Children's care: family centred but child focused.

Family-centred care is a widely used but loosely defined model of care often used in children's nursing. Although this allows for flexibility in its application, it also means that nurses can have very different ideas about its meaning. Recent decisions about the implementation of the COVID-19 vaccination programme for children under the age of 16 years in the UK and other countries have further confused this, as it has brought into question the relative position of children and their families in the decision-making process. Over time, the legislative and social positions of children have changed. Children are increasingly seen as being separate but related to their family, with an emphasis on their own human, legal, and ethical rights, including allowing children to choose the type of support they require for their care to reduce any undue stress. This article puts these into a current and contextual framework to better help nurses understand the historical as well as the contemporary reasons for the status of family-centred care today.

Dual-role nurse interpreter perceptions of language barriers and Spanish-speaking patients: A qualitative study.

AIM: As the United States population is ever changing and is growing in diverse population patterns, the health care system is called to initiate responsive health care practices that are based on the public's changing and diverse cultural patterns. This study sought to explore the perceptions of certified medical interpreter dual-role nurses and their experiences with Spanish-speaking patients from admission to discharge in hospital stays. DESIGN: A qualitative descriptive case study was applied in this study. METHODS: Data was collected from nurses working at a United States Southwest Borderland hospital using purposive sampling and semi-structured in-depth interviews. A total of four dual-role nurses participated, and thematic narrative analysis was applied. RESULTS: Four major themes emerged. The main themes were "being a dual-role nurse interpreter," "patient experience," "culture and competence, "and "nursing and caring," With each major theme multiple sub themes emerged. Two sub themes emerged with "being a dual-role nurse interpreter," and two sub themes emerged with "patient experiences." The major themes that emerged from the interviews indicated that the language barrier greatly affects Spanish-speaking patients in their hospital stay. Participants reported having at least one encounter with a Spanish-speaking patient that was not afforded interpretation services or had interpretation from someone other than a qualified interpreter. Patients experienced confusion, apprehension and anger associated with not being able to communicate their needs to the healthcare system. CONCLUSIONS: According to the experiences of the certified dual-role nurse interpreters, having a language barrier makes a tremendous impact on the care of Spanish-speaking patients. Nurse participants describe how patients and their family members experience dissatisfaction, anger and confusion when there is a language barrier and most importantly how language barriers have detrimental effects on patients with wrong medication prescriptions and wrong diagnosis. CLINICAL RELEVANCE: When hospital administration recognize and support nurses as certified medical interpreters as a key component for patient care when assisting persons with limited English proficiency, patients are empowered to become active members of their healthcare regimen. The role of dual-role nurses enables brokering between the healthcare system and serves as a tool to bridge health disparities based on linguistic inequities existing in healthcare. Recruitment and retention of certified medical interpreter trained Spanish-speaking nurses deter errors in healthcare and makes a positive impact on the healthcare regimen of Spanish-speaking patients enabling patient empowerment through education and advocacy.

At-Admission Prediction of Mortality and Pulmonary Embolism in COVID-19 Patients Using Statistical and Machine Learning Methods: An International Cohort Study (preprint)

By September, 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients.

Understanding Health System Resilience in responding to a pandemic: experience and lessons from an evolving context of federalization in Nepal (preprint)

Introduction The COVID-19 pandemic has tested the resilience capacities of health systems worldwide and has highlighted the need to understand the concept, pathways, and elements to resilience in different country contexts. In this study, we assessed the health system response to COVID-19 and examined the processes of policy formulation, communication and implementation at the three tiers of government in Nepal, including the dynamic interactions between tiers. Nepal was experiencing the early stages of federalization reform when COVID-19 pandemic hit the country and clarity in roles and capacity to implement functions were the prevailing challenges especially among the subnational governments.Methods We adopted a cross-sectional exploratory design, using mixed methods. We carried out a document review of all policy documents introduced in response to COVID-19 from January-December 2020, and collected qualitative data through 22 key informant interviews at three tiers of government, during January-March 2021. Two municipalities were purposively selected for data collection in Lumbini province. Our analysis is based on a resilience framework that has been developed by our research project, ReBUILD for Resilience, which helps to understand pathways to health system resilience through absorption, adaptation and transformation.Results In the newly established federal structure, the existing emergency response structure and plans were utilized, which were yet to be tested in the decentralized structure. Federal government effectively led the policy formulation process, with minimal engagement of sub-national governments. The local governments did not demonstrate resilience capacities, due to the novelty of the federal system and their consequent lack of experience, confusion on roles, insufficient management capacity and governance structures at local level and limited availability of human, technical and financial resources.Conclusions The study findings emphasize the importance of strong and flexible governance structures and strengthened capacity of subnational governments to effectively manage pandemics. The study elaborates on the key areas and pathways that contribute to resilience capacities of health systems from the experience of Nepal. We draw out lessons for other fragile and shock-prone settings.

Neurological Manifestations in COVID-19 Infection: A Systematic Review and Meta-Analysis.

BACKGROUND: Growing evidence showed that coronavirus disease 2019 (COVID-19) infection may present with neurological manifestations. This review aimed to determine the neurological manifestations and complications in COVID-19. METHODS: We conducted a systematic review and meta-analysis that included cohort and case series/reports involving a population of patients confirmed with COVID-19 infection and their neurologic manifestations. We searched the following electronic databases until April 18, 2020: PubMed, Embase, Scopus, and World Health Organization database (PROSPERO registration number: CRD42020180658). RESULTS: From 403 articles identified, 49 studies involving a total of 6,335 confirmed COVID-19 cases were included. The random-effects modeling analysis for each neurological symptom showed the following proportional point estimates with 95% confidence intervals: "headache" (0.12; 0.10-0.14; I2 = 77%), "dizziness" (0.08; 0.05-0.12; I2 = 82%), "headache and dizziness" (0.09; 0.06-0.13; I2 = 0%), "nausea" (0.07; 0.04-0.11; I2 = 79%), "vomiting" (0.05; 0.03-0.08; I2 = 74%), "nausea and vomiting" (0.06; 0.03-0.11; I2 = 83%), "confusion" (0.05; 0.02-0.14; I2 = 86%), and "myalgia" (0.21; 0.18-0.25; I2 = 85%). The most common neurological complication associated with COVID-19 infection was vascular disorders (n = 23); other associated conditions were encephalopathy (n = 3), encephalitis (n = 1), oculomotor nerve palsy (n = 1), isolated sudden-onset anosmia (n = 1), Guillain-Barré syndrome (n = 1), and Miller-Fisher syndrome (n = 2). Most patients with neurological complications survived (n = 14); a considerable number of patients died (n = 7); and the rest had unclear outcomes (n = 12). CONCLUSION: This review revealed that neurologic involvement may manifest in COVID-19 infection. What has initially been thought of as a primarily respiratory illness has evolved into a wide-ranging multi-organ disease.

Why are different estimates of the effective reproductive number so different? A case study on COVID-19 in Germany (preprint)

The effective reproductive number Rt has taken a central role in the scientific, political, and public discussion during the COVID-19 pandemic, with numerous real-time estimates of this quantity routinely published. Disagreement between estimates can be substantial and may lead to confusion among decision-makers and the general public. In this work, we compare different estimates of the national-level effective reproductive number of COVID-19 in Germany in 2020 and 2021. We consider the agreement between estimates from the same method but published at different time points (within-method agreement) as well as retrospective agreement across different approaches (between-method agreement). Concerning the former, estimates from some methods are very stable over time and hardly subject to revisions, while others display considerable fluctuations. To evaluate between-method agreement, we reproduce the estimates generated by different groups using a variety of statistical approaches, standardizing analytical choices to assess how they contribute to the observed disagreement. These analytical choices include the data source, data pre-processing, assumed generation time distribution, statistical tuning parameters, and various delay distributions. We find that in practice, these auxiliary choices in the estimation of Rt may affect results at least as strongly as the selection of the statistical approach. They should thus be communicated transparently along with the estimates.

Deprivation effect on COVID-19 cases incidence and severity: a geo-epidemiological study in PACA region, France (preprint)

IntroductionThe spread of the COVID-19 pandemic, and its severity, is spatially heterogenous. At the individual level, the socioeconomic status (SES) profile is known to be associated with COVID-19 incidence and severity. The aim of this geo epidemiological study was to investigate the link between SES profile and potential confounders, and COVID-19 incidence and hospitalization rates, at a fine geographical scale. MethodsWe analyzed COVID-19 incidence and severity during two epidemic waves between September 2020 and June 2021, in Provence Alpes Cotes dAzur, a 5 million inhabitants French region. The region is divided into sub-municipal areas that we have classified according to their SES profile. We then conducted a spatial analysis of COVID-19 indicators depending on SES profile, age structure, and health services provision. This analysis considered spatial autocorrelation between areas. ResultsCOVID-19 incidence rates in more deprived areas were similar to those in wealthiest ones. Hospitalization rates of COVID-19 cases in conventional care units were greater in more deprived vs wealthiest areas: Standardized Incidence Ratio (SIR) were respectively 1.34 [95% confidence interval 1.18 - 1.52] and 1.25 [1.13 - 1.38] depending on the epidemic wave. This gap was even greater regarding hospitalization rates of cases in critical care units: SIR = 1.64 [1.30 - 2.07] then 1.33 [1.14 - 1.55] depending on the epidemic wave. Hospitalization rates of COVID-19 cases in conventional care units were also greater in areas with high proportion of elderly people vs young people: SIR respectively 1.24 [1.11 - 1.38] and 1.22 [1.13 - 1.32] depending on the wave. ConclusionConsidering age structure and health services provision, a deprived SES profile is associated to a greater COVID-19 severity in terms of hospitals admissions, in conventional care units and in critical care units. This result implies targeting risk prevention efforts on these areas in pandemic situations, and highlights the need to develop access to healthcare to deprived populations in anticipation of periods of crisis. Key messagesWhat is already known on this topic - Socioeconomic status is associated to COVID-19 incidence and severity, at an individual scale or at a large spatial scale. What this study adds - We showed the positive relationship between deprivation and COVID-19 incidence and hospitalization rates at a fine sub-municipal geographical scale. We considered confusion factors like demographic structure and health services provision. How this study might affect research, practice or policy - These findings may help predict at a fine scale where the impact will be most severe in pandemic situations and make it possible to target risk prevention efforts on these areas.

Misdiagnosis of multisystem inflammatory syndrome in children: A diagnostic challenge.

AIMS: As the COVID-19 pandemic continues, multisystem inflammatory syndrome in children (MIS-C) maintains its importance in the differential diagnosis of common febrile diseases. MIS-C should be promptly diagnosed because corticosteroid and/or intravenous immunoglobulin treatment can prevent severe clinical outcomes. In this study, we aimed to evaluate clinical presentation, diagnostic parameters and management of MIS-C and compare its clinical features to those of common febrile disease. METHODS: This study was conducted at a tertiary-level university hospital between December 2020 and October 2022. One hundred and six children who were initially considered to have MIS-C disease were included in the study. During the follow-up period in the hospital, when the clinical and laboratory findings were re-evaluated, 38 out of 106 children were diagnosed differently. The clinical and laboratory findings of 68 children followed up with the diagnosis of MIS-C and 38 children who were initially misdiagnosed as MIS-C but with different final diagnoses were retrospectively compared. RESULTS: We identified 68 patients with MIS-C and 38 patients misdiagnosed as MIS-C during the study period. Infectious causes (71%), predominantly bacterial origin, were the most frequently confused conditions with MIS-C. Patients with MIS-C were older and had a more severe clinical course with high rates of respiratory distress, shock, and paediatric intensive care unit admission. While rash and conjunctivitis were more common among patients with MIS-C, cough, abdominal pain and diarrhoea were observed more frequently in patients misdiagnosed as MIS-C. Lower absolute lymphocyte counts, platelet counts and higher C-reactive protein and fibrinogen levels, pathological findings on echocardiography were the distinctive laboratory parameters for MIS-C. Multivariate analysis showed that older age, presence of conjunctivitis, high level of serum CRP and lower platelets were the most discriminative predictors for the diagnosis of MIS-C. CONCLUSION: There are still no specific findings to diagnose MIS-C, which therefore can be confused with different clinical conditions. Further data are needed to assist the clinician in the differential diagnosis of MIS-C and the diagnostic criteria should be updated over time.

Medical Face Masks and Emotion Recognition from the Body: Insights from a Deep Learning Perspective (preprint)

The COVID-19 pandemic has undoubtedly changed the standards and affected all aspects of our lives, especially social life. It has forced people to extensively wear medical face masks, in order to prevent transmission. This face occlusion can strongly irritate emotional reading from the face and urges us to incorporate the whole body for emotion recognition, as it needs to play a more major role, despite its complementary nature. In this paper, we want to conduct insightful studies about the effect of face occlusion on emotion recognition performance, and showcase the superiority of full body input over plain masked face. We utilize a deep learning model based on the Temporal Segment Network framework and aspire to fully overcome the consequences of the face mask. Although single RGB stream models can adapt and learn both facial and bodily features, this may lead to irrelevant information confusion. By processing those features separately and fusing their preliminary prediction scores with a late fusion scheme, we are more effectively taking advantage of both modalities. This architecture can also naturally support temporal modeling, by mingling information among neighboring segment frames. Experimental results suggest that spatial structure plays a more important role for an emotional expression, while temporal structure is complementary.

Development of Moral Injury in ICU Professionals During the COVID-19 Pandemic: A Prospective Serial Interview Study.

OBJECTIVES: During the COVID-19 pandemic, ICU professionals have faced moral problems that may cause moral injury. This study explored whether, how, and when moral injury among ICU professionals developed in the course of the COVID-19 pandemic. DESIGN: This is a prospective qualitative serial interview study. SETTING: Two hospitals among which one university medical center and one teaching hospital in the Netherlands. SUBJECTS: Twenty-six ICU professionals who worked during the COVID-19 pandemic. INTERVENTIONS: None. MEASUREMENTS MAIN RESULTS: In-depth interviews with follow-up after 6 and 12 months. In total, 62 interviews were conducted. ICU professionals narrated about anticipatory worry about life and death decisions, lack of knowledge and prognostic uncertainty about COVID-19, powerlessness and failure, abandonment or betrayal by society, politics, or the healthcare organization, numbness toward patients and families, and disorientation and self-alienation. Centrally, ICU professionals describe longitudinal processes by which they gradually numbed themselves emotionally from patients and families as well as potentially impactful events in their work. For some ICU professionals, organizational, societal, and political responses to the pandemic contributed to numbness, loss of motivation, and self-alienation. CONCLUSIONS: ICU professionals exhibit symptoms of moral injury such as feelings of betrayal, detachment, self-alienation, and disorientation. Healthcare organizations and ICU professionals themselves should be cognizant that these feelings may indicate that professionals might have developed moral injury or that it may yet develop in the future. Awareness should be raised about moral injury and should be followed up by asking morally injured professionals what they need, so as to not risk offering unwanted help.

Experiencing a slow passage of time was an indicator of social and temporal disorientation during the Covid-19 pandemic.

Time dilation was experienced in most countries and across the several years of the Covid-19 crisis: the passage of time was deemed slower than before the pandemic, and the distance to the beginning of the pandemic seemed longer than it really was. An outstanding question is how these two aspects of time judgements relate to other temporal, social and affective disturbances. We developed and validated a 59-item questionnaire to explore these questions. 3306 participants completed the questionnaire in France in May and June 2021. Here, we analyse group differences and find that both slow passage of time and long distance judgements were associated with larger disturbances across all domains under study. These included temporal disruptions-the aptness to project oneself into the future, the sense of a rift between pre-pandemic and pandemic time, the ability to locate oneself in time, the capacity to recall the order of past events-, as well as an overall sense of social disorientation, and trauma-specific disturbances. In contrast, both fast passage of time and short distance judgements were associated with beneficial effects across all of the mentioned domains. Our results indicate that perceived passage of time and temporal distance judgements are key indicators of social and temporal disorientation.

Natural history of long-COVID in a nationwide, population cohort study (preprint)

Previous studies on the natural history of long-COVID have been few and selective. Without comparison groups, disease progression cannot be differentiated from symptoms originating from other causes. The Long-COVID in Scotland Study (Long-CISS) is a Scotland-wide, general population cohort of adults who had laboratory-confirmed SARS-CoV-2 infection matched to adults never infected. Serial, self-completed, online questionnaires collected information on pre-existing health conditions and current health: 26 symptoms and health-related quality of life, six, 12 and 18 months after the index test. Those previously infected also self-reported current recovery status (fully, partially or not recovered). Here we show that, of those with previous symptomatic infection, 35% reported persistent incomplete/no recovery, 12% improvement and 12% deterioration. At six and 12 months, one or more symptom was reported by 71.5% and 70.7% respectively of those previously infected, compared with 53.5% and 56.5% of those never infected. Altered taste, smell and confusion improved over time compared to the never infected group and adjusted for confounders. Conversely, late onset dry and productive cough, and hearing problems were more likely following SARS-CoV-2 infection than among those never infected. Whilst resolution of some symptoms of long-COVID (altered taste/smell and confusion) is reassuring, late onset cough and hearing problems in some individuals merits further investigation.

Covid-19 affects taste independently of smell: results from a combined chemosensory home test and online survey from a global cohort (N=10,953) (preprint)

People often confuse smell loss with taste loss, so it is unclear how much gustatory function is reduced in patients self-reporting taste loss. Our pre-registered cross-sectional study design included an online survey in 12 languages with instructions for self-administering chemosensory tests with ten household items. Between June 2020 and March 2021, 10,953 individuals participated. Of these, 3,356 self-reported a positive and 602 a negative COVID-19 diagnosis (COVID+ and COVID-, respectively); 1,267 were awaiting test results (COVID?). The rest reported no respiratory illness and were grouped by symptoms: sudden smell/taste changes (STC, N=4,445), other symptoms excluding smell or taste loss (OthS, N=832), and no symptoms (NoS, N=416). Taste, smell, and oral irritation intensities and self-assessed abilities were rated on visual analog scales. Compared to the NoS group, COVID+ was associated with a 21% reduction in taste (95% Confidence Interval (CI): 15-28%), 47% in smell (95%-CI: 37-56%), and 17% in oral irritation (95%-CI: 10-25%) intensity. In all groups, perceived intensity of smell (r=0.84), taste (r=0.68), and oral irritation (r=0.37) was correlated. Our findings suggest most reports of taste dysfunction with COVID-19 were genuine and not due to misinterpreting smell loss as taste loss (i.e., a classical taste-flavor confusion). Assessing smell and taste intensity of household items is a promising, cost-effective screening tool that complements self-reports and helps to disentangle taste loss from smell loss. However, it does not replace standardized validated psychophysical tests.

Burden, Causation, and Particularities of long-COVID in African populations: A rapid systematic review (preprint)

BackgroundThe global estimated prevalence of long COVID-19 is 43%, and the most common symptoms found globally are fatigue, confusion, or lack of confusion, and dyspnea, with prevalence rates of 23%, 14%, and 13%, respectively. However, long COVID still lacks an overall review in African populations. The aim of this review was to determine the prevalence of long COVID, its most common symptoms, comorbidities, and pathophysiological mechanisms. MethodsA systematic review of long COVID in African populations was conducted. The random effects model was used to calculate the pooled prevalence rates (95% CI). If the results could not be pooled, a narrative synthesis was performed. ResultsWe included 14 studies from 7 African countries, totaling 6,030 previously SARS-CoV-2 infected participants and 2,954 long COVID patients. Long COVID had a pooled prevalence of 41% [26%-56%]. Fatigue, dyspnea, and confusion or lack of concentration were the most common symptoms, with prevalence rates (95% CI) of 41% [26%-56%], 25% [12%-38%], and 40% [12%-68%], respectively. Long COVID was associated with advanced age, being female, more than three long COVID symptoms in the acute phase, initial fatigue and dyspnea, post-recovery stress, sadness, and sleep disturbances, and loss of appetite at symptoms onset, mild, moderate, and severe, pre-existing obesity, hypertension, diabetes mellitus, and the presence of any chronic illness (P [≤]0.05). According to our review, high micro clot and platelet poor plasma (PPP) viscosity explain the pathophysiology of long COVID. ConclusionLong COVID prevalence in Africa was comparable to the global prevalence. However, the prevalence of the most common symptoms was higher in Africa. Comorbidities associated with long COVID may lead to additional complications in African populations due to hypercoagulation and thrombosis.

Development and validation of a quantitative instrument for measuring temporal and social disorientation in the Covid-19 crisis.

We developed a quantitative Instrument for measuring Temporal and Social Disorientation (ITSD), aimed at major crises such as the Covid-19 pandemic. Disorientation has been identified as one of the central elements of the psychological impact of the Covid-19 era on the general public, but so far, the question has only been approached qualitatively. This paper offers an empirical, quantitative approach to the multi-faceted disorientation of the Covid-19 pandemic by operationalising the issue with the help of the ITSD. The ITSD was developed through multiple stages involving a preliminary open-ended questionnaire followed by a coder-based thematic analysis. This paper establishes the reliability and validity of the resulting ITSD using a 3-step validation process on a sample size of 3306.

Factors Associated with Long Covid Symptoms in an Online Cohort Study (preprint)

Importance: Prolonged symptoms following SARS-CoV-2 infection, or Long COVID, is common, but few prospective studies of Long COVID risk factors have been conducted. Objective: To determine whether sociodemographic factors, lifestyle, or medical history preceding COVID-19 or characteristics of acute SARS-CoV-2 infection are associated with Long COVID. Design: Cohort study with longitudinal assessment of symptoms before, during, and after SARS-CoV-2 infection, and cross-sectional assessment of Long COVID symptoms using data from the COVID-19 Citizen Science (CCS) study. Setting: CCS is an online cohort study that began enrolling March 26, 2020. We included data collected between March 26, 2020, and May 18, 2022. Participants: Adult CCS participants who reported a positive SARS-CoV-2 test result (PCR, Antigen, or Antibody) more than 30 days prior to May 4, 2022, were surveyed. Exposures: Age, sex, race/ethnicity, education, employment, socioeconomic status/financial insecurity, self-reported medical history, vaccination status, time of infection (variant wave), number of acute symptoms, pre-COVID depression, anxiety, alcohol and drug use, sleep, exercise. Main Outcome: Presence of at least 1 Long COVID symptom greater than 1 month after acute infection. Sensitivity analyses were performed considering only symptoms beyond 3 months and only severe symptoms. Results: 13,305 participants reported a SARS-CoV-2 positive test more than 30 days prior, 1480 (11.1% of eligible) responded to a survey about Long COVID symptoms, and 476 (32.2% of respondents) reported Long COVID symptoms (median 360 days after infection). Respondents' mean age was 53 and 1017 (69%) were female. Common Long COVID symptoms included fatigue, reported by 230/476 (48.3%), shortness of breath (109, 22.9%), confusion/brain fog (108, 22.7%), headache (103, 21.6%), and altered taste or smell (98, 20.6%). In multivariable models, number of acute COVID-19 symptoms (OR 1.30 per symptom, 95%CI 1.20-1.40), lower socioeconomic status/financial insecurity (OR 1.62, 95%CI 1.02-2.63), pre-infection depression (OR 1.08, 95%CI 1.01-1.16), and earlier variants (OR 0.37 for Omicron compared to ancestral strain, 95%CI 0.15-0.90) were associated with Long COVID symptoms. Conclusions and Relevance: Variant wave, severity of acute infection, lower socioeconomic status and pre-existing depression are associated with Long COVID symptoms.

COVID-19 Activity Risk Calculator as a Gamified Public Health Intervention Tool (preprint)

Public health intervention techniques have been highly significant in reducing the negative impact of several epidemics and pandemics. Among all of the wide-spread diseases, one of the most dangerous one has been severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or Coronavirus disease 2019 (COVID-19). The impact of the virus has been observed in over 200 countries leading to hospitalizations and deaths of millions of people. Currently existing COVID-19 risk estimation tools provided to the general public have been highly variable during the pandemic due to its dependency on rapidly evolving factors such as community transmission levels and variants. There has also been confusion surrounding certain personal protective strategies such as risk reduction by mask-wearing and vaccination. In order to create a simplified easy-to-use tool for estimating different individual risks associated with carrying out daily-life activity, we developed COVID-19 Activity Risk Calculator (CovARC). CovARC serves as a gamified public health intervention as users can "play with" how different risks associated with COVID-19 would change depending on several different factors when carrying out a daily routine activity. Empowering the public to make informed, data-driven decisions about safely engaging in activities may help to reduce COVID- 19 levels in the community. In this study, we demonstrate a streamlined, scalable and accurate COVID-19 risk calculation system. Our study also showcases quantitatively, the increased impact of interventions such as vaccination and mask-wearing when cases are higher, which could prove as a validity to inform and support policy decisions around mask mandate case thresholds and other non-pharmaceutical interventions.

Face masks impair facial emotion recognition and induce specific emotion confusions.

Face masks are now worn frequently to reduce the spreading of the SARS-CoV-2 virus. Their health benefits are undisputable, but covering the lower half of one's face also makes it harder for others to recognize facial expressions of emotions. Three experiments were conducted to determine how strongly the recognition of different facial expressions is impaired by masks, and which emotions are confused with each other. In each experiment, participants had to recognize facial expressions of happiness, sadness, anger, surprise, fear, and disgust, as well as a neutral expression, displayed by male and female actors of the Radboud Faces Database. On half of the 168 trials, the lower part of the face was covered by a face mask. In all experiments, facial emotion recognition (FER) was about 20% worse for masked faces than for unmasked ones (68% correct vs. 88%). The impairment was largest for disgust, followed by fear, surprise, sadness, and happiness. It was not significant for anger and the neutral expression. As predicted, participants frequently confused emotions that share activation of the visible muscles in the upper half of the face. In addition, they displayed response biases in these confusions: They frequently misinterpreted disgust as anger, fear as surprise, and sadness as neutral, whereas the opposite confusions were less frequent. We conclude that face masks do indeed cause a marked impairment of FER and that a person perceived as angry, surprised, or neutral may actually be disgusted, fearful, or sad, respectively. This may lead to misunderstandings, confusions, and inadequate reactions by the perceivers.

User feedback on the NHS Test & Trace Service during COVID-19: the use of machine learning to analyse free-text data from 37,914 UK adults (preprint)

Objectives The UK government's approach to the pandemic relies on a test, trace and isolate strategy, mainly implemented via the digital NHS Test & Trace Service. Feedback on user experience is central to the successful development of public-facing services. As the situation dynamically changes and data accumulate, interpretation of feedback by humans becomes time-consuming and unreliable. The specific objectives were to 1) evaluate a human-in-the-loop machine learning technique based on structural topic modelling in terms of its serviceability in the analysis of vast volumes of free-text data, 2) generate actionable themes that can be used to increase user satisfaction of the Service. Methods We evaluated an unsupervised Topic Modelling approach, testing models with 5-40 topics and differing covariates. Two human coders conducted thematic analysis to interpret the topics. We identified a Structural Topic Model with 25 topics and metadata as covariates as the most appropriate for acquiring insights. Results Results from analysis of feedback by 37,914 users from May 2020 to March 2021 highlighted issues with the Service falling within three major themes: multiple contacts and incompatible contact method and incompatible contact method, confusion around isolation dates and tracing delays, complex and rigid system. Conclusions Structural Topic Modelling coupled with thematic analysis was found to be an effective technique to rapidly acquire user insights. Topic modelling can be a quick and cost-effective method to provide high quality, actionable insights from free-text feedback to optimize public health services.

Metaphors of adolescence during COVID-19 pandemic: a mixed-method analysis in relation to well-being and alexithymia. (preprint)

This study investigates the association between alexithymic traits, self-perceived well-being, and self-representations in adolescents as expressed via narrative metaphors during the COVID-19 epidemic. The sample comprised 229 Italian adolescents (51.1% females, mean age = 16.64). The research design was based on an exploratory, parallel, mixed-method approach. A semi-structured online interview was used as the major data gathering tool including both standardized quantitative questionnaire and open-ended questions. Data were analyzed by means of descriptive statistics, quantitative textual analysis and multidimensional co-word correspondence analysis. Main findings reveal a general low level of perceived well-being associated with alexithymia, affecting adolescents’ lexical choices for their metaphors. Alexithymia-related low levels of well-being correspond to metaphors in which confusion and overpowering emotions predominate. Vivid pictures indicating vitality and a bright view on the future is often correlated with high levels of well-being. Metaphors emerge as powerful tools for investigating well-being in adolescents since closely related to inner states.