Clinical Learning Research Articles

Nursing Students' Perception of the Clinical Learning Environment: A Longitudinal, Cohort Study.

The clinical learning environment (CLE) plays a vital role in students' learning in clinical settings. However, to our knowledge, no longitudinal cohort studies have been published on how CLE influences nursing students' learning during clinical placements. This study investigated a cohort of nursing students' perceptions of CLE during their first and third-year clinical placements. The clinical learning environment inventory (CLEI) questionnaire was used in this study. In 2021, a convenience sample of 450 first-year nursing students was invited to complete the CLEI questionnaire. In 2023, the same cohort of students in their third year of study were invited to complete the questionnaire. Personalization, satisfaction, and task orientation had higher mean scores than the other CLEI subscales. The lowest mean scores were found for the teaching innovation and individualization subscales. Multiple regression and bivariate correlation analyses revealed task orientation as the strongest predictor of student satisfaction with the CLE. Nursing students in Singapore have a moderately positive satisfaction with their CLE. Clinical instructors should design innovative lesson plans to improve the student experience and learning in the CLE.

Clinical learning of nursing students during the COVID-19 pandemic in Limpopo province, South Africa.

The Nursing Education Programme was affected during the coronavirus disease 2019 (COVID-19) pandemic, resulting in nursing students being unable to participate in the clinical experiential learning required by the South African Nursing Council. The study seeks to explore and describe nursing students' experiences of clinical experiential learning during the COVID-19 pandemic. A qualitative, explorative and descriptive, research design was used in the study. A non-probability purposive sampling method was used, and 55 nursing students participated in the study. Data were collected through six focus group discussions, consisting of 8-12 nursing students in each group. Data were analysed following Tesch's open coding method. Three themes emerged from the study's findings: The impact of COVID-19 on the clinical experiential learning of nursing students, the effects of COVID-19 on the mental well-being of nursing students, and nursing students' experiences of support during the COVID-19 pandemic. Notably, 11 sub-themes emerged. The findings of this study reveal that the COVID-19 pandemic severely disrupted the Nursing Education Programme, highlighting the challenges of inadequate clinical hours, restricted clinical access and the significant psychological impact on students.Contribution:This study adds to the literature on students' experiences during clinical experiential learning in South Africa during the COVID-19 pandemic.

Improve clinical feature-based bladder cancer survival prediction models through integration with gene expression profiles and machine learning techniques

BackgroundBladder cancer (BCa), one of the most common cancers worldwide, is characterized by high rates of recurrence, progression, and mortality. Machine learning algorithms offer promising advancements in enhancing predictive models. This study aims to develop robust machine learning models for predicting BCa survival using clinical and gene expression data. MethodsClinical data from BCa patients were obtained from the Surveillance, Epidemiology, and End Results database. Cox proportional hazards regression models assessed the association between clinical variables and overall survival. Machine learning algorithms, including logistic regression, random forest, XGBoost, decision tree, and LightGBM, were employed to predict survival at 1, 3, and 5 years. The TAGO database, combined with the data from The Cancer Genome Atlas and four databases from the Gene Expression Omnibus, which have available genomic data and clinical data, were selected. Gene expression data were transformed into gene sets data, and the performance of models based on clinical data and gene sets data and their combination were compared. Furthermore, the impact of model-derived scores on overall survival was evaluated. ResultsAmong 138,741 BCa patients with available clinical data, key independent predictors of survival included age, race, marital status, surgery, chemotherapy, radiation, and TNM stages. Clinical data machine learning (CML) models used these clinical predictors to achieve AUC values of 0.860, 0.821, and 0.804 in the testing sets for predicting survival at 1, 3, and 5 years, respectively. In the TAGO database, which has 863 patients with clinical and genomic data, the integrated clinical and gene expression machine learning model (IML) outperformed the CML and gene expression machine learning (GML) models in survival prediction. Patients with higher IML and GML model scores exhibited poorer survival outcomes. ConclusionsThis study successfully identifies key clinical and genomic predictors, a significant step forward in BCa research. The development of predictive models for BCa survival underscores the potential of integrated data approaches in improving BCa management and treatment strategies.

Harnessing risk assessment for thrombosis and bleeding to optimize anticoagulation strategy in nonvalvular atrial fibrillation.

Oral anticoagulation (OAC) following catheter ablation (CA) of nonvalvular atrial fibrillation (NVAF) is essential for the prevention of thrombosis events. Inappropriate application of OACs does not benefit thrombosis prevention but may be associated with a higher risk of bleeding. Therefore, this study aims to develop clinical data-driven machine learning (ML) methods to predict the risk of thrombosis and bleeding to establish more precise anticoagulation strategies for patients with NVAF. Patients with NVAF underwent CA therapy were enrolled from Southwest Hospital from 2015 to 2023. This study compared eight ML algorithms to evaluate the predictive power for both thrombosis and bleeding. Model interpretations were recognized by feature importance and SHapley Addictive exPlanations methods. With potential essential risk factors, simplified ML models were proposed to improve the feasibility of the tool. A total of 1055 participants were recruited, including 105 patients with thrombosis and 252 patients with bleeding. The models based on XGBoost achieved the best performance with accuracies of 0.704 and 0.781 for thrombosis and bleeding. Age, BNP and the duration of heparin and are closely related to the high risk of thrombosis, whereas anticoagulation strategy, BNP and lipids play a crucial role in the occurrence of bleeding. The optimized models enrolling crucial risk factors, RF-T for thrombosis and Xw-B for bleeding, achieved the best recalls of 0.774 and 0.780, respectively. The optimized models will have a great clinical application in predicting thrombosis and bleeding among NVAF patients and will form the basis for future score scales.

Developing Indigenous Cultural Safety in Law: Clinical Legal Education as a Method for Getting it Done

The imperative of law schools to embed Indigenous cultural safety in legal education is well established. This paper argues that clinical legal education can make an important pedagogical contribution to the development of Indigenous cultural safety within the study of law. Drawing on a case study of a legal clinic in Logan, Queensland, this paper details clinic teaching and learning activities, and highlights the role of yarning as a process for engaging cultural humility and understanding. A review of pedagogical theories is provided to demonstrate that multiple theoretical approaches support the clinical method as an effective vehicle for delivering transformative learning on issues such as institutional racial bias within law, the legal profession, and broader society. Clinic evaluation reveals strong cultural safety learning outcomes. This paper concludes with some observations about the clinic’s strengths and limitations, including the benefits of devolving autonomy for clinic design to Indigenous clinical supervisors, issues of scalability and funding for community stakeholders.

International nursing students and clinical learning environments: A convergent mixed-methods study

AimTo acquire a comprehensive understanding of the international nursing students' clinical learning environments, comparing and contrasting qualitative and quantitative insights. BackgroundThe influx of international nursing students has increased in Italy and across Europe. These students, diverse in culture and language, encounter significant challenges to their education in clinical learning environments. Designconvergent mixed-methods research. MethodsQualitative and quantitative data were collected concurrently and independently, with equal emphasis, following a QUAL-QUANT structure. Qualitative analysis used descriptive content analysis, while quantitative data were based on descriptive and correlation analyses on surveys using the CALD scale. ResultsOverall 96 international nursing students participated in 24 focus groups. The CALD scale mean scores ranged from 2.7 to 4.5. The qualitative analysis presented two overarching themes: factors that promote a successful clinical learning environment and factors that inhibit a successful clinical learning environment in international students. The integration of qualitative and quantitative data generated four concordant and one discordant meta-inferences about the learning environment. ConclusionsCulturally sensitive clinical learning environments are imperative for the holistic development of international nursing students. Nurse educators must cultivate transcultural competencies and pedagogical skills to enhance the competencies and skills of this student population effectively.

So You Are a Clinical Instructor-Now What?

Many nuclear medicine technologists find themselves in the role of clinical instructor, often without much in the way of educational background. This article provides a few recommendations on how to get started in this role. After distinguishing between the roles of affiliate education supervisor and clinical instructor, the article discusses 2 basic tools: the clinical course learning outcomes and the student handbook. Expectations for students are reviewed. An important aspect of clinical instruction is the attitude of the instructor. Clinical instructors can motivate students or demotivate them, with this choice having a significant impact on the student's development. Overall, the desire and determination to be pleasant and helpful to students make the greatest difference in their development into nuclear medicine technologists.

Level of Satisfaction on Clinical Learning Environment among Nursing Students of Nepalgunj Nursing Campus at Kohalpur

Introduction: Clinical education is a major component of the undergraduate nursing curriculum. To practice a safe beginning level of nursing care, new graduates must have developed not only the theoretical knowledge on which to base their care but also the practical application skills required to implement that knowledge. The clinical learning environment can have a great influence on the development of attitude, knowledge, skills, and problem-solving ability of students. The clinical learning environment plays a crucial role, especially during the clinical training of student nurses, as they face the reality of their roles and responsibilities of being nurses. Aims: To find out undergraduate nursing student’s satisfaction with their clinical learning environment. Methods: This cross-sectional study was conducted in the Nepalgunj Nursing Campus. The study was conducted among 40 students who were studying Proficiency Certificate Level in Nursing at the Nepalgunj Nursing Campus, Kohalpur. A non-probability sampling method was used to select the sample. A semi-structured self-administered questionnaire and the Clinical Learning Environment, Supervision, and Nurse Teacher Scale (CLES+T) were used for data collection. The Clinical Learning Environment, Supervision, and Nurse Teacher Scale is an internationally valid and reliable instrument used to evaluate the quality of clinical learning environments for students in the health professions. Results: More than half of the nursing students (52.50%) were highly satisfied with the clinical learning environment. The association between the level of satisfaction among nursing students and age, marital status, last clinical placement ward, frequency of meeting nurse teachers, and use of e-communication tools with nursing teachers was not statistically significant. Conclusion: In today’s education system, which is centered on students’ learning concepts and expectations, assessing the students’ satisfaction level can be one of the innovative ways to bring positive changes to both the students’ and teachers’ experiences. However, the availability of limited research studies on this matter, makes it hard to draw any conclusions. Hence, future studies should focus on identifying the various factors influencing the satisfaction level of students with clinical learning.

Peer Support Ambassadors: A Program to Advance a Supportive and Inclusive Clinical Learning Environment.

Peer support is beneficial to physicians in distress, but few institutions have created formal programs that train residents and fellows to effectively support their peers. Existing curricula also do not address the differential experience of residents from historically excluded groups, who are more likely to experience distressing mistreatment and discrimination in the clinical learning environment. The Graduate Medical Education (GME) Peer Support Ambassador (PSA) Program aimed to address this gap by: (1) offering peer support skills and trauma-informed care training to a diverse cohort of resident leaders representing a range of specialties, (2) deploying these leaders to support their peers, and (3) facilitating opportunities for participants to train other residents in these skills. In the PSA program's inaugural year, 10 residents were trained in fundamentals of peer support, trauma-informed care, and the restorative mindset. The training increased participants' confidence and skills in these areas, increased their understanding of when to refer a co-resident for additional levels of support, and their awareness of resources for mental health care and addressing mistreatment and discrimination. Beyond the skills training, the program broadened participants' perspectives about other residents' experiences and helped them feel more connected to residents in other specialties. Opportunities to improve the PSA program include creating more opportunities for program participants to connect between sessions and after the training, publicizing the program more effectively to residents experiencing distress, and training a larger number of residents in peer support skills.

Do nursing students' attitudes to clinical practice training affect the levels of vocational motivation?

It is extremely important for nursing students to be professionally motivated to train qualified future professional nurses. Students' vocational motivation is affected by their experiences in clinical and academic learning environments. The aim of this study was to investigate the correlation between the vocational motivation levels of nursing students and their attitudes toward clinical practice. 292 nursing students participated in the cross-sectional, descriptive study. The Student Information Form, Nursing Students' Attitudes Towards Clinical Practices Scale, Motivation Sources and Problems Scale (MSPS) were used to gather the data. The average score for students' attitudes toward clinical practice was 107.08±18.13, while the total score for MSPS stood at 3.80±0.63. A positive correlation was identified between the attitude toward clinical practice and vocational motivation levels (r = 0.367; p < 0.001). There were positive correlations between the intrinsic motivation (r = 0.572; p < 0.001) and extrinsic motivation (r = 0.58; p < 0.001), and negative correlations were observed between the negative motivation (r=-0.324; p < 0.001) and the attitude toward clinical practice scale. There were positive correlations between belief and expectation (r = 0.492; p < 0.001) and positive approach (r = 0.532; p < 0.001) with the MSPS. In the multiple regression analysis, intrinsic motivation, extrinsic motivation, satisfaction with studying nursing, and participation in vocational courses were determined as effective predictors of attitudes towards clinical practice and explained 60.4% of the variance. The study concluded that nursing students' attitudes toward clinical practices affect vocational motivation. Clinical learning environments should be arranged in a way to increase the motivation level of students towards professional learning.

Clinical Learning Activities and Improvements in NP Student Self-Evaluation Scores.

Clinical Learning Activities and Improvements in NP Student Self-Evaluation Scores.

Beyond labs: unveiling dynamics of dental students' transition from pre-clinical to clinical training in a Saudi dental school.

To assess the factors affecting the transition of dental students from pre-clinical to clinical courses in an outcome-based curriculum. This cross-sectional study surveyed dental students in the third and fourth academic years of the Bachelor of Dental and Oral Surgery (BDS) program at the College of Dentistry, Jouf University. Ethically approved and powered by the G Power software, the study employed a modified questionnaire validated through a pilot test to assess five domains. Likert scale responses were analyzed using SPSS v.25, revealing insights into clinical workload, patient interaction, and learning experiences. Multiple regression analysis was used to assess the impact of clinical skill application, workload, transition to clinics, and patient interaction on learning experience as well as CGPA. The Mann-Whitney U test compared the ranks of two independent samples, making it less sensitive to outliers and more suitable for data with non-normal distributions. In this study, the response rate of the participants was 70%. A total of 44 dental students in their third and fourth years of the program completed the survey. The multiple regression analysis showed that the predictors collectively explained 36.1% of the variance in the learning experience (Adjusted R2 = 0.361). "Transition to Clinics" had a significant positive effect on learning experience (β = 0.292, p = 0.012), "Workload" (β = -0.203, p = 0.393) and "Patient Interaction" (β = 0.443, p = 0.168) were not significant predictors. The Mann-Whitney U test revealed no significant gender differences in transition to clinics, workload, patient interaction, application of clinical skills, and learning experience (U = 33.09 to -40.33, p > 0.05), but a significant difference in transition to clinics between third- and fourth-year students (U = 31.56 to -43.24, p < 0.05). The results of this study demonstrate that the transition to clinical training can be intricate, and that multiple elements have an impact on this process. It is crucial to have support systems that facilitate the transition into the clinical learning environment.

Deep learning Radiomics Based on Two-Dimensional Ultrasound for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer.

We investigate the predictive value of a comprehensive model based on preoperative ultrasound radiomics, deep learning, and clinical features for pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for the breast cancer. We enrolled 155 patients with pathologically confirmed breast cancer who underwent NAC. The patients were randomly divided into the training set and the validation set in the ratio of 7:3. The deep learning and radiomics features of pre-treatment ultrasound images were extracted, and the random forest recursive elimination algorithm and the least absolute shrinkage and selection operator were used for feature screening and DL-Score and Rad-Score construction. According to multifactorial logistic regression, independent clinical predictors, DL-Score, and Rad-Score were selected to construct the comprehensive prediction model DLRC. The performance of the model was evaluated in terms of its predictive effect, and clinical practicability. Compared to the clinical, radiomics (Rad-Score), and deep learning (DL-Score) models, the DLRC accurately predicted the pCR status, with an area under the curve (AUC) of 0.937 (95%CI: 0.895-0.970) in the training set and 0.914 (95%CI: 0.838-0.973) in the validation set. Moreover, decision curve analysis confirmed that the DLRC had the highest clinical value among all models. The comprehensive model DLRC based on ultrasound radiomics, deep learning, and clinical features can effectively and accurately predict the pCR status of breast cancer after NAC, which is conducive to assisting clinical personalized diagnosis and treatment plan.

Lived experiences of medical students of online learning: lessons for adopting virtual learning in medical education

BackgroundThe COVID 19 lockdown created a shift in medical education from the traditional physical classroom to online learning.ObjectivesTo explore the lived experiences of students in various years of medical education attending a medical college in Chennai, India.MethodsIn this qualitative exploration of lived experiences we conducted 4 focus group discussions among students of the four years in the medical college with the help of a checklist. We recorded the interviews, transcribed them and performed a thematic content analysis.ResultsThere was a gendered impact of the lockdown on the online learning experiences with women students finding it challenging to attend classes balancing their gender roles of performing household chores. Online learning offered some advantages in the form of increased participation and engagement due to the partial anonymity. The greatest disadvantage of online learning was lack of clinical learning experience. The students resorted to fabricating case studies for discussion, which some students found useful and some commented that it can never replace real life clinical discussions. A generational gap between adoption of technology between the senior professors and the students hampered the online learning. Online assessments were challenging, and many students resorted to cheating in these exams.ConclusionsThough online learning offers several advantages, it has serious limitations in offering the clinical learning experience. While planning adoption of online learning into routine medical education adequate time must be set aside for real life clinical exposure in addition to the online lectures and demonstrations for conceptual understanding.

Using the Four Ps of telehealth framework to enhance doctor of nursing practice (DNP) Telehealth Curriculum

BackgroundTelehealth is now a necessary component of health care delivery, and its use among health care professionals was accelerated by the COVID-19 pandemic. ProblemNurse practitioner (NP) programs generally incorporate telehealth competencies within their curriculum, preparing NPs to effectively deliver telehealth and improve health outcomes. ApproachWe developed and implemented a telehealth blueprint to enhance telehealth content within our clinical Doctor of Nursing Practice (DNP) program guided by the Four Ps of the Telehealth Framework planning, preparing, providing, and performance evaluation. OutcomesThe Four Ps for Telehealth Framework assisted us in scaffolding content across the 3 years of the DNP program. Telehealth competencies were delivered through multiple modalities: online modules, experiential and clinical learning, and discussions of challenges related to telehealth. Students overwhelming reported that they were prepared to use telehealth technology upon graduation. ConclusionsThe Four Ps for Telehealth Framework was used to successfully integrate telehealth content into our DNP curriculum.

Understanding Residents' and Supervisors' Views on Developing Support-Autonomy Balance Through Supervision Methods in Postgraduate Dental Training: AQualitative Study.

Supervisors continuously need to decide when to provide clinical opportunities for unsupervised patient care to facilitate residents' development in the complex clinical learning context. The aim of this study is to explore residents' and supervisors' views and understanding of the influence of clinical supervision on affording a balanced support-autonomy from the cognitive apprenticeship (CA) theoretical lens. Residents and supervisors, representing all disciplines, participated in five focus groups and four semi-structured individual interviews. Purposive and convenience sampling methods were used for recruiting participants. The reflexive thematic analysis approach was used for inductive data analysis. A total of 15 residents and 8 supervisors participated in this study. All agreed that CA teaching methods can be applied across all levels. Participants experienced changes in their supervision methods and supervisor-resident interactions at different levels of training. They related the selection of supervision to task-, resident- and supervisor-related factors. Learning facilitating factors in clinical learning environment were identified and suggestions to enrich residents' learning experiences were also reported. The current study found that a one-size-fits-all paradigm may not be effective for clinical supervision. It contributes to our understanding of how the CA model may be used to guide supervisor behaviour and how such practices can be modified to residents' level of development and competencies.

Lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses

BackgroundThe integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and accuracy remains a significant challenge due to variations in data recording and reporting standards.MethodsWe developed lab2clean, a novel algorithm aimed at automating and standardizing the cleaning of retrospective clinical laboratory results data. lab2clean was implemented as two R functions specifically designed to enhance data conformance and plausibility by standardizing result formats and validating result values. The functionality and performance of the algorithm were evaluated using two extensive electronic medical record (EMR) databases, encompassing various clinical settings.Resultslab2clean effectively reduced the variability of laboratory results and identified potentially erroneous records. Upon deployment, it demonstrated effective and fast standardization and validation of substantial laboratory data records. The evaluation highlighted significant improvements in the conformance and plausibility of lab results, confirming the algorithm’s efficacy in handling large-scale data sets.Conclusionslab2clean addresses the challenge of preprocessing and cleaning clinical laboratory data, a critical step in ensuring high-quality data for research outcomes. It offers a straightforward, efficient tool for researchers, improving the quality of clinical laboratory data, a major portion of healthcare data. Thereby, enhancing the reliability and reproducibility of clinical research outcomes and clinical machine learning models. Future developments aim to broaden its functionality and accessibility, solidifying its vital role in healthcare data management.Graphical

Learning by Clinical Reasoning Versus Interactive Lecture: An Analytical and Experimental Study of Teaching Urological Emergencies

To scrutinize the progression of clinical reasoning and theoretical knowledge by comparing the impact of Clinical Reasoning-Based Learning (CRBL) sessions with interactive lectures (IL). In this experimental study conducted from November 15, 2021, to May 7, 2022, we focused on second-year students in the second cycle of medical studies. Four specific urologic emergency scenarios (nephritic colic, macroscopic hematuria, acute scrotal pain, and urinary incontinence in men) were selected for interactive teaching sessions. Four groups were studied. One urology item was taught via CRBL, the rest via IL. Each item was taught once with CRBL and thrice with IL. After instruction, learners took a 10-point evaluative test with multiple-choice questions and clinical scenarios. Four groups of 14 learners attended our department, for a total number of 56 participants. Each student attended 4 learning sessions (1 CRBL session and 3 ILs) with a number of tests completed at 4 for each. The total number of tests taken was 224. The scoring of each test was out of 10 with theoretical scores between 0 and 10. The overall median score was 7/10. We noted better ratings after the CRBL sessions (n=56) with a median of 8/10 [4-10] compared to the IL sessions (n=168) whose median was 6 [3-10] with a significant difference between the 2 learning methods (P<.001). The CRBL sessions were significantly better than the ILs at developing the clinical reasoning and theoretical knowledge in urology of our medical students.

Nursing Students' Satisfaction Regarding Clinical Learning Environment at Liaqat College of Nursing for Female

The clinical learning environment is where nursing students gain hands-on experience and apply their academic knowledge in real-world healthcare environments. The clinical learning environment is a complex system of components within a healthcare facility that influence learning outcomes. A cross-sectional study was conducted between February and March 2024 at Liaquat College of Nursing in Jamshoro, Sindh, Pakistan. The study population included Generic BSN students in their first, second, and third years. BSN Generic students who wanted to take part in this study were included. Data was collected using a non-randomized convenience sampling technique. The intended sample size was 70 nursing students selected from Liaquat College of Nursing for Female in Jamshoro. The results reveal that most BSN Generic students "agreed" with the statement that the "clinical instructor was competent and about his/her skills", with a percentage of 51.4%. Overall, the findings indicate that the clinical learning environment is satisfactory. In addition, students were satisfied with the competency of the clinical instructor, and the findings also concluded that patients in healthcare settings are adequately cared for by healthcare providers. Satisfaction in clinical settings often correlates with a deeper understanding of nursing practices. Students are more likely to engage actively, when they are content with their clinical experiences.

Leveraging the Impact of Nurses on the Educational Experience and Professional Development of the Physician Trainee.

Nurses play an essential role in the receptivity and support of the learning environment for physician trainees as they develop their clinical skills and professional identity. Although effective interprofessional teams are increasingly identified as critical to patient safety, their impact on the educational experience of learners in the clinical environment is under-recognized. We argue that highlighting nurses' contributions to physician trainee development at the start of their employment in an academic setting can encourage all providers to actively build a supportive clinical learning environment. [J Contin Educ Nurs. 2024;55(9):421-422.].