Dataset for attitude measures towards Dengue control efforts with the potential of digital technology during COVID-19
Cite this dataset
Purnama, Sang Gede; Susanna, Dewi (2023). Dataset for attitude measures towards Dengue control efforts with the potential of digital technology during COVID-19 [Dataset]. Dryad. https://doi.org/10.5061/dryad.jdfn2z3f0
The data is conducted using an online survey with 6 variables. These include perceptions of the need for digital information systems, dangers of DHF, benefits of DHF control programs, program constraints, and environ- mental factors related to attitudes toward controlling DHF. Respondents answered with a Likert scale of 1–5, where 1, 2 3, 4, and 5 represent strongly disagree, disagree, neutral, agree, and strongly agree. The questionnaire was made by discussing with experts and testing about 30 respondents to measure the validity and reliability. Respondents were selected based on inclusion criteria, aged more than 17 years, having an address in Denpasar City for more than one year, and willing to answer questions. The results of the validity and reliability tests found that 46 of the indicators were declared valid. Invalid indicators are excluded and not used. The final questionnaire can be found as Extended data. It was then distributed online using a google form, and data collection was carried out in the Denpasar City area, which is endemic to DHF. Table 1 shows a description of the data from the composites and indicators, as well as the definitions of attitudes towards dengue control efforts with the other five composites.
This study was analyzed using PLS-SEM with SmartPLS 3.0 software. It analyzed five variables related to attitudes towards dengue control. The PLS-SEM analysis uses two stages, and the first describes the measurement model connecting the constructs and indicators to the theory. In the second stage, the structural model determines the determinants of the relationship between the construction and the hypothetical model.
The data can be opened with Microsoft Excel and for analysis statisctics software such SPSS, STATA, etc.
University of Indonesia, Award: NKB-257/UN2.RST/HKP.05.00/2022