Search results

Does working alliance have an influence on pain and physical functioning in patients with chronic musculoskeletal pain; a systematic review

BackgroundWorking alliance can possibly influence patients’ experiences of pain and physical functioning. The aim of this systematic review is to merge evidence from literature regarding the influence of patients’ perceived working alliance on pain and physical functioning in patients with chronic musculoskeletal pain.MethodsA systematic review in which randomized controlled trials and cohort studies were included that assessed the influence of working alliance on either pain or physical functioning in patients with chronic musculoskeletal pain. The methodological quality of the included studies were rated by means of the PEDro score and STROBE statement.ResultsThe first step of the search process provided 1469 studies. After screening, five studies were included in this review including one RCT and four cohort studies of patients with chronic musculoskeletal pain. One cohort study was rated as low methodological quality and the other studies as high methodological quality. There was a significant effect of working alliance on the outcome of pain severity, pain interference, and physical functioning in all studies. Physical functioning was measured by means of questionnaires and functional capacity tests. The effect on questionnaires was positive; the effect was conflicting on functional capacity.ConclusionWhen influencing pain with treatment, a patient’s perceived working alliance during treatment does predict pain reduction and improvement in physical functioning. It is recommended to inquire about a patient’s working alliance during treatment in patients with chronic musculoskeletal pain.

Sustainability of urban freight transport

AI-based exhaust gas temperature

Data-driven condition-based maintenance (CBM) and predictive maintenance (PdM) strategies have emerged over recent years and aim at minimizing the aviation maintenance costs and environmental impact by the diagnosis and prognosis of aircraft systems. As the use of data and relevant algorithms is essential to AI-based gas turbine diagnostics, there are different technical, operational, and regulatory challenges that need to be tackled in order for the aeronautical industry to be able to exploit their full potential. In this work, the machine learning (ML) method of the generalised additive model (GAM) is used in order to predict the evolution of an aero engine’s exhaust gas temperature (EGT). Three different continuous synthetic data sets developed by NASA are employed, known as New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS), with increasing complexity in engine deterioration. The results show that the GAM can be predict the evolution of the EGT with high accuracy when using several input features that resemble the types of physical sensors installed in aero gas turbines currently in operation. As the GAM offers good interpretability, this case study is used to discuss the different data attributes a data set needs to have in order to build trust and move towards certifiable models in the future.

Who uses running apps and sports watches?

Individual and unorganized sports with a health-related focus, such as recreational running, have grown extensively in the last decade. Consistent with this development, there has been an exponential increase in the availability and use of electronic monitoring devices such as smartphone applications (apps) and sports watches. These electronic devices could provide support and monitoring for unorganized runners, who have no access to professional trainers and coaches. The purpose of this paper is to gain insight into the characteristics of event runners who use running-related apps and sports watches. This knowledge is useful from research, design, and marketing perspectives to adequately address unorganized runners’ needs, and to support them in healthy and sustainable running through personalized technology. Data used in this study are drawn from the standardized online Eindhoven Running Survey 2014 (ERS14). In total, 2,172 participants in the Half Marathon Eindhoven 2014 completed the questionnaire (a response rate of 40.0%). Binary logistic regressions were used to analyze the impact of socio-demographic variables, running-related variables, and psychographic characteristics on the use of running-related apps and sports watches. Next, consumer profiles were identified. The results indicate that the use of monitoring devices is affected by socio-demographics as well as sports-related and psychographic variables, and this relationship depends on the type of monitoring device. Therefore, distinctive consumer profiles have been developed to provide a tool for designers and manufacturers of electronic running-related devices to better target (unorganized) runners’ needs through personalized and differentiated approaches. Apps are more likely to be used by younger, less experienced and involved runners. Hence, apps have the potential to target this group of novice, less trained, and unorganized runners. In contrast, sports watches are more likely to be used by a different group of runners, older and more experienced runners with higher involvement. Although apps and sports watches may potentially promote and stimulate sports participation, these electronic devices do require a more differentiated approach to target specific needs of runners. Considerable efforts in terms of personalization and tailoring have to be made to develop the full potential of these electronic devices as drivers for healthy and sustainable sports participation.

Supervisor and Student Perspectives on Undergraduate Thesis Supervision in Higher Education

Diagnosing teachers are teachers who perceive diagnostic information about students’ learning process, interpret these aspects, decide how to respond, and act based on this diagnostic decision. During supervision meetings about the undergraduate thesis supervisors make in-the-moment decisions while interacting with their students. We regarded research supervision as a teaching process for the supervisor and a learning process for the student. We tried to grasp supervisors’ in-the-moment decisions and students’ perceptions of supervisors’ actions. Supervisor decisions and student perceptions were measured with video-stimulated recall interviews and coded using a content analysis approach. The results showed that the in-the-moment decisions our supervisors made had a strong focus on student learning. Supervisors often asked questions to empower students or to increase student understanding. These supervising strategies seemed to be adapted to students’ needs, as the latter had positive perceptions when their control increased or when they received stimuli to think for themselves.

Playing the DISC: turning on TRAIL death receptor-mediated apoptosis in cancer

Formation of the pro-apoptotic death-inducing signaling complex (DISC) can be initiated in cancer cells via binding of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) to its two pro-apoptotic receptors, TRAIL receptor 1 (TRAIL-R1) and TRAIL-R2. Primary components of the DISC are trimerized TRAIL-R1/-R2, FADD, caspase 8 and caspase 10. The anti-apoptotic protein FLIP can also be recruited to the DISC to replace caspase 8 and form an inactive complex. Caspase 8/10 processing at the DISC triggers the caspase cascade, which eventually leads to apoptotic cell death. Besides TRAIL, TRAIL-R1- or TRAIL-R2-selective variants of TRAIL and agonistic antibodies have been designed. These ligands are of interest as anti-cancer agents since they selectively kill tumor cells. To increase tumor sensitivity to TRAIL death receptor-mediated apoptosis and to overcome drug resistance, TRAIL receptor ligands have already been combined with various therapies in preclinical models. In this review, we discuss factors influencing the initial steps of the TRAIL apoptosis signaling pathway, focusing on mechanisms modulating DISC assembly and caspase activation at the DISC. These insights will direct rational design of drug combinations with TRAIL receptor ligands to maximize DISC signaling. © 2009 Elsevier B.V. All rights reserved.