This is an exploratory, cross-sectional survey designed to explore the associations between self-reported adherence to antihypertensive medications and potential MoBCs for adherence (including self-efficacy, self-regulation, behavioral automaticity, and HTN knowledge). This was a fully remote trial. Participant consent and survey assessments were conducted using REDCap, an approved secure data collection tool [28, 29]. Participants were compensated $50 for participation. The protocol for this trial was approved by the Northwell Health Institutional Review Board in November 2024.

We recruited 101 participants who were prescribed antihypertensive medication. Inclusion criteria can be found in Table 1. Patients were required to be diagnosed with HTN, have a current prescription for antihypertensive medication, and have a recent outpatient contact between December 2023 and January 2025. We excluded non-English speaking individuals to improve the validity and reliability of all study measures (some of which have not been validated in other languages).

With support from the Northwell Health Quantitative Intelligence team, we utilized the electronic health record (EHR) to identify over 3,500 participants who were potentially eligible for the trial. These participants were contacted directly using the contact information provided in the EHR, namely email and phone number. Recruitment for the trial occurred between February and March of 2025. Potentially eligible patients were randomly selected and contacted via a brief email explaining the nature of the study and directing them to a REDCap survey with further information. The REDCap survey contained a more detailed overview of study requirements, a copy of the consent form for review, and contact information for study personnel.

Patients who indicated their interest in this REDCap survey were directed to a brief screening survey to confirm their current HTN diagnosis, that they are currently prescribed a hypertensive medication, and that they had contact with their provider between December 2023 and January 2025.

Individuals deemed ineligible for the study based on their responses to this survey were immediately notified through the REDCap software. Eligible individuals were automatically directed to a digital consent form to review and sign in REDCap.

Adherence to antihypertensive medication was measured using the Hill-Bone Compliance to High Blood Pressure Therapy Scale (HB-HBP) [30]. The HB-HBP is a 14-item survey measure scored on a 4-point Likert scale rated from 4 “None of the time” to 1 “All of the time”. The HB-HBP contains a 9-item subscale used to measure self-reported adherence to antihypertensive/high blood pressure medication. Questions asked “How often do you decide NOT to take your high blood pressure medication?” and “How often do you forget to get your prescriptions filled?” Scores were summed to generate a total score, with higher scores indicating better adherence. For the purposes of this analysis, individuals who scored below the lowest quartile cut-off point on the HB-HBP medication adherence subscale were defined as being nonadherent. The HB-HBP also contains two other scales related to high blood pressure therapy: 1) a 2-item scale measuring adherence to medical appointments and 2) a 3-item scale measuring dietary intake of salty foods. As these two other scales are associated with higher blood pressure levels and have shown good reliability/validity with the medication adherence sub-scale on the HB-HBP [30], these additional scales were also examined in exploratory analyses.

We have identified 4 potential MoBCs for the current study: self-efficacy, treatment self-regulation, behavioral automaticity, and HTN knowledge. Self-efficacy, defined as beliefs about one’s ability to successfully perform a behavior, has been identified as a key MoBC for many behavior change theories [31], and has been found to be integral to medication adherence [32–34], especially to antihypertensive medications [35]. Low medication adherence self-efficacy, defined as a low level of belief in an individual’s ability to consistently take medication as prescribed, is a potential modifiable reason for nonadherence. Self-regulation, defined as the ability of an individual to regulate their own behavior, is also a key MoBC for a variety of health outcomes [36], including medication adherence [37, 38]. Behavioral automaticity, defined as the degree to which an individual engages in a behavior automatically and without thinking [39, 40], has also been found to be associated with adherence to antihypertensives [41]. Behavioral automaticity is also more commonly known as “habit”, i.e., a behavior performed automatically. HTN knowledge is defined as an individual’s awareness of the symptoms of HTN, the potential consequences of HTN, and how HTN can be treated. Low levels of HTN knowledge about medications have previously been associated with nonadherence to antihypertensive medications [21, 42–44].

Analysis for the primary aim outcome: The primary aim for this study is to examine the associations between medication adherence measured using the HB-HBP and four potential MoBCs: Self-efficacy, treatment self-regulation, behavioral automaticity, and HTN knowledge. First, we compared scores on these measures between individuals with low adherence and high adherence using independent samples t-tests. Participant characteristics were also compared between low and high adherence groups using an independent samples t-test for continuous variables and Pearson Chi-squared tests for categorical variables. We then examined the association between MoBC scores and continuous HB-HBP adherence scores using median regression analysis. A median regression model was utilized to provide a more robust comparison due to the small sample size and potentially non-linear distribution of medication adherence. We utilized participant characteristics as covariates in these regression analyses. Finally, we conducted a multivariate median regression model with all MoBCs and covariates included to identify if any MoBCs are associated with self-reported antihypertensive adherence, controlling for all other MoBCs.

The sample of 101 participants had a mean age of 61.7 years (SD = 13.1 years), was 59.4% female (n = 60), 66.3% White (n = 67), 7.9% Hispanic (n = 8), and 99.0% insured (n = 100). Full sample characteristics can be found in Table 2. In the sample, there were 17 participants (16.8%) who self-reported low levels of adherence, defined by scoring ≤ 33 on the 9-item medication adherence scale of the HB-HBP (below the lowest cut-point for the lowest quartile). This score corresponds to either reporting taking medication “None of the time” on a single item or “Most of the time” on three items for the HB-HBP. Participants who self-reported low levels of adherence were younger, more likely to be female, and less likely to identify as White than those with high adherence (Table 2).

Comparisons of MoBC by adherence groups showed that individuals who self-reported low levels of adherence also reported lower scores on the MASES [mean (SD) = 2.68 (0.53)] relative to individuals with high levels of adherence [mean (SD) = 3.28 (0.28); independent sample t-test p < 0.001; Table 2]. Individuals with self-reported low levels of adherence also had lower scores on HTN knowledge than [mean (SD) = 7.56 (0.81)] relative to individuals with high levels of adherence [mean (SD) = 8.06 (1.09); independent sample t-test p = 0.045; Table 2]. The distribution of MoBC scores by adherence group can be found in Figure 1.

In regression analyses, self-efficacy was associated with continuous self-reported medication adherence scores on the HB-HBP in the unadjusted model [coefficient (95% CI) = 5.20 (4.51 to 7.55)], the covariate adjusted model [coefficient (95% CI) = 4.64 (3.43 to 7.49)], and the model adjusted for all other MoBCs [coefficient (95% CI) = 4.84 (3.30 to 7.37); Table 3]. HTN knowledge was also associated with continuous medication adherence in the unadjusted regression model [coefficient (95% CI) = 0.50 (0.22 to 1.51); Table 3] and remained significant in covariate-adjusted and multivariate models. This suggests that self-efficacy and HTN knowledge are uniquely associated with self-reported adherence after adjustment for covariates and other MoBCs. All other MoBCs were not significantly associated with continuous medication adherence scores at any level of adjustment.

Analysis of the associations between reasons for medication adherence and self-reported adherence was not statistically significant for independent samples t-tests (Table 4). However, in bivariate correlation analyses examining the association between continuous HB-HBP medication adherence scores and reasons for medication adherence, adherence was associated with participant beliefs (r = –0.20, p = 0.04), participant concerns about side effects (r = –0.31, p = 0.002), practical access barriers (r = –0.21, p = 0.04), and unintentional adherence/forgetfulness (r = –0.36, p < 0.001; Table 5). Only intentional reasons for nonadherence were not significantly associated with continuous HB-HBP scores. In addition, reasons for medication adherence were associated with medication adherence self-efficacy. For example, concerns about side effects were strongly negatively associated with self-efficacy (r = –0.48, p < 0.001; Table 5).

In addition to these correlations, we found many significant associations between MoBC measures. For example, self-efficacy was strongly associated with autonomous self-regulation (r = 0.39, p < 0.001; Table 5). The full correlation matrix for all study measures can be found in Table 5. It should be noted that due to multiple comparisons, any inferences drawn from these correlation analyses should be interpreted cautiously.

The current study has several strengths. Firstly, we did not solely recruit individuals with problems adhering to antihypertensive medications. Instead, we recruited all individuals prescribed antihypertensive medication. This allows our study to examine MoBC levels in individuals with different self-reported adherence. In addition, we were able to obtain a preliminary, exploratory estimate of the prevalence of antihypertensive nonadherence within our health system, though this estimate may not reflect the full population of our health system. Secondly, we examined multiple potential MoBCs simultaneously. As a result, we can examine the association between each MoBC and adherence individually and in combination.

However, it should also be noted that this study has several limitations. Firstly, we collected data on a relatively small sample of patients who were taking antihypertensive medication. The sample was a majority female, predominantly white, and nearly all patients were insured. It is unlikely that these results will be representative of the full population of patients treated with antihypertensive medication in our health system. It should also be noted that we conducted a remote, digital survey trial. This would likely create a bias towards participants with high levels of digital literacy. We also compensated participants for completing the survey, which could also potentially introduce bias. Secondly, the current study has a cross-sectional design, which precludes longitudinal analyses of the associations between antihypertensive adherence and potential MoBCs. Further, cross-sectional findings prevent the determination of causality. If MoBCs are truly important targets for interventions, then changes in MoBCs should be associated with proportional changes in health behaviors. We cannot demonstrate these causal effects in this study. Though we plan to utilize the findings from the current study to justify future longitudinal clinical trials, we did not have the resources to run such a trial at this time. Finally, the current trial utilizes a self-report measure of medication adherence, which could potentially be subject to bias. However, it should be noted that medication adherence research often relies on self-report adherence measures [13]. It should also be noted that only 17% of the sample were nonadherent to medications, suggesting most individuals participating did not have high levels of nonadherence to antihypertensive medications. Further, non-adherence was classified based on the lowest quartile of responses in this particular sample. Other samples will likely have different cut-offs using the same approach. Therefore, the dichotomous analyses comparing low and high adherence levels should be interpreted cautiously. It is also possible that shared method variance may result from utilizing a self-report adherence measure in conjunction with self-reported MoBCs, though it is uncertain how this might enhance or dilute the associations shown in the current study [65].

The findings of the current exploratory study reinforce previous literature showing that MoBCs are associated with adherence to antihypertensive medications. Further, our study supports prior findings showing that self-efficacy for adherence is strongly associated with self-reported adherence behavior. HTN knowledge was also found to be associated with self-reported adherence. As a result, we believe that interventions targeting self-efficacy for medication adherence and HTN knowledge are potentially useful targets for MoBCs for behavioral interventions to improve antihypertensive adherence. However, we also believe that adherence to antihypertensive medications is a complex behavior that is likely to be influenced by multiple MoBCs simultaneously. We also recognize that the magnitude of the association between a particular MoBC and antihypertensive adherence may differ based on each individual and the potential causes of that individual’s behavior. Future research should examine the benefits of tailored interventions targeting specific mechanisms of adherence and potentially utilize self-reported reasons for nonadherence to guide and tailor the intervention approach.