The Effectiveness of a Traditional Chinese Medicine–Based Mobile Health App for Individuals With Prediabetes: Randomized Controlled Trial
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Abstract
Background: Traditional Chinese medicine (TCM) theories assert that body constitution and meridian energy lay the foundation for disease prevention. TCM-based health concepts have not yet been incorporated into mobile health (mHealth) apps for individuals with prediabetes. Objective: The aim of this study was to examine the effectiveness of a TCM mHealth app for individuals with prediabetes. Methods: This randomized controlled trial recruited 121 individuals with prediabetes at a teaching hospital in New Taipei City between February 2020 and May 2021. The participants were randomly assigned to the TCM mHealth app group (n=42), ordinary mHealth app group (n=41), or control group (n=38). All participants received the usual care that included 15-20 minutes of health education about the disease, along with healthy diet and exercise encouragement. The ordinary mHealth app included physical activity (PA), diet, and disease education, along with individual records. The TCM mHealth app additionally included qi and body constitution information, along with constitution-based PA and diet advice. The control group received the usual care alone and did not have access to any app. Data were collected at baseline, at the end of the 12-week intervention, and 1 month after the intervention. Body constitution, including yang-deficiency, yin-deficiency, and phlegm-stasis, was measured according to the Body Constitution Questionnaire, with higher scores indicating a greater deficiency. Body energy was examined using the Meridian Energy Analysis Device. The Short-Form 36 questionnaire was used to evaluate health-related quality of life (HRQOL), which yielded physical component scores and mental component scores, with higher scores indicating better physical and mental aspects of HRQOL, respectively. Results: Compared to the control group, the TCM mHealth app group showed greater improvement in hemoglobin A1c (HbA1c), yang-deficiency and phlegm-stasis body constitution, and BMI; however, no significant differences were found in these outcomes between the TCM mHealth app and ordinary mHealth app groups. The TCM mHealth app group showed better improvement in body energy and mental component scores than the ordinary mHealth app group. There were no significant differences in fasting plasma glucose, yin-deficiency body constitution, Dietary Approaches to Stop Hypertension dietary behavior, and total PA among the three groups after the intervention. Conclusions: Use of either the ordinary or TCM mHealth app improved HRQOL among individuals with prediabetes. Compared to the outcomes of controls not using any app, use of the TCM mHealth app was effective at improving HbA1c, BMI, yang-deficiency and phlegm-stasis body constitution, and HRQOL. Moreover, using the TCM mHealth app seemed to improve the body energy and HRQOL more than when using the ordinary mHealth app. Further studies with a larger sample size and longer follow-up period may be necessary to determine whether the differences favoring the TCM app are clinically meaningful. Trial Registration: ClinicalTrials.gov NCT04096989; https://clinicaltrials.gov/ct2/show/NCT04096989
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Of 12 DCP studies assessing dysglycemia, 9 (75%) reported positive population health outcomes and 3 (25%) showed neutral effects.
“Of the 12 studies (92.3%) assessing the effects of dysglycemia, 9 (75%) reported positive population health outcomes, such as significant HbA1c reduction compared to the control group in Kim et al [45] using virtual reality (VR) technology and Everett et al [46] using AI interventions (P<.05). Furthermore, 3 (25%) studies [40,44,47] showed the effect was neutral.”
From Digital Health Interventions to Prevent Type 2 Diabetes Mellitus: Systematic Review (2025) · cites this paper as [47]
The Results (Primary Outcomes; page unavailable) report no significant effect on fasting plasma glucose, but a significant HbA1c reduction in the TCM app group compared with controls. Thus, this paper does not support classifying its dysglycemia findings as neutral. As a single trial, it also cannot establish the citing review’s counts of 9 positive and 3 neutral studies. (LLM, conf=0.88)
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- Authors
- Chung, H.-W., Tai, C.-J., Chang, P., Su, W.-L., & Chien, L.-Y.
- Affiliations
- National Yang Ming Chiao Tung University (TW)
- Taipei Medical University (TW)
- Tzu Chi University (TW)
- Corresponding author
- Chien, Li-Yin
- Venue
- JMIR mHealth and uHealth
- Publisher
- JMIR Publications Inc.
- Published
- 2023-06-20
- Volume
- 11
- Pages
- e41099
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC10337399
- OpenAlex
- W4378191580
- Cited by
- 29
- References
- 61
- Citations by year
- 2026: 6 · 2025: 13 · 2024: 7 · 2023: 3
- FWCI
- 10.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Complementary and alternative medicine › Traditional Chinese Medicine Studies
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- prediabetes, traditional Chinese medicine, mobile health apps, body constitution, yang deficiency, yin deficiency, phlegm stasis, health-related quality of life, physical activity, dietary behavior, body mass index, fasting blood glucose, health education, diabetes prevention, DASH diet
- MeSH terms
- Humans, Medicine, Chinese Traditional, Prediabetic State, Quality of Life, Yin Deficiency, Telemedicine, Mobile Applications
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Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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