Maternal distress and parenting during COVID-19: differential effects related to pre-pandemic distress?

BACKGROUND: Distinguishing whether and how pre-existing characteristics impact maternal responses to adversity is difficult: Does prior well-being decrease the likelihood of encountering stressful experiences? Does it protect against adversity's negative effects? We examine whether the interaction between relatively uniformly experienced adversity (due to COVID-19 experience) and individual variation in pre-existing (i.e., pre-pandemic onset) distress predicted mothers' pandemic levels of distress and insensitive caregiving within a country reporting low COVID-19 death rates, and strict nationwide regulations. METHOD: Fifty-one Singaporean mothers and their preschool-aged children provided data across two waves. Pre- pandemic onset maternal distress (i.e., psychological distress, anxiety, and parenting stress) was captured via self-reports and maternal sensitivity was coded from videos. Measures were repeated after the pandemic's onset along with questionnaires concerning perceived COVID-19 adversity (e.g., COVID-19's impact upon stress caring for children, housework, job demands, etc.) and pandemic-related objective experiences (e.g., income, COVID-19 diagnoses, etc.). Regression analyses (SPSS v28) considered pre-pandemic onset maternal distress, COVID-19 stress, and their interaction upon post-pandemic onset maternal distress. Models were re-run with appropriate covariates (e.g., objective experience) when significant findings were observed. To rule out alternative models, follow up analyses (PROCESS Model) considered whether COVID-19 stress mediated pre- and post-pandemic onset associations. Models involving maternal sensitivity followed a similar data analytic plan. RESULTS: Pre-pandemic maternal distress moderated the association between COVID-19 perceived stress and pandemic levels of maternal distress (ß = 0.22, p < 0.01) but not pandemic assessed maternal sensitivity. Perceived COVID-19 stress significantly contributed to post-pandemic onset maternal distress for mothers with pre-pandemic onset distress scores above (ß = 0.30, p = 0.05), but not below (ß = 0.25, p = 0.24), the median. Objective COVID-19 adversity did not account for findings. Post-hoc analyses did not suggest mediation via COVID-19 stress from pre-pandemic to pandemic maternal distress. CONCLUSIONS: Pre-existing risk may interact with subsequent perceptions of adversity to impact well-being. In combination with existing research, this small study suggests prevention programs should focus upon managing concurrent mental health and may highlight the importance of enhanced screening and proactive coping programs for people entering high stress fields and/or phases of life.

Digital Disease Surveillance for Emerging Infectious Diseases: An Early Warning System Using the Internet and Social Media Data for COVID-19 Forecasting in Canada.

BACKGROUND: Emerging Infectious Diseases (EID) are a significant threat to population health globally. We aimed to examine the relationship between internet search engine queries and social media data on COVID-19 and determine if they can predict COVID-19 cases in Canada. METHODS: We analyzed Google Trends (GT) and Twitter data from 1/1/2020 to 3/31/2020 in Canada and used various signal-processing techniques to remove noise from the data. Data on COVID-19 cases was obtained from the COVID-19 Canada Open Data Working Group. We conducted time-lagged cross-correlation analyses and developed the long short-term memory model for forecasting daily COVID-19 cases. RESULTS: Among symptom keywords, "cough," "runny nose," and "anosmia" were strong signals with high cross-correlation coefficients >0.8 ( rCough = 0.825, t - 9; rRunnyNose = 0.816, t - 11; rAnosmia = 0.812, t - 3 ), showing that searching for "cough," "runny nose," and "anosmia" on GT correlated with the incidence of COVID-19 and peaked 9, 11, and 3 days earlier than the incidence peak, respectively. For symptoms- and COVID-related Tweet counts, the cross-correlations of Tweet signals and daily cases were rTweetSymptoms = 0.868, t - 11 and tTweetCOVID = 0.840, t - 10, respectively. The LSTM forecasting model achieved the best performance (MSE = 124.78, R2 = 0.88, adjusted R2 = 0.87) using GT signals with cross-correlation coefficients >0.75. Combining GT and Tweet signals did not improve the model performance. CONCLUSION: Internet search engine queries and social media data can be used as early warning signals for creating a real-time surveillance system for COVID-19 forecasting, but challenges remain in modelling.

Investigating Canadian Public Attitudes Toward COVID-19 Vaccine Mandates with a Nested Analysis Framework.

BACKGROUND: Social media is an important medium for studying public attitudes toward COVID-19 vaccine mandates in Canada, and Reddit network communities are a good source for this. METHODS: This study applied a "nested analysis" framework. We collected 20378 Reddit comments via the Pushshift API and developed a BERT-based binary classification model to screen for relevance to COVID-19 vaccine mandates. We then used a Guided Latent Dirichlet Allocation (LDA) model on relevant comments to extract key topics and assign each comment to its most relevant topic. RESULTS: There were 3179 (15.6%) relevant and 17199 (84.4%) irrelevant comments. Our BERT-based model achieved 91% accuracy trained with 300 Reddit comments after 60 epochs. The Guided LDA model had an optimal coherence score of 0.471 with four topics: travel, government, certification, and institutions. Human evaluation of the Guided LDA model showed an 83% accuracy in assigning samples to their topic groups. CONCLUSION: We develop a screening tool for filtering and analyzing Reddit comments on COVID-19 vaccine mandates through topic modelling. Future research could develop more effective seed word-choosing and evaluation methods to reduce the need for human judgment.

Tele-Balint under the microscope: What really happens in Tele-Balint groups?

OBJECTIVE: Balint groups provide a safe space for clinicians to discuss difficult cases, with the aim of deepening the clinician-patient relationship and providing space for self-introspection and personal development. During this COVID-19 period, mental health clinicians need a platform to undergo professional supervision and peer learning sessions, which can be provided for by Tele-Balint sessions. This study aims to understand the workings of Balint groups in a multi-disciplinary team, through exploring the experience and perceptions of mental health clinicians in a tertiary obstetrics- and paediatrics-focused hospital in Singapore towards Tele-Balint groups, and examining if these groups can address their professional needs. METHOD: A mixed-methods study was conducted. 26 mental health clinicians who had participated in Tele-Balint groups since March 2020 completed a semi-structured questionnaire, and 12 of them were interviewed. Qualitative analysis of interview transcripts was performed. RESULTS: Qualitative analysis revealed 5 themes. The first 4: professional and personal growth of clinicians, providing emotional support to clinicians, burnout in clinicians: what contributes and what helps, and psychological safety, address whether Tele-Balint groups meet clinicians' needs. The last theme, evolution of nature of Balint groups, addresses whether Tele-Balint groups meet clinicians' needs during the time of a pandemic. CONCLUSIONS: Tele-Balint group participation was found to be beneficial in facilitating personal and professional growth, providing emotional support and preventing burnout, despite some limitations. Members should maintain flexibility towards the Balint process, in order to accommodate others who have differing needs, especially in a multi-disciplinary group.

Navigating the cellular landscape in tissue: Recent advances in defining the pathogenesis of human disease.

Over the past decade, our understanding of human diseases has rapidly grown from the rise of single-cell spatial biology. While conventional tissue imaging has focused on visualizing morphological features, the development of multiplex tissue imaging from fluorescence-based methods to DNA- and mass cytometry-based methods has allowed visualization of over 60 markers on a single tissue section. The advancement of spatial biology with a single-cell resolution has enabled the visualization of cell-cell interactions and the tissue microenvironment, a crucial part to understanding the mechanisms underlying pathogenesis. Alongside the development of extensive marker panels which can distinguish distinct cell phenotypes, multiplex tissue imaging has facilitated the analysis of high dimensional data to identify novel biomarkers and therapeutic targets, while considering the spatial context of the cellular environment. This mini-review provides an overview of the recent advancements in multiplex imaging technologies and examines how these methods have been used in exploring pathogenesis and biomarker discovery in cancer, autoimmune and infectious diseases.

Service process factors affecting patients' and clinicians' experiences on rapid teleconsultation implementation in out-patient neurology services during COVID-19 pandemic: a scoping review.

BACKGROUND: The adoption of teleconsultation for outpatient neurology services was limited until the onset of the COVID-19 pandemic which forced many outpatient neurology services to rapidly switch to virtual models. However, it remains unclear how this change has impacted patients' and clinicians' perceptions of service quality. The purpose of this scoping review is to identify process factors that influence patients' and clinicians' experiences of outpatient teleconsultation services during COVID-19. METHODS: Arksey and O'Malley scoping review framework was used to search PubMed, Scopus, CINAHL, and PsycInfo for original peer-reviewed research studies that examined the experiences of synchronous teleconsultation between a clinician and patient in a home-setting since the World Health Organization announced the COVID-19 global pandemic. The service quality model SERVQUAL was used to conduct a deductive thematic analysis to identify the key factors that impacted the patients' and clinicians' perception of teleconsultation services. RESULTS: A total of nineteen studies published between January 1, 2020, and April 17, 2021, were identified. The most common service process factors affecting the patients' and clinicians' experiences of teleconsultation were technical issues, addressing logistical needs, communication, ability to perform clinical activities, appropriate triage, and administrative support. CONCLUSIONS: Our findings identified six key service process factors affecting the patients' and clinicians' teleconsultation experiences in outpatient neurology services. The need for improvement of triage process and standardizing administrative virtual care pathway are identified as important steps to improve patients and clinicians' teleconsultation experiences compared to pre-COVID era. More research is needed to assess outpatient neurology teleconsultation service quality from patients' and clinicians' perspectives.

Public Attitudes During the Second Lockdown: Sentiment and Topic Analyses Using Tweets From Ontario, Canada.

Objective: This study aimed to explore topics and sentiments using tweets from Ontario, Canada, during the second wave of the COVID-19 pandemic. Methods: Tweets were collected from December 5, 2020, to March 6, 2021, excluding non-individual accounts. Dates of vaccine-related events and policy changes were collected from public health units in Ontario. The daily number of COVID-19 cases was retrieved from the Ontario provincial government's public health database. Latent Dirichlet Allocation was used for unsupervised topic modelling. VADER was used to calculate daily and average sentiment compound scores for topics identified. Results: Vaccine, pandemic, business, lockdown, mask, and Ontario were six topics identified from the unsupervised topic modelling. The average sentiment compound score for each topic appeared to be slightly positive, yet the daily sentiment compound scores varied greatly between positive and negative emotions for each topic. Conclusion: Our study results have shown a slightly positive sentiment on average during the second wave of the COVID-19 pandemic in Ontario, along with six topics. Our research has also demonstrated a social listening approach to identify what the public sentiments and opinions are in a timely manner.

Improving the Care of Diverse Patient Populations: Let's Advance the Dialogue for Strategies to Address and Navigate the Elephant in the Room (P05)

Outcomes 1. Understand the development of cultural humility by completing a real-time self-assessment of implicit biases 2. Demonstrate recognition of individual implicit biases and exercise cultural curiosity via use of 1 or 2 components of the 5 “R”s tool, which includes cultural humility, mindfulness and compassion 3. Recognize 1 or 2 strategies intended to improve understanding of the cultural values and preferences of those from other cultures Cultural beliefs shape perceptions of illness, prognosis, and suffering and inform preferences for palliative and end-of-life care. Cultural identification encompasses many things: age, gender identity, ethnicity, ability, language, sexual orientation, religion, nationality, and socioeconomic status. Cultural identification and beliefs of patients often differ from those of their clinicians. This range of beliefs, values, and preferences in the clinician-patient relationship creates potential for discord, mistrust, and diminished quality of care. Studies suggest that clinicians and patients and families find interactions where cultural discordance exists challenging. Cultural humility has been found to enhance trust, increase the likelihood of clinically competent care, and increase satisfaction. Increasing clinicians’ cultural humility has been suggested as a mechanism for reducing healthcare disparities. Profound disparities in care have been exposed and exacerbated by the COVID-19 pandemic, which may relate to differences in cultural beliefs and mistrust in the healthcare system. Intentionally recognizing, evaluating, and addressing implicit bias and cultural humility, as well as honoring cultural values and preferences, are strategies that promote access to equitable, high quality, patient-centered care. This session will provide practical strategies and tools for clinicians caring for culturally diverse patients and their families. It will include facilitator-guided experiential learning within small groups using videos, role play, and discussion. Participants will learn and practice strategies to explore cultural beliefs, values, and preferences of those with serious illness and the impact on care preferences;develop shared understanding and exercise respect for individuals regardless of potential cultural-discordant dynamics;and enhance clinician resilience by understanding one's own implicit biases and practicing cultural humility strategies. The session will challenge individual beliefs and assumptions to facilitate personal and professional growth and will increase awareness of implicit biases, enhance confidence, and improve comfort in communication while promoting respect for those from cultural communities discordant with our own.

To Advance High-Impact Practices, Improve Institutional Data

The article discusses the need to be attentive to data processes that support High-Impact Practices (HIPs) and explores the importance of better data collection so that institutions can develop quality HIPs. It develops approach entails collaboratively developing data frameworks and collecting data from people across campus, not just those in institutional research offices, as well as including students' voices.

Public Attitudes During the Second Lockdown: Sentiment and Topic Analyses Using Tweets From Ontario, Canada

Objective: This study aimed to explore topics and sentiments using tweets from Ontario, Canada, during the second wave of the COVID-19 pandemic. Methods: Tweets were collected from December 5, 2020, to March 6, 2021, excluding non-individual accounts. Dates of vaccine-related events and policy changes were collected from public health units in Ontario. The daily number of COVID-19 cases was retrieved from the Ontario provincial government’s public health database. Latent Dirichlet Allocation was used for unsupervised topic modelling. VADER was used to calculate daily and average sentiment compound scores for topics identified. Results: Vaccine, pandemic, business, lockdown, mask, and Ontario were six topics identified from the unsupervised topic modelling. The average sentiment compound score for each topic appeared to be slightly positive, yet the daily sentiment compound scores varied greatly between positive and negative emotions for each topic. Conclusion: Our study results have shown a slightly positive sentiment on average during the second wave of the COVID-19 pandemic in Ontario, along with six topics. Our research has also demonstrated a social listening approach to identify what the public sentiments and opinions are in a timely manner.

In Situ Measurement of Airborne Particle Concentration in a Real Dental Office: Implications for Disease Transmission.

Aerosols generated during dental procedures are one of the most significant routes for infection transmission and are particularly relevant now in the context of COVID-19 pandemic. This study aimed to assess the effectiveness of an indoor air purifier on dental aerosol dispersion in dental offices. The spread and removal of aerosol particles generated from a specific dental operation in a dental office are quantified for a single dental activity in the area near the generation and corner of the office. The effects of the air purifier, door condition, and particle sizes on the spread and removal of particles were investigated. The results show that, in the worst-case scenario, it takes 95 min for 0.5-µm particles to settle and that it takes a shorter time for the larger particles. The air purifier expedited the removal time at least 6.3 times faster than the case with no air purifier in the generation zone. Our results also indicate that particles may be transported from the source to the rest of the room even when the particle concentrations in the generation zone dropped back to the background. Therefore, it is inaccurate to conclude that indoor purifiers help reduce the transmission of COVID-19. Dental offices still need other methods to reduce the transmission of viruses.

What social media told us in the time of COVID-19: a scoping review.

With the onset of the COVID-19 pandemic, social media has rapidly become a crucial communication tool for information generation, dissemination, and consumption. In this scoping review, we selected and examined peer-reviewed empirical studies relating to COVID-19 and social media during the first outbreak from November, 2019, to November, 2020. From an analysis of 81 studies, we identified five overarching public health themes concerning the role of online social media platforms and COVID-19. These themes focused on: surveying public attitudes, identifying infodemics, assessing mental health, detecting or predicting COVID-19 cases, analysing government responses to the pandemic, and evaluating quality of health information in prevention education videos. Furthermore, our Review emphasises the paucity of studies on the application of machine learning on data from COVID-19-related social media and a scarcity of studies documenting real-time surveillance that was developed with data from social media on COVID-19. For COVID-19, social media can have a crucial role in disseminating health information and tackling infodemics and misinformation.

Perinatal Anxiety and Depression During COVID-19.

The novel coronavirus disease 2019 (COVID-19) outbreak places perinatal women at higher risk of developing anxiety and depression. Uncertainty, fear, and confusion in medical, social, economic, occupational, and political aspects of life in the United States add to existing stressors that perinatal women experience. To optimize the quality of perinatal care during the pandemic, appropriate mental health interventions must be implemented to prevent and alleviate perinatal anxiety and depression and improve maternal and infant outcomes. Measures include increased screening, nonpharmacologic and/or pharmacologic interventions, and the use of telehealth for care delivery.

Risk Factors, Presentation, and Course of Coronavirus Disease 2019 in a Large, Academic Long-Term Care Facility.

OBJECTIVE: To describe clinical characteristics and risk factors associated with coronavirus disease 2019 (COVID-19) in long-stay nursing home residents. DESIGN AND PARTICIPANTS: Retrospective cohort study (March 16, 2020 to May 8, 2020). SETTING: Academic long-term chronic care facility (Boston, MA). PARTICIPANTS: Long-term care residents. METHODS: Patient characteristics and clinical symptoms were obtained via electronic medical records and Minimum Data Set. Staff residence was inferred by zip codes. COVID-19 infection was confirmed by polymerase chain reaction testing using nasopharyngeal swabs. Residents were followed until discharge from facility, death, or up to 21 days. Risks of COVID-19 infection were modeled by generalized estimating equation to estimate the relative risk (RR) and 95% confidence intervals (CI) of patient characteristics and staff community of residence. RESULTS: Overall 146 of 389 (37.5%) long-stay residents tested positive for COVID-19. At the time of positive test, 66 of 146 (45.5%) residents were asymptomatic. In the subsequent illness course, the most common symptom was anorexia (70.8%), followed by delirium (57.6%). During follow-up, 44 (30.1%) of residents with COVID-19 died. Mortality increased with frailty (16.7% in pre-frail, 22.2% in moderately frail, and 50.0% in frail; P < .001). The proportion of residents infected with COVID-19 varied across the long-term care units (range: 0%‒90.5%). In adjusted models, male sex (RR 1.80, 95% CI 1.07, 3.05), bowel incontinence (RR 1.97, 95% CI 1.10, 3.52), and staff residence remained significant predictors of COVID-19. For every 10% increase in the proportion of staff living in a high prevalence community, the risk of testing positive increased by 6% (95% CI 1.04, 1.08). CONCLUSIONS AND IMPLICATIONS: Among long-term care residents diagnosed with COVID-19, nearly one-half were asymptomatic at the time of diagnosis. Predictors of COVID-19 infection included male sex, bowel incontinence, and staff residence in a community with a high burden of COVID-19. Universal testing of patients and staff in communities with high COVID-19 rates is essential to mitigate outbreaks.