https://www.tandfonline.com/doi/abs/10.1080/09593985.2018.1456585
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Introduction: The field of motor learning (ML) plays a pivotal role in physical therapy (PT), and its implementation has been shown to improve intervention outcomes. The objective of this study was to assess physical therapists’ ML-related self-efficacy, self-reported implementation, and environmental workplace factors. An additional aim was to report the psychometric properties of a questionnaire that was developed to assess the above-mentioned constructs.
Methods: An observational, cross-sectional survey was completed by 289 physical therapists (average age: 38.7 (9.7), with 11.3 (9.7) years of experience and 74% female). Construct validity, internal consistency, and test–retest reliability were tested. The main outcome measures were the scores of the three scales of the questionnaire, referring to self-efficacy in ML, implementation of ML principles, and workplace environment features.
Results: The questionnaire had sound psychometric qualities. Respondents perceived ML as an integral part of PT. ML-related self-efficacy and implementation of ML principles were moderate (2.95/5 (0.7) and 3.04/5(0.8), respectively). PT practice had a significant effect on ML-related self-efficacy (p = 0.035) and implementation (p = 0.0031). Respondents who had undergone ML training in their graduate program reported higher ML-related self-efficacy (p = 0.007). Respondents who had postgraduate training in ML reported significantly more extensive implementation (p = 0.024). Lack of knowledge and lack of time were perceived as the major barriers to implementation. Conclusions: Level of self-efficacy might be insufficient to support the systematic implementation of ML principles in practice. Addressing impeding individual- and organizational-level factors might facilitate ML self-efficacy and implementation. Postgraduate education facilitates ML implementation.
Methods: An observational, cross-sectional survey was completed by 289 physical therapists (average age: 38.7 (9.7), with 11.3 (9.7) years of experience and 74% female). Construct validity, internal consistency, and test–retest reliability were tested. The main outcome measures were the scores of the three scales of the questionnaire, referring to self-efficacy in ML, implementation of ML principles, and workplace environment features.
Results: The questionnaire had sound psychometric qualities. Respondents perceived ML as an integral part of PT. ML-related self-efficacy and implementation of ML principles were moderate (2.95/5 (0.7) and 3.04/5(0.8), respectively). PT practice had a significant effect on ML-related self-efficacy (p = 0.035) and implementation (p = 0.0031). Respondents who had undergone ML training in their graduate program reported higher ML-related self-efficacy (p = 0.007). Respondents who had postgraduate training in ML reported significantly more extensive implementation (p = 0.024). Lack of knowledge and lack of time were perceived as the major barriers to implementation. Conclusions: Level of self-efficacy might be insufficient to support the systematic implementation of ML principles in practice. Addressing impeding individual- and organizational-level factors might facilitate ML self-efficacy and implementation. Postgraduate education facilitates ML implementation.
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