The power of triangulation

Triangulation is an “expensive” word. It just means looking at an issue from more than one viewpoint. It applies to the research methods, data sources, theories and models that researchers use, and even the research teams themselves. It’s about blending elements which individually lack something to build a more cohesive whole.

The goal is to increase validity and reliability by approaching a research question from different angles. Doing so allows us to cross-verify findings and minimise the biases inherent in any single approach.

Understanding speeding behaviour  

We recently finished a project about speeding. Our goal was to examine ways to encourage drivers to keep to speed limits. We recruited two groups and put dashcams in their cars for a week: 

• Those who said they always kept to the speed limit
• Those who said they broke the speed limit from time to time

The surprising thing? Everyone broke speed limits. In fact, some who claimed not to speed had more incidents of speeding than those who admitted it. Attitudes didn’t correlate with behaviour one bit. 

We also spent time driving with people on their regular journeys — going to work, picking the kids up from school, and going to the shops. We thought the interviewer effect could mean people would be on their best driving behaviour with us present. Truth be told, after five minutes of driving, people forgot we were there. 

The best things come in threes

This accompanied driving really helped our contextual understanding of where people drive too fast. Real-world driving is often automatic. Most of us will have experienced a time when we’ve been commuting and suddenly realised we can’t remember driving for the past five minutes.

You can drive the same route so frequently that you’re able to respond to it automatically. Here, driving is a trade-off between reacting to unexpected occurrences (someone cut me up!) and habit (context-triggered actions when driving a known route).

This is why tactics like vehicle-activated signage and road redesign make a real difference to speeding behaviours. In observations, we saw how they refocus driver attention. We used the ISM model to structure our analysis. It breaks down behaviour into three parts: 

• Individual factors relating to the person: their values, attitudes, skills, and evaluations 
• Social factors relating to the presence of other people on the road
• Material factors relating to aspects of the environment and infrastructure which affect how the driver interacts with the road

Whilst we uncovered lots relating to the individual and their personal circumstances, many of the surprising and counter-intuitive findings related to material factors. Reviewing driving footage showed us how much people reduced their speeds on narrower roads, for example. 

Define. Observe. Triangulate

Our analysis of the cues in the built and social environment — combined with individual beliefs and habits — formed the basis of a new strategy to encourage behaviour change, which we developed in interviews and group workshops.

This project has been a reminder of some of the principles we abide by:

• We define the behaviour carefully 
• We observe, as well as ask 
• We triangulate our methods to get the complete picture 

The last one is particularly important. Attitudes are a poor predictor of driving behaviour. When it comes to a complex issue like speeding, researching attitudes alone is not enough.

Free copies of our book, Closing the Say-Do Gap, are available now. Drop us a line to grab yours.