Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Nov 9, 2018
Open Peer Review Period: Nov 9, 2018 - Jan 4, 2019
Date Accepted: Apr 6, 2019
(closed for review but you can still tweet)
Is wearable technology becoming part of us? Developing and validating a measurement scale for wearable technology embodiment.
ABSTRACT
Background:
The increased wearability of technology has enabled individuals to access and interact with technology in such a way that it has become more and more an integral part of one’s body, mind, and sense of self. This phenomenon, which is referred to in this paper as wearable technology embodiment, has led to extensive conceptual considerations in various research fields. These considerations and further possibilities to quantify wearable technology embodiment are of particular value to the mHealth field. For example, to predict the effectiveness of mHealth interventions, knowing the extent to which people embody the technology might be crucial. To facilitate examining wearable technology embodiment we developed a measurement scale for this construct.
Objective:
The wearable technology embodiment scale is a 3 dimensional scale including 9 measurement items. The items are distributed evenly between the 3 dimensions which include: body extension, cognitive extension, and self-extension. The objective of the study was to conceptualize wearable technology embodiment, create an instrument to measure it, and test the predictive validity of the scale using well known constructs related to technology adoption.
Methods:
Data were collected through a vignette-based survey (n=182). Each respondent was given three different vignettes, describing a hypothetical situation using a different type of mobile or wearable technology with the purpose of tracking daily activities: a smart phone, a smart wristband, and a smart watch. The scale dimensions and item reliability was tested for validity and goodness of fit.
Results:
Convergent validity of the three dimensions and their reliability was confirmed via the CFA factor loadings45 (> 0.70), AVE values40 (> 0.50) and minimum item to total correlations50 (> 0.40) which exceeded established threshold value. The reliability of the dimensions was also confirmed as cronbach’s alpha and composite reliability exceeded 0.70. Good fit was found within three dimensions as inter-correlated first-order factors. Predictive validity testing showed that these dimensions significantly add to multiple constructs associated with predicting the adoption of new technologies (i.e.: trust, perceived usefulness, involvement, attitude, and continuous intention).
Conclusions:
The wearable technology embodiment measurement instrument has shown promise as a tool to measure the extension of an individual’s body, cognition, and self, as well as predict certain aspects of technology adoption. This three dimensional tool can be applied to mixed method research and used by wearable technology developers to improve future versions through such things as: fit, improved accuracy of biofeedback data, and customizable features or fashion to connect to the users personal identity. Further research is recommended to apply this tool to multiple scenarios and technologies, and more diverse user groups.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.