Article Title

Perceived Credibility of Weight Management Apps/Websites among Female College Students


1Clark, A., 1Kretsch, J., 1Haros, P., 1Gelfen, G., 2Albright, C., 1Jerome, G.J. 1Towson University, Towson, MD, 2Immaculata University, Immaculata, PA

Purpose: Apps and websites aimed at helping individuals make lifestyle changes to manage their weight are readily available. Students are often early adopters of technology; however they also have the burden of determining the accuracy, credibility and evidence-base of these technologies. Methods: There were 110 female college students with an average age 21.5 (SD=4.9) and BMI of 25.5 kg/m2(SD=5.7) who completed a survey via email and an in-person visit which included standardized height and weight. Participants used a 7-point likert scale to indicate the extent a characteristic detracted from the credibility (-3), was neutral (0) or added to the credibility (+3) for both the app/website they used and for an ideal app/website. They also indicated if 12 different evidence based strategies were used in their app/website or would be used in an ideal app/website. Results: Participants provided lower than ideal credibility ranks for the apps/websites they were using and reported that believability, trustworthiness, and expert content increased the credibility while spelling errors, questionable advertising and mismatched domain names decreased credibility. Additionally, 87% of participants used apps/websites that included some but not all of the identified evidence based strategies, and only 33% expected the apps/websites to include the full complement of evidence based strategies. Conclusion: Participants selected apps/websites that they considered less than ideal. The extent that apps/websites are not utilizing a full range of evidenced based approaches may limit an individual’s weight management success and lead to frustration. Ensuring that college students use safe and effective methods to manage their weight could lead to better health across their lifetime.

Research funded by the School of Emerging Technology, Towson University

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