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Annals of Telecommunications
Erschienen in: Annals of Telecommunications 1-2/2014

01.02.2014

Privacy concerns in assisted living technologies

verfasst von: Vaibhav Garg, L. Jean Camp, Lesa Lorenzen-Huber, Kalpana Shankar, Kay Connelly

Erschienen in: Annals of Telecommunications | Ausgabe 1-2/2014

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Abstract

The challenges of an aging population require the adoption of in-home and medical technologies to complement the traditional caregiver model. Adoption of such technologies is, however, impinged by privacy concerns. This study investigates a four-dimensional framework that explains the trade-offs between functionality and privacy as constructed by older adults. The four dimensions constitute perceived utility, data granularity, data recipient, and activity sensitivity. We conducted a survey-based study to empirically examine the applicability and robustness of this framework. Our results have implications for the adoption of a wide range of privacy-enhancing technologies. By focusing on the intersection of an under-studied group (nontechnical older adults) and sensitive data (medical and at home), this work has the potential to enable privacy enhancing technologies (PETs) that might be widely adopted.
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Fußnoten
1
Assistive monitoring technologies refer to solutions that can be used by individuals with chronic conditions and their health-care providers to monitor their health behaviors.
 
2
Financial assets owned by older adults are increasing. One tenth of all publicly held bonds are held by people over 65 years of age [6]. By 2020, older adults will own one third of all publicly held stocks in America. Older adults are, however, highly susceptible to scams and financial fraud. According to the Federal Trade Commission, over 20 % of the victims of financial fraud are older adults [4]
 
3
Bonferroni correction states that if p is the appropriate p value to avoid type 1 errors, and n is the number of comparisons being made, then the appropriate p value should be p / n. In general, the number of comparisons being made in this study is 3, and the traditionally accepted p value is 0.05, therefore the p value in this study should be less than 0.05/3 or 0.01667. We consider an even more conservative estimate of 0.001.
 
4
AIC quantifies how well a model fits the data. AIC cannot provide an absolute measure of the fit. Thus, the goodness of the fit is relative. In general, a smaller AIC value indicates a better fit.
 
5
A positive estimate implies that an increase in the independent variable leads to an increase in the dependent variable.
 
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Metadaten
Titel
Privacy concerns in assisted living technologies
verfasst von
Vaibhav Garg
L. Jean Camp
Lesa Lorenzen-Huber
Kalpana Shankar
Kay Connelly
Publikationsdatum
01.02.2014
Verlag
Springer Paris
Erschienen in
Annals of Telecommunications / Ausgabe 1-2/2014
Print ISSN: 0003-4347
Elektronische ISSN: 1958-9395
DOI
https://doi.org/10.1007/s12243-013-0397-0

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