Dulce Digital: An mHealth SMS-Based Intervention ImprovesGlycemic Control in HispanicsWith Type 2 DiabetesDiabetes Care 2017;40:1349–1355 | https://doi.org/10.2337/dc17-0230

OBJECTIVE

Type 2 diabetes is growing in epidemic proportions and disproportionately affectslower-income, diverse communities. Text messaging may provide one of the mostrapid methods to overcome the “digital divide” to improve care.

RESEARCH DESIGN AND METHODS

A randomized, nonblinded, parallel-groups clinical trial design allocatedN = 126 low-income, Hispanic participants with poorly controlled type 2 diabetes to receive theDulce Digital intervention or usual care (UC). Dulce Digital participants received up tothree motivational, educational, and/or call-to-action text messages per day over6 months. The primary outcome was HbA1c; lipids, blood pressure, and BMI weresecondary outcomes. Satisfaction and acceptability were evaluated via focus groupsand self-report survey items.

RESULTS

The majority of patients were middle-aged (mean age 48.43 years, SD 9.80), female(75%), born in Mexico (91%), and uninsured (75%) and reported less than a ninth-grade education level (73%) and mean baseline HbA1c 9.5% (80 mmol/mol), SD 1.3,and fasting plasmaglucose 187.17mg/dL, SD 64.75. A statistically significant time-by-group interaction effect indicated that theDulceDigital group achieved a significantlygreater reduction in HbA1c over time compared with UC (P = 0.03). No statisticallysignificant effects were observed for secondary clinical indicators. The number ofblood glucose values texted in by participants was a statistically significant predictorof month 6 HbA1c (P < 0.05). Satisfaction and acceptability ratings for the DulceDigital intervention were high.

CONCLUSIONS

Use of a simple, low-cost text messaging programwas found to be highly acceptablein this sample of high-risk, Hispanic individuals with type 2 diabetes and resulted ingreater improvement in glycemic control compared with UC.

Type 2 diabetes is growing in epidemic proportions in the U.S. and worldwide. TheInternational Diabetes Federation estimates that by 2040 there will be 642 millionpeople living with diabetes worldwide, an increase of.50% compared with the pre-sent day (1). The U.S. has the highest prevalence of diabetes among developed nations(i.e., 11% of the population between 20 and 79 years of age) (1), and individuals ofethnic/minority and low socioeconomic status are disproportionately affected (2,3). A

1Scripps Whittier Diabetes Institute, ScrippsHealth, San Diego, CA2Department of Psychology, San Diego StateUniversity, San Diego, CA3University of California, San Diego, San Diego,CA4Neighborhood Healthcare, San Diego, CA

Corresponding authors: Athena Philis-Tsimikas,tsimikas.athena@scrippshealth.org, Linda C.Gallo, lgallo@mail.sdsu.edu, and James Schultz,jims@nhcare.org.

Received 30 January 2017 and accepted 11 May2017.

Clinical trial reg. no. NCT01749176, clinicaltrials.gov.

This article contains Supplementary Data onlineat http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc17-0230/-/DC1.

© 2017 by the American Diabetes Association.Readers may use this article as long as the workis properly cited, the use is educational and notfor profit, and the work is not altered. More infor-mation is available at http://www.diabetesjournals.org/content/license.

See accompanying article, p. 1342.

Addie L. Fortmann,1 Linda C. Gallo,2

Maria Isabel Garcia,1 Mariam Taleb,1

Johanna A. Euyoque,1 Taylor Clark,1

Jessica Skidmore,1 Monica Ruiz,1

Sapna Dharkar-Surber,3 James Schultz,4

and Athena Philis-Tsimikas1

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recent study (4) in the 26 states and Dis-trict of Columbia that expandedMedicaidunder the Affordable Care Act found thatdiabetes diagnoses increased by 23% in2014 compared with the previous year.Hispanic individuals in the U.S. experiencehigher rates of type 2 diabetes and, oncediagnosed, exhibit poorer glycemic controlthan non-Hispanic white individuals (3,5).Diabetes self-management education

(DSME) and support is aneffectivemethodto improve clinical and cost outcomes (6,7)and can be successfully tailored for ethni-cally diverse populations (e.g., Philis-Tsimikas et al. [8]). However, many at-riskindividuals are unable to access DSMEand support because of practical (e.g.,work, transportation, caregiving) andhealth care access barriers (9–12). Infact, in 2012 only 4.7% of the 21 millionpeople with diagnosed diabetes accessedany accredited DSME program (9). To im-prove patient and practice performanceoutcomes, alternativemethods must effi-ciently and effectively extend the reach ofthe care team to those in need of addi-tional support to reach clinical targets.The widespread adoption of mobilephone technologies, including amonglow-income and older adults (13), high-lights the potential for mobile health(mHealth) technology to circumvent the

practical barriers inherent to traditional(e.g., face-to-face) visits.

Short messaging service (SMS), or textmessaging, is among the most frequentlyusedmobile communicationmethods andhas been adopted by an estimated three-quarters of mobile users worldwide (14).Text messaging is simple to implementand may provide one of the most rapidmethods to overcome the recently impli-cated limitationof the “digital divide” (15)to improve care. In theU.S., texting amongadults in 2011was higher amongHispanics(83%) and African Americans (76%) thanamong non-Hispanic whites (70%) (16).Ninety-nine percent of received text mes-sages are opened, and 90%are readwithin3min of receipt (17). Thus, textmessagingrepresents an opportunity to provide fre-quent, daily, low-cost, and interactivecommunication that could prove ben-eficial for population-level diabetesinterventions.

Recent research syntheses have shownthat mHealth interventions improve ad-herence and clinical control in patientswith type 2 diabetes (18–20). However,most studies were small and nonrandom-ized and resulted in limited clinical improve-ments (20–23). Further, few studies haveexamined the implications of integratingthese mHealth technologies into care or

the feasibility and acceptability of suchapproaches in underserved populations(19,24). The current study addressesthese gaps by investigating the glycemicbenefit and acceptability of a culturallytailored, SMS-based DSME and supportintervention (Dulce Digital) among under-served Hispanics with poor control in fed-erally qualified health centers in SouthernCalifornia.

RESEARCH DESIGN AND METHODS

Study Sample and SettingBetween October 2012 and February2014, 126 individuals consented and en-rolled into the Dulce Digital study (Fig. 1).The sample included Spanish-speakingand English-speaking Hispanic menand women, 18–75 years of age, whowere uninsured or underinsured (Medic-aid) and had type 2 diabetes and poorglycemic control (as indicated by anHbA1c level of $7.5% [58 mmol/mol]).Individuals with plans to move outsidethe region and those with a severe phys-ical or mental condition that would inter-fere with participation were excluded.Participants were recruited from clinicsites within Neighborhood Healthcare, anetwork of federally qualified health cen-ters in San Diego and Riverside countiesthat serves predominantly low-income

Figure 1—CONSORT flow diagram. appts, appointments.

1350 Texting Intervention in Hispanics With Diabetes Diabetes Care Volume 40, October 2017

individuals of an ethnic/racial minority.All procedures were approved by theScrippsHealth Institutional ReviewBoard.

Study Design and InterventionThe intervention was tested using aparallel-groups, nonblinded, randomizeddesign. Blocked random assignment withequal allocation was used to assign par-ticipants toDulceDigital or usual care (UC),using a randomly generated numberssequence. Participants were informedof group assignment after the baselineassessment.At the baseline visit, all participants

viewed a 15-min diabetes educationalvideo developed by Scripps. All partici-pants received a blood glucose meter(OneTouchVerioMeter; LifeScan, Inc.,Mil-pitas, CA), testing strips, and instructionson use. A physical assessment with fastingvenous blood draw and study question-naires were completed at baseline, month3, and month 6. Assessments were per-formed by trained, bilingual research assis-tants at clinic sites in English and Spanish.Participants received an incentive at eachassessment and continued to receiveUCatthe clinic for the study duration. UC ser-vices available to all patients included visitswith a primary care physician, certified di-abeteseducator, andgroupDSME,althoughthe use of the services was dependent onphysician and patient initiative.After randomization, participants as-

signed to Dulce Digital (n = 63) were pro-vided with instructions on how to receiveand send textmessages. Participants whodid not have a cell phone with textingcapability were provided one (Kajeet,Inc., McLean, VA) (n = 22) at no cost forthe duration of the study. Participants us-ing their own phones had the costs of theadditional texts covered by the study($12/month). Content for the text mes-sages was primarily derived from our cul-turally appropriate DSME curriculum(Project Dulce), which has been shownto improve clinical, behavioral, and costoutcomes in this population and others(8,25,26). In addition to the core educa-tional messages derived from ProjectDulce (e.g., “Use small plates! Portionswill look larger and you may feel more sat-isfied after eating.”), the Dulce Digital in-tervention provided ongoing support viamotivational messages (e.g., “It takes ateam! Get the support you needdfamily,friends and support groups can help youto succeed.”),medication reminders (e.g.,

“Tick, tock. Take your medication at thesame time every day!”), and blood glu-cose monitoring prompts (e.g., “Time tocheck your blood sugar. Please text backyour results.”). All content was convertedinto 119 brief,#160 character, text mes-sage–friendly format and sent out via acontracted patient health managementtechnology platform (Rip Road LLC, NewYork, NY). Two to three messages a daywere sent at study start, with frequencytapering over 6 months. Message timingwas standardized across all participantsand correlated with traditional meal ortesting times. Blood glucose–monitoringprompts encouraged participants to textmessage in their next observed value; onevalue$250or#70mg/dL or three valuesbetween 181 and 250 mg/dL prompteda bilingual study coordinator to call theparticipant to assess possible reasonsfor hyperglycemia/hypoglycemia and toencourage as-needed follow-up withproviders. The study coordinator alsocontacted the participant if there wasno blood glucose value sent in for1 week. Medical management was notprovided by the coordinator.

Demographic and Outcome MeasuresParticipants self-reported sociodemo-graphic characteristics. Information re-garding prescribed medications wasextracted from electronic health records.HbA1c and lipids (total cholesterol, LDLcholesterol, HDL cholesterol, and triglyc-erides) were conducted by the laborato-ries of Quest Diagnostics (West Hills, CA),which adhere to guidelines set forth bythe College of American Pathologists. Sys-tolic and diastolic blood pressure weremeasured with a standardized protocolaccording to guidelines using a standarddigital sphygmomanometer (HEM-907XL;Omron). Body weight and height weremeasured using a traditional balancescale and stadiometer to the nearest 0.1lb and 0.2 inch, respectively. Finally, DulceDigital participants (only) completed self-report items at the month 6 assessmentvisit to evaluate intervention feasibilityand acceptability. To obtain further detailregarding participants’ perceptions ofDulce Digital, two 90-min focus groupswere conductedwith a randomly selected20% of intervention group participants.

Statistical AnalysisData analysis was performed using IBMSPSS Statistics for Windows, version23.0 (IBM Corporation, Armonk, NY) and

Hierarchical Linear and Nonlinear Model-ing software (HLM7; Scientific SoftwareInternational, Lincolnwood, IL) by A.L.F.Descriptive statistics were obtained, anddistributions were examined for normal-ity. The triglyceride variable was signifi-cantly skewed as was the natural logtransformed to normalize the distribu-tion; however, because no appreciabledifferences between analyses using trans-formed versus untransformed variableswere observed, results are presented foruntransformed data only.

Mixed models were used to examinewhether the two groups evidenced differ-ential rates of change over time for HbA1cand secondary outcomes (i.e., time-by-group interactions). To evaluate a possi-ble dosage effect on the primary outcomein Dulce Digital, the number of text mes-sages and the number and duration ofstudy coordinator phone callswere exam-ined as predictors of month 6 HbA1c levelwhile controlling for baseline HbA1c level.All analyses controlled for age and sex.

RESULTS

Participant CharacteristicsThe majority of patients were middle-aged, female, born in Mexico, and unin-sured and reported less than aninth-gradeeducation (Table 1). At baseline, the over-all sample (N = 126) exhibited poor glyce-mic control (mean HbA1c 9.5% [80 mmol/mol], SD 1.3; fasting plasma glucose187.17 mg/dL, SD 64.75); mean lipid val-ues were close to target, and blood pres-sure averages were in the normal range.No between-group differences were ob-served in clinical outcomes at baseline(P values.0.10).

Thirteen (10.3%) participants were lostto follow-up (Fig. 1). At baseline, theseparticipants reported higher annual in-comes (P = 0.002) and were less likely toown a cell phone (P = 0.04) than thosewho completed at least one follow-upassessment; no other statistically signifi-cant differences were observed (P values.0.05).

Clinical Control OutcomesUsing an intent-to-treat approach, allN = 126 participants were included inmultilevel modeling analyses examiningdifferences in the rates of change overtime between the groups. Group meansfor all indicators at baseline,month 3, andmonth 6 are shown in Table 2. A statisti-cally significant time-by-group interaction

care.diabetesjournals.org Fortmann and Associates 1351

effect was observed for the primary out-come, HbA1c (P = 0.03), indicating thatDulce Digital exhibited greater improve-ment in glycemic control across timecompared with UC (Fig. 2A). The DulceDigital group exhibited a significantlylower mean HbA1c level compared withUC at both month 3 (8.5 6 1.2% [69.0 613.1 mmol/mol] vs. 9.3 6 1.9% [78.0 620.8 mmol/mol], P = 0.03) and month6 (8.5 6 1.2% [69.0 6 13.1 mmol/mol]vs. 9.4 6 2.0% [78.0 6 20.8 mmol/mol],P = 0.03), after controlling for baselineHbA1c. No significant time-by-group inter-action effects were observed for anyother clinical indicators. Because of signif-icant group differences in the number ofindividuals prescribed oral (P = 0.03) andinjectable (P = 0.02) antihyperglycemicagents at baseline (Table 1), these vari-ables were examined as covariates inHbA1c analyses. Neithermedication status

at baseline nor changes in medicationsover the 6-month period altered the re-sults. Further, the proportion of individu-als who received medication changesduring the study did not differ signifi-cantly between Dulce Digital (n = 37;51%) and UC (n = 32; 59%; P = 0.38).

Dosage-Effect AnalysesParticipants in the Dulce Digital interven-tion received an average of 354.17 textmessages (SD 44.94); variation is attribut-able to a small number of participants(n = 6)who chose to discontinue receivingtexts prior to the end of the study and toreceiving additional texts during the1-month window for completing the finalstudy visit. Participants textedback 3–352blood glucose values (mean 57.77 bloodglucose values, SD 60.01). The number ofblood glucose values texted in by partici-pants predictedmonth 6 HbA1c (P = 0.03);

with each additional blood glucose valuesent in, an additional 0.006 decrease inHbA1c level was observed at month6 (Fig. 2B). The number of text messagessent out to participants was not a signif-icant predictor of month 6 HbA1c levels(P = 0.28). Nineteen of 63 (30%) partici-pants in the Dulce Digital interventionreceived phone calls from the study coor-dinator in response to out-of-range bloodglucose values. For these n = 19 partici-pants, the number of coordinator phonecontacts ranged from 3 to 13 calls/participant (mean 7.63 calls, SD 2.81);the modal call duration was 5 min. Nei-ther the number nor the total duration ofcoordinator phone calls per participantpredicted month 6 HbA1c levels (P values.0.05).

Feasibility and AcceptabilityIn response to the subset of self-reportitems administered in the Dulce Digitalgroup (only) at month 6, the vastmajorityof participants indicated that the textmessages helped them to manage theirdiabetes “a lot” (96%), that they wouldcontinue receiving Dulce Digital text mes-sages if given the choice (96%), and thatthey would recommend Dulce Digital to afriend or family member with diabetes(97%). Consistent with these findings, fo-cus group participants (n = 12) indicatedhigh acceptability; common themes thatemerged indicated that text messageswere sufficient in frequency and easy tounderstand. However, individuals whowere provided with a separate studyphone reported that it was inconvenientto carry two phones.

CONCLUSIONS

To our knowledge, this is the first random-ized controlled trial using a text message–based DSME and support intervention todemonstrate significantly greater impro-vements in glycemic control comparedwith UC in a high-risk, underserved, His-panic population. These findings suggestthat, if implemented on a wider scale,simple, low-cost, text message–basedmHealth approaches such as Dulce Digitalhave the potential to achieve a significantpublic health benefit in diabetes, achronic health condition that is rapidly in-creasing in the Hispanic and other under-served populations.

In this study, all patients had an initialHbA1c level $7.5%, with the majority(61.9%) exhibiting an HbA1c level $9%,

Table 1—Baseline characteristics for the Dulce Digital and UC groups

Dulce Digital (n = 63) UC (n = 63)

Age, years, mean (SD) 47.8 (9.0) 49.1 (10.6)

SexFemale 46 (73) 48 (76)Male 17 (27) 15 (24)

Country of originMexico 59 (93) 55.0 (89)U.S. 2 (3) 4.0 (6)Other 2 (3) 3.0 (5)

Preferred LanguageSpanish 59 (94) 57 (91)English 4 (6) 6 (9)

Education§Less than ninth-grade education 46 (76) 44 (70)Ninth-grade education or higher 17 (24) 19 (30)

Insurance coverage§Insured 15 (24) 16 (25)Uninsured 48 (76) 47 (75)

Household monthly income§,$1,000/month 18 (29) 23 (37)$1,000 to $1,999/month 35 (55) 33 (52)$$2,000/month 10 (16) 7 (11)

Marital status§Married or living with partner 45 (72) 44 (69.8)Unmarried 18 (28) 19 (30.2)

Cell phone useOwn cell phone 54 (86) 51 (81)Use text messaging 39 (72) 44 (86)

Age of diabetes diagnosis, mean (SD) 38.6 (9.2) 40.7 (10.5)

Prescribed medicationsOral medication* 46 (73) 40 (64)Insulin* 2 (3) 5 (8)Combination therapy (oral plus insulin) 15 (24) 14 (22)

Data are reported as n (%), unless otherwise noted. Data are basedon all individuals who completeda baseline assessment (N = 126). *Indicates a statistically significant difference between groups(P, 0.05). §Education, income, insurance, and marital status categories were collapsed for easeof presentation.

1352 Texting Intervention in Hispanics With Diabetes Diabetes Care Volume 40, October 2017

thus placing themat high risk for diabetescomplications. The Dulce Digital groupmean did not reach the optimal levelof ,7.0–7.5%. However, during the6-month intervention, 68% of Dulce Digi-tal participants achieved reductions inHbA1c levels, with individual decreasesranging from 20.1% to 24.6%. Overall,Dulce Digital achieved a mean 1% reduc-tion in HbA1c, which exceeds the averageeffect size reported in reviews of othermHealth approaches (pooled HbA1cD =20.5%) (18–20) and the average HbA1creduction reported in a recent synthesisof 118 traditional DSME trials (averageHbA1cD = 0.74%) (27). Baseline HbA1c lev-els in the reviewed studies ranged fromnear normal (6.5%) to extremely elevated(9.8%), which is similar to the results of

our study. In one review fromGreenwoodet al. (28), it was noted, unsurprisingly,that when study participants’mean base-line HbA1c level was at or close to goal, asmall intervention effect was seen. Therelationship of the baseline HbA1c levelto the intervention effect demonstratesthe importance of choosing the optimalpopulation for interventions. With thecurrent broad use of diabetes registriesand the ease of identifying higher-riskindividuals using population health man-agement methods, it may be worthwhileto focus initial efforts of technology inter-ventions in our higher-risk patients. AnHbA1c reduction of the magnitude foundin the current study should not be under-estimated and should be considered notonly statistically significant but also

clinically relevant; it rivals the effectsof some glucose-lowering medications(29–31) and has been associated withdecreased risk for retinopathy, nephrop-athy, and neuropathy (32–34).

Notably, the number of blood glucosevalues texted in by participants predictedmonth 6 HbA1c values. Individuals whosent in more blood glucose values mayhave been more actively engaged withthe intervention (and were thus readingmore of the DSME messages) and/ormore active participants in their health.Nonetheless, additional research is neededto reach conclusions about themechanismunderlying this relationship. Results did notindicate a significant “dosage” effect be-tween text message frequency and HbA1clevel. However, further research is war-ranted to determine the “optimal” fre-quency of texts, acknowledging thatoptimizationwill likely need to be individ-ualized according to each patient’sunique needs and preferences. Similarly,the number of phone contacts with thestudy coordinator (in response to bloodglucose values) did not predict month6 HbA1c levels. This finding is not surpris-ing given the brief, safety-focused natureof these calls; the coordinator did not pro-vide health coaching or in-depth clinicalguidance but rather assessed for emer-gent safety risks and recommended phy-sician follow-up as appropriate.

No statistically significant interventioneffects were observed for secondary clin-ical indicators. However, this may be dueto the fact that, on average, blood pres-sure and lipids were close to target levelsat baseline, leaving little room for im-provement. Further, the Dulce Digitalcontent was not designed to address lipidor blood pressure control.

The current results should be inter-preted in the context of several limitations.First, although attritionwas comparable tothat observed in prior studies (35), attri-tion was higher in the intervention grouprelative to the UC group. Thus, it is possi-ble that participants who remained in thestudy were more engaged. A worst-casescenario sensitivity analysis is presentedin Supplement A. Second, it is unknownhowmuch of the intervention contentwasreceived (i.e., read or comprehended) byparticipants. Nonetheless, the number ofblood glucose values texted inmaybe con-strued as an indirect indicator of interven-tion engagement. Third, 44%of potentiallyeligible individuals were enrolled, with the

Table 2—Clinical outcome means for the Dulce Digital and UC groups

Clinical indicator

Baseline Month 3 Month 6

n Mean (SD) n Mean (SD) n Mean (SD)

HbA1c*%Dulce Digital 63 9.5 (1.2) 50 8.5 (1.2) 50 8.5 (1.2)UC 63 9.6 (1.4) 57 9.3 (1.9) 59 9.4 (2.0)

mmol/molDulce Digital 63 80 (13.1) 50 69 (13.1) 50 69 (13.1)UC 63 81 (15.3) 57 78 (20.8) 59 78 (20.8)

Fasting blood glucose (mg/dL)Dulce Digital 63 184.0 (63.2) 50 164.6 (46.4) 50 161.3 (49.7)UC 63 190.3 (66.7) 57 186.5 (66.8) 59 186.5 (68.5)

Total cholesterol (mg/dL)Dulce Digital 63 178.9 (38.1) 50 170.3 (32.4) 50 175.2 (33.1)UC 63 193.7 (48.2) 57 193.7 (44.0) 59 192.6 (39.6)

HDL (mg/dL)Dulce Digital 63 44.5 (11.5) 50 42.9 (12.1) 50 42.3 (10.5)UC 63 48.0 (14.6) 57 48.3 (13.0) 59 46.4 (10.7)

LDL (mg/dL)Dulce Digital 61 96.7 (32.8) 48 91.2 (28.0) 48 95.9 (29.8)UC 58 108.1 (32.2) 53 106.2 (28.4) 54 107.5 (33.8)

Triglycerides (mg/dL)Dulce Digital 63 186.3 (104.3) 50 192.3 (139.7) 50 185.4 (95.9)UC 63 197.5 (144.9) 57 207.9 (172.3) 59 204.6 (129.6)

SBP (mmHg)Dulce Digital 58 122.8 (15.9) 46 120.6 (14.3) 45 122.4 (17.2)UC 63 124.7 (21.9) 52 123.1 (17.9) 53 120.5 (17.6)

DBP (mmHg)Dulce Digital 58 75.1 (9.6) 46 72.9 (8.5) 45 73.7 (11.1)UC 63 74.7 (10.8) 52 72.7 (9.1) 53 72.3 (10.4)

BMI (kg/m2)Dulce Digital 63 31.5 (6.0) 49 31.7 (5.2) 50 31.9 (5.4)UC 63 32.2 (6.6) 57 32.0 (6.1) 58 32.1 (6.6)

Weight (lb)Dulce Digital 63 173.1 (34.6) 49 176.2 (33.0) 50 174.1 (27.8)UC 63 176.4 (41.6) 57 174.2 (39.7) 58 175.2 (41.6)

All analyses controlled for age and sex; however, unadjusted means are reported. DBP, diastolicblood pressure; SBP, systolic blood pressure. *Indicates a statistically significant time-by-groupinteraction effect (P, 0.05).

care.diabetesjournals.org Fortmann and Associates 1353

majority reporting practical barriers thatare commonlyexperienced inunderservedpopulations (e.g., no transportation, workconflict, caregiving responsibilities, othertime conflict). Thus, it is expected that byintroducing the Dulce Digital program aspart of routine clinic care, program reachcould be expanded to individuals whocould not attend additional (research-required) visits. Finally, this trial was notdesigned to examine cost-effectiveness.However, with respect to sustainabilityand scalability of an intervention such asDulce Digital compared with other low-resource settings, the promise of textmes-sage–based programs is great. There is no

additional cost for the technical infra-structure whether it is delivered to400 or 4,000 individuals. The cost to thepatient/user is only related to the textmessages, and for Dulce Digital (in partic-ular) a smartphone is not required. Inother research, a significant population-level cost savings was attributed to a text-messaging program designed to facilitatediabetes care coordination in a predomi-nantly African American population (22).This study included a care managementcomponent facilitated by nurses or med-ical assistants.

Dulce Digital offers a potential solutionto the burgeoning primary care demand-

capacity imbalance to better address thecomplex needs of the growing number ofindividuals with type 2 diabetes. Text-messaging approaches are attractive as achronic disease public health interventionfor a number of reasons, including theirfrequent use, enormous reach, low cost,and relative simplicity. Mobile phone andtexting use is high among Hispanics (16), agroup that experiences disparate diabe-tes prevalence and outcomes. Moreover,the present investigation indicated thatthe Dulce Digital approach was highly ac-ceptable in this population. This model isflexible, lending itself to adaptation forother chronic conditions (e.g., arthritis,chronic pain) and for delivery by otherpersonnel to address the health needsof underserved populations across the na-tion. Future investigations should examinethe sustainability of the improvementsin glycemic control beyond 6 months;expanding intervention content to targetadditional populations at risk for diabetesand other cardiometabolic indicators thatare central to diabetes control (e.g., bloodpressure, lipids); and individualizing textmessage content and delivery timing andfrequency to each patient’s unique needsand progress.

Acknowledgments.The authors thank the staffand participants of the Dulce Digital study fortheir important contributions and the adminis-tration and staff atNeighborhoodHealthcare fortheir partnership in this investigation. The authorsalso thankpeereducatorMagdalenaHernandez, anemployee of ScrippsWhittier Diabetes Institute, forrecruitment and cohort maintenance support.Funding. The current research was supportedby McKesson Foundation grant 115M803379and National Center for Advancing TranslationalSciences grant NCATS 1UL1 TR001114-01. TheInvestigator-Initiated Study Program of LifeScan,Inc., providedglucose testingmeters and strips forall participants.Duality of Interest. No potential conflicts of in-terest relevant to this article were reported.Author Contributions. A.L.F. researched andanalyzed data and wrote and reviewed themanuscript. L.C.G. contributed to the researchdevelopment, conduct of research, and dataanalysis and wrote and reviewed the manu-script. M.I.G. contributed to the conduct ofresearch and data analysis and reviewed themanuscript. M.T. contributed to the researchdata and analysis and reviewed themanuscript.J.A.E., T.C., and J.Sk. contributed to the researchanalysis and reviewed the manuscript. M.R.,S.D.-S., and J.Sc. contributed to the researchdevelopmentandconductofresearchandreviewedthemanuscript. A.P.-T. contributed to the researchdevelopment, conduct of research, and researchanalysis and wrote and reviewed the manuscript.

Figure 2—A: HbA1cmeans and 95%CIs for theDulceDigital andUC groups at baseline,month 3, andmonth6.B: Association between the number of blood glucose values texted in by participantswith achange in HbA1c level from baseline to month 6 in the Dulce Digital group. Values adjacent to errorbars represent the mean number of texts for each quintile. Note: The texting variable was analyzedas a continuous variable but was binned into quintiles for graphical presentation. Although HbA1cchange is represented on the y-axis for ease of interpretation, the month 6 HbA1c level was used asthe outcome variable (with control for baseline HbA1c level) in regression analyses. Because of thecurvilinear appearance of this relationship, the texting predictor was also examined using a qua-dratic term; however, the quadratic variable was not statistically significant.

1354 Texting Intervention in Hispanics With Diabetes Diabetes Care Volume 40, October 2017

A.P.-T. is theguarantorof thisworkand,assuch,hadfull access to all the data in the study and takesresponsibility for the integrity of the data and theaccuracy of the data analysis.Prior Presentation. Parts of this study werepresented in abstract form at the 74th ScientificSessions of the American Diabetes Association,San Francisco, CA, 13–17 June 2014.

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