Evolution of the public opinion on COVID-19 vaccination in Japan.

BACKGROUND: Vaccines are promising tools to control the spread of COVID-19. An effective vaccination campaign requires government policies and community engagement, sharing experiences for social support, and voicing concerns about vaccine safety and efficiency. The increasing use of online social platforms allows us to trace large-scale communication and infer public opinion in real-time. OBJECTIVE: This study aims to identify the main themes in COVID-19 vaccine-related discussion on Twitter in Japan and track how the popularity of the tweeted themes evolved during the vaccination campaign. Furthermore, we aim to understand the impact of critical social events on the popularity of the themes. METHODS: We collected more than 100 million vaccine-related tweets written in Japanese and posted by 8 million users (approx. 6.4% of the Japanese population) from January 1 to October 31, 2021. We used the Latent Dirichlet Allocation to perform automated topic modeling of tweet texts during the vaccination campaign. In addition, we performed an interrupted time series regression to evaluate the impact of four critical social events on public opinion. RESULTS: We identified 15 topics grouped into 4 themes: Personal issue, Breaking news, Politics, and Conspiracy and humour. The evolution of the popularity of themes revealed a shift in public opinion, initially sharing the attention over personal issues (individual aspect), collecting information from the news (knowledge acquisition), and government criticisms towards focusing on personal issues. Our analysis showed that the Tokyo Olympic Games affected public opinion more than other critical events but not the course of the vaccination. Public opinion about politics was significantly affected by various social events, positively shifting the attention in the early stages of the vaccination campaign and negatively later. CONCLUSIONS: This study showed a striking shift in public interest in Japan, with users splitting their attention to various themes early in the vaccination campaign and then focusing only on personal issues, as trust in vaccines and policies built up. An interrupted time series regression analysis showed that the vaccination rollout to the general population (under 65) increased the popularity of tweets about practical advice and personal vaccination experience and the Tokyo Olympic Games disrupted public opinions but not the course of the vaccination campaign. The methodology developed here allowed us to monitor the evolution of public opinion and evaluate the impact of social events on the public opinion from large-scale Twitter data.

Noncompliance with Hypertension Treatment and Related Factors among Kumamoto Earthquake Victims Who Experienced the COVID-19 Pandemic during Postearthquake Recovery Period.

Survivors of the Kumamoto earthquake of 2016 experienced the coronavirus disease (COVID-19) outbreak while carrying additional burdens that might bring inadequate coping. This cross-sectional survey aimed to identify untreated and interrupted consultations among those with hypertension and related factors and to identify the disaster's long-term effects. Of the 19,212 earthquake survivors who had moved to permanent housing, 7367 (4196 women and 3171 men, mean age 61.8 ± 17.3 years) completed a self-administered questionnaire. The prevalence of hypertension was 41.4%. The results of the logistic regression analysis with the significant independent variables in the bivariate analysis were: reduced income due to COVID-19 (AOR = 3.23, 95%CI = 2.27-4.58) and poor self-rated health (AOR = 2.49, 95%CI = 1.72-3.61) were associated with a risk of untreated or discontinued treatment. Moreover, living in rental, public or restoration public housing was also significantly associated with a higher risk of hypertension noncompliance (AOR = 1.92, 95%CI = 1.20-3.07; AOR = 2.47, 95%CI = 1.38-4.42; AOR = 4.12, 95%CI = 1.14-14.90). These results suggest that changes due to COVID-19, the extent of self-rated health and the type of permanent housing influence the hypertension consulting behaviour of earthquake survivors during recovery. It is crucial to implement long-term public support for the mental health, income and housing concerns of the survivors.

Latent Dirichlet allocation topic modeling of free-text responses exploring the negative impact of the early COVID-19 pandemic on research in nursing.

AIM: To derive latent topics from free-text responses on the negative impact of the pandemic on research activities and determine similarities and differences in the resulting themes between academic-based and clinical-based researchers. METHODS: We performed a secondary analysis of free-text responses from a cross-sectional online survey conducted by the Japan Academy of Nursing Science of its members in early 2020. The participants were categorized into two groups by workplace (academic-based and clinical-based researchers). Latent Dirichlet allocation (LDA) topic modeling was used to extract latent topics statistically and list important keywords/text associated with the topics. After organizing similar topics by principal component analysis (PCA), we finally derived topic-associated themes by reading the keywords/texts and determining the similarity and differences of the themes between the two groups. RESULTS: A total of 201 respondents (163 academic-based and 38 clinical-based researchers) provided free-text responses. LDA identified eight and three latent topics for the academic-based and clinical-based researchers, respectively. While PCA re-grouped the eight topics derived from the former group into four themes, no merging of the topics from the latter group was performed resulting in three themes. The only theme common to the two groups was "barriers to conducting research," with the remaining themes differing between the groups. CONCLUSIONS: Using LDA topic modeling with PCA, we identified similarities and differences in the themes described in free-text responses about the negative impact of the pandemic between academic-based and clinical-based researchers. Measures to mitigate the negative impact of pandemics on nursing research may need to be tailored separately.

Prediction models for the impact of the COVID-19 pandemic on research activities of Japanese nursing researchers using deep learning.

AIM: This study aimed to construct and evaluate prediction models using deep learning to explore the impact of attributes and lifestyle factors on research activities of nursing researchers during the COVID-19 pandemic. METHODS: A secondary data analysis was conducted from a cross-sectional online survey by the Japanese Society of Nursing Science at the inception of the COVID-19 pandemic. A total of 1089 respondents from nursing faculties were divided into a training dataset and a test dataset. We constructed two prediction models with the training dataset using artificial intelligence (AI) predictive analysis tools; motivation and time were used as predictor items for negative impact on research activities. Predictive factors were attributes, lifestyle, and predictor items for each other. The models' accuracy and internal validity were evaluated using an ordinal logistic regression analysis to assess goodness-of-fit; the test dataset was used to assess external validity. Predicted contributions by each factor were also calculated. RESULTS: The models' accuracy and goodness-of-fit were good. The prediction contribution analysis showed that no increase in research motivation and lack of increase in research time strongly influenced each other. Other factors that negatively influenced research motivation and research time were residing outside the special alert area and lecturer position and living with partner/spouse and associate professor position, respectively. CONCLUSIONS: Deep learning is a research method enabling early prediction of unexpected events, suggesting new applicability in nursing science. To continue research activities during the COVID-19 pandemic and future contingencies, the research environment needs to be improved, workload corrected by position, and considered in terms of work-life balance.

Estimation of mRNA COVID-19 Vaccination Effectiveness in Tokyo for Omicron Variants BA.2 and BA.5: Effect of Social Behavior.

The variability of the COVID-19 vaccination effectiveness (VE) should be assessed with a resolution of a few days, assuming that the VE is influenced by public behavior and social activity. Here, the VE for the Omicron variants (BA.2 and BA.5) is numerically derived for Japan's population for the second and third vaccination doses. We then evaluated the daily VE variation due to social behavior from the daily data reports in Tokyo. The VE for the Omicron variants (BA.1, BA.2, and BA.5) are derived from the data of Japan and Tokyo with a computational approach. In addition, the effect of the different parameters regarding human behavior on VE was assessed using daily data in Tokyo. The individual VE for the Omicron BA.2 in Japan was 61% (95% CI: 57-65%) for the second dose of the vaccination from our computation, whereas that for the third dose was 86% (95% CI: 84-88%). The individual BA.5 VE for the second and third doses are 37% (95% CI: 33-40%) and 63% (95% CI: 61-65%). The reduction in the daily VE from the estimated value was closely correlated to the number of tweets related to social gatherings on Twitter. The number of tweets considered here would be one of the new candidates for VE evaluation and surveillance affecting the viral transmission.

Support nursing researchers' need from academic societies during COVID-19: A cross-sectional survey.

The activities of nursing researchers have been constrained by the COVID-19 pandemic. Therefore, this study aimed to investigate the types of support and related factors that nursing researchers hope to receive from academic societies during the pandemic and to obtain suggestions for the role of academic societies in supporting nursing researchers and expanding research. An online survey was conducted with 1532 Japan Academy of Nursing Science members. The survey included 19 items of potential support from the society during the COVID-19 pandemic as well as open-ended questions. Data were analyzed statistically and qualitatively. For 9 of the 19 items, over 50% of respondents reported that they "needed" or "very much needed" support. Multivariate analysis results showed that younger respondents and those with family members requiring care were significantly more likely to report needs for some items. In the open-ended comments, there were several suggestions for activities, including "Lobbying for revision of regulations on research implementation." Nursing researchers expressed needs for support that reflect their demographic characteristics and situations, including collaboration across organizations and securing research-promotion and skill-development opportunities online.

Relationship between research activities and individual factors among Japanese nursing researchers during the COVID-19 pandemic.

AIM: To explore the individual factors (such as gender, division of household labor, childcare and elder care) and their impact on research activities in the Japanese nursing research community during the early stage of the COVID-19 pandemic from April to June in 2020. DESIGN: Cross-sectional study. METHODS: An online survey with a self-reported questionnaire was conducted on Japan Academy of Nursing Science members to explore the impacts of individual factors among Japanese nursing researchers from April to June 2020. A multivariate logistic regression model was used for data analysis. RESULTS: A total of 1,273 participants (90.7% female, 85.8% university faculty) were included in the analysis. This survey showed that no evidence of a significant gender gap was found in research activities in Japanese nursing researchers during the COVID-19 pandemic. Research activities during the pandemic were associated with time and motivation.

Propensity-matched comparisons of factors negatively affecting research activities during the COVID-19 pandemic between nursing researchers working in academic and clinical settings in Japan.

AIM: To determine the factors associated with reduced research activities during the COVID-19 pandemic in 2020 by comparing nursing researchers working in academic and clinical settings. METHODS: This was a secondary analysis of data collected by the Japan Academy of Nursing Sciences, which conducted a cross-sectional online survey when the pandemic began. We included respondents who worked in either academic or clinical settings and responded that the pandemic negatively affected their research activities. First, we computed a propensity score (PS) using a logistic regression model. Then we performed a one-to-one ratio matching between the groups based on the PS to control imbalances between the groups. We identified the factors negatively affecting research activities and who to consult about research concerns by comparing the groups using Chi-square or Fisher's exact tests. RESULTS: There were 1,532 participants, with a response rate of 16.1%. After PS matching, 214 participants (107 for each group) were included. We identified three significant factors associated with reduced research activities: (i) time required for learning new information and communication technology (ICT) skills; (ii) time required for supporting colleagues with ICT issues; and (iii) time required for preparing and evaluating teaching materials. Approximately 20% of our participants in both settings had nobody to consult regarding research concerns. CONCLUSION: We found that the time spent on ICT-related issues negatively affected the research activities of nursing researchers when the pandemic began in Japan. In such an emergency, nursing researchers needed an opportunity to share their difficulties as a part of a support service.

Characteristics of early-career nurse researchers negatively impacted during the COVID-19 pandemic: a cross-sectional study.

OBJECTIVES: This study aimed to identify typical patterns and determinants of early-career nurse researchers (ECNRs: age ≤45 years) who reported that their research activities were negatively impacted during the COVID-19 pandemic, using a data mining methodology. To gain a deeper understanding of the characteristics of these ECNRs, we compared them with the characteristics of senior nurse researchers (SNRs: age ≥46 years). DESIGN: A cross-sectional study. PARTICIPANTS: 1532 nurse researchers. DATA COLLECTION AND ANALYSIS: We conducted an anonymous online questionnaire survey that assessed individual and professional attributes of nurse researchers and their experiences from April to June 2020. We analysed the association between the impact on research activities and the individual and professional attributes using cross-tabulation, and employed the chi-square automatic interaction detection technique to perform population segmentation. RESULTS: We found that difficulties in research management, an increased burden of student education and organisational management, and organisational management position were relatively important factors for determining the negative impact of COVID-19 on the research activities of ECNRs (p<0.05). For both ECNRs and SNRs, the most relevant determinant of disrupted research activities was 'difficulties in research management' (χ2=34.7 and 126.5, respectively, p<0.001 for both). However, only ECNRs yielded 'position in organisational management' and was extracted only for ECNRs (χ2=7.0, p=0.008). CONCLUSIONS: Difficulties in research management and an increased burden of student education and organisational management had an unfavourable impact on the research activities of ECNRs. To ensure quality of nursing care and nursing science development during and after the COVID-19 era, it is important to support ECNRs in their nursing research activities and career development. Our findings could contribute to the prioritisation of interventions and policymaking for ECNRs who are particularly at risk of being negatively affected by the pandemic.

Initial impact of the COVID-19 pandemic on time Japanese nursing faculty devote to research: Cross-sectional survey.

AIM: To investigate how nursing faculties' perceived time devoted to research changed during the first wave of the pandemic in Japan (April-June 2020) compared to pre-pandemic. METHODS: This cross-sectional study was conducted online from July 1 to August 10, 2020 and involved 1,023 nursing faculties in Japan. Participants were asked to respond to a questionnaire based on their experiences from April to June 2020. We calculated descriptive statistics for several measures and examined associations between professional/personal demographic factors and declines in overall research time. RESULTS: Of the 1,023 participants, 71.1% were spending less time on overall research activity; 79.6% spent less time attending academic events/conferences, and 77.4% spent less time conducting experiments/surveys. In contrast, 81.2% spent more time teaching, a much greater proportion than the global scientific community in a previous survey. As for work time allocation during the pandemic, teaching was by far the one activity that participants spent the most time on. Logistic regression analysis revealed that declines in overall research time were associated with several professional demographic factors, such as type of university, current academic position, and acquisition status of Japan's major research grant (KAKENHI) (all p < .05). CONCLUSIONS: Nursing faculties in Japan clearly spent less time on research, and more time on teaching during the first wave of the pandemic compared to pre-pandemic. The initial impact of the pandemic on nursing faculties revealed through this study is an eye-opener and a start for addressing the long-term impact on the nursing scientific community.