Automated Author ProfileHa, Toan
Ha, Toan
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 8.4 (sum of 6 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
No description available
Authors
- Ha, Toan
This survey dataset examines COVID-19-related knowledge, attitudes, and adoption of prevention behaviors. The survey was conducted among non-random sample of 464 Connecticut residents in the U.S in the early stage of social distancing and shutdown from March 23 to March 29, 2020. The questionnaires were developed by using Qualtrics software. Participants were purposively recruited. Participants could choose a hyperlink for self-administration of the survey online or were interviewed over the phone or other means of communication and record their answers online. Data was transferred from Qualtrics to SPSS Version 26.0 for analysis. Data were analyzed using frequencies, percentages, means, and standard deviations.
Authors
- Ha, Toan
This survey dataset examines COVID-19-related knowledge, attitudes, and adoption of prevention behaviors. The survey was conducted among non-random sample of 464 Connecticut residents in the U.S in the early stage of social distancing and shutdown from March 23 to March 29, 2020. The questionnaires were developed by using Qualtrics software. Participants were purposively recruited. Participants could choose a hyperlink for self-administration of the survey online or were interviewed over the phone or other means of communication and record their answers online. Data was transferred from Qualtrics to SPSS Version 26.0 for analysis. Data were analyzed using frequencies, percentages, means, and standard deviations.
Authors
- Ha, Toan
This survey dataset examines COVID-19-related knowledge, attitudes, and adoption of prevention behaviors. The survey was conducted among non-random sample of 464 Connecticut residents in the U.S in the early stage of social distancing and shutdown from March 23 to March 29, 2020. The questionnaires were developed by using Qualtrics software. Participants were purposively recruited. Participants could choose a hyperlink for self-administration of the survey online or were interviewed over the phone or other means of communication and record their answers online. Data was transferred from Qualtrics to SPSS Version 26.0 for analysis. Data were analyzed using frequencies, percentages, means, and standard deviations.
Authors
- Ha, Toan
No description available
Authors
- Ha, Toan