Background:Current technology innovations, such as wearables, have caused surprising reactions and feelings of deep connection to devices. Some researchers are calling mobile and wearable technologies cognitive prostheses, which are intrinsically connected to individuals as if they are part of the body, similar to a physical prosthesis. Additionally, while several studies have been performed on the phenomenology of receiving and wearing a physical prosthesis, it is unknown whether similar subjective experiences arise with technology.Objective:In one of the first qualitative studies to track wearables in a longitudinal investigation, we explore whether a wearable can be embodied similar to a physical prosthesis. We hoped to gain insights and compare the phases of embodiment (ie, initial adjustment to the prosthesis) and the psychological responses (ie, accept the prosthesis as part of their body) between wearables and limb prostheses. This approach allowed us to find out whether this pattern was part of a cyclical (ie, period of different usage intensity) or asymptotic (ie, abandonment of the technology) pattern.Methods:We adapted a limb prosthesis methodological framework to be applied to wearables and conducted semistructured interviews over a span of several months to assess if, how, and to what extent individuals come to embody wearables similar to prosthetic devices. Twelve individuals wore fitness trackers for 9 months, during which time interviews were conducted in the following three phases: after 3 months, after 6 months, and at the end of the study after 9 months. A deductive thematic analysis based on Murray’s work was combined with an inductive approach in which new themes were discovered.Results:Overall, the individuals experienced technology embodiment similar to limb embodiment in terms of adjustment, wearability, awareness, and body extension. Furthermore, we discovered two additional themes of engagement/reengagement and comparison to another device or person. Interestingly, many participants experienced a rarely reported phenomenon in longitudinal studies where the feedback from the device was counterintuitive to their own beliefs. This created a blurring of self-perception and a dilemma of “whom” to believe, the machine or one’s self.Conclusions:There are many similarities between the embodiment of a limb prosthesis and a wearable. The large overlap between limb and wearable embodiment would suggest that insights from physical prostheses can be applied to wearables and vice versa. This is especially interesting as we are seeing the traditionally “dumb” body prosthesis becoming smarter and thus a natural merging of technology and body. Future longitudinal studies could focus on the dilemma people might experience of whether to believe the information of the device over their own thoughts and feelings. These studies might take into account constructs, such as technology reliance, autonomy, and levels of self-awareness.
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Background: In frail older people with natural teeth factors like polypharmacy, reduced salivary flow, a decrease of oral self-care, general healthcare issues, and a decrease in dental care utilization contribute to an increased risk for oral complications. On the other hand, oral morbidity may have a negative impact on frailty. Objective: This study explored associations between oral health and two frailty measures in community-dwelling older people. Design: A cross-sectional study. Setting: The study was carried out in a Primary Healthcare Center (PHC) in The Netherlands. Participants: Of the 5,816 persons registered in the PHC, 1,814 persons were eligible for participation at the start of the study. Measurements: Two frailty measures were used: 1. Being at risk for frailty, using Electronical Medical Record (EMR) data, and: 2. Survey-based frailty using ‘The Groningen Frailty Indicator’ (GFI). For oral health measures, dental-record data (dental care utilization, dental status, and oral health information) and self-reported oral problems were recorded. Univariate regression analyses were applied to determine the association between oral health and frailty, followed by age- and sex-adjusted multivariate logistic regressions. Results: In total 1,202 community-dwelling older people were included in the study, 45% were male and the mean age was 73 years (SD=8). Of all participants, 53% was at risk for frailty (638/1,202), and 19% was frail based on the GFI (222/1,202). A dental emergency visit (Odds Ratio (OR)= 2.0, 95% Confidence Interval (CI)=1.33;3.02 and OR=1.58, 95% CI=1.00;2.49), experiencing oral problems (OR=2.07, 95% CI=1.52;2.81 and OR=2.87, 95% CI= 2.07;3.99), and making dietary adaptations (OR=2.66, 95% CI=1.31;5.41 and OR=5.49, 95% CI= 3.01;10.01) were associated with being at risk for frailty and surveybased frailty respectively. Conclusions: A dental emergency visit and self-reported oral health problems are associated with frailty irrespective of the approach to its measurement. Healthcare professionals should be aware of the associations of oral health and frailty in daily practice.
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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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