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      Fall Prevention Self-Assessments Via Mobile 3D Visualization Technologies: Community Dwelling Older Adults’ Perceptions of Opportunities and Challenges

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          Abstract

          Background

          In the field of occupational therapy, the assistive equipment provision process (AEPP) is a prominent preventive strategy used to promote independent living and to identify and alleviate fall risk factors via the provision of assistive equipment within the home environment. Current practice involves the use of paper-based forms that include 2D measurement guidance diagrams that aim to communicate the precise points and dimensions that must be measured in order to make AEPP assessments. There are, however, issues such as “poor fit” of equipment due to inaccurate measurements taken and recorded, resulting in more than 50% of equipment installed within the home being abandoned by patients. This paper presents a novel 3D measurement aid prototype (3D-MAP) that provides enhanced measurement and assessment guidance to patients via the use of 3D visualization technologies.

          Objective

          The purpose of this study was to explore the perceptions of older adults with regard to the barriers and opportunities of using the 3D-MAP application as a tool that enables patient self-delivery of the AEPP.

          Methods

          Thirty-three community-dwelling older adults participated in interactive sessions with a bespoke 3D-MAP application utilizing the retrospective think-aloud protocol and semistructured focus group discussions. The system usability scale (SUS) questionnaire was used to evaluate the application’s usability. Thematic template analysis was carried out on the SUS item discussions, think-aloud, and semistructured focus group data.

          Results

          The quantitative SUS results revealed that the application may be described as having “marginal-high” and “good” levels of usability, along with strong agreement with items relating to the usability ( P=.004) and learnability ( P<.001) of the application. Four high-level themes emerged from think-aloud and focus groups discussions: (1) perceived usefulness (PU), (2) perceived ease of use (PEOU), (3) application use (AU) and (4) self-assessment (SA). The application was seen as a useful tool to enhance visualization of measurement guidance and also to promote independent living, ownership of care, and potentially reduce waiting times. Several design and functionality recommendations emerged from the study, such as a need to manipulate the view and position of the 3D furniture models, and a need for clearer visual prompts and alternative keyboard interface for measurement entry.

          Conclusions

          Participants perceived the 3D-MAP application as a useful tool that has the potential to make significant improvements to the AEPP, not only in terms of accuracy of measurement, but also by potentially enabling older adult patients to carry out the data collection element of the AEPP themselves. Further research is needed to further adapt the 3D-MAP application in line with the study outcomes and to establish its clinical utility with regards to effectiveness, efficiency, accuracy, and reliability of measurements that are recorded using the application and to compare it with 2D measurement guidance leaflets.

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          Most cited references81

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          Older Adults Talk Technology: Technology Usage and Attitudes.

          Older adults (n = 113) participated in focus groups discussing their use of and attitudes about technology in the context of their home, work, and healthcare. Participants reported using a wide variety of technology items, particularly in their homes. Positive attitudes (i.e., likes) outnumbered negative attitudes (i.e., dislikes), suggesting that older adults perceive the benefits of technology use to outweigh the costs of such use. Positive attitudes were most frequently related to how the technology supported activities, enhanced convenience, and contained useful features. Negative attitudes were most frequently associated with technology creating inconveniences, unhelpful features, as well as security and reliability concerns. Given that older adults reported more positive than negative attitudes about the technologies they use, these results contradict stereotypes that older adults are afraid or unwilling to use technology. These findings also highlight the importance of perceived benefits of use and ease of use for models of technology acceptance. Emphasizing the benefits of technology in education and training programs may increase future technology adoption.
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            Emerging Patient-Driven Health Care Models: An Examination of Health Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking

            A new class of patient-driven health care services is emerging to supplement and extend traditional health care delivery models and empower patient self-care. Patient-driven health care can be characterized as having an increased level of information flow, transparency, customization, collaboration and patient choice and responsibility-taking, as well as quantitative, predictive and preventive aspects. The potential exists to both improve traditional health care systems and expand the concept of health care though new services. This paper examines three categories of novel health services: health social networks, consumer personalized medicine and quantified self-tracking.
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              What about N? A methodological study of sample-size reporting in focus group studies

              Background Focus group studies are increasingly published in health related journals, but we know little about how researchers use this method, particularly how they determine the number of focus groups to conduct. The methodological literature commonly advises researchers to follow principles of data saturation, although practical advise on how to do this is lacking. Our objectives were firstly, to describe the current status of sample size in focus group studies reported in health journals. Secondly, to assess whether and how researchers explain the number of focus groups they carry out. Methods We searched PubMed for studies that had used focus groups and that had been published in open access journals during 2008, and extracted data on the number of focus groups and on any explanation authors gave for this number. We also did a qualitative assessment of the papers with regard to how number of groups was explained and discussed. Results We identified 220 papers published in 117 journals. In these papers insufficient reporting of sample sizes was common. The number of focus groups conducted varied greatly (mean 8.4, median 5, range 1 to 96). Thirty seven (17%) studies attempted to explain the number of groups. Six studies referred to rules of thumb in the literature, three stated that they were unable to organize more groups for practical reasons, while 28 studies stated that they had reached a point of saturation. Among those stating that they had reached a point of saturation, several appeared not to have followed principles from grounded theory where data collection and analysis is an iterative process until saturation is reached. Studies with high numbers of focus groups did not offer explanations for number of groups. Too much data as a study weakness was not an issue discussed in any of the reviewed papers. Conclusions Based on these findings we suggest that journals adopt more stringent requirements for focus group method reporting. The often poor and inconsistent reporting seen in these studies may also reflect the lack of clear, evidence-based guidance about deciding on sample size. More empirical research is needed to develop focus group methodology.
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                Author and article information

                Contributors
                Journal
                JMIR Hum Factors
                JMIR Hum Factors
                JMIR Human Factors
                JMIR Human Factors
                JMIR Publications (Toronto, Canada )
                2292-9495
                Apr-Jun 2017
                19 June 2017
                : 4
                : 2
                : e15
                Affiliations
                [1] 1Department of Computer Science Brunel University LondonUnited Kingdom
                [2] 2School of Health and Social Care London South Bank University LONDONUnited Kingdom
                Author notes
                Corresponding Author: Arthur Money arthur.money@ 123456brunel.ac.uk
                Author information
                http://orcid.org/0000-0001-5800-4088
                http://orcid.org/0000-0003-1063-3680
                http://orcid.org/0000-0001-6158-7237
                Article
                v4i2e15
                10.2196/humanfactors.7161
                5495970
                28630034
                b71195ae-9298-40b2-9909-6dea8f24f924
                ©Julian Hamm, Arthur Money, Anita Atwal. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 19.06.2017.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on http://humanfactors.jmir.org, as well as this copyright and license information must be included.

                History
                : 15 December 2016
                : 25 January 2017
                : 3 February 2017
                : 24 April 2017
                Categories
                Original Paper
                Original Paper

                health informatics,falls,occupational therapy,assistive equipment provision process,self-assessment,measurement guidance,extrinsic risk factors,3d visualization,technology-based systems

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