<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="letter"><front><journal-meta><journal-id journal-id-type="nlm-ta">J Med Internet Res</journal-id><journal-id journal-id-type="publisher-id">jmir</journal-id><journal-id journal-id-type="index">1</journal-id><journal-title>Journal of Medical Internet Research</journal-title><abbrev-journal-title>J Med Internet Res</abbrev-journal-title><issn pub-type="epub">1438-8871</issn><publisher><publisher-name>JMIR Publications</publisher-name><publisher-loc>Toronto, Canada</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">v27i1e80794</article-id><article-id pub-id-type="doi">10.2196/80794</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Letter</subject></subj-group></article-categories><title-group><article-title>Engagement With Text Messaging Improves Cardiovascular Medication Adherence: Secondary Analysis of a Randomized Controlled Trial</article-title></title-group><contrib-group><contrib contrib-type="author"><name name-style="western"><surname>Shore-Plavec</surname><given-names>Rowan</given-names></name><degrees>PSM</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>Zucker</surname><given-names>Rachel</given-names></name><degrees>MPH</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Glorioso</surname><given-names>Thomas J</given-names></name><degrees>MS</degrees><xref ref-type="aff" rid="aff3">3</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Bull</surname><given-names>Sheana</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff4">4</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Allen</surname><given-names>Larry A</given-names></name><degrees>MD, MHS</degrees><xref ref-type="aff" rid="aff5">5</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Saseen</surname><given-names>Joseph J</given-names></name><degrees>PharmD</degrees><xref ref-type="aff" rid="aff6">6</xref><xref ref-type="aff" rid="aff7">7</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Trinkley</surname><given-names>Katy E</given-names></name><degrees>PharmD</degrees><xref ref-type="aff" rid="aff6">6</xref><xref ref-type="aff" rid="aff7">7</xref><xref ref-type="aff" rid="aff8">8</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Peterson</surname><given-names>Pamela</given-names></name><degrees>MD, MSPH</degrees><xref ref-type="aff" rid="aff5">5</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Waughtal</surname><given-names>Joy</given-names></name><degrees>MPH</degrees><xref ref-type="aff" rid="aff8">8</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Ho</surname><given-names>P Michael</given-names></name><degrees>MD, PhD</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib></contrib-group><aff id="aff1"><institution>College of Natural Sciences and Mathematics, University of Denver</institution><addr-line>Denver</addr-line><addr-line>CO</addr-line><country>United States</country></aff><aff id="aff2"><institution>Institute for Health Research, Kaiser Permanente Colorado</institution><addr-line>16601 East Centretech Parkway</addr-line><addr-line>Aurora</addr-line><addr-line>CO</addr-line><country>United States</country></aff><aff id="aff3"><institution>Clinical Assessment, Reporting, and Tracking Program, Office of Quality and Patient Safety, Veterans Health Administration</institution><addr-line>Washington, DC</addr-line><country>United States</country></aff><aff id="aff4"><institution>Clinic Chat LLC</institution><addr-line>Denver</addr-line><addr-line>CO</addr-line><country>United States</country></aff><aff id="aff5"><institution>Division of Cardiology, School of Medicine, University of Colorado Anschutz Medical Campus</institution><addr-line>Aurora</addr-line><addr-line>CO</addr-line><country>United States</country></aff><aff id="aff6"><institution>Department of Family Medicine, School of Medicine, University of Colorado Anschutz Medical Campus</institution><addr-line>Aurora</addr-line><addr-line>CO</addr-line><country>United States</country></aff><aff id="aff7"><institution>Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus</institution><addr-line>Aurora</addr-line><addr-line>CO</addr-line><country>United States</country></aff><aff id="aff8"><institution>Adult and Child Center for Outcomes Research and Delivery Science (ACCORDS), School of Medicine, University of Colorado Anschutz Medical Campus</institution><addr-line>Aurora</addr-line><addr-line>CO</addr-line><country>United States</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Coristine</surname><given-names>Andrew</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>Oluwole</surname><given-names>Odumbo</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>Omachonu</surname><given-names>Rebecca</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Rachel Zucker, MPH, Institute for Health Research, Kaiser Permanente Colorado, 16601 East Centretech Parkway, Aurora, CO, 80011, United States, 1 303-739-3595; <email>rachel.x.zucker@kp.org</email></corresp></author-notes><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>24</day><month>11</month><year>2025</year></pub-date><volume>27</volume><elocation-id>e80794</elocation-id><history><date date-type="received"><day>16</day><month>07</month><year>2025</year></date><date date-type="rev-recd"><day>24</day><month>10</month><year>2025</year></date><date date-type="accepted"><day>24</day><month>10</month><year>2025</year></date></history><copyright-statement>&#x00A9; Rowan Shore-Plavec, Rachel Zucker, Thomas J Glorioso, Sheana Bull, Larry A Allen, Joseph J Saseen, Katy E Trinkley, Pamela Peterson, Joy Waughtal, P Michael Ho. Originally published in the Journal of Medical Internet Research (<ext-link ext-link-type="uri" xlink:href="https://www.jmir.org">https://www.jmir.org</ext-link>), 24.11.2025. </copyright-statement><copyright-year>2025</copyright-year><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://www.jmir.org/">https://www.jmir.org/</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://www.jmir.org/2025/1/e80794"/><abstract><p>We conducted this secondary analysis to assess whether greater engagement with a text messaging intervention was associated with improved cardiovascular medication adherence at 12 months.</p><sec sec-type="registered-report"><title>International Registered Report Identifier (IRRID)</title><p>RR2-10.1186/s13063-021-05453-9</p></sec></abstract><kwd-group><kwd>cardiovascular disease</kwd><kwd>medication adherence</kwd><kwd>texting</kwd><kwd>interactive chatbot</kwd><kwd>behavioral nudges</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>Medication nonadherence remains a significant barrier to the optimal management of chronic cardiovascular diseases, leading to increased morbidity and health care costs [<xref ref-type="bibr" rid="ref1">1</xref>]. Digital interventions, particularly text-based nudges, are potential strategies for enhancing medication adherence [<xref ref-type="bibr" rid="ref2">2</xref>-<xref ref-type="bibr" rid="ref5">5</xref>]. The Nudge study (NCT 03973931) compared the effectiveness of three different text-based interventions versus usual care to improve medication adherence among patients with documented medication refill gaps (time between medication supply end and the next refill) [<xref ref-type="bibr" rid="ref6">6</xref>]. There was no difference in adherence (assessed by proportion of days covered [PDC]) at 12 months between any of the intervention groups and usual care [<xref ref-type="bibr" rid="ref6">6</xref>].</p><p>While the main Nudge study results were null [<xref ref-type="bibr" rid="ref6">6</xref>], prior studies suggest patient engagement in mHealth interventions is critical to their success [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref7">7</xref>,<xref ref-type="bibr" rid="ref8">8</xref>]. We conducted this secondary analysis to assess whether greater engagement with the text messaging interventions was associated with improved medication adherence at 12 months. We hypothesized that patients who replied to study texts would have higher medication adherence defined by a shorter gap length between medication refills and higher refill adherence.</p></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Ethical Considerations</title><p>The study was deemed minimal risk, and a waiver of consent was obtained from the Colorado Multiple Institutional Review Board (18&#x2010;2779). A deidentified dataset was used for the current analyses. Patients were not compensated to participate in the study.</p></sec><sec id="s2-2"><title>Study Overview</title><p>Details of the main Nudge study have been previously described, including the inclusion and exclusion criteria [<xref ref-type="bibr" rid="ref1">1</xref>]. For secondary analyses, we restricted the cohort to patients randomized to text messaging arms in the study. During the intervention period, patients receiving study texts could respond: (1) &#x201C;STOP&#x201D; to opt-out of the study; (2) &#x201C;DONE&#x201D; if medication had been refilled; (3) numeric response in reply to a chatbot question; or (4) free text response. We categorized patient engagement into four mutually exclusive groups: (1) &#x201C;Opt-out Response&#x201D; for &#x201C;STOP;&#x201D; (2) &#x201C;Other Response&#x201D; for any non&#x2010;standard, free text reply (&#x201C;<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>); (3) &#x201C;Standard Response&#x201D; for standard replies like &#x201C;DONE&#x201D; or a numeric response; and (4) &#x201C;No response&#x201D; for patients who did not reply to any messages.</p><p>Differences between groups were tested using ANOVA for continuous variables and multiple degree of freedom chi-squared tests for categorical variables (<xref ref-type="table" rid="table1">Table 1</xref>). Adjusted PDC differences between responders and nonresponders were estimated using a Generalized Estimating Equation model with an identity link and independent covariance, adjusting for the treatment arm and relevant patient characteristics (<xref ref-type="table" rid="table1">Table 1</xref>). The median unadjusted gap lengths (calculated as the number of days from the end of medication supply to the subsequent refill) with interquartile ranges were calculated for initial enrollment gaps using Kaplan-Meier estimates. Unadjusted gap lengths and the 1-year PDC by response status were reported along with adjusted estimates of differences in PDC relative to those without a response. Analyses were performed using R software (version 4.4.1; R Foundation for Statistical Computing), with &#x03B1;=.05.</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Patient demographics, clinical characteristics and study assignment across response groups.</p></caption><table id="table1" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Variable</td><td align="left" valign="bottom" colspan="4">Counts of type of response</td><td align="left" valign="bottom"><italic>P</italic> value</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">No (n=3686)</td><td align="left" valign="bottom">Opt-out (n=456)</td><td align="left" valign="bottom">Other (n=843)</td><td align="left" valign="bottom">Standard (n=1963)</td><td align="left" valign="bottom"/></tr></thead><tbody><tr><td align="left" valign="top">Study arm, n (%)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">&#x2003; Generic</td><td align="left" valign="top">1395 (38)</td><td align="left" valign="top">155 (34)</td><td align="left" valign="top">233 (28)</td><td align="left" valign="top">541 (28)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; Behavioral</td><td align="left" valign="top">1184 (32)</td><td align="left" valign="top">139 (30)</td><td align="left" valign="top">251 (30)</td><td align="left" valign="top">731 (37)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003;Behavioral + Chatbot</td><td align="left" valign="top">1107 (30)</td><td align="left" valign="top">162 (36)</td><td align="left" valign="top">359 (42)</td><td align="left" valign="top">691 (35)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">Health care system, n (%)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">&#x2003; Denver Health</td><td align="left" valign="top">3083 (84)</td><td align="left" valign="top">277 (61)</td><td align="left" valign="top">668 (79)</td><td align="left" valign="top">1314 (67)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; UCHealth</td><td align="left" valign="top">290 (8)</td><td align="left" valign="top">100 (22)</td><td align="left" valign="top">53 (6)</td><td align="left" valign="top">261 (13)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003;Veterans Affairs</td><td align="left" valign="top">313 (8)</td><td align="left" valign="top">79 (17)</td><td align="left" valign="top">122 (15)</td><td align="left" valign="top">388 (20)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">Demographics</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; Age, mean (SD)</td><td align="left" valign="top">59.9 (12.9)</td><td align="left" valign="top">62.9 (13.2)</td><td align="left" valign="top">59.5 (11.2)</td><td align="left" valign="top">59.9 (12.7)</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">&#x2003; Female, (n) %</td><td align="left" valign="top">1732 (47)</td><td align="left" valign="top">189 (41)</td><td align="left" valign="top">413 (49)</td><td align="left" valign="top">929 (47)</td><td align="left" valign="top">.07</td></tr><tr><td align="left" valign="top">&#x2003; Race, n (%)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top">.01</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; American Indian or Alaska Native</td><td align="left" valign="top">37 (1)</td><td align="left" valign="top">5 (1)</td><td align="left" valign="top">12 (1)</td><td align="left" valign="top">18 (1)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Asian</td><td align="left" valign="top">50 (1)</td><td align="left" valign="top">1 (1)</td><td align="left" valign="top">7 (1)</td><td align="left" valign="top">23 (1)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Black or African American</td><td align="left" valign="top">636 (17)</td><td align="left" valign="top">47 (10)</td><td align="left" valign="top">137 (16)</td><td align="left" valign="top">305 (16)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Native Hawaiian/Pacific Islander</td><td align="left" valign="top">7 (1)</td><td align="left" valign="top">0 (0)</td><td align="left" valign="top">0 (0)</td><td align="left" valign="top">4 (1)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; White</td><td align="left" valign="top">2522 (68)</td><td align="left" valign="top">362 (79)</td><td align="left" valign="top">579 (69)</td><td align="left" valign="top">1339 (70)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Multiple</td><td align="left" valign="top">20 (1)</td><td align="left" valign="top">4 (1)</td><td align="left" valign="top">6 (1)</td><td align="left" valign="top">10 (1)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Unknown</td><td align="left" valign="top">414 (11)</td><td align="left" valign="top">37 (8)</td><td align="left" valign="top">102 (12)</td><td align="left" valign="top">204 (10)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; Ethnicity, n (%)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Hispanic</td><td align="left" valign="top">1904 (51)</td><td align="left" valign="top">0150 (33)</td><td align="left" valign="top">470 (56)</td><td align="left" valign="top">891 (45)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Non-Hispanic</td><td align="left" valign="top">1759 (48)</td><td align="left" valign="top">302 (66)</td><td align="left" valign="top">367 (43)</td><td align="left" valign="top">1051 (54)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Unknown</td><td align="left" valign="top">23 (1)</td><td align="left" valign="top">4 (1)</td><td align="left" valign="top">6 (1)</td><td align="left" valign="top">21 (1)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content> Spanish speaking, n (%)</td><td align="left" valign="top">1033 (28)</td><td align="left" valign="top">70 (15)</td><td align="left" valign="top">335 (4)</td><td align="left" valign="top">513 (26)</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">&#x2003; Marital status, n (%)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Married</td><td align="left" valign="top">1430 (38)</td><td align="left" valign="top">200 (44)</td><td align="left" valign="top">375 (44)</td><td align="left" valign="top">909 (46)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Single</td><td align="left" valign="top">1545 (42)</td><td align="left" valign="top">156 (34)</td><td align="left" valign="top">288 (34)</td><td align="left" valign="top">647 (33)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Divorced/Widowed</td><td align="left" valign="top">693 (19)</td><td align="left" valign="top">97 (21)</td><td align="left" valign="top">177 (21)</td><td align="left" valign="top">383 (20)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Unknown</td><td align="left" valign="top">18 (1)</td><td align="left" valign="top">3 (1)</td><td align="left" valign="top">3 (1)</td><td align="left" valign="top">24 (1)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; Insurance, n (%)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Medicare</td><td align="left" valign="top">1446 (39)</td><td align="left" valign="top">213 (47)</td><td align="left" valign="top">274 (32)</td><td align="left" valign="top">658 (33)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Medicaid</td><td align="left" valign="top">1141 (31)</td><td align="left" valign="top">90 (20)</td><td align="left" valign="top">212 (25)</td><td align="left" valign="top">477 (24)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Commercial</td><td align="left" valign="top">649 (17)</td><td align="left" valign="top">75 (16)</td><td align="left" valign="top">239 (28)</td><td align="left" valign="top">471 (24)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003;Veterans Affairs</td><td align="left" valign="top">9 (1)</td><td align="left" valign="top">3 (1)</td><td align="left" valign="top">1 (1)</td><td align="left" valign="top">10 (1)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; None</td><td align="left" valign="top">299 (8)</td><td align="left" valign="top">36 (8)</td><td align="left" valign="top">87 (10)</td><td align="left" valign="top">209 (11)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; Unknown</td><td align="left" valign="top">142 (4)</td><td align="left" valign="top">39 (8)</td><td align="left" valign="top">30 (4)</td><td align="left" valign="top">138 (7)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; At least 1 interactive voice response<break/>&#x2003;message, n (%)</td><td align="left" valign="top">273 (7)</td><td align="left" valign="top">57 (12)</td><td align="left" valign="top">17 (2)</td><td align="left" valign="top">269 (14)</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">Qualifying condition(s)<sup><xref ref-type="table-fn" rid="table1fn1">a</xref></sup>, n (%)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; Atrial fibrillation</td><td align="left" valign="top">206 (6)</td><td align="left" valign="top">41 (9)</td><td align="left" valign="top">40 (5)</td><td align="left" valign="top">127 (6)</td><td align="left" valign="top">.01</td></tr><tr><td align="left" valign="top">&#x2003;Coronary artery disease</td><td align="left" valign="top">537 (15)</td><td align="left" valign="top">80 (18)</td><td align="left" valign="top">93 (11)</td><td align="left" valign="top">272 (14)</td><td align="left" valign="top">.01</td></tr><tr><td align="left" valign="top">&#x2003; Diabetes mellitus</td><td align="left" valign="top">1883 (51)</td><td align="left" valign="top">229 (50)</td><td align="left" valign="top">438 (52)</td><td align="left" valign="top">924 (47)</td><td align="left" valign="top">.02</td></tr><tr><td align="left" valign="top">&#x2003;Hyperlipidemia</td><td align="left" valign="top">1634 (44)</td><td align="left" valign="top">246 (54)</td><td align="left" valign="top">382 (45)</td><td align="left" valign="top">951 (48)</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">&#x2003;Hypertension</td><td align="left" valign="top">2922 (79)</td><td align="left" valign="top">367 (8)</td><td align="left" valign="top">657 (78)</td><td align="left" valign="top">1541 (79)</td><td align="left" valign="top">.65</td></tr><tr><td align="left" valign="top">Medical history, n (%)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003;Congestive heart failure</td><td align="left" valign="top">298 (8)</td><td align="left" valign="top">39 (9)</td><td align="left" valign="top">52 (6)</td><td align="left" valign="top">133 (7)</td><td align="left" valign="top">.10</td></tr><tr><td align="left" valign="top">&#x2003;Chronic kidney disease</td><td align="left" valign="top">355 (10)</td><td align="left" valign="top">39 (9)</td><td align="left" valign="top">61 (7)</td><td align="left" valign="top">141 (7)</td><td align="left" valign="top">.01</td></tr><tr><td align="left" valign="top">&#x2003;Cardiovascular disease</td><td align="left" valign="top">244 (7)</td><td align="left" valign="top">32 (7)</td><td align="left" valign="top">40 (5)</td><td align="left" valign="top">96 (5)</td><td align="left" valign="top">.02</td></tr><tr><td align="left" valign="top">&#x2003; Depression</td><td align="left" valign="top">675 (18)</td><td align="left" valign="top">88 (19)</td><td align="left" valign="top">164 (19)</td><td align="left" valign="top">399 (20)</td><td align="left" valign="top">.32</td></tr><tr><td align="left" valign="top">&#x2003; Prior myocardial infarction</td><td align="left" valign="top">185 (5)</td><td align="left" valign="top">23 (5)</td><td align="left" valign="top">34 (4)</td><td align="left" valign="top">83 (4)</td><td align="left" valign="top">.43</td></tr><tr><td align="left" valign="top">&#x2003; Prior revascularization</td><td align="left" valign="top">100 (3)</td><td align="left" valign="top">21 (5)</td><td align="left" valign="top">22 (3)</td><td align="left" valign="top">46 (2)</td><td align="left" valign="top">.07</td></tr><tr><td align="left" valign="top">&#x2003;Posttraumatic stress disorder</td><td align="left" valign="top">144 (4)</td><td align="left" valign="top">26 (6)</td><td align="left" valign="top">47 (6)</td><td align="left" valign="top">117 (6)</td><td align="left" valign="top">&#x003C;.01</td></tr><tr><td align="left" valign="top">&#x2003; Substance abuse</td><td align="left" valign="top">170 (5)</td><td align="left" valign="top">21 (5)</td><td align="left" valign="top">39 (5)</td><td align="left" valign="top">76 (4)</td><td align="left" valign="top">.61</td></tr><tr><td align="left" valign="top">Baseline medication class, % (n)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; Active class</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top">.04</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; 1</td><td align="left" valign="top">917 (25)</td><td align="left" valign="top">97 (21)</td><td align="left" valign="top">192 (23)</td><td align="left" valign="top">522 (26)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; 2</td><td align="left" valign="top">876 (24)</td><td align="left" valign="top">115 (25)</td><td align="left" valign="top">210 (25)</td><td align="left" valign="top">586 (26)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; 3+</td><td align="left" valign="top">1893 (51)</td><td align="left" valign="top">244 (54)</td><td align="left" valign="top">441 (52)</td><td align="left" valign="top">935 (48)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; Study class</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; 1</td><td align="left" valign="top">2467 (67)</td><td align="left" valign="top">345 (76)</td><td align="left" valign="top">588 (70)</td><td align="left" valign="top">1433 (73)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; 2</td><td align="left" valign="top">770 (21)</td><td align="left" valign="top">70 (15)</td><td align="left" valign="top">167 (20)</td><td align="left" valign="top">361 (18)</td><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x2003; 3+</td><td align="left" valign="top">449 (12)</td><td align="left" valign="top">41 (9)</td><td align="left" valign="top">88 (10)</td><td align="left" valign="top">169 (9)</td><td align="left" valign="top"/></tr></tbody></table><table-wrap-foot><fn id="table1fn1"><p><sup>a</sup>This number exceeds 100% due to the fact that one patient can have more than one qualifying condition(s) for this study.</p></fn></table-wrap-foot></table-wrap></sec></sec><sec id="s3" sec-type="results"><title>Results</title><p>A total of 9501 patients were enrolled; 9269 had complete follow-up data (the CONSORT diagram has been published previously [<xref ref-type="bibr" rid="ref6">6</xref>]). After excluding 2321 usual care patients, we analyzed 6948 individuals; 3262 (46.9%) responded to an intervention message. Among the 3262 responders, 456 (14%) opted out, 843 (25.8%) provided other responses and 1963 (60.2%) provided standard responses. Patients who engaged with the messages, particularly standard responders, differed significantly from nonresponders, with engagement more likely among those in certain health care systems or on fewer medications (<xref ref-type="table" rid="table1">Table 1</xref>).</p><p>Patients who engaged with the texts, regardless of response type, had a shorter gap length compared to patients who did not respond. In addition, patients who responded to any messages had a higher adherence at 12 months, which persisted after the adjustment for demographics and clinical characteristics (<xref ref-type="table" rid="table2">Table 2</xref>).</p><table-wrap id="t2" position="float"><label>Table 2.</label><caption><p>Initial gap length and 1-year medication adherence (proportion of days covered; PDC) by patient response type.</p></caption><table id="table2" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Patient response type</td><td align="left" valign="bottom" colspan="2">Unadjusted</td><td align="left" valign="bottom" colspan="3">Adjusted</td></tr><tr><td align="left" valign="top">&#x2003;</td><td align="left" valign="top">Initial gap length in days, median (IQR)</td><td align="left" valign="top">1-year PDC</td><td align="left" valign="top">Difference in PDC</td><td align="left" valign="top">95% CI</td><td align="left" valign="top"><italic>P</italic> value</td></tr></thead><tbody><tr><td align="left" valign="top">Response</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; No response (Ref)</td><td align="left" valign="top">16 (1-109)</td><td align="left" valign="top">55.9</td><td align="left" valign="top">&#x2014;<sup><xref ref-type="table-fn" rid="table2fn1">a</xref></sup></td><td align="left" valign="top">&#x2014;</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top">&#x2003; Any response</td><td align="left" valign="top">7 (1-29)</td><td align="left" valign="top">71</td><td align="left" valign="top">15.2</td><td align="left" valign="top">13.7-16.8</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">Sub-groups (Ref: No response)</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top">&#x2003; Opt-out</td><td align="left" valign="top">8 (1-41)</td><td align="left" valign="top">67.5</td><td align="left" valign="top">9.6</td><td align="left" valign="top">6.1-13.1</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">&#x2003; Other</td><td align="left" valign="top">7 (1-32)</td><td align="left" valign="top">70</td><td align="left" valign="top">14.5</td><td align="left" valign="top">12.2-16.7</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">&#x2003; Standard</td><td align="left" valign="top">7 (1-25)</td><td align="left" valign="top">72.1</td><td align="left" valign="top">16.6</td><td align="left" valign="top">14.9-18.4</td><td align="left" valign="top">&#x003C;.001</td></tr></tbody></table><table-wrap-foot><fn id="table2fn1"><p><sup>a</sup>not applicable.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><p>This secondary analysis assessed the association between engagement and medication adherence in a text messaging clinical trial. We enrolled a diverse patient population including a large proportion of Hispanic and Spanish-speaking patients as well as patients who are traditionally medically underserved (ie, receiving care at federally qualified health centers and veterans affairs centers). Overall, 47% of intervention arm patients engaged with texts. Any engagement was associated with shorter medication gap lengths, and higher medication adherence at 12 months. While our participants included diverse and traditionally underserved patients, these findings may not be generalizable to patients without access to or comfort with text messaging, who would have been ineligible for the parent trial.</p><p>Another potential limitation lies in our response classification criteria. Patients who submitted nonstandard responses were placed exclusively in the &#x201C;Other Response&#x201D; group, which may conflate ambiguous interactions with more meaningful engagement. Furthermore, we cannot determine causality between engagement and adherence given this post-hoc analysis.</p><p>Our findings are consistent with prior literature highlighting the importance of patient engagement in mHealth interventions to improve adherence and self-management [<xref ref-type="bibr" rid="ref2">2</xref>-<xref ref-type="bibr" rid="ref5">5</xref>]. Collectively, these findings suggest that patient engagement is a strong marker for, and is closely associated with, higher medication adherence.</p></sec></body><back><ack><p>This work received logistical and technical support from the NIH Pragmatic Trials Collaboratory Coordinating Center through cooperative agreement U24AT009676 from the National Center for Complementary and Integrative Health (NCCIH), National Institute of Allergy and Infectious Diseases (NIAID), National Cancer Institute (NCI), National Institute on Aging (NIA), National Heart, Lung, and Blood Institute (NHLBI), National Institute of Nursing Research (NINR), National Institute of Minority Health and Health Disparities (NIMHD), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), NIH Office of Behavioral and Social Sciences Research (OBSSR), and NIH Office of Disease Prevention (ODP). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NHLBI or the NCCIH, NIAID, NCI, NIA, NINR, NIMHD, NIAMS, OBSSR, or ODP, or the NIH. No generative AI was used in any portion of the manuscript generation.</p></ack><notes><sec><title>Funding</title><p>This work was supported within the National Institutes of Health (NIH) Pragmatic Trials Collaboratory by cooperative agreement UG3HL168504 from the National Heart, Lung, and Blood Institute (NHLBI).</p></sec><sec><title>Data Availability</title><p>The datasets generated or analyzed during this study are available from the corresponding author on reasonable request.</p></sec></notes><fn-group><fn fn-type="con"><p>Conceptualization: SB, MH, LA, JS, KT and PP</p><p>Data curation: TG</p><p>Formal analysis: TG</p><p>Funding acquisition: SB and MH</p><p>Methodology: SB, MH, LA, JS, KT and PP</p><p>Project administration: JW</p><p>Writing &#x2013; original draft: RSP and RZ</p><p>Writing &#x2013; review &#x0026; editing: SB, MH, LA, JS, KT, PP, and JW</p></fn><fn fn-type="conflict"><p>SB is the President and a Co-Founder of Clinic Chat, LLC, the company that developed and 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