The Effect of Digital-Based Simulation on Physiotherapy Students
NCT ID: NCT05863650
Last Updated: 2025-07-28
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
60 participants
INTERVENTIONAL
2024-10-11
2024-12-02
Brief Summary
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Musculoskeletal problems will be selected for the patient scenarios to be used in the simulation and algorithms will be arranged for the simulation. After the algorithms are created, a website with patient scenarios containing these algorithms will be established with the support of a software company. In addition to the website, a database will be created and the applications made on the site will be recorded.
In our study, stepped wedge design will be used. 100 volunteer students participating in the study will start face-to-face training after preliminary evaluations are made. Afterwards, every two weeks, a randomized group of 20 people will be included in the hybrid training, which includes both face-to-face and simulation training. In the face-to-face education group, the educational content prepared in parallel with the patient scenarios in the hybrid education group will be applied in the classroom environment by the students together with the educators themselves. In the hybrid training group, one case analysis will be done every week on the website designed under the supervision of researchers, and one case analysis will be done through face-to-face training.
The self-efficacy and clinical reasoning levels of the students included in the study will be evaluated with the Physiotherapist Self-Efficacy Questionnaire and the Clinical Reasoning Assessment Tool. The same evaluations will be repeated after the students in both groups have completed their 10-week education. Afterwards, students' satisfaction levels and suggestions from the simulation will be evaluated with qualitative questions, and opinions and suggestions about simulation will be collected by creating themes.
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Detailed Description
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Self-efficacy is a concept that is effective in shaping one's behavior. Academic self-efficacy is the individual's belief in himself about how successful he will be in the face of the academic tasks he will face throughout his academic life and at what level he can fulfill these tasks.
In recent years, digital learning designs have been increasingly used in teaching practices in higher education. Various designs offer opportunities to improve self-regulation abilities, facilitate active learning, and make the learning process more transparent. It covers a variety of technologies such as digital learning designs, virtual reality, podcasts, apps, educational games, 360° video and animations. These technologies can be applied directly in learning activities or combined with other planned learning activities.
In studies, digital learning designs in physiotherapy education have been criticized because they are not based on a theoretical learning perspective. A systematic review on the role of computer-assisted learning in physiotherapy education concluded that it has been substantially less researched compared to other health professions education.
Conditions
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Study Design
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RANDOMIZED
CROSSOVER
OTHER
SINGLE
Study Groups
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Hybrid Education
60 volunteer students participating in the study will start face-to-face training after preliminary evaluations are made. Afterwards, a randomized group of 10 people will be included in the simulation training every week. In the face-to-face education group, a case analysis will be applied by the students themselves together with the educators in the classroom environment. In the simulation group, one case analysis will be made every week on the website designed under the supervision of researchers.
Digital based simulation
Algorithms will be created for various musculoskeletal diseases and these algorithms will be controlled by taking the opinions of physiotherapists and physicians who are experts in their fields. After the algorithms are created, a website with patient scenarios containing these algorithms will be established with the support of a software company. In addition to the website, a database will be created and the applications made on the site will be recorded. In this way, the data of users using the website will be collected.
Face to Face Education
60 volunteer students participating in the study will start face-to-face training after preliminary evaluations are made. Afterwards, a randomized group of 10 people will be included in the simulation training every week. In the face-to-face education group, a case analysis will be applied by the students themselves together with the educators in the classroom environment. In the simulation group, one case analysis will be made every week on the website designed under the supervision of researchers.
Face to face education
In the face-to-face education group, one case analyzes will be applied by the students together with the educators themselves in the classroom environment, with the educational content prepared in parallel with the patient scenarios in the simulation-based education group.
Interventions
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Digital based simulation
Algorithms will be created for various musculoskeletal diseases and these algorithms will be controlled by taking the opinions of physiotherapists and physicians who are experts in their fields. After the algorithms are created, a website with patient scenarios containing these algorithms will be established with the support of a software company. In addition to the website, a database will be created and the applications made on the site will be recorded. In this way, the data of users using the website will be collected.
Face to face education
In the face-to-face education group, one case analyzes will be applied by the students together with the educators themselves in the classroom environment, with the educational content prepared in parallel with the patient scenarios in the simulation-based education group.
Eligibility Criteria
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Inclusion Criteria
* Having agreed to participate in the study
* Being in the 6th semester of their studies
Exclusion Criteria
18 Years
25 Years
ALL
Yes
Sponsors
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Health Institutes of Turkey
OTHER_GOV
Marmara University
OTHER
Responsible Party
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Locations
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Marmara University
Istanbul, , Turkey (Türkiye)
Countries
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References
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Montpetit-Tourangeau K, Dyer JO, Hudon A, Windsor M, Charlin B, Mamede S, van Gog T. Fostering clinical reasoning in physiotherapy: comparing the effects of concept map study and concept map completion after example study in novice and advanced learners. BMC Med Educ. 2017 Dec 1;17(1):238. doi: 10.1186/s12909-017-1076-z.
Zimmerman BJ. Self-Efficacy: An Essential Motive to Learn. Contemp Educ Psychol. 2000 Jan;25(1):82-91. doi: 10.1006/ceps.1999.1016.
Veneri D. The role and effectiveness of computer-assisted learning in physical therapy education: a systematic review. Physiother Theory Pract. 2011 May;27(4):287-98. doi: 10.3109/09593985.2010.493192. Epub 2010 Aug 8.
Odegaard NB, Myrhaug HT, Dahl-Michelsen T, Roe Y. Digital learning designs in physiotherapy education: a systematic review and meta-analysis. BMC Med Educ. 2021 Jan 13;21(1):48. doi: 10.1186/s12909-020-02483-w.
Blackstock FC, Watson KM, Morris NR, Jones A, Wright A, McMeeken JM, Rivett DA, O'Connor V, Peterson RF, Haines TP, Watson G, Jull GA. Simulation can contribute a part of cardiorespiratory physiotherapy clinical education: two randomized trials. Simul Healthc. 2013 Feb;8(1):32-42. doi: 10.1097/SIH.0b013e318273101a.
Sandoval-Cuellar C, Alfonso-Mora ML, Castellanos-Garrido AL, Del Pilar Villarraga-Nieto A, Goyeneche-Ortegon RL, Acosta-Otalora ML, Del Pilar Castellanos-Vega R, Cobo-Mejia EA. Simulation in physiotherapy students for clinical decisions during interaction with people with low back pain: randomised controlled trial. BMC Med Educ. 2021 Jul 9;21(1):375. doi: 10.1186/s12909-021-02812-7.
Zhong BL, Luo W, Li HM, Zhang QQ, Liu XG, Li WT, Li Y. Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey. Int J Biol Sci. 2020 Mar 15;16(10):1745-1752. doi: 10.7150/ijbs.45221. eCollection 2020.
van Lankveld W, Jones A, Brunnekreef JJ, Seeger JPH, Bart Staal J. Assessing physical therapist students' self-efficacy: measurement properties of the Physiotherapist Self-Efficacy (PSE) questionnaire. BMC Med Educ. 2017 Dec 12;17(1):250. doi: 10.1186/s12909-017-1094-x.
Phillips AC, Mackintosh SF, Bell A, Johnston KN. Developing physiotherapy student safety skills in readiness for clinical placement using standardised patients compared with peer-role play: a pilot non-randomised controlled trial. BMC Med Educ. 2017 Aug 10;17(1):133. doi: 10.1186/s12909-017-0973-5.
Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine (Phila Pa 1976). 2000 Dec 15;25(24):3186-91. doi: 10.1097/00007632-200012150-00014. No abstract available.
Holdar U, Wallin L, Heiwe S. Why do we do as we do? Factors influencing clinical reasoning and decision-making among physiotherapists in an acute setting. Physiother Res Int. 2013 Dec;18(4):220-9. doi: 10.1002/pri.1551. Epub 2013 May 2.
Torres G, Villagran I, Fuentes J, Araya JP, Jouannet C, Fuentes-Lopez E. Interactive virtual scenarios as a technological resource to improve musculoskeletal clinical reasoning skills of undergraduate physiotherapy students. Physiother Theory Pract. 2022 Aug;38(8):1016-1026. doi: 10.1080/09593985.2020.1809043. Epub 2020 Aug 19.
Hough J, Levan D, Steele M, Kelly K, Dalton M. Simulation-based education improves student self-efficacy in physiotherapy assessment and management of paediatric patients. BMC Med Educ. 2019 Dec 16;19(1):463. doi: 10.1186/s12909-019-1894-2.
Koivisto JM, Haavisto E, Niemi H, Haho P, Nylund S, Multisilta J. Design principles for simulation games for learning clinical reasoning: A design-based research approach. Nurse Educ Today. 2018 Jan;60:114-120. doi: 10.1016/j.nedt.2017.10.002. Epub 2017 Oct 24.
Halabchi F, Hassabi M. Acute ankle sprain in athletes: Clinical aspects and algorithmic approach. World J Orthop. 2020 Dec 18;11(12):534-558. doi: 10.5312/wjo.v11.i12.534. eCollection 2020 Dec 18.
Other Identifiers
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22112022-108
Identifier Type: -
Identifier Source: org_study_id
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