{"title":"Determinants of Digital Health Information Search (DHIS) Behaviour: Extending UTAUT with healthcare behaviour constructs","authors":"Surya Neeragatti, R. Dehury, N. Sripathi","doi":"10.24083/apjhm.v18i1.1685","DOIUrl":null,"url":null,"abstract":"Introduction: As the availability of huge amounts of digital health information content increases, the popularity of Digital Health Information Search (DHIS) has increased. This paper explores the determinants that influence the intention to DHIS by the public by extending the UTAUT model with health behaviour constructs like health consciousness, attitude towards health information, and trust in DHI.\nMethod: The instrument was created by adapting scales from previous studies. Survey forms were circulated through online platforms with the snowball sampling technique. With the 345 finalized sample, analysis was carried out, and structural equation modelling (SEM) is used for data analysis with the help of SPSS v.26 and AMOS v.26.\nResults: Sample demographics show that 60% of the respondents have experience of 5 years in using smartphones, and 70% of respondents use the smartphone from 1 to 6 hours per day. We see that less time was spent on digital health information (DHI). For searching DHI, respondents use Google/other browsers and for sharing it, WhatsApp is the most used app. The reliability of scales was checked in SPSS, which resulted in Cronbach's alpha value greater than 0.7 for all scales. The hypothesis testing resulted in all the constructs showing a significant relationship. We see that performance expectancy, social influence, and trust in DHI showed a strong significant relation with the intention to DHIS.\nConclusion: This study extends the literature in information systems adoption studies by adding a combination of the technology acceptance model with health constructs. Factors influencing the intention to DHIS are accessibility, influence from peers, and information reliability are more concerned. This study shows the importance and need for genuine DHI from valid healthcare providers, in which the creators of healthcare information, like Government and private healthcare providers, have to be more conscious.","PeriodicalId":42935,"journal":{"name":"Asia Pacific Journal of Health Management","volume":" ","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2023-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia Pacific Journal of Health Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24083/apjhm.v18i1.1685","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: As the availability of huge amounts of digital health information content increases, the popularity of Digital Health Information Search (DHIS) has increased. This paper explores the determinants that influence the intention to DHIS by the public by extending the UTAUT model with health behaviour constructs like health consciousness, attitude towards health information, and trust in DHI.
Method: The instrument was created by adapting scales from previous studies. Survey forms were circulated through online platforms with the snowball sampling technique. With the 345 finalized sample, analysis was carried out, and structural equation modelling (SEM) is used for data analysis with the help of SPSS v.26 and AMOS v.26.
Results: Sample demographics show that 60% of the respondents have experience of 5 years in using smartphones, and 70% of respondents use the smartphone from 1 to 6 hours per day. We see that less time was spent on digital health information (DHI). For searching DHI, respondents use Google/other browsers and for sharing it, WhatsApp is the most used app. The reliability of scales was checked in SPSS, which resulted in Cronbach's alpha value greater than 0.7 for all scales. The hypothesis testing resulted in all the constructs showing a significant relationship. We see that performance expectancy, social influence, and trust in DHI showed a strong significant relation with the intention to DHIS.
Conclusion: This study extends the literature in information systems adoption studies by adding a combination of the technology acceptance model with health constructs. Factors influencing the intention to DHIS are accessibility, influence from peers, and information reliability are more concerned. This study shows the importance and need for genuine DHI from valid healthcare providers, in which the creators of healthcare information, like Government and private healthcare providers, have to be more conscious.