Binge drinking alcohol and circadian misalignment in night shift nurses is associated with decreased resiliency to COVID-19 infection

Background: Nurses and other first responders are at high risk of exposure to the SARS-CoV2 virus, and many have developed severe COVID-19 infection. A better understanding of the factors that increase the risk of infection after exposure to the virus could help to address this. Although several risk factors such as obesity, diabetes, and hypertension have been associated with an increased risk of infection, many first responders develop severe COVID-19 without established risk factors. As inflammation and cytokine storm are the primary mechanisms in severe COVID-19, other factors that promote an inflammatory state could increase the risk of COVID-19 in exposed individuals. Alcohol misuse and shift work with subsequent misaligned circadian rhythms are known to promote a pro-inflammatory state and thus could increase susceptibility to COVID-19. To test this hypothesis, we conducted a prospective, cross-sectional observational survey-based study in nurses using the American Nursing Association network. Method(s): We used validated structured questionnaires to assess alcohol consumption (the Alcohol Use Disorders Identification Test) and circadian typology or chronotype (the Munich Chronotype Questionnaire Shift -MCTQ-Shift). Result(s): By latent class analysis (LCA), high-risk features of alcohol misuse were associated with a later chronotype, and binge drinking was greater in night shift workers. The night shift was associated with more than double the odds of COVID-19 infection of the standard shift (OR 2.67, 95% CI: 1.18 to 6.07). Binge drinkers had twice the odds of COVID-19 infection of those with low-risk features by LCA (OR: 2.08, 95% CI: 0.75 to 5.79). Conclusion(s): Working night shifts or binge drinking may be risk factors for COVID-19 infection among nurses. Understanding the mechanisms underlying these risk factors could help to mitigate the impact of COVID-19 on our at-risk healthcare workforce.Copyright © 2023 The Authors. Alcohol: Clinical and Experimental Research published by Wiley Periodicals LLC on behalf of Research Society on Alcohol.

Deterioration of the subjective financial well-being during the coronavirus pandemic: a latent transition analysis

PurposeThe authors seek (1) to identify the profiles of subjective financial well-being (SFWB) of bank customers before and during the coronavirus disease 2019 (COVID-19) pandemic, (2) to analyze the transition to profiles of lower SFWB during the pandemic and (3) to identify the factors driving such transitions.Design/methodology/approachThe authors surveyed five countries during 2019 and 2020 to measure SFWB. The authors applied latent class analysis (LCA) to identify profiles of bank customers according to a mix of SFWB indicators in pre-pandemic times (Study 1). The authors validated the profiles during the pandemic and identified the SFWB dimensions that deteriorated during the crisis (Study 2). Finally, the authors applied latent transition analysis (LTA) to explore transitions to profiles of lower SFWB and identify the drivers.FindingsThe authors identified three profiles of customers in pre- and post-pandemic periods for four dimensions of SFWB: control over finances, capacity to absorb financial shocks, ability to track financial goals and financial freedom. Gender, age, trust in banks and bank-supporting policies were related to transitions across profiles of SFWB during the pandemic. These relationships are contingent upon contextual country-related variables.Research limitations/implicationsBanks and policymakers should reduce customers' exposure to the pandemic's long-lasting adverse effects on SFWB and should identify and control the multiplier role that contextual variables play.Originality/valueExtant literature has not fully identified the dimensions of SFWB that changed due to the COVID-19 pandemic. The authors narrow this gap by identifying three SFWB profiles of customers, analyzing the patterns of SFWB change and connecting these changes to individual, provider and contextual factors.

Not all home drinking is equal: A latent class analysis of drinking patterns and alcohol consumption levels following initial COVID-19 restrictions in Australia, New Zealand and the United Kingdom.

INTRODUCTION: Initial COVID-19 restrictions forced changes in the contexts (e.g., with who and where) within which individuals consumed alcohol. We aimed to explore different profiles of drinking contexts during initial COVID-19 restrictions and their association with alcohol consumption. METHOD: We used latent class analysis (LCA) to explore subgroups of drinking contexts among 4891 respondents of the Global Drug Survey from the United Kingdom, New Zealand and Australia who reported drinking alcohol in the month prior to data collection (3 May-21 June 2020). Ten binary LCA indicator variables were generated from a survey question about last month alcohol settings. Negative binomial regression was used to explore the association between the latent classes and respondents' total number of drinks consumed in the last 30 days (i.e., alcohol consumption). RESULTS: The LCA found six distinct classes of individuals who reported drinking in the following contexts: household (36.0%); alone (32.3%); alone and household (17.9%); gatherings and household (9.5%); party (3.2%); and everywhere (1.1%), with the last group associated with the highest probability of increased alcohol consumption during this time. Male respondents and those aged 35 or older were most likely to report increased alcohol consumption. DISCUSSION AND CONCLUSIONS: Our findings suggest that drinking contexts, sex and age influenced alcohol consumption during the early stages of the COVID-19 pandemic. These findings highlight a need for improved policy targeting risky drinking in home settings. Further research should explore whether COVID-19-induced shifts in alcohol use persist as restrictions are lifted.

How to reduce vaccination hesitancy? The relevance of evidence and its communicator.

Even though the immediate urgency of the COVID-19 pandemic seems to have passed, many countries did not reach the vaccination rates they initially aimed for. The stagnation in vaccine uptake during the height of the pandemic presented policy makers with a challenge that remains unresolved and is paramount for future pandemics and other crises: How to convince the (often not insubstantial) unvaccinated proportion of the population of the benefits of a vaccination? Designing more successful communication strategies, both in retrospect and looking ahead, requires a differentiated understanding of the concerns of those that remain unvaccinated. Guided by the elaboration likelihood model, this paper has two objectives: First, it explores by means of a latent class analysis how unvaccinated individuals might be characterized by their attitudes towards COVID-19 vaccination. Second, we investigate to what extent (i) varying types of evidence (none/anecdotal/statistical) can be employed by (ii) different types of communicators (scientists/politicians) to improve vaccination intentions across these subgroups. To address these questions, we conducted an original online survey experiment among 2145 unvaccinated respondents from Germany where a substantial population share remains unvaccinated. The results suggest three different subgroups, which differ regarding their openness towards a COVID-19 vaccination: Vaccination opponents (N = 1184), sceptics (N = 572) and those in principle receptive (N = 389) to be vaccinated. On average, neither the provision of statistical nor anecdotal evidence increased the persuasiveness of information regarding the efficacy of a COVID-19 vaccine. However, scientists were, on average, more persuasive than politicians (relatively increase vaccination intentions by 0.184 standard deviations). With respect to heterogeneous treatment effects among the three subgroups, vaccination opponents seem largely unreachable, while sceptics value information by scientists, particularly if supported by anecdotal evidence (relatively increases intentions by 0.45 standard deviations). Receptives seem much more responsive to statistical evidence from politicians (relatively increases intentions by 0.38 standard deviations).

Latent class analysis of imaging and clinical respiratory parameters from patients with COVID-19-related ARDS identifies recruitment subphenotypes

Introduction: Patients with COVID-19-related acute respiratory distress syndrome (ARDS) require respiratory support with invasive mechanical ventilation and show varying responses to recruitment manoeuvres. In patients with ARDS not related to COVID-19, two pulmonary subphenotypes that differed in recruitability were identified using latent class analysis (LCA) of imaging and clinical respiratory parameters [1]. We aimed to validate these phenotypes and evaluate if similar subphenotypes are present in patients with COVID-19-related ARDS. Method(s): This is the retrospective analysis of mechanically ventilated patients with COVID-19-related ARDS who underwent CT scans at positive end-expiratory pressure of 10 cmH2O and after a recruitment manoeuvre at 20 cmH2O. LCA was applied to quantitative CT-derived parameters, clinical respiratory parameters, blood gas analysis and routine laboratory values before recruitment to identify subphenotypes. Result(s): 99 patients were included. Using 12 variables, a two-class LCA model was identified as best fitting. Subphenotype 2 (recruitable) was characterized by a lower PaO2/ FiO2, lower normally aerated lung volume and lower compliance as opposed to a higher nonaerated lung mass and higher mechanical power when compared to subphenotype 1 (non-recruitable) (Fig. 1). Patients with subphenotype 2 had more decrease in non-aerated lung mass in response to a standardized recruitment manoeuvre (p = 0.024) and were mechanically ventilated longer until successful extubation (adjusted SHR 0.46, 95% CI 0.23-0.91, p = 0.026), while no difference in survival was found (p = 0.814). Conclusion(s): A recruitable and non-recruitable subphenotype were identified in patients with COVID-19-related ARDS. The subphenotypes are similar to non-COVID-19-related ARDS and are promising for identification of recruitable patients in future practice as they can be classified with only few clinically available parameters before the recruitment manoeuvre.

A Risk Profile for Disordered Eating Behaviors in Adolescents with Type 1 Diabetes: A Latent Class Analysis Study.

(1) Background: This multi-center study aimed to identify a risk profile for disordered eating behaviors (DEBs) in youth with type 1 diabetes (T1D) based on their dietary intake, lipid profile, body mass index (BMI-SDS), and glycometabolic control. (2) Methods: Adolescents aged 11 to 18 years from five centers across Italy were recruited. Lipid profile, HbA1c, BMI-SDS, and dietary intake data were collected. The risk for developing DEBs was assessed via the Diabetes Eating Problems Survey-R (DEPS-R) questionnaire. A latent class analysis (LCA) was performed using a person-centered approach. (3) Results: Overall, 148 participants aged 11-18 (12.1, ±3.34), 52% males with a mean diabetes duration of 7.2 (±3.4), were enrolled. Based on the results of the DEBS-R score, LCA allowed us to highlight two different classes of patients which were defined as "at-risk" and "not at-risk" for DEB. The risk profile for developing DEBs is characterized by higher BMI-SDS (23.9 vs. 18.6), higher HbA1c (7.9 vs. 7.1%), higher LDL cholesterol (99.9 vs. 88.8 mg/dL), lower HDL cholesterol (57.9 vs. 61.3 mg/dL), higher proteins (18.2 vs. 16.1%), and lower carbohydrates (43.9 vs. 45.3%). Adolescents included in the "at-risk" class were significantly older (p = 0.000), and their parents' SES was significantly lower (p = 0.041). (4) Conclusions: This study allowed us to characterize a risk profile for DEBs based on dietary behavior and clinical parameters. Early identification of the risk for DEBs allows timely intervention and prevention of behavior disorders.

Older People in Germany During the COVID-19 Pandemic:The Least, the More, and the Most Affected.

Older people have been identified as a particularly vulnerable group during the COVID-19 pandemic. However, the question of how older people actually fared during the COVID-19 pandemic has only been sporadically addressed. This article aims to partly fill this gap by classifying subgroups of older people using Latent Class Analysis. Indicators used are: risk perception, safety behavior, and well-being. To predict subgroup membership, age, gender, living arrangement, children, chronic illness, conflict, socioeconomic status, and migration history are controlled for. The data analyzed stem from a phone survey among 491 older people (75-100 years) in Germany conducted in September/October 2020. Results show that three subgroups of older people - the least, the more and the most affected - can be formed based on their risk perception, safety behavior, and well-being, indicating the usefulness of these three constructs for identifying and studying older people particularly affected by the COVID-19 pandemic and the measures taken to contain it. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12062-021-09352-4.

Factors influencing the learning transfer of nursing students in a non-face-to-face educational environment during the COVID-19 pandemic in Korea: a cross-sectional study using structural equation modeling.

PURPOSE: The aim of this study was to identify factors influencing the learning transfer of nursing students in a non-face-to-face educational environment through structural equation modeling and suggest ways to improve the transfer of learning. METHODS: In this cross-sectional study, data were collected via online surveys from February 9 to March 1, 2022, from 218 nursing students in Korea. Learning transfer, learning immersion, learning satisfaction, learning efficacy, self-directed learning ability and information technology utilization ability were analyzed using IBM SPSS for Windows ver. 22.0 and AMOS ver. 22.0. RESULTS: The assessment of structural equation modeling showed adequate model fit, with normed χ2=1.74 (P<0.024), goodness-of-fit index=0.97, adjusted goodness-of-fit index=0.93, comparative fit index=0.98, root mean square residual=0.02, Tucker-Lewis index=0.97, normed fit index=0.96, and root mean square error of approximation=0.06. In a hypothetical model analysis, 9 out of 11 pathways of the hypothetical structural model for learning transfer in nursing students were statistically significant. Learning self-efficacy and learning immersion of nursing students directly affected learning transfer, and subjective information technology utilization ability, self-directed learning ability, and learning satisfaction were variables with indirect effects. The explanatory power of immersion, satisfaction, and self-efficacy for learning transfer was 44.4%. CONCLUSION: The assessment of structural equation modeling indicated an acceptable fit. It is necessary to improve the transfer of learning through the development of a self-directed program for learning ability improvement, including the use of information technology in nursing students' learning environment in non-face-to-face conditions.

THE ROLE OF HOUSEHOLD SENTIMENTS AND EXPECTATIONS DURING THE COVID-19 CRISIS: EVIDENCE FROM THE SPECIAL SURVEY OF ITALIAN HOUSEHOLDS

We study the role played by household expectations on own economic prospects and sentiments on general economic conditions in shaping their actual and planned consumption behavior. Using data from the Special Survey of Italian Households collected by the Banca d'Italia, we implement a latent class analysis to cluster households into homogeneous groups based on their sentiments. Then, we study the relation between these clusters and household expectations with consumption and saving behavior. Our results show that sentiments and expectations are not statistically related to shopping behavior during the pandemic. On the other hand, they are significant determinants of consumption plans and expected savings. In particular, pessimistic households are more likely to plan a reduction in consumption in the near future;nonetheless, they are less likely to expect positive savings in the 12-month period following the interview. The share of pessimistic households decreases throughout 2021, and if we impute consumption expenditure levels from an external source we find that the share of aggregate consumption of pessimistic households is low. Overall, our results suggest that this group of households may play a limited role in affecting the overall economic situation in the future. © SOCIETÀ EDITRICE IL MULINO.

Role of creative classes in sustainable agricultural development: focusing on creating shared value in rural Japan

The purpose of this study was to clarify the role of creative classes in sustainable agriculture development through creating shared value in rural Japan by applying latent class analysis (LCA), structural equation modeling (SEM) and cognitive map analysis to the results of a questionnaire survey of farmers. Two hypotheses were set for verification: "There are a certain number of Japanese farmers who belong to the creative class” (H1) and "The creative class is highly entrepreneurial, appreciates the attractiveness of agriculture, prefers sustainability policies and seeks to create shared value in agriculture" (H2). We obtained analytical results as follows. First, from the results of the latent class analysis (LCA), farmers were classified into four classes (class 1: Majority, class 2: Early adopter, class 3: Laggard, class 4: Innovator). In addition, Class 4 (innovator) was interpreted as the creative class because most respondents answered positively about creative thinking, job satisfaction, life satisfaction, innovation orientation, social capital and cognitive changes due to the COVID-19 epidemic. Second, the analysis of the structural equation modeling (SEM) revealed the factors affected the entrepreneurship, namely preference for agricultural policy and impact on creating shared value in agriculture in the creative class. In other words, we found that the evaluation of the multi-functionality of agriculture influences each element for entrepreneurship of the creative class, and also influences the preference for agricultural policy and creation of shared value. Thirdly, analysis of cognitive maps revealed that creative classes contribute to sustainable agricultural and rural development through the creation of shared value. However, in current Japan, the creative classes are concentrated in urban areas and farmers highly value the risk of failure, so there is no virtuous cycle for the entrepreneurial environment to shape entrepreneurial attitudes. Therefore, it is important for policies to develop creative classes in flatland agricultural areas and mountainous areas, and build networks for the creative classes among different regions. © 2023, The Japan Section of the Regional Science Association International.

Is there a Common Digital Market in the European Union? Implications for the European Digitalization Strategy

Due to the impact of the COVID‐19 pandemic, people has changed the way they work, learn and socialize. As result, it is important to identify the pre‐existing digital gaps to implement the European Union digitalization strategy. This study aims to identify typologies of internet use in the 28 European Union (EU) countries (at the time of the survey), based on the characteristics of the users and their internet usage patterns. A two‐level latent class analysis was applied. At the first level, individuals within each country were grouped according to their characteristics of internet use;and, simultaneously, at the second level, countries were grouped based on the similar structure of individual segments. Using data from Eurobarometer, results show that internet use in the EU digital market is not homogeneous. The European Commission should take these pre‐existing gaps into account in the EU digitalization strategy.

Changes in concerns and preventative behaviours of Canadians during the COVID-19 pandemic and their demographic associations

Understanding diversity of views, values, and experiences through audience segmentation are essential elements in effective public health messaging. The present study aims to describe the patterns of preventive behaviours and concerns among Canadians throughout different times of the pandemic, as well as identify demographic characteristics that are associated with these patterns. A probability-based sample of 4,627 Canadians was collected by Statistics Canada to complete COVID-19-related surveys in April 2020 and July 2020. Latent class analysis was used to determine the clusters of concerns and preventive behaviours from 21 variables;a set of chi-square tests were run to determine the demographic association. Six classes emerge with varying levels of concerns and preventive behaviours across both time points, albeit some of the group interpretations have changed. Most notably, one latent group showed very little concern about the pandemic. All groups, including the ones with the least concern, still performed the most basic preventive measures such as washing their hands more often across both times. There were also some notable groups who were concerned about social cohesion on top of concerns for overall population health. Demographic associations appear mixed across time, although men, rural residents, and those with lower education were more likely to be in the group showing the least concerns and fewest preventive behaviours. Novel strategies might be required to reach segments whose concerns might be unaddressed and continually skeptical towards public health messaging for the ongoing vaccine rollouts and future health crisis. (PsycInfo Database Record (c) 2023 APA, all rights reserved) (French) La comprehension de la diversite des points de vue, des valeurs et des experiences par la segmentation de l'auditoire est un element essentiel pour assurer l'efficacite des messages de sante publique. Cette etude vise a decrire les modeles de comportements et de preoccupations en matiere de prevention chez les Canadiens a differents moments de la pandemie, ainsi qu'a identifier les caracteristiques demographiques qui sont associees a ces modeles. En avril 2020 et en juillet 2020, Statistique Canada a constitue un echantillon probabiliste de 4 627 Canadiens pour repondre a des enquetes sur la COVID-19. Une analyse de classe latente a ete realisee pour determiner les groupes de preoccupations et les comportements preventifs a partir de 21 variables;une serie de tests du khi carre a ete effectuee pour etablir une correlation demographique. Il en est ressorti six categories comportant divers degres de preoccupations et de comportements preventifs au cours des deux periodes, quoique certaines interpretations de groupe aient change. Plus particulierement, un groupe latent s'est montre tres peu preoccupe par la pandemie. Tous les groupes, y compris ceux qui etaient les moins preoccupes, ont tout de meme applique les mesures preventives les plus elementaires, comme se laver les mains plus souvent au cours des deux periodes. Certains groupes ont notamment place la cohesion sociale en tete de leurs preoccupations sur la sante generale de la population. Les correlations demographiques semblent inegales selon les periodes, bien que les hommes, les habitants des zones rurales et les personnes ayant un faible niveau d'education soient plus susceptibles de faire partie du groupe qui se preoccupe le moins de la sante et adopte le moins de comportements preventifs. De nouvelles strategies pourraient etre necessaires pour atteindre les segments de la population dont les preoccupations pourraient ne pas etre prises en compte et qui restent sceptiques a l'egard des messages de sante publique sur le deploiement de vaccins en cours et les prochaines crises sanitaires. (PsycInfo Database Record (c) 2023 APA, all rights reserved) Impact Statement This study contributes to the existing body of work that shows how certain demographics tend to have different patterns of concerns, values, and behaviours at different times during the COVID-19 pandemic. Public health policies need to consider these differences when doing public outreach through tailoring their messages for different subpopulations to increase the messaging's effectiveness. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

An exploration of Australian attitudes towards privacy

Purpose: Using technology to meet national security expectations and requirements is not new. Nations attempt to strike a balance between security and the (expressed or otherwise) privacy needs of citizens. Attacks (physical or cyber) on citizens shift the equilibrium point towards security. In contrast, civil liberties organisations act to preserve or increase privacy. The purpose of this paper is to explore Australian attitudes towards privacy and surveillance during the COVID-19 pandemic. In addition, this paper aims to discover what (if any) factors contribute to societal acceptance of privacy encroachment implicated by surveillance programs. Design/methodology/approach: Data collection occurred during 2021 using a cross-sectional survey comprising a variety of self-assessment questions. In addition, anchoring vignettes were introduced as a means of contextualising complex concepts, i.e. privacy and security. Finally, latent class analysis (LCA) was used to identify homogenous patterns within the data, referred to as "classes” for the analysis of trust. Findings: First, the survey revealed that citizens appear to be unconcerned about surveillance in public and private spaces (although this may be a temporary effect resulting from the pandemic). The potential for identification, however, does raise concerns. Second, LCA surfaced a specific group that were more likely to trust entities and showed less concern about surveillance in society. Finally, even this latter group displayed a "trust deficit” in specific organisations (private businesses and social media firms). Research limitations/practical implications: The tension between security and privacy remains, even in a post-pandemic world;therefore, the authors consider that the results, whilst interesting, are preliminary. Notwithstanding this, the findings provide insight into Australian attitudes towards privacy and surveillance and, consequently, provide input into public policy. Originality/value: This is the most recent survey of the Australian public concerning this issue. The analysis of the effect of the pandemic on attitudes provides further value. © 2023, Emerald Publishing Limited.

Post-consultation acute respiratory tract infection recovery: a latent class-informed analysis of individual patient data.

BACKGROUND: There is a lack of evidence regarding post-consultation symptom trajectories for patients with respiratory tract infections (RTIs) and whether patient characteristics can be used to predict illness duration. AIM: To describe symptom trajectories in patients with RTIs, and assess baseline characteristics and adverse events associated with trajectories. DESIGN AND SETTING: The study included data about 9103 adults and children from 12 primary care studies. METHOD: A latent class-informed regression analysis of individual patient data from randomised controlled trials and observational cohort studies was undertaken. Post-consultation symptom trajectory (severity and duration), re-consultation with same or worsening illness, and admission to hospital were assessed. RESULTS: In total, 90% of participants recovered from all symptoms by 28 days, regardless of antibiotic prescribing strategy (none, immediate, and delayed antibiotics). For studies of RTI with cough as a dominant symptom (n = 5314), four trajectories were identified: 'rapid (6 days)' (90% of participants recovered within 6 days) in 52.0%; 'intermediate (10 days)' (28.9%); 'slow progressive improvement (27 days)' (12.5%); and 'slow improvement with initial high symptom burden (27 days)' (6.6%). For cough, being aged 16-64 years (odds ratio [OR] 2.57, 95% confidence interval [CI] = 1.72 to 3.85 compared with <16 years), higher presenting illness baseline severity (OR 1.51, 95% CI = 1.12 to 2.03), presence of lung disease (OR 1.78, 95% CI = 1.44 to 2.21), and median and above illness duration before consultation (≥7 days) (OR 1.99, 95% CI = 1.68 to 2.37) were associated with slower recovery (>10 days) compared with faster recovery (≤10 days). Re-consultations and admissions to hospital for cough were higher in those with slower recovery (ORs: 2.15, 95% CI = 1.78 to 2.60 and 7.42, 95% CI = 3.49 to 15.78, respectively). CONCLUSION: Older patients presenting with more severe, longer pre-consultation symptoms and chronic lung disease should be advised they are more likely to experience longer post-consultation illness durations, and that recovery rates are similar with and without antibiotics.

Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis.

INTRODUCTION: Although messenger RNA (mRNA) vaccines have been developed and widely utilized to mitigate the coronavirus disease (COVID-19) pandemic, it is essential to describe the adverse events (AEs) following immunization. This study aimed to identify the patterns associated with serious AE reports after mRNA COVID-19 vaccination in the World Health Organization (WHO)'s global scale database (VigiBase). METHODS: This study performed a latent class analysis (LCA) of reports of serious AEs following mRNA COVID-19 vaccination from VigiBase between December 28, 2020 , and February 28, 2022 (N = 312878). The Medical Dictionary for Regulatory Activities (MedDRA) System Organ Class (SOC) terms were selected for LCA. The reporting characteristics in accordance with the cluster were described. We used a multinomial logistic regression model to estimate the association between potential factors and each cluster. RESULTS: Five clusters of AE reports were distinguished through LCA: infection AEs (cluster 1), cardiac AEs (cluster 2), respiratory/thrombotic AEs (cluster 3), systemic AEs (cluster 4), and nervous system AEs (cluster 5). Compared to cluster 4, cluster 2 had a higher proportion of males (OR 2.98; 95% confidence interval (CI) 2.87-3.09), and cluster 1 had a longer time to onset than other AEs (≥ 14 days) (OR 16.2; 95% CI 15.5-16.9). CONCLUSION: Using LCA, we found five clusters of serious AEs following mRNA COVID-19 vaccination. Each cluster was distinguished by potential factors such as age, gender, region, and time to onset. We suggest that monitoring should carefully consider the patterns of young males with cardiac AEs and elderly individuals with thrombosis after respiratory AEs. Our findings could contribute to enhancing understanding of safety profiles and establishing management strategies for serious AEs of special interest following mRNA COVID-19 vaccination.

Initial risk factors, self-compassion trajectories, and well-being outcomes during the COVID-19 pandemic: A person-centered approach.

Introduction: We investigated whether initial risk classes and heterogeneous trajectories of self-compassion over the course of the pandemic may impact well-being outcomes 1 year into the pandemic. Methods: A large, representative sample of Canadians (N = 3,613; 50.6% women) was sampled longitudinally over 11 waves (April 2020-April 2021), using a rolling cross-sectional survey design. Analyses were conducted in three steps: (1) latent class analysis to identify heterogeneity in risk factors (sociodemographic, cognitive-personality, health-related) early in the pandemic, (2) latent class growth analysis (LCGA) to identify longitudinal self-compassion trajectories, and (3) GLM to examine effects of risk factor classes and self-compassion trajectories, as well as their interaction, on later well-being (mental health, perceived control, life satisfaction). Results and Discussion: Four risk factor classes emerged, with 50.9% of participants experiencing low risk, 14.3% experiencing multiple risks, 20.8% experiencing Cognitive-Personality and Health risks, and 14.0% experiencing sociodemographic and Cognitive-Personality risks. Four self-compassion trajectories also emerged, with 47.7% of participants experiencing moderate-high self-compassion that decreased then stabilized, 32.0% experiencing moderate self-compassion that decreased then stabilized, 17.3% experiencing high and stable self-compassion across time, and 3.0% experiencing low and decreasing self-compassion. Comparisons of well-being outcomes 1 year post-pandemic indicated that higher levels of self-compassion over time may protect against the impact of initial risk on well-being outcomes. Further work is still needed on heterogeneity in experiences of risk and protective factors during stressful life events.

Profiles of risk factors for depressive and anxiety symptoms during the COVID-19 pandemic: A latent class analysis.

The COVID-19 pandemic has caused a high burden in the general population. The exposure to an accumulation of risk factors, as opposed to a single risk, may have been associated with higher levels of depressive and anxiety symptoms during the pandemic. This study aimed to (1) identify subgroups of individuals with distinct constellations of risk factors during the COVID-19 pandemic and (2) investigate differences in levels of depressive and anxiety symptoms. German participants (N = 2245) were recruited between June-September 2020 through an online survey (ADJUST study). Latent class analysis (LCA) and multiple group analyses (Wald-tests) were conducted to identify profiles of risk factors and examine differences in symptoms of depression (PHQ-9) and anxiety (GAD-2). The LCA included 14 robust risk factors of different domains, for example, sociodemographic (e.g., age), health-related (e.g., trauma), and pandemic-related (e.g., reduced income) factors. The LCA identified three risk profiles: High sociodemographic risk (11.7%), high social and moderate health-related risk (18.0%), and low general risk (70.3%). Individuals with high sociodemographic risk reported significantly higher symptom levels of depression and anxiety than the remaining groups. A better understanding of risk factor profiles could help to develop targeted prevention and intervention programs during pandemics.

COVID-19 vaccine attitudes and facilitators among people in Australia who inject drugs.

INTRODUCTION: We aimed to describe COVID-19 vaccination attitudes and identify potential facilitators for vaccine uptake among people who inject drugs. METHODS: People who inject drugs were recruited from all eight Australian capital cities (N = 884; 65% male, mean age 44 years) and interviewed face-to-face or via telephone in June-July 2021. COVID-19 and broader vaccination attitudes were used to model latent classes. Correlates of class membership were assessed through multinomial logistic regression. Probability of endorsing potential vaccination facilitators were reported by class. RESULTS: Three classes of participants were identified: 'vaccine acceptant' (39%), 'vaccine hesitant' (34%) and 'vaccine resistant' (27%). Those in the hesitant and resistant groups were younger, more likely to be unstably housed and less likely to have received the current season influenza vaccine than the acceptant group. In addition, hesitant participants were less likely to report a chronic medical condition than acceptant participants. Compared to vaccine acceptant and hesitant participants, vaccine-resistant participants were more likely to predominantly inject methamphetamine and to inject drugs more frequently in the past month. Both vaccine-hesitant and resistant participants endorsed financial incentives for vaccination and hesitant participants also endorsed facilitators related to vaccine trust. DISCUSSION AND CONCLUSION: People who inject drugs who are unstably housed or predominantly inject methamphetamine are subgroups that require targeted interventions to increase COVID-19 vaccination uptake. Vaccine-hesitant people may benefit from interventions that build trust in vaccine safety and utility. Financial incentives may improve vaccine uptake among both hesitant and resistant people.

Who is lost to follow-up in HIV care? Assessment of care retention over time and the impact of COVID-19. Longitudinal analysis of the PISCIS cohort.

INTRODUCTION: People living with HIV who are lost to follow-up have a greater risk of health deterioration, mortality, and community transmission. OBJECTIVE: Our aim was to analyse both how rates of loss to follow-up (LTFU) changed between 2006 and 2020 and how the COVID-19 pandemic affected these rates in the PISCIS cohort study of Catalonia and the Balearic Islands. METHODS: We analysed socio-demographic and clinical characteristics of LTFU yearly and with adjusted odds ratios to assess the impact of these determinants on LTFU in 2020 (the year of COVID-19). We used latent class analysis to categorize classes of LTFU based on their socio-demographic and clinical characteristics at each year. RESULTS: In total, 16.7% of the cohort were lost to follow-up at any time in the 15 years (n = 19 417). Of people living with HIV who were receiving follow-up, 81.5% were male and 19.5% were female; of those who were lost to follow-up, 79.6% and 20.4% were male and female, respectively (p < 0.001). Although rates of LTFU increased during COVID-19 (1.11% vs. 0.86%, p = 0.024), socio-demographic and clinical factors were similar. Eight classes of people living with HIV who were lost to follow-up were identified: six for men and two for women. Classes of men (n = 3) differed in terms of their country of birth, viral load (VL), and antiretroviral therapy (ART); classes of people who inject drugs (n = 2) differed in terms of VL, AIDS diagnosis, and ART. Changes in rates of LTFU included higher CD4 cell count and undetectable VL. CONCLUSIONS: The socio-demographic and clinical characteristics of people living with HIV changed over time. Although the circumstances of the COVID-19 pandemic increased the rates of LTFU, the characteristics of these people were similar. Epidemiological trends among people who were lost to follow-up can be used to prevent new losses of care and to reduce barriers to achieve Joint United Nations Programme on HIV/AIDS 95-95-95 targets.

Coping with Covid: Exploring reconfigurations of Flemish news repertoires in the wake of the COVID-19 pandemic.

As we are now rounding up our second year with COVID-19, studies have provided insight into the pandemic's impact on news practices around the world. However, most of these accounts describe data from the early months of the outbreak. Further research is needed to explore the shapes that news repertoires might have settled into in the wake of the pandemic. By comparing data from a Latent Class Analysis of news repertoires using the Digital News Report 2020 and 2021, this paper contributes to extant knowledge of the pandemic's impact on news use in Flanders. We find that users were significantly more likely to adopt Casual rather than Limited news repertoires in 2021, pointing to a potential growth in news habits of users with a previously limited repertoire.