Purpose: The aim of this study was to assess physiotherapists’ clinical use and acceptance of a novel telemonitoring platform to facilitate the recording of measurements during rehabilitation of patients following anterior cruciate ligament reconstruction. Additionally, suggestions for platform improvement were explored. Methods: Physiotherapists from seven Dutch private physiotherapy practices participated in the study. Data were collected through log files, a technology acceptance questionnaire and focus group meetings using the “buy a feature” method. Data regarding platform use and acceptance (7-point/11-point numeric rating scale) were descriptively analysed. Total scores were calculated for the features suggested to improve the platform, based on the priority rating (1 = nice to have, 2 = should have, 3 = must have). Results: Participating physiotherapists (N = 15, mean [SD] age 33.1 [9.1] years) together treated 52 patients during the study period. Platform use by the therapists was generally limited, with the number of log-ins per patient varying from 3 to 73. Overall, therapists’ acceptance of the platform was low to moderate, with average (SD) scores ranging from 2.5 (1.1) to 4.9 (1.5) on the 7-point Likert scale. The three most important suggestions for platform improvement were: (1) development of a native app, (2) system interoperability, and (3) flexibility regarding type and frequency of measurements. Conclusions: Even though health care professionals were involved in the design of the telemonitoring platform, use in routine care was limited. Physiotherapists recognized the relevance of using health technology, but there are still barriers to overcome in order to successfully implement eHealth in routine care.
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STUDY DESIGN: Meta-analysis.OBJECTIVES: To define the accuracy of clinical tests for assessing anterior cruciate ligament (ACL) ruptures.BACKGROUND: The cruciate ligaments, and especially the ACL, are among the most commonly injured structures of the knee. Given the increasing injury prevalence, there is undoubtedly a growing need for clinical decision making of health care providers. We reviewed the literature to analyze the diagnostic accuracy of the clinical examination for assessing ACL ruptures.METHODS AND MEASURES: MEDLINE (1966 to April 2005), EMBASE (1989 to April 2005), and CINAHL (1982 to April 2005) searches were performed. Also reference lists of the included studies were reviewed. Studies selected for data extraction were those that addressed the accuracy of at least 1 physical diagnostic test for ACL rupture and compared the performance of the clinical examination of the knee with a reference standard, such as arthroscopy, arthrotomy, or MRI. Searching was limited to English, German, and Dutch languages.RESULTS: Twenty-eight studies that assessed the accuracy of clinical tests for diagnosing ACL ruptures met the inclusion criteria. Study results were, however, heterogeneous. The Lachman test is the most valid test to determine ACL tears, showing a pooled sensitivity of 85% (95% confidence interval [CI], 83-87) and a pooled specificity of 94% (95% CI, 92-95). The pivot shift test is very specific, namely 98% (95% CI, 96-99), but has a poor sensitivity of 24% (95% CI, 21-27). The anterior drawer test shows good sensitivity and specificity in chronic conditions, respectively 92% (95% CI, 88-95) and 91% (95% CI, 87-94), but not in acute conditions.CONCLUSION: In case of suspected ACL injury it is recommended to perform the Lachman test. Because the pivot shift test is very specific both in acute as well as in chronic conditions, it is recommended to perform the pivot shift test as well.
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Primary anterior cruciate ligament (ACL) injury prevention programs effectively reduce ACL injury risk in the short term. Despite these programs, ACL injury incidence is still high, making it imperative to continue to improve cur- rent prevention strategies. A potential limitation of current ACL injury prevention training may be a deficit in the transfer of conscious, optimal movement strategies rehearsed during training sessions to automatic movements required for athletic activities and unanticipated events on the field. Instructional strategies with an internal focus of attention have traditionally been utilized, but may not be optimal for the acquisition of the control of complex motor skills required for sports. Conversely, external-focus instructional strategies may enhance skill acquisition more efficiently and increase the transfer of improved motor skills to sports activities. The current article will present in- sights gained from the motor-learning domain that may enhance neuromuscular training programs via improved skill development and increased reten- tion and transfer to sports activities, which may reduce ACL injury incidence in the long term.
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In societies where physical activity levels are declining, stimulating sports participation in youth is vital. While sports offer numerous benefits, injuries in youth are at an all-time high with potential long-term consequences. Particularly, women football's popularity surge has led to a rise in knee injuries, notably anterior cruciate ligament (ACL) injuries, with severe long-term effects. Urgent societal attention is warranted, supported by media coverage and calls for action by professional players. This project aims to evaluate the potential of novel artificial intelligence-based technology to enhance player monitoring for injury risk, and to integrate these monitoring pathways into regular training practice. Its success may pave the way for broader applications across different sports and injuries. Implementation of results from lab-based research into practice is hindered by the lack of skills and technology needed to perform the required measurements. There is a critical need for non-invasive systems used during regular training practice and allowing longitudinal monitoring. Markerless motion capture technology has recently been developed and has created new potential for field-based data collection in sport settings. This technology eliminates the need for marker/sensor placement on the participant and can be employed on-site, capturing movement patterns during training. Since a common AI algorithm for data processing is used, minimal technical knowledge by the operator is required. The experienced PLAYSAFE consortium will exploit this technology to monitor 300 young female football players over the course of 1 season. The successful implementation of non-invasive monitoring of football players’ movement patterns during regular practice is the primary objective of this project. In addition, the study will generate key insights into risk factors associated with ACL injury. Through this approach, PLAYSAFE aims to reduce the burden of ACL injuries in female football players.
