Groups can be prioritised across different issues, using mixed methods:
- Data analysis based on risk factors across issues and outcomes
- Stratification of risk factors
- Validating the data with frontline staff
- Strengths-based conversations
- Social prescribing through our community connections or contact centre
How can you value and blend “hard” and “soft” data like stories and testimonials from frontline staff or residents themselves?
…So that frontline staff and residents can relate to the insights because…they’ve created them
…So that policymakers can relate to the people they’re designing for so that you humanise the data rather than turning individuals into numbers…
Helping people carry out their own research helps them feel ownership over the issues in their communities and build relationships with others to develop “social neighbourhood watches” and co-design how they could use digital to self-report in a way they could better understand their behaviour and what triggers change (i.e. Moodscope, Mapy My Walk)
What if we empowered citizen scientists to predict or anticipate trends in their local networks (be it on the flu, stress, unemployment, etc.)?
