Use Of Tool Research Articles

Pneumonia diagnosis performance in the emergency department: a mixed-methods study about clinicians' experiences and exploration of individual differences and response to diagnostic performance feedback.

We sought to (1) characterize the process of diagnosing pneumonia in an emergency department (ED) and (2) examine clinician reactions to a clinician-facing diagnostic discordance feedback tool. We designed a diagnostic feedback tool, using electronic health record data from ED clinicians' patients to establish concordance or discordance between ED diagnosis, radiology reports, and hospital discharge diagnosis for pneumonia. We conducted semistructured interviews with 11 ED clinicians about pneumonia diagnosis and reactions to the feedback tool. We administered surveys measuring individual differences in mindset beliefs, comfort with feedback, and feedback tool usability. We qualitatively analyzed interview transcripts and descriptively analyzed survey data. Thematic results revealed: (1) the diagnostic process for pneumonia in the ED is characterized by diagnostic uncertainty and may be secondary to goals to treat and dispose the patient; (2) clinician diagnostic self-evaluation is a fragmented, inconsistent process of case review and follow-up that a feedback tool could fill; (3) the feedback tool was described favorably, with task and normative feedback harnessing clinician values of high-quality patient care and personal excellence; and (4) strong reactions to diagnostic feedback varied from implicit trust to profound skepticism about the validity of the concordance metric. Survey results suggested a relationship between clinicians' individual differences in learning and failure beliefs, feedback experience, and usability ratings. Clinicians value feedback on pneumonia diagnoses. Our results highlight the importance of feedback about diagnostic performance and suggest directions for considering individual differences in feedback tool design and implementation.

P.019 A shared decision-model toolkit for pregnancy related care in neurology

Background: Shared decision-making (SDM) is a dynamic, patient-engaged approach to collaborative medical care. Limited SDM tools exist in pregnancy. We aimed to examine the need and usability of a novel SDM tool for pharmaco-therapeutic treatment of neurological conditions in pregnancy. Methods: This is an exploratory mixed-methods study. Non-pregnant women of any age were recruited using convenience, purposive sampling from an academic neurology clinic in Toronto. Participants reported the user friendliness of the SDM by completing the systems usability (SUS) questionnaire and participated in a focus group to further elaborate on their experience. Results: Eleven participants completed the survey 45% each between age 31-40, and 51-60. Median time spent on the tool was 17.2 minutes, and median SUS score 70 (<68 being not usable). Thematic data analysis from 2 focus groups, identified technical and content improvements: use of inclusive language, simplified design, and importance of patient engagement in SDM. Conclusions: Based on our preliminary results, a SDM web-tool for medication-related concerns of pregnant patients with neurological conditions is needed and usable. With integration of patients’ lived experiences, this novel tool may serve as an anchor point for future work in this field.

A survey on students’ use of AI at a technical university

We report the results of a 4800-respondent survey among students at a technical university regarding their usage of artificial intelligence tools, as well as their expectations and attitudes about these tools. We find that many students have come to differentiated and thoughtful views and decisions regarding the use of artificial intelligence. The majority of students wishes AI to be integrated into their studies, and several wish that the university would provide tools that are based on reliable, university-level materials. We find that acceptance of and attitudes about artificial intelligence vary across academic disciplines. We also find gender differences in the responses, which however are smaller the closer the student’s major is to informatics (computer science).

Electronic maternal and child health application usability, feasibility and acceptability among healthcare providers in Amhara region, Ethiopia.

An innovative electronic Maternal and Child Health (eMCH) application was developed to support operational and clinical decision-making in maternal and child health services. End-user-based evaluation of eHealth application is a critical step to ascertain how successfully users can learn and use it, and improve the technology. Therefore, this study aimed to evaluate the eMCH tool usability, feasibility, and acceptability among healthcare providers (HCPs) in the Amhara region, Ethiopia. A cross-sectional study was conducted among HCPs working in six public healthcare facilities. The usability evaluation was done on 24 HCPs across three professional categories using the ISO 9241-11 usability guideline. One hundred nine HCPs were participated in the feasibility and acceptability study. Data were collected using a standard usability tool, think-aloud protocol, a self-administered approach, and Open Broadcaster Software Studio version 26.1.1 video recorder. Descriptive statistics were used to describe the data. A Kruskal-Wallis test was used to measure the association between mean scores and categories of HCPs. The recorded videos were used for the log file analysis method. None of the HCP categories were able to complete all the tasks without errors. The average number of errors and restarts were 7.5 and 2.8, respectively. The average number of restarts was directly proportional to the average number of errors. The participants successfully completed more than 70% of the tasks without requiring any assistance or guidance. Forty-seven comments or errors were identified from the think-aloud analysis and 22 comments from the usability metrics analysis. Overall, statistically significant performance differences were observed among the three HCP groups across the majority of the usability evaluation metrics. Fifty-seven percent of HCPs scored higher than the mean on the feasibility study. Slightly higher than half, 56 (51.4%), of the HCPs scored higher than the mean score on the acceptability study. The usability evaluation identified vital comments and usability flaws that were essential for the eMCH tool to be upgraded. The tool was feasible and acceptable as reported by end-users. Therefore, the errors and usability flaws of the tool should be fixed before deployment to other healthcare settings.

Nurse by numbers: The impact of early warning systems on nurses' higher-order thinking, a quantitative study.

To evaluate registered nurses' perceptions of whether the mandated use of the early warning system vital signs tool impacts the development of nurses' higher-order thinking skills. A concurrent mixed methods study design. Using an online survey, registered nurses' perceptions were elucidated on whether early warning system algorithmic tools affected the development of their higher-order thinking. Likert-type matrix questions with additional qualitative fields were used to obtain information on nurse's perceptions of the tool's usefulness, clinical confidence in using the tool, compliance with escalation protocols, work environment and perceived compliance barriers. Most of the 305 (91%) participants included in the analysis had more than 5 years of nursing experience. Most nurses supported the early warning tool and were happy to comply with escalation protocols if the early warning score concurred with their assessment of the patient (63.6%). When the score and the nurse's higher-order thinking did not align, some had the confidence to override the escalation protocol (40.0%), while others omitted (69.4%) or inaccurately documented vital signs (63.3%) to achieve the desired score. Very few nurses (3.6%) believe using early warning tools did not impede the development of higher-order thinking. Although experienced nurses appreciate the support of early warning tools, most value patient safety above the tools and rely on their higher-order thinking. The sustained development and use of nurses' higher-order thinking should be encouraged, possibly by adding a critical thinking criterion to existing algorithmic tools. The study has implications for all nurses who utilize algorithmic tools, such as early warning systems, in their practice. Relying heavily on algorithmic tools risks impeding the development of higher-order thinking. Most experienced nurses prioritize their higher-order thinking in decision-making but believe early warning tools can impede higher-order thinking. Registered nurses participated as survey respondents.

Comparative evaluation of the web-based contiguous cartogram generation tool go-cart.io.

Area cartograms are map-based data visualizations in which the area of each map region is proportional to the data value it represents. Long utilized in print media, area cartograms have also become increasingly popular online, often accompanying news articles and blog posts. Despite their popularity, there is a dearth of cartogram generation tools accessible to non-technical users unfamiliar with Geographic Information Systems software. Few tools support the generation of contiguous cartograms (i.e., area cartograms that faithfully represent the spatial adjacency of neighboring regions). We thus reviewed existing contiguous cartogram software and compared two web-based cartogram tools: fBlog and go-cart.io. We experimentally evaluated their usability through a user study comprising cartogram generation and analysis tasks. The System Usability Scale was adopted to quantify how participants perceived the usability of both tools. We also collected written feedback from participants to determine the main challenges faced while using the software. Participants generally rated go-cart.io as being more usable than fBlog. Compared to fBlog, go-cart.io offers a greater variety of built-in maps and allows importing data values by file upload. Still, our results suggest that even go-cart.io suffers from poor usability because the graphical user interface is complex and data can only be imported as a comma-separated-values file. We also propose changes to go-cart.io and make general recommendations for web-based cartogram tools to address these concerns.

Evaluation of the Scientific Quality and Usability of Digital Dietary Assessment Tools

The importance of digital tools for dietary assessment has increased in recent years, both commercially and scientifically. In the field of nutrition research, the digitization of dietary assessment methods presents many opportunities and risks. One of the main challenges is ensuring scientific quality while maintaining good usability. In this context, an evaluation tool was developed based on the guidelines of the European Food Safety Authorization (EFSA; 2009 and 2014), complemented by the usability aspect of health-related applications. This was followed by a literature search concerning the available dietary assessment tools, which were analyzed according to the evaluation criteria. Eight applications were included in the study after reviewing the inclusion and exclusion criteria for the digital tools. A total of thirty-eight requirements in eight main categories were defined for the evaluation, which the best possible dietary assessment tool should meet. The evaluation showed that none of the tested tools currently meet all the defined requirements or categories. The aspects of usability and the accuracy of data collection showed a positive correlation, suggesting a direct link between the two categories and providing an important approach for future developments.

Open dynamics of entanglement in mesoscopic bosonic systems

A key issue in quantum information is finding an adequate description of mesoscopic systems that is simpler than full quantum formalism yet retains crucial information about non-classical phenomena like entanglement. In particular, the study of fully bosonic systems undergoing open evolution is of great importance for the advancement of photonic quantum computing and communication. In this paper, we propose a mesoscopic description of such systems based on boson number correlations. This description allows for tracking Markovian open evolution of entanglement of both non-Gaussian and Gaussian states and their sub-Poissonian statistics. It can be viewed as a generalization of the reduced state of the field formalism (Alicki 2019 Entropy 21 705), which by itself does not contain information about entanglement. As our approach adopts the structure of the description of two particles in terms of first quantization, it allows for broad intuitive usage of known tools. Using the proposed formalism, we show the robustness of entanglement against low-temperature damping for four-mode bright squeezed vacuum state and beam-splitted single photon. We also present a generalization of the Mandel Q parameter. Building upon this, we show that the entanglement of the state obtained by beam splitting of a single occupied mode is inherited from sub-Poissonian statistics of the input state.

Cryogenic Deep Drawing Tool Design for Reduced Heat Transfer

Subject of this study is the usage of macro-structured tools for deep drawing of aluminum alloys at cryogenic temperatures in order to increase the drawing depth. The advantage of the macro-structure is the reduced contact area, which primarily leads to a reduction in frictional forces in the flange area and also minimizes the heat transfer from the tool to the cooled sheet metal. In addition to the geometry of the tools, the heat transfer is also influenced by the thermal properties of the tool materials. Therefore, the tool must be designed to reduce heat flux and thermal diffusivity. In this regard, substitute materials for the tools, specifically polymer, and steel-shielded polymer, were investigated. In this context, the heat transfer coefficients between the tool material and the aluminum blank are determined experimentally. The influence of thermal conditions on the cryogenic deep drawing process are investigated numerically and experimentally. The result of the study is an improved process understanding to ensure the blank temperature in a cryogenic range and increase the resistance against bottom cracks.

A short responsive interaction scale: construction and preliminary reliability and validity

Background: Responsive interactions among caregivers and newborns are essential for positive and optimal growth and development. The aim of this cross-sectional study was to develop and validate a short responsive interaction tool (SRIS) to assess caregiver responsiveness of newly delivered mothers. Methods: The SRIS consists of twenty elements that are used to classify new-born handling, interactions, consoling techniques, engagement, and distress. High reliability and internal consistency were shown in the data gathered from 257 mothers (Cronbach's alpha=0.8354). The scale's one-dimensional structure was discovered through construct validity analysis, demonstrating the consistency of the scale's evaluation of response interactions. Results: The results indicate that the valid and reliable instrument for gauging the responsiveness of caregivers during their initial contact with neonates. It provides a useful and approachable method with possible uses in healthcare settings and research for evidence-based parenting interventions. Conclusions: To improve the tool's generalizability and usefulness in fostering early childhood development and parental engagement, further research is necessary to validate it across a variety of contexts.

Social Media Data Mining and Mental Health Status Assessment Based on Sentiment Analysis

The usage of the word Power quality in recent times acquired intensified interest due to the complex industrial processes. The usage of intelligent tools to improve power quality is increasing day by day, as assumption of present day power system as a linear model is unsatisfactory. This paper deals with analysis of Differential Evolution (DE), Hybrid Differential Evolution (HDE) and Variable Scaling Hybrid Differential Evolution for harmonic reduction in the source current with optimal tuning of PI controller gain values. Shunt Active power Filter is one of the better solution to suppress the source current harmonics which are induced into power system because of nonlinear loads. Current controller called HBCC is considered for gating operation of switches in Voltage Source Inverter. The Intelligent tuned PQ theory is used for reference current generation. The then obtained compensating currents are injected at point of common coupling for current disturbance mitigation. Simulations of MATLAB/SIMULINK environment of the present work shows the efficacy.

Examining the Effectiveness of Educational Tools and Elements Used in Medical Textbooks: Students' Perspective.

Background As textbooks constitute a foundational component of medical education, it is imperative to conduct a rigorous evaluation of their efficacy by examining the fundamental elements and tools utilized within these textbooks and how multiple factors may alter the effectiveness of such components. Materials and methods We conducted a cross-sectional, survey-based study where 251 subjects anonymously rated the effectiveness of different tools and elements/factors used in medical textbooks using 5-point Likert scales. The population surveyed included year 1 to 5 medical students at Alfaisal University, where students are admitted to medical school directly after high school, with an approximately equal male-to-female admission rate. Students were asked to rate the effectiveness of the following tools: chapter summary, end-of-chapter questions, tables of contents, graphic elements, diagrams, tables, flowcharts, mind maps, sidebars, and links to online resources. In admission, they were asked to rate textbooks regarding the following elements/factors: text clarity, directness to the concept intended, flow of ideas, language complexity, and clinical (vertical) and multidisciplinary (horizontal) integration. The Chi-square, post-hoc, Spearman's correlation, and Kruskall-Wallis tests were used in the statistical analysis to determine the differences and correlations in the students' self-ratings of different variables. Results The students rated tools such as diagrams and graphic elements as the most effective. Graphic elements were rated as significantly more effective by first- and fourth-year students. This corresponds to being exposed to new environments (the first exposure to the study of medicine and the first exposure to clinical clerkship), indicating their effectiveness in introducing new concepts and setting of change. Furthermore, end-of-chapter summaries and questions were rated significantly as being more effective by females (P<0.05). The aim behind using textbooks and the frequency might be governed by how students rate textbooks regarding multiple elements or factors, including directness to the concept intended, flow of ideas, and language complexity. Interestingly, all the above findings were consistent throughout all grade point average groups. Discussion In the rising age of e-learning, our study shows that the tools employed by textbooks remain effective. Our findings are partially consistent with existing literature, which underscores correlations between demographic variables and learning styles. We show that the effectiveness of various tools employed in textbooks can vary depending on the educational setting. While demographic factors generally did not impact students' perceptions of tool effectiveness, gender-specific differences were observed in the perceived effectiveness of end-of-chapter summaries and questions, with female students rating them as more effective, which aligns with existing literature. Conclusions Our study shows that students still perceive the tools employed by textbooks as effective. The perceived effectiveness of various tools utilized within textbooks may be influenced by certain demographic factors and settings, with graphics often proving the most efficacious. This study provides valuable insights for authors of medical textbooks, helping them optimize the usage of various tools by considering the specific characteristics and requirements of the intended audience.

A Comprehensive Review on Cutting Tool Material in Hard Turning Performance

The work presents a comprehensive review on the influences of cutting tool material on the efficiency of hard turning process. Major trends in tool use and coating innovations are specified. The results of the hard turning process are evaluated through a number of main parameters such as surface roughness, cutting force, cutting heat, and wear mechanism. These results show that high cutting forces and cutting temperatures are still the huge challenges in choosing cutting tool materials in hard turning. This also limits the applicability of these materials and increases tooling costs due to the need to move towards using cutting tools with higher grades and hardness. The analysis results also point out the necessity of using appropriate cooling lubrication technology to support the hard turning process, helping to improve tool usage efficiency and the effectiveness of the hard turning process.

The Challenge of Traditional Teaching Approach: A Study on the Path to Improve Classroom Teaching Effectiveness Based on Secondary School Students' Psychology

Currently, the psychological issues faced by secondary school students and their impact on classroom instruction are widely discussed. Throughout the middle school years, adolescents experience both physical and cerebral development. As material living conditions improve and social attitudes diversify, secondary school children experience fast cognitive development, possess a strong sense of self, and may also exhibit anxiety and rebellious tendencies. Nevertheless, the present traditional classroom exhibits many drawbacks, including a singular teaching approach, disconnection from real-world applications, insufficient emphasis on perceptual skills development, and disregard for students' active engagement in information acquisition. Conventional classrooms are no longer capable of fulfilling the requirements of learners. Thus, considering the psychological traits of middle school children, this study proposes the following recommendations: Firstly, create a classroom environment that is focused on the needs and interests of the students. Secondly, use the cooperative learning approach inside the classroom. Lastly, incorporate the usage of multimedia tools and techniques for instructional purposes.

Evaluation of a Digital Dementia Registry's IT Architecture After a Three-Year Period in Practice: digiDEM Bayern.

The project "digiDEM Bayern" aims to set up a registry with long-term follow-up data on people with dementia and their family caregivers. For that purpose an Electronic Data Capture (EDC) system linked with a Participant Management (PM) system has been established. This study evaluates the acceptance and usability of the IT tools supporting all data management processes in order to further improve the system and associated processes. For this purpose we collected the key numbers of the registry, and used the System Usability Scale (SUS) to evaluate the interactions of the data management systems in a wide area. Thirty-six research partners (RP) and six study team (ST) members completed the anonymous online survey. The EDC system overall reached an average SUS score of 73.42 and the PM system of 77.92. The two systems fulfil their required task and, therefore, simplify the work of the RP in the data collection process and of the ST during the data quality checks. Integrating the used systems is therefore recommended for registry studies in other medical areas.

Common challenges and suggestions for risk of bias tool development: a systematic review of methodological studies

ObjectivesTo review the findings of studies that have evaluated the design and/or usability of key risk of bias (RoB) tools for the assessment of RoB in primary studies, as categorized by the Library of Assessment Tools and InsTruments Used to assess Data validity in Evidence Synthesis Network (a searchable library of RoB tools for evidence synthesis): Prediction model Risk Of Bias ASessment Tool (PROBAST) , Risk of Bias-2 (RoB2), Risk Of Bias In Non-randomised Studies of Interventions (ROBINS-I), Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), Quality Assessment of Diagnostic Accuracy Studies-Comparative (QUADAS-C), Quality Assessment of Prognostic Accuracy Studies (QUAPAS), Risk Of Bias in Non-randomised Studies of Exposures (ROBINS-E), and the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) RoB checklist. Study Design and SettingSystematic review of methodological studies. We conducted a forward citation search from the primary report of each tool, to identify primary studies that aimed to evaluate the design and/or usability of the tool. Two reviewers assessed studies for inclusion. We extracted tool features into Microsoft Word and used NVivo for document analysis, comprising a mix of deductive and inductive approaches. We summarized findings within each tool and explored common findings across tools. ResultsWe identified 13 tool evaluations meeting our inclusion criteria: PROBAST (3), RoB2 (3), ROBINS-I (4), and QUADAS-2 (3). We identified no evaluations for the other tools. Evaluations varied in clinical topic area, methodology, approach to bias assessment, and tool user background. Some had limitations affecting generalizability. We identified common findings across tools for 6/14 themes: (1) challenging items (eg, RoB2/ROBINS-I “deviations from intended interventions” domain), (2) overall RoB judgment (concerns with overall risk calculation in PROBAST/ROBINS-I), (3) tool usability (concerns about complexity), (4) time to complete tool (varying demands on time, eg, depending on number of outcomes assessed), (5) user agreement (varied across tools), and (6) recommendations for future use (eg, piloting) and development (add intermediate domain answer to QUADAS-2/PROBAST; provide clearer guidance for all tools). Of the other eight themes, seven only had findings for the QUADAS-2 tool, limiting comparison across tools, and one (“reorganization of questions”) had no findings. ConclusionEvaluations of key RoB tools have posited common challenges and recommendations for tool use and development. These findings may be helpful to people who use or develop RoB tools. Guidance is necessary to support the design and implementation of future RoB tool evaluations.

The Impact of Artificial Intelligence Tools on Academic Writing Instruction in Higher Education: A Systematic Review

With the growth of Artificial Intelligence technologies, there is interest in studying their potential impact on university academic writing courses. This study examined whether AI tools are replacing these courses by exploring how they effectively replace traditional academic writing instruction and this shift’s potential benefits and drawbacks. The researcher reviewed existing literature on integrating AI tools into academic writing instruction. The findings provide insights to educators navigating the integration of Artificial Intelligence tools into writing curricula while maintaining instructional quality and academic integrity standards. By synthesizing the latest research, this study can inform decisions about the appropriate use of Artificial Intelligence in teaching essential writing skills. Increased use of Artificial Intelligence writing tools has sparked debate about their role in academic writing instruction. Universities like Stanford have updated policies around Artificial Intelligence tool usage and academic integrity. The University of California issued guidance acknowledging the prevalence of generative Artificial Intelligence on campuses. Middlebury College banned classroom use of ChatGPT over concerns it could impede critical thinking and writing skill development. Results show that while Artificial Intelligence helps with grammar and style, questions remain about its impact on creativity and critical thinking. However, Artificial Intelligence is not replacing university writing courses. These courses teach critical thinking, research, citation, argumentation, creativity, originality, and ethics, which Artificial Intelligence lacks. Academic writing courses offer a complete learning experience. Artificial Intelligence may improve academic writing but is unlikely to replace traditional courses soon. A balanced approach integrating Artificial Intelligence support while preserving core elements of academic writing education appears most effective for preparing students for diverse writing challenges.

Translating a motivational interviewing intervention for childhood cancer survivors into an eHealth tool: A user-centered design process.

Childhood cancer survivors have a higher risk of developing cardiomyopathy than members of the general population. Screening echocardiograms can facilitate early detection and treatment of cardiomyopathy. Furthermore, motivational interviewing can increase uptake of cardiac screening. However, such approaches are time- and resource-intensive, which limits their reach to the survivors who need them. We describe how we utilized a user-centered design process to translate an in-person motivational interviewing intervention into an eHealth tool to improve cardiac screening among childhood cancer survivors. We used an iterative, three-phase, user-centered design approach: (i) setting the stage (convening advisory boards and reviewing the original intervention), (ii) content programming and development (writing and programming intervention text and flow), and (iii) intervention testing (research team testing and cognitive interviews.) For cognitive interviews, participants were recruited via institutional participant registries and medical records. Data were analyzed using rapid qualitative analysis. During Phase 1, we identified survivor and provider advisors and outlined elements of the in-person intervention to change for the eHealth tool. During Phases 2 and 3, advisors recommended several modifications that guided the final intervention content and flow. Examples include: acknowledging potential hesitation or apprehension surrounding medical screenings, addressing barriers and facilitators to obtaining screening, and improving the tool's usability and appeal. In Phase 3, cognitive interview participants suggested additional refinements to the intervention language. This translation process shows that continued in-depth engagement of community advisors and iterative testing can improve the applicability of an eHealth to survivors' lived experiences and social contexts.

A Pioneer Tool to Reduce Restrictive Practices toward People with Intellectual and Developmental Disabilities.

Reducing restrictive practices toward individuals with intellectual and developmental disabilities is a globally recognized imperative and human rights priority. This paper presents a novel tool called LibRe for assessing and reducing restrictive practices. This tool involved an instrumental multistage design and collaboration between professionals, individuals with disabilities, family members, and experts from different fields. It addresses diverse restrictive practices in five key domains: physical or mechanical, chemical or pharmacological, structural, relational, and practices related to contexts and supports. It addresses practices that are pertinent to the Spanish context and that existing tools have not covered. Embedded as a step within an organizational approach, LibRe fosters organizational transformation and provides resources to achieve outcomes within reduction plans for restrictive practices. In total, 156 teams comprising 585 professionals, 64 people with disabilities, and 44 family members responded to the tool. In terms of evidence for internal structure validity, the oblique five-factor model exhibited an adequate fit through confirmatory factor analysis, along with satisfactory reliability indices, according to ordinal alpha and omega. Users positively appraised the tool's usefulness and identified its strengths and challenges. Although further research is needed, preliminary evidence frames LibRe as a useful resource for practice and research.

Computer Modeling Analysis of Electric Vehicle's Choice Behavior Considering Latent Variables

At present, there are few researches on the influence of psychological latent variables on the choice behavior of electric vehicles, and lack of consideration of individual heterogeneity. In this study, computer modeling was used to construct not only a traditional discrete choice model that takes into account individual heterogeneity, but also a hybrid choice model,which takes into account psychological latent variables are constructed to explore the mutual effects of observable personal attributes, vehicle attributes and difficult to directly observe psychological latent variables on consumers’ choice behavior of electric vehicles. The estimation results of hybrid choice model with psychological latent variables and the traditional discrete choice model without considering psychological latent variables are compared. The result show that perceived usefulness, perceived risk and purchasing attitude have a significant impact on consumers’ choice behavior of electric vehicles. Compared with traditional discrete choice model, the hybrid choice model, which takes into account psychological latent variables has significantly higher prediction accuracy and has better interpretation ability and fitting effect. The research results can provide theoretical support for further expanding the electric vehicle market and formulating relevant policieshe usage of the word Power quality in recent times acquired intensified interest due to the complex industrial processes. The usage of intelligent tools to improve power quality is increasing day by day, as assumption of present day power system as a linear model is unsatisfactory. This paper deals with analysis of Differential Evolution (DE), Hybrid Differential Evolution (HDE) and Variable Scaling Hybrid Differential Evolution for harmonic reduction in the source current with optimal tuning of PI controller gain values. Shunt Active power Filter is one of the better solution to suppress the source current harmonics which are induced into power system because of nonlinear loads. Current controller called HBCC is considered for gating operation of switches in Voltage Source Inverter. The Intelligent tuned PQ theory is used for reference current generation. The then obtained compensating currents are injected at point of common coupling for current disturbance mitigation. Simulations of MATLAB/SIMULINK environment of the present work shows the efficacy.