Chapter 2: Behaviour Change Model

Introduction

Appreciative Inquiry (AI) is a cyclical tool following a ‘4D’ process (Discover, Dream, Design and Deliver), which acts as a learning loop. AI can help facilitate positive change in community settings by involving people at risk and other stakeholders. In BRIC’s case, the risk is the increase in future flooding incidents.

The BRIC teams implemented the AI process in each pilot site at the beginning of the project to ensure that planned BRIC activities and events embedded themselves within the strengths of the communities and could be used to influence positive decisions and actions.

The AI cycle

AI starts from a motivating feeling of enthusiasm and hope rather than from the ‘issue or problem’ itself. It has four stages:

Discover

Identifies the community’s current situation, i.e. where do they feel they are now?

Dream

Uses the baseline data from the discovery stage and allows those using the AI process to imagine what the community could look like in the future

Design

Uses the collected information and data to form an implementation plan of events and activities

Deliver

Events and activities are delivered to bring about change

Stavros, J. M. (2008). Appreciative Inquiry Handbook for Leaders of Change (2nd ed.). Brunswick, USA: Crown Custom Publishing.
Stavros, J. M. (2008). Appreciative Inquiry Handbook for Leaders of Change (2nd ed.). Brunswick, USA: Crown Custom Publishing.

AI – A behaviour change model in practice

This guidance uses the Plymouth City Council (PCC) Lipson and Trefusis Park pilot area to illustrate how AI works as a behaviour change model.

Discover Stage

PCC conducted AI in this area via face-to-face interviews, public consultation surveys and a Google form (accessed via a QR code in a newsletter). In total, the team collected 105 responses.

The AI questions table shows the questions asked. The team started with neutral questions to encourage a person to talk (questions 1 and 2). A topical question relevant to resilience was then raised: for this, PCC asked about climate change (question 3). Having built rapport, the person was then asked about their flood preparedness (questions 4 and 5).

1 - What do you like about this area?

2 - How could things improve here?

3 - What are your thoughts on climate change?

4 - On a scale of 1 to 5 (1 = not prepared at all; 5 = very prepared), if you were flooded tomorrow, how prepared do you feel you would be?

5 - Why have you given this score?

The BRIC team conducted the AI interviews in pairs so one person could talk and be attentive to the interviewee and the other could write down what they said. All responses were recorded anonymously, in the first person and as close to the actual words spoken as possible.

Sessions were carried out on different days of the week, at differing times and in different parts of the area, so that a wide range of people were consulted. The team were pleased to find that most people were willing to stop and share their stories.

AI data is collected anonymously to encourage people to speak freely. Therefore, the limited demographic data of gender and age gathered was by observation only and could be considered subjective. However, monitoring this data helped the team to reach a broad audience.


Dream Stage

To learn from the Discovery stage, PCC held four AI listening events. They invited various stakeholders, including the Environment Agency, South West Water Services Limited (SWW) and the emergency services. They also included other PCC departments and community groups interested in flood risk management, the Lipson community and Trefusis Park.

The listening events allowed participants to look deeper at the stories collected and to imagine what the community could look like with future interventions. Including local stakeholders not only added to the depth of the BRIC Team’s understanding but also provided those stakeholders with opportunities to learn from the community engagement.

During each event, the AI responses were shared in the first person, keeping the answers as close to the actual words spoken as possible, including swear words. This approach was to enable the event participants to imagine they were listening to the community speaking directly to them.

While the team read the stories aloud, participants were asked to listen and note any key and common themes that emerged. A Google Jamboard was then used to collect those key themes and facilitate discussions about how stakeholders could use the information in their work or projects to inform future activities or plans. 54

The Google Jamboard image shows the key themes and concerns identified and discussed at the first listening event held with the Lipson Vale area stakeholders.

POSITIVES :

  • residents are generally aware of climate change and are taking action, such as recycling and eating less meat
  • residents like the park and value their green space: it is mostly used by dog walkers
  • during COVID-19 restrictions, the park had become an essential place for exercise and social contact

NEGATIVES :

  • some travellers encamped in Trefusis Park, which resulted in the community feeling worried for their safety
  • there were many comments about the lack of bins and dog mess
  • fly tipping in the stream was also raised as a concern

FLOOD PREPAREDNESS :

  • people were generally not prepared for flooding: some reasons identified were that residents had not thought about flooding before or they felt they were unlikely to flood because they live on a hill

The stakeholders were also asked to identify ways that the key themes could inform their work and that of the BRIC Team. In summary, they thought:

  • wider improvements could be made in the park, such as seating and information boards
  • outreach work with young people who use the park would be beneficial
  • about how other community initiatives, like the local litter-picking community interest company Clean Our Patch, could be involved
  • about how the BRIC team could bridge the gap between those living on a hill who will not flood but don’t realise they could be contributing to flood risk, and those at the bottom of the hill who are in the flood risk zone

Hosting the listening events enabled the PCC BRIC team to engage stakeholders about their plans. It also resulted in additional stakeholder engagement that would not have happened without the events. For example:

  • stronger relationships have been built with councillors, who do not often hear the direct voice of their communities
  • the team attended Efford Youth Club to gauge the young people’s views about a particular area within Trefusis Park – this has resulted in plans for a half-size basketball pitch, which did not appear in the original plans
  • close collaboration with SWW has resulted in them donating water butts for PCC’s “Make a Pledge to Slow the Flow” competition

Design Stage

The Plymouth BRIC team used the AI results to develop an implementation strategy for a public consultation. That consultation was for a planned capital flood relief scheme for Trefusis Park. The information from AI had shown that:

  • as the park is regularly used, there was likely to be significant interest in the scheme
  • people had been so willing to engage that it was clear that face-to-face events would be helpful to increase the volume and quality of feedback
  • events should be scheduled on different days (including at the weekend) and at differing times to maximise the number of attendees

The team asked themselves how they could increase residents’ responses while raising flood risk awareness. In answer to this question, they designed more face-to-face engagement activities than is the norm for public consultations. They also planned other activities such as:

  • community newsletters
  • slow the flow activities
  • mini pop-up events in Trefusis Park
  • presentations
  • attendance at external events and volunteer meetings

The BRIC team paid careful attention to the public consultation survey to ensure that the questions were relevant to the design team and properly reflected people’s views about what they like about the park and what they would like to see improved. Flood preparedness questions were included to gather more information about peoples’ knowledge and experience of flooding in the area.


Deliver Stage

Following the first three stages of the AI loop, the interventions detailed below were carried out by the Plymouth BRIC Team in the Lipson Vale and Trefusis Park area. The aim was to explain PCC’s two design options for the Trefusis Park SuDS scheme and to gather support and comments about the plans:

  • The team sent 3700 letters and leaflets to residents within a 500-metre buffer zone around Trefusis Park
  • Six consultation events were held in various locations and at differing times of the day/week, including:
    • a Saturday morning event in a local church hall – 10 attendees
    • two outdoor events in Trefusis Park – 31 attendees
    • one event in a local public house – 12 attendees
    • one event in a local primary school – 6 attendees
    • one online event – 1 attendee

The team spoke to 60 residents, and 50 survey forms were returned.

Back around the AI loop

Now that PCC has completed lots of activities and events, both during the public consultation and since, it is time to think about the lessons learned and ask:

What needs to be done to continue changing the behaviours and mindset within the targeted communities so they can become truly resilient when it comes to flooding? 

This question will require PCC to re-visit parts of the AI 4D cycle. As BRIC was only a two-year project, it was impractical to carry out another set of AI interviews in the community. Therefore, the team chose to take a more targeted approach and work with residents who had given their contact details and indicated a desire to become involved as volunteers.

Conclusions and Recommendations

  • AI has proven to be a powerful tool to show the similarities and differences within communities
  • PCC are sure that their engagement was more effective than if they had not gone through the AI cycle
  • It avoided assumptions being made about the community – their level of knowledge and what is important to them
  • AI builds understanding (because it is carried out together with our community and stakeholders)
  • It builds empathy (because it is carried out together)
  • It builds trust (because it is carried out together)
  • It gives legitimacy (because it gives an opportunity to talk to lots of people)