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10.1016/j.ijmedinf.2021.104414 http://scihub22266oqcxt.onion/10.1016/j.ijmedinf.2021.104414 33639328!ä!33639328 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Med+Inform 2021 ; 149 (ä): 104414 Nephropedia Template TP {{tp|p=33639328|t=2021. Profiling adopters (and non-adopters) of a contact tracing mobile application: Insights from Australia |pdf=|usr=}}{{33639328}} gab.com Text Profiling adopters (and non-adopters) of a contact tracing mobile application: Insights from Australia JO: Int J Med Inform http://www.kidney.de/pget.php?&tw=1&pmid=33639328 #FOAvip OBJECTIVE: Many governments are using contact tracing mobile applications (CTMAs) yet public adoption of such systems has been relatively low. The main objective of this paper is to profile adopters (and non-adopters) of Australia's COVIDSafe CTMA. MATERIALS AND METHODS: We use latent profile analysis to examine predictors of CTMA download behaviour. Specifically, we draw on a representative Australian sample (N = 2575) to examine the interplay between age, education, income, dispositional desire for privacy and political ideology on download behaviour. We examine trust in government as a mediating mechanism between profiles and download behaviour. RESULTS: Our analysis produces seven profiles. Trust in government mediates the relationship between most profiles and download behaviour. A combination of wealth and education appear to be key explanatory factors of CTMA download behaviour. Two profiles -- comprising individuals with high income and education -- had the highest rates of download behaviour. Profiles with low download percentages comprised politically left-leaning participants with average to low income and education. CONCLUSION: Our findings clearly indicate the profiles of people who are (not) likely to download a CTMA. Practical ways to improve widespread adoption include providing structural support to the more vulnerable members of society, making clear the societal benefits of downloading CTMAs, and engaging in bipartisan promotion of such apps. Twit Text FOAVip Profiling adopters (and non-adopters) of a contact tracing mobile application: Insights from Australia ????Int J Med Inform http://www.kidney.de/pget.php?&tw=1&pmid=33639328 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33639328 #FOAvip English Wikipedia <ref>{{Cite pmid|33639328}}</ref> Profiling adopters (and non-adopters) of a contact tracing mobile application: Insights from Australia #MMPMID33639328 Lockey S; Edwards MR; Hornsey MJ; Gillespie N; Akhlaghpour S; Colville S Int J Med Inform 2021[May]; 149 (ä): 104414 PMID33639328show ga OBJECTIVE: Many governments are using contact tracing mobile applications (CTMAs) yet public adoption of such systems has been relatively low. The main objective of this paper is to profile adopters (and non-adopters) of Australia's COVIDSafe CTMA. MATERIALS AND METHODS: We use latent profile analysis to examine predictors of CTMA download behaviour. Specifically, we draw on a representative Australian sample (N = 2575) to examine the interplay between age, education, income, dispositional desire for privacy and political ideology on download behaviour. We examine trust in government as a mediating mechanism between profiles and download behaviour. RESULTS: Our analysis produces seven profiles. Trust in government mediates the relationship between most profiles and download behaviour. A combination of wealth and education appear to be key explanatory factors of CTMA download behaviour. Two profiles -- comprising individuals with high income and education -- had the highest rates of download behaviour. Profiles with low download percentages comprised politically left-leaning participants with average to low income and education. CONCLUSION: Our findings clearly indicate the profiles of people who are (not) likely to download a CTMA. Practical ways to improve widespread adoption include providing structural support to the more vulnerable members of society, making clear the societal benefits of downloading CTMAs, and engaging in bipartisan promotion of such apps. |*COVID-19[MESH] |*Mobile Applications[MESH] |Australia[MESH] |Contact Tracing[MESH] |Humans[MESH]Profiling adopters (and non-adopters) of a contact tracing mobile appl(epmc).pdf DeepDyve Pubget Overpricing