Background Although numerous studies have been published on the predictors of COVID-19 vaccine hesitancy, some possible predictors remain underexplored. In this study, we explored the associations of unwillingness and indecisiveness regarding COVID-19 vaccination with generalized trust, mental health conditions such as depression and generalized anxiety, and fear of COVID-19. Methods Data of wave 1 (from October 27 till November 6, 2020) and wave 3 (from April 23 till May 6, 2021) of a longitudinal online study conducted in Japan were used for the analyses. Unvaccinated participants were asked at wave 3 about their willingness to be vaccinated, with possible responses of willing, unwilling, or undecided. These three responses were used as the outcome variable, and multinomial logistic regression analyses were conducted with willingness to be vaccinated as the reference group. Explanatory variables included generalized trust, depression, generalized anxiety, and fear of COVID-19 both at wave 1 and 3, and sociodemographic and health-related variables. Results Of the 11,846 valid respondents, 209 (1.8%) answered that they had already been vaccinated against COVID-19, 7089 (59.8%) responded that they were willing to be vaccinated, 3498 (29.5%) responded that they were undecided, and 1053 (8.9%) responded that they were unwilling to be vaccinated. After adjusting for covariates, we found that: (1) participants with lower levels of generalized trust at wave 1 and 3 were more likely to be undecided or unwilling at wave 3; (2) respondents with moderately severe or severe depression at wave 1 and 3 were more likely to be undecided at wave 3; (3) participants with moderate or severe levels of generalized anxiety at wave 3 but not at wave 1 were more likely to be unwilling at wave 3; and (4) respondents with high levels of fear of COVID-19 at wave 1 and 3 were less likely to be undecided and unwilling at wave 3. Conclusions Generalized trust, mental health conditions such as depression and generalized anxiety, and low level of fear of COVID-19 are associated with unwillingness or indecision regarding being vaccinated against COVID-19.

BackgroundNotwithstanding a high expectation for internet-based cognitive behavioral therapy (iCBT) for reducing depressive symptoms, many of iCBT programs have limitations such as temporary effects and high drop-out rates, possibly due to their complexity. We examined the effects of a free, simplified, 5-minute iCBT program by comparing it with a simplified emotion-focused mindfulness (sEFM) exercise and with a waiting list control group.MethodsA total of 974 participants, who were recruited using the website of a market research company, were randomly assigned to the iCBT group, the sEFM group, and the control group. Those in the intervention arms performed each exercise for 5 weeks. The primary outcome measure was the Center for Epidemiological Studies Depression scale (CES-D) at postintervention. Secondary outcome measures were the Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder-7 scale (GAD-7). Intention-to-treat analyses were conducted.ResultsDuring postintervention assessment, there were no significant differences between the intervention arms and the control group in the CES-D, although the difference between the iCBT arm and control group was close to significance (p = 0.05) in favor of iCBT. There was a significant difference in the PHQ-9 in favor of the sEFM group compared with the control group. There were no significant differences in outcome measures between the three groups at the 6-week follow-up.ConclusionsAlthough both iCBT and sEFM have the potential to temporarily reduce depressive symptoms, substantial improvements are required to enhance and maintain their effects.Trial registrationThis trial is registered with the UMIN Clinical Trial Registry (UMIN-CTR) (ID: UMIN000015097) on 1 October 2014.Electronic supplementary materialThe online version of this article (doi:10.1186/s12888-017-1248-8) contains supplementary material, which is available to authorized users.

Share-copy and redistribute the material in any medium or format. Adapt-remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution-You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Background: Many people take medicines to control high blood pressure (BP), or hypertension. Randomized clinical trials (RCT) are usually used for the evaluation of effects of medicines. However, RCT have some serious problems. Data and Methods: We evaluated the effects of BP medicines in Japan using a dataset containing 113,979 cases. We employed four statistical methods in the analysis. First, we simply compared the systolic blood pressure (SBP) of individuals with and without BP medicines. We then used a regression model with a dummy variable, representing taking medicines or not. We replaced the dummy variable by its expected value, and estimated the regression model again. Finally, we selected individuals who had both taken and not taken medicines at different times. The effect of sample selection was also considered in the estimation. Results: For the simple comparison, SBP with BP medicines was 11 mmHg higher than without medicines. In the next regression analysis, SBP with BP medicines was still 5 mmHg higher. When the dummy variable was replaced by its expected value, SBP with medicines decreased by 7 mmHg. For individuals taking medicines at some times and not at others, SBP decreased by 9 and 8 mmHg in models with and without a sample bias correction, respectively. Conclusion: The methods eliminated some problems of RCT and might be attractive. However, we obtained contradictory conclusions depending on the statistical methods employed, despite using the identical dataset. Statistical methods must be selected carefully to obtain a reliable evaluation. Limitations: The dataset was observatory, and the sample period was only 3 years.

Background: Behaviors to avoid infection are key to minimizing casualties of the COVID-19 pandemic, as well as to avoid excessive interventions that are less effective. This study aims to identify behavioral patterns associated with SARS-CoV-2 infection in the real world. Methods: A questionnaire-based cross-sectional study was conducted targeting a research panel of NTTCom Online Marketing Solutions Corporation or its affiliates. Data were extracted so that their demographic composition ratios matched the population estimates. Individuals who answered with consistency to have been diagnosed with SARS-CoV-2 at a medical facility were categorized into a SARS-CoV-2 group. Differences in lifestyles were compared using multiple regression and inverse probability weighing. Results: In total 13,277 participants were included, of whom 44 (0.33%) were categorized as the SARS-CoV-2 group. Diagnosis of SARS-CoV-2 was negatively correlated with crowd avoidance, mask wearing, and hand-washing behavior. On the contrary, the diagnosis was positively correlated with some behaviors that appear to be preventive actions against the infection, such as changing clothes frequently, sanitizing belongings, and remote working. Conclusions: It is important to conduct evidence-based intervention on people’s behaviors and to avoid excessive interventions that are less effective, so that people can minimize the indirect harm, such as exhaustion and economic loss.