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      The alcohol tracker application: an initial evaluation of user preferences

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          Abstract

          Background

          The prevalence of at-risk drinking and alcohol use disorders is increasing. Advances in technology have resulted in numerous smartphone applications for this disorder. However, there are still concerns about the evidence base of previously developed alcohol applications.

          Objective

          The following study aims to illustrate how the authors have made use of innovative methodologies to overcome the issues relating to the accuracy of tracking the amount of alcohol one has consumed; it also aims to determine user perceptions about the innovative tracker and various other features of an alcohol self-management application among a group of individuals from the general population of a developed country (Canada).

          Methodology

          A native alcohol self-management application was developed. In order to determine user perspectives towards this new innovative application, the authors took advantage and made use of crowdsourcing to acquire user perspectives.

          Results

          Our results showed that smartphone ownership is highest among the age group of 35–44 years (91%) and lowest for those aged between 55 and 64 (58%). Our analysis also showed that 25–34-year-olds and 35–44-year-olds drink more frequently than the other groups. Results suggest that notification and information were the two most useful functions, with psychotherapy expected to be the least useful. Females indicated that notification service was the most useful function, while males preferred the information component.

          Conclusions

          This study has demonstrated how the authors have made use of innovative technologies to overcome the existing concerns pertaining to the utilisation of the blood alcohol concentration levels as a tracker. In addition, the authors have managed to highlight user preferences with regard to an alcohol application.

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          Most cited references7

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          The Smartphone in Medicine: A Review of Current and Potential Use Among Physicians and Students

          Background Advancements in technology have always had major impacts in medicine. The smartphone is one of the most ubiquitous and dynamic trends in communication, in which one’s mobile phone can also be used for communicating via email, performing Internet searches, and using specific applications. The smartphone is one of the fastest growing sectors in the technology industry, and its impact in medicine has already been significant. Objective To provide a comprehensive and up-to-date summary of the role of the smartphone in medicine by highlighting the ways in which it can enhance continuing medical education, patient care, and communication. We also examine the evidence base for this technology. Methods We conducted a review of all published uses of the smartphone that could be applicable to the field of medicine and medical education with the exclusion of only surgical-related uses. Results In the 60 studies that were identified, we found many uses for the smartphone in medicine; however, we also found that very few high-quality studies exist to help us understand how best to use this technology. Conclusions While the smartphone’s role in medicine and education appears promising and exciting, more high-quality studies are needed to better understand the role it will have in this field. We recommend popular smartphone applications for physicians that are lacking in evidence and discuss future studies to support their use.
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            Apnea MedAssist: real-time sleep apnea monitor using single-lead ECG.

            We have developed a low-cost, real-time sleep apnea monitoring system ''Apnea MedAssist" for recognizing obstructive sleep apnea episodes with a high degree of accuracy for both home and clinical care applications. The fully automated system uses patient's single channel nocturnal ECG to extract feature sets, and uses the support vector classifier (SVC) to detect apnea episodes. "Apnea MedAssist" is implemented on Android operating system (OS) based smartphones, uses either the general adult subject-independent SVC model or subject-dependent SVC model, and achieves a classification F-measure of 90% and a sensitivity of 96% for the subject-independent SVC. The real-time capability comes from the use of 1-min segments of ECG epochs for feature extraction and classification. The reduced complexity of "Apnea MedAssist" comes from efficient optimization of the ECG processing, and use of techniques to reduce SVC model complexity by reducing the dimension of feature set from ECG and ECG-derived respiration signals and by reducing the number of support vectors.
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              “I Have No Clue What I Drunk Last Night” Using Smartphone Technology to Compare In-Vivo and Retrospective Self-Reports of Alcohol Consumption

              Aim This research compared real-time measurements of alcohol consumption with retrospective accounts of alcohol consumption to examine possible discrepancies between, and contextual influences on, the different accounts. Method Building on previous investigations, a specifically designed Smartphone technology was utilized to measure alcohol consumption and contextual influences in de facto real-time. Real-time data (a total of 10,560 data points relating to type and number of drinks and current social / environmental context) were compared with daily and weekly retrospective accounts of alcohol consumption. Results Participants reported consuming more alcoholic drinks during real-time assessment than retrospectively. For daily accounts a higher number of drinks consumed in real-time was related to a higher discrepancy between real-time and retrospective accounts. This effect was found across all drink types but was not shaped by social and environmental contexts. Higher in-vivo alcohol consumption appeared to be related to a higher discrepancy in retrospectively reported weekly consumption for alcohol beverage types other than wine. When including contextual factors into the statistical models, being with two or more friends (as opposed to being alone) decreased the discrepancy between real-time and retrospective reports, whilst being in the pub (relative to being at home) was associated with greater discrepancies. Conclusions Overall, retrospective accounts may underestimate the amount of actual, real-time alcohol consumed. Increased consumption may also exacerbate differences between real-time and retrospective accounts. Nonetheless, this is not a global effect as environmental and social contexts interact with the type of alcohol consumed and the time frame given for reporting (weekly vs. daily retrospective). A degree of caution therefore appears warranted with regards to the use of retrospective self-report methods of recording alcohol consumption. Whilst real-time sampling is unlikely to be completely error free, it may be better able to account for social and environmental influences on self-reported consumption.
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                Author and article information

                Journal
                BMJ Innov
                BMJ Innov
                bmjinnov
                bmjinnov
                BMJ Innovations
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2055-642X
                January 2016
                9 October 2015
                : 2
                : 1
                : 8-13
                Affiliations
                [1 ]National Addictions Management Service (NAMS), Institute of Mental Health, Singapore
                [2 ]E-Health Research Consortium
                [3 ]University of British Columbia , Vancouver, British Columbia, Canada
                [4 ]Institute of Mental Health , Singapore, Singapore
                [5 ]Shandong University , Shandong, China
                [6 ]Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore (NUS)
                Author notes
                [Correspondence to ] Dr Melvyn Zhang, Level 9, Department of Psychological Medicine, National University Healthcare Systems (NUHS) Tower Block, 5 Lower Kent Ridge Road, Singapore 119074, Singapore; melvynzhangweibin@ 123456gmail.com
                Article
                bmjinnov-2015-000087
                10.1136/bmjinnov-2015-000087
                4789684
                27019744
                70cb1a96-4602-4fc4-a696-7e760f96c282
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 11 September 2015
                : 17 September 2015
                Categories
                mHealth and wearable health technologies
                1506
                2265
                Original article
                Custom metadata
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                medical apps,mhealth,psychiatry
                medical apps, mhealth, psychiatry

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