Evidence map›Paper›PMID 40144913›Full record

ArticleGHM open2021

Prevention of Worsening Diabetes through Behavioral Changes by an IoT-based Self-Monitoring System in Japan (PRISM-J): Study design and rationale for a multicenter, open-label, randomized parallel-group trial.

Ryotaro Bouchi, Kazuo Izumi, Hiroshi Ohtsu, Kengo Miyo, Shigeho Tanaka, Noriko Satoh-Asahara, Kazuo Hara, Masato Odawara, Yoshiki Kusunoki, Hidenori Koyama and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in GHM open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

16 authors.

Ryotaro BouchiDiabetes and Metabolism Information Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan.
Kazuo IzumiCenter for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan.
Hiroshi OhtsuDepartment of Clinical Study and Informatics, Clinical Epidemiology Section/JCRAC Data Center, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan.
Kengo MiyoCenter for Medical Informatics Intelligence, National Center for Global Health and Medicine, Tokyo, Japan.
Shigeho TanakaFaculty of Nutrition, Kagawa Nutrition University, Saitama, Japan.
Noriko Satoh-AsaharaDepartment of Endocrinology, Metabolism, and Hypertension Research, Clinical Research Institute, National Hospital Organization Kyoto Medical Center, Kyoto, Japan.
Kazuo HaraDepartment of Endocrinology and Metabolism, Saitama Medical Center, Jichi Medical University, Saitama, Japan.
Masato OdawaraDepartment of Diabetology, Metabolism, and Endocrinology, Tokyo Medical University Hospital, Tokyo, Japan.
Yoshiki KusunokiDepartment of Diabetes, Endocrinology and Clinical Immunology, Hyogo College of Medicine, Hyogo, Japan.
Hidenori KoyamaDepartment of Diabetes, Endocrinology and Clinical Immunology, Hyogo College of Medicine, Hyogo, Japan.
Takeshi OnoueDepartments of Endocrinology and Diabetes, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Hiroshi ArimaDepartments of Endocrinology and Diabetes, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Kazuyo TsushitaFaculty of Nutrition, Kagawa Nutrition University, Saitama, Japan.
Hirotaka WatadaDepartment of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Takashi KadowakiToranomon Hospital, Tokyo, Japan.
Kohjiro UekiDepartment of Diabetes and Endocrinology and Metabolism, Center Hospital, National Center for Global Health and Medicine, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of the Internet-of-Things has improved glycemic control in individuals with diabetes in several small-scale studies with a short follow-up period. This large-scale randomized controlled trial investigates whether a smartphone-based self-management support system prevents the worsening of glycemic control in individuals with type 2 diabetes. Individuals with type 2 diabetes (age range 20-74 years;

Indexed as

applicationbehaviour modificationglycemic controltype 2 diabetes

Identifiers

PMID40144913
PMCPMC11933935

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.