The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index; none of the 47 sources its claims cite is checked for support yet.
Educational intervention using a mobile app to enhance sports nutrition knowledge and dietary habits in student-athletes: a randomized controlled trial
Open accessAbstract
Introduction: The increasing use of digital tools in education offers innovative ways to improve health behaviors. This study aims to evaluate the effectiveness of a mobile application intervention in enhancing sports nutrition knowledge and improving dietary habits among university student-athletes. Methods: A total of 100 university student-athletes were randomly assigned to either an experimental group (n = 50), which utilized the “MyFitnessPal” mobile application for nutrition education, or a control group (n = 50), which received traditional lecture-based instruction. Both groups completed validated pre- and post-intervention questionnaires over a three-month period to assess changes in sports nutrition knowledge and dietary habits. Results: The experimental group showed significantly greater improvements in both sports nutrition knowledge and dietary habits compared to the control group (p < 0.05). Discussion: These findings suggest that mobile applications like “MyFitnessPal” are more effective than traditional educational methods in enhancing nutritional awareness and promoting healthier dietary behaviors among student-athletes. Mobile application-based interventions can play a key role in improving athletic performance and overall health. Future research should explore the long-term impact and generalizability of such interventions across diverse athletic populations.
Overview
CoChat Summary
TL;DR
In a three-month randomized controlled trial of 100 university student-athletes, the MyFitnessPal mobile-app group showed significantly greater post-intervention sports nutrition knowledge and dietary-habit scores than the traditional lecture group. The authors conclude app-based education was more effective than lectures, while noting short duration, self-report, and single-university limitations.
Key findings
- Groups were comparable at baseline on sex, training experience, and BMI; 100 participants were randomized 50 control/50 experimental.
- Sports Nutrition Knowledge (normalized 0–100) was higher in the experimental group: 74.34 ± 23.62 vs control 65.62 ± 13.59; F = 12.760, p < 0.001.
- Dietary Habits score was higher in the experimental group: 54.00 ± 10.57 vs control 48.08 ± 10.76; F = 10.456, p = 0.001.
- The paper states traditional education improved nutritional awareness, but the digital intervention produced more significant results.
Methods
- RCT over 3 months; 100 student-athletes from a private university, ages 18–25, active in sport, able to use mobile apps; randomized to MyFitnessPal app (n = 50) or traditional lectures (n = 50). App group had modules on macronutrients, micronutrients, hydration, meal timing, and performance nutrition plus tracking and weekly reminders; control had six ~60-min lectures over 3 months covering the same content.
- Pre/post questionnaires: 59-item “NK for Athletes” sports nutrition knowledge questionnaire (+1 correct, −1 incorrect, 0 unanswered; normalized to 0–100) and 13-item Dietary Habits questionnaire (stated maximum 39). Normality assessed by Kolmogorov–Smirnov; due to non-normal distributions, non-parametric tests were used, with ANOVA for group comparisons.
Limitations
- Paper-stated: 3-month duration may not capture long-term behavior change; self-reported questionnaires risk bias; single private university limits generalizability; no athletic performance/health outcomes assessed; no analysis of which app features drove effects.
- Evident: no blinding or allocation-concealment procedure is described; baseline outcome means are not reported, so baseline equivalence on SNK/DH cannot be verified; reported DH means (54.00, 48.08) exceed the stated DH maximum of 39 without explanation; Cronbach’s alpha values differ between Methods (0.731 SNK, 0.724 DH) and Results Table 2 (0.925 SNK, 0.912 DH).
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Claims the paper makes
0 Valid · 0 Not valid · 28 Not checked · 38 Own results and interpretations
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results showed that the use of the MyFitnessPal mobile application was more effective in improving sports nutrition awareness and eating habits in the experimental group compared to the control group that received traditional education through lectures.”
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although traditional education was effective in improving nutritional awareness, digital interventions provided more significant results.”
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“The results of this study show that the experimental group that used the “MyFitnessPal” application demonstrated a significant improvement in their level of nutrition knowledge, which is consistent with research showing that digital interventions can be effective in enhancing nutritional knowledge and changing eating behaviors”
What the sources say
- Not checked yetcites Jospe et al., 2015 source
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Nevertheless, there are a number of barriers that can prevent athletes from putting optimal nutrition practices into action (AlKasasbeh et al., 2024; Malinauskas et al., 2007). These factors include limited time, insufficient meal preparation facilities, financial constraints, poor meal planning skills, inadequate preparation skills, and time-shift travel demands.”
What the sources say
- Not matchedcites AlKasasbeh et al., 2024
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Malinauskas et al., 2007
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Poor knowledge of nutrition is a potential barrier that negatively affects athletes’ performance”
What the sources say
- Not matchedcites Amawi et al., 2023a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Amawi et al., 2023b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Amawi et al., 2023c
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
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- The quote only partly states this claim. 3
- Probably not a substantial claim. 29
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
§ Materials and methods
“The scale showed good reliability, with a Cronbach’s alpha of 0.724”
§ Results
“Dietary Habits (DH) 0.912 13”
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
§ Materials and methods
“The maximum score that can be obtained in this section is set at 39 points.”
§ Results
“the experimental group had a mean DH score of 54.00 ± 10.57 (95% CI: 52.00–56.00), compared to 48.08 ± 10.76 (95% CI: 46.50–49.66) in the control group.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Materials and methods
“raw scores were normalized to a 0–100 scale using the following formula: Normalized Score = (Raw Score ÷ 59) × 100.”
§ Materials and methods
“+1 point was awarded for each correct answer, −1 point for each incorrect answer, and 0 points were awarded for items that were not answered.”
Citations
Cites
Food Choice: A Conceptual Model of the Process
FURST, T., CONNORS, M., BISOGNI, C. A., SOBAL, J., & FALK, L. W. (1996) · Appetite · doi:10.1006/appe.1996.0019 · Cited by 1,230
Prevalence of Eating Disorders in Elite Athletes Is Higher Than in the General Population
Sundgot-Borgen, J., & Torstveit, M. K. (2004) · Clinical Journal of Sport Medicine · doi:10.1097/00042752-200401000-00005 · Cited by 1,077
Nutrition knowledge and food intake
Wardle, J., Parmenter, K., & Waller, J. (2000) · Appetite · doi:10.1006/appe.1999.0311 · Cited by 935
Dietary Assessment Methodology
Thompson, F. E., & Subar, A. F. (2017) · Nutrition in the Prevention and Treatment of Disease · doi:10.1016/b978-0-12-802928-2.00001-1 · Cited by 913
Martin, C. K., Han, H., Coulon, S. M., Allen, H. R., Champagne, C. M., & Anton, S. D. (2008) · British Journal of Nutrition · doi:10.1017/s0007114508027438 · Cited by 328
Guidelines for Daily Carbohydrate Intake: Do Athletes Achieve Them?
Burke, L. M., Cox, G. R., Cummings, N. K., & Desbrow, B. (2001) · Sports Medicine · doi:10.2165/00007256-200131040-00003 · Cited by 325
Nutrition Knowledge in Athletes: A Systematic Review
Heaney, S., O’Connor, H., Michael, S., Gifford, J., & Naughton, G. (2011) · International Journal of Sport Nutrition and Exercise Metabolism · doi:10.1123/ijsnem.21.3.248 · Cited by 321
Elite athletes: Effects of the pressure to be thin
Byrne, S., & McLean, N. (2002) · Journal of Science and Medicine in Sport · doi:10.1016/s1440-2440(02)80029-9 · Cited by 290
Torres-McGehee, T. M., Pritchett, K. L., Zippel, D., Minton, D. M., Cellamare, A., & Sibilia, M. (2012) · Journal of Athletic Training · doi:10.4085/1062-6050-47.2.205 · Cited by 290
A Life Course Perspective: Understanding Food Choices in Time, Social Location, and History
Devine, C. M. (2005) · Journal of Nutrition Education and Behavior · doi:10.1016/s1499-4046(06)60266-2 · Cited by 278
Research works printed but not linked: 1
- Malinauskas, 2007, Summer league college baseball players: do dietary intake and barriers to healthy eating differ between game and non-game days?, RT Journal
Cited by
Orhan, B. E., Alkasasbeh, W. J., Karaçam, A., Canlı, U., Adigüzel, N. S., & Amawi, A. T. (2026) · Frontiers in Nutrition · doi:10.3389/fnut.2026.1754963 · Cited by 11
Self-citationMushkani, E. A., Hamidy, F., Mushkani, T. A., Daanish, A. F., & Rahmani, M. R. (2026) · Harm Reduction Journal · doi:10.1186/s12954-025-01389-4 · Cited by 4
Addressing Food Insecurity Among College Athletes: Strategies to Overcome Barriers to Food Access
Bodian, G., Starkoff, B. E., & Lenz, E. K. (2026) · Journal of Nutrition Education and Behavior · doi:10.1016/j.jneb.2026.01.013 · Cited by 4
Artificial intelligence and wearables in sport: performance, injury risk, and wellbeing
Alkasasbeh, W. J., Amawi, A. T., Grivas, G. V., Orhan, B. E., & Alawamleh, T. (2026) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2026.1838507 · Cited by 4
Self-citationAlkasasbeh, W. J., Orhan, B. E., Alawamleh, T., Grivas, G. V., & Amawi, A. T. (2026) · Discover Public Health · doi:10.1186/s12982-026-01761-0 · Cited by 3
Self-citation
Metadata
- Authors
- AlKasasbeh, W. J., Amawi, A. T., Al-Nawaiseh, S. J., Alshorman, D., Alshdaifat, K., Alawamleh, T., & Orhan, B. E.
- Affiliations
- Middle East University (JO)
- University of Jordan (JO)
- Istanbul Aydın University (TR)
- Corresponding author
- AlKasasbeh, Walaa Jumah
- Venue
- Frontiers in Education
- Publisher
- Frontiers Media SA
- Published
- 2025-08-18
- Volume
- 10
- ISSN
- 2504-284X (ISSN-L)
- OpenAlex
- W4413284153
- Cited by
- 14
- References
- 55
- Citations by year
- 2026: 14
- FWCI
- 9.77
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Education (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- mobile health intervention, sports nutrition knowledge, dietary habits, student athletes, MyFitnessPal, nutrition education, university athletes, digital health education, lecture method comparison
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
