PREPARATION OF AN EFFECTIVE TRADITIONAL CHINESE MEDICINAL COMPOUND FOR SLEEP-AID SACS IN THE TREATMENT OF INSOMNIA IN OLDER PEOPLE: A DELPHI METHOD STUDY
- Nursing department,dali bai autonomous prefecture peoples hospital,yunnan, dali, china.
- School of health medicine guangzhou huashang college, guangdong,guangzhouchina.
- Peking university health science center-nursing academy, macau polytechnique university, macau.
- Department of cadre ward, general hospital of southern theater command, guangzhou, china.
- The third affiliated hospital of guangzhou medical university, guangdong, guangzhou, china.
- Department of gynecology shenzhen nanshan peoples hospital, guangdong,shenzhen,china.
Abstract
Objective: To establish an expert consensus on an optimal Traditional Chinese Medicine (TCM) compound for use in sleep-aid sacs to treat insomnia in older adults.
Methods: A three-round Delphi study was conducted with 12 TCM experts from a Class Three Grade A hospital in Guangzhou, China, from April to July 2021. An initial list of herbs was developed based on a literature review. Experts rated the importance of each herb on a 5-point Likert scale over three successive questionnaire rounds. Statistical analysis, including mean scores, coefficient of variation (CV), and Kendalls W coefficient, was used to assess the concentration and coordination of expert opinions.
Conclusion: The Delphi method successfully facilitated a consensus among TCM experts, resulting in a scientifically derived and reliable herbal compound for treating insomnia in older people via sleep-aid sacs. This study provides a validated, non-invasive therapeutic option and a methodological reference for future research in TCM-based quality of life interventions.
Keywords
How to Cite This Article
Xue Feng, Ying Zhou, Cindy Sin U Leong, Jingwen Chen, Xiaofang Zou and Chuyuan Miao (2025); PREPARATION OF AN EFFECTIVE TRADITIONAL CHINESE MEDICINAL COMPOUND FOR SLEEP-AID SACS IN THE TREATMENT OF INSOMNIA IN OLDER PEOPLE: A DELPHI METHOD STUDY, International Journal of Advanced Research (IJAR), 13 (07), 1317-1326, ISSN 2320-5407. DOI: https://doi.org/10.21474/IJAR01/21443
Corresponding Author
Article Analytics
This work is licensed under a Creative Commons Attribution 4.0 International License.





