Search

Background/Objectives: Since the importance of robust theory-driven research is emphasized in medical education and little data are available on the intentions of medical and healthcare students regarding interprofessional collaboration, this study aimed to analyze the behavioral intentions of Polish medical and healthcare students to undertake interprofessional collaboration in their future work. This study follows the assumptions of the theory of planned behavior, including analysis of the students’ attitudes, subjective norms, and perceived behavioral control in this regard. Methods: Data were collected from March to July 2023 on the population of students at Poznan University of Medical Sciences (Poland) using a questionnaire developed using dedicated manuals on the theory. Results: The students demonstrated generally positive behavioral intentions and attitudes, with a mean total attitude score of 103.13 ± 33.31 in a possible range of −231 to 231. Their sense of social pressure to engage in interprofessional collaboration was weak to moderate positive, as indicated by their total subjective norm score equal on average to 57.01 ± 42.98 in a possible range of −189 to 189, or mixed when evaluated directly. Furthermore, even though they presented a neutral or moderately positive direct assessment of their perceived behavioral control, its indirect measure was weak to moderately negative, with a mean total perceived behavioral control of −80.78 ± 59.21 in a possible range of −231 to 231. Conclusions: The findings suggest that students’ perceptions of mixed social pressure and the presence of barriers or obstacles to collaboration may negatively impact their perceived ease and willingness to collaborate, even despite their initially positive attitudes towards it.

The abrupt transition from the traditional model of medical education to online learning caused by the COVID-19 pandemic led to unprecedented changes in the education of future healthcare professionals. This study aimed to evaluate the opinions of Polish healthcare students on the changes introduced due to the COVID-19 pandemic and propose recommendations for improvement. Data were collected from June to July 2020 using an online questionnaire. The results demonstrate that students were generally satisfied with the online learning solutions implemented during the pandemic and appreciated their teachers’ efforts. In their opinion, some of the solutions should also be continued after the pandemic. Students noticed positive aspects of online learning: time efficiency, bigger student-friendliness and unlimited attention from teachers, the flexibility of the learning process, better learning conditions for students, and absences due to illness and other random situations. However, they also noticed its disadvantages: problems with the Internet connection and technical aspects, attitudes of teachers, limited interpersonal relations, limited learning of practical skills, health concerns, students’ engagement and distractions at home, and assessment. To conclude, our results indicate some necessary recommendations to improve the quality of further online learning in medical schools during the COVID-19 pandemic.

Multiple choice questions (MCQs) are commonly used for assessing students, but medical teachers may lack training in writing them. MCQs often have imperfections called item-writing flaws (IWFs) that can affect students’ results and impede objective evaluation of their knowledge. This study aimed to evaluate a guideline-based faculty development intervention on writing MCQs at Levels 1 and 2 of the Kirkpatrick Model. MCQs written by teachers prior and after the intervention were analyzed with the Shapiro–Wilk test, Student’s t -test, and Wilcoxon signed-rank test as appropriate. In addition, the phenomenological approach was chosen to describe experiences of 10 teachers in semi-structured in-depth interviews. Results showed satisfaction of teachers with the document. They found it helpful in writing MCQs and noticed the requirement for another guidelines. They appreciated it for its briefness and clarity. The statistical analysis of the quality of MCQs before and after the intervention showed that the document contributed to a statistically significant reduction of IWFs. To conclude, our results showed that a guideline document on writing MCQs may serve as a well-received and effective faculty development intervention. The document may be used as a flexible, time-saving, and just-in-time learning method, fitting needs of medical teachers.

The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learning (ML) algorithms can process vast amounts of data to uncover informative patterns and relationships within the data, even with limited prior knowledge. Therefore, there has been a rapid growth in the development of software specifically designed for the analysis and interpretation of microbiome data using ML techniques. These software incorporate a wide range of ML algorithms for clustering, classification, regression, or feature selection, to identify microbial patterns and relationships within the data and generate predictive models. This rapid development with a constant need for new developments and integration of new features require efforts into compile, catalog and classify these tools to create infrastructures and services with easy, transparent, and trustable standards. Here we review the state-of-the-art for ML tools applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on ML based software and framework resources currently available for the analysis of microbiome data in humans. The aim is to support microbiologists and biomedical scientists to go deeper into specialized resources that integrate ML techniques and facilitate future benchmarking to create standards for the analysis of microbiome data. The software resources are organized based on the type of analysis they were developed for and the ML techniques they implement. A description of each software with examples of usage is provided including comments about pitfalls and lacks in the usage of software based on ML methods in relation to microbiome data that need to be considered by developers and users. This review represents an extensive compilation to date, offering valuable insights and guidance for researchers interested in leveraging ML approaches for microbiome analysis.

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.

The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 “ML4Microbiome” that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.

The number of microbiome-related studies has notably increased the availability of data on human microbiome composition and function. These studies provide the essential material to deeply explore host-microbiome associations and their relation to the development and progression of various complex diseases. Improved data-analytical tools are needed to exploit all information from these biological datasets, taking into account the peculiarities of microbiome data, i.e., compositional, heterogeneous and sparse nature of these datasets. The possibility of predicting host-phenotypes based on taxonomy-informed feature selection to establish an association between microbiome and predict disease states is beneficial for personalized medicine. In this regard, machine learning (ML) provides new insights into the development of models that can be used to predict outputs, such as classification and prediction in microbiology, infer host phenotypes to predict diseases and use microbial communities to stratify patients by their characterization of state-specific microbial signatures. Here we review the state-of-the-art ML methods and respective software applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on the application of ML in microbiome studies related to association and clinical use for diagnostics, prognostics, and therapeutics. Although the data presented here is more related to the bacterial community, many algorithms could be applied in general, regardless of the feature type. This literature and software review covering this broad topic is aligned with the scoping review methodology. The manual identification of data sources has been complemented with: (1) automated publication search through digital libraries of the three major publishers using natural language processing (NLP) Toolkit, and (2) an automated identification of relevant software repositories on GitHub and ranking of the related research papers relying on learning to rank approach.

Abstract Background Changes in Polish demographic data with a growing number of culturally and linguistically diverse patients stipulate new directions in medical education to prepare future physicians to work effectively across cultures. However, little is known about Polish medical students’ willingness to gain cross-cultural knowledge and skills, desire to get engaged in interactions with patients from diverse cultural backgrounds, expectations and needs concerning cross-cultural training as well as challenges they face in the path to cultural competence. Methods Therefore, in this study, we conducted and thematically analysed fifteen semi-structured interviews with medical students to broaden our understanding of medical students’ perception of cross-cultural competence enhancement. Results The conducted thematic analysis allowed for the development of four themes, which showed that Polish medical students perceived skills and knowledge necessary to facilitate culturally congruent care as indispensable to form quality patient-doctor relations, believed that lack of cultural sensitivity may lead to dangerous stereotype formation and insufficient competence may be the source of stress and anxiety resulting in confusion and lack of confidence. Finally, numerous suggestions have been made by participants on how to improve their cross-cultural competence. Students emphasized, however, the role of medical education with active and experiential learning methods, including simulation-based training, in the process of equipping them with the knowledge and skills necessary to provide best quality care to culturally diverse patients. Conclusions Our analysis indicated that Polish medical students seem to hold positive attitudes towards cultural competence development and view it as an important component of physician professionalism.

Given the limited and scattered data on nursing students’ behavioral intentions regarding interprofessional collaboration and the factors influencing them, there is a need for comprehensive, theory-driven research on the topic from nursing students’ perspectives. Using a theoretical framework provided by the theory of planned behavior, this study aimed to evaluate the behavioral intentions of Polish nursing students regarding interprofessional collaboration, including their attitudes, subjective norms, and perceived behavioral control. Sixteen nursing students participated in semi-structured interviews. Data were collected on the MS Teams application between February and May 2022 using a thematic guide created following manuals dedicated to the theory. They were thematically analyzed by two researchers using Atlas.ti Software. The results showed that students’ attitudes were mostly positive. The benefits of interprofessional collaboration included positive patient outcomes, exchange of mutual knowledge and expertise, comfort, and improved work atmosphere. The risks originating from human-dependent factors were viewed as a negative aspect. The relevant groups of people influencing their subjective norms comprised nursing community representatives, other medical professionals, patients, and members of society. Perceived behavioral control aspects covered the work organization, lack of incentives for collaboration, atmosphere and habits prevailing in the workplace, and insufficient practical experience and knowledge regarding collaboration. To conclude, although positive attitudes expressed by nursing students seem to constitute a positive predictor of their involvement in interprofessional collaboration, relevant decision-makers should address negative feelings and aspects identified during this study.

Abstract Background The transformation of a pharmacist’s role from that of a drug dispenser to an advisor and patient educator, partially accelerated by the COVID-19 pandemic, requires a thorough change in the pharmacy curriculum. Preparation for the provision of modern pharmaceutical services requires the use of the most advanced teaching methods, such as pharmaceutical simulation. Knowledge alone does not guarantee students’ readiness and motivation to take on new challenges in their professional work, but it seems crucial that graduates of medical faculties have the ability to practically apply their knowledge, including in new and nonstandard situations. Therefore, in our study, we proposed an intervention using a simulation method (peer role play) in teaching pharmaceutical care, and we assessed its impact on students’ levels of self-perceived confidence and self-efficacy in accordance with Bandura’s theory. The aim of the study was to verify whether the introduction of these types of classes could be a useful element of pharmacy curriculum renewal. Methods The questionnaire-based study was conducted during pharmaceutical care peer role-playing classes in a simulation environment with a debriefing session among 85 final-year pharmacy students at Poznan University of Medical Sciences, Poland. The questionnaire consisted of two surveys: the General Self-Efficacy Scale (GSE) and a pre-post self-assessment and self-efficacy questionnaire. Results There was a positive correlation between the GSE score and self-efficacy (R = 0.52, p

Abstract Background Patients with asthma and chronic obstructive pulmonary disease could benefit from education on using inhalers provided by pharmacists. However, pharmacists may have limited competencies, indicating the necessity to implement appropriate postgraduate courses. The study aimed to evaluate an inhaler use course for pharmacists, including its impact on participants’ knowledge and satisfaction. Methods The study involved 261 pharmacists from community pharmacies and was conducted between September 2019 and March 2021. A pre-post analysis of their knowledge of the topic was applied. Additionally, at the beginning of the course, participants were asked about their educational needs, and at the end, they completed a satisfaction survey. The preferred learning formats indicated by participants were interactive workshops and lectures. Results As a result of the course, both their actual and self-assessed level of knowledge significantly increased. The percentage of correct answers in the test before the training was 24.4%, while after, it was 84.3% (p

Abstract Background Interprofessional collaboration enhances the use of competencies of different medical team members. Additionally, pharmacists’ involvement in patient care has been shown to improve their outcomes and seems particularly valuable in chronic diseases. Therefore, due to the aging of society and the increasing prevalence of chronic diseases, efforts are needed to involve pharmacists more broadly in patient care. However, there is a limited understanding of what factors could influence their willingness to participate in an interprofessional care team, especially among pharmacy students only entering the profession. This study aimed to fill these knowledge gaps by exploring graduating pharmacy students’ intentions in this regard guided by the theory of planned behavior. Methods We conducted seventeen semi-structured interviews with graduating pharmacy students of Poznan University of Medical Sciences, which were then thematically analyzed by two researchers. Results Positive attitudes of respondents, who mentioned the possibility of acquiring new knowledge, skills, and competencies, increased prestige and appreciation of the pharmacist’s profession, a better quality of patient care, and the support and relief offered to other team members as a result of collaboration, seem to strengthen their intentions. However, they also expressed their worries about potential errors and knowledge gaps, which constituted an example of some existing negative feelings. The identified sources of generally mixed social pressure toward the behavior included other pharmacists and pharmacy students, physicians, patients, their relatives and friends, and the decision and policymakers. Finally, their intentions may also be weakened by the mentioned perceived behavioral control aspects, like their level of pharmaceutical and clinical knowledge, skills, and experience, their knowledge of representatives of other professions and collaboration, the atmosphere at their future place of work, co-workers’ potential reluctance to collaborate with them, finding time for collaboration, the existence of incentives and gratification system, and existing legal regulations. Conclusions The attitudes of graduating pharmacy students toward interprofessional collaboration seem mostly positive, but their intentions might be weakened by the mixed sense of social pressure and factors decreasing their perceived behavioral control.

Abstract Background The diversity of tasks entrusted to medical teachers with their simultaneous responsibility for the safety of patients and the effective education of future healthcare professionals requires maintaining a skillful balance between their teaching, scientific and clinical activities. Meanwhile, the COVID-19 pandemic disrupted the work of both healthcare facilities and medical universities, forcing already overworked medical teachers to establish a new balance. One’s ability to perform effectively in new, ambiguous, or unpredictable situations was described by Albert Bandura as a self-efficacy concept. Consequently, this study aimed to identify factors affecting the self-efficacy of medical teachers and the influence of the COVID-19 pandemic on them. Methods Twenty-five semi-structured interviews with medical teachers were conducted using a flexible thematic guide. They were transcribed and analyzed by two independent researchers (researcher triangulation) with phenomenology as the qualitative approach. Results Identified themes demonstrate a process of the evolvement of clinical teachers’ self-efficacy in response to the sudden outbreak of the COVID-19 pandemic, namely the decline of self-efficacy in the first phase of the crisis, followed by building task-specific self-efficacy and the development of general self-efficacy. Conclusions The study shows the significance of providing care and support for medical teachers during a health crisis. Crisis management decision-makers at educational and healthcare institutions should consider the different roles of medical teachers and the possibility of overburden associated with the cumulation of the excessive number of patient, didactic, and research duties. Moreover, faculty development initiatives and teamwork should become a vital part of the organizational culture of medical universities. A dedicated tool acknowledging the specificity and context of medical teachers’ work seems necessary to quantitatively evaluate their sense of self-efficacy.

Abstract Background Interprofessional collaboration constitutes a vital part of modern patient care, and many of its benefits for patients, medical staff, and the healthcare system have been described. However, little is known about factors influencing medical students’ intentions to work in a collaborative practice after graduation. Therefore, with the theory of planned behavior by Ajzen as a framework, this study aimed to evaluate their intentions and identify factors that influence their attitudes, subjective norms, and perceived behavioral control. Methods For this purpose, eighteen semi-structured interviews were conducted with medical students following a thematic guide developed according to the theory. They were thematically analyzed by two independent researchers. Results The results showed that their attitudes contained positive (better patient care, comfort and safety of work, learning and development opportunities) and negative examples like the fear of conflicts, losing authority and mistreatment. Sources of social pressure regarding the behavior (subjective norms) involved their peers, other physicians, representatives of other medical professions, patients, and managing bodies. Finally, perceived behavioral control included limited occasions for contacts and interprofessional learning during the studies, existing stereotypes and prejudices, legal regulations and systemic solutions, organizational aspects, and existing relations at the ward. Conclusions Analysis showed that Polish medical students generally seem to hold positive views on interprofessional collaboration and feel positive social pressure to get involved in interprofessional teams. However, factors listed in perceived behavioral control may act as barriers in the process.

Abstract Background Ajzen’s theory of planned behavior (TPB) postulates that individuals’ behavioral intention is influenced by their attitudes, subjective norms, and perceived behavioral control. Therefore, it can be used to broaden the understanding of particular behaviors, including healthcare workers’ professional activities. Methods In this study, we used TPB as a theoretical framework to evaluate semi-structured interviews with pharmacists and physicians to build an understanding of the interprofessional collaboration between them. Sixteen semi-structured interviews were conducted with pharmacists and eleven with physicians. The sample of participants comprised a diverse group with varying work experience and workplaces. Data were analyzed independently by two researchers following the thematic analysis method using ATLAS.ti software. Data saturation was set in the absence of new issues arising during the interviews. Results The content analysis allowed for the determination of six main themes: the relationship between previous experiences and attitudes towards collaboration, pharmacist’s role in collaboration, mutual reluctance toward collaboration, the role of decision- and policy-makers, knowledge and qualifications gaps regarding collaboration, and lack of organizational paths. Conclusions Despite both physicians and pharmacists displaying positive attitudes towards collaboration may foster their intention to establish a professional partnership, subjective norms (e.g., the lack of appropriate legal regulations) and perceived behavioral control (physicians’ lack of awareness about pharmacists’ qualifications and the low level of interpersonal skills) might impede the process.

Abstract Background The Communication Skills Attitude Scale (CSAS) is a recognized tool for assessment of attitudes towards communication learning. In the original version, it consists of 26 items divided on theoretical assumptions into two subscales: Positive and Negative Attitudes Scales. However, the evidence for its structure seems unsatisfactory, and a simple division into positive and negative attitudes may be insufficient to describe attitudes of medical students towards communication learning. Moreover, the existing evidence of the test-retest reliability of the CSAS seems limited. Consequently, this study aimed to provide more evidence on its psychometric properties while validating the CSAS questionnaire in a cohort of Polish medical students. Methods The CSAS was translated, adapted into Polish, and validated in a cohort of 389 Polish medical students. Statistical analysis involved, among others, parallel analysis to determine the number of factors, confirmatory factor analysis to compare the proposed model with theory-based ones, and test-retest reliability analysis. Results Conducted analysis revealed that in the examined population, the CSAS should rather consist of four than two subscales. Proposed four subscales addressed perceived outcomes of communication learning, positive and negative attitudes towards it (affective components), and factors motivating students to learn communication (a cognitive component of attitudes). Results of test-retest reliability were satisfactory for individual items and subscales. Conclusions This study presented a valid and reliable version of the Communication Skills Attitude Scale for Polish medical students and confirmed previous assumptions that CSAS may also be appropriate for assessment of affective and cognitive components of attitudes. Future research should, based on Ajzen’s Theory of Planned Behavior, make attempts to develop a tool assessing not only attitudes but also subjective norms and perceived behavioral control.