Facilitators and Barriers to Student Learning and Impact of an Undergraduate Clinical Posting in Psychiatry: A Thematic Analysis

Background: There is an absence of information on empirical evaluation of undergraduate psychiatry training programs in India. We aimed to evaluate a clinical posting in psychiatry for undergraduate medical students. Methods: We employed levels one and two of Kirkpatrick’s four-level program evaluation model. The qualitative study used written feedback that was collected using a semistructured questionnaire. For quantitative metrics, we used end-of-posting assessment scores and frequencies of standard comments provided by examiners on case-based discussions with students to evaluate their clinical skills. Results: We obtained written feedback from 40 female and 19 male fifth-semester students. We identified facilitators (patient interaction, outpatient department observation and teaching, demonstration of signs, case presentation and discussion, evening posting, observation of clinical work, use of anecdotes while teaching, and lectures by senior faculty) and barriers (organizational issues related to evening posting and disinterest in didactic teaching) to the students learning psychiatry, and the perceived impact of the posting for the students (changed attitudes, knowledge, self-efficacy, and skills acquired). The mean total score on case-based discussion, assigned to 22 groups of students, was 3.86 out of 5. Conclusion: We described the impact of the posting and identified unique facilitators and barriers to students’ learning in psychiatry. These findings will inform the choice of teaching-learning methods in the context of the new Competency-Based undergraduate Medical Education (CBME) curriculum.

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Evaluation of a Case-Based Primary Care Pediatric Conference Curriculum

Journal of Graduate Medical Education ◽

10.4300/jgme-d-10-00118.1 ◽

2011 ◽

Vol 3 (2) ◽

pp. 224-231 ◽

Cited By ~ 6

Author(s):

Jaideep S. Talwalkar ◽

Ada M. Fenick

Keyword(s):

Primary Care ◽

Clinical Skills ◽

Core Competencies ◽

Ambulatory Setting ◽

Free Form ◽

The Impact ◽

Standardized Curriculum ◽

Academic Year ◽

Case Based ◽

Care Conference

Abstract Background Our goal was to assess the impact of a standardized residency curriculum in ambulatory pediatrics on residents' participation, satisfaction, and confidence. Methods A case-based curriculum for weekly primary care conference was developed to replace the existing free-form review of topics at the Yale Pediatrics Residency Program. Before the curricular switch, faculty preceptors and members of the academic year 2005–2006 intern class completed surveys designed to measure conference occurrence and resident attendance, participation, satisfaction, and confidence in clinical skills. One year after the curricular switch, identical surveys were completed by faculty preceptors and members of the academic year 2006–2007 intern class. Results Faculty surveys indicated that conferences took place significantly more often after the curricular switch. The number of residents at conference each day (3.18 vs 4.50; P < .01) and the percentage who actually spoke during conference (45% vs 82%, P < .01) significantly increased. There were 18 demographically similar interns in each of the 2 classes. Members of the academic year 2006–2007 intern class, having trained exclusively with the standardized curriculum, were significantly more likely to respond favorably to survey items about participation, satisfaction, and confidence. In addition, they were more likely to endorse survey items that reflected explicit goals of the standardized curriculum and the Accreditation Council for Graduate Medical Education core competencies. Conclusion Implementation of a structured curriculum for ambulatory care improved interns' self-reported participation, satisfaction, and confidence. The primary care conference occurred more dependably after the curricular change, and improvements in attendance and participation were documented. Pediatric residency programs may make better use of conference time in the ambulatory setting through the use of structured, case-based educational material.

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Overcapacity Risk of China’s Coal Power Industry: A Comprehensive Assessment and Driving Factors

Sustainability ◽

10.3390/su13031426 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1426

Author(s):

Delu Wang ◽

Xun Xue ◽

Yadong Wang

Keyword(s):

Evaluation Model ◽

Supply And Demand ◽

Correlation Effect ◽

Power Industry ◽

Environmental Benefits ◽

Risk Level ◽

Correlation Based Feature Selection ◽

Coal Power ◽

And Control ◽

The Impact

The comprehensive and accurate monitoring of coal power overcapacity is the key link and an important foundation for the prevention and control of overcapacity. The previous research fails to fully consider the impact of the industry correlation effect; making it difficult to reflect the state of overcapacity accurately. In this paper; we comprehensively consider the fundamentals; supply; demand; economic and environmental performance of the coal power industry and its upstream; downstream; competitive; and complementary industries to construct an index system for assessing coal power overcapacity risk. Besides; a new evaluation model based on a correlation-based feature selection-association rules-data envelopment analysis (CFS-ARs-DEA) integrated algorithm is proposed by using a data-driven model. The results show that from 2008 to 2017; the risk of coal power overcapacity in China presented a cyclical feature of “decline-rise-decline”, and the risk level has remained high in recent years. In addition to the impact of supply and demand; the environmental benefits and fundamentals of related industries also have a significant impact on coal power overcapacity. Therefore; it is necessary to monitor and govern coal power overcapacity from the overall perspective of the industrial network, and coordinate the advancement of environmental protection and overcapacity control.

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Impact of Dataset Size on Classification Performance: An Empirical Evaluation in the Medical Domain

Applied Sciences ◽

10.3390/app11020796 ◽

2021 ◽

Vol 11 (2) ◽

pp. 796

Author(s):

Alhanoof Althnian ◽

Duaa AlSaeed ◽

Heyam Al-Baity ◽

Amani Samha ◽

Alanoud Bin Dris ◽

...

Keyword(s):

Empirical Evaluation ◽

Classification Performance ◽

Support Vector ◽

Robust Model ◽

Original Distribution ◽

C4.5 Decision Tree ◽

Dataset Size ◽

Overall Performance ◽

Medical Domain ◽

The Impact

Dataset size is considered a major concern in the medical domain, where lack of data is a common occurrence. This study aims to investigate the impact of dataset size on the overall performance of supervised classification models. We examined the performance of six widely-used models in the medical field, including support vector machine (SVM), neural networks (NN), C4.5 decision tree (DT), random forest (RF), adaboost (AB), and naïve Bayes (NB) on eighteen small medical UCI datasets. We further implemented three dataset size reduction scenarios on two large datasets and analyze the performance of the models when trained on each resulting dataset with respect to accuracy, precision, recall, f-score, specificity, and area under the ROC curve (AUC). Our results indicated that the overall performance of classifiers depend on how much a dataset represents the original distribution rather than its size. Moreover, we found that the most robust model for limited medical data is AB and NB, followed by SVM, and then RF and NN, while the least robust model is DT. Furthermore, an interesting observation is that a robust machine learning model to limited dataset does not necessary imply that it provides the best performance compared to other models.

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Emergency Capacity of Small Towns to Endure Sudden Environmental Pollution Accidents: Construction and Application of an Evaluation Model

Sustainability ◽

10.3390/su13105511 ◽

2021 ◽

Vol 13 (10) ◽

pp. 5511

Author(s):

Delu Wang ◽

Yadong Wang

Keyword(s):

Environmental Pollution ◽

Evaluation Model ◽

Empirical Evaluation ◽

Analytic Network Process ◽

Small Towns ◽

Evaluation Index System ◽

Four Dimensions ◽

Recovery Capacity ◽

Network Process ◽

Response And Recovery

Sudden environmental pollution accidents (SEPAs) in small towns are characterized by high uncertainty, complex evolution, and fast spread speed, and they cause serious harm to a wide geographic range. Thus, SEPAs greatly challenge the emergency management systems of enterprises and governments. Therefore, improving the emergency capacity of small towns (ECST) to withstand SEPAs deserves more attention. In this study, the evolution mechanism of SEPAs is systematically analyzed, revealing the interactions among various situational elements in the SEPA occurrence process. Then, an evaluation index system of the ECST response to SEPAs is constructed based on four dimensions: monitoring and early warning capacity, preparedness and mitigation capacity, response, and recovery capacity. The system includes 68 indicators and covers the key stages of the SEPA life cycle. Finally, an evaluation model of the ECST to SEPAs is proposed based on the analytic network process method, and the small town of Jiangyin City is selected as a case study for empirical evaluation. The proposed evaluation model considers the interactions and interdependent feedback between indexes, effectively improving the accuracy and scientific nature of the evaluation results. Thus, this model provides a solid decision-making reference for governments and a quantitative theoretical basis for the formulation of measures targeted at SEPAs.

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The use of text mining to detect key shifts in Japanese first-year medical student professional identity formation through early exposure to non-healthcare hospital staff

BMC Medical Education ◽

10.1186/s12909-021-02818-1 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yayoi Shikama ◽

Yasuko Chiba ◽

Megumi Yasuda ◽

Maham Stanyon ◽

Koji Otani

Keyword(s):

Text Mining ◽

Professional Identity ◽

Identity Formation ◽

Role Models ◽

Healthcare Professionals ◽

Clinical Work ◽

Working Environment ◽

First Year ◽

Professional Identity Formation ◽

The Impact

Abstract Background Professional identity formation is nurtured through socialization, driven by interaction with role models, and supported through early clinical exposure (ECE) programmes. Non-healthcare professionals form part of the hospital community but are external to the culture of medicine, with their potential as role models unexplored. We employed text mining of student reflective assignments to explore the impact of socialization with non-healthcare professionals during ECE. Methods Assignments from 259 first-year medical students at Fukushima Medical University, Japan, underwent hierarchical cluster analysis. Interrelationships between the most-frequently-occurring words were analysed to create coding rules, which were applied to elucidate underlying themes. Results A shift in terms describing professional characteristics was detected, from “knowledge/skill” towards “pride [in one’s work]” and “responsibility”. Seven themes emerged: contribution of non-healthcare professionals, diversity of occupation, pride, responsibility, teamwork, patient care and gratitude. Students mentioning ‘contribution of non-healthcare professionals’ spoke of altruistic dedication and strong sense of purpose. These students expressed gratitude towards non-healthcare professionals for supporting clinical work, from a doctor’s perspective. Conclusion Socialization with non-healthcare professionals provides important insights into the hospital working environment and cultural working norms. Through role modelling altruism and responsibility, non-healthcare professionals positively influenced student professional identity formation, promoting self-conceptualisation as a doctor.

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Evaluating the Impact of Training Health Professionals to Deliver Brief Motivational and Skills-Based Interventions for Cannabis Use Disorder

Journal of Tropical Psychology ◽

10.1017/jtp.2012.1 ◽

2012 ◽

Vol 2 ◽

Author(s):

Dion Alperstein ◽

Jan Copeland

Keyword(s):

Clinical Training ◽

Health Workers ◽

Clinical Skills ◽

Cannabis Use ◽

Evidence Based ◽

Transfer Of Knowledge ◽

Evidence Based Treatment ◽

Cognitive Behavioural ◽

The Impact

Background: While there is considerable evidence that brief motivational and skills-based interventions for substance use are effective, little is known regarding the transfer of knowledge from research to practice. This study aims to evaluate the effectiveness of two half-day didactic clinical training workshops for allied health workers, which did not incorporate feedback or supervision, via independent follow-up three months post training.Methods: In total, 1322 participants attended either or both of the evidence-based treatment workshops run by the National Cannabis Prevention and Information Centre. Of those participants, 495 (37%) completed an online follow-up evaluation three months later regarding their use of the newly learnt intervention(s).Results: At follow-up, 270 (54.5%) participants had an opportunity to use the skills and 144 (53.3%) of those participants reported having used the clinical skills taught in the workshop. Of those who used one of the interventions, 90 (62.5%) participants reported their clients had reduced or quit their cannabis use. Furthermore, 43 (30%) of these participants had attempted to train others in the workplace in the techniques learnt in the workshop.Conclusion: Even a half-day didactic clinical training workshop on evidence-based brief cognitive–behavioural techniques delivered to clinicians working in the field can improve knowledge and confidence among clinicians and outcomes among their clients with cannabis use related problems.

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