ABSTRACT
Health literacy and hypertension control are more limited in rural U.S. residents relative to metropolitan counterparts. Contemporary hypertension guidelines advocate for health education and home blood pressure monitoring (HBPM) to advance hypertension management. We conducted a preliminary assessment of the effect of health literacy on utilization of a virtual coaching agent, a computerized animation to converse with patient users, to promote HBPM. We recruited individuals from primary care practices in rural Pennsylvania; measured health literacy with the Brief Health Literacy Screen (BRIEF) and the Newest Vital Sign (NVS); and monitored virtual coach interactions and frequency of HBPM for 26 weeks. Participants (n = 59; age 58 ± 15 years, 59% female, 71% < bachelor's degree) had 1.03 ± 1.05 agent interactions and 5.4 ± 3.6 HBPM sessions/week over 1487 total participant‐weeks. Virtual coach use was associated with greater odds of achieving the target HBPM frequency of 4 readings per week (Odds Ratio [OR] per interaction, 1.10 [95% Confidence Interval [CI]: 1.01–1.20]). This association was moderated by health literacy as measured by the BRIEF (interaction p = 0.01); with a greater magnitude among those with limited/marginal literacy (OR 1.31 per interaction, 95% CI: 1.10–1.57). NVS did not significantly moderate the association (interaction p = 0.12). In this preliminary cohort, use of a virtual coach was associated with higher adherence to HBPM in individuals with limited health literacy as measured by the BRIEF. Our results suggest that the frequency of virtual coach interactions is strongly associated with improvement in HBPM adherence among individuals with limited health literacy compared with those with adequate health literacy.
Clinical Trial Registration: NCT05546931
Keywords: chronic disease self‐management, health literacy, home blood pressure monitoring, hypertension
Abbreviations
- AOR
Adjusted Odds Ratio
- BRIEF
Brief Health Literacy Screen
- COM‐B
Capability Opportunity Motivation–Behavior
- HBPM
Home Blood Pressure Monitoring
- NVS
Newest Vital Sign
1. Introduction
The rural health divide in the U.S. is well established. Individuals residing in rural regions experience greater poverty and lower educational attainment than metropolitan counterparts [1]. They additionally experience higher rates of both limited health literacy and hypertension prevalence [2, 3]. Contemporary guidelines and professional society consensus statement advocate for implementation of home blood pressure monitoring (HBPM) to promote hypertension self‐management, contributing to improved blood pressure control, and increase patient self‐efficacy [4, 5]. Rural individuals with hypertension may specifically benefit from HBPM given its capacity to reduce geographic obstacles to care [6, 7].
Significant barriers limit implementation of HBPM despite its demonstrated utility. Patient‐level challenges to HBPM include education on proper technique, numeracy to interpret readings, finances, and adherence to monitoring [8, 9]. Structural factors may likewise contribute to limited implementation of HBPM, such as clinics’ lacking sufficient staff, equipment or infrastructure to provide behavioral reinforcement, and integration of HBPM results into routine clinical care [8]. Nevertheless, HBPM has broad and scalable potential to meet the profound population‐level challenge of limited blood pressure control [4, 5].
As novel approaches to support HBPM are essential, we developed a virtual coaching agent, a lifelike digital health application to promote health behaviors. This technology precedes the current digital avatars described as chatbots, while incorporating synthetic speech and providing focused health counseling [10, 11]. Virtual coaches deliver education, behavioral prompts, and personalized feedback, extending the reach of healthcare providers beyond clinic visits. A virtual coach has additional capacity to address health literacy, essential to hypertension self‐management and related to medication adherence, blood pressure control, self‐management behaviors, and HBPM engagement. We developed a virtual coach with the objective of promoting HBPM in rural individuals with poorly controlled hypertension. Here we present preliminary results describing the association of coach use with HBPM and its modification by health literacy.
2. Methods
2.1. Study Design and Participants
Participants were recruited from rural family and internal medicine ambulatory clinics affiliated with a large, regional health care system in western Pennsylvania. Eligibility criteria were age ≥18 years; systolic blood pressure ≥140–199 or diastolic blood pressure ≥90 mm Hg, determined from an average of the two most recent ambulatory measurements within the past 18 months with one reading in the prior 6 months; and not currently pregnant and without intention to become pregnant during the 12‐month study. Following consent and randomization, participants underwent a baseline interview and were mailed (1) an electronic blood pressure cuff with capacity for upload to a digital cloud for storage and retrieval; (2) a study smartphone preloaded with the virtual coach and blood pressure tracking applications; and (3) a customized booklet with an orientation to the study, calendar of assessments, and instructions for using the virtual coach and HBPM. Participants received standardized instruction on HBPM as informed by contemporary professional society guidelines and confirmation of their ability to operate study devices [4, 5]. The duration of study participation was 6 months following HBPM training.
2.2. Intervention
The virtual coach intervention (Figure 1) was informed by the Capability Opportunity Motivation—Behavior (COM‐B) Model, a well‐validated, widely used approach with demonstrated effectiveness at achieving a behavior change [12, 13, 14]. We developed the virtual coach curriculum to provide: (1) self‐efficacy for management of hypertension; (2) education about hypertension, its causes, outcomes, and pharmacologic treatment; (3) conduct of HBPM including instructions on measurement, scheduling 4 times weekly, and explanation of reports sent to providers; (4) guidance to address obstacles to adherence to medications for hypertension; (5) advisement on health behaviors (e.g., physical activity, weight loss, stress reduction, adequate sleep) to address hypertension; and (6) preparation for the medical encounter, such as developing questions for health care providers and self‐advocacy. Virtual coach content was informed by patients, clinicians, and professional society guidelines. Use of the virtual coach was measured as the number of interactions per week.
FIGURE 1.
Key features of the virtual coach for hypertension self‐management Lucy. (A) The virtual coach providing an introduction to establish role in supporting blood pressure management. (B) Menu of educational topics related to hypertension. (C) Blood pressure monitoring interface to display two‐week average blood pressure and trend.
2.3. Study Assessments
Assessments at baseline included demographics (age, sex, race, and ethnicity) and the following social factors: (1) educational attainment categorized as high school or less, associate degree, some college, vocational or trade school, bachelor, graduate, professional school degree; (2) annual household income categorized as ≤$19,999, $20,000–$49,999, $50,000–$99,999, or ≥$100,000; (3) and ownership of a smartphone.
We assessed health literacy with two complementary measures: (1) the Brief Health Literacy Screen (BRIEF), a 4‐item instrument (range 4–20) which measures self‐reported health literacy [15], and (2) the Newest Vital Sign (NVS), a 6‐item instrument (range 0–6; 0–1, limited; 2–3, marginal; 4–6, adequate health literacy), an objective measure of health literacy [16]. We dichotomized BRIEF Scores as “Limited or Marginal” (<17) or “Adequate” (≥ 17) and NVS scores as “Less than Adequate” (<4) or “Adequate” (≥ 4) based on prior validated studies [17, 18].
2.4. Study Outcome: HBPM
The primary outcome was the quantity of engagement with HBPM for each 7‐day period of study enrollment. Participants were advised to measure their blood pressure 4 times weekly, on 2 mornings and afternoons of their choosing. This schedule was based on expert recommendations [4, 5, 19] to obtain morning and evening BP and the goal of achieving a reliable average blood pressure longitudinally while reducing participant attrition.
2.5. Statistical Analysis
2.5.1. Primary Analysis
We summarized continuous variables by their mean and standard deviation and categorical variables by their distributions. Using t‐test for continuous variables and Fischer's exact test for categorical variables, we tested differences in cohort characteristics among participants with adequate compared to those with limited health literacy as assessed by BRIEF. We defined weekly HBPM continuously and dichotomously as less than or ≥4 measures per 7‐day period. We assessed the association between engagement with the virtual coach (our independent variable) and HBPM (our dependent variable) in multivariable‐adjusted regression analyses.
We examined the effect of health literacy on the association between virtual coach use and HBPM by fitting two separate multivariable‐adjusted binomial mixed‐effects models. We added a multiplicative interaction term between weekly app interactions and health literacy measures (NVS and BRIEF). We chose this modeling approach to account for the binary nature of the outcome (HBPM <4 or ≥4 readings per week) and the longitudinal data structure with repeated weekly measurements nested within participants.
A random intercept for participant identifier was included in the model to account for between‐participant variability in adherence to HBPM. Continuous predictors were standardized (scaled by standard deviation) to facilitate model convergence. Resulting coefficients and confidence intervals were back‐transformed to their original units (e.g., adjusted odds ratio [OR] per 1‐year increase in age) for interpretation. All models were adjusted for time (study week), age, educational attainment (dichotomized as < or ≥ bachelor's degree), and mobile phone ownership (yes/no). A p‐value of <0.05 was considered statistically significant.
2.6. Sensitivity Analysis
We performed a sensitivity analysis using a threshold of ≥6 readings per week, based on current professional society consensus, which recommend HBPM for at least 3 days per week with both morning and evening measurements [4, 5]. This analysis was conducted to ensure our findings remain robust when applying these more stringent adherence standards. We further conducted a sensitivity analysis including sex, given its relevance to health behaviors and outcomes, and a p‐value of <0.05 was considered statistically significant. All analyses were conducted using R (Version 4.5.0) with the lme4 and gtsummary packages.
3. Results
The cohort consisted of 61 individuals (age 57.6 ± 14.7 years, 59% female sex, 92% white race, 29% ≥bachelor's degree), of whom 59 participants provided sufficient data for inclusion in the analysis. The remaining 2 participants did not complete a full week of HBPM and were consequently removed from this analysis. Over the 1487 participant‐weeks analyzed, participants engaged in a mean of 1.03 ± 1.05 interactions with the virtual coach agent and 5.4 ± 3.6 HBPM readings per week. The mean adherence rate to the weekly HBPM goal (≥4 readings) was 62.4%±33.7%, with a median of 76.9% (IQR: 30.8%–92.3%). Adherence trends over the study period, stratified by health literacy, are shown in Figure 2. While adherence generally declined over the study period for all participants, individuals with limited or marginal health literacy maintained a higher mean number of weekly readings compared to those with adequate health literacy. As shown by Figure 2, both groups sustained near or above the target threshold of ≥4 readings per week for the majority of the duration of the study.
FIGURE 2.
Trends in HBPM Adherence by Health Literacy Level.
This line graph illustrates the mean number of HBPM readings per week over the study period. Data are stratified by BRIEF Health Literacy scores: Adequate (blue) and Limited or Marginal (red). Shaded areas represent the 95% confidence intervals. The dotted horizontal line represents a mean of 6 readings per week, while the dashed horizontal line indicates a threshold of 4 readings per week.
More frequent interactions with the virtual coach were associated with greater odds of achieving the HBPM adherence target (OR 1.10 per interaction, 95% CI: 1.01–1.20, p = 0.02) in multivariable‐adjusted models. We identified a significant interaction with health literacy (BRIEF) and the association between virtual coach and HBPM use (interaction p = 0.01; interaction OR 1.28, 95% CI: 1.05–1.55). Specifically, among individuals with limited health literacy as assessed by the BRIEF, use of the virtual coach was associated with a 1.3‐fold increased odds of achieving the target HBPM frequency of ≥4 readings per week (OR 1.31 per interaction, 95% CI: 1.10–1.57, p<0.01). When we included sex as a covariate in a sensitivity analysis, we identified no difference in the relation of limited health literacy (as measured by the BRIEF) and blood pressure measurement (OR 1.31 per interaction, 95% CI: 1.10–1.57). Figure 3 graphically presents the interaction between health literacy as assessed by the BRIEF and the relationship between total number of weekly interactions with the coach and HBPM. As demonstrated by the red line in the figure, corresponding to participants with limited or marginal health literacy, the likelihood of achieving the target HBPM ≥4 readings per week increased directly with number of weekly coach sessions. In contrast, we did not observe a significant interaction between health literacy as assessed by the NVS and virtual coach use (interaction OR 1.17, 95% CI: 0.96–1.42, p = 0.12).
FIGURE 3.
Association between weekly virtual coach interactions and probability of ≥4 HBPM readings per week, stratified by Brief Health Literacy Screen (BRIEF) dichotomized as “limited or marginal” (red line) or “adequate” (blue line) health literacy. Dotted lines indicate 95% confidence intervals for each estimate. Among participants with limited or marginal health literacy, the probability of achieving ≥4 HBPM readings rises sharply with increased number of coach interactions, approaching 100% after approximately 10 interactions per week. Participants with adequate health literacy are 50%–60%, even at higher interaction levels.
In a sensitivity analysis defining the weekly HBPM goal as ≥6 readings (Table 1), the mean adherence rate was 39.6% ± 32.8%. Multivariable‐adjusted main effects models demonstrated that virtual coach use remained significantly associated with achieving ≥6 readings (OR 1.11, 95% CI: 1.04–1.18, p = 0.001). Furthermore, the interaction between health literacy (BRIEF) and virtual coach use remained highly significant (interaction p = 0.003; interaction OR 1.24, 95% CI: 1.08–1.43) with increased odds of achieving the target HBPM among individuals with limited or marginal health literacy (OR 1.29 per interaction, 95% CI: 1.14–1.47, p<0.001). The association was not significant for those with adequate health literacy (OR 1.04 per interaction, 95% CI: 0.97–1.11, p = 0.24). Table 2 summarizes the results of the primary analysis compared to the sensitivity analysis.
TABLE 1.
Virtual Coach Interactions and HBPM Adherence: Primary versus Sensitivity Analysis Comparison.
| Metric |
Original analysis (≥4 readings per week) |
p‐value |
Sensitivity analysis (≥6 readings per week) |
p‐value |
|---|---|---|---|---|
| Main effect: App interactions (overall cohort) |
OR 1.10 (95% CI: 1.01–1.20) |
0.021 |
OR 1.11 (95% CI: 1.04–1.18) |
0.001 |
| Interaction p‐value (health literacy * app interactions) |
OR 1.28 (95% CI: 1.05–1.55) |
0.013 |
OR 1.24 (95% CI: 1.08–1.43) |
0.003 |
| Effect in limited/marginal group (BRIEF < 17) |
OR 1.31 (95% CI: 1.10–1.57) |
0.003 |
OR 1.29 (95% CI: 1.14–1.47) |
<0.001 |
| Effect in adequate group (BRIEF ≥ 17) |
OR 1.02 (95% CI: 0.94–1.11) |
0.57 |
OR 1.04 (95% CI: 0.97–1.11) |
0.24 |
Note: Adjusted for study week, age, educational attainment, and mobile phone ownership
TABLE 2.
Cohort characteristics stratified by BRIEF ≥17 and <17.
| Characteristic | Overall, N = 61 | Adequate N = 40 | Limited or Marginal N = 21 | p‐value |
|---|---|---|---|---|
| Age, years | 57.6 ± 14.7 | 57.5 ± 15.6 | 57.9 ± 13.2 | >0.9 |
| Sex | 0.027 | |||
| Female | 36 (59.0%) | 28 (70.0%) | 8 (38.1%) | |
| Male | 25 (41.0%) | 12 (30.0%) | 13 (61.9%) | |
| Ethnicity | 0.3 | |||
| Hispanic or Latino | 2 (3.3%) | 2 (5.0%) | 0 (0.0%) | |
| Not Hispanic or Latino | 58 (95.1%) | 38 (95.0%) | 20 (95.2%) | |
| Refused/Unknown | 1 (1.6%) | 0 (0.0%) | 1 (4.8%) | |
| Race | 0.2 | |||
| Black | 4 (6.6%) | 1 (2.5%) | 3 (14.3%) | |
| White | 56 (91.8%) | 38 (95.0%) | 18 (85.7%) | |
| Other | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| Refused/Unknown | 1 (1.6%) | 1 (2.5%) | 0 (0.0%) | |
| Education | 0.005 | |||
| High School or Less | 17 (27.9%) | 8 (20.0%) | 9 (42.9%) | |
| Associate degree, Some College, Vocational or Trade School | 26 (42.6%) | 15 (37.5%) | 11 (52.4%) | |
| Bachelor, Graduate, Professional School Degree | 18 (29.5%) | 17 (42.5%) | 1 (4.8%) | |
| Income | 0.4 | |||
| Less than $50,000 | 22 (36.1%) | 12 (30.0%) | 10 (47.6%) | |
| $50,000 or more | 33 (54.1%) | 24 (60.0%) | 9 (42.9%) | |
| Refused | 6 (9.8%) | 4 (10.0%) | 2 (9.5%) | |
| Mobile phone owners | 55 (90.2%) | 36 (90.0%) | 19 (90.5%) | >0.9 |
| Newest Vital Sign (NVS) score | 0.005 | |||
| Mean ± SD | 4.1 ± 1.8 | 4.6 ± 1.6 | 3.2 ± 1.8 | |
| Median (Q1, Q3) | 5.0 (3.0, 5.0) | 5.0 (4.0, 6.0) | 3.0 (3.0, 5.0) | |
| NVS category | 0.007 | |||
| Less than adequate (NVS <4) | 18 (29.5%) | 7 (17.5%) | 11 (52.4%) | |
| Adequate (NVS ≥4) | 43 (70.5%) | 33 (82.5%) | 10 (47.6%) | |
| Brief Health Literacy Screening Tool (BRIEF) score | 17.1 ± 2.8 | 18.8 ± 1.2 | 13.9 ± 1.8 | <0.001 |
Note: Data are presented as mean ± SD for continuous variables and number (%) for categorical variables. Percentages are based on the total sample (N = 61). P‐values are calculated from t‐test (continuous) or Fischer's exact test (categorical).
4. Discussion
We assessed the association between use of a virtual coach and adherence to HBPM among rural individuals with chronic hypertension. We further examined how health literacy modified the relationship between virtual coach use and HBPM. Our results, based on a limited‐sized sample, showed that increased frequency of virtual coach use was associated with a higher likelihood of participants achieving a weekly HBPM goal articulated as HBPM goal ≥4 readings per week. We observed that this positive association between frequency of virtual coach use and HBPM adherence was especially significant among participants with limited literacy, as measured by the BRIEF.
Notably, the study cohort demonstrated strong engagement with HBPM throughout the study period, with the majority of participants consistently meeting or exceeding the expected frequency of monitoring. We conducted a sensitivity analysis using a threshold of ≥6 readings per week, as suggested by professional society consensus statement and guidelines [4, 5]. The sensitivity analysis yielded results consistent with our primary findings, demonstrating that the association between virtual coach interactions and HBPM adherence for individuals with limited health literacy remained robust regardless of adherence threshold. Smartphone‐based coaching has the potential to support HBPM by incorporating multilevel strategies that educate, reinforce and guide self‐management, and reduce barriers to consistent adherence to HBPM.
Hypertension is a complex chronic condition that demands sustained patient engagement and education. Widespread implementation of HBPM remains suboptimal [20, 21, 22], despite evidence for its cost‐effective effect on hypertension control and advocacy by contemporary hypertension guidelines. A key question is how to increase HBPM engagement and its longitudinal adherence. We appreciate a virtual coach as a scalable strategy to bridge this implementation gap; a virtual coach has capacity to provide plain‐language education, graphic demonstrations of HBPM, and personalized feedback to improve patient understanding and motivation for chronic disease self‐management. Our team's prior work using a virtual agent affirmed that such approaches can support medication adherence and reduce health care utilization [10, 11].
Virtual coaches demonstrate potential for broader translation into routine hypertension care and individualized support independent of location or clinic access. Rural populations may experience limited access to healthcare and health‐related educational resources, potentially accompanied by social isolation that may exacerbate hypertension [1]. A virtual agent may provide the practical, accessible support that alleviates social and structural barriers to care.
Various mobile health interventions have been employed to support HBPM with incorporation of lifestyle change and medication adherence [23]. Studies in rural adults have largely utilized non coaching mobile applications with improvement in blood pressure control [6, 7]. Prior study evaluated smartphone hypertension coaching interventions in urban adults with uncontrolled hypertension and reported modest improvements in self‐confidence and heterogenous effects on blood pressure [24]. Our program employed the COM‐B behavioral framework to advance motivation and adherence to HBPM. Our study extends the literature on coaching mobile health interventions to advance HBPM by focusing on a rural cohort with a high proportion of individuals with limited education and limited health literacy.
Health literacy is central to effective HBPM and its longitudinal adherence. Successful HBPM requires patients to understand and follow measurement instructions, incorporate monitoring into their routine self‐management, and accurately record and interpret results [25]. Numeracy skills are also critical for correctly reporting and acting on blood pressure readings, and are important for participation in remote or self‐monitored BP programs [26]. Individuals with adequate health literacy are more likely to sustain regular HBPM compared to those with limited health literacy [27].
Individuals with limited health literacy often struggle to understand medical terms and instructions [28]. A virtual coach addresses these barriers by using plain language, visual aids, and audio instructions to explain HBPM concepts and demonstrate correct use of a blood pressure monitor. In this study, we assessed health literacy with 2 distinct measures to capture different dimensions of patient capability and whether they modify the effectiveness of a virtual coach to promote HBPM. We employed the BRIEF, which measures self‐perceived health literacy or self‐reported competence in managing health‐related tasks, relying on individuals’ self‐assessment rather than direct demonstration of literacy‐related skills [15]. The NVS is a complementary objective assessment of health literacy that evaluates literacy skills (comprehension, numeracy, and the ability to process health information) through performance‐based tasks [16].
We observed that self‐perceived literacy (BRIEF) significantly moderated the association between use of the virtual coach and HBPM. In contrast, the objective functional literacy (NVS) did not. We consider that the BRIEF reflects individuals’ perceived ability to manage health tasks, potentially reflecting self‐efficacy, rather than objective, functional literacy. Tailoring agent content to health literacy levels and specific individual needs was beyond the scope of this endeavor. It is possible that high‐literacy participants found content less engaging, contributing to lower interaction frequency.
4.1. Strengths and Limitations
This study has several strengths. The prospective design enhanced our ability to infer a potential causal relationship between engagement with the virtual coach and HBPM adherence. The coaching intervention adhered to guideline‐based recommendations to promote hypertension self‐management with the multilevel framework informed by the COM‐B model. Our measurement of health literacy with two complementary measures enhanced our determination of how health literacy may interact with the effectiveness of a virtual coach to promote HBPM.
Our study also has noteworthy limitations. First, the generalizability of our findings is limited, as we conducted our study in a rural region of western Pennsylvania. Generalizability is further limited by the demographic composition of our sample, which was predominantly white (92%) and female (59%). These characteristics do not reflect the broader population of individuals with hypertension, particularly in racially and ethnically diverse or urban settings. Statistical power limited by the small sample size included here. Second, the data included here are limited by design and did not include more granular assessment of use of the virtual coach to ascertain which components of the agent may promote HBPM adherence. It is possible, for example, that more extensive use of the agent or engagement with particular content may have varied promotion of HBPM adherence. Third, we recognize that our health literacy measures are screening instruments that do not capture nuanced components of literacy that may influence either engagement with a virtual coach or HBPM. Finally, we included a limited number of covariates in our multivariable‐adjusted model and cannot exclude residual confounding.
5. Conclusion
5.1. Our Findings Suggest That the Frequency of Virtual Coach Interactions is Strongly
Associated with improvement in HBPM adherence among individuals with limited health literacy compared with those with adequate health literacy. The modification of intervention effectiveness by health literacy underscores the importance of tailoring digital health strategies for accessibility to any level of health literacy. This study adds to the growing evidence base supporting the role of mobile health interventions in chronic disease self‐management, especially in populations that experience health literacy barriers.
Funding
This work was supported by NIH/NHLBI awards R01HL160749 and K24HL160527.
Ethics Statement
Approved by the University of Pittsburgh IRB.
Consent
Informed consent was obtained from all participants.
Conflicts of Interest
Brian Kaleida reports a conflict of interest as he is the Chief Executive Officer (CEO) of SimCoach Games. All other authors declare no conflicts of interest.
Acknowledgments
This work was supported by NIH/NHLBI awards R01HL160749 and K24HL160527. The authors are solely responsible for the design and conduct of this study, all study analyses, as well as the drafting and editing of the manuscript and its final contents.
Data Availability Statement
The data underlying this article will be shared on reasonable request to the corresponding author.
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Associated Data
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Data Availability Statement
The data underlying this article will be shared on reasonable request to the corresponding author.