Introduction Gastric cancer is one of the leading causes of cancer-related mortality worldwide, making early detection and prevention essential. Existing mobile health applications in this field are predominantly treatment-oriented and focused on post-diagnostic stages, leaving a significant gap in primary prevention coverage and identification of precursor conditions. The aim of this study is the systematic identification of data requirements related to precursor conditions of gastric cancer through review of clinical guidelines and evidence-based studies, in order to provide a conceptual framework for designing an informative, directive, and preventive mobile health application based on a rule-based (non-AI) approach. Method This study is a systematic review conducted in accordance with the PRISMA 2020 protocol. A comprehensive search was performed across PubMed, Google Scholar, Scopus, Web of Science, and UpToDate databases from January 2005 to March 2024. Inclusion criteria encompassed authoritative clinical guidelines, consensus studies, and research articles related to diagnosis, screening, or precursor conditions of gastric cancer. Source quality was assessed using the Mixed Method Appraisal Tool. Finally, 24 sources (19 primary sources including 14 clinical guidelines, 1 consensus study, and 4 research articles; plus 5 UpToDate sources as supplementary evidence) were included in the analysis. Findings From the systematic analysis of 19 primary sources, three main categories of precursor conditions for gastric cancer were identified: (a) baseline risk factors (family history, hereditary syndromes, previous gastric surgery), (b) diagnosed medical conditions ( Helicobacter pylori infection, gastritis, gastric ulcer, iron-deficiency anemia, Epstein-Barr virus), and (c) functional symptoms of the upper gastrointestinal tract (dyspepsia, gastroesophageal reflux, and related symptoms). This classification forms the basis of a four-level risk assessment framework that translates precursor conditions into understandable questions for general users. Conclusion This study presents the first comprehensive evidence-based framework for data requirements of a preventive mobile health application for gastric cancer. The proposed framework, with its focus on primary prevention and deterministic decision-making engine, offers the potential to create a conceptual infrastructure for early interventions and public health literacy enhancement. Major limitations include the conceptual nature of the design and lack of field validation. Future studies should focus on practical implementation, clinical effectiveness evaluation, user acceptance, and integration with health systems to realize the potential for reducing the burden of gastric cancer, particularly in high-prevalence regions.
Zolfaghari et al. (Sun,) studied this question.
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