This study explored the dimensionality and measurement invariance of a multidimensional measure for evaluating teachers’ perceptions of the quality of their relationships with principals at the dyadic level. Participants were 630 teachers (85.9% female) from 220 primary and 204 secondary schools across the Netherlands. Teachers completed the 10-item Principal–Teacher Relationship Scale (PTRS) for their principals. Confirmatory factor analyses (CFA) provided evidence for a two-factor model, including a relational Closeness and Conflict dimension. Additionally, multigroup CFA results indicated strong invariance of the PTRS across school type, teacher gender, and teaching experience. Last, secondary school teachers and highly experienced teachers reported lower levels of Closeness and higher levels of Conflict in the relationship with their principal compared to primary school teachers and colleagues with less experience. Accordingly, the PTRS can be considered a valid and reliable measure that adds to the methodological repertoire of educational leadership research by focusing on both positive and negative aspects of dyadic principal–teacher relationships.
Study selection: Randomized controlled trials published after 2007 with (former) healthcare patients ≥ 21 years of age were included if physical activity was measured objectively using a wearable monitor for both feedback and outcome assessment. The main goal of included studies was promoting physical activity. Any concurrent strategies were related only to promoting physical activity. Data extraction: Effect sizes were calculated using a fixed-effects model with standardized mean difference. Information on study characteristics and interventions strategies were extracted from study descriptions. Data synthesis: Fourteen studies met the inclusion criteria (total n = 1,902), and 2 studies were excluded from meta-analysis. The overall effect size was in favour of the intervention groups (0.34, 95% CI 0.23–0.44, p < 0.01). Study characteristics and intervention strategies varied widely. Conclusion: Healthcare interventions using feedback on objectively monitored physical activity have a moderately positive effect on levels of physical activity. Further research is needed to determine which strategies are most effective to promote physical activity in healthcare programmes. Lay Abstract Wearable technology is progressively applied in health care and rehabilitation to provide objective insight into physical activity levels. In addition, feedback on physical activity levels delivered by wearable monitors might be beneficial for optimizing their physical activity. A systematic review and meta-analysis was conducted to evaluate the effectiveness of interventions using feedback on objectively measured physical activity in patient populations. Fourteen studies including 1902 patients were analyzed. Overall, the physical activity levels of the intervention groups receiving objective feedback on physical activity improved, compared to the control groups receiving no objective feedback. Mostly, a variety of other strategies were applied in the interventions next to wearable technology. Together with wearable technology, behavioral change strategies, such as goal-setting and action planning seem to be an important ingredient to promote physical activity in health care and rehabilitation. LinkedIn: https://www.linkedin.com/in/hanneke-braakhuis-b9277947/ https://www.linkedin.com/in/moniqueberger/
MULTIFILE
The use of measurement instruments has become a major issue in physical therapy, but their use in daily practice is infrequent. The aims of this case report were to develop and evaluate a plan for the systematic implementation of two measurement instruments frequently recommended in Dutch physical therapy clinical guidelines: the Patient-Specific Complaints instrument and the Six-Minute Walk Test.
The objective of Waterrecreatie Nederland is to improve water recreation in the Netherlands. One of the focus points that the foundation focuses on is strengthening sustainable water recreation. With this study, Waterrecreatie Nederland wants to map the current CO2 emissions of recreational shipping (here: sailing and motor boats), in order to be able to report and communicate about this, and also as a baseline measurement for future monitoring in this area.Societal IssueShipping has a substantial impact on several environmental systems, amongst others through air and water pollution, and its contribution to climate change. The role of recreational shipping in these issues is not well known, as measurements are scarce and often partly based on assumptions. Benifit to societyThis project tries to strengthen the knowledge base on the carbon (CO2) emissions of recreational shipping in the Netherlands, and to provide detail on fuel use, fuel types, distances, etc. That knowledge can help in making more informed choices on the future development of recreational shipping, with a lower impact on climate change.
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.
Rugpijn komt voor bij veel paarden. De pijngrens van ieder paard is verschillend, het is lastig te constateren of een paard rugpijn heeft. De oorzaken van rugpijn kunnen uiteenlopen zoals slecht passend zadel, kreupelheid, orgaanproblemen, manier van rijden, overbelasting of wervelblokkades. Momenteel wordt rugpijn geconstateerd middels handelingen zoals voelen aan spieren of wervels, visueel beoordelen van de rug. Objectieve analyses op gebied van rug problematieken en bewegingskwaliteit zijn op dit moment erg uitdagend. Het is mensenwerk en vaak zijn de meningen verdeeld zelfs tussen experts met ruime ervaring. Het equine back measurement system kan voor de sector een gamechanger worden door de mogelijkheid om de rug/romp beweging van het paard te objectiveren en kwantificeren en zodoende rugklachten te kunnen aantonen. Het equine back measurement systeem maakt met behulp van sensoren een 3D scan van het rugoppervlak tijdens bewegen (stap/draf) op een lopende band. Middels AI software analyse volgt hieruit een resultaat van de metingen en geeft het systeem aan waar opvallende afwijkingen zitten in de bewegende oppervlaktepatronen. Met deze informatie kan dan bijv. een zadelmaker het zadel op de juiste manier instellen voor het betreffende paard of zijn er indicaties voor nader veterinair onderzoek. Het equine back measurement system zou gecombineerd kunnen worden met alle bestaande lopende band opstellingen voor paarden. In de toekomst zou het systeem zelfs gebruikt kunnen worden om een nieuw te ontwikkelen zadel met luchtkamers aan te sturen. In dit project ligt de focus op genereren van een 3D model met behulp van sensoren zoals dieptecamera’s. Op basis van de ervaring met bewegingsmetingen bij paarden van projectpartner Equimoves is gebleken dat het systeem 200 - 300 metingen per seconde moet kunnen maken om voldoende details te kunnen zien. Bij dit project zijn verder betrokken Peard (zadeldrukmetingen) en Paardenkliniek Venlo.
