The objective of this study was to synthesize English and Spanish literature to determine whether electronic health interventions (EHIs) such as telehealth, telemedicine, digital health, and mobile health (mHealth) improve A1C, blood glucose, BMI, and/or weight among Hispanic/Latino adults with type 2 diabetes or overweight/obesity in the Americas.
Searches were conducted in June 2021 using the Scientific Electronic Library Online, Cumulative Index of Nursing and Allied Health Literature, PubMed, and PsycInfo literature databases. Studies were identified that investigated the effect of an EHI on A1C, blood glucose, BMI, or weight in populations that were ≥12% Hispanic/Latino adults with type 2 diabetes or overweight/obesity, were conducted in the Americas, and were published in English or Spanish. Study quality was determined using the Quality Index Score. Data were extracted and synthesized, and themes were identified.
Twenty-five studies met inclusion criteria, including 23 in English (from the United States) and two in Spanish (from Chile). A total of 22 investigated type 2 diabetes, and three investigated overweight/obesity. The studies encompassed 6,230 participants, including 3,413 Hispanic/Latino adults. Sixty-three percent of studies demonstrated significant improvements in A1C or blood glucose and 67% in weight. Thirteen studies offered an EHI in both English and Spanish, and six offered the intervention in either English or Spanish alone. All EHIs involving mHealth exclusively and most (90%) involving more than one electronic modality demonstrated a higher number of significant findings compared with those having only one EHI modality, especially telehealth (44.4%). EHIs lasting ≤12 months had more significant findings (72.7%) than those lasting >12 months (50%). Six studies had industry-related funding, with 83.3% of those demonstrating significant improvements in outcomes.
EHIs improved A1C and weight in adults (n = 4,355), including 45.5% Hispanic/Latino adults. mHealth and EHIs using more than one electronic modality and those lasting ≤12 months were especially effective. However, overall study quality was modest. Future research should be conducted in Spanish-speaking countries in Latin America and should compare the effectiveness of different EHI modalities.
Type 2 diabetes is a major obesity-related public health concern worldwide (1) with a marked burden in the Americas. The United States and Mexico have the third and sixth highest prevalence rates of type 2 diabetes in adults globally (13.0 and 15.7%, respectively) (2–4). Incidence of type 2 diabetes in the United States varies among different racial/ethnic groups. After American Indians/Alaska Natives (14.7%), the second highest prevalence of diagnosed type 2 diabetes in the country is concentrated in the Hispanic/Latino population (12.5%), followed by non-Hispanic Blacks (11.7%), non-Hispanic Asians (9.2%), and non-Hispanic Whites (7.5%). Between 2017 and 2018, the incidence of type 2 diabetes in Hispanic/Latino adults was 9.0 cases/1,000 people, a higher rate than in other races/ethnicities (3). These epidemiological patterns suggest that Hispanic/Latino populations may have a higher risk of other major health outcomes such as cardiovascular diseases and premature death than other populations. Thus, a comprehensive strategy to counteract type 2 diabetes and obesity in these individuals is urgently needed.
Part of the solution to this challenge may be found in the rapid advancements in information and communication technology (ICT) that are a Force of Change shaping individuals’ interactions (5). Approximately 67% of adults in 40 countries are Internet users, and 76% are involved in online open-access platforms requiring electronic devices (6). Although disparities among population subgroups remain, some reports indicate that Hispanic people are more likely than non-Hispanic Whites to use mobile devices and the Internet to send and receive emails, access video or pictures, download apps, and send text messages (7,8). Therefore, given its widespread use and diverse scope, ICT can be an allied instrument against the type 2 diabetes and obesity epidemics in the Americas that disproportionately affect Hispanics/Latinos.
Electronic health (eHealth) is a cost-effective and safe use of ICT in support of epidemiological surveillance, education and research, and health care services (9,10). Since 2012, the World Health Organization has promoted the development and evaluation of eHealth strategies to improve health, acknowledging their potential capability to minimize barriers such as language and distance (9,10). Leveraging such features in countries of the Americas such as Mexico is crucial given that 48.5% of the population has no effective access to health services (11).
eHealth encompasses a series of ICT components. Two examples are mobile health (mHealth), which is the use of mobile phones or digital tablets to collect, process, and report data focused on medical and public health practices, and telehealth, the practice of medicine at a distance (9,10). There are different mechanisms through which eHealth can positively affect obesity-related conditions. For example, online platforms, complex digital systems, artificial intelligence, or apps and features nested in electronic devices have been used to enhance motivation among users of online health and weight loss programs (12–14), improve diet and physical activity patterns (15–17), facilitate effective screening for type 2 diabetes complications (18), and deliver type 2 diabetes education that reinforces regular medical visits, self-management, and metabolic control (19).
Recent research provides supportive evidence for the use of eHealth interventions (EHIs) as instrumental actions to prevent and ameliorate type 2 diabetes and obesity. A meta-analysis concluded that EHIs in 21 randomized clinical trials from North America, Europe, and Asia significantly reduced A1C values in 3,787 participants with poorly controlled type 2 diabetes compared with usual care (mean differences up to –0.40% [95% CI –0.54 to –0.26]) (20,21). A pooled analysis of 21 systematic reviews and meta-analyses, eight randomized controlled trials (RCTs), one clinical trial, and one qualitative study from the United States and other countries showed that telemedicine interventions triggered a significant decline in A1C levels of up to a −0.64% weighted mean difference (95% CI −1.01 to −0.26%], P <0.001) in participants with type 2 diabetes (22). Regarding obesity, a systematic review with meta-analysis of 84 studies from multiple continents involving 139 intervention groups (76%) with at least one technological component showed that EHIs achieved greater weight loss than standard care (mean difference −2.70 kg [95% CI −3.33 to −2.08 kg], P <0.001) (23). Another systematic review compiling data from six U.S. trials involving racial/ethnic minorities (3–13% Hispanic) suggested that EHIs can yield small amounts of short-term weight loss (24).
Assessments of evidence quality that account for risk of bias and internal and external validity have been carried out in previous systematic reviews (20–24). However, the presence of potential competing interests has not been extensively incorporated into the narrative of EHI evaluation. Previous literature demonstrates that industry-funded reviews and reviews conducted by authors with conflicts of interest had more favorable findings and/or conclusions related to artificial sweeteners and weight outcomes than reviews without conflicts of interest (25). Thus, it is important to document whether partially or fully funded studies by industry and/or authors with potential competing interests might generate systematic bias in studies on EHIs.
Despite the literature demonstrating benefits of EHIs, the systematic reviews and meta-analyses cited previously devoted little effort to evaluating the effects of EHIs on type 2 diabetes and obesity specifically among Hispanic/Latino individuals, nor did they include literature published in Spanish (20,21,23). Furthermore, one of the reviews that focused on type 2 diabetes only included one EHI (22), and the review investigating the EHI on weight management in racial/ethnic minorities did not include any studies with mHealth interventions (24), demonstrating a significant gap in the literature. Therefore, the purpose of this systematic review was to synthesize the available evidence published in English and Spanish on the effects of EHIs on type 2 diabetes and overweight/obesity outcomes among Hispanic/Latino adults from the Americas. Additionally, we explored potential conflicts of interests within this literature.
Research Design and Methods
Overview of Search
This systematic review aimed to determine the state of the science of published interventions for type 2 diabetes and obesity in Hispanic/Latino adults that were executed in English or Spanish via any electronic platform in the region of the Americas and involved EHIs, including telehealth, telemedicine, digital health, and mHealth interventions (9,10). Definitions are provided in Table 1. The research question was constructed using the PICO (patient/population, intervention, comparison, and outcomes) method (26). The population under investigation included Hispanic/Latino adults with type 2 diabetes or obesity/overweight. The intervention had to include an EHI with or without comparison group or groups. The outcomes could include changes in A1C, blood glucose, BMI, or weight. The protocol was registered on PROSPERO (#158799).
Definitions of EHIs
| Intervention Type | Definition |
|---|---|
| Telehealth | Automated or real-time telephone calls |
| Telemedicine | Interventions or telemetry, including but not limited to scales, eye health screeners, and blood pressure devices, that are provided via remote link and video conferences |
| Digital health | Newsletters and interactive lessons or modules |
| mHealth | Text messages, mobile fitness devices (e.g., Fitbit, Apple Watch, and Samsung Galaxy Watch), and mobile phone apps. |
| Intervention Type | Definition |
|---|---|
| Telehealth | Automated or real-time telephone calls |
| Telemedicine | Interventions or telemetry, including but not limited to scales, eye health screeners, and blood pressure devices, that are provided via remote link and video conferences |
| Digital health | Newsletters and interactive lessons or modules |
| mHealth | Text messages, mobile fitness devices (e.g., Fitbit, Apple Watch, and Samsung Galaxy Watch), and mobile phone apps. |
Data Sources and Search Strategy
The literature searches were conducted in January and February of 2020 and updated in June 2021 using the Scientific Electronic Library Online (SciELO), Cumulative Index of Nursing and Allied Health Literature (CINAHL), PubMed, and PsychInfo databases. Medical Subject Headings (MeSH) terms were used when applicable. For example, CINAHL included MeSH terms for telehealth, whereas PubMed and PsychInfo did not. Searches were conducted in cycles interchanging Latin*/Hispanic or Latino/Hispanic, type 2 diabetes/type 2 diabetes mellitus, obesity, and telehealth, telemedicine, eHealth, digital health, and mhealth without publication date restrictions. Given that most of the literature available on SciELO is published in Spanish and comes from Latin American countries, the terms Latin*/Latino and Hispanic were omitted for the searches.
Searches were conducted by one author for English articles (A.L.O.) and another for Spanish articles (K.M.). Articles were screened based on inclusion and exclusion criteria by two reviewers separately for articles in English (E.L. and A.L.O.) and Spanish (L.C.G. and K.M.). First, publication titles and abstracts were screened for inclusion independently by the reviewers. When publication titles and abstracts were not sufficiently explicit to determine inclusion, full-text articles were reviewed. Reference lists for all included articles and relevant systematic reviews found during the search were reviewed to identify additional articles for inclusion. The included articles were compared by the authors, and discrepancies were discussed. A third reviewer (R.E.L.) was consulted when consensus could not be reached to resolve discrepancies.
Inclusion Criteria
Studies were included if they met the following criteria: 1) original research published in a peer-reviewed journal in English and/or Spanish, 2) experimental and/or quasi-experimental study design, 3) study sample ≥12% Hispanic/Latino, 4) adults ≥18 years of age, 5) subjects diagnosed with type 2 diabetes by a health care provider or having an A1C ≥6.5%, and/or diagnosed as having overweight/obesity or having a BMI ≥25.0 kg/m2, 6) included an EHI intervention (telehealth, telemedicine, digital health, or mHealth), 7) reported outcomes related to type 2 diabetes and/or obesity (i.e., A1C, blood glucose, BMI, or weight), and 8) conducted in countries that comprise the Americas (North America, Central America, South America) or the Caribbean islands. The criterion that studies have a sample that includes at least 12% Hispanic/Latino adults was chosen because there were limited studies that included 100% Hispanic/Latino adults. Systematic reviews, conference abstracts, dissertations, gray literature, and studies with comorbidities or pregnancy as inclusion criteria were excluded.
Data Extraction
Data extracted from each publication included authors, year of publication, design, sample size and demographics (age, sex, Hispanic/Latino ethnicity, proportion of Spanish speakers), country of implementation, intervention type (telehealth, telemedicine, digital health, or mHealth) and length, intervention components, language of intervention, type 2 diabetes or obesity outcomes (A1C, fasting blood glucose [FBG], serum blood glucose, BMI, or weight), covariates, findings, study quality score, and funding source. Industry-related funding included any funding, supplies, and/or compensation provided by any for-profit organization. Two authors extracted data from each study, and data were compared. Discrepancies were discussed and, if consensus could not be reached, a third reviewer (R.E.L.) was consulted.
Evaluation of Study Quality
The Quality Index Score (QIS) was used to evaluate the quality of included studies (27). The QIS measure was selected for its versatility to evaluate both randomized and nonrandomized experimental studies and includes 27 questions. For this study, one question related to data dredging was eliminated because this concept is rarely reported. Studies were scored with either 0 (does not meet criteria) or 1 (meets criteria) for all questions except one. This question could receive a score of 0 (does not meet criteria, 1 (partially meets criteria), or 2 (fully meets criteria). Of the 26 questions included, there were 27 possible points, and categories for assessment included a reporting score (of 11), external validity (of 3), internal validity bias (of 6), internal validity selection bias (of 6), and power (of 1).
Narrative Analysis/Synthesis
Because of the high level of heterogeneity among the designs, interventions, and outcomes, a meta-analysis was not conducted. Data were organized, summarized, and narratively synthesized separately for adults with type 2 diabetes and overweight/obesity by EHI type, intervention length and language, and funding support, comparing the number of significant findings with the number of findings that were not significant across studies. Themes were identified and presented.
Results
Searches identified 244 English and 39 Spanish study titles screened after duplicates were removed. One-hundred and fifty-two English and 23 Spanish studies were excluded after reviewing titles and abstracts because they did not meet inclusion criteria. Ninety-two English and 16 Spanish studies were reviewed in full text, with 79 English and 15 Spanish studies excluded because they did not meet inclusion criteria. A total of 10 English and one Spanish study were identified through manually searching reference lists and contributed to a total of 23 studies published in English (28–50) and two published in Spanish (51,52) that were included in this review (Figure 1). Twenty-two studies met inclusion criteria for type 2 diabetes (28–32,34–40,42–51), and three met criteria for overweight obesity (33,41,52).
Diagram of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart for study selection. aEnglish language. bSpanish language.
Diagram of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart for study selection. aEnglish language. bSpanish language.
Sample Characteristics
Detailed information for each study is presented in Table 2. A total of 6,230 participants were included across studies, with study samples sizes ranging from 16 (38) to 1,665 (45). One study did not report age (28), but the remainder of the studies included mean, median, or modal age ranges between 18 (48) and 72 (30) years. One study did not report female participant enrollment; however, this study focused on veterans and may not have included females (30). The remaining studies included female sample sizes ranging from 5 to 1,046 with a total of 3,709 female participants (60%). The sample sizes of Hispanic/Latino participants across the 25 studies ranged from 5 (23% of the study sample) (40) to 586 (35% of the study sample) (45). The proportion of Hispanic/Latino participants in the combined studies was ∼55% for a total of 3,413. Twenty-three studies were conducted in the United States (28–50) and two in Chile (51,52). Study designs included 15 RCTs (28,29,31–34,39,41–43,45–47,50,52), five feasibility/pilot studies (30,38,40,48,49), one quasi-randomized trial (51), one randomized reinforcement study (37), one randomized three-arm trial (44), and two single pre-/post-test studies (35,36). The studies were published between 2000 and 2021. Of note, the overall sample size and number of female and Hispanic/Latino participants are approximate totals, because the descriptive characteristics provided for each study were inconsistent and based on either participants who completed only baseline or both baseline and follow-up data collections. The first n extracted for each study in Table 2 is the sample size for which sociodemographic characteristics are presented in each study.
Included Articles
| Article | Design | Sample | Country | EHI Type, Length | Intervention Components | Language | Outcomes | Covariates | Findings |
|---|---|---|---|---|---|---|---|---|---|
| Type 2 diabetes outcomes | |||||||||
| Anderson et al. (28) | RCT | n = 295 (completers: n = 211); mean age: not provided; female: 58% (n = 171); Hispanic/Latino: 76% (n = 223); Spanish speakers: 58% (n = 172) | United States | Telehealth, 12 months | IG: usual care plus weekly, biweekly, or monthly telephonic disease management calls CG: usual care | English and Spanish | A1C | Baseline A1C |
|
| Arora et al. (29) | RCT | n = 128 (completers: n = 92); mean age: 50.7 years; female: 64% (n = 82); Hispanic/Latino: 87% (n = 112); Spanish speakers: 72% (n = 92) | United States | mHealth, 6 months | IG: two daily text messages promoting self-care and medication adherence CG: usual care | English and Spanish | A1C | None |
|
| Dang et al. (30) | Pilot | n = 41 (enrolled: n = 69); mean age: 72.0 years; female: not provided; Hispanic/ Latino: 15% (n = 6) | United States | Telemedicine, 9 months | Telephone-based, in-home patient monitoring messaging device with care coordination and educational materials | English | A1C | None |
|
| Fortmann et al. (31) | RCT | n = 126 (completers: n = 113); mean age: 48.4 years; female: 75% (n = 94); Hispanic/Latino: 100% (n = 126); Spanish speakers: 92% (n = 116) | United States | Telehealth and mHealth, 6 months | IG: ≤3 daily motivational, educational, and/or call-to-action text messages; telephone calls if hyperglycemic, hypoglycemic, or no glucose value provided for 1 week CG: usual care | English and Spanish | A1C, FBG | Age, sex |
|
| Frosch et al. (32) | RCT | n = 201 (completers: n = 182); mean age: in IG 56.7 years and in CG 54.3 years; female 48% (n = 100); Hispanic/Latino: 56% (n = 113) | United States | Telehealth and digital health, 6 months | IG: 24-minute DVD video and booklet with ≤5 telephone coaching sessions with bilingual nurse educator (2.5 hours maximum total coaching time) CG: 20-page brochure | English and Spanish | A1C | None |
|
| Heisler et al. (34) | RCT | n = 188 (completers: n = 176); mean age: in IG 51.0 years and in CG 52.0 years; female: 71% (n = 133); Hispanic/Latino: 57% (n = 107) | United States | Telehealth and digital health, 6 weeks | IG: 1- to 2-hour session with community health worker using iDecide and two follow-up phone calls CG: print materials | English and Spanish | A1C | Baseline health literacy |
|
| Jackson et al. (35) | Experimental | n = 38 (enrolled: n = 40, optional extension: n = 29; optional extension completers: n = 19); median age: 56 years; female: 55% (n = 21); Hispanic/Latino: 100% (n = 38) | United States | mHealth, 3 months with optional 3-month extension | One to three daily educational, motivational, and community resource/event text messages related to diabetes self-management; reply texts with ability to text the Latina health educator and receive responses, remote monitoring, and care management Optional extension: educational and supportive text messages | Spanish | A1C | None |
|
| Jiwani et al. (36) | Clinical demonstration project | n = 62 (a 3 months: n = 36, at 6 months: n = 52, at 12 months: n = 61); mean age: 67.6 years; female: 8% (n = 5); Hispanic/Latino: 58% (n = 36) | United States | Telehealth, 6 weeks | Pedometer; initial (goal-setting, healthy food, benefits of walking) and follow-up face-to-face visits; weekly telephone calls related to walking and step counts | English* | A1C | None |
|
| Khanna et al. (50) | RCT | n = 75 (completers: n = 49); mean age: in IG 51.0 years and in CG 53.0 years; female: 41% (n = 31); Hispanic/Latino: 100% (n = 75); Spanish speakers: 100% (n = 75) | United States | Telehealth, 12 weeks | IG: 10-minute informational video related to risks of uncontrolled type 2 diabetes, benefits of low-glycemic diet, and study protocol, plus automated telephone nutrition support and feedback on entered dietary information consumed in the past 24 hours CG: 10-minute informational video | Spanish | A1C | None |
|
| Lange et al. (51) | Quasi-experimental randomized trial | n = 426 (enrolled: n = 640); mean age: in IG 53.8 years and in CG 52.8 years; female: 69% (n = 292); Hispanic/Latino: 100% (n = 426); Spanish speakers: 100% (n = 426) | Chile | Telehealth, 15 months | IG: average of six telephone calls lasting for an average of 10 minutes; telephone counseling for diabetes self–management by nurses trained in motivational interviewing CG: usual care | Spanish | A1C | Baseline A1C, years with diabetes |
|
| Lorig et al. (37) | Randomized reinforcement | n = 387 (completers: n = 300); mean age: 52.1 years; female: 62% (n = 239); Hispanic/Latino: 100% (n = 387); Spanish speakers: 100% (n = 387) | United States | Telehealth, 18 months | IG: Spanish Diabetes Self-Management Program plus 15 monthly automated calls; content included self-assessment of diabetes management skills, two 90-second vignettes about diabetes, and an invitation to leave a message CG: Spanish Diabetes Self-Management Program group sessions | Spanish | A1C | Baseline A1C, demographic variables (not specified) |
|
| Mayes et al. (38) | Feasibility | n = 16 (enrolled: n = 19); mean age: 51.0 years, female: 81% (n = 13); Hispanic/Latino: 100% (n = 16) | United States | Telehealth, telemedicine, and digital health, 3.5 years | Promatoras, home glucose monitoring over the Internet, communication via phone and e-mail, and audio and video interviews | English and Spanish | A1C | None |
|
| Millan-Ferro et al. (39) | RCT | n = 307 (completers: n = 240); mean age: 55.2 years; female: 55% (n = 169); Hispanic/Latino: 88% (n = 269) | United States | Telehealth and telemedicine, 5 months | IG: informational booklet related to type 2 diabetes management and A1C monitoring plus A1C Now device measurements completed at home at months 1, 2, 4, and 5; telephone call with nurse practitioner after each A1C Now measurement related to treatment plans CG: informational booklet | English and Spanish | A1C | None |
|
| Myers et al. (40) | Pilot | n = 22 (enrolled: n = 29, A1C post-test n = 12); mean age: in IG 56.6 years and in CG 58.7 years; female: 55% (n = 12); Hispanic/Latino: 23% (n = 5) | United States | Telemedicine or telehealth, 3 months | IG 1: weekly (month 1) to biweekly (months 2 and 3) video visits with endocrinologist, digital tablet with Bluetooth blood pressure monitor, scale, and pulse oximeter uploaded data daily, and daily medication reminders IG 2: monthly telephone calls for 3 months from endocrinologist related to medication, diet, lifestyle, with provider recommendations | English | A1C | None |
|
| Piette et al. (43) | RCT | n = 248 (enrolled: n = 280); mean age: in IG 56.0 years and in CG 53.0 years; female: 59% (n = 146); Hispanic/Latino: 50% (n = 123); Spanish speakers: 26% (n = 64) | United States | Telehealth, 12 months | IG: usual care plus biweekly automated telephone calls with assessment lasting 5–8 minutes, including patient-reported self-monitored blood glucose levels, glycemic control, symptoms, medical care, optional diabetes health tips; weekly nurse assessment with follow-up (based on protocol) via telephone providing diabetes-related information and education CG: usual care | English and Spanish | A1C and serum blood glucose | Baseline A1C, insulin use |
|
| Piette et al. (42) | RCT | n = 272 (enrolled: n = 292); mean age: in IG 60.0 years and in CG 61.0 years; female: 3% (n = 8); Hispanic/Latino: 13% (n = 34) | United States | Telehealth, 12 months | IG: biweekly automated telephone calls with assessment lasting 5–8 minutes, including patient-reported self-monitored blood glucose levels, glycemic control, symptoms, medical care, optional health promotion messages; weekly nurse assessment with follow-up (based on protocol) via telephone, providing diabetes-related information and education CG: usual care | English and Spanish | A1C and serum blood glucose | Baseline A1C |
|
| Schillinger et al. (44) | Randomized three-arm trial | n = 339 (completers: n = 305); mean age: 56.1 years; female: 59% (n = 200); Hispanic/Latino: 47% (n = 159); Spanish speakers: 43% (n = 146) | United States | Telehealth, 9 months | IG 1: automated telephone self-management consisting of weekly calls over 9 months; responses triggered automated health education messages and/or nurse phone follow-up; 6–10 minutes to complete IG 2: group medical visits for education and patient activation; 90-minute monthly sessions with 6–10 participants CG: usual care | English, Spanish, and Cantonese | A1C | Baseline A1C |
|
| Shea (45) | RCT | n = 1,665 (completers: n = 1,417); mean age: 71.0 years; female: 63% (n = 1,046); Hispanic/Latino: 35% (n = 586); Spanish speakers: 35% (n = 579) New York City: n = 775; female: 69.5% (n = 539); Hispanic/Latino: 74.1% (n = 574); Spanish speakers: 73.3% (n = 568) Upstate New York: n = 890; female: 57% (n = 507); Hispanic/Latino: 1.3% (n = 12); Spanish speakers: 1.2% (n = 11) | U.S. | Telemedicine and digital health, 12 months | IG: home telemedicine unit provided videoconferencing, remote glucose and blood pressure monitoring with upload, access to patient data, and Web-based messaging with case managers and access to educational website CG: usual care | English and Spanish | A1C | Baseline A1C, clustering group heterogeneity, residual variances |
|
| Vaughan et al. (46) | RCT | n = 89 (completers: n = 83); mean age: in the IG 56.0 years and in the CG 53.9 years; female: 72% (n = 64); Hispanic/Latino: 100% (n = 89); Spanish speakers: 100% (n = 89) | United States | Telehealth or mHealth, 12 months | IG: community health workers called or texted participants (depending on preference) weekly in months 1–6 and bimonthly in months 7–12; content was related to glucose control, medication adherence, and questions or concerns; monthly in-person group sessions for 6 months; low-cost medication access CG: usual care | Spanish | A1C | None |
|
| Walker et al. (47) | RCT | n = 526 (randomized: n = 527, completers: n = 444); mean age: 55.5 years; female: 67% (n = 353); Hispanic/Latino: 22.6% (n = 119) | United States | Telehealth, 12 months | IG: up to 10 calls at 4- to 6-week intervals from health educator; content was personalized and focused on diabetes medication adherence and healthy lifestyle changes CG: print materials | English and Spanish | A1C | Baseline A1C, age, sex, insulin use |
|
| Watterson et al. (48) | Quasi- experimental pilot | n = 210 (completers: n = 178, pilot: n = 50, chart review comparison group: n = 160); age-group: 18–44 years 19% (n = 40), 45–54 years 31% (n = 66), and 55–64 years 50% (n = 104); female: 62% (n = 131); Hispanic/Latino: 69% (n = 145); Spanish speakers 56% (n = 117) | United States | mHealth, 12 weeks | IG: text-messaging program; automated, interactive, and unidirectional text messages related to diabetes self-management and education; three to four text messages per week CG: usual care from chart review | English and Spanish | A1C | Only in subgroup analyses: site, age, sex, primary language, race |
|
| Welch et al. (49) | Pilot | n = 30 (completers: n = 29); mean age: 60.6 years; female: 57% (n = 17); Hispanic/Latino: 27% (n = 8) | United States | Telehealth and telemedicine, 3 months | Electronic pillbox integrated into diabetes remote home monitoring system; nurse interventionists received monitoring data and contacted by phone at scheduled time points | English | A1C | None |
|
| Overweight/obesity outcomes | |||||||||
| Godino et al. (33) | RCT | n = 404 (completers: n = 341); mean age: 22.7 years; female: 70% (n = 284); Hispanic/Latino: 31% (n = 125) | United States | Telemedicine, digital health, and mHealth or only digital health, 24 months | IG 1: six modules, including Facebook, mobile apps, text messaging, emails, website with blog posts, technology-mediated health coaching sessions (≤10 sessions of 5–15 minutes in length); instructed to use ≥1 modality ≥5 times/week over 24 months IG 2: Website access to general health and wellness information, general weight loss information, and quarterly newsletters via e-mail; participants encouraged to interact with the website weekly | English | Weight | Sex, ethnicity, college education |
|
| Patrick et al. (41) | RCT | n = 65 (completers: n = 52); mean age: 44.9 years; female: 80% (n = 52); Hispanic/Latino: 25% (n = 16) | United States | Telehealth and mHealth, 4 months | IG: personalized text and small-picture messages sent two to five times per day, printed materials, monthly telephone calls with health counselor CG: monthly printed materials | English | Weight | Baseline weight, sex, age |
|
| Pérez Ewert et al. (52) | RCT | n = 70 (completers: n = 65); mean age: 52.8 years; female: 66% (n = 46); Hispanic/Latino: 100% (n = 70) | Chile | Telehealth and mHealth 6–9 months | IG: counseling via telephone calls and text messages related to knowledge on prediabetes prevention and control, physical activity, and healthy diet and self-monitoring equipment CG: usual care, self-monitoring equipment | Spanish | Weight | None |
|
| Article | Design | Sample | Country | EHI Type, Length | Intervention Components | Language | Outcomes | Covariates | Findings |
|---|---|---|---|---|---|---|---|---|---|
| Type 2 diabetes outcomes | |||||||||
| Anderson et al. (28) | RCT | n = 295 (completers: n = 211); mean age: not provided; female: 58% (n = 171); Hispanic/Latino: 76% (n = 223); Spanish speakers: 58% (n = 172) | United States | Telehealth, 12 months | IG: usual care plus weekly, biweekly, or monthly telephonic disease management calls CG: usual care | English and Spanish | A1C | Baseline A1C |
|
| Arora et al. (29) | RCT | n = 128 (completers: n = 92); mean age: 50.7 years; female: 64% (n = 82); Hispanic/Latino: 87% (n = 112); Spanish speakers: 72% (n = 92) | United States | mHealth, 6 months | IG: two daily text messages promoting self-care and medication adherence CG: usual care | English and Spanish | A1C | None |
|
| Dang et al. (30) | Pilot | n = 41 (enrolled: n = 69); mean age: 72.0 years; female: not provided; Hispanic/ Latino: 15% (n = 6) | United States | Telemedicine, 9 months | Telephone-based, in-home patient monitoring messaging device with care coordination and educational materials | English | A1C | None |
|
| Fortmann et al. (31) | RCT | n = 126 (completers: n = 113); mean age: 48.4 years; female: 75% (n = 94); Hispanic/Latino: 100% (n = 126); Spanish speakers: 92% (n = 116) | United States | Telehealth and mHealth, 6 months | IG: ≤3 daily motivational, educational, and/or call-to-action text messages; telephone calls if hyperglycemic, hypoglycemic, or no glucose value provided for 1 week CG: usual care | English and Spanish | A1C, FBG | Age, sex |
|
| Frosch et al. (32) | RCT | n = 201 (completers: n = 182); mean age: in IG 56.7 years and in CG 54.3 years; female 48% (n = 100); Hispanic/Latino: 56% (n = 113) | United States | Telehealth and digital health, 6 months | IG: 24-minute DVD video and booklet with ≤5 telephone coaching sessions with bilingual nurse educator (2.5 hours maximum total coaching time) CG: 20-page brochure | English and Spanish | A1C | None |
|
| Heisler et al. (34) | RCT | n = 188 (completers: n = 176); mean age: in IG 51.0 years and in CG 52.0 years; female: 71% (n = 133); Hispanic/Latino: 57% (n = 107) | United States | Telehealth and digital health, 6 weeks | IG: 1- to 2-hour session with community health worker using iDecide and two follow-up phone calls CG: print materials | English and Spanish | A1C | Baseline health literacy |
|
| Jackson et al. (35) | Experimental | n = 38 (enrolled: n = 40, optional extension: n = 29; optional extension completers: n = 19); median age: 56 years; female: 55% (n = 21); Hispanic/Latino: 100% (n = 38) | United States | mHealth, 3 months with optional 3-month extension | One to three daily educational, motivational, and community resource/event text messages related to diabetes self-management; reply texts with ability to text the Latina health educator and receive responses, remote monitoring, and care management Optional extension: educational and supportive text messages | Spanish | A1C | None |
|
| Jiwani et al. (36) | Clinical demonstration project | n = 62 (a 3 months: n = 36, at 6 months: n = 52, at 12 months: n = 61); mean age: 67.6 years; female: 8% (n = 5); Hispanic/Latino: 58% (n = 36) | United States | Telehealth, 6 weeks | Pedometer; initial (goal-setting, healthy food, benefits of walking) and follow-up face-to-face visits; weekly telephone calls related to walking and step counts | English* | A1C | None |
|
| Khanna et al. (50) | RCT | n = 75 (completers: n = 49); mean age: in IG 51.0 years and in CG 53.0 years; female: 41% (n = 31); Hispanic/Latino: 100% (n = 75); Spanish speakers: 100% (n = 75) | United States | Telehealth, 12 weeks | IG: 10-minute informational video related to risks of uncontrolled type 2 diabetes, benefits of low-glycemic diet, and study protocol, plus automated telephone nutrition support and feedback on entered dietary information consumed in the past 24 hours CG: 10-minute informational video | Spanish | A1C | None |
|
| Lange et al. (51) | Quasi-experimental randomized trial | n = 426 (enrolled: n = 640); mean age: in IG 53.8 years and in CG 52.8 years; female: 69% (n = 292); Hispanic/Latino: 100% (n = 426); Spanish speakers: 100% (n = 426) | Chile | Telehealth, 15 months | IG: average of six telephone calls lasting for an average of 10 minutes; telephone counseling for diabetes self–management by nurses trained in motivational interviewing CG: usual care | Spanish | A1C | Baseline A1C, years with diabetes |
|
| Lorig et al. (37) | Randomized reinforcement | n = 387 (completers: n = 300); mean age: 52.1 years; female: 62% (n = 239); Hispanic/Latino: 100% (n = 387); Spanish speakers: 100% (n = 387) | United States | Telehealth, 18 months | IG: Spanish Diabetes Self-Management Program plus 15 monthly automated calls; content included self-assessment of diabetes management skills, two 90-second vignettes about diabetes, and an invitation to leave a message CG: Spanish Diabetes Self-Management Program group sessions | Spanish | A1C | Baseline A1C, demographic variables (not specified) |
|
| Mayes et al. (38) | Feasibility | n = 16 (enrolled: n = 19); mean age: 51.0 years, female: 81% (n = 13); Hispanic/Latino: 100% (n = 16) | United States | Telehealth, telemedicine, and digital health, 3.5 years | Promatoras, home glucose monitoring over the Internet, communication via phone and e-mail, and audio and video interviews | English and Spanish | A1C | None |
|
| Millan-Ferro et al. (39) | RCT | n = 307 (completers: n = 240); mean age: 55.2 years; female: 55% (n = 169); Hispanic/Latino: 88% (n = 269) | United States | Telehealth and telemedicine, 5 months | IG: informational booklet related to type 2 diabetes management and A1C monitoring plus A1C Now device measurements completed at home at months 1, 2, 4, and 5; telephone call with nurse practitioner after each A1C Now measurement related to treatment plans CG: informational booklet | English and Spanish | A1C | None |
|
| Myers et al. (40) | Pilot | n = 22 (enrolled: n = 29, A1C post-test n = 12); mean age: in IG 56.6 years and in CG 58.7 years; female: 55% (n = 12); Hispanic/Latino: 23% (n = 5) | United States | Telemedicine or telehealth, 3 months | IG 1: weekly (month 1) to biweekly (months 2 and 3) video visits with endocrinologist, digital tablet with Bluetooth blood pressure monitor, scale, and pulse oximeter uploaded data daily, and daily medication reminders IG 2: monthly telephone calls for 3 months from endocrinologist related to medication, diet, lifestyle, with provider recommendations | English | A1C | None |
|
| Piette et al. (43) | RCT | n = 248 (enrolled: n = 280); mean age: in IG 56.0 years and in CG 53.0 years; female: 59% (n = 146); Hispanic/Latino: 50% (n = 123); Spanish speakers: 26% (n = 64) | United States | Telehealth, 12 months | IG: usual care plus biweekly automated telephone calls with assessment lasting 5–8 minutes, including patient-reported self-monitored blood glucose levels, glycemic control, symptoms, medical care, optional diabetes health tips; weekly nurse assessment with follow-up (based on protocol) via telephone providing diabetes-related information and education CG: usual care | English and Spanish | A1C and serum blood glucose | Baseline A1C, insulin use |
|
| Piette et al. (42) | RCT | n = 272 (enrolled: n = 292); mean age: in IG 60.0 years and in CG 61.0 years; female: 3% (n = 8); Hispanic/Latino: 13% (n = 34) | United States | Telehealth, 12 months | IG: biweekly automated telephone calls with assessment lasting 5–8 minutes, including patient-reported self-monitored blood glucose levels, glycemic control, symptoms, medical care, optional health promotion messages; weekly nurse assessment with follow-up (based on protocol) via telephone, providing diabetes-related information and education CG: usual care | English and Spanish | A1C and serum blood glucose | Baseline A1C |
|
| Schillinger et al. (44) | Randomized three-arm trial | n = 339 (completers: n = 305); mean age: 56.1 years; female: 59% (n = 200); Hispanic/Latino: 47% (n = 159); Spanish speakers: 43% (n = 146) | United States | Telehealth, 9 months | IG 1: automated telephone self-management consisting of weekly calls over 9 months; responses triggered automated health education messages and/or nurse phone follow-up; 6–10 minutes to complete IG 2: group medical visits for education and patient activation; 90-minute monthly sessions with 6–10 participants CG: usual care | English, Spanish, and Cantonese | A1C | Baseline A1C |
|
| Shea (45) | RCT | n = 1,665 (completers: n = 1,417); mean age: 71.0 years; female: 63% (n = 1,046); Hispanic/Latino: 35% (n = 586); Spanish speakers: 35% (n = 579) New York City: n = 775; female: 69.5% (n = 539); Hispanic/Latino: 74.1% (n = 574); Spanish speakers: 73.3% (n = 568) Upstate New York: n = 890; female: 57% (n = 507); Hispanic/Latino: 1.3% (n = 12); Spanish speakers: 1.2% (n = 11) | U.S. | Telemedicine and digital health, 12 months | IG: home telemedicine unit provided videoconferencing, remote glucose and blood pressure monitoring with upload, access to patient data, and Web-based messaging with case managers and access to educational website CG: usual care | English and Spanish | A1C | Baseline A1C, clustering group heterogeneity, residual variances |
|
| Vaughan et al. (46) | RCT | n = 89 (completers: n = 83); mean age: in the IG 56.0 years and in the CG 53.9 years; female: 72% (n = 64); Hispanic/Latino: 100% (n = 89); Spanish speakers: 100% (n = 89) | United States | Telehealth or mHealth, 12 months | IG: community health workers called or texted participants (depending on preference) weekly in months 1–6 and bimonthly in months 7–12; content was related to glucose control, medication adherence, and questions or concerns; monthly in-person group sessions for 6 months; low-cost medication access CG: usual care | Spanish | A1C | None |
|
| Walker et al. (47) | RCT | n = 526 (randomized: n = 527, completers: n = 444); mean age: 55.5 years; female: 67% (n = 353); Hispanic/Latino: 22.6% (n = 119) | United States | Telehealth, 12 months | IG: up to 10 calls at 4- to 6-week intervals from health educator; content was personalized and focused on diabetes medication adherence and healthy lifestyle changes CG: print materials | English and Spanish | A1C | Baseline A1C, age, sex, insulin use |
|
| Watterson et al. (48) | Quasi- experimental pilot | n = 210 (completers: n = 178, pilot: n = 50, chart review comparison group: n = 160); age-group: 18–44 years 19% (n = 40), 45–54 years 31% (n = 66), and 55–64 years 50% (n = 104); female: 62% (n = 131); Hispanic/Latino: 69% (n = 145); Spanish speakers 56% (n = 117) | United States | mHealth, 12 weeks | IG: text-messaging program; automated, interactive, and unidirectional text messages related to diabetes self-management and education; three to four text messages per week CG: usual care from chart review | English and Spanish | A1C | Only in subgroup analyses: site, age, sex, primary language, race |
|
| Welch et al. (49) | Pilot | n = 30 (completers: n = 29); mean age: 60.6 years; female: 57% (n = 17); Hispanic/Latino: 27% (n = 8) | United States | Telehealth and telemedicine, 3 months | Electronic pillbox integrated into diabetes remote home monitoring system; nurse interventionists received monitoring data and contacted by phone at scheduled time points | English | A1C | None |
|
| Overweight/obesity outcomes | |||||||||
| Godino et al. (33) | RCT | n = 404 (completers: n = 341); mean age: 22.7 years; female: 70% (n = 284); Hispanic/Latino: 31% (n = 125) | United States | Telemedicine, digital health, and mHealth or only digital health, 24 months | IG 1: six modules, including Facebook, mobile apps, text messaging, emails, website with blog posts, technology-mediated health coaching sessions (≤10 sessions of 5–15 minutes in length); instructed to use ≥1 modality ≥5 times/week over 24 months IG 2: Website access to general health and wellness information, general weight loss information, and quarterly newsletters via e-mail; participants encouraged to interact with the website weekly | English | Weight | Sex, ethnicity, college education |
|
| Patrick et al. (41) | RCT | n = 65 (completers: n = 52); mean age: 44.9 years; female: 80% (n = 52); Hispanic/Latino: 25% (n = 16) | United States | Telehealth and mHealth, 4 months | IG: personalized text and small-picture messages sent two to five times per day, printed materials, monthly telephone calls with health counselor CG: monthly printed materials | English | Weight | Baseline weight, sex, age |
|
| Pérez Ewert et al. (52) | RCT | n = 70 (completers: n = 65); mean age: 52.8 years; female: 66% (n = 46); Hispanic/Latino: 100% (n = 70) | Chile | Telehealth and mHealth 6–9 months | IG: counseling via telephone calls and text messages related to knowledge on prediabetes prevention and control, physical activity, and healthy diet and self-monitoring equipment CG: usual care, self-monitoring equipment | Spanish | Weight | None |
|
Language not specified; assumed to be English because of inclusion of both Hispanic and non-Hispanic adults. CG, control group; IG, intervention group.
EHIs
Nine studies consisted of only a telehealth intervention (28,36,37,42–44,47,50,51), three included only mHealth (29,35,48), and one used only telemedicine (30). The remaining studies included a combination of EHI, including three with telehealth and mHealth (31,41,52), two with telehealth and telemedicine (39,49), two with telehealth and digital health (32,34), and one each with telemedicine and digital health (45); telehealth, telemedicine, and digital health (38); telemedicine, mHealth, and digital health (33); telehealth or telemedicine (40); and telehealth or mHealth (46). Table 3 summarizes significant findings by EHI type.
Significant Findings by EHI Type
| EHI Type | Studies, n | Significant Findings, n |
|---|---|---|
| Type 2 diabetes outcomes | ||
| Telehealth | 9 | 4 |
| Telemedicine | 1 | 0 |
| mHealth | 3 | 3 |
| Telehealth and telemedicine | 2 | 2 |
| Telehealth and digital health | 2 | 2 |
| Telehealth and mHealth | 1 | 1 |
| Telehealth or telemedicine | 1 | 0 |
| Telehealth or mHealth | 1 | 1 |
| Telemedicine and digital health | 1 | 1 |
| Telehealth, telemedicine, and digital health | 1 | 1 |
| Overweight/obesity outcomes | ||
| Telehealth and mHealth | 2 | 1 |
| Telemedicine, mHealth, and digital health or digital health only | 1 | 1 |
| EHI Type | Studies, n | Significant Findings, n |
|---|---|---|
| Type 2 diabetes outcomes | ||
| Telehealth | 9 | 4 |
| Telemedicine | 1 | 0 |
| mHealth | 3 | 3 |
| Telehealth and telemedicine | 2 | 2 |
| Telehealth and digital health | 2 | 2 |
| Telehealth and mHealth | 1 | 1 |
| Telehealth or telemedicine | 1 | 0 |
| Telehealth or mHealth | 1 | 1 |
| Telemedicine and digital health | 1 | 1 |
| Telehealth, telemedicine, and digital health | 1 | 1 |
| Overweight/obesity outcomes | ||
| Telehealth and mHealth | 2 | 1 |
| Telemedicine, mHealth, and digital health or digital health only | 1 | 1 |
The length of the interventions ranged from 6 weeks (34,36) to 3.5 years (38), with a mean length of 9.8 ± 8.7 months. One study had a 3-month EHI with an optional 3-month extension (35), and another had an EHI that ranged in length from 6 to 9 months (52). Table 4 shows the number of significant findings by EHI length.
Significant Findings by Intervention Length
| EHI Length | Studies, n | Significant Findings, n |
|---|---|---|
| Type 2 diabetes outcomes | ||
| 6 weeks | 2 | 2 |
| 3 months | 5 | 3 |
| 5 months | 1 | 1 |
| 6 months | 4 | 4 |
| 9 months | 2 | 0 |
| 12 months | 6 | 5 |
| 15 months | 1 | 0 |
| 18 months | 1 | 0 |
| 3.5 years | 1 | 1 |
| Overweight/obesity outcomes | ||
| 4 months | 1 | 1 |
| 6–9 months | 1 | 0 |
| 24 months | 1 | 1 |
| EHI Length | Studies, n | Significant Findings, n |
|---|---|---|
| Type 2 diabetes outcomes | ||
| 6 weeks | 2 | 2 |
| 3 months | 5 | 3 |
| 5 months | 1 | 1 |
| 6 months | 4 | 4 |
| 9 months | 2 | 0 |
| 12 months | 6 | 5 |
| 15 months | 1 | 0 |
| 18 months | 1 | 0 |
| 3.5 years | 1 | 1 |
| Overweight/obesity outcomes | ||
| 4 months | 1 | 1 |
| 6–9 months | 1 | 0 |
| 24 months | 1 | 1 |
The 3-month EHI with an optional 3-month extension is included in both type 2 diabetes 3-month and 6-month outcomes.
A majority of studies (88%) conducted follow-up data collection at conclusion of the EHI (28–33,35,37,38,40–43,45,49–52) or soon after (i.e., 1 month [39], 1.5 months [34], and 3 months [44] after the EHI). Data collection for one study ranged between immediately post-intervention and 9 months after the EHI (48), and only one investigated long-term changes in outcomes at 10.5 months (36). One study only provided preliminary findings after 6 months for a 12-month EHI (46).
Approximately half of the studies (52%) provided the EHI in both English and Spanish (28,29,31,32,34,38,39,42–45,47,48), and the remaining studies provided the EHI only in English (24%) (30,33,36,40,41,49) or only in Spanish (24%) (35,46,50–52). Table 5 provides the number of significant findings by EHI language.
Significant Findings by Intervention Language
| EHI Language | Studies, n | Significant Findings, n |
|---|---|---|
| Type 2 diabetes outcomes | ||
| English or Spanish | 13 | 11 |
| English only | 4 | 2 |
| Spanish only | 5 | 2 |
| Overweight/obesity outcomes | ||
| English only | 2 | 2 |
| Spanish only | 1 | 0 |
| EHI Language | Studies, n | Significant Findings, n |
|---|---|---|
| Type 2 diabetes outcomes | ||
| English or Spanish | 13 | 11 |
| English only | 4 | 2 |
| Spanish only | 5 | 2 |
| Overweight/obesity outcomes | ||
| English only | 2 | 2 |
| Spanish only | 1 | 0 |
Nine studies compared the EHI with usual care (28,29,31,42,43,45,46,48,51), five did not include a comparison group (30,35,36,38,49), and two compared different EHIs (33,40). One study compared the EHI, a nonelectronic intervention (group medical visits), and usual care (44).
Ten studies included one or more subgroup analyses, which investigated changes in outcomes based on baseline A1C (28,30,35,39,42,45,46). Depending on the study, these analyses looked at outcomes for those with a baseline A1C <7, 7–9, and >9%; ≥7%; ≥7.4 and ≥7.9% for those ≥65 years of age; ≥8%; ≥9%; <9 and ≥9%; or >10 vs. ≤10%. Some studies included subgroup analyses for Spanish speakers (29,43), Hispanic/Latino adults (30), age (≤70 vs. >70 years), engagement in EHI (intervention response rate ≥64.5 vs. <64.5%) (48), site (New York City or upstate New York) (45), and baseline A1C at the site level (New York City ≥7% and upstate New York ≥7%) (45). None of the studies investigating overweight/obesity included subgroup analyses.
Type 2 Diabetes
Twenty-two studies investigated the impact of an EHI on type 2 diabetes outcomes (28–32,34–40,42–51), all of which included A1C as an outcome. One study also included FBG (31), and two studies also included serum blood glucose (42,43), of which neither reported whether participants were fasting. The total number of participants included across the 22 studies was 5,691, with 3,327 female (58%) and 3,202 Hispanic/Latino participants (56%).
Telehealth was used in 77.3% of studies (28,31,32,34,36–40,42–44,46,47,49–51), followed by telemedicine (27.3%) (30,38–40,45,49), mHealth (22.7%) (29,31,35,46,48), and digital health (18.2%) (32,34,38,45). EHI types were offered alone, in combination, and/or as an option. Table 3 provides the number of significant findings by EHI type.
EHI length ranged from 6 weeks (36) to 3.5 years (38) with a mean length of 9.5 ± 8.6 months. Table 4 provides the number of significant findings by EHI length. Thirteen studies provided the EHI in both English and Spanish (28,29,31,32,34,38,39,42–45,47,48), five only in Spanish (35,37,46,50,51), and four only in English (30,36,40,49). Table 5 provides the number of significant findings by EHI language.
Fifteen of the 22 studies (68%) (29,31,32,34–36,38,39,42,43,45–49) demonstrated significant improvements in A1C for the sample and/or in subgroup analyses. The total combined sample of adults with significant improvements in A1C was 3,886 with 47.4% (n = 1,842) Hispanic/Latino adults. Findings demonstrated that A1C significantly improved for the intervention group (IG) in eight studies (32,34–36,38,39,46,49). Reductions in A1C ranged from −0.4 to −2.4% with a mean reduction of −0.90 ± 0.75%. Three studies (45–47) demonstrated a significant difference in A1C improvements for the IG compared with the control group (CG) for the sample and in one study (29) that included a subgroup analysis for Spanish speakers (mean difference −0.52 ± 0.41%, range −0.18 to −0.98%). Two studies (29,35) were not included in both mean calculations because they provided median values rather than means.
Three studies demonstrated significantly lower A1C for the IG compared with the CG, including for the total sample (31), Spanish speakers (43), and in another study (42) that analyzed participants with baseline A1C ≥8 and ≥9% separately (mean difference between IG and CG −0.90 ± 0.28%, range −0.5 to −1.1%). In another study, the authors conducted a subgroup analysis based on engagement with the EHI during the intervention and found that participants who engaged more with the EHI (response rate ≥64.5%) had a significant decrease in A1C compared with less engaged participants (response rate <64.5%) (mean difference −2.23%) (48). However, there were no significant findings related to A1C improvements for the total sample in either study with a subgroup analysis.
One study demonstrated that A1C was maintained for the IG but significantly increased in the CG, with significant differences in A1C between the IG and the CG (51). In the one study with FBG as an outcome, there were no significant differences or reductions in FBG (31). Out of the two studies with serum blood glucose as an outcome (42,43), one demonstrated significantly lower serum blood glucose in the IG compared with the CG (43) even though there were no significant differences in A1C. In the studies by Frosch et al. (32) and Heisler et al. (34), there were significant reductions in A1C for both the IG and the CG; however, there were no significant differences between the IG and CG A1C reductions. The only study that examined outcomes more than once post-intervention (36) demonstrated that A1C improvements persisted 10.5 months after the intervention.
Overweight/Obesity
Three studies investigated the effects of an EHI on overweight/obesity, and all included weight as the outcome of interest (33,41,52). The studies included a total of 539 participants, of whom 382 were female (71%) and 211 were Hispanic/Latino (39%). The types of EHI reported in the overweight/obesity studies included telehealth and mHealth (41,52) and telemedicine, mHealth, and digital health (33). Table 3 provides the number of significant findings by EHI type. The EHI length ranged from 4 to 24 months with a mean length of 12.3 ± 10.4 months. Table 4 provides the number of significant findings by EHI length. Two studies provided the EHI in English only (33,41) and one in Spanish only. Table 5 provides the number of significant findings by EHI language.
Two of the three studies (33,41) demonstrated a significant reduction in weight (66.7%) in the IG compared with the CG. However, one of those studies only demonstrated significant decreases in weight for the IG compared with the CG at 6 and 12 months during a 24-month intervention (33). In addition, both the IG and CG included an EHI, and the authors did not test for within-group changes. The total combined sample of adults with significant improvements in weight was 469 with 30.1% (n = 141) Hispanic/Latino adults.
Study Quality Assessment
Quality assessments of each study can be found in Table 6. Overall, the study quality was moderate, reporting 65.9% of items with a mean score of 17.80 ± 3.5 of 27 possible points. None of the studies reported all items, and the most items included in any study was 24 (34). Studies demonstrated the lowest quality on external validity criteria, and only 11 of 25 studies reported a power analysis. On the reporting subscale, the average study reported 8.76 of 11 items (79.6%), with reporting of 3.88 (64.7%) for the six internal validity items.
Quality Index Ratings
| Total Score (27 Possible) | Reporting Score (11 Possible) | External Validity (3 Possible) | Internal Validity Bias (6 Possible) | Internal Validity Selection Bias (6 Possible) | Power (1 Possible) | |
|---|---|---|---|---|---|---|
| Article | ||||||
| Anderson et al. (28) | 18 | 9 | 0 | 4 | 4 | 1 |
| Arora et al. (29) | 17 | 9 | 0 | 3 | 4 | 1 |
| Dang et al. (30) | 13 | 6 | 0 | 4 | 2 | 1 |
| Fortmann et al. (31) | 19 | 10 | 0 | 4 | 5 | 0 |
| Frosch et al. (32) | 22 | 10 | 1 | 4 | 6 | 1 |
| Godino et al. (33)a | 22 | 10 | 0 | 5 | 6 | 1 |
| Heisler et al. (34) | 24 | 9 | 2 | 6 | 6 | 1 |
| Jackson et al. (35) | 14 | 7 | 0 | 4 | 3 | 0 |
| Jiwani et al. (36) | 15 | 8 | 0 | 4 | 3 | 0 |
| Khanna et al. (50) | 19 | 8 | 1 | 4 | 5 | 1 |
| Lange et al. (51)b | 19 | 9 | 1 | 3 | 5 | 1 |
| Lorig et al. (37) | 15 | 8 | 0 | 4 | 3 | 0 |
| Mayes et al. (38) | 8 | 7 | 0 | 1 | 0 | 0 |
| Millan-Ferro et al. (39) | 19 | 10 | 0 | 4 | 5 | 0 |
| Myers et al. (40) | 19 | 9 | 0 | 4 | 6 | 0 |
| Patrick et al. (41)a | 17 | 9 | 0 | 4 | 4 | 0 |
| Pérez Ewert et al. (52)a,b | 17 | 8 | 1 | 3 | 4 | 1 |
| Piette et al. (43) | 20 | 9 | 1 | 5 | 5 | 0 |
| Piette et al. (42) | 20 | 10 | 0 | 5 | 5 | 0 |
| Schillinger et al. (44) | 21 | 10 | 1 | 4 | 5 | 1 |
| Shea (45) | 18 | 9 | 1 | 4 | 4 | 0 |
| Vaughan et al. (46) | 19 | 8 | 1 | 4 | 5 | 1 |
| Walker et al. (47) | 19 | 10 | 0 | 4 | 5 | 0 |
| Watterson et al. (48) | 19 | 10 | 1 | 4 | 4 | 0 |
| Welch et al. (49) | 12 | 7 | 1 | 2 | 2 | 0 |
| Mean ± SD | 17.80 ± 3.48 | 8.76 ± 1.16 | 0.48 ± 0.59 | 3.88 ± 0.97 | 4.24 ± 1.45 | 0.44 ± 0.51 |
| Total Score (27 Possible) | Reporting Score (11 Possible) | External Validity (3 Possible) | Internal Validity Bias (6 Possible) | Internal Validity Selection Bias (6 Possible) | Power (1 Possible) | |
|---|---|---|---|---|---|---|
| Article | ||||||
| Anderson et al. (28) | 18 | 9 | 0 | 4 | 4 | 1 |
| Arora et al. (29) | 17 | 9 | 0 | 3 | 4 | 1 |
| Dang et al. (30) | 13 | 6 | 0 | 4 | 2 | 1 |
| Fortmann et al. (31) | 19 | 10 | 0 | 4 | 5 | 0 |
| Frosch et al. (32) | 22 | 10 | 1 | 4 | 6 | 1 |
| Godino et al. (33)a | 22 | 10 | 0 | 5 | 6 | 1 |
| Heisler et al. (34) | 24 | 9 | 2 | 6 | 6 | 1 |
| Jackson et al. (35) | 14 | 7 | 0 | 4 | 3 | 0 |
| Jiwani et al. (36) | 15 | 8 | 0 | 4 | 3 | 0 |
| Khanna et al. (50) | 19 | 8 | 1 | 4 | 5 | 1 |
| Lange et al. (51)b | 19 | 9 | 1 | 3 | 5 | 1 |
| Lorig et al. (37) | 15 | 8 | 0 | 4 | 3 | 0 |
| Mayes et al. (38) | 8 | 7 | 0 | 1 | 0 | 0 |
| Millan-Ferro et al. (39) | 19 | 10 | 0 | 4 | 5 | 0 |
| Myers et al. (40) | 19 | 9 | 0 | 4 | 6 | 0 |
| Patrick et al. (41)a | 17 | 9 | 0 | 4 | 4 | 0 |
| Pérez Ewert et al. (52)a,b | 17 | 8 | 1 | 3 | 4 | 1 |
| Piette et al. (43) | 20 | 9 | 1 | 5 | 5 | 0 |
| Piette et al. (42) | 20 | 10 | 0 | 5 | 5 | 0 |
| Schillinger et al. (44) | 21 | 10 | 1 | 4 | 5 | 1 |
| Shea (45) | 18 | 9 | 1 | 4 | 4 | 0 |
| Vaughan et al. (46) | 19 | 8 | 1 | 4 | 5 | 1 |
| Walker et al. (47) | 19 | 10 | 0 | 4 | 5 | 0 |
| Watterson et al. (48) | 19 | 10 | 1 | 4 | 4 | 0 |
| Welch et al. (49) | 12 | 7 | 1 | 2 | 2 | 0 |
| Mean ± SD | 17.80 ± 3.48 | 8.76 ± 1.16 | 0.48 ± 0.59 | 3.88 ± 0.97 | 4.24 ± 1.45 | 0.44 ± 0.51 |
Overweight/obesity outcomes.
Spanish studies.
Funding Sources
Funding sources of included studies are described in Table 7. Six of the 25 studies (24.0%) identified industry-related funding (29,31,38,39,41,51), and 83.3% of those studies demonstrated significant improvements in outcomes (29,31,38,39,41). Among the studies focusing on type 2 diabetes–related outcomes, five of the 22 studies (22.7%) indicated that they had industry-related funding (29,31,38,39,51). Four of those five (80%) demonstrated significant improvements in outcomes (29,31,38,39). Of the three studies investigating overweight/obesity-related outcomes (33,41,52), only one (33.3%) included any industry-related funding, and that study demonstrated significant improvements (100%) (41). One study did not identify any sources of funding (30).
Significant Findings by Funding Source
| Article | Funding Source | Significant Improvement | Industry-Related Funding Source* |
|---|---|---|---|
| Anderson et al. (28) | Connecticut Health Foundation | No | No |
| Arora et al. (29) | McKesson Foundation Agile Health purchased TExT-MED program; authors (Drs. Arora and Menchine) were hired by Agile Health after study completion | Yes | Yes |
| Dang et al. (30) | Not provided | No | Unknown |
| Fortmann et al. (31) | McKesson Foundation National Center for Advancing Translational Sciences Investigator-Initiated Study Program of LifeScan, Inc. provided glucose testing meters and strips | Yes | Yes |
| Frosch et al. (32) | Robert Wood Johnson Foundation Foundation for Informed Medical Decision Making National Institute on Aging/National Institutes of Health | Yes | No |
| Godino et al. (33)** | National Heart, Lung, and Blood Institute/National Institutes of Health | Yes | No |
| Heisler et al. (34) | Agency for Healthcare Research and Quality National Institute of Diabetes and Digestive and Kidney Diseases | Yes | No |
| Jackson et al. (35) | Kaiser Permanente Northern California Community Benefit Program | Yes | No |
| Jiwani et al. (36) | Veterans Administration Geriatrics and Extended Care T21 Non-Institutional Long Term Care Initiative The Veterans Administration Office of Rural Health The San Antonio Geriatrics Research, Education and Clinical Center at the South Texas Veterans Health Care System The San Antonio Older Americans Independence Center at the University of Texas Health Science Center at San Antonio | Yes | No |
| Khanna et al. (50) | University of California Institute for Mexico and the United States Visiting Scholar Award University of California Institute for Mexico and the United States and El Consejo Nacional de Ciencia y Tecnologia Collaborative Research Grant Department of Medicine discretionary account The National Institute of Diabetes and Digestive and Kidney Diseases for Diabetes Translational Research at Kaiser Permanente and University of California, San Francisco | No | No |
| Lange et al. (51) | School of Nursing and Department of Family Medicine of the School of Medicine at Pontificia Universidad Catolica De Chile Ministry of Health, Directorate of Health, Education and Care of Minors of the Commune of Puente Alto Service of Metropolitan Health South East ENTEL Call Center S.A. School of Nursing at Ottawa University Quality Improvement Program for Complex Chronic Conditions of the University of Michigan Chilean National Commission for Scientific and Technological Research | No | Yes |
| Lorig et al. (37) | National Institutes of Nursing Research/National Institutes of Health Michigan Diabetes Research and Training Center | No | No |
| Mayes et al. (38) | Pharmaceutical companies provided drugs used for medication adjustments | Yes | Yes |
| Millan-Ferro et al. (39) | Bayer HealthCare LLC provided funding and A1C NOW POC A1C devices | Yes | Yes |
| Myers et al. (40) | Empire Clinical Research Investigator Program | No | No |
| Patrick et al. (41)** | National Cancer Institute Santech, Inc.; author, Dr. Patrick, is co-owner of and receives consulting income | Yes | Yes |
| Pérez Ewert et al. (52)** | National Fund for Health Research and Development, Chile Health area of the Florida Municipal Corporation, Chile (Spanish acronym: COMUDEF) | No | No |
| Piette et al. (43) | Clinical Research Grants Program of the American Diabetes Association Health Services Research and Development Service and Mental Health Strategic Health Group, Department of Veterans Affairs | Yes | No |
| Piette et al. (42) | The Health Services Research and Development Service, Mental Health Strategic Health Care Group, and Quality Enhancement Research Initiative, Department of Veterans Affairs The American Diabetes Association | Yes | No |
| Schillinger et al. (44) | The Commonwealth Fund Agency for Healthcare Research and Quality The California Endowment The San Francisco Department of Public Health The California Healthcare Foundation National Institutes of Health | No | No |
| Shea (45) | Centers for Medicare and Medicaid Services | Yes | No |
| Vaughan et al. (46) | National Institute of Diabetes and Digestive and Kidney Diseases/National Institutes of Health Houston Veterans Affairs Health Services Research Development Center for Innovations in Quality, Effectiveness, and Safety at the Michael E. DeBakey VA Medical Center | Yes | No |
| Walker et al. (47) | National Institutes of Health | Yes | No |
| Watterson et al. (48) | Berkeley Research Impact Initiative by the UC Berkeley Library | Yes | No |
| Welch et al. (49) | McKesson Foundation | Yes | No |
| Article | Funding Source | Significant Improvement | Industry-Related Funding Source* |
|---|---|---|---|
| Anderson et al. (28) | Connecticut Health Foundation | No | No |
| Arora et al. (29) | McKesson Foundation Agile Health purchased TExT-MED program; authors (Drs. Arora and Menchine) were hired by Agile Health after study completion | Yes | Yes |
| Dang et al. (30) | Not provided | No | Unknown |
| Fortmann et al. (31) | McKesson Foundation National Center for Advancing Translational Sciences Investigator-Initiated Study Program of LifeScan, Inc. provided glucose testing meters and strips | Yes | Yes |
| Frosch et al. (32) | Robert Wood Johnson Foundation Foundation for Informed Medical Decision Making National Institute on Aging/National Institutes of Health | Yes | No |
| Godino et al. (33)** | National Heart, Lung, and Blood Institute/National Institutes of Health | Yes | No |
| Heisler et al. (34) | Agency for Healthcare Research and Quality National Institute of Diabetes and Digestive and Kidney Diseases | Yes | No |
| Jackson et al. (35) | Kaiser Permanente Northern California Community Benefit Program | Yes | No |
| Jiwani et al. (36) | Veterans Administration Geriatrics and Extended Care T21 Non-Institutional Long Term Care Initiative The Veterans Administration Office of Rural Health The San Antonio Geriatrics Research, Education and Clinical Center at the South Texas Veterans Health Care System The San Antonio Older Americans Independence Center at the University of Texas Health Science Center at San Antonio | Yes | No |
| Khanna et al. (50) | University of California Institute for Mexico and the United States Visiting Scholar Award University of California Institute for Mexico and the United States and El Consejo Nacional de Ciencia y Tecnologia Collaborative Research Grant Department of Medicine discretionary account The National Institute of Diabetes and Digestive and Kidney Diseases for Diabetes Translational Research at Kaiser Permanente and University of California, San Francisco | No | No |
| Lange et al. (51) | School of Nursing and Department of Family Medicine of the School of Medicine at Pontificia Universidad Catolica De Chile Ministry of Health, Directorate of Health, Education and Care of Minors of the Commune of Puente Alto Service of Metropolitan Health South East ENTEL Call Center S.A. School of Nursing at Ottawa University Quality Improvement Program for Complex Chronic Conditions of the University of Michigan Chilean National Commission for Scientific and Technological Research | No | Yes |
| Lorig et al. (37) | National Institutes of Nursing Research/National Institutes of Health Michigan Diabetes Research and Training Center | No | No |
| Mayes et al. (38) | Pharmaceutical companies provided drugs used for medication adjustments | Yes | Yes |
| Millan-Ferro et al. (39) | Bayer HealthCare LLC provided funding and A1C NOW POC A1C devices | Yes | Yes |
| Myers et al. (40) | Empire Clinical Research Investigator Program | No | No |
| Patrick et al. (41)** | National Cancer Institute Santech, Inc.; author, Dr. Patrick, is co-owner of and receives consulting income | Yes | Yes |
| Pérez Ewert et al. (52)** | National Fund for Health Research and Development, Chile Health area of the Florida Municipal Corporation, Chile (Spanish acronym: COMUDEF) | No | No |
| Piette et al. (43) | Clinical Research Grants Program of the American Diabetes Association Health Services Research and Development Service and Mental Health Strategic Health Group, Department of Veterans Affairs | Yes | No |
| Piette et al. (42) | The Health Services Research and Development Service, Mental Health Strategic Health Care Group, and Quality Enhancement Research Initiative, Department of Veterans Affairs The American Diabetes Association | Yes | No |
| Schillinger et al. (44) | The Commonwealth Fund Agency for Healthcare Research and Quality The California Endowment The San Francisco Department of Public Health The California Healthcare Foundation National Institutes of Health | No | No |
| Shea (45) | Centers for Medicare and Medicaid Services | Yes | No |
| Vaughan et al. (46) | National Institute of Diabetes and Digestive and Kidney Diseases/National Institutes of Health Houston Veterans Affairs Health Services Research Development Center for Innovations in Quality, Effectiveness, and Safety at the Michael E. DeBakey VA Medical Center | Yes | No |
| Walker et al. (47) | National Institutes of Health | Yes | No |
| Watterson et al. (48) | Berkeley Research Impact Initiative by the UC Berkeley Library | Yes | No |
| Welch et al. (49) | McKesson Foundation | Yes | No |
Any funding, supplies, and/or compensation provided by industry.
Overweight-/obesity-related outcomes.
Discussion
The purpose of this systematic review was to determine the effects of EHIs on type 2 diabetes and overweight/obesity-related outcomes in samples containing at least 12% Hispanic/Latino adults living in the Americas from literature published in English and Spanish. Overall, this review found that EHIs demonstrated improvements in both A1C (29,31,32,34–36,38,39,43,45–47,49) and weight (33,41) in a large sample of adults (N = 4,355), nearly half of whom (45.5%, n = 1,983) were Hispanic/Latino. These findings are consistent with previous research from different countries investigating EHIs in samples that included minimal or no Hispanic/Latino adults (18–22).
This review found that mHealth seemed particularly useful. Studies that included only mHealth (29,35,48) or more than one type of EHI including mHealth (31,32,34,38,39,45,49) improved type 2 diabetes outcomes compared with those with only one type of EHI other than mHealth. Furthermore, telehealth demonstrated limited efficacy in improving A1C (36,42,43,47) unless combined with other types of EHIs (31,32,34,38,39,49). All three studies investigating the effect of EHIs on weight included more than one type of EHI (33,41,52) with all three including mHealth, which was the type of EHI missing in the previous review conducted with a focus on racial/ethnic minorities (19).
Overall, the rigor of the available research is relatively modest, impeding best-practice recommendations and improvements in treatment optimization. Most studies in this review compared EHIs to usual care or had no comparison group and lacked comparisons between different EHIs, similar to what has been found in previous reviews including adults with type 2 diabetes or overweight/obesity (18–22). This lack of granularity limits the ability to provide evidence-based recommendations about which specific types of EHI significantly improve outcomes compared with other EHIs and further prevents optimization of EHIs by implementing only the critical components necessary to improve health outcomes. Future research should be conducted to test different EHIs in rigorous trials to determine the most effective types of EHI to improve type 2 diabetes and obesity-related outcomes in Hispanic/Latino adults.
The majority of EHIs were available in Spanish (28,29,31,32,34,35,37–39,42–48,50–52) and demonstrated overall improvements in outcomes (29,31,32,34,35,38,39,42,43,45–48). Furthermore, when participants were provided the option to choose the EHI in English or Spanish, there were a greater number of significant findings (29,31,32,34,38,39,42,43,45,47,48). Approximately 28% of Hispanic/Latino adults in the United States are not fluent in English, and 70% speak a language other than English in the home (53). Offering comfort in terms of intervention language appears crucial to the success of EHIs. It has been documented in face-to-face health care settings that language barriers are associated with less access to medical services, lower adherence to treatments, and poorer health outcomes (54–56).
Most studies included in this review were conducted in the United States (28,29,31,32,34,35,37–39,42–48,50) and published in English. Only two studies that were published in Spanish met inclusion criteria, and both were conducted in Chile (51,52). Although researchers from Mexican government health institutions have encouraged the use of certain eHealth components (i.e., social media platforms) as low-cost tools to address issues in public health nutrition (57), we did not identify studies carried out in this country. The paucity of studies from Mexico and other Latin American countries prevents generalizability of recommendations regarding EHIs for Hispanic/Latino populations living outside of the United States. As previously noted (57), and confirmed by this review, the creation of an official commission and national resource allocation are needed to expand research in this field of study and lead the development of policies to ultimately leverage the potential that EHIs have to improve health care access across Latin America and reach those limited by distance, resources, or their respective health care system’s shortcomings (57), who otherwise may not have the opportunity to receive care.
Funding should also be considered when investigating the quality of the available evidence linking EHIs with health outcomes. Governmental agencies and foundations were the most common sources of funding for the studies in this review. However, all studies with support or resources provided by interested funders from industry (29,31,38,39,41) demonstrated significant improvements in outcomes, except for one (51). This pattern is consistent with one previous investigation pertaining to a different field of study on how potential conflicts of interest may introduce bias into study findings (23). Significant improvements in health outcomes from these studies should be interpreted with caution. Replication studies should be conducted with nonindustry funding and investigators who do not have conflicting interests.
Strengths and Limitations
This is the first systematic review conducted to synthesize the evidence published in English and Spanish to determine the efficacy of EHIs to improve type 2 diabetes or overweight/obesity among Hispanic/Latino adults. A systematic and comprehensive approach was used during data extraction following established a priori parameters. This is the first systematic review to consider the presence of potentially conflicting interests in original EHI research.
Limitations included that meta-analysis could not be reliably conducted because of the heterogeneity among studies, including the different combinations of EHIs intervention components, length of the interventions, and outcomes. However, our review yielded summary results whose directionality is generally consistent with that observed in previous studies that meta-analyzed original research from diverse populations (18–22). Technology is constantly evolving, rendering many of the intervention apps, software, or other technological components rapidly obsolete, which limits the ability to translate specific findings into current practice settings. The largest subgroup of Hispanic/Latino adults living in the United States is from Mexico (58); however, the only published studies identified outside of the United States were conducted in Chile (n = 2). This threatens external validity, limiting the generalizability of the review beyond the United States.
This systematic review demonstrated that EHIs improve type 2 diabetes and overweight/obesity outcomes in Hispanic/Latino adults. Programs offering more than one type of EHI and those offered in English and Spanish improve health outcomes more than those with only one type of EHI, with the exception for mHealth, and those offered only in English or only in Spanish.
Technology is a Force of Change that can enhance efforts to improve health outcomes for those with type 2 diabetes and overweight/obesity (5); however, greater efforts are needed from researchers, policymakers, and corporate partners to successfully carry out more EHI-related investigations with timely dissemination of findings, given that technology evolves so rapidly. Future research should be conducted to compare the efficacy of different types of EHI to improve type 2 diabetes and overweight/obesity outcomes, including studies conducted in Mexico and other Spanish-speaking countries in the Americas. Additionally, research should be evaluated for bias related to potential conflicts of interest. Practitioners should recommend EHIs to adult populations, including Hispanic/Latino adults, through programs that include multiple EHI strategies and refrain from recommending programs that only include the EHI of telehealth.
Article Information
Acknowledgments
The authors acknowledge and thank the J. William Fulbright Foreign Scholarship Board, Council for International Exchange of Scholars, Institute of International Education, U.S., and Comexus Fulbright García-Robles, Mexico, as well as Dr. Simón Barquera and the National Institute for Public Health, Mexico, for hosting R.E.L. as a U.S. Fulbright-García Robles Core Scholar to Mexico in 2019–2020.
FUNDING
This research was supported by a grant awarded to E.L. from the National Heart, Lung, and Blood Institute of the National Institutes of Health (L30 HL159808), the Instituto Nacional de Salud Publica in Mexico, and the Arizona State University Center for Health Promotion and Disease Prevention. This project was also supported by scholarships from the Mexican Council of Science and Technology, Fundación México en Harvard, and Harvard University, provided to K.M.
Duality of Interest
No potential conflicts of interest relevant to this article were reported.
Author Contributions
All authors contributed to article screening and data extraction. E.L., A.L.O., K.M., and R.E.L. synthesized and wrote this manuscript. A.L.O. and K.M. conducted all searches. R.E.L. conceptualized the review. All authors reviewed and edited the manuscript. E.L. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Prior Presentation
Some of the information in this article was presented in abstract form at the Society of Behavioral Medicine’s 43rd Annual Meeting & Scientific Sessions in Baltimore, MD, on 7 April 2022.
