Thompson, Joanne H. ORCID: https://orcid.org/0009-0002-7327-3766, Thompson, Jonathan ORCID: https://orcid.org/0000-0002-4007-187X and Bailey, Stephen (2024) Shared decision‐making in advanced physiotherapy and first contact physiotherapy management of adults with musculoskeletal disorders in the United Kingdom: An online cross‐sectional survey. Journal of Evaluation in Clinical Practice, 30 (7). pp. 1297-1308.
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Abstract
Rationale: Advanced practice physiotherapy roles (Advanced Physiotherapy Practitioners [APPs] and First Contact Physiotherapists [FCPs]) are pivotal in supporting patients to manage their musculoskeletal (MSK) conditions. Having a greater understanding of how decisions are made by these practitioners will inform competency frameworks and improve the provision of patient‐centred care. Aim: To evaluate the current knowledge, views and use of shared decision‐making in MSK advanced physiotherapy practice in the United Kingdom. Methods: A cross‐sectional survey using an online questionnaire was used to collect demographic information, knowledge, views and self‐reported use of shared decision‐making (SDM) of APPs and FCPs who work with adults with MSK disorders in the United Kingdom. Results: Responses from 49 participants (25 APPs and 24 FCPs) were included in the study. In total, 80% of participants had received SDM training and overall high levels of knowledge were shown. Only 12% of participants used a communication model to facilitate SDM. In total, 80% of participants reported making decisions together with the patient either always or most of the time. FCPs favoured a more patient‐led approach to decision‐making compared to APPs who favoured collaborative decision‐making. The most commonly reported barriers to SDM included lack of time, lack of patient education resources, lack of access to patient decision aids and treatment pathway restrictions. Conclusions: The responses in this study showed that overall APPs and FCPs have good knowledge of SDM and report routine use of collaborative and patient‐led decision‐making approaches.
Item Type: | Article |
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Status: | Published |
DOI: | 10.1111/jep.14043 |
School/Department: | School of Science, Technology and Health |
URI: | https://ray.yorksj.ac.uk/id/eprint/10217 |
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