Evidence mapPaperPMID 41528767Full record

ArticleJMIR formative research2026

Developing a Customizable Texting Intervention for Diabetes Self-Management: Participatory Design Approach.

Stephanie A Robinson, Popy Shell, Linda Am, Courtney L Bilodeau, Howard S Gordon, Constance R Uphold, Varsha G Vimalananda, Sarah L Cutrona, Timothy P Hogan, Bridget Smith and 1 more

Abstract read
In one paragraph

Article in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Stephanie A RobinsonCenter for Health Optimization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-1352-217X
Popy ShellMalcolm Randall Department of Veterans Affairs Medical Center, Gainseville, FL, United States.ORCID https://orcid.org/0000-0002-1519-4632
Linda AmCenter for Health Optimization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-4775-1763
Courtney L BilodeauCenter for Health Optimization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0009-0009-8403-6732
Howard S GordonJesse Brown Department of Veterans Affairs Medical Center, Chicago, IL, United States.ORCID https://orcid.org/0000-0002-6712-5954
Constance R UpholdMalcolm Randall Department of Veterans Affairs Medical Center, Gainseville, FL, United States.ORCID https://orcid.org/0000-0001-5230-6480
Varsha G VimalanandaCenter for Health Optimization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0003-0738-672X
Sarah L CutronaCenter for Health Optimization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-4795-8377
Timothy P HoganCenter for Health Optimization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-6888-0927
Bridget SmithVA Hines Healthcare System, US Department of Veterans Affairs, Hines, IL, United States.ORCID https://orcid.org/0000-0002-3301-8843
Stephanie L ShimadaCenter for Health Optimization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-6517-5122

Funding

HSRD VA I01 HX002477HSRD VA IK2 HX003532
6 · The paper itself

Abstract

backgroundUncontrolled diabetes contributes to serious comorbidities and mortality. Effective self-management can improve outcomes, though barriers such as limited education and support often prevent patients from engaging in such behaviors. Automated texting systems show promise to deliver diabetes self-management education as they are accessible and scalable. Furthermore, customizing these systems may further enhance patient engagement compared to standard, one-size-fits-all approaches. However, such customization is more resource-intensive, and it remains unclear whether the added effort meaningfully enhances diabetes self-management and outcomes.

objectiveThis study aimed to describe the development of 2 versions of an automated texting system intervention for diabetes self-management: (1) a standard, education-only intervention (Diabetes Self-Management Support; DSMS) and (2) an interactive, customizable intervention (Diabetes Self-Management Support + Interactive and Customizable Messages; DSMS+).

methodsTwo versions of an automated texting system intervention were developed using a participatory design approach that incorporated input from veterans and expert clinicians. Message content was refined through feedback from a multidisciplinary team, veteran coinvestigators, national surveys, interviews, clinical expert panel reviews, and beta testing. Surveys were mailed to 1000 potential participants, oversampling rural, low-income, minority, and female participants. Respondents rated message relevance and provided preferences for content, timing, and frequency. Interviews provided customization preferences. A clinical expert panel reviewed all messages for safety and appropriateness. Beta testing informed final refinements.

resultsNinety-two surveys were completed (9.2% response rate). Respondents rated 62% of the messages as personally relevant and 61% confidence-enhancing. Interviews with 23 respondents revealed a preference for 1-2 texts per day, emphasizing topics such as healthy eating and weight management. The clinical expert panel reviewed 536 messages, flagging 81 for revision. Beta testing confirmed feasibility and informed refinements to clarity and timing. The 2 resulting interventions were built in the US Department of Veterans Affairs' automated texting system, Annie.

conclusionsTwo text messaging interventions, DSMS and DSMS+, were developed to support diabetes self-management among US veterans. DSMS delivers standard educational content, while DSMS+ incorporates interactive features and personalization. The subsequent clinical trial will assess whether customization enhances engagement and improves diabetes outcomes, providing insights into the potential of tailored mobile health interventions for chronic disease management.

Indexed as

Diabetes MellitusSelf-ManagementText MessagingAdherence InterventionsFemaleHumansMaleMiddle AgedPatient Education as Topicmobile phoneself-managementtext messagingtype 2 diabetesveterans

Identifiers

PMID41528767
PMCPMC12848483

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.