Evidence map›Paper›PMID 28005532›Full record

ArticlePreventing chronic disease2016

Designing a Text Messaging Intervention to Improve Physical Activity Behavior Among Low-Income Latino Patients With Diabetes: A Discrete-Choice Experiment, Los Angeles, 2014-2015.

Magaly Ramirez, Shinyi Wu, Elizabeth Beale

Registry-linked trialOpen access · diamondAbstract read
In one paragraph

Article in Preventing chronic disease, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06411769 (Evidence-based Intervention to Improve Walking Engagement in El Paso, Texas), which is not on this map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
5.8field-weighted citation impact, top 4% 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.

NCT06411769 narecruitingnot on this mapstarted 2024, after this paper: background citation

Evidence-based Intervention to Improve Walking Engagement in El Paso, Texas

TypeinterventionalSponsorUniversity of Texas, El PasoRan2024 to 2027Enrolled406ConditionsActivity Trackers, Physical ActivityArms50K4LIfe, SMS Text Messaging, Individual, School
3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. UsingProgress in community health partnerships : research, education, and action · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Pilot of interactive texting for diabetes self-management education and support.Journal of the American Pharmacists Association : JAPhA
    Article
  19. 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

3 authors at 2 institutions in 1 country.

Magaly RamirezFielding School of Public Health, Department of Health Policy and Management, University of California, Los Angeles, 650 Charles Young Dr S, 31-269 CHS Box 951772, Los Angeles, CA 90095-1772. Email: ramirezma@ucla.edu.
Shinyi WuSchool of Social Work and Viterbi School of Engineering, University of Southern California, Los Angeles, California.
Elizabeth BealeDivision of Endocrinology, Diabetes and Metabolism, Keck School of Medicine, University of Southern California, Los Angeles, California. Dr Ramirez was affiliated with the Viterbi School of Engineering, University of Southern California, Los Angeles, California, when the research was conducted.
University of California, Los Angeles · USUniversity of Southern California · US

Funding

Secondary Stroke prevention by Uniting Community and Chronic care model teams Early to End Disparities: the SUCCEED TrialU54NS081764 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SARKISIAN, CATHERINE A · 2012 to 2016
$11.3M
NINDS NIH HHS U54 NS081764
6 · The paper itself

Abstract

introductionAutomated text messaging can deliver self-management education to activate self-care behaviors among people with diabetes. We demonstrated how a discrete-choice experiment was used to determine the features of a text-messaging intervention that are important to urban, low-income Latino patients with diabetes and that could support improvement in their physical activity behavior.

methodsIn a discrete-choice experiment from December 2014 through August 2015 we conducted a survey to elicit information on patient preferences for 5 features of a text-messaging intervention. We described 2 hypothetical interventions and in 7 pairwise comparisons asked respondents to indicate which they preferred. Respondents (n = 125) were recruited in person from a diabetes management program of a safety-net ambulatory care clinic in Los Angeles; clinicians referred patients to the research assistant after routine clinic visits. Data were analyzed by using conditional logistic regression.

resultsWe found 2 intervention features that were considered by the survey respondents to be important: 1) the frequency of text messaging and 2) physical activity behavior-change education (the former being more important than the latter). Physical activity goal setting, feedback on physical activity performance, and social support were not significantly important.

conclusionA discrete-choice experiment is a feasible way to elicit information on patient preferences for a text-messaging intervention designed to support behavior change. However, discrepancies may exist between patients' stated preferences and their actual behavior. Future research should validate and expand our findings.

Indexed as

ExerciseAdultDiabetes MellitusFemaleHealth BehaviorHealth PromotionHispanic or LatinoHumansLogistic ModelsLos AngelesMaleMiddle AgedPatient PreferencePovertySafety-net ProvidersSelf Care

Identifiers

PMID28005532
PMCPMC5201152
OpenAlexW2565942298

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.