Scale Insights: qualitative analysis of drowning prevention

The recent pilot called Safe Futures (announced August 20, 2025) aims to deliver Swim to Survive lessons to at‑risk youth after two siblings drowned July 31 in Dryden, Ont. This post shows researchers, policy teams, and UX/ program leads how to run a practical qualitative analysis of drowning prevention programs to surface barriers, donor levers, and replication signals. Read the CBC source here: www.cbc.ca/news/canada/thunder-bay/safe-futures-initiative-drowning-prevention-1.7612865. If you want to test these steps on transcripts, school feedback, or donor notes, try a secure AI workflow at www.evidano.com.

Fast take: why this matters for researchers and program owners

Safe Futures (Oct pilot target) is a community-funded effort to deliver free Swim to Survive lessons for grades 3 and 7, removing cost and access barriers. The initiative is driven by Shendy's Swim School and partners including the Lifesaving Society and Canadian Drowning Prevention Coalition (announcement published Aug 20, 2025).

Problem: Many children in at‑risk cohorts can’t pass basic survival skills; Swim to Survive requires a 50 m swim and 1 minute tread.
Data signal: Lifesaving Society (July 2025) reports ~47% of Ontario drownings happen in lakes/ponds, 20% in rivers, place-based risk matters.
Research payoff: Qualitative analysis reveals why kids miss lessons (transport, cost, curriculum fit), what motivates donors, and how to scale.

Findings snapshot

Element	Value / Example	Source / Implication
Announcement date	Aug 20, 2025	CBC News, program framing and pilot timeline
Trigger event	Drowning deaths: July 31, 2025 (ages 12 & 15 (Dryden, Ont.)	Local advocacy (Water Wings)) spurs program urgency
Target cohorts	Grades 3 and 7; at‑risk youth	Designed to hit early-school and pre-teen survival skill gaps
Core skills (Swim to Survive)	Rotate/roll into deep water; tread 1 min; swim 50 m	Defines assessment and learning outcomes
Place-based risk	47% lakes/ponds; 20% rivers	Lifesaving Society, July 2025 report, informs geography of outreach
Primary barrier	Access & cost; schools without pools	Program removes cost; logistics remain research focus

What happened (method & mechanics)

Shendy's Swim School president Eric Shendelman is piloting Safe Futures to fund Swim to Survive sessions for students who otherwise lack access. The program bundles transport, equipment, and snacks to reduce non-financial friction and seeks municipal, corporate, and community buy-in. The pilot intends to gather participant feedback for replication decisions.

Why qualitative research matters here: it explains why half of children in some school trials cannot complete the Swim to Survive test, and which non-technical barriers (e.g., no bathing suits, parental consent, timing) stop participation.
Primary qualitative inputs to capture: interviews with teachers/principals, focus groups with students and parents, donor feedback, logistics notes from pool operators, and field observations during lessons.

How to run a qualitative analysis of drowning prevention programs

1) Inputs to collect

Interview transcripts (school admins, swim instructors, parents, students), consent forms, donation & sponsorship emails, field observation notes, and any short surveys after lessons.

Include date, location, participant role, and segment tags (e.g., urban/rural, school with/without pool).

2) Coding & themes to prioritize

Access barriers (cost, transport, equipment), Curriculum fit (PE scheduling, grade timing), Safety perceptions (parental fears, cultural notes), Funding levers (business, municipal), Replicability signals (pool availability, volunteer capacity).

Predefine a codebook with these themes and allow emergent subcodes (e.g., 'bathingsuit stigma').

3) Cross‑segment comparisons

Compare urban vs rural schools, grades 3 vs 7, donor types, and families with prior swimming exposure. Look for frequency shifts (e.g., 'transport' cited 70% in rural interviews).

Quantify co-occurrence (e.g., 'consent' frequently appears with 'parental mistrust').

Implications for policy, UX, and program leads

Three practical implications surfaced by a focused qualitative read:

Design for logistics, not just skill: Free lessons reduce cost barriers, but transport, clothing, and scheduling are equally decisive.
Localize outreach by water type: Given 47% of drownings occur in lakes/ponds, rural outreach and community-targeted messaging must differ from pool-based messaging.
Measure both outcomes and experience: track skill attainment (50 m swim) and reasons for dropout to inform iterative improvements.

Do more, faster with Evidano

Ingest and standardize multi-source inputs

Import interview transcripts, survey spreadsheets, donor emails, and observation notes into one workspace. Evidano automatically timestamps and tags documents so you can pivot by cohort or geography without manual merging (see www.evidano.com).

Automate thematic + cross-segment analysis

Run thematic extraction across transcripts to find top barriers (e.g., transport, consent) and use cross-segment filters to compare rural vs urban responses. Evidano produces frequency tables and co‑occurrence networks that surface patterns faster than manual coding.

Secure transcription, translation, and stakeholder-ready outputs

Use built-in transcription (custom dictionary, PII redaction) for parent interviews, plus translation where needed. Export hierarchical codebooks, clickable quotes, and visualizations for funders and school boards, all with end-to-end encryption and no third-party model training.

Run small pilots to scale

Set up an Evidano project for the October pilot, collect post-session feedback, run a two-week analysis sprint, and produce a one-page decision memo for municipal partners.

Practical 7‑step checklist to reproduce this analysis

Follow this run‑book for a two‑week pilot analysis:

1) Collect inputs: 20 interviews (admins/instructors/parents), 3 short student focus groups, and 100 post-session surveys.
2) Import to Evidano: transcripts, spreadsheets, and observation notes.
3) Apply codebook: start with access/cost/logistics/safety/funding; allow emergent subcodes.
4) Run thematic extraction and cross-segment frequency reports.
5) Validate with 3 stakeholder follow-ups (member‑checking).
6) Produce visuals: co-occurrence network, word cloud, and hierarchical codes → subcodes.
7) Deliver a one-page memo with prioritized fixes and a replication checklist for other municipalities.

FAQ: common questions from program evaluators

Q: When should I use qualitative analysis here?

A: Use it to understand barriers, motivations, and context that numbers alone (e.g., pass rates) don’t explain, essential for program design and donor messaging.

Q: How do I compare segments reliably?

A: Tag transcripts with cohort metadata (school, grade, urban/rural) and run cross-segment frequency/co-occurrence analyses to surface divergent patterns.

Q: Is this research ethical with minors?

A: Always follow consent/assent procedures, anonymize PII, and treat findings as program‑improvement (non‑diagnostic). Use secure tooling and redaction features where required.

Wrapping up: immediate next moves

If you’re evaluating Safe Futures-style pilots, focus qualitative effort on the logistics and experience gaps that block participation (transport, equipment, consent, and scheduling) and quantify those across segments.

Pilot a two-week Evidano workflow to go from raw transcripts to stakeholder-ready recommendations.
Generate a replication pack (codebook + visuals + memo) to accelerate municipal and corporate buy-in.

Ready to run this on your pilot data? Start a secure project at www.evidano.com and convert community feedback into prioritized actions for safer waterways.

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