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Evaluation of Fitness Apps

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Title:
Evaluation of Fitness Apps
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Murphy, Meghan E
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English

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Apples ( jstor )
Calories ( jstor )
Educational evaluation ( jstor )
Exercise ( jstor )
Mobile applications ( jstor )
Rating scales ( jstor )
Running ( jstor )
Smartphones ( jstor )
Software applications ( jstor )
Walking ( jstor )
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Undergraduate Honors Thesis

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Abstract:
Background: The importance of maintaining physical fitness and staying healthy are sometimes forgotten amongst Americans. The health implications of not completing the minimum amount of suggested exercise per week are huge and can be life threatening. Smart-phone based apps provide opportunities for effective physical activity by promoting self-management and facilitating health information. The objective in this research was to evaluate the most relevant fitness apps from the Apple app store. Methods: The “Health and Wellness” category in the Apple app store provided 160 fitness apps. They were sorted based on relevance and only English-language apps were included. Apps classified as “business”, “games”, “sport”, “lifestyle”, “graphics and design” were excluded. The Mobile App Rating Scale (MARS) was designed to rate these mobile health apps on their quality and effectiveness. The categories included engagement, functionality, aesthetics, information quality, and subjective quality categories, to develop 23 subcategories from which the individual MARS items were developed. Each item used a 5-point scale (1-Inadequate, 2-Poor, 3-Acceptable, 4-Good, 5-Excellent). A total of nine people were trained to utilize MARS and review the fitness apps. Results: Over 100 apps have been evaluated. Early results show a wide variety of fitness trackers and workout programs. The ongoing research will evaluate the design, accuracy, features, and content of the apps. Discussion: There is a need to investigate and find what fitness apps are available to customers and how effective these apps are. This study will allow insight into what features and gaps exist in the current app market that meet customer activity goals. Public Health and/or Health Professions Relevance: This research focuses on the benefits of utilizing fitness apps to improve one’s physical health. These results can benefit individuals looking to work out and stay healthy. Funding Source: SHARC Student Role: Evaluated 31 apps using the MARS. Collected and analyzed data for mentor ( en )
General Note:
Awarded Bachelor of Health Science, summa cum laude, on May 2, 2017. Major(s): Health Science. Emphasis/Concentration: General Health Sciences
General Note:
College or School: College of Public Health & Health Professions
General Note:
Advisor: Mark W. Hart. Advisor Deptarment or School: Epidemiology

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University of Florida
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University of Florida
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Copyright Meghan E Murphy. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.

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Honors Thesis Submission Form Name: Megan Murphy UFID: 28261543 Additional Authors: Dr. Mark Hart Email: meganemurphy@ufl.edu Major: Health Science; Pre OT Advisor Name: Dr. Mark Hart Advisor Email: kramtrah@phhp.ufl.edu Advisor Department: Epidemiology Thesis Title: Evaluation of Fitness Apps Abstract (200 words max): Evaluation of Fitness Apps Background: The importance of maintaining physical fitness and staying healthy are sometimes forgotten amongst Americans. The health implications of not completing the minimum amount of suggested exercise per week are huge and can be life threatening. Smart phone bas ed apps provide opportunities for effective physical activity by promoting self management and facilitating health information. The objective in this research was to evaluate the most relevant fitness apps from the Apple app store. Methods: sorted based on relevance and only English Mobile App Rating Scale (MARS) was designed to rate these mobile health apps on their quality and effectiveness. The categories included engagement, functionality, aesthetics, information quality, and subjective quality categories, to develop 23 subcategor ies from which the individual MARS items were developed. Each item used a 5 point scale (1 Inadequate, 2 Poor, 3 Acceptable, 4 Good, 5 Excellent). A total of nine people were trained to utilize MARS and review the fitness apps. Results: Over 100 apps have been evaluated. Early results show a wide variety of fitness trackers and workout programs. The ongoing research will evaluate the design, accuracy, features, and content of the apps. (For Office Use Only) Major: _________________ Designation: ____________ Graduation Term: ________

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Discussion: There is a need to investigate and find what fitness apps a re available to customers and how effective these apps are. This study will allow insight into what features and gaps exist in the current app market that meet customer activity goals. Public Health and/or Health Professions Relevance: This research focus es on the benefits of utilizing fitness healthy. Funding Source: SHARC Student Role: Evaluated 31 apps using the MARS. Collected and analyzed data fo r mentor. StudentSignature/Date: 3/13/2017 Thesis Adv isor Signature/Date: 3/13/2017 Departmental Honors Coordinator Signature _________________________________________ Please indicate your preference for public access to your thesis by initialing the appropriate statement below: X ___ I grant permission to the University of Florida to list the title and abstract of this thesis in a publicly accessible database. _____ I do not grant permission to the University of Florida to list the title and abstract of this thesis publicly. If you wish to make the entire thesis publicly available, you must also complete the Internet Distribution Permissions Form, available at http://digital.uflib.ufl.edu/procedures/copyright/GrantofPermissions.doc If you do not include this form, your thesis will be archived but will not be viewable online.



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Running Head: EVALUATION OF FITNESS APPS 1 Evaluation of Fitness Apps March 13 2017 Megan Murphy Dr. Mark Hart, Ed.D., M.A.L.S. University of Florida

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EVALUATION OF FITNESS APPS 2 Abstract Evaluation of Fitness Apps Background: The importance of maintaining physical fitness and staying healthy are sometimes forgotten amongst Americans. The health implications of not completing the minimum amount of suggested exercise per week are huge and can be life threatening. Smart phone bas ed apps provide opportunities for effective physical activity by promoting self management and facilitating health information. The objective in this research was to evaluate the most relevant fitness apps from the Apple app store. Methods: They were sorted based on relevance and only English language apps were included. Apps Mobile App Rating Scale (MARS) was designed to rate these mobile health apps on their quality and effectiveness. The categories included engagement, functionality, aesthetics, information quality, and subjective quality categories, to develop 23 subcategor ies from which the individual MARS items were developed. Each item used a 5 point scale (1 Inadequate, 2 Poor, 3 Acceptable, 4 Good, 5 Excellent). A total of nine people were trained to utilize MARS and review the fitness apps. Results: Over 100 apps have been evaluated. Early results show a wide variety of fitness trackers and workout programs. The ongoing research will evaluate the design, accuracy, features, and content of the apps. Discussion: There is a need to investigate and find what fitness apps a re available to customers and how effective these apps are. This study will allow insight into what features and gaps exist in the current app market that meet customer activity goals.

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EVALUATION OF FITNESS APPS 3 Public Health and/or Health Professions Relevance: This research focus es on the benefits of looking to work out and stay healthy. Funding Source: SHARC Student Role: Evaluated 31 apps using the MARS. Collected and analyzed data fo r mentor.

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EVALUATION OF FITNESS APPS 4 Evaluation of Fitness Apps Introduction Fitness There is substantial evidence that regular physical activity leads to a heal thy lifestyle and prevents physical and mental diseases while boosting self esteem. Physical activity is defined as any movement by the body that is produced by skeletal muscles and requires energy expenditure (Waleh, 2016). It reduces the risk for developing obesity, diabetes, car diovascular diseases, depression, certain cancers, and anxiety. Physical inactivity across the United States is becoming a large concern due to the risk factors that come along with it. The World Health Organization lists physical inactivity as the fourth leading risk factor for cardiovascular diseases, just behind high blood pressure, smoking, and diabetes (Kraus et al., 2015). Physical inactivity accounts for nearly 3.2 million deaths globally each year (Waleh, 2016). One third of the American population is considered obese, and one third of the population is overweight (Waleh, 2016). The Centers for Disease Control and Prevention reports that this is a growing trend as more Americans are fitting into these categories of either obese or overweight. Obesit y leads to many serious health problems which includes stroke, cardiovascular disease, and diabetes (Gowin et al., 2015). On the other hand, the prevalence of fitness across the United States is not examined nearly as much as the prevalence of obesity. The last time a national youth fitness survey was conducted was more than 25 years ago (Bai et al., 2015). The declining patterns of physical activity correspond to the age related lower levels of fitness amongst boys and girls.

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EVALUATION OF FITNESS APPS 5 mHealth The use of phones a nd technology has grown exponentially in recent years. 13.4 billion a pps were downloaded in the first quarter of 2013 (Stoyanov et al. 2015). There is growing interest amongst researchers and health professionals over the use of smartphones and apps to pro vide interventions to help alter behavior towards fitness and personal well being. Due to the low costs, portability of smart phones and the apps that come along with them, smartphones allow easy access to health care and revolutionize behavioral intervent ion methods. Electronic interventions have a better chance of reaching a larger number of people with fewer costs and resources (Schweitzer et al., 2016). For example, people are able to check their blood glucose levels through a smart phone app. This has greatly reduced the costs and stress that comes along with having diabetes. MARS The increase in telehealth has led to a need for health professionals to assess the actual quality of these apps and decide whether or not they are effective in what they cla im to be achieving. A relatively new type of scoring scale is being used to rate health mobile apps, called Mobile App Rating Scale (MARS). Stoyanov et al. (2015) conducted a study in Australia on 60 different apps in the iTunes app store. The researchers individually rated these apps using the MARS and later convened to share their results. This led to a revision of the MARS. The categories examined when using this scale includes: app classification, aesthetics/graphics, engagement/entertainment, function ality/performance, information/quality, and subjective quality. Categories are rated on a number scale from 1 to 5, with 5 being excellent and that the user would recommend this app to someone in the future. The MARS is the first mHealth app quality rating tool to measure these

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EVALUATION OF FITNESS APPS 6 multidimensional categories of an app. These revised categories and number scale are used in this research study. Case Studies One study (Davis et al., 2016) pointed out that many fitness apps located in the iTunes store may be popu lar to their users, but they are not effective in changing the behavior of their users overall. Furthermore, the a pps this study examined, especially calorie counting apps, did not promote a healthy lifestyle change for life. Most of the changes were only temporary and not long term. This is a huge limitation when using mobile health products as an intervention for promoting fitness. Apps provided the user with general information on the health topic, but did not provide enough knowledge on how to change their behavior in the future when not accessing the particular app. McAlister et al (2008) found that in order to improve health behavior through of them, result, a healthier and more fit lifestyle term and frequent rewards that people give the Aims and Hypothesis The aim of this study is to evaluate health and wellness apps available in the Apple store utilizing the MARS. The primary focus of this study was on physical fitness. We aim to discover t he best F itness app located in the Apple store. Few studies have researched mHealth and technology, therefore this research will hopefully serve as a guide for future studies.

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EVALUATION OF FITNESS APPS 7 Methods Recruitment A total of nine undergraduate students at the University of Florida, including myself, were trained to use the MARS to evaluate fitness apps in the Apple store. Three video tutorials were watched by the trainees on the procedure of evaluating apps using th e MARS. During each training session, the researchers reviewed the MARS in great depth and provided two examples for the trainees to practice the proper steps in properly utilizing the MARS. d 160 fitness apps. They were sorted based on relevance and only English Data Collection The Mobile App Rating Scale (MARS) was designed to rate these mobile health apps on their quality and effectiveness. The categories included engagement, functionality, aesthetics, information quality, and subjective quality categories, to develop 23 subcategories from which the individual MARS items were developed. Each item used a 5 point scale (1 Inadequate, 2 Poor, 3 Acceptable, 4 Good, 5 Excellent). The category criteria was carefully decided on by the titles and types of apps in each category. There was a total of 102 apps that were select ed based on relevance to the above categories. Out of the total apps, 2 were randomly selected and used for training purposes only. The remaining 100 apps were then divided into three groups for evaluation purposes. Once the Fitness apps were chosen, the trainees were split into 3 groups. A list of approximately 33 mobile apps was distributed to each group. The trainees were instructed to evaluate each app individually based on the MARS criteria.

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EVALUATION OF FITNESS APPS 8 Data Analysis The total quality score of the apps was calculated by gathering the mean score of engagement, functionality, aesthetics, and information quality objectives from the 5 point scale rating. This provided the top ranked apps in each section of the MARS. A mean score was also collected by averaging a ll the sections together for each individual app. The subjective quality and app specific items were scored separately from the mean scores. Results All apps in this study were rated using a 5 point scale: 1 Inadequate, 2 Poor, 3 Acceptable, 4 Good, 5 Excellent. The engagement criteria is defined as how fun, interesting, customizable, interactive, and well targeted physical activity apps are to the target audience. T hese t welve apps had the highest average mean s cores in terms of engagement (see Appendix A for engagement results). In the next category, f unctionality of apps were evaluated based on app functioning, easy to learn, navigation, flow logic, and gestural design o f app. The mean scores in Section B were evaluated in order to determine the top 12 apps in this category. Two of the apps have an average score of 5, ind i cating a highly functional app (see Appendix B for functionality results). The a esthetics category focused on the graphic design, overall visual appeal, color scheme, and stylistic consistency of the apps (see Appendix C for aesthetics results). In addition, the information category involves apps scored on the availability of high quality information f rom a credible source (see Appendix D for information results). The top 15 Fitness apps were chosen based on the average scores derived from the MARS categories of engagement, functionality, aesthetics, and information utilizing the 5 point scale (see App endix E for Top 15 Fitness apps results).

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EVALUATION OF FITNESS APPS 9 es of qualities contribute to a high scoring app. Discussion The MARS provides a reliable and multidimensional analysis of mobile apps that can provide useful data for health professionals, researchers, and app developers. This study narrowed the primary focus of apps to those in the F it ness category of the iPhone Apple store. We evaluated 102 apps base d on the MARS criteria, providing results for the top apps in each section and overall top apps in the search. Top apps scored high in each category, althou gh no app received a perfect score of 20 High internal consistency was accounted for through the inter rater reliability. This indicates a reliable measure of F itness app quality ratings. Apps were rated using iPhones due to rater convenience and access t initially piloted on iPhone devices. Limitations Apps in the Fitness category of the Apple store are constantly updated. Since the study and MARS analysis many of the apps used have been updated and now have more curre nt versions. Updates on these apps have the potential to alter the results from this analysis. Furthermore, there is potential for newer fitness apps to be developed. Future Research Further research can be conducted to inv estigate apps that could be used for health promotion interventions that are focused on improving health through physical activity In addition, the specific q ualities of apps that rank highly can be used to improve existing apps, or

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EVALUATION OF FITNESS APPS 10 even create new ones. This research can also b e used as a tool for future app evaluations in the Apple store.

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EVALUATION OF FITNESS APPS 11 References Bai, Y., Saint Maurice, P.F., Welk, G.J., Allums Featherstone, K., Candelaria, N., Anderson, K. (2015). Prevalence of Youth Fitness in the United States: Baseline Results from the NFL PLAY 60 FITNESSGRAM Partnership Project. The Journal of Pediatrics, 167, 662 668. Davis, S.F., Ellsworth, M.A., Payne, H.E., Hall, S.E., West, J.H., Nordhagen, A.L. (2 016). Health Behavior Theory in Popular Calorie Counting Apps: A Content Analysis. Journal of Medical Internet Research, mHealth, and uHealth, 4(1). doi: 10.2196/mhealth.4177 Gowin, M., Cheney, M., Gwin, S., Wann, T.F. (2015). Health and Fitness App Use in College Students: A Qualitative Study. American Journal of Health Education, 46, 223 230. McAlister AL, Perry CL, Parcel GS. How individuals, environments, and health behaviors interact: social cognitive theory. In: Glanz K, Rimer BK, Viswanath K, e ditors. Health Behavior and Health Education: Theory, Research, and Practice. 4th edition. San Francisco: Jossey Bass; 2008:169 188. The national physical a ctivity plan: a call to action from the american heart association: a science advisory from the american heart association. Circulation. 131(21), 1932 40. doi: 10.1161/CIR.0000000000000203 Schweitzer, A.L., Ross, J.T., Klein, C.J., Lei, K.Y., Mackey, E.R (2016). An Electronic Wellness Program to Improve Diet and Exercise in College Students: A Pilot Study. Journal of Medical Internet Research, mHealth, and uHealth, 5(1). Stoyanov, S.R., Hides, L., Kavanagh, D.J., Zelenko, O., Tjondronegoro D., Mani, M. (2015). Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps. Journal of Medical Internet Research, mHealth, and uHealth, 3(1), e27.

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EVALUATION OF FITNESS APPS 12 Waleh, M.Q. (2016). Impacts of Physical Activity on the Obese. Obesity Management in Pri mary Care, 43(1), 97 107. doi:10.1016/j.pop.2015.08.014.

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EVALUATION OF FITNESS APPS 13 Appendix A Table 1: Engagement Fitness App Title Average Score Argus Calorie 4.7 Calorie Counter Pro 4.7 Weight Loss Coach by Fooducate 4.7 CARROT Fit 4.5 Cody Fitness Video 4.5 Map My Fitness GPS Workout Tracker 4.5 Running and Walking with Endomondo 4.5 Weight Loss Diet & Calorie Calculator (Spark People) 4.5 FitStar Yoga 4.4 Get In Shape: Couch to 5K 4.4 MyPlate Calorie Tracker 4.4 Pacer Pedometer Plus weight loss 4.4 Tables 1 provides the top averaged scores of fitness apps evaluated in Section A: Engagement of the MARS evaluation. Appendix B Table 2: Functionality Fitness App Title Average Score FitPort: Your Fitness Dashboard 5 UP by Jawbone Track Health & Fitness 5 8fit 4.83 Calorie Counter 4.83 Cody Fitness Video 4.83 Nike+ Running 4.83 Pocket Yoga 4.83 Running and Walking with Endomondo 4.83 Sports Tracker For Running, Cycling 4.83 Spring Running Music Walking & Running 4.83 Wahoo Fitness Bluetooth Powered 4.83 Yoga Studio 4.83 Table 2 provides the top averaged scores of fitness apps evaluated in section B: Functionality of the MARS evaluation.

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EVALUATION OF FITNESS APPS 14 Appendix C Table 3: Aesthetics Fitness App Title Average Score CARROT Fit 5 Get In Shape: Couch to 5K 4.83 Spring Running Music Walking & Running 4.83 UP by Jawbone Track Health & Fitness 4.83 7 Minute Workout (Wahoo) 4.67 Calorie Counter Pro 4.67 Clue Period Tracker 4.67 Get Moving 4.67 Human: Activity tracker walking, running 4.67 Pacer Pedometer Plus weight loss 4.67 Runtastic GPS Running and Fitness 4.67 Runtastic PRO GPS Running and Fitness 4.67 Strava Running and Cycling GPS Run 4.67 Table 3 provides the top averaged scores of fitness apps evaluated in section C: Aesthetics of the MARS evaluation. Appendix D Table 4: Information Fitness App Title Average Score My Macros+ diet 4.43 Nike + Running 4.29 JEFIT Workout 4.14 Map my Run+ GPS Running 4.14 Map my Walk GPS walking 4.14 Nike+ FuelBand 4.14 Runmeter GPS Pedometer Running 4.14 Trail Tracker GPS Outdoor Maps 4.14 5k Runner 4 Get in Shape: Couch to 5k 4 Lose it! 4 Rise Nutrition & weight loss coach 4 Runkeeper GPS Running, Walk, Cycle 4 Runtastic GPS Running & Fitness Tracker 4 Runtastic Me 4 Sworkit personalized workout 4 Table 4 provides the top averaged scores of fitness apps evaluated in section D: Information of the MARS evaluation.

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EVALUATION OF FITNESS APPS 15 Appendix E Table 5: Top 15 Fitness Apps Fitness App Title Average Score Get In Shape: Couch to 5K 17.9 UP by Jawbone Track Health & Fitness 17.59 Running and Walking with Endomondo 17.52 Strava Running and Cycling GPS Run 17.29 Spring Running Music Walking & Running 17.28 Weight Loss Coach by Fooducate 17.06 Calorie Counter Pro 17.03 Pacer Pedometer Plus weight loss 16.99 5k Runner 16.96 CARROT Fit 16.8 Map My Walk GPS Walking 16.78 FitStar Personal Trainer 16.75 Cody Fitness Video 16.67 Freelectics Bodyweight 16.59 Table 5 provides the top 15 fitness apps based on the overall average score evaluated in the MARS evaluation.



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Form online: http://digital.uflib.ufl.edu/procedures/c opyright/GrantofPermissions.doc Honors Thesis GRANT OF PERMISSIONS : Internet Distribution Agreement In reference to the following Undergraduate Honors Thesis, including any supplementary file (s): Megan Murphy, Dr. Mark Hart Evaluation of Fitness Apps University Of Florida : Gainesville, FL April 30, 2017 I, _________ Megan Murphy __ _______________________ as copyright holder or licensee with the authority to grant copyright permissions for the aforementioned title(s), hereby authorize the University of Florida, acting on behalf of the Board of Trustees of the University of Florida to digitize, distribute and archive the title(s) for nonprofit, educational purposes via the Internet or successive technologies. This is a non exclusive grant of permissions for on line and off line use for an indefinite term. Off line uses shall be c onsistent either, for educational uses, with the terms of U.S. copyright legislation's "fair use" provisions or, by the University of Florida, with the maintenance and preservation of an archival copy. Digitization allows the University of Florida to gener ate image and text based versions as appropriate and to provide and enhance access using search software. This grant of permissions prohibits use of the digitized versions for commercial use or profit. ___________ Megan Murphy ___________________________ Signature o f Copyright Holder ______________ Megan Murph y ________________________ Printed or Typed Name of Copyright Holder ______ 4/14/2017 _________ Date of Signature Attention : IR Manager Digital Production Services ; Smathers Libraries University of Florida P.O. Box 11700 3 Gainesville, FL32611 700 3 P: 352. 273.2831 IRManager@uflib.ufl.edu