The use of in-body wearable devices is increasing in the healthcare sector, given their capacity to diagnose diseases and monitor health conditions. At the same time, some of these devices have entered the market and are being researched for use in workplace settings to enhance workers’ health and safety. However, neither specific EU legislation nor national law currently regulates the use of in-body wearables in employment, raising questions about the safeguarding of workers’ fundamental rights to privacy and data protection. Addressing the challenges posed by this regulatory gap, this article explores whether the European legislative framework employed in the healthcare sector for medical devices could be applied to the use of in-body wearables in employment settings. It also discusses the application of a key principle of the General Data Protection Regulation when in-body wearables are used in the workplace: lawfulness.
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Background: To experience external objects in such a way that they are perceived as an integral part of one's own body is called embodiment. Wearable technology is a category of objects, which, due to its intrinsic properties (eg, close to the body, inviting frequent interaction, and access to personal information), is likely to be embodied. 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 with regard to quantifying wearable technology embodiment are of particular value to the mobile health (mHealth) field. For example, the ability to predict the effectiveness of mHealth interventions and knowing the extent to which people embody the technology might be crucial for improving mHealth adherence. To facilitate examining wearable technology embodiment, we developed a measurement scale for this construct. Objective: This study aimed 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. The introduced instrument has 3 dimensions and includes 9 measurement items. The items are distributed evenly between the 3 dimensions, which include body extension, cognitive extension, and self-extension.Methods: Data were collected through a vignette-based survey (n=182). Each respondent was given 3 different vignettes, describing a hypothetical situation using a different type of wearable technology (a smart phone, a smart wristband, or a smart watch) with the purpose of tracking daily activities. Scale dimensions and item reliability were tested for their validity and Goodness of Fit Index (GFI). Results: Convergent validity of the 3 dimensions and their reliability were established as confirmatory factor analysis factor loadings45 (>0.70), average variance extracted values40 (>0.50), and minimum item to total correlations50 (>0.40) exceeded established threshold values. The reliability of the dimensions was also confirmed as Cronbach alpha and composite reliability exceeded 0.70. GFI testing confirmed that the 3 dimensions function as intercorrelated first-order factors. Predictive validity testing showed that these dimensions significantly add to multiple constructs associated with predicting the adoption of new technologies (ie, 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 3-dimensional instrument 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 measurement instrument to multiple scenarios and technologies, and more diverse user groups.
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Objective: To evaluate psychometrics of wearable devices measuring physical activity (PA) in ambulant children with gait abnormalities due to neuromuscular conditions. Data Sources: We searched PubMed, Embase, PsycINFO, CINAHL, and SPORTDiscus in March 2023. Study Selection: We included studies if (1) participants were ambulatory children (2-19y) with gait abnormalities, (2) reliability and validity were analyzed, and (3) peer-reviewed studies in the English language and full-text were available. We excluded studies of children with primarily visual conditions, behavioral diagnoses, or primarily cognitive disability. We performed independent screening and inclusion, data extraction, assessment of the data, and grading of results with 2 researchers. Data Extraction: Our report follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We assessed methodological quality with Consensus-based Standards for the selection of health measurement instruments. We extracted data on reported reliability, measurement error, and validity. We performed meta-analyses for reliability and validity coefficient values. Data Synthesis: Of 6911 studies, we included 26 with 1064 participants for meta-analysis. Results showed that wearables measuring PA in children with abnormal gait have high to very high reliability (intraclass correlation coefficient [ICC]+, test-retest reliability=0.81; 95% confidence interval [CI], 0.74-0.89; I2=88.57%; ICC+, interdevice reliability=0.99; 95% CI, 0.98-0.99; I2=71.01%) and moderate to high validity in a standardized setting (r+, construct validity=0.63; 95% CI, 0.36-0.89; I2=99.97%; r+, criterion validity=0.68; 95% CI, 0.57-0.79; I2=98.70%; r+, criterion validity cutoff point based=0.69; 95% CI, 0.58-0.80; I2=87.02%). The methodological quality of all studies included in the meta-analysis was moderate. Conclusions: There was high to very high reliability and moderate to high validity for wearables measuring PA in children with abnormal gait, primarily due to neurological conditions. Clinicians should be aware that several moderating factors can influence an assessment.
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