Reducing Children's Distress Towards Flu Vaccinations

This study has been completed.
Information provided by (Responsible Party):
Tanya Beran, University of Calgary Identifier:
First received: February 3, 2012
Last updated: February 7, 2012
Last verified: February 2012

February 3, 2012
February 7, 2012
October 2011
November 2011   (final data collection date for primary outcome measure)
Faces Pain Scale-Revised [ Time Frame: 5 mins before and immediate after vaccination ] [ Designated as safety issue: No ]
The Faces Pain Scale-Revised was administered to children and their parents while in the waiting room and after consent was signed. Once this questionnaire and consent were completed, the parent and child entered the vaccination room for the vaccination. As soon as the vaccination was completed, the Faces Pain Scale-Revised was re-administered.
Same as current
No Changes Posted
Behavioral Approach-Avoidance Distress Scale [ Time Frame: one week after vaccination was administered ] [ Designated as safety issue: No ]
The Behavioral Approach-Avoidance Distress Scale was used by researchers one week after the data collection phase was completed while reviewing the videos.
Same as current
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Reducing Children's Distress Towards Flu Vaccinations
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Millions of children in North America receive an annual flu vaccination, many of whom are at risk of experiencing severe distress. Children frequently use technologically advanced devices such as computers and cell phones. Based on this familiarity, the investigators introduced another sophisticated device - a humanoid robot to- interact with children during their vaccination. The investigators hypothesized that these children would experience less distress than children who did not have this interaction.
57 children (30 male; age, mean + SD: 6.87 + 1.34 years) were randomly assigned to a vaccination session with a nurse who used standard administration procedures, or with a robot who was programmed to use cognitive-behavioral strategies with them while a nurse administered the vaccination. Measures of distress were completed by children, parents, nurses, and researchers.
Observational Model: Case Control
Time Perspective: Prospective
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Non-Probability Sample
children in the general public and from hospital ages 5-9 years
Children's Distress During Flu Vaccination
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  • humanoid robot distration
    The robot NAO, academic edition (Aldebaran Robotics) was used in this study. Some of its features include an on-board fully programmable computer CPU: x86 AMD Geode with 500 MHz, 256 MB SDRAM and 1 GB flash memory, WiFi (802.11g) and Ethernet, two cameras with up to 30 frames per second, two hands with self adaptive gripping abilities, force sensitive sensors on its arms and feet to perceive contact with objects, Light Emission Diodes in its eyes and body, four microphones to identify the source of sounds, and two loud speakers for communication where tone and voice pitch can be modified in real-time. It runs on a native Linux Operating system platform and can be programmed using a proprietary SDK called NaoQi, or in C, C++, Ruby and Urbi, which makes it compatible with other robot simulators such as Microsoft Robotics Developer Studio.
  • control
    standard care procedures were used during the vaccination
Beran TN, Ramirez-Serrano A, Vanderkooi OG, Kuhn S. Reducing children's pain and distress towards flu vaccinations: a novel and effective application of humanoid robotics. Vaccine. 2013 Jun 7;31(25):2772-7. doi: 10.1016/j.vaccine.2013.03.056. Epub 2013 Apr 24.

*   Includes publications given by the data provider as well as publications identified by Identifier (NCT Number) in Medline.
November 2011
November 2011   (final data collection date for primary outcome measure)

Inclusion Criteria:

  • ages 5-9 years,
  • boys and girls

Exclusion Criteria:

  • children with pervasive developmental disability
5 Years to 9 Years
Contact information is only displayed when the study is recruiting subjects
E 23795
Tanya Beran, University of Calgary
University of Calgary
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Principal Investigator: Tanya Beran, PhD University of Calgary
University of Calgary
February 2012

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP