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.
Collecting local memories on-line is a growing practice with participatory elements on different levels. Three levels of participation – micro, meso and macro – are introduced by describing an exemplary case: the Memory of East in Amsterdam. These levels of this particular case can be grounded in the statements of the Convention on the Value of Cultural Heritage for Society. This indicates that the Memory of East case might be a good practice. However, looking at 53 other cases shows that the three levels are present, but designed differently with respect to the degree in which residents participate. Since the convention is not specific enough we choose the notion of cultural citizenship to assess the value of cases like these. We claim that the cases that have more focus on ordinary residents participating on all three levels assures a sustainable and self-feeding system, which is the best answer to the goals of the convention.
Recent advancements in mobile sensing and wearable technologies create new opportunities to improve our understanding of how people experience their environment. This understanding can inform urban design decisions. Currently, an important urban design issue is the adaptation of infrastructure to increasing cycle and e-bike use. Using data collected from 12 cyclists on a cycle highway between two municipalities in The Netherlands, we coupled location and wearable emotion data at a high spatiotemporal resolution to model and examine relationships between cyclists' emotional arousal (operationalized as skin conductance responses) and visual stimuli from the environment (operationalized as extent of visible land cover type). We specifically took a within-participants multilevel modeling approach to determine relationships between different types of viewable land cover area and emotional arousal, while controlling for speed, direction, distance to roads, and directional change. Surprisingly, our model suggests ride segments with views of larger natural, recreational, agricultural, and forested areas were more emotionally arousing for participants. Conversely, segments with views of larger developed areas were less arousing. The presented methodological framework, spatial-emotional analyses, and findings from multilevel modeling provide new opportunities for spatial, data-driven approaches to portable sensing and urban planning research. Furthermore, our findings have implications for design of infrastructure to optimize cycling experiences.
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