Evidano is an AI-powered qualitative data analysis platform that helps teams ingest transcripts, surveys, and review PDFs to produce thematic, cross-segment, and stakeholder-ready outputs while protecting sensitive data. The July 16, 2026 PLOS One protocol describes a sequential explanatory mixed-methods trial to develop a quality-improvement intervention for school-based support teams (SBSTs) in Gauteng secondary schools, combining large-scale screening (n≈440) with in-depth SBST interviews (≈20) and a pilot pre-post intervention. Read the protocol: PLOS One protocol. Note: this is research-focused guidance, not clinical advice.
Key Takeaways
The PLOS One July 16, 2026 protocol uses a sequential explanatory mixed-methods design to develop an SBST quality-improvement intervention by combining n≈440 screening data, a scoping review (2015–2025), and ≈20 SBST interviews into a pilot evaluation.
An AI-enabled workflow shortens the path from raw audio and survey CSVs to stakeholder-ready evidence while retaining methodological rigor and ethics safeguards.
- Protocol structure: quantify prevalence with validated screeners (PHQ‑A, GAD‑7, ITQ‑CA, PEARLS), synthesize intervention evidence via a scoping review, then conduct SBST interviews to design the intervention.
- Analysis plan: SPSS v30 (ANOVA, multivariable regression, cluster-aware models) and NVivo 15 with Colaizzi phenomenological analysis for qualitative coding.
- Pilot targets and timeline: quantitative sample n=440, pilot post-intervention target n≈206, recruitment June 2025–Mar 2026 with results expected January 2027.
- Practical gain: AI-assisted transcription, auto-coding, cross-segment matrices, and one-click visual reports speed reporting and preserve security for sensitive adolescent data.
Findings snapshot
| Metric | Value | Source / Implication |
|---|---|---|
| Publication date | 16 July 2026 | PLoS One protocol |
| Design | Sequential explanatory mixed-methods | Quant → Qual → Intervention |
| Estimated school population | 6, 042 learners (4 schools) | Purposive selection: 2 urban, 2 township |
| Quantitative sample | n = 440 (calculated with Slovin) | PHQ‑A, GAD‑7, ITQ‑CA, PEARLS used |
| Qualitative sample | ≈20 SBST members (initial) | Descriptive phenomenology; Colaizzi analysis; NVivo 15 |
| Intervention evaluation | Pre-post quasi-experimental; target n≈206 | SPSS v30; ANOVA & multivariable regression |
| Timeline (recruit) | June 2025–Mar 2026; completion Dec 2026 | Results expected Jan 2027 |
What the protocol actually does (plain English)
The protocol quantifies adolescent problems using validated screeners, synthesizes intervention evidence via a scoping review (2015–2025), and runs in-depth SBST interviews to surface lived experience and operational barriers that inform a pilot intervention.
This study first quantifies common adolescent problems using validated screeners (PHQ‑A for depression, GAD‑7 for anxiety, ITQ‑CA for trauma, PEARLS for ACEs).
The protocol then synthesizes intervention evidence via a scoping review covering 2015–2025 and runs in-depth SBST interviews to surface lived experience and operational barriers.
- Triangulation: quantitative prevalence → scoping evidence → SBST lived experience feeds the intervention design.
- Analysis plan: SPSS v30 for quantitative tests (t-tests, chi-square, ANOVA, multivariable regression, cluster-aware models); NVivo 15 plus Colaizzi framework for qualitative coding and theme development.
- Pilot & evaluate: a pre-post test of the SBST quality-improvement package with convenience sampling (post-intervention target n≈206).
So what for researchers, UX teams & policy analysts
Researchers (mixed-methods teams)
Researchers can use the protocol's three-source triangulation to strengthen internal validity by using prevalence numbers to guide interview focus and subgroup comparisons (age, grade, location).
Use the protocol's quantitative prevalence to select subgroups for qualitative probing and predefine how to handle clustering by school and grade (the protocol recommends mixed-effects models or cluster-robust SEs).
School / implementation teams
School implementation teams can use SBSTs as feasible levers for early identification if capacity gaps are addressed through the protocol's capacity building, screening guides, and referral pathways.
Plan on on-site support during data collection for ethical safety: the protocol requires mental-health professionals on call during fieldwork.
Policy & funders
Policy makers and funders can use the protocol's explicit sample sizes and timelines to create realistic budgets for screening, interviews, and pilot evaluation.
Scoping-review methods and PRISMA-ScR reporting in the protocol make findings easier to synthesize into policy briefs and evidence summaries.
Do more, faster with Evidano (mapped to this protocol)
Problem: scattered inputs (surveys, audio interviews, grey lit)
Evidano ingests questionnaires, interview transcripts, PDFs, and scraped grey literature into one secure corpus for integrated analysis.
Evidano consolidates study inputs so teams avoid manual file management across formats.
Problem: manual NVivo coding and slow triangulation
Evidano provides AI-assisted thematic coding that matches Colaizzi’s approach, auto-suggests themes and exemplar quotes, and exports hierarchical codes compatible with NVivo-style workflows.
Evidano's auto-coding reduces manual tagging time while preserving the ability to refine codes collaboratively.
Problem: multilingual schools & transcription errors
Evidano offers transcription with custom dictionaries, PII redaction, and translation to reduce time before coding and ensure consistent terminology across transcripts.
Evidano's custom dictionary feature standardizes teacher titles, school names, and medical vocabulary across transcripts.
Problem: comparing subgroups (urban vs township, grades)
Evidano runs cross-segment analysis and frequency breakdowns by cohort, plus co-occurrence networks and word clouds to surface differential themes quickly.
Evidano exports frequency tables and cross-segment matrices for further statistical testing in SPSS or R as needed.
Problem: stakeholder-ready outputs
Evidano produces one-click visual reports and an AI chat over your documents to answer ad-hoc stakeholder questions, speeding policy memos and presentations.
Evidano's exportable visuals and slide-ready outputs support rapid dissemination to school leaders and funders.
Security & governance
Evidano encrypts data at rest and in transit and does not use customer data to train third-party models, a practical fit for sensitive adolescent health research and ethics committees.
Evidano provides access controls and retention settings to meet institutional review board and data governance requirements.
Run-book: 7 steps to reproduce this study with AI-enabled qualitative research
This run-book lists seven steps to reproduce the study using an AI-enabled qualitative workflow and secure data handling.
Step 1: Import your instruments and raw files, survey CSVs, audio/video, and PDFs (consent forms, scoping review PDFs).
- Evidano auto-maps survey variables and supports custom dictionaries for screening tool labels (PHQ‑A, GAD‑7, ITQ‑CA, PEARLS).
Step 2: Transcribe and clean interviews with PII redaction and custom medical/school vocabulary.
- Use Evidano transcription to standardize terms (teacher titles, school names) and to create time-stamped transcripts for quotes.
Step 3: Auto-code with a seed codebook (Colaizzi-style nodes), then review and refine codes collaboratively.
- Evidano suggests themes, extracts exemplar quotes, and produces code co-occurrence matrices for pattern detection.
Step 4: Run cross-segment analyses to compare urban vs township, grade levels, or PHQ‑A severity bands.
- Frequency tables and effect-size summaries can be exported for SPSS or R if needed.
Step 5: Merge scoping review extracts with empirical themes to inform the intervention content (screening, referral flow, capacity building).
- Attach evidence snippets and links for each proposed intervention component to streamline reporting.
Step 6: Prepare stakeholder deliverables, slide-ready visuals, a one-page brief, and an interactive dataset with AI chat for Q&A.
- Use co-occurrence networks and hierarchical code trees to show why particular referral pathways were prioritized.
Step 7: Archive and enforce retention/consent rules (the protocol stores data 15 years). Use Evidano encryption and access controls to meet ethics requirements.
FAQ: School-based support teams (SBSTs)
Can Evidano replace NVivo for Colaizzi analysis?
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Evidano can replicate the phenomenological coding flow and export hierarchical codebooks compatible with NVivo for hybrid workflows.
Evidano replicates the Colaizzi steps: extract significant statements, formulate meanings, cluster themes, and it exports hierarchical codebooks for teams that want to continue working in NVivo.
How do you compare subgroups rigorously?
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Combine Evidano’s frequency and cross-segment matrices with SPSS or R inferential tests as recommended in the protocol to surface statistically supported thematic differences.
Evidano provides cross-segment matrices and frequency tables which can be exported for ANOVA, mixed-effects models, or other tests suggested in the protocol.
Is sensitive adolescent data safe on Evidano?
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Evidano encrypts data at rest and in transit and does not use customer data to train third-party models, simplifying ethics approvals and data governance.
Evidano supports PII redaction, access controls, and retention settings aligned with the protocol's 15-year storage rule.
Wrapping up & next steps
An AI-enabled workflow accelerates mixed-methods SBST evaluations while preserving methodological rigor and ethical safeguards.
If you are preparing a mixed-methods school mental-health evaluation like the July 16, 2026 PLOS One protocol, an AI-enabled workflow shortens the path from raw audio and survey CSVs to stakeholder-ready evidence while retaining methodological rigor and ethics safeguards.
- Start small: pilot transcription plus auto-coding on five interviews to validate code suggestions and the custom dictionary.
- Then scale: run cross-segment frequency reports and generate co-occurrence networks to help prioritize intervention components.
Ready to reproduce this protocol faster? See how Evidano handles transcripts, surveys, thematic and cross-segment analysis, secure storage, and stakeholder reports at Evidano, or get started directly: Try Evidano for free.
Topics
- SBST qualitative analysis
- school mental health
- mixed-methods protocol
- Colaizzi NVivo
- Evidano
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