Discovery research to understand how Trinidadians navigate crime information and what they'd need from a real-time safety app
Trinidad and Tobago has experienced a significant spike in violent crime in recent years — yet no localized, real-time crime awareness tool exists for residents. In the US, apps like Citizen have changed how people navigate safety in their cities. Nothing comparable exists for Trinidad.
AlerTT is a concept for a real-time crime awareness app built specifically for the Trinidadian context. Before any product decisions could be made, a discovery research study was needed to understand the actual problem space — how people currently access crime information, how that gap affects their behavior, and what they'd need from an app to actually trust and use it.
Primary research questions: How do Trinidadians currently navigate crime awareness? How does the information gap affect daily behavior? What would make a real-time safety app trustworthy and usable in this specific cultural context?
Critically, this study was designed to surface not just feature preferences, but the psychological and behavioral reality of living with crime anxiety in Trinidad — grounding product decisions in real user experience rather than assumption.
An 18-question mixed-methods survey was designed and deployed across personal networks, WhatsApp groups, Instagram, and Reddit's r/trinidadandtobago community. The instrument was structured in five sections: current behavior, emotional response, app concept reaction, privacy concerns, and demographics.
The survey was built in Google Forms and distributed through a combination of personal WhatsApp groups, Instagram stories, direct family forwards into broader Trinidadian networks, and a post in r/trinidadandtobago. This multi-channel approach was designed to capture demographic diversity — particularly older age groups and respondents from different regions — rather than relying solely on the researcher's immediate peer network.
The instrument combined Likert scales and linear ratings for quantitative analysis with open-ended questions on trust, distrust, and privacy concerns for thematic analysis. Closed questions established behavioral baselines; open questions surfaced the nuanced reasoning behind those behaviors — the kind of insight that would directly shape product decisions.
Only 2 of 42 respondents typically find out about crime incidents near them within minutes. The majority hear the same day (17) or the next day or later (11). Three respondents rarely find out at all. The dominant channels — Facebook/Instagram (13), word of mouth (8), WhatsApp groups (7) — are slow, unverified, and fragmented. Mean satisfaction with current crime information access was just 4.67 out of 10.
This was the most striking behavioral finding. Crime concern affects daily decisions — routes taken, places visited, travel times — at a mean score of 6.19 out of 10. More concretely: 73% of respondents have avoided a place or activity due to fear of crime in the past 6 months, with 43% having done so multiple times. Only 3 respondents (7%) said they had never avoided anything. Crime anxiety isn't abstract — it's shaping real behavior across the country.
Mean likelihood to use AlerTT if it existed: 8.14 out of 10. For a concept product with no existing market presence, this is a strong signal. The most wanted alert types were shooting/gun violence (34 of 42), robbery/theft (30), gang-related activity (30), and kidnapping (26) — all violent crime categories, not property crime. This has direct implications for alert prioritization in the product design.
The open-ended responses told a consistent and nuanced story. Misinformation and fake news was the single most cited concern. But the trust picture is more complex than "people want verified information." Three distinct trust themes emerged from thematic analysis of Q11 and Q13:
A significant finding on report handling: 50% of respondents (21 of 42) want both anonymous AND verified options to coexist — not one or the other. This suggests a dual-track verification system rather than a single approach.
Only 6 of 42 respondents (14%) said they would not share their location at all. The majority are willing under the right conditions: 17 would share only while using the app, 7 are comfortable with always-on, and 9 said it depends on what more information they received. Privacy anxiety is real but addressable through transparent design — not a fundamental barrier to adoption.
These findings translate directly into five product decisions a team building AlerTT would need to make:
This research demonstrates that the problem AlerTT is solving is not just a product gap — it's a behavioral one. Crime fear is actively constraining how Trinidadians live: where they go, when they travel, what they do. A well-designed awareness tool doesn't just inform people — it restores agency.
That framing should guide every product decision: the measure of success is not engagement metrics or daily active users. It's whether people feel more free to move through their country.
The sample skewed male. 49 of 76 respondents were men. Given that women often experience crime anxiety differently — and that gender differences in fear of crime are well-documented in the literature — a follow-up study with a more balanced gender sample would likely surface different trust and safety concerns worth designing for.
Qualitative interviews would deepen the trust findings. The open-ended responses on trust and distrust were the richest data in the study — but a survey format limits how deep you can go. Follow-up interviews with 6–8 respondents representing different trust profiles would generate more actionable design insight, particularly around the anonymity question.
The police distrust finding deserves its own study. Multiple respondents raised concerns about law enforcement access to their data — some quite strongly. This is a meaningful design constraint that likely varies by region, age, and personal history. Understanding it more precisely would directly shape governance and privacy architecture decisions.
Concept testing would be the logical next step. This study established the problem space and user needs. The next research phase would be concept testing — showing users low-fidelity prototypes of different alert and verification designs to see which trust mechanisms actually land in practice.
To demonstrate what the research recommendations would look like in practice, a functional prototype was built in React Native using Expo. Every design decision maps directly to a finding from the n=76 study — the alert type priority order, the dual-track verification system, the location-sharing defaults, and the anonymous vs. verified reporting flow.