Post-pandemic American travelers' behavior given a chikungunya outbreak

Introduction: Mosquito-borne diseases have historically affected communities, especially in tropical areas where mosquitoes and illnesses are endemic. Globalization, climate change, and increased travel have created ideal conditions for outbreaks of mosquito-borne diseases that could threaten the American health system and place a burden on the national economy, especially in southern states. Methods: The study adopts a quantitative cross-sectional design with a retrospective survey carried out using the Pollfish platform in June 2022. The data were analyzed using descriptive statistics and hierarchical multiple regression to assess the three hypotheses: (H1) Chikungunya awareness is related to sociodemographic factors;(H2) Wearing long sleeves and pants is related to (a) Chikungunya awareness and (b) information-seeking behaviors, when controlling for sociodemographic variables;(H3) Use of insect repellents is related to (a) Chikungunya awareness and (b) information-seeking behaviors when controlling for sociodemographic variables. Results: The results highlight the relationships between chikungunya's awareness, information-seeking behavior, and willingness to engage in protective behaviors. 45.91% of the participants mentioned not having heard about chikungunya, and 67.07% of respondents had sought information about mosquito-borne illnesses in the past, 55.9% have looked at the U.S. State Department's website for mosquito-borne diseases, 38.32% have visited the U.S. CDC website for information specifically about chikungunya. Conclusions: The results of this study show that most American travelers are unaware of chikungunya and its mode of transmission. Travel could likely introduce the chikungunya virus to the United States. Despite increased health information-seeking behavior among U.S. residents after the Covid19 pandemic, Chikungunya awareness is low.

Applications of xylitol in food, material, health, and medical sector

Xylitol is considered as one of the top relevant biorefinery sugar-derived products due to its interesting properties and its use has already been approved in more than forty countries. This polyol is mainly recognized in the food sector due to its sweetness equivalent to sucrose but with a significantly lower glycemic index. A great variety of products formulated with xylitol can be found in the market, being most industrially applied in chewing gum production. However, xylitol has others interesting properties, with several clinical applications, acting both on the prevention and treatment of diseases, such as cardiovascular diseases, otitis and diabetes. This chapter comprehensively presents the established and in development xylitol applications, from food to medical sector, including recently discovered COVID-19 treatment potential, and chemical industries applications, exploring xylitol-based materials and its use on tissue-engineering. In addition, xylitol safety and side effects are explored, including the main policies regarding its use. © Springer Nature Switzerland AG 2022. All rights reserved.

Incidental tomographic findings in patients with a Confirmed Diagnosis of COVID-19: An Observational Study

Objective: Describe incidental tomographic in the sample, correlating them with risk factors for chest diseases and sociodemographic data. Method(s): This is a retrospective and observational study covering 162 patients admitted to the COVID sector of the HU/UFJF, from April 1, 2020, to July 7, 2021, with a confirmed laboratory diagnosis of COVID-19. The variables were described in absolute and relative frequencies. The comparison of the correlation between the outcome variable (the tomographic findings) for independent samples was performed using Pearson's chi-square test (without correction) or Fisher's test when relevant. Result(s): Of the 162 patients, 15.4% had a solitary pulmonary nodule;14.8% had multiple pulmonary nodules;1.8%, lung mass;3.1%, mediastinal mass, and 9.3% had mediastinal adenomegaly. Findings such as excavations, pleural effusion, emphysema, PTE, pneumothorax, chronic interstitial disease, cavitation, aneurysms, and significant atheromatosis, classified in this study in the "Other" category showed impressive results, with an overall prevalence of 81.5%. This study demonstrated that 34% of patients had two or more types of incidental CT findings and that 88.3% of patients had at least some type of incidental CT finding. Conclusion(s): The pandemic of SARS-CoV-2 infections has brought a series of challenges and lessons learned to healthcare teams around the world. The massive implementation of highly sensitive diagnostic methods, such as chest tomography, ends up bringing an additional challenge, which is to deal with incidental findings, making good clinical reasoning necessary to avoid unnecessary investigations and not leave without diagnosis and treatment of diseases in early and asymptomatic stages.Copyright © 2023 Faculdade de Medicina de Ribeirao Preto - U.S.P.. All rights reserved.

Analyzing the impact of the covid epidemic on beach access traffic

The covid 19 epidemic has been marking the pace of life around the world for the last two years, and it left clear marks on economic activity, our social life and even the pollution associated with human activity. One of the consequences is related to the decrease in car traffic, especially in the months of mandatory social confinement. This work analyzes the impact of the epidemic on traffic regarding access to the beaches of Barra and Costa Nova in the region of Aveiro, Portugal, through the infrastructure of the PASMO project. Therefore, the weekly and weekend traffic profiles evolution were analyzed over the various months of 2020. The work also compared the evolution of infections with the evolution of road traffic, as well as the impact of the various events related to the epidemic in road traffic.

TEXT SUMMARIZATION AS AN EMPIRICAL LEGAL RESEARCH TOOL BASED ON MACHINE LEARNING ALGORITHMS

This paper aims to explore text summarization techniques as a tool for empirical legal research, creating a summary of the decisions given the phrases predictive power with regard to the decision outcome. A dataset of habeas corpus decisions prompted by innumerable courts in Brazil is used that explicitly cite the COVID pandemic as a reason for requesting the release of the patients. A predictive model is created and through this analysis we propose to find the arguments most correlated with the outcome. © 2022 Universidad Diego Portales. All rights reserved.

AI-Based mHealth App for Covid-19 or Cardiac Diseases Diagnosis and Prognosis

Covid-19 has rapidly spread and affected millions of people worldwide. For that reason, the public healthcare system was overwhelmed and underprepared to deal with this pandemic. Covid-19 also interfered with the delivery of standard medical care, causing patients with chronic diseases to receive subpar care. As chronic heart failure becomes more common, new management strategies need to be developed. Mobile health technology can be utilized to monitor patients with chronic conditions, such as chronic heart failure, and detect early signs of Covid-19, for diagnosis and prognosis. Recent breakthroughs in Artificial Intelligence and Machine Learning, have increased the capacity of data analytics, which may now be utilized to remotely conduct a variety of tasks that previously required the physical presence of a medical professional. In this work, we analyze the literature in this domain and propose an AI-based mHealth application, designed to collect clinical data and provide diagnosis and prognosis of diseases such as Covid-19 or chronic cardiac diseases. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The role of cardiac troponin-I as a prognostic tool for mortality in patients hospitalized with COVID-19

Background: Coronavirus disease 2019 (COVID-19) has been associated with significant morbidity and mortality, with cardiovascular involvement being usual. Elevations in cardiac Troponin-I level has proposed as an independent biomarker for mortality among patients with COVID-19. Aim(s): To evaluate the role of high sensivity Troponin-I (hs-TnI) level at hospital admission in predicting 30 day in-hospital mortality and 6-month mortality in patients hospitalized with a COVID-19 diagnosis. Method(s): We performed a retrospective single-center cohort study including consecutive patients aged 18 years and older who were admitted for COVID-19, during a 1-year period (n=818). We excluded patients with acute coronary syndrome (n=23), patients with acute heart failure (n=42), and patients in which hs-TnI level was not dosed at admission (n=163). Patients were divided into two groups according to hs-TnI levels: Hs-TnI <19.8 vs hs-TnI >=19.8 pg/mL. Primary outcomes were 30-day in-hospital mortality and 6-months mortality. According to the data distribution, appropriate statistical tests were conducted to compare independent samples. Multivariable logistic regression was used to analyze mortality risk. Receiver operator characteristics (ROC) curve and area under the curve (AUC) were obtained to determine the discriminative power of hs-TnI as a predictor of mortality. (Figure 1). Result(s): This cohort included 590 patients. Mean age was 71 >=+/-15 years and 52.4% were men. Overall, 209 patients (35.4%) had elevated hs- TnI levels and 381 patients had normal hs-TnI levels. Individuals in the hs-TnI >=19.8 pg/mL group were older (80+/-11 vs 66+/-14 years, p<0.001) and presented higher prevalence of chronic heart failure (24.9% vs 7.1%, p<0.001), hypertension (77.0% vs 57.5%, p<0.001), atrial fibrillation/flutter (19.1% vs 5.5%, p<0.001), prior stroke (12.4% vs 5.2%, p=0.001) and ischemic heart disease (12.4% vs 3.7%, p<0.001). There was no difference in length of hospital stay between the groups (8.0 [IQR 9.6] in hs-TnI 19.8 pg/mL group vs 9.0 [IQR 8.0] normal hs-TnI group, p=0.669). Troponin-I was the only independent predictor of in-hospital mortality (OR 3.80, CI 95%: 2.44-5.93, p<0.001), see Table 1. The troponin levels had the highest area under the receiver operating characteristic curv (AUC) with an AUC of 0.705 (95% CI: 0.667-0.742, p<0.001) for association with the inhospital mortality (figure 1). There was no difference in 6-months mortality between the two groups. Conclusion(s): Acute myocardial injury is common in patients hospitalized with COVID-19. In the present study a TnI level >=19.8 pg/mL was predictor of 30 days in-hospital mortality, suggesting that raised levels of this biomarker is associated with adverse prognosis. This tool might be useful for COVID-19 patient risk stratification. Further studies are needed to provide robust data and reliable recommendations on this theme.

Implementing a Data Integration Infrastructure for Healthcare Data – A Case Study

Conducting epidemiologic research usually requires a large amount of data to establish the natural history of a disease and achieve meaningful study design, and interpretations of findings. This is, however, a huge task because the healthcare domain is composed of a complex corpus and concepts that result in difficult ways to use and store data. Additionally, data accessibility should be considered because sensitive data from patients should be carefully protected and shared with responsibility. With the COVID-19 pandemic, the need for sharing data and having an integrated view of the data was reaffirmed to identify the best approaches and signals to improve not only treatments and diagnoses but also social answers to the epidemiological scenario. This paper addresses a data integration scenario for dealing with COVID-19 and cardiovascular diseases, covering the main challenges related to integrating data in a common data repository storing data from several hospitals. Conceptual architecture is presented to deal with such approaches and integrate data from a Portuguese hospital into the common repository used to explore data in a standardized way. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Mental Health Issues and Life Conditions of Adolescents with Juvenile Dermatomyositis and Other Autoimmune Rheumatic Diseases during Covid-19 Quarantine

Background. Autoimmune rheumatic diseases (ARD) include various chronic conditions with high morbidity and mortality rates, and an increased risk of infections, including the new COVID-19. It is possible that adolescents with ARD have higher levels of psychological distress which may affect their mental health and life conditions. The objectives were to assess mental health and life conditions in adolescents with autoimmune rheumatic diseases (ARD) and healthy controls in social isolation, emphasizing some demographic aspects and daily routine of adolescents with juvenile dermatomyositis (JDM) during the COVID-19 quarantine. Methods. A cross-sectional study, performed from July 2020 to October 2020, included 155 ARD adolescents and 105 healthy controls. Online survey composed by self-reported strengths and difficulties questionnaire (SDQ) and a semi-structured questionnaire was filled in regarding demographic data, daily home and school routine, physical activities and COVID-19 information during the pandemic. Results. The patients included in the study presented the following underlying diseases: 15% JDM, 29% juvenile systemic lupus erythematosus (JSLE) and 56% juvenile idiopathic arthritis (JIA). Among adolescents with JDM, 71% were female, 54% Caucasian and the median age was 14 years (range 10-18). Regarding school data, 92% JDM participants attended school before pandemic, 75% studied in public schools and up to 17% did not present home schooling during the quarantine. All JDM patients agreed with stay-home policy after pandemic outbreak, and they reported change in life routine (96%), sleep problems (29%), sleep after midnight (75%) and increased screen time (87%). Worsening of family financial situation (37%) and increased family violence (8%) were also observed. Concerning mental health assessment, it was verified that one third of JDM subjects presented abnormal total difficulties and emotional scores of SDQ. No differences were found regarding sex, ethnicity and current age between ARD patients and controls (p>0.05). The frequencies of abnormal SDQ total (32% vs. 32%, p=0.901) and emotional (38% vs. 35%, p=0.653) were similar in both groups. Logistic regression analyses in ARD patients demonstrated that female (OR=2.4;95%CI 1.0-6.0;p=0.044) was associated with severe emotional SDQ dysfunction, whereas poor sleep quality was considered risk factor for both worse total SDQ (OR 2.6;95% CI 1.2-5.5;p=0.009) and emotional SDQ scores (OR=4.6;95%CI 2.2-9.7;p<0.001). Comparisons between ARD patients with and without current prednisone use showed higher median scores of peer problems in the first group [3(0-10) vs. 2(0-7), p=0.049]. The median and frequencies of SDQ scores and domains were similar between JDM, JSLE and JIA (p>0.05). Conclusions. Approximately one third of JDM, JSLE and JIA patients presented abnormal total difficulties and emotional scores of SDQ. Female sex and poor sleep quality were the main factor associated with emotional impact in these ARD adolescents.

The Higher Education Teacher and the New Challenges of Teaching in the Context of Digital Technologies: A Socio-Cognitive Approach

This article aims to analyze the metaphorical meanings that higher education teachers have attributed to digital technologies in the context of the COVID-19 pandemic. Our qualitative research is a phenomenological study using reports produced by faculty members from nine public universities in the North/Northeast of Brazil on the Google Forms platform as an instrument for the generation of data. The study assumes a socio-cognitive view of language, focused on the theoretical contribution of Cognitive Linguistics, with a conceptual metaphor approach, directed at corpus and discourse. Using the target-domain method to identify metaphors based on the corpus, those with a negative nature, such as exclusion and despair, stand out more frequently. © 2022 Centro de Estudos Sociais da Universidade de Coimbra. All rights reserved.

Wearable Temperature Sensor and Artificial Intelligence to Reduce Hospital Workload

Patient sensing and data analytics provide information that plays an important role in the patient care process. Patterns identified from data and Machine Learning (ML) algorithms can identify risk/abnormal patients' data. Due to automatization this process can reduce workload of medical staff, as the algorithms alert for possible problems. We developed an integrated approach to monitor patients' temperature applied to COVID-19 elderly patients and an ML process to identify abnormal behavior with alerts to physicians. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Hospitalised patients with COVID-19: the impact of nosocomial infections

Introduction: COVID-19 is a disease caused by the SARS-CoV-2 virus. Healthcare-associated infections (HCAI) are infections acquired during a stay in a hospital or other healthcare setting that were not incubating at the time of admission. Objective(s): To describe the impact of HCAI in hospitalised patients with COVID-19. Method(s): A retrospective and descriptive study of hospitalised patients with COVID-19 in a Portuguese hospital in 2020 was conducted. Result(s): The sample consisted of 1110 patients of whom 229 acquired HCAI. The main comorbidities were hypertension 62.45% (n=143), obesity 24.01% (n=55), arrhythmias 20.52% (n=47), ischaemic heart 11.35% (n=26) and heart failure 16.16%. Infectious agents were isolated in 27.95% (n=64), with Escherichia coli and Klebsiella pneumoniae being the most frequent. HCAI's classification were: 5.68% (n=13) nosocomial bacteraemia 31.89% (n=73);urinary tract infection 54.15% (n=124);hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia 8.28% (n=19). Ventilatory support required: 14.85% (n=34) didn't require, 49.34% (n=113) conventional oxygen therapy (COT);2.62% (n=6) high flow therapy, 3.06% (n=7) non-invasive ventilation, 16.16% (n=37) HelmetCPAP, 12.66% (n=29) invasive mechanical ventilation (IMV) and 1.31% (n=3) ECMO. The mean number of days of admission was 14.84 (+/-13.67). The probability of death HCAI's patients was OR 1.63, 95% CI 1.154-2.304. Conclusion(s): The sample shows a high incidence of nosocomial infections. The most frequent HCAI were HAP mainly with clinical diagnosis. Clinical stabilisation of comorbidities and COT were effective for most patients but IMV and Helmet-CPAP for the most severe. HCAI are a high risk factor for mortality.

COPD and COVID-19: a dangerous association?

Introduction: Chronic obstructive pulmonary disease (COPD) is the most common chronic respiratory disease. Currently, there is no clear evidence that COPD increases Coronavirus disease 2019 (COVID-19) susceptibility or if it is a risk factor for developing more severe COVID-19. Objective(s): To describe the characteristics of patients hospitalized for COVID-19 with a pre-existing diagnosis of COPD. Method(s): A retrospective and descriptive study of patients hospitalized with COVID-19 during 2020 in a Portuguese hospital. Result(s): The study included 1,110 individuals. Of these, 8.92% (n=99) had pre-existing COPD. 64.65% (n=64) were male with mean ages 76,16 (+/-10.4) and 35.35% (n=35) were female with mean ages 81,43 (+/-9.1). The comorbidities were: high blood pressure 67.68% (n=67), diabetes mellitus 30.30% (n=30), heart failure 26.26% (n=26), obesity 24.24% (n=24), arrhythmias 24.24% (n=24), stroke 11.11% (n=11), ischemic heart disease 11.11% (n=11). Regarding the respiratory support: no respiratory support 15.15% (n=15), conventional oxygen therapy 56.57% (n=56), Highflow therapy 3.03% (n=3), Non-invasive ventilation 12.12% (n=12), Helmet-CPAP 11.11% (n=11) and Invasive mechanical ventilation 2.02% (n=2). The mortality rate for COPD's patients was 20.20% (95% CI 29.06-11.36), while the mortality rate for patients without COPD was 18.69 (95% CI 16.03-21.36). The estimated risk of death was calculated for patients with COPD [OR 1.11 (95% CI 0.66-1.86)]. Conclusion(s): COPD's patients are mostly ederly men with comorbidities. The most effective treatment for them was stabilization of comorbidities and conventional oxygen and for the most severe Helmet-CPAP and NIV. In addition, COPD patients had no higher risk of mortality from COVID-19 than individuals without a pre-existing diagnosis of COPD.

Talent management in the "new normal”—Case study of Indian IT services multinationals in China

Emerging market multinational corporations (MNCs) are coming under increasing scrutiny for their international performance. While the success of Indian IT multinationals in the West has been extensively researched and reported, there is a lack of research on their relative failure in China. The rise of economic nationalism and the COVID-19 pandemic pose challenges for the mobility of professionals and the global talent management (GTM) strategy of MNCs. Through in-depth interviews with senior managers from four well-known Indian IT services multinationals, this article presents an evidence-based critique of the design and implementation of their GTM strategy both inside and outside China. It focuses specifically on the quality of the IT talent pool in China, control and coordination issues, and the challenges of workforce localization. © 2021 Wiley Periodicals LLC.

[Actual adherence to dimethyl fumarate in patients with relapsing-remitting multiple sclerosis]. / Adhesión real al dimetilfumarato en pacientes con esclerosis múltiple remitente-recurrente.

INTRODUCTION: Multiple sclerosis is a chronic neurological disease with numerous disease-modifying treatments available, including dimethyl fumarate (DMF), a first-line therapy for relapsing-remitting multiple sclerosis. Although rates of discontinuation of DMF are generally low in clinical trials, non-adherence to treatment is associated with poorer clinical outcomes. Assessing real-world adherence and predictive factors is critical to be able to improve clinical outcomes for patients. This study evaluated adherence to DMF over 24 months in a cohort of patients treated in a Portuguese healthcare centre. PATIENTS AND METHODS: A prospective, non-interventional, single-centre study with 24 months' follow-up was conducted. The study included adult patients with relapsing-remitting multiple sclerosis treated with DMF in routine clinical practice. Adherence to DMF was calculated and patients were considered to have adhered if the value was above 80%. Clinical and socio-demographic variables were compared between groups. RESULTS: Of the 80 patients included, 74% were women, with a mean age of 39 years and a mean age of 32 years at diagnosis. Twenty-six patients had not received any previous treatment. Adherence varied between 93, 82 and 87.5% at 6, 12 and 24 months, respectively. No differences were found between patients who had not received any prior treatment and those who had been treated. CONCLUSION: This real-world analysis showed significant adherence to DMF treatment by Portuguese patients over a period of two years. However, these results must be interpreted in the light of the substantial changes in outpatient consultations and the various periodic restrictions due to the COVID-19 pandemic, which had an important effect on patient follow-up and data collection.

TITLE: Adhesión real al dimetilfumarato en pacientes con esclerosis múltiple remitente-recurrente.Introducción. La esclerosis múltiple es una enfermedad neurológica crónica con numerosos tratamientos modificadores de la enfermedad disponibles, incluido el dimetilfumarato (DMF), una terapia de primera línea para la esclerosis múltiple remitente-recurrente. Aunque las tasas de discontinuación del DMF suelen ser bajas en los ensayos clínicos, la falta de adhesión al tratamiento se asocia con peores resultados clínicos. Evaluar la adhesión en el mundo real y los factores predictivos es fundamental para mejorar los resultados clínicos de los pacientes. Este estudio evaluó la adhesión al DMF durante 24 meses en una cohorte de pacientes tratados en un centro portugués. Pacientes y métodos. Estudio prospectivo no intervencionista, de un solo centro, con un seguimiento de 24 meses. El estudio incluyó a pacientes adultos con esclerosis múltiple remitente-recurrente tratados con DMF en la práctica clínica habitual. Se calculó la adhesión al DMF y se consideró que los pacientes eran adherentes si el valor estaba por encima del 80%. Se compararon variables clínicas y sociodemográficas entre grupos. Resultados. De los 80 pacientes incluidos, el 74% eran mujeres, con una edad media de 39 años y una edad media en el momento del diagnóstico de 32 años. Veintiséis pacientes no habían recibido tratamiento previo. La adhesión varió entre el 93, el 82 y el 87,5% a los 6, 12 y 24 meses, respectivamente. No se encontraron diferencias entre los pacientes que no habían recibido tratamiento previo y los que sí lo habían recibido. Conclusión. Este análisis en el mundo real mostró una adhesión significativa al tratamiento con DMF durante dos años por parte de los pacientes portugueses. No obstante, estos resultados deben interpretarse considerando los cambios sustanciales en las consultas externas y las diversas restricciones periódicas debidas a la pandemia de COVID-19, que afectaron en gran medida al seguimiento de los pacientes y a la recopilación de datos.

University and Industry Collaboration in the Era of Smart Specialisation: Empirical Research on Sustainable Knowledge Transfer

The coronavirus disease-19 pandemic has forced universities worldwide to develop stronger crisis responses in order to support the surrounding communities more effectively. These solutions are based on collaborations between higher education institutions and industries that facilitate knowledge co-creation. Historically, universities have been knowledge-intensive institutions capable of producing additional findings through research. Currently, these organisations' most important contributions to national economies are related to universities' development of fresh knowledge and technical expertise. In parallel, all industries' business environments have become extremely dynamic, which requires companies to focus on new solutions, rapid development and cost efficiency. To cope with these pressures, industries have been forced to search for new partners, so university-industry collaboration (UIC) has become a key resource for managers seeking to promote innovation and technological development. This study explored the relationship between research and innovation based on smart specialisation strategies and UIC, including the roles of university-industry (U-I) joint research and academics' motivations for interacting with industries. Based on data collected from 841 Portuguese and Spanish researchers, the results reveal that smart specialisation policies' effects on UIC are driven by U-I joint research development and university faculty members' motivations for co-operating with industry professionals. The findings indicate that U-I research activities and universities' incentives to collaborate with industries fully convert smart specialisation strategies' effects into higher levels of U-I knowledge transfer. © 2022, Academic Conferences and Publishing International Limited. All rights reserved.

Experience in managing action research on hepatitis C survey in the prison community

We aimed to report the experience in managing action research on hepatitis C investi-gation in the prison community in the Triangulo Mineiro region, Minas Gerais, Brazil. The proposal was developed from March 2019 to March 2020, reaching 240 people to contain the spread of the disease through a survey, testing, and mo-nitoring of positive cases. We adopted intersecto-ral action with articulation between Universities, Medical Society, Teaching Hospital, and State Secretariat for Justice and Public Security. Strategies for the management of action research are descri-bed: study settings and stakeholders, registration and formalization of the activity, application of tests, and management of reagent inmates. We identified difficulties regarding the accommoda-tion of routines among the research team and the proper functioning of the penitentiary, which required extensive training between the parties and managerial articulations. We consider that the report collaborates with the organization of future research aimed at accessing this still invi-sible population, the prison community when it highlights the strategies adopted to conduct the research. Copyright © 2022, Associacao Brasileira de Pos - Graduacao em Saude Coletiva. All rights reserved.

Reflections on Agile Software Development: A Conversion Master Case study

This research to practice paper presents a reflective study showing the observations of the teaching teams and the practices during industrial projects for the Master of Software Development (MSwDev) program at Victoria University of Wellington (VUW), New Zealand. It is a conversion master program that helps the students to acquire specific skills to be ready for the transition to the software development industry, including the ability to work in an Agile team. Software development projects supported by industrial partners are an excellent means to evaluate the technical capacity of the students and the required skills. This reflective paper describes the evolution of an industry-sourced problem-based agile student project, which over three successive years, has included students from three different cohorts (User Experience (UX), Business Analysts (BA), and Software Developers (SwDev)). This year, a collaboration between different cohorts was not possible. Thus only software development students formed the agile teams.This paper describes and reflects on the teaching staff's useful and problematic observations over the last twelve months using only the SwDev cohort and correlates that to the previous reflections when three different cohorts formed an Agile team. Those reflections are described, and several recommendations are drawn from the experiences. The authors also discuss the lessons learnt and the effect of COVID-19 on the teams' performance. © 2022 IEEE.