Factors Influencing Nutritional Intake and Interests in Educational Content of Athletes and Sport Professionals Toward the Development of a Clinician-Supported Mobile App to Combat Relative Energy Deficiency in Sport: Formative Research and a Description of App Functions

Abstract

Background: Relative energy deficiency in sport (RED-S) as a consequence of athlete malnutrition remains a prominent issue. However, it remains underrecognized, in part due to the perceived outward health of athletes. The Eat2Win app was designed to combat RED-S and athlete malnutrition by providing education, behavior modification, and direct communication with expert sports dietitians to athletes and sport professionals (professionals who work with athletes, eg, sport coaches and athletic trainers).

Objective: The purpose of this formative research was to gain critical insight on motivators and barriers to optimal nutritional intake from both the athletes' and sport professionals' perspectives. Additionally, since these 2 groups represent the primary end users of an app aimed at improving athlete nutrition and reducing the risk of RED-S, a secondary objective was to gain insight on the preferences and perceptions of app-based educational content and functionality.

Methods: An electronic survey was developed by an interdisciplinary team of experts. Survey questions were established based upon prevailing literature, professional dietetic field experience, and app design considerations to obtain respondent knowledge on key sports nutrition topics along with motivations and barriers to meal choices. Additionally, the survey included questions about the development of an integrative, clinician-support app aimed at addressing RED-S. These questions included preferences for educational content, modes of in-app information, and communication delivery for the target population (app end users: athletes and sport professionals). The survey was distributed through Research Electronic Data Capture (REDCap) to athletes and sport professionals using targeted email, social media, and community engagement campaigns. The electronic survey was available from May 4 to August 2, 2022.

Results: Survey respondents (n=1352) included athletes and professionals who work with athletes from a variety of settings, like high school, collegiate, professional, and club sports. Respondents reported high interest in 8 core sports nutrition topics. The preferred modes of information and communication delivery were visual formats (eg, videos and infographics) and in-app alerts (eg, direct messaging and meal reminders). Only athlete respondents were asked about motivators and barriers that influence meal choices. "Health" and "sports performance" were the highest scoring motivators, while the highest scoring barriers were "cost of food," "easy access to unhealthy food," and "time to cook or prepare food." Notably, survey respondents provided positive feedback and interest using a novel function of the app: real-time meal feedback through food photography.

Conclusions: The Eat2Win app is designed to combat RED-S and athlete malnutrition. Results from this study provide critical information on end-user opinions and preferences and will be used to further develop the Eat2Win app. Future research will aim to determine whether the Eat2Win app can prevent RED-S and the risk of athlete malnutrition to improve both health and performance.

Keywords: RED-S; dietitian; mHealth; malnutrition; mobile health; performance; relative energy deficiency in sport; sports nutrition; technology.

Figure 1

Previous mobile app use and interest in Eat2Win functions. Survey respondents were asked yes or no questions about their use of mobile apps and several Eat2Win functions. Separate questions were asked to athletes and sport professionals. Individual missing data points were excluded from analysis.

Figure 2

Interest in sports nutrition topics. Survey respondents were asked to rate their interest in a variety of sports nutrition topics, with 0 being not interested at all and 10 being extremely interested. Individual missing data points were excluded from analysis. Data are presented as mean (SD), n. Question (Q) 1: 7.9 (2.2), 1197. Q2: 7.9 (2.2), 1195. Q3: 7.6 (2.3), 1192. Q4: 7.8 (2.2), 1196. Q5: 7.7 (2.2), 1201. Q6: 7.8 (2), 1200. Q7: 7.9 (1.9), 1205. Q8: 7.5 (2.3), 1201. Au: arbitrary units.

Figure 3

Preferred mode of information delivery. Survey respondents were asked to rate their preferred mode of delivery for information on sports nutrition topics, with 0 being not interested at all and 10 being extremely interested. Individual missing data points were excluded from analysis. Data are presented as mean (SD), n. Question (Q) 1: 7.5 (2.2), 1191. Q2: 6.9 (2.5), 1191. Q3: 7.4 (2.2), 1193. Q4: 7.7 (2.2), 1196. Q5: 7.5 (2.4), 1186. Q6: 6.9 (2.5), 1193. Q7: 7.5 (2.2), 1188. Q8: 7.1 (2.4), 1193. Q9: 7.0 (2.3), 1193. Au: arbitrary units.

Figure 4

Motivators to meal choices. Athlete respondents were asked about 10 motivators to meal choices and the frequency of which those motivators influenced meal choice using a modified Likert scale. Frequency data are presented (number of respondents that selected each item).

Figure 5

Barriers to meal choices. Athlete respondents were asked about 11 common barriers that influenced their meal choices and to rate those barriers on a 0-10 scale, with 0 representing not a barrier at all and 10 signifying a major barrier. Frequency data are presented (number of respondents that selected each item).