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Background: The COVID-19 pandemic has necessitated changes in European healthcare systems, with a significant proportion of COVID-19 cases being managed on an outpatient basis in primary healthcare (PHC). To alleviate the burden on healthcare facilities, many European countries developed contact-tracing apps and symptom checkers to identify potential cases. As the pandemic evolved, the European Union introduced the Digital COVID-19 Certificate for travel, which relies on vaccination, recent recovery, or negative test results. However, the integration between these apps and PHC has not been thoroughly explored in Europe. Objective: To describe if governmental COVID-19 apps allowed COVID-19 patients to connect with PHC through their apps in Europe and to examine how the Digital COVID-19 Certificate was obtained. Methodology: Design and setting: Retrospective descriptive study in PHC in 30 European countries. An ad hoc, semi-structured questionnaire was developed to collect country-specific data on primary healthcare activity during the COVID-19 pandemic and the use of information technology tools to support medical care from 15 March 2020 to 31 August 2021. Key informants belong to the WONCA Europe network (World Organization of Family Doctors). The data were collected from relevant and reliable official sources, such as governmental websites and guidelines. Main outcome measures: Patient's first contact with health system, governmental COVID-19 app (name and function), Digital COVID-19 Certification, COVID-19 app connection with PHC. Results: Primary care was the first point of care for suspected COVID-19 patients in 28 countries, and 24 countries developed apps to complement classical medical care. The most frequently developed app was for tracing COVID-19 cases (24 countries), followed by the Digital COVID-19 Certificate app (17 countries). Bulgaria, Italy, Serbia, North Macedonia, and Romania had interoperability between PHC and COVID-19 apps, and Poland and Romania's apps considered social needs. Conclusions: COVID-19 apps were widely created during the first pandemic year. Contact tracing was the most frequent function found in the registered apps. Connection with PHC was scarcely developed. In future pandemics, connections between health system levels should be guaranteed to develop and implement effective strategies for managing diseases. [ABSTRACT FROM AUTHOR]

Background: Premenstrual dysphoric disorder is a depressive disorder affecting 5%–8% of people with menstrual cycles. Despite evidence that facial emotion detection is altered in depressive disorders, with enhanced detection of negative emotions (negativity bias), minimal research exists on premenstrual dysphoric disorder. Objectives: The goal of this study was to investigate the effect of premenstrual dysphoric disorder symptoms and the premenstrual phase on accuracy and intensity at detection of facial emotions. Design: Cross-sectional quasi-experimental design. Method: The Facial Emotion Detection Task was administered to 72 individuals assigned female at birth with no premenstrual dysphoric disorder (n = 30), and provisional PMDD (n = 42), based on a retrospective Diagnostic and Statistical Manual of Mental Disorders—Fifth Edition -based measure of premenstrual dysphoric disorder. Facial emotion detection was examined both irrespective of menstrual cycle phase, and as a function of premenstrual phase (yes, no). The task used neutral-to-emotional facial expression morphs (15 images/morph). Participants indicated the emotion detected for each image within the progressive intensity morph. For all six basic emotions (sad, angry, fearful, happy, disgust, and surprise), two scores were calculated: accuracy of responses and the intensity within the morph at which the correct emotion was first detected (image number). Results: Individuals reporting moderate/severe symptoms of premenstrual dysphoric disorder had more accurate and earlier detection of disgust, regardless of cycle phase. In addition, those with provisional premenstrual dysphoric disorder detected sad emotions earlier. A premenstrual dysphoric disorder group × cycle phase interaction also emerged: individuals reporting premenstrual dysphoric disorder symptoms were more accurate at detecting facial emotions during the premenstrual phase compared to the rest of the cycle, with a large effect size for sad emotions. Conclusion: The findings suggest enhanced facial emotion processing in individuals reporting symptoms of premenstrual dysphoric disorder, particularly for sadness and disgust. However, replication is required with larger samples and prospective designs. This premenstrual dysphoric disorder premenstrual emotion detection advantage suggests an adaptive cognitive mechanism in premenstrual syndrome/premenstrual dysphoric disorder, and challenges stigma surrounding premenstrual experiences. Plain Language Summary: Women with Severe Premenstrual Syndrome or Probable Premenstrual Dysphoric Disorder are Better at Identifying Emotional Expressions on People's Faces, Especially During the Premenstrual Phase Premenstrual dysphoric disorder is a depressive disorder affecting women where they experience emotional and physical symptoms during the premenstrual phase (i.e. the week before one's period). It is a severe form of premenstrual syndrome. Research indicates that depression can affect facial emotion recognition. Accurately recognizing other people's emotions is an important skill that helps us develop social connections and keep ourselves and others safe. Quick recognition of facial emotions allows us to understand and support others, and quickly identify dangerous situations by recognizing other people's emotional responses. The goal of this study was to examine how premenstrual dysphoric disorder symptoms and the premenstrual phase may affect the ability of women to recognize and identify emotions on other people's faces. A total of 72 women (42 with premenstrual dysphoric disorder, 30 without premenstrual dysphoric disorder) completed the Facial Emotion Detection Task. This task measured how accurate and early the women were able to detect happiness, sadness, anger, fear, surprise, and disgust in faces. Women with moderate/severe symptoms of premenstrual dysphoric disorder had more accurate and earlier detection of disgust, regardless of where they were in their menstrual cycle. Women with premenstrual dysphoric disorder detected sad emotions earlier. Furthermore, women with premenstrual dysphoric disorder were more accurate at detecting facial emotions when they were tested in the premenstrual phase, and were especially more accurate in detecting sad emotions. The findings suggest that women with premenstrual dysphoric disorder are better at detecting facial emotions and show a premenstrual dysphoric disorder premenstrual emotion detection advantage. This tendency for women with premenstrual dysphoric disorder to better detect emotions in others, particularly when they are in the premenstrual cycle phase, would have benefits. As one of the first reports of a potentially beneficial effect of premenstrual syndrome for women, the findings may help decrease stigma associated with premenstrual dysphoric disorder and premenstrual syndrome. Further research is needed to replicate and extend these findings. [ABSTRACT FROM AUTHOR]

Background: Childhood myopia represents a global concern with increasing prevalence in recent decades. Lifestyle factors significantly impact myopia. Aim: To evaluate lifestyle factors in myopic children from a metropolitan area in Europe. Methods: This was a descriptive study including myopic subjects aged 4–18 years. Patient demographic and clinical data were collected, including cycloplegic refraction in spherical equivalent refraction (SER) and axial length (AL). In addition, a questionnaire on lifestyle factors was conducted between September 2022 and April 2023. Results: A total of 321 myopic children were included, aged 10.72 ± 3.05 years, of whom 51.4% were boys, with SER −2.25 ± 1.9 D and AL 24.54 ± 0.98 mm. The mean age of myopia onset was 7.69 ± 3.05 years. A total of 59.8% had family history of myopia. Those children who had <2 h/day of screen time (on weekdays) presented SER −2 ± 1.91 D, compared to those who had >2 h/day, SER: −2.50 ±1.88 D (p = 0.009). Children who spent <2 h/day doing near work after school were less myopic compared to those who spent >2 h/day (SER: −1.75 ± 1.83 vs. SER: −2.75 ± 1.82, respectively, p = 0.03). However, no significant association was observed between SER and AL and time spent outdoors nor between SER and AL and academic performance (p > 0.05). Conclusions: Screen time and near-work time appear to be lifestyle factors related to myopia. [ABSTRACT FROM AUTHOR]