Remote patient monitoring acceptance trends among older adults residing in a frontier state

• Published in: Computers in human behavior Vol. 44; pp. 174 - 182
• Main Authors: Giger, Jarod T., Pope, Natalie D., Vogt, H. Bruce, Gutierrez, Cassity, Newland, Lisa A., Lemke, Jason, Lawler, Michael J.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2015
• Subjects: Acceptance; Adults; Health monitoring; Mathematical models; Monitoring; Norms; Older adults; Patients; Pilots; Robust methodology; Rural; TAM; Technology utilization; Trends; Rural; Health monitoring; TAM; Older adults; Robust methodology
• ISSN: 0747-5632; 1873-7692
• DOI: 10.1016/j.chb.2014.11.044

•We examine remote patient monitoring acceptance for older adults in a frontier state.•Family and friends may influence technology acceptance-promoting behaviors.•Monitoring technology could translate into higher levels of patient engagement.•Our methodology is promising for geographically isolated populations. This pilot study aims to present a methodological approach for investigating remote patient monitoring system acceptance trends for older adults residing in a frontier state. For this purpose, extended Technology Acceptance Model (TAM) variables, which included subjective norm, perceived usefulness, perceived ease of use, and behavioral intention were investigated using growth curve methods and modern resampling techniques. Results revealed our methodological and analytical approach shows promise for investigating technology acceptance over time on subjects where little literature exists and where recruiting adequate sample sizes for statistical power purposes may be challenging. Results of the data analysis showed there was a significant and reliable linear trend on subjective norm. Time did not predict perceived usefulness, perceived ease of use, or behavioral intention, indicating the levels of these factors were high and stable over the course of the study. Older adults accepted remote patient monitoring, and family and friends may influence technology acceptance promoting behaviors. The longer participants used the technology, the more they perceived those important to them would want them to use it. Attention to social influence to optimize the implementation of in-home health monitoring among this population is warranted. Recommendations for future research are provided.