Understanding User Needs for a Mobile Health Application: Insights into Fasting, Training, and Muscle Development

Lila Setiyani, Eldawati Eldawati, Wafiqah Yasmin Azhar, Devi Fajar Wati, Dedih Dedih, Hanny Hikmayanti

Abstract


Mobile Health (mHealth) applications are increasingly used to support intermittent fasting, fitness training, and nutrition tracking. However, existing solutions remain fragmented, focusing on isolated domains without addressing users’ holistic health needs. This study aimed to explore user needs and preferences for an integrated mobile health application that combines fasting, training, and muscle development, emphasizing feature importance, usability expectations, and privacy concerns. A mixed-methods approach was used: a survey (n = 50) captured demographic profiles, feature prioritization, and usability expectations, while interviews (n = 10) explored user experiences and challenges. Quantitative data were analyzed using descriptive statistics, while qualitative interview responses were grouped into key themes through manual coding and interpretation. Results from both approaches were triangulated to strengthen the validity and reliability of findings. Users prioritized workout progression tracking (M = 4.94, SD = 0.18, 95% CI [4.89, 4.99]) and protein/macro monitoring (M = 4.20, SD = 0.42) over fasting timers (M = 2.92/5) or motivational features (M = 2.88). Usability expectations were high (Ease of Use = 6.06/7; System Capability Fit = 6.36/7), and privacy was a non-negotiable factor (M = 5.00/5). Themes revealed frustrations with incomplete exercise libraries, fragmented features, and lack of personalization. The study highlights the need for integrated, user-centered mHealth applications that unify fasting, training, and nutrition while embedding privacy-by-design principles. Future work will advance this study through prototype development and usability testing using SUS and UMUX-Lite metrics.


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Keywords


Mhealth; User Needs; Intermittent Fasting; Training; Muscle Development; Nutrition Tracking; Usability; Privacy; Mixed Methods

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Barcode

Journal of Applied Data Sciences

ISSN : 2723-6471 (Online)
Collaborated with : Computer Science and Systems Information Technology, King Abdulaziz University, Kingdom of Saudi Arabia.
Publisher : Bright Publisher
Website : http://bright-journal.org/JADS
Email : taqwa@amikompurwokerto.ac.id (principal contact)
    support@bright-journal.org (technical issues)

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