Category Archives: Communication Design

Nudging Accurate Road Crash Investigation

Around 400 people lose their lives on Indian roads every day. In order to reduce this death count and improve road safety, we need to identify the root causes and then determine solutions. Accurate data capture is critical for this.

The road incident data in India is collected through local police and recorded in FIRs (First Information Report) at the police stations. The investigation reports from the local police stations are sent to the State Governments, who in turn send their report to the Central Government. The police data is used in publishing annual reports of ‘Accidental Deaths and Suicides in India’ and ‘Road Accidents in India’ by two government organizations, National Crime Records Bureau and Ministry of Road Transport and Highways respectively.

Data collected by the police could be subjective as it depends on how the police personnel interpret and ascribe reasons for the incident during investigation at the site. A motor vehicle collision could happen due to faulty road design, pedestrian’s fault, driver’s fault, poor visibility and many other reasons, but more often than not, the driver is blamed. To address this bias and to make crash investigation more objective, an effective and efficient data collection system should be in place.

The route patrolling team (RPT) is usually the first responder for incidents on national or state highways. They record the details of the incidents – the people involved, vehicles involved, cause and type of the incident, date and time of the incident, etc. Because of their ‘first responder’ status, many a times, RPT data forms the basis for the police report. For our Road Safety projects, we designed Crash Investigation Form for the RPT (route patrolling team) with a goal of making the form more objective.

To illustrate the problem of subjectivity, let us look at some examples from our Road Safety projects.

While interacting with a truck driver involved in an incident, the driver revealed that he lost control as he was blinded for a second due to glare of headlights in the opposite lane and rammed into the median opening structure. The RPT classified the cause of this incident as ‘driver was sleepy.’

In another incident, the car driver (admittedly over-speeding) said that in order to avoid running into an auto trying to cut across at the median opening, he turned his vehicle and rammed into the highway guardrail. While investigating the incident, the RPT concluded the reason as ‘driver was over-speeding.’

In both these incidents, the actual causes were ignored – glare in the first incident and a vehicle trying to cut across at high speed in the second incident. We realized that many a times, the RPT interpret the cause of the incident and prepare the report accordingly rather than objectively recording the information, resulting in skewed data and misrepresentation of the incidents.

We redesigned the Crash Investigation Form to nudge the RPT to capture the details in sequence and to hold off analysis of the cause of the incident till the very end of the report. Collecting details like ‘position of the vehicle(s)’ [Fig 1] before and after incident and ‘vehicle damage status’ [Fig 2] is crucial in identifying the cause of the incident and person responsible for the incident.

 

Fig 1

 

Fig 2

Also, capturing incident details is a monotonous process due to which the person collecting data might fail to focus on specific details resulting in skewed data. We designed the Crash Investigation Form with visuals [Fig 3] to make the data collection process more engaging, self explanatory and easy.    

Fig 3

A new incident recording format for the police has been approved and introduced recently by the Transport Research Wing, Ministry of Road Transport & Highways, Government of India. This report is intended to minimize subjectivity while recording the incident details and to arrive at the actual cause of the incident by capturing the technical details like road surface and traffic control systems in place at the incident site. Will this new format aid the police personnel in accurate collection of crash data and minimize subjectivity?

To begin with, it could be difficult for few police personnel to understand and remember terms like ‘staggered junction,’ ‘four arm junction’ ‘paved/unpaved surface,’ etc., (even though workshops are planned to train the police) while filling the details at the incident site. The process to arrive at the ‘cause of the incident’ in the new format could have been more analytical by capturing details like ‘position of the vehicle(s) before and after incident’ and ‘vehicle damage status’ – this is very crucial as solutions/preventive measures depend on the cause of the incidents. The text-heavy report could also have been made easier with illustrations to aid data-capture and reduce monotony. All these aspects might eventually result in incorrect data collection negating the purpose of designing a new format.

For an unbiased and accurate data collection, it is imperative that the Incident Recording Form should be comprehensive, yet easy to understand; visually more engaging; and follow a sequence in data collection with an objective approach in determining the cause of the incident.

P.S.  Only few sections from the Crash Investigation Report designed by us have been published here for reference.

Are all crashes, ‘accidents?’

FinalMile works on a number of road safety projects where we are tasked with reducing incidents on highways. A key part of the work is discussions with the safety team and road users. When we ask them to narrate incidents they have seen or been in, many would say, “I was in an accident” or “I saw an accident.”  Oxford Dictionary defines accident as ‘an unfortunate incident that happens unexpectedly and unintentionally.’  Is it apt to call all the road incidents, ‘accidents?’

The word ‘accident’ is misleading because accident is something that just happens and is unintentional, whereas most crashes happen because of a bad decision made by a driver on the road. Even the crashes that happen due to over-speeding, distracted driving, or driving under influence (DUI) are referred to as accidents. When a driver responsible for a crash says “it was an accident,” what is implied is this: “I did not intend to do it” or “it was unavoidable” even though it was an active decision/choice made by the driver to over-speed, drive when drunk or text while driving. It is the same when a pedestrian jaywalks or crosses without looking. Calling them ‘accidents’ removes the active role the driver or the pedestrian played.

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Head-on collision involving two trucks, killing both the drivers on spot; one of the drivers was drunk – a picture taken during one of our road safety projects.

According to the National Crime Records Bureau (NCRB) report, during the year 2014 in India, 4,50,898 road collisions resulted in 1,41,526 deaths. As per the report, 47.9% of these fatalities were due to over-speeding, 41.5% were due to dangerous/careless driving and overtaking, 5.3% due to poor weather conditions, 2.8% due to mechanical defect and 2.6% due to DUI. If we exclude the fatalities that happened due to poor weather conditions and mechanical failure, 92% of the fatalities were due to driver’s error.

Source: NCRB report 2014
Source: NCRB report 2014

Also, based on a data studied by National Highway Traffic Safety Administration (NHTSA) of US, 94% of the collisions are due to driver’s error. Around 20 years ago, the US Department of Transportation initiated a campaign to eliminate the use of word ‘accident,’ and police departments of New York City and San Francisco have replaced the word ‘collision’ for ‘accident’ while filling out collision reports.  According to US National Highway Traffic Safety Administration, ‘changing the way we think about events, and the words we use to describe them, affects the way we behave. Motor vehicle crashes and injuries are predictable, preventable events. Continued use of the word “accident” promotes the concept that these events are outside of human influence or control. In fact, they are predictable results of specific actions.’

It is not just about control during the event. Language affects the chain of reasoning far beyond the event. People have a more general tendency to attribute their own behavior to situational factors and other’s behavior to dispositional factors – a social bias known as the “fundamental attribution error.”  Attribution theory helps us to understand why, in case of a crash, the driver attributes his fault to situational factors such as poor visibility or another vehicle, while ascribing behavior of the other driver to dispositional factors such as reckless/wrong side driving or over-speeding. The word ‘accident’ aids in ascribing the reason of the crash to external factors and makes it easy to rationalize. When the crash is clearly attributable to driver’s error, by calling it an accident, the driver is being excused for his negligence and unsafe behavior.  By referring to the crashes as accidents where the driver was not following the posted speed limits, manoeuvring dangerously on the road, or getting behind the wheel drunk, we are not holding the person responsible for the act. It is not that someone has to be blamed or held responsible for every crash, it is to make drivers more responsible and realize that crashes do not happen randomly.

The word ‘accident’ is very colloquial and it is a difficult task for sure to bring about the change in our system, but replacing it with ‘crash’ or ‘collision’ would be the first step to change our perception towards road safety.

Who is likely to win? Depends on How you ask

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The race is heating up. And so are the experts that are conducting, interpreting and concluding opinion polls. As the focus of US presidential election is moving away from on primaries to the final competition, we should expect results from hundreds of opinion polls predicting the winner.

A recent NY times article suggested that Clinton leads Trump by around 10 percentage points. If you believe these polls, then you may be hopeful or concerned depending on which side you are on. But there is a small issue. The result may not be accurate.

This article indicates that there is a significant difference in the results of polls conducted online vs over the phone. The lead comes down four percent when surveys are conducted online. One the reasons cited is the social desirability bias – a desire to project a positive image when one is worried of being judged based on their response. People may go at any lengths to avoid the discomfort and embarrassment of stating an unfavorable response even if that is their honest response. But in a situation of anonymity, I may go back to my preference.

The problem is not new and its not limited to presidential polls. The issue has been discussed extensively in market research. And it becomes much more pronounced in sensitive areas of financial and health care related decision making. Imagine talking to a individual undergoing financial hardships and being delinquent on their debts. Or a conversation around understanding why someone is not adhering to their antibiotics regimen.

Clearly, we need more sophisticated research methodologies to deal with such sensitive matters. In our work in the social sector, we have regularly innovated our research processes to mange these issues. For example, in one of our projects in Africa we used a gamification based research tool wherein the format incentivized true responses over socially desirable response. The research methodology was recognized by The Esomar Congress 2015 where Final Mile won the Best Case History award.

Innovative tools for learning voter’s preference also exist. The Iowa Electronics Market established back in 1988 is one of the early pioneers. Even changing the way the question is framed can have a significant impact. For example, instead of framing the survey question as which candidate are you likely to vote, a better question would be which candidate is likely to win. So while we monitor the election outcomes, it will also be interesting to study the prediction accuracies of the different research tools.

Image Credit: Indian Panorama

Nutrition SBCC Video

Final Mile is part of the SBCC (Social Behavior Change Communication) Expert Working Group constituted by SPRING & GAIN under the aegis of USAID. The EWG is tasked with evolving SBCC strategies for improving Nutrition behaviors at scale. Two S’s are critical to this strategy: Scale & Social.

Final Mile played a key role in shaping of this strategy. The Nutrition community, thanks partly to our efforts, saw value in using learnings from Behavioral Economics, Cognitive Neuroscience and Design Thinking to shape SBCC strategies. The case studies and approaches we shared have demonstrated that application of Behavioral Sciences can be achieved at scale provided we use the right research tools and test various interventions, in context. The future of SBCC in Nutrition is being shaped by a group of highly committed organisations that have proven expertise in their areas and we are delighted to be in that group. Here is a short video that captures the essence of this evolving SBCC strategy. It also captures one of our projects that has been featured as one of the “Great SBCC Examples”

 

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