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BackgroundCurrent 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. ObjectiveIn 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. MethodsWe 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. ResultsOverall, 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. ConclusionsThere 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.

BackgroundTo 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. ObjectiveThis 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. MethodsData 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). ResultsConvergent validity of the 3 dimensions and their reliability were established as confirmatory factor analysis factor loadings (>0.70), average variance extracted values (>0.50), and minimum item to total correlations (>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). ConclusionsThe 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.

The most productive way to reform education would be to invest in effective early childhood education programs. Such an investment would produce remarkable educational, social, and economic benefits. It would also transcend the current divisive debates about education reform by uniting advocates with different perspectives on issues of funding, accountability, and school choice. An investment in universal pre-K would provide a model of authentic assessment of student learning and genuine accountability through documentation. It would also create an exemplar of real school choice by giving families the ability to select from a variety of options for their children. Furthermore, an investment in social constructivist early childhood education programs--programs in which children are encouraged to build knowledge through meaningful relationships--would yield particularly robust investment returns for children and for the nation.

Over the past few decades many corporate organisations have moved to open-plan office designs, mostly due to financial and logistical benefits. However, recent studies have found significant drawbacks to open plan offices and it is unclear how office designs can facilitate the best work output and company culture. Current design practice aims to optimise efficiency of space, but no previous research has tested the effect of office design experimentally in a working office. This paper describes an experiment comparing four different office designs (Open-plan, Zoned open-plan, Activity based, and Team offices) against a suite of wellbeing and productivity metrics in a real world technology company. Results suggest that two very different designs (Zoned open-plan and Team offices) perform well compared to Open-plan office designs. Zoned open-plan and Team office designs improved employee satisfaction, enjoyment, flow, and productivity, while Activity based and Open-plan designs performed poorly by comparison. The Open-plan office design was rated more poorly by employees, had higher levels of unsafe noise, and once employees no longer had to be in the Open-plan office design of the experiment, they spent more time at their desks., Competing Interests: Authors 1 and 3 (JP, MH) are employed by Booking.com. Booking.com fully funded this research, but did not have any influence over the study design, or decision to publish. Data collection and analysis was conducted using Booking.com data resources. The Booking Public Relations and Data Privacy teams checked the manuscript and submitted data for factual correctness and to ensure no commercially sensitive or PII information was released. Author 4 (WO) is employed by CBRE Consulting, and was contracted by Booking.com to manage the project. CBRE Consulting did not provide any funding, and had no influence over any stage of the project. Author 2 (EN) is employed by Learn Adapt Build, and was contracted by CBRE Consulting to advise on the data collection and analysis stages of the project. Learn Adapt Build did not provide any funding for any stage of the project. This does not alter our adherence to PLOS ONE policies on sharing data and materials.