The health bar

Mateevitsi, Victor; Reda, Khairi; Leigh, Jason; Johnson, Andrew

doi:10.1145/2582051.2582072

Cited by 37 publications

(16 citation statements)

References 5 publications

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“…For instance, the studies by Van Dantzig and colleagues, Slootmaker and colleagues, Ferreira and colleagues, and Carr and colleagues [47,89,91,93] used USB-type protocols for sending environment-based sensor data to the users’ workstations, where the prompts were scheduled and delivered. USB protocol was also used in early prototypes of connected systems [56,94] to actuate novel user interfaces (eg, mechanically controlled sculpture and ambient light) from an Arduino, which is an open-source platform for creating interactive electronic objects.…”

Section: Resultsmentioning

confidence: 99%

Digital Interventions to Reduce Sedentary Behaviors of Office Workers: Scoping Review

Huang¹,

Benford²,

Blake³

2019

J Med Internet Res

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Background There is a clear public health need to reduce office workers’ sedentary behaviors (SBs), especially in the workplace. Digital technologies are increasingly being deployed in the workplace to measure and modify office workers’ SBs. However, knowledge of the range and nature of research on this topic is limited; it also remains unclear to what extent digital interventions have exploited the technological possibilities. Objective This study aimed to investigate the technological landscape of digital interventions for SB reduction in office workers and to map the research activity in this field. Methods Terms related to SB, office worker, and digital technology were applied in various combinations to search Cochrane Library, Joanna Briggs Institute Database of Systematic Reviews, MEDLINE, PsycARTICLES, PsycINFO, Scopus, Association for Computing Machinery Digital Library, Engineering index Compendex, and Google Scholar for the years 2000 to 2017. Data regarding the study and intervention details were extracted. Interventions and studies were categorized into development, feasibility and/piloting, evaluation, or implementation phase based on the UK Medical Research Council (MRC) framework for developing and evaluating complex interventions. A novel framework was developed to classify technological features and annotate technological configurations. A mix of quantitative and qualitative approaches was used to summarize data. Results We identified 68 articles describing 45 digital interventions designed to intervene with office workers’ SB. A total of 6 common technological features had been applied to interventions with various combinations. Configurations such as “information delivery and mediated organizational and social support” and “digital log and automated tailored feedback” were well established in evaluation and implementation studies; in contrast, the integration of passive data collection, connected devices, and ATF or scheduled prompts was mostly present in development and piloting research. Conclusions This review is the first to map and describe the use of digital technologies in research on SB reduction in office workers. Interdisciplinary collaborations can help to maximize the potential of technologies. As novel modes of delivery that capitalize on embedded computing and electronics, wireless technologies have been developed and piloted in engineering, computing, and design fields, efforts can be directed to move them to the next phase of evaluation with more rigorous study designs. Quality of research may be improved by fostering conversations between different research communities and encouraging researchers to plan, conduct, and report their research under the MRC framework. This review will be particularly informative to those deciding on areas where further research or development is needed and to those looking to locate the relevant expertise, resources, ...

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Section: Resultsmentioning

confidence: 99%

Digital Interventions to Reduce Sedentary Behaviors of Office Workers: Scoping Review

Huang¹,

Benford²,

Blake³

2019

J Med Internet Res

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“…Ambient notifications in the form of light colors or light effects received increasing research interest distributed across recent years (e.g., [2,3,7,5,6,10]). For example, Hazlewood et al [3] studied a small spherical object made of frosted glass, which illuminated with different colors in order to reflect the confidence level of students during university courses.…”

Section: Related Workmentioning

confidence: 99%

Exploring Opportunistic Ambient Notifications in the Smart Home to Enhance Quality of Live

Seiderer

Dang

André

2017

Enhanced Quality of Life and Smart Living

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Smart home technology became more and more widespread within recent years. They aim to make life easier and taking over unwanted tasks. In traditional homes, it is often not clear whether all windows and doors of a house are closed before inhabitants leave the home or go to sleep. However, this can be easily addressed by smart homes. We present a system based on opportunistically located ambient lights that assist inhabitants of a smart home in answering this question. In this paper, we show the concept of our system and the inhabitant-centered design process behind the development. The system was installed in a one-family smart home. We report on insights gained through data collected from this deployment over a period of six months. Within interviews, we found that the ambient light system gave inhabitants a more confident feeling about open doors/windows.

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“…• Entertain: this role refers to the idea that for certain users, the chronic condition they face is managed easier in a fun interactive way. Some applications use serious games [37,38], while other rely on gamifying their platforms to engage the users and gain their time and attention [21,28]. In such systems, rewards, scores, and other engaging methods are adopted [21,28,37,38].…”

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confidence: 99%

“…Sample of participants. The sample size across the primary studies ranged between five up to 375 participants [28,35]. This is a significant difference among studies that measure the outcome of systems with multiple similarities.…”

mentioning

confidence: 99%

“…This difference in the number of participants involved in each experiment changes the dynamics of measuring the outcome out of the study. For the study with only five participants [28], it is logistically, and technically easier to measure whether the patients adopted the system past the experimentation phase. However, when the number of participant is 55 folds larger, with a number of participants of 275 [35], finding the objectivity in measuring the effectiveness of the system on the participants is supposedly significantly difficult.…”

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confidence: 99%

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On How Chronic Conditions Affect the Patient-AI Interaction: A Literature Review

Sqalli

Al-Thani

2020

Healthcare

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Background: Across the globe, managing chronic diseases has been recognized as a challenge for patients and healthcare providers. The state of the art in managing chronic conditions requires not only responding to the clinical needs of the patient, but also guaranteeing a comfortable state of wellbeing for them, despite living with the disease. This demands mutual effort between the patient and the physician in constantly collecting data, monitoring, and understanding the disease. The advent of artificial intelligence has made this process easier. However, studies have rarely attempted to analyze how the different artificial intelligence based health coaching systems are used to manage different types of chronic conditions. Objective: Throughout this grounded theory literature review, we aim to provide an overview for the features that characterize artificial intelligence based health coaching systems used by patients with chronic diseases. Methods: During our search and paper selection process process, we use three bibliographic libraries (PubMed, IEEE Xplore, and ACM Digital Library). Using the grounded theory, we extract overarching themes for the artificial intelligence based health coaching systems. These systems are then classified according to their role, platform, type of interaction with the patient, as well as targeted chronic conditions. Of 869 citations retrieved, 31 unique studies are included in this review. Results: The included studies assess 14 different chronic conditions. Common roles for AI-based health coaching systems are: developing adherence, informing, motivating, reminding, preventing, building a care network, and entertaining. Health coaching systems combine the aforementioned roles to cater to the needs of the patients. The combinations of these roles differ between multilateral, unilateral, opposing bilateral, complementing bilateral, one-role-missing, and the blurred role combinations. Conclusion: Clinical solutions and research related to artificial intelligence based health coaching systems are very limited. Clear guidelines to help develop artificial intelligence-based health coaching systems are still blurred. This grounded theory literature review attempted to shed the light on the research and development requirements for an effective health coaching system intended for patients with chronic conditions. Researchers are recommended to use this review to identify the most suitable role combination for an effective health coaching system development.

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The health bar

Cited by 37 publications

References 5 publications

Digital Interventions to Reduce Sedentary Behaviors of Office Workers: Scoping Review

Digital Interventions to Reduce Sedentary Behaviors of Office Workers: Scoping Review

Exploring Opportunistic Ambient Notifications in the Smart Home to Enhance Quality of Live

On How Chronic Conditions Affect the Patient-AI Interaction: A Literature Review

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