Qualitative analysis of plastic waste enterprises

This section describes the study methods and the main thematic findings from the focus group discussions. The study used focus group discussions to compare specialist plastic waste enterprises with general or mixed waste collectors across two cities, with Accra hosting six FGDs and Kisumu hosting four FGDs plus a small apex-trader meeting; audio was transcribed, translated where needed, and thematically coded using NVivo.

• 11 FGDs, n=87 participants; Accra fieldwork: 26 Sep–5 Oct 2022; Kisumu: 2–3 Oct 2023.
• Shared challenges reported included societal stigma, harassment and extortion, hazardous items and rising diaper/faecal contamination, lack of equipment, and transport or fuel costs.
• Plastic-specific challenges in Accra included price volatility driven by seasonal sachet-water use and bulk imports, and theft of stored separated plastics; many sub-collectors were elderly women facing musculo-skeletal risks.
• Mixed-waste-specific challenges included illegal undercutting by unregistered collectors and higher disposal fees, and slower separation where households do not separate waste.
• Participant requests included PPE, secure storage, transport support, representative associations, price-regulation or local recycling agents, and occupational health programmes.

This run-book gives seven practical steps to turn transcripts into policy-ready insight using the same inputs and themes as the PLOS One study.

• 1) Gather inputs: audio files, transcripts, registration lists, and the PLOS paper for reference: PLOS One.
• 2) Auto-transcribe and translate in Evidano; add custom dictionary entries for local terms such as 'aboboya' and 'sachet rubbers'.
• 3) Import or create a codebook mirroring the PLOS study themes; run AI-assisted coding across transcripts.
• 4) Run cross-segment queries (city, role, gender, season) to quantify theme frequency and extract representative quotes per segment.
• 5) Visualize findings: co-occurrence network (for example, 'price volatility' ↔ 'seasonal demand'), hierarchical themes, and word clouds.
• 6) Validate results with member-check extracts and export interactive reports for stakeholders.
• 7) Schedule recurring imports to monitor seasonal volatility and evaluate interventions longitudinally.

This section summarises recommended next steps to turn FGDs like the PLOS One study into policy-ready insights. If teams need to extract policy-ready insights from FGDs (11 FGDs, n=87), run reproducible thematic and cross-segment analysis, visualise co-occurrence, and set up longitudinal monitoring for price and flow volatility.

• Start a pilot: import two to three transcripts, auto-transcribe, auto-code, and generate a cross-segment summary to test assumptions.
• Secure the data and speed decision cycles, and Try Evidano for free to link your next qualitative project to evidence that policymakers and funders can act on.