Laying the foundations for a behavioural intervention project — Part Two

Experimentation Works
7 min readMay 26, 2021

In this blog series, we will focus on the first two phases of the British Columbia Behavioural Insights Group (BC BIG)’s RIDE Model for Behaviour Shift. This post, the second in the series, will cover the Research phase.

Part 2: Research

In Part one of this series, we introduced you to the Scoping phase of the British Columbia Behavioural Insights Group (BC BIG’s) RIDE Model for Behaviour Shift. In this section, we now focus on the second phase of the model: the ever-so-important Research phase.

Image of the BC Behavioural Insights Group “RIDE Model for Behaviour Shift” used for project work. Six columns represent the six stages of the project cycle (i.e., Scoping phase, followed by the Research, Innovate, Data collection, and Evaluate phases, and ending with a decision on behalf of the client whether or not to Scale the intervention). The first two phases (i.e., Scope and Research) are highlighted.

While the Research phase follows the Scoping phase in the RIDE Model for behaviour shift, in practice research is often conducted throughout the Scoping phase. Indeed, a certain degree of research can be necessary to uncover the behaviours underlying a policy challenge and to identify potential touchpoints to determine whether a behavioural insights (BI) approach is suitable. However, even once the parameters of a BI project have been scoped, important questions will still remain. The Research phase is dedicated to answering these questions, which typically revolve around gaining a better understanding of the challenge from the perspectives of the people involved. These insights are then used to inform the design of the intervention.

In this post, we will cover the methods and considerations around conducting research as part of a BI project. This material may be familiar to public servants with a background in research and citizen engagement. However, we hope that our behavioural focus here will make this of interest to everyone. Specifically, this post will cover:

  1. What is the difference between descriptive and causal research?
  2. Why is descriptive research important?
  3. How can we identify which behavioural barriers exist in relation to a policy challenge?
  4. What is meant by “desk” and “field” research methods?

What exactly do we mean by “research”?

The term “research” is very broad and can mean different things to different people depending on the context. With respect to BI, we often think about a distinction between two forms of research: descriptive and causal. As their names imply, descriptive research focuses on describing the behavioural challenge as it currently exists, whereas causal research aims to identify underlying causes of behaviours.

In the RIDE Model for Behaviour Shift, the Research phase involves descriptive research, whereas the Data and Evaluate phases involve causal research. In a BI project, causal research is typically conducted to empirically evaluate the impact of an intervention. As such, this post focuses on descriptive research approaches.

A three-tiered hierarchy depicts how research can be either Descriptive or Causal and then how Descriptive research can be further broken down into Desk Research or Field Research. Examples of Desk Research include jurisdictional scans and behavioural science literature reviews. Examples of Field Research include focus groups and interviews.

Why conduct descriptive research?

Descriptive research helps us to better understand the who, what, how, when, and where of a policy challenge. It is about exploring the experiences of users of a service or system to identify how it meets, or misses, their unique needs. It can be helpful to think of descriptive research as a method for challenging assumptions and developing hypotheses. We might think we know why members of a target population are not following through with a specific behaviour. We would do research to check assumptions and develop new hypotheses. For example, we may want to know why high school graduates (target population) do not apply to universities (behaviour) in greater numbers? One current assumption is that they are concerned about the financial requirements. Research may reveal another possible explanation — perhaps they are deterred by a complicated application process. With a clearer sense of barriers and where they show up, teams are then better equipped to develop impactful solutions.

For example, the Behavioural Insights Team (BIT) in the UK was looking to solve a challenge whereby they sought to increase collections of fines imposed by the courts, considering that a large amount of money was being spent (and charged to defendants) for bailiffs to chase overdue court payments. Before designing the intervention, a researcher from BIT shadowed a bailiff for a day to conduct research with the population of interest. By visiting the homes of the letter recipients, they noticed that in many cases there was mail piling up outside. These individuals received so many pieces of mail, the request for payment was being overlooked. As a result of this user research, they tested a different communication approach: sending a text message with the recipient’s name to people who had failed to pay their fine in order to give them one final chance to pay before issuing a distress warrant for the bailiffs. The result was a significant increase in payments in response to the text, by around ten percentage points.[1]

What to look for?

When thinking about drivers and barriers related to a behaviour, famed behavioural scientist and author Dan Ariely draws on the analogy of a rocket ship. Encouraging a desired behaviour is like launching a rocket into space. There are two key forces that we need to consider:

  1. The Fuel: Things that move someone towards the behaviour, and
  2. Friction: Things that get in the way.

If you’re looking to change a behaviour — or move the rocket ship — you’ll need to gain a sense of both forces to see what can be adjusted. Unless there are changes in friction or fuel, you tend to stick to the status quo, with the ship going nowhere.

A rocket ship with an arrow going in forward direction (Fuel) and an arrow going in the reverse direction (Friction).

In addition to drivers and barriers, it can be valuable to use descriptive research methods to learn more about:

  • The decision environment: What is the context in which actors are making decisions or performing the behaviours that underlie the policy challenge?
  • The touchpoints: What opportunities exist to engage with the population? (e.g., forms, letters, websites, signs, text messages, etc.).
  • Sentiments and perspectives: How do actors describe their views and feelings related to the policy challenge? Are there any heuristics or psychological biases at play?

What does descriptive research look like?

The research method described above (i.e., having a researcher shadow a bailiff for a day to conduct research with the population of interest) is just one example of a research method. Research methods vary depending on the context, population of interest, and available resources (finances and time). Some research activities can be conducted from one’s desk by simply reading through background materials, analyzing available administrative data, and/or consulting the internet. This cost-effective “desk” research can be contrasted with “field” research (sometimes called “user” research), which is typically more involved and can include methods like interviews, focus groups, or surveys. Although field research tends to be more costly and extensive (e.g., recruiting participants and leveraging a skilled facilitator), the insights are often worth this added effort. This research is tailored to the specific challenge or question. And because the project team is in charge of its design, they can ensure accuracy and ethical processes.

Often at BC BIG, we use a co-design model, whereby we invite our clients to come with us to interview citizens or field staff, so they can hear firsthand about the issues and challenges they face. Even if they don’t participate in the research themselves, hearing about the findings can still be impactful. Sometimes this is the first time they’ve engaged with or heard from the people they serve or the staff that deliver the services and programs they design and oversee.

Desk research and literature reviews

Aside from the value of referring to existing administrative data during the Research phase, academic literature is another valuable source of information during this phase. Certainly, the growing trend towards open-source publications has made published academic findings more accessible than ever. Google Scholar can be a great reference, although some articles are still posted behind paywalls. Along with the proliferation of knowledge, however, can come contradictory findings. This is where referring to meta-analyses and systematic reviews — which combine the results of multiple studies — can provide extremely helpful overviews. In addition, unpublished articles such as dissertations, white papers, and cross-jurisdictional scans can be very useful. Related reports from consulting firms, as well as any existing process maps, journey maps and other outputs/artifacts from human-centered designers or other disciplines, can also be useful in helping to understand the context. In addition, searching for relevant articles in community publications, such as Behavioral Scientist and Behavioral Science & Policy Association, can also be a great source of information for the Research phase of a BI project.

We hope that this two-part series has equipped you with some practical tools to assist with the Scoping and Research phases of a BI project. Happy researching!

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Post by Mikayla Ford (Methods Specialist) and Christine Kormos (Senior Behavioural Scientist), both with the BC Behavioural Insights Group (BC BIG). Housed within British Columbia’s Public Service Agency, BC BIG employs a small team of behavioural scientists, innovation methods specialists, and other professionals who, under a consultancy co-design model, collaborate with ministries and academic partners to generate and test simple solutions to policy problems. The team applies a behavioural insights approach to evidence-based policymaking that draws on evidence from the behavioural sciences (psychology, economics, and neuroscience) about how conscious deliberation interacts with nonconscious processes to influence behaviour, and uses that knowledge to design more effective policies, programs and services for citizens and client ministries.

Article également disponible en français ici : Jeter les bases d’un projet d’intervention comportementale — Partie 2 | par L’expérimentation à l’œuvre | Mai, 2021 | Medium

References:

[1]https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/60539/BIT_FraudErrorDebt_accessible.pdf

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