Evidence mapPaperPMID 39879607Full record

SynthesisJournal of medical Internet research2025

Effectiveness of Different Intervention Modes in Lifestyle Intervention for the Prevention of Type 2 Diabetes and the Reversion to Normoglycemia in Adults With Prediabetes: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Yachen Wang, Xin Chai, Yueqing Wang, Xuejun Yin, Xinying Huang, Qiuhong Gong, Juan Zhang, Ruitai Shao, Guangwei Li

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Trial
  2. [The Effect of Konjac Glucomannan on Blood Glucose and Insulin Levels in Obese Patients With Prediabetes].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026
    Trial
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Use of technology in prediabetes and precision prevention.Journal of diabetes investigation · 2025
    Review
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yachen Wang *School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0009-0000-4492-0886
Xin Chai *School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0009-0002-4373-3178
Yueqing Wang *School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-3676-5123
Xuejun YinSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0001-8446-9591
Xinying HuangSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-9948-6869
Qiuhong GongFuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-8781-1214
Juan ZhangSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-1161-1072
Ruitai ShaoSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0009-0006-8506-9534
Guangwei LiSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-3873-1875

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLifestyle interventions have been acknowledged as effective strategies for preventing type 2 diabetes mellitus (T2DM). However, the accessibility of conventional face-to-face interventions is often limited. Digital health intervention has been suggested as a potential solution to overcome the limitation. Despite this, there remains a significant gap in understanding the effectiveness of digital health for individuals with prediabetes, particularly in reducing T2DM incidence and reverting to normoglycemia.

objectiveThis study aimed to assess the effectiveness of different intervention modes of digital health, face-to-face, and blended interventions, particularly the benefits of digital health intervention, in reducing T2DM incidence and facilitating the reversion to normoglycemia in adults with prediabetes compared to the usual care.

methodsWe conducted a comprehensive search in 9 electronic databases, namely MEDLINE, Embase, ACP Journal Club, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Cochrane Clinical Answers, Cochrane Methodology Register, Health Technology Assessment, and NHS Economic Evaluation Database through Ovid, from the inception to October 2024. This review included randomized controlled trials (RCTs) that studied the effectiveness of lifestyle interventions in adults with prediabetes. The overall intervention effect was synthesized using a random-effects model. The I² statistic was used to assess heterogeneity across the RCTs. We performed a subgroup analysis to explore the effectiveness of digital health, face-to-face, and blended interventions compared with the control group, which received usual care.

resultsFrom an initial 7868 records retrieved from 9 databases, we identified 54 articles from 31 RCTs. Our analysis showed that face-to-face interventions demonstrated a significant 46% risk reduction in T2DM incidence (risk ratio [RR] 0.54, 95% CI 0.47-0.63; I²=43%; P<.001), and a 46% increase in the reversion to normoglycemia (RR 1.46, 95% CI 1.11-1.91; I²=82%; P=.006), when compared with the control group. On the other hand, digital health interventions, compared with the control group, were associated with a 12% risk reduction in T2DM incidence (RR 0.88, 95% CI 0.77-1.01; I²=0.6%; P=.06). Moreover, the blended interventions combining digital and face-to-face interventions suggested a 37% risk reduction in T2DM incidence (RR 0.63, 95% CI 0.49-0.81;I²<0.01%; P<.001) and an 87% increase in the reversion to normoglycemia (RR 1.87, 95% CI 1.30-2.69; I²=23%; P=.001). However, no significant effect on the reversal of prediabetes to normoglycemia was observed from the digital health interventions.

conclusionsFace-to-face interventions have consistently demonstrated promising effectiveness in both reductions in T2DM incidence and reversion to normoglycemia in adults with prediabetes. However, the effectiveness of digital health interventions in these areas has not been sufficiently proven. Given these results, further research is required to provide more definitive evidence of digital health and blended interventions in T2DM prevention in the future.

trial registrationPROSPERO CRD42023414313; https://tinyurl.com/55ac4j4n.

Indexed as

Diabetes Mellitus, Type 2Life StylePrediabetic StateAdultHumansRandomized Controlled Trials as Topicdigital health interventionintervention modelifestyle interventionmeta-analysismobile phoneprediabetic statereviewsystematic reviewtype 2 diabetes mellitus

Identifiers

PMID39879607
PMCPMC11822313

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.