Objective Depression is a prevalent mental disorder associated with substantial social and familial burdens, and exercise is increasingly recognized as a promising non-pharmacological intervention; however, research is hindered by heterogeneous approaches, safety concerns, and individual variability. A structured knowledge framework may support the development of more personalized exercise prescription. This study aimed to construct PEPRKD-Depression (Personalized Exercise Prescription Recommendation Knowledge Database for Depression), a structured knowledge database of exercise interventions for depression, to systematically integrate existing literature and provide a knowledge foundation for personalized exercise prescription. Methods Data were sourced from PubMed and included original studies on exercise interventions for depression published between 1960 and 2023. Relevant data including structured exercise programs, patient information, fitness and risk assessments, adverse events, and outcomes, were extracted, standardized, and organized. The knowledge database was developed with Vue3, hosted on Nginx, and uses MySQL for data storage. Results PEPRKD-Depression includes 567 studies with 769 exercise intervention protocols involving 100,794 subjects across 49 countries. It extracted 662 depression-related items (e.g., symptoms, disorders, perinatal and subthreshold depression). Exercise regimens followed the “FITT-VPP” principle: Frequency, Intensity, Time, Type, Volume, Progression, Periods of time. The knowledge database is publicly available at: https://dpa.bioinf.org.cn/ . Conclusion PEPRKD-Depression is a comprehensive exercise therapy knowledge database for depression that provides a structured repository of exercise intervention information that may serve as a preliminary knowledge resource for future personalized exercise recommendation research and decision-support applications.
Li et al. (Sun,) studied this question.