Knowledge, Attitudes, Beliefs and Behaviors of Physiotherapists to Evidence-Based Practice: A Cross-Sectional Survey

Introduction: Physiotherapists work as autonomous professionals and in team with other healthcare professionals. The present-day healthcare literature consists of arguments about the importance of outcome research and evidence-based practice. Therefore, studying the currently used and new treatmentprocedures along with their supporting evidences is of prime importance particularly to the new graduates.Aim: To determine physiotherapists’ self-reported knowledge, attitudes, beliefs and behaviors to evidencebased practice within a university setting.Method: A cross-sectional survey was conducted among postgraduate physiotherapy students (n=75) within the Gujarat University. Participants completed evidence-based practice questionnaire (EBP-Q) designed to determine knowledge, attitudes, beliefs and behaviors, as well as demographic information about themselves and practice settings. Most responses of questionnaire were rated on a 5-point Likert scale, between ‘strongly agree’ and ‘strongly disagree’. Some items included yes/no/do not know responses, whereas others consisted of understand completely/understand somewhat/do not understand responses.Result: Data was analyzed using SPSS version 20.0. Percentage of participants was calculated for responses of knowledge, attitudes, beliefs and behaviors domains in the questionnaire.Conclusion: Physiotherapists have a positive attitude and beliefs about EBP; however, the knowledge and behaviors among them was relatively poor

Internet of Things: Definition, Applications, Issues and Future Prospective

Internet of Things (IoT) is the extension of Internet into the physical environment around us; by the embodiment of electronics into the everyday physical objects that we tend to use. This makes the digital and physical entities linked by the means of appropriate communication technologies. Penetration of these everyday objects into the web strengthens the goal of offering a whole new set of services to the users, showing them the amalgamation of varied devices, versatile data and various technologies as one common operating picture, using IoT. With the IoT advancements in various sectors, more number of devices are being digitally augmented leading to the discovery of newer issues and challenges that are faced due to these 3 Vs; varied devices, versatile data and various technologies. This survey focuses on identification of such issues and challenges in IoT; suggesting some clues for future research

SARCASM DETECTION IN ONLINE REVIEW TEXT

Sarcasm is a type of sentiment where people express negative sentiment using positive connotation words in text and vice-versa. In this work, we propose a cross-domain sarcasm detection framework that allows acquisition, storage and processing of tweets for detecting sarcastic content in online reviews. We conduct our experiments on Amazon product review dataset namely the Sarcasm Corpus Version1 having about 2000 reviews. We use Support Vector Machines (SVM) and Neural Networks (NN) for detecting sarcasm using lexical, pragmatic, linguistic incongruity and context incongruity features. We report the results and present a comparative evaluation of SVM and NN classifiers for single domain sarcasm detection indicating their suitability for the task. Then, we use these models for cross-domain sarcasm detection. The experimental results indicate the reliability of our approach

Investigating the seasonal variability in source contribution to PM(2.5)and PM(10)using different receptor models during 2013-2016 in Delhi, India

The present work deals with the seasonal variations in the contribution of sources to PM(2.5)and PM(10)in Delhi, India. Samples of PM(2.5)and PM(10)were collected from January 2013 to December 2016 at an urban site of Delhi, India, and analyzed to evaluate their chemical components [organic carbon (OC), elemental carbon (EC), water-soluble inorganic components (WSICs), and major and trace elements]. The average concentrations of PM(2.5)and PM(10)were 131 +/- 79 mu g m(-3)and 238 +/- 106 mu g m(-3), respectively during the entire sampling period. The analyzed and seasonally segregated data sets of both PM(2.5)and PM(10)were used as input in the three different receptor models, i.e., principal component analysis-absolute principal component score (PCA-APCS), UNMIX, and positive matrix factorization (PMF), to achieve conjointly corroborated results. The present study deals with the implementation and comparison of results of three different multivariate receptor models (PCA-APCS, UNMIX, and PMF) on the same data sets that allowed a better understanding of the probable sources of PM(2.5)and PM(10)as well as the comportment of these sources with respect to different seasons. PCA-APCS, UNMIX, and PMF extracted similar sources but in different contributions to PM(2.5)and PM10. All the three models extracted 7 similar sources while mutually confirmed the 4 major sources over Delhi, i.e., secondary aerosols, vehicular emissions, biomass burning, and soil dust, although the contribution of these sources varies seasonally. PCA-APCS and UNMIX analysis identified a less number of sources (besides mixed type) as compared to the PMF, which may cause erroneous interpretation of seasonal implications on source contribution to the PM mass concentration

Exploring the support needs of young adult caregivers, their issues, and preferences towards a web-based tool: a mixed-method study

BackgroundYoung adult caregivers (YACs, aged 18–25) who take care of a loved one may juggle between caregiving responsibilities and other life areas such as education and social life, leading to an imbalance in their lives. The web-based tool ‘MantelzorgBalans’ aims to support informal caregivers (ICGs) in balancing caregiving tasks and activities in other life areas. However, this tool was designed to support ICGs of loved ones receiving palliative care and is not yet tailored to the needs of YACs. In order to do so, in this study we aim to explore (i) challenges and support needs of YACs in caregiving, (ii) their needs towards the content of the ‘MantelzorgBalans’ tool, and (iii) issues they encountered in using the tool and their preferences for adaptation of the tool.MethodWe conducted semi-structured interviews and usability testing with 13 student YACs in the Netherlands. Within usability testing, we used three approaches: (i) a thinking-aloud approach (verbalizing thoughts while using the tool), (ii) a task-based performance approach (scoring task completion rate), and (iii) questionnaires. We used thematic analysis to synthesize the qualitative data. For the quantitative data, we calculated frequencies and mean scores.ResultsOur findings suggest that the majority of YACs faced challenges in balancing caregiving with life areas such as education and social life. They needed support from healthcare professionals who could listen to them without judging them. With respect to the MantelzorgBalans tool, YACs needed more information on how to provide emotional support to their loved one and the emotional support that is available for them. In regards to the aesthetics, they preferred bright colours and more visuals in the tool. Overall, they were satisfied with the information presented in the tool, but they were neutral in their willingness to use it in the future.ConclusionFrom this study, we learn that YACs may experience specific challenges and needs in general, and towards a web-based tool in specific. In the near future, it will be important to develop digital tools to support YACs that match their specific needs. This may enable healthcare professionals to offer targeted and personalized digital support to YACs in future

A Framework for Biomechanical Analysis of Jump Landings for Injury Risk Assessment

Competitive sports require rapid and intense movements, such as jump landings, making athletes susceptible to injuries due to altered neuromuscular control and joint mechanics. Biomechanical features during landings are associated with injury risk, emphasizing proper movement and postural stability. Computer vision techniques offer a time-efficient, noninvasive, and unbiased method to assess jump-landings and identify injury risks. This study proposes a video analysis framework to evaluate jump landing biomechanics in athletes todetermineirregularmovementsandincorrectpostures.It providesadviceandrecommendationstocoachesforinjury predictionandtrainingimprovements.Theproposedframework istestedusingcountermovementjumpvideosof17NCAA DivisionIfemalebasketballathletes.Theresultsindicateda lowMeanAbsoluteError(0.97),highcorrelation(0.89),high averageaccuracy(98.31%)andF1score(0.98),signifyingthe framework’sreliabilityinidentifyinginjuryrisk

Study of pion production in νμ\nu_{\mu} interactions on 40^{40}Ar in DUNE using GENIE and NuWro event generators

The study of pion production and the effects of final state interactions (FSI) are important for data analysis in all neutrino experiments. For energies at which current neutrino experiments are being operated, a significant contribution to pion production is made by resonance production process. After its production, if a pion is absorbed in the nuclear matter, the event may become indistinguishable from quasi-elastic scattering process and acts as a background. The estimation of this background is very essential for oscillation experiments and requires good theoretical models for both pion production at primary vertex and after FSI. Due to FSI, the number of final state pions is significantly different from the number produced at primary vertex. As the neutrino detectors can observe only the final state particles, the correct information about the particles produced at the primary vertex is overshadowed by FSI. To overcome this difficulty, a good knowledge of FSI is required which may be provided by theoretical models incorporated in Monte Carlo (MC) neutrino event generators. In this work, we will present simulated events for two different MC generators - GENIE and NuWro, for pion production in $\nu_{\mu}$CC interactions on $^{40}$Ar target in DUNE experimental set up. A brief outline of theoretical models used by generators is presented. The results of pion production are presented in the form of tables showing the occupancy of primary and final state pion topologies with 100$\%$ detector resolution and with kinetic energy detector threshold cuts. We observe that NuWro (v-19.02.2) is more transparent (less responsive) to absorption and charge exchange processes as compared to GENIE (v-3.00.06), pions are more likely to be absorbed than created during their intranuclear transport and there is need to improve detector technology to improve the detector threshold for better results.Comment: 14 pages, 6 figures, 10 table