It's been a good pandemic for me': Working with coaching and psychotherapy clients, with a focus on clients with a diagnosis of pure obsessive compulsive disorder

Many of the coaching clients are high achievers and in most of the prepandemic sessions presented as confident, in control and professional. Their reasons for coaching were often focused on their desire to move to the next level, which called for them to identify their strengths and perceived weaknesses and take action to address the identified gaps in their skills and knowledge through the coaching or through further training. This chapter offers a 'good enough' experience for clients and so, during the pandemic, moved reluctantly to working via online platforms or telephone sessions, depending on the client's preference. During the pandemic it is encouraged to build in the time to take walks before and after online sessions and, when it became possible to do so, to start taking that coffee time again rather than going straight from an online psychotherapy session to online business. The client with a pure obsessive compulsive disorder (POCD) diagnosis also saw benefits to their being-in-the-world from the pandemic. POCD often manifests as intrusive, inappropriate and shameful thoughts on which the person will ruminate. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

MIMIC model of teachers and students attitudes towards online learning during Covid-19: A gender perspective

Academic institutions around the globe have shifted to online learning because of the unpredictable spread of COVID-19. The present study aimed to compare teachers' and students' attitudes towards online learning during the pandemic and to examine the effects of gender differences on their attitudes. In study 1, we adapted the Test of eLearning Related Attitudes for Pakistani students in three steps: expert review, piloting, and validation. The individual and collective expert review was performed to adapt the teacher version into the student version using the Technique for Research of Information by the Animation of a Group of Experts (TRIAGE). We tested three sets of measurement invariance models for participants' status and gender in study 2. Data were collected from 289 university teachers (men = 158, women = 131) and 444 undergraduate students (boys = 156, girls = 287). The results demonstrated that both groups had highly positive yet different attitudes towards online learning. Teachers were more satisfied than students. Model fit was poor, and the overall factor structure, factor loadings, and intercepts varied across groups. Intergroup gender invariance illustrated heterogeneity in attitudes towards online learning favoring men teachers and boy students. Study strengths and implications for the promotion of a positive experience of online learning are discussed.

E-Learning Readiness Assessment Using Machine Learning Methods

Assessing e-learning readiness is crucial for educational institutions to identify areas in their e-learning systems needing improvement and to develop strategies to enhance students' readiness. This paper presents an effective approach for assessing e-learning readiness by combining the ADKAR model and machine learning-based feature importance identification methods. The motivation behind using machine learning approaches lies in their ability to capture nonlinearity in data and flexibility as data-driven models. This study surveyed faculty members and students in the Economics faculty at Tlemcen University, Algeria, to gather data based on the ADKAR model's five dimensions: awareness, desire, knowledge, ability, and reinforcement. Correlation analysis revealed a significant relationship between all dimensions. Specifically, the pairwise correlation coefficients between readiness and awareness, desire, knowledge, ability, and reinforcement are 0.5233, 0.5983, 0.6374, 0.6645, and 0.3693, respectively. Two machine learning algorithms, random forest (RF) and decision tree (DT), were used to identify the most important ADKAR factors influencing e-learning readiness. In the results, ability and knowledge were consistently identified as the most significant factors, with scores of ability (0.565, 0.514) and knowledge (0.170, 0.251) using RF and DT algorithms, respectively. Additionally, SHapley Additive exPlanations (SHAP) values were used to explore further the impact of each variable on the final prediction, highlighting ability as the most influential factor. These findings suggest that universities should focus on enhancing students' abilities and providing them with the necessary knowledge to increase their readiness for e-learning. This study provides valuable insights into the factors influencing university students' e-learning readiness.

Skills Training of Infectious Diseases in the Community：a Survey Research of Questions

Background As the most basic unit of infectious disease prevention and control，community health service institutions are the frontline and important gateway for the prevention and control of infectious disease. Primary care physicians are responsible for epidemic surveillance，vaccination，health promotion and assistance to centers for disease control in investigating and disposing outbreaks and public health emergencies in their districts，and play an active role in disease prevention and control by groups，susceptible population protection，infectious source control and health education，as well as the effective prevention and control of infectious diseases. Objective To understand the ability of primary care physicians to diagnose and treat infectious diseases in the community，analyse their existing problems and shortcomings，design and conduct a series of intensive training related to infectious diseases for improving the capacity of infectious disease prevention and control at the primary level；To evaluate the effectiveness of online continuing medical education，so as to provide a reference for better continuing medical education on infectious diseases in the community. Methods All participants of the National Community Infectious Diseases Continuing Education Conference held by the Department of Family Medicine of the University of Hong Kong-Shenzhen Hospital in November 2021 were selected as research subjects from November 2021 to March 2022. The questionnaires were distributed to all registered attendees before and after the conference through the QR code of the questionnaire star，and the content of pre-conference questionnaire included demographic characteristics of the participants，participation in infectious disease training in the community since started working，diagnosis and treatment of infectious diseases in the community，subjective attitudes towards the prevention and control of infectious diseases in the community（willingness to manage infectious diseases in the community，satisfaction with their own infectious disease management skills），expertise in infectious disease prevention and control and knowledge related to conference content，attitude towards hepatitis B. The content of the post-conference questionnaire mainly included knowledge about the content of conference，attitude towards hepatitis B and satisfaction survey of this online conference. A total of 301 primary care physicians completed the questionnaire before and after the conference，and a total of 194 completed the questionnaire before and after the conference. Results Among all participants，166 （55.1%） had attended infectious disease training in the community，of whom 49（29.5%） were satisfied with their infectious disease diagnosis and treatment ability；135（44.8%） had not attended the training，of whom 22（16.3%） were satisfied with their infectious disease diagnosis and treatment ability. 143（86.1 %） of 166 participants who had attended infectious disease training in the community indicated their willingness to manage community infectious diseases，99（73.3%） of 135 participants who had not attended infectious disease training in the community indicated their willingness to manage community infectious diseases. 66（27.3%） of participants who were satisfied with their infectious disease diagnosis and treatment ability indicated their willingness to manage community infectious diseases. The top three infectious disease tests conducted by the institutions were hepatitis B，AIDS，and hepatitis C；the top three infectious diseases treated in the past six months were hepatitis B，influenza，hand，foot and mouth disease. Different self-evaluation and willingness to train may affect the willingness to manage community infectious diseases（P<0.05）. Among the participants who completed the questionnaire both before and after the conference，the highest correct answer rate for compulsory management of statutory infectious diseases before the conference was 89.7%，the owest accuracy rate for the type of disinfection of the COVID-19 infection was only 17.0%，the correct rates of other questions ranged from 34.0% to 40.7%. The correct rates of the questions after the conference were higher than those before the conference，and the correct rates ranged from 48.9% to 52.6%. The score of attitude towards hepatitis B after the conference was higher than that before the conference （P<0.05）. In terms of feedback after conference，254（98.1%） expressed satisfaction in the total of 259 questionnaires. In terms of suggestions for online conference，179（69.1%） and 174（67.2%） participants believed that online fluency and online interaction need to be improved. Conclusion The primary care physicians receive relatively less infectious diseases training in the community，inadequate infectious diseases training in the community can improve the confidence of self-competence，attitude of active management of infectious diseases and diagnosis and treatment ability in the primary care physicians. The future direction of continuing medical education should focus on the training of emerging infectious diseases and novel medical concepts，relevant experts should be invited to comment on the necessity and effectiveness of training in the community. © 2023 Chinese General Practice. All rights reserved.

The Syncretic Effect of Dual-Source Data on Affective Computing in Online Learning Contexts: A Perspective from Convolutional Neural Network with Attention Mechanism

Affective computing (AC) has been regarded as a relevant approach to identifying online learners' mental states and predicting their learning performance. Previous research mainly used one single-source data set, typically learners' facial expression, to compute learners' affection. However, a single facial expression may represent different affections in various head poses. This study proposed a dual-source data approach to solve the problem. Facial expression and head pose are two typical data sources that can be captured from online learning videos. The current study collected a dual-source data set of facial expressions and head poses from an online learning class in a middle school. A deep learning neural network using AlexNet with an attention mechanism was developed to verify the syncretic effect on affective computing of the proposed dual-source fusion strategy. The results show that the dual-source fusion approach significantly outperforms the single-source approach based on the AC recognition accuracy between the two approaches (dual-source approach using Attention-AlexNet model 80.96%;single-source approach, facial expression 76.65% and head pose 64.34%). This study contributes to the theoretical construction of the dual-source data fusion approach, and the empirical validation of the effect of the Attention-AlexNet neural network approach on affective computing in online learning contexts.

Challenges of Teaching English Language Online: Teachers Perspective

Virtual online teaching was adopted at the Iraqi educational institutions: schools and universities when COVID-19 break out. It was the only alternative to revival the education sector after locking down schools and universities by the condition of the quarantine. The scenario of locking down schools and universities after the spread of COVID-19 pandemic pushed stakeholders and decision makers to switch the educational process to the online mode (Thi1 &Minh, 2021). This sudden shift arose many issues and challenges which was faced by both teachers as well as learners, soon questions about the validity and authenticity of the educational process and outcomes were raised. The current study seeks to uncover hidden issues and challenges which English language teachers at Diyala University encounter at this critical period 2019-2022. A semi-structured interview was utilized as the instrument of this small scale qualitative and descriptive study. The qualitative raw data obtained from the interview transcripts were thematically coded and analyzed. The finding were interpreted in two directions: first: failure of the new online teaching process in obtaining the desired educational outcomes outlined by the ministries of education and higher education due to several reasons: uncontrolled examination session which led to student cheating and resulted in unauthentic grading marks. In addition to internet connection issues which is added to the teachers burden and affect negatively EFL teaching process. Secondly: it was proven that online teaching can be beneficial in the sense that it can save time and effort if new strategies of assessment were adopted, intensive training courses for teachers as well as students were applied, in addition to providing good internet service for both student and teacher. © 2023 Otjivanda Presse.Essen. All rights reserved.

MOOCs Usage in Russian Higher Educational Institutions: Why Is Not There Any Increasing Demand for MOOCs During Emergency Distance Learning

The abrupt transition to distance learning during the outbreak of the COVID-19 pandemic triggered an urgent need for online resources at higher education institutes (HIEs). Creating analogues of traditional full-time courses demanded for competencies and time resources. In this case ready-made massive open online courses (MOOCs) were supposed to be the most obvious and fastest solution for HIEs. However, analytics demonstrated that educational institutions did not consider MOOC a promising option. This contradiction served as an incentive to conduct this research, which includes the analysis of both non-reactive (MOOCs platform analytics) and reactive (online survey and interviews with instructors) data. Based on our research, we can conclude that the reasons for not integrating MOOCs at Russian HIEs during the COVID-19 pandemic are the following: the peculiarities of MOOCs format, low motivation of instructors, administrative risks, and the uncertainty of HIEs' and national policies on MOOCs integration. This article will be useful for those who determine educational policy in Russia, university administrators, methodologists responsible for the development of digital educational technologies in HIEs, as well as researchers of higher education. © 2023 Moscow Polytechnic University. All rights reserved.

THE APPLICABILITY OF ONLINE DISPUTE RESOLUTION (ODR) IN THE BRAZILIAN LEGAL SYSTEM: DISPUTE RESOLUTION BY JUDICIARY BRANCH IN DIGITAL MEDIA AND THEIR REFLECTIONS DURING SOCIAL ISOLATION

The paper aims to give an account on the development of the online dispute resolution (ODR) in the Brazilian legal reality, as an alternative to the traditional model. The description of the aspects of ODR, demonstrating its versatility in the face of disputes endured by contemporary society were achieved through a qualitative methodology based on bibliographical research, international and national diplomas. Then, its execution is observed in foreign legal system, considering its particularities. After that, the birth of online dispute resolution is highlighted in the Brazilian legal system and its gradual regulation before the pandemic situation of SARS-CoV-2. In conclusion, the study asserts the effectiveness and flexibility of ODR for dispute resolution in front of the Judiciary Branch. © 2022, Universidade do Estado do Rio de Janeiro. All rights reserved.

Performance Analysis of Learner Behavior Through Online Learning Using Learning Management System

This paper discusses the performance analysis of learner behavior through online learning using Learning Management System (LMS). The analysis is performed based on the survey of lecturers and students activities. The parameters of survey consist of the problems discussion which arise in the online learning, the level of student absorption of lecture material, the level of student attendance, and the feedback on lecturer performance carried out by students. Problems that arise in the online learning include lecturers are not being able to control as much as 37%, network disturbances are as much as 22%, students having difficulty understanding lecture material are as much as 19% which are indicated by students with D score of 10%, C score of 60%, and B score of 30%. Meanwhile 17% of students use LMS and the remaining 5% have no problems with the online learning. On the other hand, students have difficulty obtaining connection for online learning of 45%, do not have a quota of 28%, and lazy of 17%. Lecturer performance feedback carried out by students based on competency parameters of pedagogic, personality, professionalism, and social shows very good score. © 2023 IEEE.

Large-Scale Analysis of New Employee Network Dynamics

The COVID-19 pandemic has accelerated digital transformations across industries, but also introduced new challenges into workplaces, including the difficulties of effectively socializing with colleagues when working remotely. This challenge is exacerbated for new employees who need to develop workplace networks from the outset. In this paper, by analyzing a large-scale telemetry dataset of more than 10,000 Microsoft employees who joined the company in the first three months of 2022, we describe how new employees interact and telecommute with their colleagues during their "onboarding"period. Our results reveal that although new hires are gradually expanding networks over time, there still exists significant gaps between their network statistics and those of tenured employees even after the six-month onboarding phase. We also observe that heterogeneity exists among new employees in how their networks change over time, where employees whose job tasks do not necessarily require extensive and diverse connections could be at a disadvantaged position in this onboarding process. By investigating how web-based people recommendations in organizational knowledge base facilitate new employees naturally expand their networks, we also demonstrate the potential of web-based applications for addressing the aforementioned socialization challenges. Altogether, our findings provide insights on new employee network dynamics in remote and hybrid work environments, which may help guide organizational leaders and web application developers on quantifying and improving the socialization experiences of new employees in digital workplaces. © 2023 ACM.

Embracing DDMT Teaching Model and Design Thinking for Organization Development

The multi-generational workforce presents challenges for organizations, as the needs and expectations of employees vary greatly between different age groups. To address this, organizations need to adapt their development and learning principles to better suit the changing workforce. The DDMT Teaching Model of Tsing Hua STEAM School, which integrates design thinking methodology, aims to address this challenge. DDMT stands for Discover, Define, Model & Modeling, and Transfer. The main aim of this study is to identify the organization development practices (OD) and gaps through interdisciplinary models such as DDMT and design thinking. In collaboration with a healthcare nursing home service provider, a proof of concept using the DDMT-DT model was conducted to understand the challenges in employment and retention of support employees between nursing homes under the healthcare organization. The paper highlights the rapid change in human experiences and mindsets in the work culture and the need for a design curriculum that is more relevant to the current and future workforce. The DDMT-DT approach can help organizations address these challenges by providing a framework for HR personnel to design training curricula that are more effective in addressing the issues of hiring and employee retention. By applying the DDMT-DT model, HR personnel can better understand the needs and motivations of the workforce and design training programs that are more relevant to their needs. The proof-of-concept research pilot project conducted with the healthcare nursing home service provider demonstrated the effectiveness of the DDMT-DT model in addressing the issues of hiring and employee retention. The project provides a valuable case study for other organizations looking to implement the DDMT-DT model in their HR practices. Overall, the paper highlights the importance of adapting HR practices to better suit the changing workforce. The DDMT-DT model provides a useful framework for organizations looking to improve their HR practices and better address the needs of their workforce.

Learner' Online Self-regulated Learning Skills: A Comparison Between Chinese Undergraduates and International African Undergraduates

The outbreak of the COVID-19 pandemic forced students to move from face-to-face learning to online learning. Online learning has high demands on students' Self-regulated Learning (SRL) skills. In this study, a questionnaire that used five-point Likert scale was administrated between international African undergraduates and Chinese undergraduate students to investigate their online learning behaviors. The questionnaire was composed of six categories: environment structuring, goal setting, time management, help-seeking, task strategies, and self-evaluation. 441 valid responses were received, 89 from international African students and 352 from Chinese undergraduates. The collected data were analyzed with SPSS Version 24.0. The results showed that there was no significant difference between Chinese student' and international African students' SRL skills in the six sub-scales. This may be due to the small sample size of African students and the similar learning environment. Larger samples are needed in future research to further verify the conclusion. The research results can be used as a reference for the future online learning design to strengthen learners' SRL skills. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Connectivity, community, and sense of belonging

This chapter illustrates how the change to a virtual setting challenged students' social connectedness and sense of belonging. It demonstrates how students found a way to build social connectedness in a virtual setting that reinforced their sense of community. The chapter discusses how Students of Color experienced the COVID-19 interruption. It offers insights into whether thriving in college is even possible for students when their means of creating community have been disrupted. At the University of Utah, the detachment was experienced by students in their interactions with faculty and their relationships with their friends, peers, and classmates. The closing of campus and the shift to online learning also limited students' social connectedness with friends, classmates, and peers. Students also relied on new communities to gain motivation and achieve academically. University employees were also a part of students' relational communities. Some students created a strong emotional connection with staff members, such as advisors and student affairs professionals. The pandemic and the resulting educational changes added another layer of complexity to the academic experiences of Students of Color. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Online education action for defeating COVID-19 in China: An analysis of the system, mechanism and mode

This study explores the online education action for defeating COVID-19 in China from the perspectives of the system, mechanism and mode. In particular, the policy development of online education in China during the epidemic includes the education informatization policy, the online education system, and the online education mechanism in China. The online education and teaching mode during the epidemic involve the synchronous live class-based teaching mode, asynchronous recording and broadcasting teaching mode, online flipped classroom teaching mode, and online tutoring-based teaching mode. Both characteristics and trends of online education in China during the epidemic have been explored in this study. In addition, the problems, discussions and remarks are also offered.

Impact of Teachers' Support Strategies on Students' Engagement of Online College English Class Experiences

During the covid-19 pandemic, students' online learning quality is imbued with teachers' support strategies while students' learning engagement is another great indicator underlies their learning experiences. Through a questionnaire survey of 500 freshmen who have had their college English class online in 2022 fall, an investigation using exploratory factor analysis, Pearson correlation analysis, stepwise regression analysis and parallel mediator model reveals the impact of teachers' support strategies (the six dimensions of challenge, authentic context, curiosity, autonomy, recognition and feedback) on the learners' online college English learning engagement (the four dimensions of cognitive engagement, behavioral engagement, emotional engagement, social engagement), thus particular concern is also given to the correlation with students' online learning experiences. It was found that even under diversified and comprehensive guiding strategies from teachers, university students' online college English learning engagement is at the medium level, among which the cognitive engagement should be devoted more. The experimental data also shows that teachers' support strategies have significant influence on learners' engagement, especially teachers' feedback and challenge setting will stimulate students to involve more in their study. In addition, both teachers' support strategies and students' learning engagement involves significant reflection of learning experiences accordingly. Based on this learning concept, related proposals see different degrees of prominence reflected in online instructional design, teachers' and students' feedback literacy, and technology-enabled innovative teaching practice are put forward, in order to effectively play the role of teacher scaffolding, learning experiences enrichment and students' engagement enhancement of online English learning. © 2023 IEEE.

Research on the Relationship between Teacher Expectations and College Students' Online English Learning Engagement

As a critical influencing factor of learning engagement, teacher expectation plays a vital role in ensuring the quality of online teaching under COVID-19. This paper investigates the relationship between teacher expectations (three dimensions of teacher support, teaching interaction, and academic feedback) on students' online English learning engagement (three dimensions of cognitive engagement, behavioral engagement, and emotional engagement) in e-learning through a questionnaire survey of 513 college students. Pearson correlation analysis and multiple regression analysis were applied as research methods. The results manifest that college students' online English learning engagement was above average, but emotional engagement needs improvement. In addition, teacher expectations of teaching interaction positively and significantly predict English e-learning engagement. Based on this, the article puts forward suggestions on the future of online teaching from the aspects of online teaching design, feedback quality of teachers and students, innovative teaching practice of technology empowerment to effectively play the role of teachers as scaffolding and improve the effectiveness of online English teaching. © 2023 IEEE.

Has COVID-19 Changed Consumers' Satisfiers and Dissatisfiers? Evidence from Online Reviews of 5-Star Hotels in Shanghai and Beijing

Many studies have analyzed the asymmetric relationship between hotel service quality attributes and satisfaction, and tried to find consumers' satisfiers and dissatisfiers, aiming at enhancing satisfaction more efficiently. However, the impact of COVID-19 has led to changes in consumers' expectations for hotel services, and the above findings might face invalidation. To date, we are still unknown whether consumers' satisfiers/dissatisfiers changed. This study fills this research gap by mining online reviews of five-star hotels from Shanghai and Beijing before and during the pandemic. The results found that the asymmetric categories of Sleep quality and Internet/Wi-Fi attributes have changed. Specifically, Sleep quality and Internet/Wi-Fi became dissatisfiers from hybrids, indicating that hoteliers only need to maintain their normal performance, and do not invest too many resources because they bring no satisfaction;attributes like Room, decoration, etc. remain hybrids. Additionally, we performed opinion extraction for the dissatisfier attributes to further understand what causes consumer dissatisfaction. The results contribute to the literature by shedding light on the pandemic's impacts on the asymmetric effects of service quality attributes. The cause analysis can help hoteliers develop specific measures to mitigate the adverse effects of COVID-19.

Exploring Social Media for Early Detection of Depression in COVID-19 Patients

The COVID-19 pandemic has caused substantial damage to global health. Even though three years have passed, the world continues to struggle with the virus. Concerns are growing about the impact of COVID-19 on the mental health of infected individuals, who are more likely to experience depression, which can have long-lasting consequences for both the affected individuals and the world. Detection and intervention at an early stage can reduce the risk of depression in COVID-19 patients. In this paper, we investigated the relationship between COVID-19 infection and depression through social media analysis. Firstly, we managed a dataset of COVID-19 patients that contains information about their social media activity both before and after infection. Secondly, We conducted an extensive analysis of this dataset to investigate the characteristic of COVID-19 patients with a higher risk of depression. Thirdly, we proposed a deep neural network for early prediction of depression risk. This model considers daily mood swings as a psychiatric signal and incorporates textual and emotional characteristics via knowledge distillation. Experimental results demonstrate that our proposed framework outperforms baselines in detecting depression risk, with an AUROC of 0.9317 and an AUPRC of 0.8116. Our model has the potential to enable public health organizations to initiate prompt intervention with high-risk patients. © 2023 ACM.

Student Perspective of Online Pedagogy Post COVID-19. A Missed Opportunity?

The COVID-19 pandemic has significantly changed education and caused unprecedented disruptions. These changes may disappear once the schools resume face-to-face classes in full force. Likewise, a positive change may not be necessarily what we want in education. This may be due to the existence of digital divide among students which cannot be ignored. During the COVID-19 pandemic, OneNote Class Notebook is used as an interactive digital whiteboard and has been evident as one of the best alternatives to the traditional whiteboard in the teaching and learning process. In this study, we aim to analyze students' perceptions of OneNote Class Notebook and the level of their continuous intention to use OneNote Class Notebook as an interactive digital whiteboard to replace the traditional whiteboard when school reopens with face-to-face lessons in the classroom in full force. The findings show that the students perceived that OneNote Class Notebook is indeed a useful tool to be used for calculus learning. But, it cannot be perceived as suitability to continue to be used during post COVID-19 period, when school reopens with physical classes in full force. In this regard, it reminds educators of the importance of rethinking education in the new normal post COVID-19 era from the perspective of curriculum studies. © 2023 IEEE.

Trends in cybercrime during the COVID-19 pandemic

The COVID-19 pandemic accelerated many organisations' reliance on the Internet, with schools, companies, and government agencies, among other institutions, all shifting their operations online in a relatively short period of time. This sudden shift created opportunities for cybercriminals, as did the burden on the healthcare sector, the rush for unemployment benefits, and the desire for up-to-date information about outbreaks and health precautions. This chapter examines the trends in cybercrime during the COVID-19 pandemic that were spurred by these changes, as well as the mitigation measures implemented by government and private industry stakeholders to help protect critical infrastructure and online operations. It argues that the nature of cybercrime and the most common forms of criminal activity did not change substantially during the pandemic, but rather that criminals' focus on whom to target and how to exploit evolving current events enabled them to wield existing criminal tools to greater effect, and potentially also at greater scale, though reliable statistics on the frequency and size of cybercrimes are scarce. Finally, the chapter considers how these trends in cybercrime forced private organisations and governments to undertake new cybersecurity measures and programs and whether the long-term effects of the pandemic might actually include stronger cybersecurity if these efforts continue past the end of the public health crisis. © 2023 the authors.