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Movement Representation Strategies as a Tool for Educational Innovation in Physiotherapy Students: A Randomized Single-Blind Controlled-Pilot Trial.

Ferran Cuenca-MartínezLuis Suso-MartíBorja Pérez-DomínguezJoaquín CalatayudRubén López-BuenoPedro GargalloMaría Blanco-DíazJose Casaña-Granell
Published in: International journal of environmental research and public health (2023)
Physiotherapy has a strictly theoretical body of knowledge, but for the most part, the physiotherapist's learning is practical. The practical part is fundamental to acquire clinical skills that the physiotherapist will later use in professional practice. The main aim of this study was to assess the effectiveness of movement representation strategies (MRS) in the improvement of manual skills of physiotherapy students as an educational innovation strategy. We randomly assigned 30 participants to an action observation practice (AOP), motor imagery practice (MIP), or sham observation (SO) group. A high velocity, low amplitude lumbar manipulation technique that is widely used in clinical physiotherapy practice was taught in one session. The primary outcomes were required time and test score. The secondary outcomes were perceived mental fatigue and perceived difficulty for learning. The outcomes were assessed preintervention and immediately after the intervention (postintervention). The main results showed that both AOP and MIP improved the total time required and the test score, as well as entailed less perceived difficulty for learning. However, both strategies showed a higher level of mental fatigue after the intervention, which was higher in the MIP group. Based on the results obtained, it seems that the application of MRS promotes greater learning of manual motor tasks in physiotherapy students and could be used as educational innovation strategies.
Keyphrases
  • healthcare
  • primary care
  • mental health
  • randomized controlled trial
  • social support
  • depressive symptoms
  • physical activity
  • quality improvement
  • high school
  • sleep quality
  • neural network