Digital-Health Tourism Research-Methodology Coronavirus-Vaccination Trials: A Study Interpreting Geometa-Data Profiling to use Mobile-Health Technologies Nigeria
Authors:   Faculty of Computing and Information Technology, Federal University Dutse, Dutse, Jigawa State, NIGERIA, Sheik Osman Wan Rozaini , Awang Hapini ,   School of Computing, Universiti Utara Malaysia, Kedah, 06010 Sintok, MALAYSIA, Abdullahi Hassan Abdullahi Hassan ,   Faculty of Computing and Information Technology, Federal University Dutse, Dutse, Jigawa State, NIGERIA,   School of Computing, Universiti Utara Malaysia, Kedah, 06010 Sintok, MALAYSIA,   Digital Technology Research Development Unit, Educational Division of Sarkin Kudu Hassan Jibril Memorial     Development Foundation, No.2 Bodan Street Birnin Kudu Jigawa State, NIGERIA
Published: November 2021

Digital-Health Tourism Innovation (DTI) worldwide is in its infancy due to the emergent of coronavirus (COVID-19) disease. With the growth of open geometa data, use of government electronic services including electronic health (e-health), electronic commerce (e-commerce) and mobile health (m-health), Artificial Intelligence (AI) and machine learning strategies. Health and primary healthcare sectors are currently adopting these innovations for socio-economic wellbeing. Digital-health (also termed as e-health) is part of digital tourism innovation. Adapting geometa data profiling to develop a digital-health tourism framework for Primary Healthcare Workers (PHWs) to use mobile health technologies in COVID-19 vaccination trials are the key challenges of this study. Nevertheless, digital health tourism skills have been launched in developing Nations that created thousands of jobs to protect digital tourism businesses from potential vulnerabilities. Despite the benefits of this novel innovation, its deployment and implementation have been treated by inadequate of ICT facilities, lack of geometa data pre-processing to remove noise, data integrity, insufficient of academic research fundings, and reliable research methodology beyond COVID-19 vaccination trials to highlight these aspects. Therefore, qualitative, and quantitative research methods using Precaution Adoption Model Process (PAMP) questionnaire are employed to enable new ways of pre-processing behavior intention factors items. Eight academic researchers who were conversant with digital health technology validated 28 behavior intention factors with average factor loading values of 50% to 75%. Pilot survey conducted among 700 respondents from March 18, 2020, to September 10, 2021, among them are undergraduate students that may use this technology for research purposes. Pre-processed geometa data have shown percentage frequency counts of internet access and other online services 8% to 95%, adapted training factors 49% to 92% and factor items 34% to 78.3% for hypothesis generation towards development of digital health tourism framework in finding explanation to COVID-19 economic challenges. Except behavior intention factors and factor items insights are known and mapped, mobile health technology design process may result in poor conclusions. Thus, patients recovered from COVID-19 infection can still be infected again.