Training with a three-dimensional multiple object-tracking (3D-MOT) paradigm improves attention in students with a neurodevelopmental condition: a randomized controlled trial

Dev Sci. 2018 Nov;21(6):e12670. doi: 10.1111/desc.12670. Epub 2018 Apr 30.


The efficacy of attention training paradigms is influenced by many factors, including the specificity of targeted cognitive processes, accuracy of outcome measures, accessibility to specialized populations, and adaptability to user capability. These issues are increasingly significant when working with children diagnosed with neurodevelopmental conditions that are characterized by attentional difficulties. This study investigated the efficacy of training attention in students with neurodevelopmental conditions using a novel three-dimensional Multiple Object-Tracking (3D-MOT) task. All students (ages 6-18 years) performed the Conners Continuous Performance Task (CPT-3) as a baseline measure of attention. They were then equally and randomly assigned to one of three groups: a treatment group, (3D-MOT); an active control group (visual strategy/math-based game, 2048); and a treatment as usual group. Students were trained on their respective tasks for a total of 15 training sessions over a five-week period and then reassessed on the CPT-3. Results showed that post-training CPT-3 performance significantly improved from baseline for participants in the treatment group only. This improvement indicates that training with 3D-MOT increased attentional abilities in students with neurodevelopmental conditions. These results suggest that training attention with a non-verbal, visual-based task is feasible in a school setting and accessible to atypically developing students with attentional difficulties.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Attention / physiology*
  • Child
  • Education / methods
  • Humans
  • Neurodevelopmental Disorders / therapy*
  • Simulation Training
  • Students
  • Task Performance and Analysis