and cross-segment comparisons by country, conflict stage, and age-group to enable the mappings the protocol plans to extract.
Evidano produces frequency tables, co-occurrence networks, and cross-segment comparisons (by country, conflict stage, age-group) enabling the exact mappings the authors plan to extract.
Audit trail & secure sharing
Evidano preserves a traceable audit trail for every coded excerpt and secures data with encryption, and it does not use customer data to train third-party models.
Every coded excerpt is traceable to the source page and reviewer, data is encrypted, and customer data is not used to train third-party models, making the platform suitable for sensitive research into children and conflict.
AI avatar follow-ups
Evidano supports AI avatar interviewers for quick structured qualitative follow-ups that integrate directly into the analysis pipeline.
If field teams need quick qualitative follow-ups, Evidano supports AI avatar interviewers to collect structured qualitative data that plugs directly into the same analysis pipeline.
Checklist: Reproduce the protocol’s qualitative analysis in 7 steps
This seven-step checklist reproduces the protocol’s qualitative analysis with AI support and retains the JBI two-reviewer model and reproducible outputs.
- 1) Centralize sources: export Medline/Scopus PDFs, NGO reports, and theses to a single Evidano project.
- 2) Preprocess: apply a custom translation dictionary for French and Portuguese, and OCR any scanned reports.
- 3) Seed codebook: import a JBI-oriented codebook (health, education, living standards) and add conflict-specific nodes (safety, legal status, psychosocial).
- 4) AI-assisted coding: run auto-coding, then have two reviewers validate and adjust codes to preserve the JBI two-reviewer model.
- 5) Cross-segment analysis: generate frequency counts and co-occurrence networks by country, conflict stage, and age subgroup.
- 6) Exportables: create a PRISMA-ScR flow, tabulated evidence maps, and a methods appendix with search strings and translation notes.
- 7) Share & archive: publish deidentified extraction tables and maintain the audit trail for reproducibility, and register materials on OSF if applicable.
Limitations & ethics note
The protocol lists limitations and emphasizes ethical sensitivity when researching children in conflict, and AI cannot replace domain judgment.
The PLOS protocol is explicit about limitations such as language scope, reliance on author descriptions of conflict stage, and iterative extraction. AI accelerates synthesis but does not replace domain judgment: subject-matter experts must validate theme definitions. Research involving children and conflict is ethically sensitive, and findings are for policy and research use, not clinical or legal determinations.
FAQ: Qualitative analysis of child poverty
What does the Raja et al. protocol aim to map?
The protocol aims to map multidimensional aspects of child poverty in African armed conflict settings.
The authors follow JBI scoping-review methods to capture health, education, living standards, and conflict-specific domains such as safety, legal status, and psychosocial well-being across quantitative, qualitative, and grey literature.
Which languages and sources does the protocol include?
The protocol includes English, French, and Portuguese sources and searches academic databases plus NGO and UN reports.
The search plan covers Medline, Embase, CINAHL, Scopus, WHO AIM, ProQuest, OATD, and NGO and UN reports, with Google Translate used for preliminary reads.
How can teams reproduce the protocol’s qualitative analysis at scale?
Teams can reproduce the protocol’s qualitative analysis by centralizing documents, applying multilingual preprocessing, seeding a JBI-aligned codebook, using AI-assisted coding with two-reviewer validation, and exporting reproducible artifacts.
A seven-step checklist in this post outlines centralizing sources, preprocessing translations and OCR, seeding and validating codebooks, cross-segment analysis, and producing PRISMA-ScR and evidence maps.
What are key limitations to watch for in this scoping review?
Key limitations include language scope, reliance on author descriptions of conflict stage, and the iterative nature of extraction.
The protocol is explicit about these limitations and recommends rigorous documentation of search strings, translation choices, and codebooks to maintain validity and stakeholder trust.
Conclusion, next steps
The Raja et al. protocol (PLOS ONE, 29 June 2026) is a robust blueprint for mapping multidimensional child poverty in African conflict settings and can be implemented faster with AI-enabled workflows while preserving reproducibility.
- Start a pilot: ingest 50 seed documents (the protocol used 90 seed articles) and run auto-coding to compare time and inter-rater consistency.
- See how the protocol’s JBI steps map to automated workflows at Evidano, then Try Evidano for free or book a demo to test on your corpus.