Complete Feedback Research Articles

A Guided Near-Peer Mentorship Program for Transitioning into Clinical Clerkships at a Regional Medical Campus

Background
 Transitioning from preclinical to clinical medical education is a significant milestone in medical training; however, it is associated with anxiety and uncertainty about adapting to a new work and learning environment. These feelings may be additionally heightened when students are also transitioning to a branch or regional campus for their clerkship training. A guided, near-peer mentorship program was designed at a regional medical campus in hopes of reducing anxiety associated with transitioning into clinical rotations, as well as teach clinical medical students how to effectively mentor a fellow student.
 Methods
 This curricular improvement program was developed and implemented at a regional campus of a US Midwestern medical school. A list of 14 topics for discussion was created from responses to reflection questions completed by students participating in the program. These topics were sorted into meeting guides that mentors could reference during three individual meetings with their mentee. Mentors attended a workshop prior to the start of the program to learn more about effective mentorship in medicine. Participants from the first two years of this program were asked to complete feedback surveys evaluating their experience in the program.
 Results
 Forty-one of 48 potential second-year students agreed to participate as mentees and 40 of 48 potential third-year students agreed to participate as mentors. Ninety-two percent of mentees agreed that participating in the program decreased their stress and anxiety about transitioning into clerkships and 96% reported they would recommend the program to other students. Among the mentors, 93% reported they would recommend the program to other students and 78% agreed that the mentorship skills they practiced during the program are useful in their professional and academic development.
 Discussion
 With the introduction of this guided, near-peer mentorship program, mentees reported feeling supported in their transition into clinical clerkships and mentors reported feeling prepared to effectively mentor a fellow student. Though such one-on-one programs can be somewhat time-intensive to establish and execute, the skills gained by mentors can serve them for the rest of their careers and the individualized advice given to mentees markedly decreases anxiety in a high-stress transition.

Choice-confirmation bias and gradual perseveration in human reinforcement learning.

Do we preferentially learn from outcomes that confirm our choices? In recent years, we investigated this question in a series of studies implementing increasingly complex behavioral protocols. The learning rates fitted in experiments featuring partial or complete feedback, as well as free and forced choices, were systematically found to be consistent with a choice-confirmation bias. One of the prominent behavioral consequences of the confirmatory learning rate pattern is choice hysteresis: that is, the tendency of repeating previous choices, despite contradictory evidence. However, choice-confirmatory pattern of learning rates may spuriously arise from not taking into consideration an explicit choice (gradual) perseveration term in the model. In the present study, we reanalyze data from four published papers (nine experiments; 363 subjects; 126,192 trials), originally included in the studies demonstrating or criticizing the choice-confirmation bias in human participants. We fitted two models: one featured valence-specific updates (i.e., different learning rates for confirmatory and disconfirmatory outcomes) and one additionally including gradual perseveration. Our analysis confirms that the inclusion of the gradual perseveration process in the model significantly reduces the estimated choice-confirmation bias. However, in all considered experiments, the choice-confirmation bias remains present at the meta-analytical level, and significantly different from zero in most experiments. Our results demonstrate that the choice-confirmation bias resists the inclusion of a gradual perseveration term, thus proving to be a robust feature of human reinforcement learning. We conclude by pointing to additional computational processes that may play an important role in estimating and interpreting the computational biases under scrutiny. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Helping the Helpers: Adaptation and Evaluation of Stress First Aid for Healthcare Workers in the Veterans Health Administration During the COVID-19 Pandemic.

Early interventions are needed to support the behavioral health of healthcare staff in the context of the COVID-19 pandemic. Stress First Aid (SFA) is a self-care and peer support model for reducing burnout and stress that is designed for use in high-stress occupations. We conducted a mixed-methods evaluation of an SFA program in the Veterans Health Administration (VHA). This brief, multi-session, didactic program was adapted for hospital workgroups. Program attendees completed a survey assessing implementation outcomes, burnout, stress, mood, and SFA skills at the beginning (N = 246) and end (n = 94) of the SFA program and a subgroup (n = 11) completed qualitative feedback interviews. Program acceptability, appropriateness, and feasibility were rated highly. From pre- to post-SFA, the impact of the pandemic on stress and anxiety, as well as proficiency in supporting peers increased. Qualitative findings suggest the program provided a shared language to discuss stress, normalized stress reactions, met a need for stress management tools, and helped staff feel valued, empowered, connected with each other. Staff reported being more aware of their stress, but SFA was insufficient to address many of the systemic sources of burnout and stress. While the SFA program was well received, the impact of brief programs is likely to be modest when implemented in the middle of an ongoing pandemic and when burnout arises from chiefly from systemic sources. Lessons learned during the program implementation that may guide future efforts are discussed.

Evidence-Based Practice (EBP) evaluation rubric for MSN students

A rubric is a measurement tool used in assessment that recognizes the criteria for completing the tasks and provides standards for each level of performance. The use of rubrics enables educators to formulate standards and explicit grading for the students. Moreover, it provides clear guidelines to the learners regarding task expectations. Improvement in nursing research has made implementing evidence-based practice feasible for nursing students. The adoption of evidence-based care process is relatively slow in the context of nursing and there is a gap in implementing evidencebased practice in a clinical setting. The culture of evidence-based care can be adopted by enhancing the student nurses' knowledge, skills, and attitude (DiCenso et al., 1998). Educators need to formulate their teaching and assessment methodologies in a way to compel their students for achieving cognitive thinking. The higher level of competencies may be inculcated in students through involving and assessing them in evidence-based, rationalized methodologies to enhance their level of critical thinking, skills, independence, and decision-making in the provision of care. The guidelines developed for the assessment of nursing students' Evidence-Based Practice need further modification with clear measurement and level of quality for reaching each level of performance. A composite analytic rubric is suggested to use when educators assess complex skills and clinical performance of nursing students. It provides complete feedback and reduces subjectivity to a great extent due to its comprehensive dimensions. It provides a common basis of judgment, and justification in feedback and enables the teacher to make a fair, valid, and reliable judgment. Moreover, it helps students identify their strengths and weaknesses and formulate their efforts for improvement.

Three years of quality assurance data assessing the performance of over 4000 grant peer review contributions to the Canadian Institutes of Health Research Project Grant Competition

The Canadian Institutes of Health Research (CIHR) commenced a Quality Assurance Program in 2019 to monitor the quality of peer review in its Project Grant Competition Peer Review Committees. Our primary aim was to describe the performance of CIHR grant peer reviewers, based on the assessments made by CIHR peer review leaders during the first 3 years of the Research Quality Assurance Program. All Peer Review Committee Chairs and (or) Scientific Officers who led peer review for CIHR in 2019, 2020, and 2021 completed Reviewer Quality Feedback forms immediately following Peer Review Committee meetings. The form assessed Performance, Future potential, Review quality, Participation, and Responsiveness. We summarised and descriptively synthesised data from assessments conducted after each of the four grant competitions. The performance of peer reviewers on 4438 occasions was rated by Chairs and Scientific Officers. Approximately one in three peer reviewers submitted outstanding reviews or discussed additional applications and one in 10 demonstrated potential as a future Peer Review Committee leader. At most, one in 20 peer reviewers was considered to have not performed adequately with respect to review quality, participation, or responsiveness. There is a need for more research on the processes involved in allocating research grant funding.

Participant experience in a longitudinal online research registry: Associations between ethnocultural identity, educational attainment, and participant feedback in the Brain Health Registry

AbstractBackgroundResearch registries focused on brain diseases, such as Alzheimer’s disease and related dementias (ADRD), have been developed to accelerate clinical study recruitment. Completion of registry components can affect the representativeness of registry populations and data, especially where retention is critical. This study aims to provide insights for online research and retention by studying participants’ perceptions of the Brain Health Registry (BHR), with a focus on those from different ethnocultural and socioeconomic backgrounds.MethodBHR is a public online registry for recruitment and longitudinal assessment focused on cognitive aging and ADRD research. Participants can provide feedback to the study team about their overall experience at any time using a questionnaire and are asked to complete feedback questionnaires after completing the Cogstate Brief Battery (CBB) (Table 1). Multivariable ordinal logistic regression estimated associations between sociodemographic characteristics (ethnocultural identity and education attainment) and feedback responses. All analyses covaried for age and gender.ResultOf all participants (N = 89,673), 5,469 (6.1%) provided feedback about their overall BHR experience and 14,676 (16.4%) provided feedback about CBB (Table 2). See Table 3 for associations between sociodemographic characteristics and feedback responses. Identifying as Latino was associated with a poorer experience with the cognitive assessment. Identifying as Latino or non‐White was associated with perceiving the cognitive assessment instructions as less clear and rating that additional help for cognitive assessment instructions would be useful. Higher educational attainment was associated with perceiving BHR site as easier to use and the instructions as clearer, as well as rating additional help for cognitive assessment instructions as less useful.ConclusionOur findings highlight the need to improve and/or tailor online cognitive assessment design and instructions to better suit the needs of diverse ethnocultural and educational populations. More research is needed to deepen insight into improvements in cognitive assessment design to facilitate engagement and retention of diverse populations.

Fully distributed event-triggered output feedback control for linear multi-agent systems with a derivable leader under directed graphs

This article studies the design method of fully distributed event-triggered output feedback protocol for linear multi-agent systems with a derivable leader under directed graphs. The research on such problems in the existing reference needs complete state feedback and the state variable of the adaptive law used in the literature controller is monotonic and non decreasing, which may make the control input exceed the actual saturation value, thus affecting the practical application. How to design a completely distributed event-triggered adaptive output feedback protocols for multi-agent systems with a derivable leader on directed graphs is an open issue. In order to overcome the difficulty of designing the controller without complete state information, we design the event-triggered output feedback protocol, and with the help of σ-modification techniques, ensure the boundedness of the adaptive law in proposed protocol. The conditions to ensure the realization of the leader–follower consensus and exclude Zeno behavior are given. Furthermore, the control protocol is fully distributed and uses neighbor information only when the event trigger conditions are satisfied. Finally, the availability of the proposed protocol is illustrated by simulation examples.

Research on Campus Food Safety Traceability System Based on BT Technology

This paper takes BT technology as a carrier and aims to establish a campus food traceability system, taking Qingdao University of Technology as an example to start the research and gradually expand to other universities. The BT technology is applied to the whole process of food sales, including the source of ingredients, food production, food sales, and food prosecution, and the information collected by the BT technology chain is put into the Campus Food Safety App, which not only provides detailed information on the whole process of food purchase from the purchase of ingredients to the purchase of campus personnel, but also provides a platform for students to report food on campus, solving the problem from the root, and making full use of the superiority of the Internet. The app not only provides a platform for students to report food on campus, but also solves the problem at the root, making full use of the superiority of the Internet to build a food traceability platform that reflects the true and high technology amount to ensure campus food safety, forming a complete feedback mechanism and becoming the last link of the campus food safety traceability system.

Internet of Things Information System and Clothing Computer Renderings Digital Art

The Internet of Things (IoT) is developing rapidly and is integrated into all aspects of life. Clothing is an indispensable part of meeting the basic needs of the human body, and its traditional functions include warmth, health care, decoration, and beauty. While as a special type of clothing that integrates multidisciplinary technology, smart clothing has a wider scope of action. With the update and iteration of science and technology, many technologies that originally belonged to nonclothing disciplines have also been applied to the clothing field. Accordingly, for the special clothing category of smart clothing based on embedded system, a set of design process that can be used for this category of smart clothing was proposed. Using this design process, an intelligent fire suit that can be used to protect the personal safety of firefighters and assist firefighters to cooperate was designed and implemented. Starting from the daily working environment and working characteristics of firefighters, this firefighting obedience analyzed the design points from the perspectives of clothing comfort, warning, toxic and harmful gas monitoring, and firefighters’ cooperation. After testing, the test results of the outer layer fabric, waterproof and moisture-permeable layer fabric, and thermal insulation and comfort layer fabric of the fire suit all met the corresponding national standards; the monitoring sensitivity of harmful gases was high; it could achieve a “good” warning effect in a dark environment. Compared with ordinary firefighting suits, it was more comfortable under the subjective and objective test and scored 0.669 higher under the seven-point scale; its interactive performance met the actual needs. The clothing has complete functions and a complete feedback mechanism, which has a positive effect on ensuring the personal safety of firefighters.

The critical role of the orbitofrontal cortex for regret in an economic decision-making task.

Regret affects decision-making behavior, which is mediated by a cognitive process known as counterfactual thinking in economic science. Several studies indicate that orbitofrontal cortex (OFC) plays a crucial role in decision-making behavior. However, the neural correlates of regret trait and the function of the OFC in decision-making remain unclear. In this study, we employed a typical monetary decision-making task, a modified 'Wheel of Fortune gamble' paradigm, to investigate decision-making behavior and its neural mechanism. We combined voxel-based morphometry (VBM) and task-evoked functional magnetic resonance imaging (fMRI) analyses to explore the neural substrates of regret trait. VBM analyses revealed that individual Regret Scale Score was negatively associated with the gray-matter volume (GMV) in the frontal and temporal areas, including the bilateral OFC. These results indicate that individuals with high regret trait have smaller GMV in these areas. Moreover, we found stronger task-evoked activation of the left OFC in high regret trait individuals during the decision-maker's choice (choose conditions) phase, whereas we did not find this relationship in computer-selected's (follow conditions) choice phase. Using generalized psychophysiological interactions (PPI) analysis, we further found that the functional connectivity of the left OFC to right inferior frontal gyrus and left cerebellum was stronger in the complete feedback choose condition (under regret theoretical framework) than partial feedback choose condition (under disappointment theoretical framework). These findings verify the critical role of the OFC in the decision-making, more importantly, provide novel insights into the morphological and functional substrates of individual regret trait.

The card guessing game: A generating function approach

Consider a card guessing game with complete feedback in which a deck of n cards ordered 1,…,n is riffle-shuffled once. With the goal to maximize the number of correct guesses, a player guesses cards from the top of the deck one at a time under the optimal strategy until no cards remain. We provide an expression for the expected number of correct guesses with arbitrary number of terms, an accuracy improvement over the results of Liu (2021). In addition, using generating functions, we give a unified framework for systematically calculating higher-order moments. Although the extension of the framework to k≥2 shuffles is not immediately straightforward, we are able to settle a long-standing McGrath's conjectured optimal strategy described in Bayer and Diaconis (1992) by showing that the optimal guessing strategy for k=1 riffle shuffle does not necessarily apply to k≥2 shuffles.

Automatic detection of the mental state in responses towards relaxation

Nowadays, considering society’s highly demanding lifestyles, it is important to consider the usefulness of relaxation from the perspective of both psychology and clinical practice. The response towards relaxation (RResp) is a mind-body interaction that relaxes the organism or compensates for the physiological effects caused by stress. This work aims to automatically detect the different mental states (relaxation, rest and stress) in which RResps may occur so that complete feedback about the quality of the relaxation can be given to the subject itself, the psychologist or the doctor. To this end, an experiment was conducted to induce both states of stress and relaxation in a sample of 20 university students (average age of 25.76pm 3.7 years old). The electrocardiographic and electrodermal activity signals collected from the participants produced a dataset with 1641 episodes or instances in which the previously mentioned mental states take place. This data was used to extract up to 50 features and train several supervised learning algorithms (rule-based, trees, probabilistic, ensemble classifiers, etc.) using and not using feature selection techniques. Besides, the authors synthesised the cardiac activity information into a single new feature and discretised it down to three levels. The experimentation revealed which features were most discriminating, reaching a classification average accuracy of up to 94.01pm 1.73% with the 6 most relevant features for the own-collected dataset. Finally, being restrictive, the same solution/subspace was tested with a dataset referenced in the bibliography (WESAD) and scored an average accuracy of 90.36pm 1.62%.

Improving the Response Rate of Teaching Feedback by Introducing Exam Practice Questions – a Quality Improvement Project

AimsAim: The quality improvement (QI) project aimed to improve the response rate of teaching feedback from medical students at Queen Mary University of London (QMUL). Background information: Universities and health care settings use students' feedback to improve the teaching and other services. The feedback is a valuable source to evaluate a service delivery and improvement. Following the COVID-19 pandemic a large majority of teaching switched to being held online. Feedback plays an important role in evaluating these new methods of teaching. However, response rates were noted to be low. This QI project aims to improve the response rate from students.MethodsThe project was registered on LifeQI and carried out during the psychiatric teaching for 4th year medical students at QMUL. The team emphasized the importance of feedback to students and produced online feedback forms which are mobile-friendly and concise. These were provided to students immediately after lectures and in an email reminder. As a change idea, five multiple choice practice questions from the topics of the day were included as a follow-on activity from the feedback form, with the expectation that this would motivate the students to complete the feedback. The response rate was calculated as a percentage (number of responses/number of attendees x 100%) and compared before and after the change was introduced using the independent t-test.ResultsIntroducing practice MCQs at the end of the feedback form resulted in a significant improvement: the response rate increased from 22.3% to 50%, more than doubled. The independent t-test found a significant increase in the number of feedback forms returned from the original rates (M = 13.8, SE = 3.0) to rates after practice questions were introduced into feedback (M = 30.6, SE = 1.7), t= -4.9 p = 0.001.ConclusionStudents’ motivation to complete feedback plays a major role in the response rate of medical students’ feedback at QMUL. Adding five MCQs on the topics of the day to the feedback form has significantly increased the response rate of 4th year medical students at QMUL. This project was limited to 4th year medical students who received online psychiatric lectures. It is important to try other change ideas in future in order to compare the outcomes.

The use of white lupine in complete feed for trout

The article presents the material on the most up-to-date, the global problem of protein deficiency in complete feedback for fish. One of the ways to solve this problem may be the use of white lupine (Lupinus Albus) in the structures of feed recipes. An important condition for the successful development of fish farming and the implementation of planned products for the production of products, to ensure food safety, occupy feeding issues. The decision of this issue puts a number of tasks to ensure feedback, rational methods of production, on the basis of advanced scientific achievements that contribute to the technological, economic development of the industry. Therefore, in experienced formulations of complete feed, the main task was to replace the white most expensive protein component into Lupine, that is, fish flour. In the first experienced recipe, the amount of lupine natives was 10%, which made it possible to reduce the fisherous flour content by 7%. The second experimental recipe in its structure contained lupine white without a shell in an amount of 22%, this made it possible to reduce the content of fish flour by 14%. The third experienced rechart contained Lupine without a shell of 25%, which made it possible to reduce the content of fish flour by 19%. Consequently, the use of white lupine in the formulations of complete feed, makes it possible to improve their nutritional value. And the use of lupine without a shell makes it possible to replace high-fingered animal feed in greater volume.

Implicit Counterfactual Effect in Partial Feedback Reinforcement Learning: Behavioral and Modeling Approach.

Context remarkably affects learning behavior by adjusting option values according to the distribution of available options. Displaying counterfactual outcomes, the outcomes of the unchosen option alongside the chosen one (i.e., providing complete feedback), would increase the contextual effect by inducing participants to compare the two outcomes during learning. However, when the context only consists of the juxtaposition of several options and there is no such explicit counterfactual factor (i.e., only partial feedback is provided), it is not clear whether and how the contextual effect emerges. In this research, we employ Partial and Complete feedback paradigms in which options are associated with different reward distributions. Our modeling analysis shows that the model that uses the outcome of the chosen option for updating the values of both chosen and unchosen options in opposing directions can better account for the behavioral data. This is also in line with the diffusive effect of dopamine on the striatum. Furthermore, our data show that the contextual effect is not limited to probabilistic rewards, but also extends to magnitude rewards. These results suggest that by extending the counterfactual concept to include the effect of the chosen outcome on the unchosen option, we can better explain why there is a contextual effect in situations in which there is no extra information about the unchosen outcome.

On the Binary Adder Channel With Complete Feedback, With an Application to Quantitative Group Testing

We determine the exact value of the optimal symmetric rate point (r, r) in the Dueck zero-error capacity region of the binary adder channel with complete feedback. We proved that the average zero-error capacity r = h(1/2-δ) ≈ 0.78974, where h(∙) is the binary entropy function and δ = 1/(2 log2(2 + √3)). Our motivation is a problem in quantitative group testing. Given a set of n elements two of which are defective, the quantitative group testing problem asks for the identification of these two defectives through a series of tests. Each test gives the number of defectives contained in the tested subset, and the outcomes of previous tests are assumed known at the time of designing the current test. We establish that the minimum number of tests is asymptotic to (log2 n)/r as n → ∞.

Interactions between nuclear receptors glucocorticoid receptor α and peroxisome proliferator–activated receptor α form a negative feedback loop

Both nuclear receptors glucocorticoid receptor α (GRα) and peroxisome proliferator-activated receptor α (PPARα) are involved in energy and lipid metabolism, and possess anti-inflammation effects. Previous studies indicate that a regulatory loop may exist between them. In vivo and in vitro studies showed that glucocorticoids stimulate hepatic PPARα expression via GRα at the transcriptional level. This stimulation of PPARα by GRα has physiological relevance and PPARα is involved in many glucocorticoid-induced pathophysiological processes, including gluconeogenesis and ketogenesis during fasting, insulin resistance, hypertension and anti-inflammatory effects. PPARα also synergizes with GRα to promote erythroid progenitor self-renewal. As the feedback, PPARα inhibits glucocorticoid actions at pre-receptor and receptor levels. PPARα decreases glucocorticoid production through inhibiting the expression and activity of type-1 11β-hydroxysteroid dehydrogenase, which converts inactive glucocorticoids to active glucocorticoids at local tissues, and also down-regulates hepatic GRα expression, thus forming a complete and negative feedback loop. This negative feedback loop sheds light on prospective multi-drug therapeutic treatments in inflammatory diseases through a combination of glucocorticoids and PPARα agonists. This combination may potentially enhance the anti-inflammatory effects while alleviating side effects on glucose and lipid metabolism due to GRα activation. More investigations are needed to clarify the underlying mechanism and the relevant physiological or pathological significance of this regulatory loop.

Review of Real-Time Biomechanical Feedback Systems in Sport and Rehabilitation.

Real-time biomechanical feedback (BMF) is a relatively new area of research. The potential of using advanced technology to improve motion skills in sport and accelerate physical rehabilitation has been demonstrated in a number of studies. This paper provides a literature review of BMF systems in sports and rehabilitation. Our motivation was to examine the history of the field to capture its evolution over time, particularly how technologies are used and implemented in BMF systems, and to identify the most recent studies showing novel solutions and remarkable implementations. We searched for papers in three research databases: Scopus, Web of Science, and PubMed. The initial search yielded 1167 unique papers. After a rigorous and challenging exclusion process, 144 papers were eventually included in this report. We focused on papers describing applications and systems that implement a complete real-time feedback loop, which must include the use of sensors, real-time processing, and concurrent feedback. A number of research questions were raised, and the papers were studied and evaluated accordingly. We identified different types of physical activities, sensors, modalities, actuators, communications, settings and end users. A subset of the included papers, showing the most perspectives, was reviewed in depth to highlight and present their innovative research approaches and techniques. Real-time BMF has great potential in many areas. In recent years, sensors have been the main focus of these studies, but new types of processing devices, methods, and algorithms, actuators, and communication technologies and protocols will be explored in more depth in the future. This paper presents a broad insight into the field of BMF.

Intelligent Classroom Teaching Assessment System Based on Deep Learning Model Face Recognition Technology

AI + education technology has had a wide and far-reaching impact on the education industry, which has been applied to classroom teaching in order to achieve real-time monitoring of the classroom and complete closed-loop feedback on teaching. In this paper, AI face recognition based on deep learning is improved and optimized through key points such as image data acquisition, localization, calibration, comparison, and deepening data models, so that the detection can be completed accurately and quickly even under the condition of light and external object interference, maximizing the accuracy and efficiency of face recognition technology under the influence of the objective environment. The traditional manual operation in classroom teaching is automated and intelligent throughout, reducing the workload of teachers and related personnel while further ensuring the scientific organization and management of classroom teaching. While making classroom teaching and learning life safer, more convenient, and more efficient, it also provides a favourable reference for the wide application and development of facial recognition technology.

Design and evaluation of multifunctional protective clothing for tunnel workers

By examining the requirements of tunnel workers, multifunctional tunnel protective clothing was proposed in this study. The traditional tunnel protective clothing was redesigned from the perspective of improving clothing structure and fabric. A safe and protective clothing system, incorporating a harmful gas detection module, position monitoring module and data transmission module, was developed. Objective evaluation tests were carried out to verify the effectiveness of the proposed protective clothing. During the medium-intensity exercise phase, the average skin temperature and humidity of the participants who wore the new protective clothing were 1.0725 °C and 2.6% lower, respectively, than those who wore the conventional protective clothing (p < 0.05). Furthermore, the new protective clothing system exhibited a highly sensitive and complete feedback mechanism. The positioning error could be controlled within ±10 cm, when the horizontal spacing distance of the base station was set to 200 m.