Matching Items (4)

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iPhone applications and improvement in weight and health parameters: a randomized controlled trial

Description

Dietary counseling from a registered dietitian has been shown in previous studies to aid in weight loss for those receiving counseling. With the increasing use of smartphone diet/weight loss applications (app), this study sought to investigate if an iPhone diet

Dietary counseling from a registered dietitian has been shown in previous studies to aid in weight loss for those receiving counseling. With the increasing use of smartphone diet/weight loss applications (app), this study sought to investigate if an iPhone diet app providing feedback from a registered dietitian improved weight loss and bio-markers of health. Twenty-four healthy adults who owned iPhones (BMI > 24 kg/m2) completed this trial. Participants were randomly assigned to one of three app groups: the MyDietitian app with daily feedback from a registered dietitian (n=7), the MyDietitian app without feedback (n=7), and the MyPlate feedback control app (n=10). Participants used their respective diet apps daily for 8-weeks while their weight loss, adherence to self-monitoring, blood bio-markers of health, and physical activity were monitored. All of the groups had a significant reduction in waist and hip circumference (p<0.001), a reduction in A1c (p=0.002), an increase in HDL cholesterol levels (p=0.012), and a reduction in calories consumed (p=0.022) over the duration of the trial. Adherence to diet monitoring via the apps did not differ between groups during the study. Body weight did not change during the study for any groups. However, when the participants were divided into low (<50% of days) or high adherence (>50% of days) groups, irrespective of study group, the high adherence group had a significant reduction in weight when compared to the low adherence group (p=0.046). These data suggest that diet apps may be useful tools for self-monitoring and even weight loss, but that the value appears to be the self-monitoring process and not the app specifically.

Contributors

Agent

Created

Date Created
2014

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Evaluation of nutritional quality through a counselor administered weight loss program utilizing a smart phone app

Description

ABSTRACT This study evaluated the LoseIt Smart Phone app by Fit Now Inc. for nutritional quality among users during an 8 week behavioral modification weight loss protocol. All participants owned smart phones and were cluster randomized to either a control

ABSTRACT This study evaluated the LoseIt Smart Phone app by Fit Now Inc. for nutritional quality among users during an 8 week behavioral modification weight loss protocol. All participants owned smart phones and were cluster randomized to either a control group using paper and pencil record keeping, a memo group using a memo function on their smart phones, or the LoseIt app group which was composed of the participants who owned iPhones. Thirty one participants completed the study protocol: 10 participants from the LoseIt app group, 10 participants from the memo group, and 11 participants from the paper and pencil group. Food records were analyzed using Food Processor by ESHA and the nutritional quality was scored using the Healthy Eating Index - 2005 (HEI-2005). Scores were compared using One-Way ANOVA with no significant changes in any category across all groups. Non-parametric statistics were then used to determine changes between combined memo and paper and pencil groups and the LoseIt app group as the memo and paper and pencil group received live counseling at biweekly intervals and the LoseIt group did not. No significant difference was found in HEI scores across all categories, however a trend was noted for total HEI score with higher scores among the memo and paper and pencil group participants p=0.091. Conclusion, no significant difference was detected between users of the smart phone app LoseIt and memo and paper and pencil groups. More research is needed to determine the impact of in-person counseling versus user feedback provided with the LoseIt smart phone app.

Contributors

Agent

Created

Date Created
2011

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Warning a distracted driver: smart phone applications, informative warnings and automated driving take-over requests

Description

While various collision warning studies in driving have been conducted, only a handful of studies have investigated the effectiveness of warnings with a distracted driver. Across four experiments, the present study aimed to understand the apparent gap in the literature

While various collision warning studies in driving have been conducted, only a handful of studies have investigated the effectiveness of warnings with a distracted driver. Across four experiments, the present study aimed to understand the apparent gap in the literature of distracted drivers and warning effectiveness, specifically by studying various warnings presented to drivers while they were operating a smart phone. Experiment One attempted to understand which smart phone tasks, (text vs image) or (self-paced vs other-paced) are the most distracting to a driver. Experiment Two compared the effectiveness of different smartphone based applications (app’s) for mitigating driver distraction. Experiment Three investigated the effects of informative auditory and tactile warnings which were designed to convey directional information to a distracted driver (moving towards or away). Lastly, Experiment Four extended the research into the area of autonomous driving by investigating the effectiveness of different auditory take-over request signals. Novel to both Experiment Three and Four was that the warnings were delivered from the source of the distraction (i.e., by either the sound triggered at the smart phone location or through a vibration given on the wrist of the hand holding the smart phone). This warning placement was an attempt to break the driver’s attentional focus on their smart phone and understand how to best re-orient the driver in order to improve the driver’s situational awareness (SA). The overall goal was to explore these novel methods of improved SA so drivers may more quickly and appropriately respond to a critical event.

Contributors

Agent

Created

Date Created
2017

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Evidence-based development of trustworthy mobile medical apps

Description

Widespread adoption of smartphone based Mobile Medical Apps (MMAs) is opening new avenues for innovation, bringing MMAs to the forefront of low cost healthcare delivery. These apps often control human physiology and work on sensitive data. Thus it is necessary

Widespread adoption of smartphone based Mobile Medical Apps (MMAs) is opening new avenues for innovation, bringing MMAs to the forefront of low cost healthcare delivery. These apps often control human physiology and work on sensitive data. Thus it is necessary to have evidences of their trustworthiness i.e. maintaining privacy of health data, long term operation of wearable sensors and ensuring no harm to the user before actual marketing. Traditionally, clinical studies are used to validate the trustworthiness of medical systems. However, they can take long time and could potentially harm the user. Such evidences can be generated using simulations and mathematical analysis. These methods involve estimating the MMA interactions with human physiology. However, the nonlinear nature of human physiology makes the estimation challenging.

This research analyzes and develops MMA software while considering its interactions with human physiology to assure trustworthiness. A novel app development methodology is used to objectively evaluate trustworthiness of a MMA by generating evidences using automatic techniques. It involves developing the Health-Dev β tool to generate a) evidences of trustworthiness of MMAs and b) requirements assured code generation for vulnerable components of the MMA without hindering the app development process. In this method, all requests from MMAs pass through a trustworthy entity, Trustworthy Data Manager which checks if the app request satisfies the MMA requirements. This method is intended to expedite the design to marketing process of MMAs. The objectives of this research is to develop models, tools and theory for evidence generation and can be divided into the following themes:

• Sustainable design configuration estimation of MMAs: Developing an optimization framework which can generate sustainable and safe sensor configuration while considering interactions of the MMA with the environment.

• Evidence generation using simulation and formal methods: Developing models and tools to verify safety properties of the MMA design to ensure no harm to the human physiology.

• Automatic code generation for MMAs: Investigating methods for automatically

• Performance analysis of trustworthy data manager: Evaluating response time generating trustworthy software for vulnerable components of a MMA and evidences.performance of trustworthy data manager under interactions from non-MMA smartphone apps.

Contributors

Agent

Created

Date Created
2015