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1981
Volume 6, Issue 1
  • ISSN: 2042-7875
  • E-ISSN: 2042-7883

Abstract

Abstract

Children’s Health State Preferences Learnt from Animation (CHILDSPLA) is an innovative, multidisciplinary collaboration between the London School of Hygiene and Tropical Medicine, Great Ormond Street Hospital and the Royal College of Art, London. The team came together to develop an animated iPad app aiming to measure the health states of children, designed to gather key data directly from them rather than through a parent or carer. Successful development of a child-friendly method for collecting health information directly from children would add considerably to the ability to measure outcomes and evaluate the effectiveness of treatments. It was expected that the app would allow children as young as 4 years old to express their views, not only because it required lower literacy competencies but also because it would be more engaging. For example, the app was designed to ask the child, ‘on a scale of 1–5 how much pain are you in today?’ but, rather than text or voice, the app showed animated representations of pain, sleeplessness and annoyance, etc. Children were involved from the outset in the design of the character and the animation performances., The style of the animation needed to be tested by the young target users to observe their responses to different styles of animated performance. Some children observed that some animation characters were acting in an exaggerated way, for comic effect, and this distanced them from empathizing with the expressed emotion, as it was not seen as genuine. This led the animator to steer away from broad and exaggerated animation in order to chase engagement and stay closer to subtler, more naturalistic performances.

The animated prototype app was tested by both sick and healthy children against other forms of gathering data. The CHILDSPLA team discussed and reflected on the challenges and knowledge emerging during the first year of the Medical Research Council-funded project.

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/content/journals/10.1386/ap3.6.1.53_1
2017-12-01
2026-04-12

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