ObjectiveTo investigate whether duration of knee symptoms influenced the magnitude of the effect of exercise therapy compared to non-exercise control interventions on pain and physical function in people with knee osteoarthritis (OA).MethodWe undertook an individual participant data (IPD) meta-analysis utilising IPD stored within the OA Trial Bank from randomised controlled trials (RCTs) comparing exercise to non-exercise control interventions among people with knee OA. IPD from RCTs were analysed to determine the treatment effect by considering both study-level and individual-level covariates in the multilevel regression model. To estimate the interaction effect (i.e., treatment x duration of symptoms (dichotomised)), on self-reported pain or physical function (standardised to 0–100 scale), a one-stage multilevel regression model was applied.ResultsWe included IPD from 1767 participants with knee OA from 10 RCTs. Significant interaction effects between the study arm and symptom duration (≤1 year vs >1 year, and ≤2 years vs>2 years) were found for short- (∼3 months) (Mean Difference (MD) −3.57, 95%CI −6.76 to −0.38 and −4.12, 95% CI-6.58 to −1.66, respectively) and long-term (∼12 months) pain outcomes (MD −8.33, 95%CI −12.51 to −4.15 and −8.00, 95%CI −11.21 to −4.80, respectively), and long-term function outcomes (MD −5.46, 95%CI −9.22 to −1.70 and −4.56 95%CI −7.33 to-1.80, respectively).ConclusionsThis IPD meta-analysis demonstrated that people with a relatively short symptom duration benefit more from therapeutic exercise than those with a longer symptom duration. Therefore, there seems to be a window of opportunity to target therapeutic exercise in knee OA.
Extended Reality (XR) technologies—including virtual reality (VR), augmented reality (AR), and mixed reality (MR)—offer transformative opportunities for education by enabling immersive and interactive learning experiences. In this study, we employed a mixed-methods approach that combined systematic desk research with an expert member check to evaluate existing pedagogical frameworks for XR integration. We analyzed several established models (e.g., TPACK, TIM, SAMR, CAMIL, and DigCompEdu) to assess their strengths and limitations in addressing the unique competencies required for XRsupported teaching. Our results indicate that, while these models offer valuable insights into technology integration, they often fall short in specifying XR-specific competencies. Consequently, we extended the DigCompEdu framework by identifying and refining concrete building blocks for teacher professionalization in XR. The conclusions drawn from this research underscore the necessity for targeted professional development that equips educators with the practical skills needed to effectively implement XR in diverse educational settings, thereby providing actionable strategies for fostering digital innovation in teaching and learning.
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