scholarly journals Reasons for and against receiving influenza vaccination in a working age population in Japan: a national cross-sectional study

2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Tsubasa Iwasa ◽  
Koji Wada
Keyword(s):  
Influenza Vaccination ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Working Age ◽  
Working Age Population

scholarly journals Factors associated with acceptance of a digital contact tracing application for COVID-19 in the Japanese working-age population

2021 ◽  
Author(s):  
Tomohiro Ishimaru ◽  
Koki Ibayashi ◽  
Masako Nagata ◽  
Seiichiro Tateishi ◽  
Ayako Hino ◽  
...  
Keyword(s):  
Cross Sectional Study ◽  
Internet Survey ◽  
Contact Tracing ◽  
Full Time ◽  
Hand Disinfection ◽  
Sectional Study ◽  
Cross Sectional ◽  
Factors Associated ◽  
Working Age ◽  
Working Age Population

Objective: This study aimed to determine factors associated with acceptance of a Digital Contact Tracing (DCT) app for Coronavirus Disease 2019 (COVID-19) in the Japanese working-age population. Methods: A cross-sectional study was performed for 27,036 full-time workers registered with an internet survey company during December 2020 in Japan. Results: The rate of downloading the DCT app was 25.1%. The DCT app was more likely to be accepted by people with married status, university graduation or above, higher income, and occupations involving desk work. Fear of COVID-19 transmission, wearing a mask, using hand disinfection, willingness to be vaccinated against COVID-19, and presence of an acquaintance infected with COVID-19 were also associated with a greater likelihood of adopting the app. Conclusions: The present findings have important implications for widespread adoption of DCT apps in working-age populations in Japan and elsewhere.

Places visited for activities outside the home after stroke: Relationship with the severity of disability

2019 ◽  
Vol 83 (6) ◽  
pp. 405-412 ◽  
Author(s):  
Alexandra Olofsson ◽  
Anneli Nyman ◽  
Ann Charlotte Kassberg ◽  
Camilla Malinowsky ◽  
Maria Larsson Lund
Keyword(s):  
Cross Sectional Study ◽  
Good Recovery ◽  
Sectional Study ◽  
Cross Sectional ◽  
Significant Difference ◽  
Fatigue Data ◽  
Severity Of Disability ◽  
Working Age ◽  
Recovery Group ◽  
Fatigue Driving

Introduction Knowledge about the places people visit or do not visit after stroke is lacking. The aim of this study was to describe and compare the places visited for activities outside the home of people with stroke of working age and to explore the influence of the severity of disability, fatigue, driving a car and sociodemographic characteristics on the total number of places visited for activities outside the home. Methods An exploratory cross-sectional study was conducted and 63 people with stroke were interviewed with instruments that covered places outside the home, severity of disability and fatigue. Data were analysed using non-parametric tests, analysis of variance and the general linear model. Results Significant difference in the total number of places visited for activities outside the home were found between all three groups of severity of disability. The good recovery group visited eight places to a significantly higher extent than those with severe/moderate disability. The severity of disability and driving a car were the only aspects that significantly influenced the total number of places visited. Conclusions Places for activities outside the home people with stroke visit and changes therein can add valuable knowledge about participation that can be used in the design of rehabilitation.

scholarly journals Can online self-reports assist in real-time identification of influenza vaccination uptake? A cross-sectional study of influenza vaccine-related tweets in the USA, 2013–2017

BMJ Open ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. e024018 ◽  
Author(s):  
Xiaolei Huang ◽  
Michael C Smith ◽  
Amelia M Jamison ◽  
David A Broniatowski ◽  
Mark Dredze ◽  
...  
Keyword(s):  
Social Media ◽  
Influenza Vaccine ◽  
Influenza Vaccination ◽  
Real Time ◽  
Vaccination Coverage ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Twitter Data ◽  
The Usa

IntroductionThe Centers for Disease Control and Prevention (CDC) spend significant time and resources to track influenza vaccination coverage each influenza season using national surveys. Emerging data from social media provide an alternative solution to surveillance at both national and local levels of influenza vaccination coverage in near real time.ObjectivesThis study aimed to characterise and analyse the vaccinated population from temporal, demographical and geographical perspectives using automatic classification of vaccination-related Twitter data.MethodsIn this cross-sectional study, we continuously collected tweets containing both influenza-related terms and vaccine-related terms covering four consecutive influenza seasons from 2013 to 2017. We created a machine learning classifier to identify relevant tweets, then evaluated the approach by comparing to data from the CDC’s FluVaxView. We limited our analysis to tweets geolocated within the USA.ResultsWe assessed 1 124 839 tweets. We found strong correlations of 0.799 between monthly Twitter estimates and CDC, with correlations as high as 0.950 in individual influenza seasons. We also found that our approach obtained geographical correlations of 0.387 at the US state level and 0.467 at the regional level. Finally, we found a higher level of influenza vaccine tweets among female users than male users, also consistent with the results of CDC surveys on vaccine uptake.ConclusionSignificant correlations between Twitter data and CDC data show the potential of using social media for vaccination surveillance. Temporal variability is captured better than geographical and demographical variability. We discuss potential paths forward for leveraging this approach.

scholarly journals Promoting Influenza Vaccination among Staff of Nursing Homes According to Behavioral Insights: Analyzing the Choice Architecture during a Nudge-Based Intervention

Vaccines ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 600
Author(s):  
Chiara Lorini ◽  
Francesca Ierardi ◽  
Claudia Gatteschi ◽  
Giacomo Galletti ◽  
Francesca Collini ◽  
...  
Keyword(s):  
Risk Perception ◽  
Qualitative Analysis ◽  
Influenza Vaccination ◽  
Comparison Group ◽  
Cross Sectional Study ◽  
Choice Architecture ◽  
Sectional Study ◽  
Cross Sectional ◽  
Vaccination Uptake ◽  
Vaccination Acceptance

(1) Background: Influenza vaccination uptake in nursing home (NH) workers is uncommon. The aim of this study was to understand the choice architecture of influenza vaccination acceptance or refusal among them and to promote vaccination acceptance using the nudge approach. (2) Methods: In autumn 2019, a nudge intervention with a contextual qualitative analysis of choice architecture of vaccination was performed among the staff of eight Tuscan NHs. In summer 2020, a cross-sectional study including the staff of 111 NHs (8 in the nudge, 103 in the comparison group) was conducted to assess the impact of the nudge intervention in promoting vaccination uptake. (3) Results: Macro-categories of motivations for vaccination uptake that emerged from the qualitative analysis were risk perception, value dimension, and trust, while those regarding refusal were risk perception, distrust, value dimension, and reasons related to one’s health. Considering the cross-sectional study, influenza vaccination uptake in the 2018–2019 season was similar in the two groups (23.6% vs. 22.2% respectively, in the nudge and comparison group), but significantly different in the 2019–2020 season: 28% in the nudge vs. 20% in the comparison group. Also, the intention to get the vaccine in the 2020–2021 season was significantly different in the two groups: 37.9% in the nudge and 30.8% in the comparison group. (4) Conclusions: Nudge interventions-simple, fast, low cost-could be effective in promoting vaccination acceptance among NH workers and the analysis of choice architecture could be useful in improving tailored, new nudge interventions aimed at modifying irrational biased and cognitive errors.

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