Background: Primary care physicians have been present on the frontline during the ongoing pandemic, adding new tasks to already high workloads. Our aim was to evaluate burnout in primary care physicians during the COVID-19 pandemic, as well as associated contributing factors. Methods: Cross-sectional study with an online questionnaire disseminated through social media, applying the snowball technique. The target population was primary care physicians working in Portugal during the first outbreak of the COVID-19 pandemic. In addition to sociodemographic data, the questionnaire collected responses to the Copenhagen Burnout Inventory (CBI), the Resilience Scale and the Depression, Anxiety, and Stress Scales (DASS-21). Data were collected from May 9 to June 8, 2020, a period comprising the declaration of a national calamity and then state of emergency, and the subsequent ease of lockdown measures. Levels of burnout in 3 different dimensions (personal, work, and patient-related), resilience, stress, depression, and anxiety were assessed. Logistic regression analyses were conducted to identify factors associated with burnout levels. Results: Among the 214 physician respondents, burnout levels were high in the 3 dimensions. A strong association was found between gender, years of professional experience, depression and anxiety, and burnout levels. Conclusions: Physician burnout in primary care is high and has increased during the pandemic. More studies are needed in the long term to provide a comprehensive assessment of COVID-19’simpact on burnout levels and how to best approach and mitigate it during such unprecedented times.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Background: Diabetes-related foot ulceration (DFU) is a common complication of diabetes, with a significant impact on survival, health care costs, and health-related quality of life. The prognosis of DFU varies widely among individuals. The International Working Group on the Diabetic Foot recently updated their guidelines on how to classify ulcers using “classical” classification and scoring systems. No system was recommended for individual prognostication, and the group considered that more detail in ulcer characterization was needed and that machine learning (ML)–based models may be the solution. Despite advances in the field, no assessment of available evidence was done. Objective: This study aimed to identify and collect available evidence assessing the ability of ML-based models to predict clinical outcomes in people with DFU. Methods: We searched the MEDLINE database (PubMed), Scopus, Web of Science, and IEEE Xplore for papers published up to July 2023. Studies were eligible if they were anterograde analytical studies that examined the prognostic abilities of ML models in predicting clinical outcomes in a population that included at least 80% of adults with DFU. The literature was screened independently by 2 investigators (MMS and DAR or EH in the first phase, and MMS and MAS in the second phase) for eligibility criteria and data extracted. The risk of bias was evaluated using the Quality In Prognosis Studies tool and the Prediction model Risk Of Bias Assessment Tool by 2 investigators (MMS and MAS) independently. A narrative synthesis was conducted. Results: We retrieved a total of 2412 references after removing duplicates, of which 167 were subjected to full-text screening. Two references were added from searching relevant studies’ lists of references. A total of 11 studies, comprising 13 papers, were included focusing on 3 outcomes: wound healing, lower extremity amputation, and mortality. Overall, 55 predictive models were created using mostly clinical characteristics, random forest as the developing method, and area under the receiver operating characteristic curve (AUROC) as a discrimination accuracy measure. AUROC varied from 0.56 to 0.94, with the majority of the models reporting an AUROC equal or superior to 0.8 but lacking 95% CIs. All studies were found to have a high risk of bias, mainly due to a lack of uniform variable definitions, outcome definitions and follow-up periods, insufficient sample sizes, and inadequate handling of missing data. Conclusions: We identified several ML-based models predicting clinical outcomes with good discriminatory ability in people with DFU. Due to the focus on development and internal validation of the models, the proposal of several models in each study without selecting the “best one,” and the use of nonexplainable techniques, the use of this type of model is clearly impaired. Future studies externally validating explainable models are needed so that ML models can become a reality in DFU care. Trial Registration: PROSPERO CRD42022308248; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022308248

(2020). General Practice and the Community: Research on health service, quality improvements and training. Selected abstracts from the EGPRN Meeting in Vigo, Spain, 17–20 October 2019. European Journal of General Practice: Vol. 26, No. 1, pp. 42-50.

Objective: To assess patients’ preferred roles in healthcare-related decision-making in a representative sample of the Portuguese population. Design: Population-based nationwide cross-sectional study. Setting and participants: A sample of Portuguese people 20 years or older were interviewed face-to-face using a questionnaire with the Problem-Solving Decision-Making scale. Outcomes: The primary outcome was patients’ preferred role for each vignette of the problem-solving decision-making scale. Sociodemographic factors associated with the preferred roles were the secondary outcomes. Results: 599 participants (20–99 years, 53.8% women) were interviewed. Three vignettes of the Problem-Solving Decision-Making scale were compared: morbidity, mortality and quality of life. Most patients preferred a passive role for both the problem-solving and decision-making components of the scale, particularly for the mortality vignette (66.1% in the analysis of the three vignettes), although comparatively more opted to share decision in the decision-making component. For the quality of life vignette, a higher percentage of patients wanted a shared role (44.3%) than with the other two vignettes. In the problem-solving component, preferences were significantly associated with area of residence (p<0.001) and educational level (p=0.013), while in the decision-making, component preferences were associated with age (p=0.020), educational level (p=0.015) and profession (p<0.001). Conclusions: In this representative sample of the Portuguese mainland population, most patients preferred a practitioner-controlling role for both the problem-solving and decision-making components. In a life-threatening situation, patients were more willing to let the doctor decide. In contrast, in a less serious situation, there is a greater willingness to participate in decision-making. We have found that shared decision-making is more acceptable to better-educated patients in the problem-solving component and to people who are younger, higher educated and employed, in the decision-making component.

Objectives To translate and culturally adapt an English language patient decision aid addressing prostate cancer screening, so it can be used by Portuguese men. Design Qualitative study. We followed the European Centre for Disease Prevention and Control’s (ECDC) five-step, stakeholder-based approach to adapting health communication materials: (1) selection of materials and process coordinators, (2) early review, (3) translation and back translation, (4) comprehension testing with cognitive semi-structured interviews and (5) proofreading. Content analysis was performed using Ligre software. Setting and participants Cognitive interviews with 15 men to refine a decision aid after its translation. Eligible participants were Portuguese native-speaking men aged 55–69 years old recruited from the local community (urban and suburban) of Oporto district through advertisements in social media and senior universities between January and March 2019. A previous diagnosis of prostate cancer was the single exclusion criterion. Results Five main themes are presented: informational content, information comprehension, sociocultural appropriateness, feelings and main message and personal perspective concerning prostate cancer screening. Most men found the translated version of the decision aid to be clear, comprehensive and appropriate for its target population, although some suggested that medical terms could be a barrier. The data collected from men’s interviews afforded the researchers the opportunity to clarify concepts and expand existing content. Conclusions A decision aid was successfully translated and adapted to the Portuguese cultural setting. Our ECDC based approach can be replicated by other workgroups to translate and culturally adapt decision aids.