Evidence map›Paper›PMID 27864165›Full record

Trial reportJournal of medical Internet research2016

Text to Move: A Randomized Controlled Trial of a Text-Messaging Program to Improve Physical Activity Behaviors in Patients With Type 2 Diabetes Mellitus.

Stephen Agboola, Kamal Jethwani, Lenny Lopez, Meghan Searl, Sandra O'Keefe, Joseph Kvedar

Open access · goldAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of medical Internet research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 15 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 15 pooled it
20.5field-weighted citation impact, top 1% of its field
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

43 citing papers in PubMed, 15 syntheses or guidelines pooled it, 93 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pooled it
  12. Pooled it
  13. Pooled it
  14. Pooled it
  15. Strengthening Delivery of Health Services Using Digital Devices.Global health, science and practice · 2018
    Pooled it
  16. Trial
  17. Trial
  18. Trial
  19. Review
  20. 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

6 authors at 3 institutions in 1 country.

Stephen AgboolaPartners Connected Health, Boston, MA, United States.ORCID 0000-0002-2161-8091
Kamal JethwaniPartners Connected Health, Boston, MA, United States.ORCID 0000-0002-0122-8002
Lenny LopezUniversity of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0001-5552-8775
Meghan SearlBrigham and Women's Hospital, Boston, MA, United States.ORCID 0000-0002-0536-8344
Sandra O'KeefeMassachusetts General Hospital, Boston, MA, United States.ORCID 0000-0003-1851-7713
Joseph KvedarPartners Connected Health, Boston, MA, United States.ORCID 0000-0002-7517-2291
Brigham and Women's Hospital · USMassachusetts General Hospital · USUniversity of California, San Francisco · US

Funding

Association of Acculturation with Type 2 Diabetes Risk Among US LatinosK23DK098280 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LOPEZ, LENNY · 2013 to 2016
$737k
NIDDK NIH HHS K23 DK098280
6 · The paper itself

Abstract

backgroundText messages are increasingly being used because of the low cost and the ubiquitous nature of mobile phones to engage patients in self-care behaviors. Self-care is particularly important in achieving treatment outcomes in type 2 diabetes mellitus (T2DM).

objectiveThis study examined the effect of personalized text messages on physical activity, as measured by a pedometer, and clinical outcomes in a diverse population of patients with T2DM.

methodsText to Move (TTM) incorporates physical activity monitoring and coaching to provide automated and personalized text messages to help patients with T2DM achieve their physical activity goals. A total of 126 English- or Spanish-speaking patients with glycated hemoglobin A

resultsAll participants (intervention: n=64; control: n=62) were included in the analyses. The intervention group had significantly higher monthly step counts in the third (risk ratio [RR] 4.89, 95% CI 1.20 to 19.92, P=.03) and fourth (RR 6.88, 95% CI 1.21 to 39.00, P=.03) months of the study compared to the control group. However, over the 6-month follow-up period, monthly step counts did not differ statistically by group (intervention group: 9092 steps; control group: 3722 steps; RR 2.44, 95% CI 0.68 to 8.74, P=.17). HbA

conclusionPersonalized text messaging can be used to improve outcomes in patients with T2DM by employing optimal patient engagement measures.

Indexed as

Cell PhoneText MessagingDiabetes Mellitus, Type 2ExerciseFemaleHumansMaleMiddle AgedTreatment Outcomeengagementmobile phonespedometersphysical activitytext messagingtype 2 diabetes

Identifiers

PMID27864165
PMCPMC5135731
OpenAlexW2550584327

What OpenQuestion 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 OpenQuestion graph.