Evidence mapPaperPMID 39625868Full record

SynthesisJMIR mHealth and uHealth2024

The Role of Smartwatch Technology in the Provision of Care for Type 1 or 2 Diabetes Mellitus or Gestational Diabetes: Systematic Review.

Sergio Diez Alvarez, Antoni Fellas, Katie Wynne, Derek Santos, Dean Sculley, Shamasunder Acharya, Pooshan Navathe, Xavier Gironès, Andrea Coda

Abstract readSystematic Review
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
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.

Sergio Diez AlvarezSchool of Medicine and Public Health, College of Health Medicine and Wellbeing, University of Newcastle, University Drive, Callaghan, Newcastle, 2308, Australia, 61409916949.ORCID 0000-0002-3393-5764
Antoni FellasSchool of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia.ORCID 0000-0003-1557-6232
Katie WynneSchool of Medicine and Public Health, College of Health Medicine and Wellbeing, University of Newcastle, University Drive, Callaghan, Newcastle, 2308, Australia, 61409916949.ORCID 0000-0002-7980-3337
Derek SantosQueen Margaret University, School of Health Sciences, Edinburgh, United Kingdom.ORCID 0000-0001-9936-715X
Dean SculleySchool of Biomedical Sciences and Pharmacy, College of Health Medicine and Wellbeing, University of Newcastle, Newcastle, Australia.ORCID 0000-0003-3972-8309
Shamasunder AcharyaSchool of Medicine and Public Health, College of Health Medicine and Wellbeing, University of Newcastle, University Drive, Callaghan, Newcastle, 2308, Australia, 61409916949.ORCID 0000-0003-4565-1571
Pooshan NavatheCentral Queensland Health, Rockhampton, Australia.ORCID 0000-0003-1768-355X
Xavier GironèsDepartment of Research and Universities, Government of Catalonia-Generalitat de Catalunya, Barcelona, Spain.ORCID 0000-0002-2329-5927
Andrea CodaSchool of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia.ORCID 0000-0003-0427-6672

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The use of smart technology in the management of all forms of diabetes mellitus has grown significantly in the past 10 years. Technologies such as the smartwatch have been proposed as a method of assisting in the monitoring of blood glucose levels as well as other alert prompts such as medication adherence and daily physical activity targets. These important outcomes reach across all forms of diabetes and have the potential to increase compliance of self-monitoring with the aim of improving long-term outcomes such as hemoglobin A1c (HbA1c). Objective: This systematic review aims to explore the literature for evidence of smartwatch technology in type 1, 2, and gestational diabetes. Methods: A systematic review was undertaken by searching Ovid MEDLINE and CINAHL databases. A second search using all identified keywords and index terms was performed on Ovid MEDLINE (January 1966 to August 2023), Embase (January 1980 to August 2023), Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, latest issue), CINAHL (from 1982), IEEE Xplore, ACM Digital Libraries, and Web of Science databases. Type 1, type 2, and gestational diabetes were eligible for inclusion. Quantitative studies such as prospective cohort or randomized clinical trials that explored the feasibility, usability, or effect of smartwatch technology in people with diabetes were eligible. Outcomes of interest were changes in blood glucose or HbA1c, physical activity levels, medication adherence, and feasibility or usability scores. Results: Of the 8558 titles and abstracts screened, 5 studies were included for qualitative synthesis in this review. A total of 322 participants with either type 1 or type 2 diabetes mellitus were included in the review. A total of 4 studies focused on the feasibility and usability of smartwatch technology in diabetes management. One study conducted a proof-of-concept randomized clinical trial including smartwatch technology for exercise time prescriptions for participants with type 2 diabetes mellitus. Adherence of participants to smartwatch technology varied between included studies, with one reporting input submissions of 58% and another reporting that participants logged 50% more entries than they were required to. One study reported significantly improved glycemic control with integrated smartwatch technology, with increased exercise prescriptions; however, this study was not powered and required a longer observational period. Conclusions: This systematic review has highlighted the lack of robust randomized clinical trials that explore the efficacy of smartwatch technology in the management of patients with type 1, type 2, and gestational diabetes. Further research is required to establish the role of integrated smartwatch technology in important outcomes such as glycemic control, exercise participation, drug adherence, and diet monitoring in people with all forms of diabetes mellitus.

Indexed as

Diabetes, GestationalDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Blood Glucose Self-MonitoringFemaleHumansPregnancyWearable Electronic Devicesblood glucosediabetesdiabetes mellitusdigital healthfeasibilityflash glucose monitoringgestational diabetesglucose monitoringmedication adherencemHealthmobile healthmobile phoneself-monitoringsmartphonessmartwatchsmartwatch technologysystematic reviewusability

Identifiers

PMID39625868
PMCPMC11629918

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.