Background: To determine whether adolescents with generalized hypermobility spectrum disorder/hypermobile Ehlers-Danlos syndrome (G-HSD/hEDS) show changes in the level of disability, physical functioning, perceived harmfulness and pain intensity after completing multidisciplinary rehabilitation treatment.Methods: Pre-test post-test design. Fourteen adolescents with G-HSD/hEDS participated. The multi-disciplinary rehabilitation treatment consisted of a combination of physical training and exposure in vivo. Physical training aims to improve aerobic capacity, muscle strength and propriocepsis for compensating hypermobility. Exposure in vivo aims to decrease disability and pain-related fear. Pre- and post-treatment assessments were conducted to assess the level of disability, physical functioning (motor performance, muscle strength and physical activity level), perceived harmfulness and pain intensity.Results: After completing multidisciplinary rehabilitation treatment, the adolescents showed a significant and clinically relevant improvement (improvement of 67%, p < 0.01) in functional disability. Furthermore, significant improvements were found in motor performance (p < 0.01), muscle strength (p < 0.05), perceived harmfulness (p < 0.01) and pain intensity (p < 0.01) after completing multidisciplinary rehabilitation treatment.Conclusion: Multidisciplinary rehabilitation treatment leads to a significantly and clinically relevant improvement in the level of disability for adolescents with G-HSD/hEDS. Positive effects were also found in physical functioning, perceived harmfulness and pain intensity. Although the results of this multidisciplinary rehabilitation treatment for adolescents with G-HSD/hEDS are promising, further study is needed to confirm these findings in a randomized design.
BACKGROUND: Differential diagnosis is a hot topic in physical therapy, especially for those working in a direct access setting dealing with neck pain and its associated disorders. All international guidelines agree in recommending to first rule out non-musculoskeletal pathologies as the cause of signs and symptoms in the patient. Although the autonomic nervous system (ANS) has a crucial role and is also involved in pain conditions, coverage of it in neuroscience textbooks and educational programmes is limited and most healthcare professionals are unfamiliar with it. Although autonomic conditions are benign in nature, they are clinically of great importance as they may be a 'red flag' warning of an injury along the sympathetic pathway. Therefore, sound knowledge of the ANS system is essential for clinicians.OBJECTIVE: To develop physical therapists' knowledge of and confidence in understanding cervical ANS function and dysfunction, thus enhancing clinical reasoning skills and the pattern recognition process, and performing and interpreting objective examinations.METHODS: This master class provides an introductory guide and essential knowledge to facilitate clinicians to understand cervical autonomic dysfunctions and their clinical evaluation. The optimal referral method is also handled.CONCLUSIONS: Gaining knowledge and understanding of the ANS, its function, its dysfunction, and the related clinical manifestations is likely to lead to a decision-making process driven by 'science and conscience'. This will empower physical therapists to be aware of subtle clues that may be offered by patients during the interview and history intake leading to the appropriate physical examination and triage.
Background: In recent years, the effectiveness and cost-effectiveness of digital health services for people with musculoskeletal conditions have increasingly been studied and show potential. Despite the potential of digital health services, their use in primary care is lagging. A thorough implementation is needed, including the development of implementation strategies that potentially improve the use of digital health services in primary care. The first step in designing implementation strategies that fit the local context is to gain insight into determinants that influence implementation for patients and health care professionals. Until now, no systematic overview has existed of barriers and facilitators influencing the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Objective: This systematic literature review aims to identify barriers and facilitators to the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Methods: PubMed, Embase, and CINAHL were searched for eligible qualitative and mixed methods studies up to March 2024. Methodological quality of the qualitative component of the included studies was assessed with the Mixed Methods Appraisal Tool. A framework synthesis of barriers and facilitators to implementation was conducted using the Consolidated Framework for Implementation Research (CFIR). All identified CFIR constructs were given a reliability rating (high, medium, or low) to assess the consistency of reporting across each construct. Results: Overall, 35 studies were included in the qualitative synthesis. Methodological quality was high in 34 studies and medium in 1 study. Barriers (–) of and facilitators (+) to implementation were identified in all 5 CFIR domains: “digital health characteristics” (ie, commercial neutral [+], privacy and safety [–], specificity [+], and good usability [+]), “outer setting” (ie, acceptance by stakeholders [+], lack of health care guidelines [–], and external financial incentives [–]), “inner setting” (ie, change of treatment routines [+ and –], information incongruence (–), and support from colleagues [+]), “characteristics of the healthcare professionals” (ie, health care professionals’ acceptance [+ and –] and job satisfaction [+ and –]), and the “implementation process” (involvement [+] and justification and delegation [–]). All identified constructs and subconstructs of the CFIR had a high reliability rating. Some identified determinants that influence implementation may be facilitators in certain cases, whereas in others, they may be barriers. Conclusions: Barriers and facilitators were identified across all 5 CFIR domains, suggesting that the implementation process can be complex and requires implementation strategies across all CFIR domains. Stakeholders, including digital health intervention developers, health care professionals, health care organizations, health policy makers, health care funders, and researchers, can consider the identified barriers and facilitators to design tailored implementation strategies after prioritization has been carried out in their local context
Low back pain is the leading cause of disability worldwide and a significant contributor to work incapacity. Although effective therapeutic options are scarce, exercises supervised by a physiotherapist have shown to be effective. However, the effects found in research studies tend to be small, likely due to the heterogeneous nature of patients' complaints and movement limitations. Personalized treatment is necessary as a 'one-size-fits-all' approach is not sufficient. High-tech solutions consisting of motions sensors supported by artificial intelligence will facilitate physiotherapists to achieve this goal. To date, physiotherapists use questionnaires and physical examinations, which provide subjective results and therefore limited support for treatment decisions. Objective measurement data obtained by motion sensors can help to determine abnormal movement patterns. This information may be crucial in evaluating the prognosis and designing the physiotherapy treatment plan. The proposed study is a small cohort study (n=30) that involves low back pain patients visiting a physiotherapist and performing simple movement tasks such as walking and repeated forward bending. The movements will be recorded using sensors that estimate orientation from accelerations, angular velocities and magnetometer data. Participants complete questionnaires about their pain and functioning before and after treatment. Artificial analysis techniques will be used to link the sensor and questionnaire data to identify clinically relevant subgroups based on movement patterns, and to determine if there are differences in prognosis between these subgroups that serve as a starting point of personalized treatments. This pilot study aims to investigate the potential benefits of using motion sensors to personalize the treatment of low back pain. It serves as a foundation for future research into the use of motion sensors in the treatment of low back pain and other musculoskeletal or neurological movement disorders.
