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Arch Iran Med. 2018;21(11): 495-501.
PMID: 30551689
Scopus ID: 85059291606
  Abstract View: 3969
  PDF Download: 2217

Original Article

An Approach Towards Reducing Road Traffic Injuries and Improving Public Health Through Big Data Telematics: A Randomised Controlled Trial Protocol

Mehrdad Azmin 1, Ayyoob Jafari 2, Nazila Rezaei 1, Kavi Bhalla 3, Dipan Bose 4, Saeid Shahraz 5, Mina Dehghani 1,6, Parastoo Niloofar 1, Soraya Fatholahi 7, Javad Hedayati 8, Hamidreza Jamshidi 9, Farshad Farzadfar 1,10*

1 Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
2 Faculty of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
3 Department of Public Health Sciences, University of Chicago, Chicago, USA
4 World Bank, Transport Specialist, Washington, DC, USA
5 Heller School of Social Policy and Management, Brandeis University, Waltham, Massachusetts, USA
6 Department of Pharmacoeconomics and Pharmaceutical Administration, School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
7 Department of Health in Disaster and Emergencies, Tehran University of Medical Sciences, Tehran, Iran
8 Safety and Traffic Department, Road Maintenance and Transportation Organization, Tehran, Iran
9 Department of Pharmacology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
10 Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
*Corresponding Author: Email: f-farzadfar@tums.ac.ir

Abstract

Objective: Deaths due to road traffic accidents (RTAs) are a major public health concern around the world. Developing countries are over-represented in these statistics. Punitive measures are traditionally employed to lower RTA related behavioural risk factors. These are, however, resource intensive and require infrastructure development. This is a randomised controlled study to investigate the effect of non-punitive behavioural intervention through peer-comparison feedback based on driver behaviour data gathered by an in-vehicle telematics device.

Design, Setting, and Participants: A randomised controlled trial using repeated measures design conducted in Iran on the drivers of 112 public transport taxis in Tehran province and 1309 inter-city busses operating nationwide. Driving data is captured by an in-vehicle telematics device and sent to a centrally located data centre using a mobile network. The telematics device is installed in all vehicles. Participants are males aged above 20 who have had the device operating in their vehicles for at least 3 months prior to the start of the trial.

Intervention: The study had three stages: 1- Driver performance was monitored for a 4-week period after which they were randomised into intervention and control groups. 2- Their performance was monitored for a 9-week period. At the end of each week, drivers in the intervention group received a scorecard and a note informing them of their weekly behaviour and ranking within their peer group. Drivers in the control group received no feedback via short messaging service (SMS). 3- Drivers did not receive further feedback and their behaviour was monitored for another 4 weeks. Primary and Secondary Outcome Measure: Primary outcome was changes in weekly driving score in intervention and control groups during stage 2 of intervention. Taxis and busses were analysed separately using generalised estimating equation analysis.

Funding and Ethical Approval: This project was funded by the National Institute for Medical Research Development (Grant No.940576) and approved by its ethics committee (Code: IR.NIMAD.REC.1394.016). This trial was registered at www.irct.ir as IRCT20180708040391N1.



Cite this article as: R. An approach towards reducing road traffic injuries and improving public health through big data telematics: a randomised controlled trial protocol. Arch Iran Med. 2018;21(11):495–501.
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Submitted: 23 Jun 2018
Accepted: 07 Oct 2018
ePublished: 01 Nov 2018
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