Eva-Maria Schomakers|Chantal Lidynia|Luisa Vervier|André Calero Valdez|Martina Ziefle
Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study
RWTH Aachen University|RWTH Aachen University|RWTH Aachen University|RWTH Aachen University|RWTH Aachen University
mobile health mhealth care apps promising technology monitor control health individually costeffectively technology widely used affordable ubiquitous many peoples lives download statistics show lifestyle apps widely used young healthy users improve fitness nutrition important aspect prevention future chronic diseases burdened health care systems worldwide may directly profit use therapy apps patients already need medical treatment monitoringwe aimed compare factors influencing acceptance lifestyle therapy apps better understand drives hinders use mhealth appswe applied established unified theory acceptance use technology 2 utaut2 technology acceptance model evaluate mhealth apps via online questionnaire 707 german participants moreover trust privacy concerns added model betweensubject study design influence predictors behavioral intention use apps compared lifestyle therapy appsthe results show model weakly predicted intention use mhealth apps r20019 hedonic motivation significant predictor behavioral intentions regarding app types determined path coefficients model lifestyle 0196 p004 therapy 0344 p001 habit influenced behavioral intention use lifestyle apps 0272 p001 social influence 0185 p001 trust 0273 p001 predicted intention use therapy apps exploratory correlation analysis relationship user factors behavioral intention calculated health app familiarity showed strongest correlation intention use r0469 p001 stressing importance experience also age r015 p004 gender r0075 p048 education level r0088 p02 app familiarity r0142 p007 digital health literacy r0215 p001 privacy disposition r0194 p001 propensity trust apps r0191 p001 correlated weakly behavioral intention use mhealth appsthe results indicate rather utilitarian factors like usefulness mhealth app acceptance influenced emotional factors like hedonic motivation partly habit social influence trust overall findings give evidence health care context new extended acceptance models need developed integration user diversity especially individuals prior experience apps mhealth