Gathering evidence: methods at a glance
Understanding risk communication begins with evidence — who is at risk, what they know, and how they access and act on information.
The Guide for Essential Research (BBC Media Action, 2024) provides practical tools for gathering this evidence through three complementary approaches:
- Desk research – making the most of existing data.
- Qualitative research – understanding people’s perspectives in depth.
- Quantitative research – measuring patterns and prevalence.
Together, they form the evidence base for designing, testing, and refining disaster risk communication strategies.
Desk research
Purpose:
To build a baseline understanding of the context before conducting new research. Desk research helps identify what is already known and where the knowledge gaps are.
What it involves:
Reviewing and analysing existing information such as reports, datasets, academic papers to form an overview of:
- The hazards, geography, and exposure of the area.
- The population profile — who lives where, and with what vulnerabilities.
- The communication environment — media access, trust, and technology use.
- Previous disaster communication or response efforts.
Typical sources:
- National statistics and census data.
- DRR research from UN system, INGOs, NGO and academia. PreventionWeb country profiles provide an overview of available sources
- Media landscape studies, Reporters without Borders country profiles
When to use:
At the start of a communication planning process — to frame research questions, identify gaps and inform subsequent research.
Key questions:
- What information about hazards, populations, and communication channels already exists?
- What gaps or inconsistencies remain?
- What further evidence is needed?
Qualitative research
Purpose:
To explore people’s lived experiences, beliefs, motivations, and barriers to action.
It helps uncover why people respond (or fail to respond) to risk information the way they do.
What it involves:
Engaging directly with individuals and communities through methods such as:
- Focus group discussions – to explore perceptions, social norms, and communication preferences.
- Key informant interviews – with local leaders, journalists, responders, or sector experts.
- Observation or participatory mapping – to see how communities interact with risk and early warning systems.
- Storytelling or case studies – to capture how communication affects behaviour and trust.
When to use:
When insight and context are more important than numbers — for example, when exploring:
- Community trust in warning systems.
- Local beliefs or traditional practices around hazards.
Key questions:
- How do people perceive risks and warnings?
- Who do they trust, and why?
- What stops or enables them from acting on risk information?
Tip:
Ensure participation across different groups (e.g. women, youth, elders, people with disabilities).
Use open-ended questions and local languages to encourage honest responses.
Quantitative research
Purpose:
To measure how widespread certain perceptions, behaviours, or communication patterns are and to track changes over time. To assess differences and preferences by demographics such as location, age, gender, age, or disability.
What it involves:
Collecting structured, numerical data through:
- Surveys (household, phone, online)
- Audience or KAP surveys (Knowledge, Attitude, and Practice)
- Media-use tracking
- Polls or mobile feedback mechanisms
When to use:
When you need data that can be generalized or compared across regions or demographics.
Key questions:
- What proportion of people are aware of disaster risks and warnings?
- How many have taken preparedness measures?
- Which information sources are most trusted?
- How does trust vary by gender, income, or location?
What it reveals:
Quantitative research helps estimate the scale of understanding or misinformation, identify who is being reached, and test which channels work best.
Tip:
Keep questionnaires concise and test them first to ensure they are clear and don’t introduce biases in the responses. Combine results with qualitative findings to deepen interpretation.