Qualitative analysis of youth cannabis attitudes

The New York 'Cannabis Honestly' listening (23 sessions, more than 450 participants) revealed a clear knowledge gap among teens and parental concern about unlicensed supply, and those insights can be reproduced with a short, automated qualitative pilot. A 2-week workflow that combines automated transcription, PII redaction, AI-assisted coding, and cross-segment analysis will surface the same themes and produce stakeholder-ready outputs.

• New York data: 23 facilitated sessions, more than 450 participants, and a core signal that roughly one-third of teens could not name the legal purchase age.
• Practical pilot: a 2-week, 7-step workflow (transcribe, code, cross-segment, validate) reproduces listening insights and yields actionable recommendations.
• Design implications: clarify legal age messaging, address unlicensed supply and product safety concerns, and pair conversation guides with place-based enforcement metrics.

Fast take: New York’s campaign grew from 23 facilitated listening sessions and more than 450 participants, aimed at giving families conversation tools while highlighting enforcement gaps.

• Source (first report): Gotham Gal (July 20, 2026).
• Core signal: ~1/3 of teens could not identify the legal age to consume cannabis, a clear knowledge gap.
• Design implication: conversation guides help, but enforcement and unlicensed supply remain structural issues.

The New York listening revealed three concrete pain points: knowledge gaps among youth about legal rules, parental anxiety about unlicensed supply and product safety, and mixed messaging across channels.

• The listening surfaced attitudinal themes (confusion, fear), behavioral signals (underage access via illicit channels), and contextual drivers (retail landscape).
• Sampling: 23 sessions and more than 450 participants are enough to surface consistent themes but not to quantify prevalence across the state.
• Interpretation caveat: facilitated sessions reveal depth and patterns, not population-level rates; follow-up surveys or administrative data are needed for prevalence.

This checklist provides a 7-step workflow to reproduce the New York listening in a two-week pilot.

• 1) Gather inputs: audio, facilitator notes, screener data (demographics).
• 2) Transcribe: use Evidano transcription with a custom dictionary for local slang and product names; redact PII.
• 3) Rapid codebook: start with 10 to 12 a priori codes (legal knowledge, access, safety, enforcement, messaging), then refine after the first four sessions.
• 4) Batch-code: run AI-assisted coding across all transcripts; review and adjudicate edge cases.
• 5) Run cross-segment analysis: compare teens versus parents versus educators; export theme frequency tables and exemplar quotes.
• 6) Validate: run a 200-response micro-survey on key knowledge gaps (for example, legal age) to estimate prevalence.
• 7) Deliver: produce one-pager for stakeholders with top three actionable recommendations, a co-occurrence map, and a verbatim quote bank.

The New York 'Cannabis Honestly' campaign showed clear knowledge gaps among youth and concerns about unlicensed supply, which invite targeted communications and enforcement-aligned interventions.

• Run a 2-week pilot using the 7-step checklist above and accelerate synthesis with Evidano.
• Want help reproducing the NY workflow on your data? Visit Evidano to start a secure pilot; Evidano can ingest transcripts, run thematic and cross-segment analyses, and produce stakeholder-ready visualizations in days.
• Try Evidano for free to begin a pilot and reproduce these listening insights on your data.