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Title: | Physiotherapist- and patient-reported barriers to guideline implementation of active physiotherapeutic management of low back pain: A theory-informed qualitative study | Authors: | BOGAERT, Liedewij Brumagne, Simon Leonard, Charlotte Lauwers, Amber Peters, Sanne |
Issue Date: | 2024 | Publisher: | ELSEVIER | Source: | Musculoskeletal Science and Practice, 73 (Art N° 103129) | Abstract: | Background and objective: Adoption of low back pain (LBP) guidelines in physiotherapeutic management is a welldocumented problem. Thereby, an in-depth understanding of the barriers to implement an active approach for both patients and physiotherapists is needed. Design: Semi-structured interviews were conducted with physiotherapists and patients with non-specific LBP. Interviews, guided by the Theoretical Domains Framework (TDF), were analyzed using the Qualitative Analysis Guide of Leuven. Results: A total of 20 participants were interviewed, including ten physiotherapists and ten patients. Our findings reveal that patients and physiotherapists face each 23 barriers spanning 14 TDF domains. The TDF domain "social influences" revealed the most barriers, followed by "beliefs about consequences" and "environmental context" for patients and physiotherapists, respectively. Five barriers did overlap between both groups (lack of guideline awareness, incorrect exercise performance, interdisciplinary communication gaps, time constraints and challenges in patient compliance). Conclusions: Barriers to LBP guideline recommended physiotherapeutic practices span all 14 TDF domains. Consequently, future implementation interventions need to address multiple TDF domains for effective LBP guideline implementation. | Notes: | Bogaert, L (corresponding author), Univ Hosp Leuven, Dept Phys & Rehabil Med, Herestr 49, B-3000 Leuven, Belgium. Liedewij.bogaert@uzleuven.be |
Keywords: | Qualitative research;Physiotherapy;Low back pain;Guidelines;Implementation science | Document URI: | http://hdl.handle.net/1942/43720 | ISSN: | 2468-7812 | e-ISSN: | 2468-7812 | DOI: | 10.1016/j.msksp.2024.103129 | ISI #: | 001284408100001 | Rights: | 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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