Evidano is an AI-powered qualitative data analysis platform that ingests reports, interview transcripts and survey data, applies AI-assisted coding, and produces reproducible thematic and cross-segment analyses. Researchers and policy teams reading the Department for Work and Pensions' IPSPC evaluation (published 25 June 2026) need a reproducible way to extract themes, compare participant segments, and translate findings into programme decisions. This post shows how to run a focused qualitative analysis of IPSPC, from ingesting the report, interview transcripts and survey data to mapping results back to the programme Theory of Change, using AI-enabled workflows. If you want to speed coding, generate cross-segment comparisons, and produce stakeholder-ready visualisations, use Evidano.
Key Takeaways
Evidano is an AI-powered qualitative data analysis platform that ingests documents and surveys, applies AI-assisted coding, and produces reproducible thematic and cross-segment analyses. This short guide describes a minimal, reproducible workflow to extract themes from the IPSPC evaluation (published 25 June 2026), map evidence to the programme Theory of Change, and compare participant segments to inform policy.
- The IPSPC evaluation, published 25 June 2026 by the Department for Work and Pensions, is an independent mixed-methods study that assesses delivery, outcomes and system effects of expanding IPS into primary care.
- Qualitative analysis should map interviews and surveys to the IPSPC Theory of Change, compare segments (referral route, condition group, employment status), and quantify theme frequencies to inform decisions.
- A seven-step reproducible workflow is provided, from ingest and ToC mapping to AI-assisted coding, cross-segment analysis and audit-ready synthesis.
Fast take: IPSPC evaluation (25 June 2026)
The UK evaluation of Individual Placement and Support in Primary Care (IPSPC) is an independent mixed-methods study published on 25 June 2026 that assesses delivery, outcomes and system effects of widening IPS into primary care and adding job-retention support.
- Source: Department for Work and Pensions
- Scope: adults with mild-to-moderate physical or mental health conditions (Equality Act 2010 definition).
Findings snapshot (summary)
This table summarises publication date, programme scope, methods and the report URL for the IPSPC evaluation.
Findings snapshot
| Item | Value | Note |
|---|---|---|
| Published | 25 June 2026 | Independent evaluation by Department for Work and Pensions |
| Programme | IPSPC (Individual Placement and Support in Primary Care) | Supported employment plus job retention element |
| Population | Adults with mild-to-moderate physical or mental health conditions | Eligibility framed by Equality Act 2010 |
| Methods | Mixed methods: qualitative interviews plus quantitative surveys | Theory-driven analysis aligned to programme Theory of Change |
| Primary goal | Understand delivery, who benefits, and system-level outcomes | Intended to inform policy and future provision |
| Report URL | Department for Work and Pensions | Full evaluation and appendices |
What the evaluation did (plain English)
The evaluation combined participant and stakeholder interviews, provider and employer feedback, and participant surveys to test hypotheses derived from the IPSPC Theory of Change. It focused on delivery (what services did), reach (who engaged), and outcomes (job starts, retention, and perceived benefits). The IPSPC innovation is twofold: widening referrals to primary care and offering support to people at risk of losing existing jobs.
- Design: Mixed-methods, theory-driven; qualitative strand mapped to the ToC.
- Data sources: Interviews with stakeholders, providers, participants and employers, plus quantitative survey data from participants.
- Analytic aim: Explain what worked, for whom, why, and system implications for future policy.
Implications for researchers and policy teams
For evaluation teams
Evaluation teams should prioritise aligning interview guides to the Theory of Change so themes map directly to hypotheses and decision points.
Structure transcripts and survey exports so evaluation teams can cross-analyse by referral route, diagnosis group, or retention support received.
For policy & commissioning
Policy and commissioning teams should look for delivery bottlenecks (referral pathways, employer engagement) and evidence where job-retention support changes employer and participant behaviour.
Policy teams should ask for segmented evidence (age, condition, employment status) rather than only aggregate outcomes.
For operational teams / providers
Operational teams and providers should use qualitative signals (barriers, employer attitudes, timing issues) to redesign referral scripts and retention touchpoints.
Providers should document feedback loops so qualitative findings become measurable pilots.
Do more, faster with Evidano (mapping to IPSPC needs)
Ingest & align to Theory of Change
Evidano ingests the full IPSPC report, interview transcripts and survey spreadsheets and enables tagging materials to Theory of Change nodes so all evidence links to the same hypotheses.
Thematic and cross-segment analysis
Evidano runs automated thematic extraction and frequency counts, then compares themes across referral routes, participant profiles, or employer types with cross-segment analysis and co-occurrence networks.
Consistent coding & reproducible outputs
Evidano applies AI-assisted coding across documents from a shared codebook for consistent theme application and produces hierarchical code to subcode visualisations for stakeholder reports.
Fill evidence gaps quickly
Evidano can generate targeted follow-up question lists from existing transcripts or support consent-first short follow-ups to test emerging hypotheses.
Security & compliance
Evidano encrypts data at rest and in transit and does not use customer data to train third-party models, making the platform suitable for sensitive programme evaluations.
7-step checklist: Reproduce the IPSPC qualitative analysis
Follow this seven-step workflow to reproduce the IPSPC qualitative analysis and move from report to decisions:
- 1) Gather inputs: upload the IPSPC report, interview transcripts, and survey CSVs to Evidano.
- 2) Map the Theory of Change: create ToC nodes and tag documents and quotes to hypotheses.
- 3) Import or create a codebook: standardise codes for barriers, enablers, employer response, and outcomes.
- 4) Run AI-assisted coding: apply codes across transcripts and extract exemplar quotes with source metadata.
- 5) Cross-segment analysis: compare themes by referral route, condition group, and employment status; generate co-occurrence networks.
- 6) Synthesize: produce an executive brief with top themes, supporting quotes, and quantified frequencies for each ToC hypothesis.
- 7) Iterate: use AI chat over the dataset to produce targeted follow-up questions or generate a short plan for piloting recommended changes.
FAQ: IPSPC qualitative analysis
Can I compare themes by participant subgroup reliably?
Yes, you can compare themes by participant subgroup reliably by importing demographic columns from your survey spreadsheet and using cross-segment analysis to surface differences in theme prevalence and co-occurrence.
How do I preserve auditability for policy decisions?
Export code application logs, quote provenance, and the exact outputs used in reports so decisions are fully traceable and audit-ready.
Is AI transcription and translation safe for sensitive interviews?
Use encrypted transcription with custom dictionaries and PII redaction and confirm consent, because ethical research requires anonymisation and local data-protection compliance.
Wrapping up: Put IPSPC evidence to work
The IPSPC evaluation (25 June 2026) offers a focused mixed-methods dataset that policy teams can translate into operational changes if analysis maps cleanly to the Theory of Change and segments are compared systematically.
- Next move: upload the report and related transcripts to Evidano to produce reproducible thematic and cross-segment analyses and stakeholder-ready visuals.
- Try a pilot: Try Evidano for free using the IPSPC materials or your programme data, secure and audit-ready.
Ethics note: This post is research-focused and non-diagnostic. Follow local consent and data-protection rules when handling interview and survey data.