Comparative analysis of the effects of the computer-based and paper-based trail making tests on oxygenation in the prefrontal cortex.

The trail making test (TMT) is a commonly used tool for evaluating executive functions, and the activation of cerebral oxygenation in the prefrontal cortex (PFC) during the test can reflect the participation of executive function. This study aimed to compare the differences in cerebral oxygenation in the PFC between the computer- and paper-based versions of the TMT and provide a theoretical basis for the optimization and clinical application of the computer-based version. A total of 32 healthy adult participants completed the computer- and paper-based TMT Types A and B. Cerebral oxygenation changes in the PFC were monitored during the experiment using near-infrared spectroscopy. Moreover, average changes in oxyhemoglobin (Δoxy-Hb) levels at the baseline and during activation periods in different types of testing were compared and analyzed. The number of correct connections in the computer-based version Type B was less than that in the paper-based version Type B (p < .001). The task time of the computer-based version was longer than that of the paper-based version (p < .001). The B/A ratio of the number of correct connections in the computer-based version was lower than that in the paper-based version (p < .001). The Δoxy-Hb in the PFC of the paper-based version was higher than that of the computer-based version (p < .001). Significant differences in oxygenation in the PFC were observed between the paper- and computer-based versions of TMT. After further improvement and correction in the subsequent development of the computer-based TMT, and taking into account the psychological feelings and preferences of the participants when performing different versions of the TMTs, the computer-based TMT is expected to play a good auxiliary role in clinical evaluation.

External post-mortem examination in virtual reality-scalability of a monocentric application.

Conducting external post-mortem examinations is an essential skill required of physicians in various countries, regardless of their specialization. However, the quality of these examinations has been a subject of continuous debates, and notable errors were reviled. In response to these shortcomings, a virtual reality (VR) application was developed at Halle's medical department in Germany, focusing on the scene of discovery and the completion of death certificates. The initial trial of this VR application in 2020 involved 39 students and 15 early-career professionals. Based on the feedback, the application underwent improvements and was subsequently introduced to the medical department in Dresden, Germany, in 2022. Its primary objective was to showcase the VR training's adaptability and scalability across various educational structures and levels of medical expertise. Out of 73 students who participated, 63 completed the evaluation process. 93.1% (n = 58) of the evaluators reported increased confidence in conducting external post-mortem examinations, and 96.8% (n = 61) felt more assured in filling out death certificates, crediting this progress to the VR training. Additionally, 98.4% (n = 62) believed that repeating forensic medical aspects in their coursework was crucial, and 96.8% (n = 61) viewed the VR examination as a valuable addition to their academic program. Despite these positive responses, 91.6% (n = 55) of participants maintained that training with real corpses remains irreplaceable due to the insufficiency of haptic feedback in VR. Nevertheless, the potential for enhancing the VR content and expanding the training to additional locations or related disciplines warrants further exploration.

The effect of computerized cognitive training and transcranial direct current stimulation on working memory among post-stroke individuals: a systematic review with meta-analysis and meta-regression.

BACKGROUND: Working memory (WM) impairment is a common phenomenon after stroke; however, its management in rehabilitation is less researched. This systematic review and meta-analysis aimed to provide a quantitative synthesis of the impact of computerised cognitive training (CCT) and transcranial direct current stimulation (tDCS) on WM span in post-stroke individuals. METHODS: The literature search in PubMed, Embase, Scopus, and Cochrane Library focused on randomized controlled trials testing the effect of CCT and tDCS on treated stroke patients as compared to untreated controls. Neuropsychological instruments such as Digit Span Forward/Backward and Visual Span Forward Tests defined the outcome of WM span. After extracting study characteristics and quality assessment using the Cochrane Risk of Bias Tool, we conducted a meta-analysis and meta-regression using standardised mean differences. RESULTS: The search yielded 4142 articles, nine of which (N = 461) fulfilled the inclusion criteria. In the case of CCT, we found significant improvement in Digit Span Backward Test (Z = 2.65, P = 0.008; 95% CI [0.10, 0.67]) and Visual Span Forward Test performance (Z = 3.05, P = 0.002; 95% CI [0.15, 0.69]), while for tDCS, we could not find a sufficient number of studies for the analysis. Furthermore, no significant moderating factor was found in the meta-regression. CONCLUSIONS: In conclusion, CCT appears to be a suitable choice to enhance WM span performance after stroke. However, further research is needed to investigate the effect of tDCS due to the limited number of studies. TRIAL REGISTRATION: The meta-analysis was conducted according to PRISMA (Preferred Reporting of Systematic Reviews and Meta-Analyses) standards with a PROSPERO registration protocol (ID: CRD42023387182).

Systematic review of the effectiveness of innovative, gamified interventions for cognitive training in paediatric acquired brain injury.

Effectiveness of innovative, gamified interventions (i.e., Augmented Reality, Computer-Based Cognitive Retraining [CBCR], and Virtual Reality [VR] in conjunction with a Serious Game) for cognitive training in paediatric ABI was evaluated. Studies were identified on PsycINFO, PubMed and Scopus; last searched 4 January 2022. Eligibility criteria were participants diagnosed with ABI and aged ≤ 18 years, experimental intervention to train cognition, cognition assessed pre- and post-intervention at: (1) The level of function, or (2) The level of activity, and written in English. ROB 2 and ROBINS-I were utilised to assess risk of bias. Extracted study characteristics were methods, participants, interventions, outcomes, and results. Seven studies were included, comprising six CBCR studies and one VR study, with 182 participants. Following CBCR: (1) Improvements were observed in several cognitive functions, but there was inconsistent evidence; (2) Improvements were reported in attention and executive functions (EF) at home and at school. Following VR: (1) Improvements were observed in attention and EF; (2) Not evaluated. Due to the small number of included studies with (relatively) small and heterogeneous samples, only a cautious interpretation of the evidence was provided. There is a need for carefully designed studies with more attention to inter-individual differences and generalisation to daily life.

Simultaneous Three-Degrees-of-Freedom Prosthetic Control Based on Linear Regression and Closed-Loop Training Protocol.

Machine learning-based controllers of prostheses using electromyographic signals have become very popular in the last decade. The regression approach allows a simultaneous and proportional control of the intended movement in a more natural way than the classification approach, where the number of movements is discrete by definition. However, it is not common to find regression-based controllers working for more than two degrees of freedom at the same time. In this paper, we present the application of the adaptive linear regressor in a relatively low-dimensional feature space with only eight sensors to the problem of a simultaneous and proportional control of three degrees of freedom (left-right, up-down and open-close hand movements). We show that a key element usually overlooked in the learning process of the regressor is the training paradigm. We propose a closed-loop procedure, where the human learns how to improve the quality of the generated EMG signals, helping also to obtain a better controller. We apply it to 10 healthy and 3 limb-deficient subjects. Results show that the combination of the multidimensional targets and the open-loop training protocol significantly improve the performance, increasing the average completion rate from 53% to 65% for the most complicated case of simultaneously controlling the three degrees of freedom.

Improving the Concrete Crack Detection Process via a Hybrid Visual Transformer Algorithm.

Inspections of concrete bridges across the United States represent a significant commitment of resources, given their biannual mandate for many structures. With a notable number of aging bridges, there is an imperative need to enhance the efficiency of these inspections. This study harnessed the power of computer vision to streamline the inspection process. Our experiment examined the efficacy of a state-of-the-art Visual Transformer (ViT) model combined with distinct image enhancement detector algorithms. We benchmarked against a deep learning Convolutional Neural Network (CNN) model. These models were applied to over 20,000 high-quality images from the Concrete Images for Classification dataset. Traditional crack detection methods often fall short due to their heavy reliance on time and resources. This research pioneers bridge inspection by integrating ViT with diverse image enhancement detectors, significantly improving concrete crack detection accuracy. Notably, a custom-built CNN achieves over 99% accuracy with substantially lower training time than ViT, making it an efficient solution for enhancing safety and resource conservation in infrastructure management. These advancements enhance safety by enabling reliable detection and timely maintenance, but they also align with Industry 4.0 objectives, automating manual inspections, reducing costs, and advancing technological integration in public infrastructure management.

Effectiveness of computerised decision aids for patients with chronic diseases in shared decision-making: A systematic review and meta-analysis.

AIMS: To synthesise the composition and effectiveness of computer-based patient decision aid (PDAs) in interventions for patients with chronic diseases. DESIGN: A systematic review with meta-analysis. METHODS: Five databases were searched, and only randomised controlled trials (RCTs)were included. This review was conducted with the PRISMA guidelines. The JBI Appraisal Tools for randomised trials were used to assess the risk of bias. We used the random-effects model to conduct meta-analyses. Evidence from RCTs was synthesised using standardised mean differences or mean differences. The GRADE system was employed to assess the certainty of evidence and recommendations. This study was registered on PROSPERO (number: CRD42022369340). DATA SOURCES: PubMed, Embase, Web of Science, CINAHL and Cochrane Library were searched for studies published before October 2022. RESULTS: The review included 22 studies, and most computer-based PDAs reported information on the disease, treatment options, pros and cons and risk comparison and value clarification. The use of computer-based PDAs showed a significant effect on decision conflict and knowledge, but not on decision regret, satisfaction, self-efficacy, anxiety and quality of life. The overall GRADE certainty of evidence was low. CONCLUSION: Although the quality of evidence was low, however, using computer-based PDAs could reduce decision conflict and enhance knowledge when making medical decisions. More research is needed to support the contention above. RELEVANCE TO CLINICAL PRACTICE: Computer-based PDAs could assist health-care providers and patients in the shared decision-making process and improving the quality of decision-making. REPORTING METHOD: This study adhered to PRISMA guidelines. NO PATIENT OR PUBLIC CONTRIBUTION.

Current perspectives and difficulties in the design of acaricides and repellents from plant-derived compounds for tick control.

Ticks and tick-borne diseases have gained increasing attention in recent years due to their impact on public health and significant losses in livestock production. The use of synthetic compounds for tick control is becoming problematic, mainly due to the resistance to commercially available products as well as their toxicity. Therefore, new alternative control methods are required. For this purpose, plant-derived extracts may be considered as effective repellents and/or acaricides. The present literature review focuses on studies evaluating the acaricidal and repellent activity of plant-derived extracts and plant secondary metabolites. We also noted recent advances in protein-ligand-docking simulation to examine the possible toxic effect of natural chemical compounds on ticks. In conclusion, plant-derived repellents/acaricides can be effective against ticks, especially in rural areas and livestock farms.

The effects of simulation-based education on undergraduate nursing students' competences: a multicenter randomized controlled trial.

BACKGROUND: Education in nursing has noticed a positive effect of simulation-based education. There are many studies available on the effects of simulation-based education, but most of those involve a single institution, nonrandomized controlled trials, small sample sizes and subjective evaluations of the effects. The purpose of this multicenter randomized controlled trial was to evaluate the effects of high-fidelity simulation, computer-based simulation, high-fidelity simulation combined with computer-based simulation, and case study on undergraduate nursing students. METHODS: A total of 270 nursing students were recruited from five universities in China. Participants were randomly divided into four groups at each institution: the high-fidelity simulation group, the computer-based simulation group, the high-fidelity simulation combined with computer-based simulation group, and the case study group. Finally, 239 participants completed the intervention and evaluation, with 58, 67, 57, and 57 participants in each group. The data were collected at three stages: before the intervention, immediately after the intervention, and three months after the intervention. RESULTS: The demographic data and baseline evaluation indices did not significantly differ among the four groups. A statistically significant difference was not observed between the four methods for improving knowledge, interprofessional collaboration, critical thinking, caring, or interest in learning. While skill improvement differed significantly among the different groups after the intervention (p = 0.020), after three months, no difference was observed (p = 0.139). The improvement in skill in the computer-based simulation group was significantly lower at the end of the intervention than that in the high-fidelity simulation group (p = 0.048) or the high-fidelity simulation combined with computer-based simulation group (p = 0.020). CONCLUSIONS: Nursing students benefit equally from four methods in cultivating their knowledge, interprofessional collaboration, critical thinking, caring, and interest in learning both immediately and over time. High-fidelity simulation and high-fidelity simulation combined with computer-based simulation improve skill more effectively than computer-based simulation in the short term. Nursing educators can select the most suitable teaching method to achieve the intended learning outcomes depending on the specific circumstances. TRIAL REGISTRATION: This clinical trial was registered at the Chinese Clinical Trial Registry (clinical trial number: ChiCTR2400084880, date of the registration: 27/05/2024).

Physical Chemistry Lab for Data Analysis of COVID-19 Spreading Kinetics in Different Countries.

The COVID-19 pandemic has passed. It gives us a real-world example of kinetic data analysis practice for our undergraduate physical chemistry laboratory class. It is a great example to connect this seemingly very different problem to the kinetic theories for chemical reactions that the students have learned in the lecture class. At the beginning of the spring 2023 semester, we obtained COVID-19 kinetic data from the "Our World in Data" database, which summarizes the World Health Organization (WHO) data reported from different countries. We analyzed the effective spreading kinetics based on the susceptible-infectious-recovered-vaccinated (SIR-V) model. We then compared the effective rate constants represented by the real-time reproduction numbers ( R t ) underlining the reported data for these countries and discussed the results and the limitations of the model with the students.

Artificial Intelligence Applications in Hepatology.

Over the past 2 decades, the field of hepatology has witnessed major developments in diagnostic tools, prognostic models, and treatment options making it one of the most complex medical subspecialties. Through artificial intelligence (AI) and machine learning, computers are now able to learn from complex and diverse clinical datasets to solve real-world medical problems with performance that surpasses that of physicians in certain areas. AI algorithms are currently being implemented in liver imaging, interpretation of liver histopathology, noninvasive tests, prediction models, and more. In this review, we provide a summary of the state of AI in hepatology and discuss current challenges for large-scale implementation including some ethical aspects. We emphasize to the readers that most AI-based algorithms that are discussed in this review are still considered in early development and their utility and impact on patient outcomes still need to be assessed in future large-scale and inclusive studies. Our vision is that the use of AI in hepatology will enhance physician performance, decrease the burden and time spent on documentation, and reestablish the personalized patient-physician relationship that is of utmost importance for obtaining good outcomes.

Adventure Legal Medicine: a free online serious game for supplementary use in undergraduate medical education.

Serious games (computer-based learning games) are increasingly used in medical education at various levels, as user access is independent of location and time and promotes non-linear learning. In legal medicine, interactive digital media are still scarce. The freely accessible online serious game "Adventure Legal Medicine" was developed as part of the "Hamburg Open Online University". The goal was to teach the basics of forensic casework in a point-and-click adventure setting consisting of five cases. During development, 40 medical students were asked to evaluate the game anonymously. The System Usability Scale (SUS) resulted in a mean score of 86.7 (SD 8.3), which corresponds to above-average usability. Further specific evaluations revealed a good to very good rating of the game with no differences in terms of gender (p = 0.214), first-year versus advanced students (p = 0.393) and students who never/rarely or sometimes/often played computer games (p = 0.780). Since there are only a few digital media so far that allow curricular integration into undergraduate teaching in legal medicine, this serious game represents a possibility to integrate digital media into both face-to-face teaching and distance learning and to use it as a supplement to the medical school's own teaching offer, encouraging users to actively engage with the subject.

A Collaborative-Care Telephone-Based Intervention for Depression, Anxiety, and at-Risk Drinking in Primary Care: The PARTNERs Randomized Clinical Trial.

BACKGROUND: Collaborative care (CC) could improve outcomes in primary care patients with common mental conditions. We assessed the effectiveness of a transdiagnostic model of telephone-based CC (tCC) delivered by lay providers to primary care patients with depression, anxiety, or at-risk drinking. METHODS: PARTNERS was a pragmatic trial in 502 primary care adults presenting with depressive symptoms, anxiety symptoms, or at-risk drinking randomized to (1) usual care by primary care providers (PCPs) enhanced with the results of computer-assisted telephone-based assessments (at baseline and 4, 8, and 12 months later) (enhanced usual care [eUC]) or (2) tCC consisting of eUC plus frequent telephone coaching and psychoeducation provided by mental health technicians who also communicated to the PCP recommendations from a psychiatrist for evidence-based pharmacotherapy, psychotherapy, or, when indicated, referrals to mental health services. The primary analysis compared the change on the 9-item Patient Health Questionnaire (PHQ-9) in participants presenting with depression (n = 366) randomized to tCC versus eUC. Secondary analyses compared changes on the Generalized Anxiety Disorder-7 scale (GAD-7) in those presenting with anxiety (n = 298); or change in the number of weekly drinks in those presenting with at-risk drinking (n = 176). RESULTS: There were no treatment or time×treatment effects between tCC and eUC on PHQ-9 scores for patients with depression during the 12-month follow-up. However, there was a treatment effect (tCC > eUC) on GAD-7 scores in those with anxiety and a time×treatment interaction effect on the number of weekly drinks (tCC > eUC) in those with at-risk drinking. CONCLUSION: Implementing transdiagnostic tCC for common mental disorders using lay providers appears feasible in Canadian primary care. While tCC was not better than eUC for depression, there were some benefits for those with anxiety or at-risk drinking. Future studies will need to confirm whether tCC differentially benefits patients with depression, anxiety, or at-risk drinking.

Effectiveness of computer-based interventions for community-dwelling people with cognitive decline: a systematic review with meta-analyses.

BACKGROUND: Cognitive deficits arise with age and can increase the risk for subjective cognitive decline (SCD) and mild cognitive impairment (MCI), which may result in dementia, leading to health problems, care dependency and institutionalization. Computer-based cognitive interventions (CCIs) have the potential to act as important counteraction functions in preserving or improving cognition concomitant to available pharmacological treatment. The aim was to assess the effectiveness of CCIs performed individually with a personal or tablet computer, game console, virtual, augmented, or mixed reality application on cognition in community-dwelling people with SCD, MCI and dementia. METHODS: A systematic review with meta-analyses of randomized controlled trials (RCTs) was performed. The systematic literature search was conducted in MEDLINE, CINAHL, Embase, Cochrane CENTRAL, IEEE Xplore Digital Library, Web of Science, Scopus and PsycINFO. In addition, a search for gray literature and backward citation searching were carried out. To judge on the evidence, two reviewers independently used the Cochrane Risk of Bias Tool. The standardized mean difference (SDM) for pooling comparable studies using the random-effects model was applied. RESULTS: Twenty-four RCTs were identified, of which 1 RCT examined CCIs in individuals with SCD, 18 RCTs with MCI, and 6 RCTs with dementia. Most interventions were conducted with personal computers. Meta-analyses with 12 RCTs showed significant effects of computer-based cognitive interventions for people with MCI in the domains memory, working memory, attention/concentration/processing speed and executive functioning, but no significant improvements in global cognition and language. Regarding dementia a meta-analysis pooled with 4 RCTs demonstrated a tendency towards, but no significant increase of memory functions (SMD 0.33, CI 95% [-0.10, 0.77]). One RCT regarding SCD reported significant improvements in memory functions for participants conducting a cognitive training on a personal computer. CONCLUSIONS: The results demonstrated that CCIs have beneficial effects on domain-specific cognition in people with MCI but no significant effects on people with dementia. In terms of SCD, one study showed significant improvements in memory functions. It seems that the beneficial effect for cognitive preservation or improvement due to CCIs occurs at the earliest intervention state. However, more research on SCD is needed. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CDR42020184069.

Utility of a multimodal computer-based assessment format for assessment with a higher degree of reliability and validity.

Multiple choice questions (MCQs) suffer from cueing, item quality and factual knowledge testing. This study presents a novel multimodal test containing alternative item types in a computer-based assessment (CBA) format, designated as Proxy-CBA. The Proxy-CBA was compared to a standard MCQ-CBA, regarding validity, reliability, standard error of measurement, and cognitive load, using a quasi-experimental crossover design. Biomedical students were randomized into two groups to sit a 65-item formative exam starting with the MCQ-CBA followed by the Proxy-CBA (group 1, n = 38), or the reverse (group 2, n = 35). Subsequently, a questionnaire on perceived cognitive load was taken, answered by 71 participants. Both CBA formats were analyzed according to parameters of the Classical Test Theory and the Rasch model. Compared to the MCQ-CBA, the Proxy-CBA had lower raw scores (p < 0.001, η2 = 0.276), higher reliability estimates (p < 0.001, η2 = 0.498), lower SEM estimates (p < 0.001, η2 = 0.807), and lower theta ability scores (p < 0.001, η2 = 0.288). The questionnaire revealed no significant differences between both CBA tests regarding perceived cognitive load. Compared to the MCQ-CBA, the Proxy-CBA showed increased reliability and a higher degree of validity with similar cognitive load, suggesting its utility as an alternative assessment format.

Effects of candidates' demographics and evaluation of the virtual Multiple Mini Interview (vMMI) as a tool for selection into paediatric training in Queensland.

INTRODUCTION: The Queensland Basic Paediatric Training Network (QBPTN) is responsible for the selection of candidates into paediatric training in Queensland. The COVID-19 pandemic necessitated interviews to be conducted 'virtually' as virtual Multiple-Mini-Interviews (vMMI). The study aimed to describe the demographic characteristics of candidates applying for selection into paediatric training in Queensland, and to explore their perspectives and experiences with the vMMI selection tool. METHODOLOGY: The demographic characteristics of candidates and their vMMI outcomes were collected and analysed with a mixed methods approach. The qualitative component was comprised of seven semi-structured interviews with consenting candidates. RESULTS: Seventy-one shortlisted candidates took part in vMMI and 41 were offered training positions. The demographic characteristics of candidates at various stages of selection were similar. The mean vMMI scores were not statistically different between candidates from the Modified Monash Model 1 (MMM1) location and others [mean (SD): 43.5 (5.1) versus 41.7 (6.7), respectively, p = 0.26]. However, there was a statistically significant difference (p value 0.03) between being offered and not offered a training position for candidates from MMM2 and above. The analysis of the semi-structured interviews suggested that candidate experiences of the vMMI were influenced by the quality of the management of the technology used. Flexibility, convenience, and reduced stress were the main factors that influenced candidates' acceptance of vMMI. Perceptions of the vMMI process focused on the need to build rapport and facilitate communication with the interviewers. DISCUSSION: vMMI is a viable alternative to face-to-face (FTF) MMI. The vMMI experience can be improved by facilitating enhanced interviewer training, by making provision for adequate candidate preparation and by having contingency plans in place for unexpected technical challenges. Given government priorities in Australia, the impact of candidates' geographical location on the vMMI outcome for candidates from MMM >1 location needs to be further explored.

Development of an assessment tool to measure communication skills among family medicine residents in the context of electronic medical record use.

BACKGROUND: The introduction of the electronic medical record (EMR) has led to new communication skills that need to be taught and assessed. There is scarce literature on validated instruments measuring electronic-specific communication skills. The aim is to develop an assessment checklist that assesses the general and EMR-specific communication skills and evaluates their content validity and reliability. METHODS: Using the SEGUE theoretical framework for communication skills, the assessment checklist items were developed by the Communication Skills Working Group (CSWG) at the family medicine department using a literature review about the positive and negative aspects of EMR use on physician-patient communication. A group of faculty members rated real resident-patient encounters on two occasions, three weeks apart. Patients were asked to fill out the Communication Assessment Tool (CAT) at the end of the encounter. RESULTS: A total of 8 residents agreed to participate in the research, with 21 clinical encounters recorded. The average total score was 65.2 ± 6.9 and 48.1 ± 9.5 for the developed scale and the CAT scale, respectively. The scale reliability was good, with a Cronbach alpha of 0.694. The test-retest reliability was 0.873, p < 0.0001. For the total score on the developed checklist, the intraclass correlation coefficient between raters (ICC) was 0.429 [0.030,0.665], p-value of 0.019. The level of agreement between any two raters on the cumulative score of the 5 subsections ranged from 0.506 (interpersonal skills) to 0.969 (end encounter). CONCLUSION: This checklist is a reliable and valid instrument that combines basic and EMR-related communication skills.

Novel innovative computer-based test (Inno-CBT) item types for national licensing examinations for health care professionals.

BACKGROUND: An effective test mechanism to evaluate clinical knowledge and skills of the entry-level healthcare professionals is important for providing clinical competency and improving patient care. This study aimed to develop novel, innovative computer-based test (Inno-CBT) item types for application in the national examination of Korean healthcare professionals. METHODS: This exploratory study was conducted from May 2021 to March 2022 by a team of faculty members from pharmacy schools in South Korea. A literature search using PubMed, Google Scholar, RISS, Web of Science, and KoreaMed was performed. Forum presentations, media articles, and previous reports by the Korea Health Personnel Licensing Examination Institute (KHPLEI) were included. Workshops were held, information and ideas were collected and conceptualized, and item types were designed, drafted, and refined. By repeating this process, the Inno-CBT item types were finalized. RESULTS: Forty-one Inno-CBT item types with 28 subtypes were developed. New digital technologies, such as a reactive responsive media interface, an animation insertion, multimedia embedding, and network surfing, were utilized in these novel types. It was anticipated that these Inno-CBT item types would effectively measure abilities in healthcare knowledge, problem-solving skills, and professional behaviors. Some potential barriers to implementing the Inno-CBT item types include item difficulty, operational unfamiliarity, complexity in scoring protocols, and network security. CONCLUSIONS: A variety of styles of novel Inno-CBT item types were developed to evaluate the multifaceted and in-depth professional abilities required for healthcare professionals. Prior to implementing these item types in the national examination, item validation and technical support should be conducted.

Using Process Data to Improve Classification Accuracy of Cognitive Diagnosis Model.

With the advance of computer-based assessments, many process data, such as response times (RTs), action sequences, Eye-tracking data, the log data for collaborative problem-solving (CPS) and mouse click/drag becomes readily available. Findings from previous studies (e.g., Peng et al., Multivariate Behavioral Research, 1-20, 2021; Xu, The British Journal of Mathematical and Statistical Psychology, 73(3), 474-505, 2020; He & von Davier, Handbook of research on technology tools for real-world skill development (pp. 750-777). IGI Global, 2016; Man & Harring, Educational and Psychological Measurement, 81(3), 441-465, 2021) suggest a substantial relationship between this human-computer interactive process information and proficiency, which means these process data were potentially useful variables for psychological and educational measurement. To make full use of the process data, this paper aims to combine two useful and easily available types of process data, including the mouse click/drag traces and the response times, to the conventional cognitive diagnostic model (CDM) to better understand individual's response behavior and improve the classification accuracy of existing CDM. Then the full Bayesian analysis using Markov chain Monte Carlo (MCMC) was employed to estimate the proposed model parameters. The viability of the proposed model was investigated by an empirical data and two simulation studies. Results indicated the proposed model combing both types of process data could not only improve the attribute classification reliability in real data analysis, but also provide an improvement on item parameters recovery and person classification accuracy.

Overcoming financial and social barriers during COVID-19: A medical student-led medical education innovation.

Background: Underrepresented minorities in medicine (URMM) may face financial and social limitations when applying to medical schools. The computer-based assessment for sampling personal characteristics (CASPER) test is used by many medical schools to assess the nonacademic competencies of applicants. Performance on CASPER can be enhanced by coaching and mentorship, which URMMs often lack, for affordability reasons, when applying to medical schools. Methods: The CASPER Preparation Program (CPP) is a free, online, 4-week program to help URMM prepare for the CASPER test. CPP features free medical ethics resources, homework and practice tests, and feedback from tutors. Two of CPPs major objectives include relieving URMM of financial burdens and increasing their accessibility to mentorship during the COVID-19 pandemic. A program evaluation was conducted using anonymous, voluntary postprogram questionnaires to assess CPPs efficacy in achieving the aforementioned objectives. Results: Sixty URMMs completed the survey. The majority of the respondents strongly agreed or agreed that CPP relieves students of financial burden (97%), is beneficial for applicants with low-socioeconomic statuses (98%), provides students with resources they could not afford (n = 55; 92%), and enables access to mentors during the pandemic (90%). Discussion: Pathway coaching programs, such as the CASPER Preparation Program, have the potential to offer URMMs mentorship and financial relief, and increase their confidence and familiarity with standardized admission tests to help them matriculate into medical schools.