Motor competence is related to acquisition of error-based but not reinforcement learning in children ages 6 to 12.

Background: An essential component of childhood development is increasing motor competence. Poor motor learning is often thought to underlie impaired motor competence, but this link is unclear in previous studies. Aims: Our aim was to test the relationship between motor competence and motor learning in the acquisition phase. Both reinforcement learning (RL) and error-based learning (EBL) were tested. We hypothesized that slower RL and slower EBL acquisition rates would relate to lower motor competence. Methods and procedures: Eighty-six participants ages 6-12 performed a target throwing task under RL and EBL conditions. The Movement Assessment Battery for Children - 2nd edition (MABC-2) provided a measure of motor competence. We assessed EBL and RL acquisition rates, baseline variability, and baseline bias from the throwing task. Outcomes and results: In a multiple linear regression model, baseline variability (ß = -0.49, p = <0.001) and the EBL acquisition rate (ß = -0.24, p = 0.018) significantly explained the MABC-2 score. Participants with higher baseline variability and slower EBL acquisition had lower motor competence scores. The RL acquisition rate was independent of MABC-2 score suggesting that RL may be less of a contributor to poor motor competence. Conclusions and implications: Children with slower EBL acquisition had lower motor competence scores but RL acquisition was unrelated to the level of motor competence. Emphasizing the unrelated reinforcement mechanisms over error-based mechanisms during motor skill interventions may help children with poor motor competence better acquire new motor skills.

Associations Between Coordination and Wearable Sensor Variables Vary by Recording Context but Not Assessment Type.

Motor coordination is an important driver of development and improved coordination assessments could facilitate better screening, diagnosis, and intervention for children at risk of developmental disorders. Wearable sensors could provide data that enhance the characterization of coordination and the clinical utility of that data may vary depending on how sensor variables from different recording contexts relate to coordination. We used wearable sensors at the wrists to capture upper-limb movement in 85 children aged 6-12. Sensor variables were extracted from two recording contexts. Structured recordings occurred in the lab during a unilateral throwing task. Unstructured recordings occurred during free-living activity. The objective was to determine the influence of recording context (unstructured versus structured) and assessment type (direct vs. indirect) on the association between sensor variables and coordination. The greatest associations were between six sensor variables from the structured context and the direct measure of coordination. Worse coordination scores were associated with upper-limb movements that had higher peak magnitudes, greater variance, and less smoothness. The associations were consistent across both arms, even though the structured task was unilateral. This finding suggests that wearable sensors could be paired with a simple, structured task to yield clinically informative variables that relate to motor coordination.