Hypertension, or high blood pressure, is a major risk factor for cardiovascular disease (CVD), stroke, renal disease, and dementia.1 Controlling blood pressure requires adherence to prescribed pharmacological and non-pharmacological therapy to reduce the risk of adverse events.2 Adherence is defined as the

Extent to which a person’s behavior–taking prescribed medication, following a diet, and/or executing lifestyle changes-corresponds with agreed-upon recommendations from a health care provider.2

Poor medication adherence, a pervasive patient-level factor associated with not achieving blood pressure targets, is associated with disease progression, avoidable hospitalization, morbidity, and mortality.1 Adherence to drug therapy lowers blood pressure, and reduces the risk for CVD and death.3–5

Approximately 50% to 80% of patients prescribed antihypertensive medications demonstrate suboptimal adherence5 and 30–50% of United States (US) adults do not adhere to drug therapy. Also, 33–69% of medication-related hospitalization in the US are due to poor medication adherence, which costs almost $100 billion a year.6 Nonadherence may occur when the patient does not initiate a new prescribed antihypertensive medication, implement therapy as prescribed by the provider, or persist with treatment as prescribed. Nonadherence undermines the benefits expected from evidence-based drug therapy and ultimately contributes to poor CVD outcomes.

Several interrelated factors influence adherence to drug therapy, including significant pill burden, complex drug regimen, cost of medications, side effects of multidrug antihypertensive regimens, poor patient-provider relationship, and clinical inertia.7,8 Devising appropriate interventions to improve adherence to therapy first requires assessing adherence and the reasons or factors affecting adherence.9 Clinicians often rely on clinical judgment in their assessment of adherence rather than using screening tools and validated instruments for assessing adherence.10

Adherence is measured with direct methods, such as directly observed therapy and measurement of drug metabolites or biomarkers, and indirect methods, such as patient self-reports, questionnaires, pill counts, rates of prescription refills, and electronic medication monitors.6,11 Each method has advantages and disadvantages and differs in accuracy, practicality, cost, and burden.12 There is no consensus on the gold standard for measuring medication adherence, and no single method meets all criteria. However, patient self-report is considered a simple and effective method to assess adherence.13,14

The Hill-Bone Compliance to High Blood Pressure Therapy (HBCHBPT) Scale is an indirect method to assess adherence to hypertension therapy via self-report.15 It is a 14-item scale that assesses patient behaviors for three behavioral domains of hypertension treatment (ie, the three (3) sub-scales): Appointment Keeping (3 items), Diet [salt intake] (2 items), Medication Adherence (9-items).15 The content validity of the original scale was assessed by a relevant literature review and an expert panel, which focused on cultural sensitivity and appropriateness of the instrument for low literacy.15 Internal consistency reliability and predictive validity of the scale were evaluated using two community-based samples of hypertensive adults enrolled in clinical trials of high blood pressure care and control. The standardized Cronbach’s alpha (α) for the total scale were 0.74 and 0.84, and the average interitem correlations of the 14 items were 0.18 and 0.28, respectively. In the initial study, high compliance scale scores, indicating better adherence, predicted significantly lower blood pressure levels and better blood pressure control.

This systematic review aims to synthesize evidence on the use of the HBCHBPT Scale, including psychometric properties, utility in diverse patient populations, and directions for future clinical use and research.

Materials and Methods

Search Strategy

We conducted a comprehensive literature review of databases with the help of an information specialist and according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines.16 We assessed the literature for studies that have used the HBCHBPT Scale.

A search strategy was derived from combinations of keys words that describe the HBCHBPT scales, for instance, “Hill-Bone”, “Hill Bone Medication Adherence Scale”, “Hill-Bone Compliance to High Blood Pressure Therapy”, separated with the “OR” Boolean operator and the search was conducted in the following databases: CINAHL, PubMed, PsychInfo, Embase, and Web of Science. Final searches were conducted on May 18, 2020. We briefly assessed the articles returned at each search to make sure they were relevant and that the articles included the terms in the search strategy. Identified articles were imported into Covidence®,17 for title and abstract screening.


For this review, we included studies that used the HBCHBPT Scale or its subscales in research. This includes original studies in which the HBCHBPT Scale was used to measure an outcome, or methodological studies involving translations and validations of the scale. Additionally, eligible articles had to be peer-reviewed, published in English, and available in full text, although the scale could be administered in the participant’s native language. Articles that only referenced the scale but did not necessarily administer the scale were excluded. Other reviews, study protocols, editorials, and commentaries were excluded.

Data Quality Assessment

The methodological quality of each article was assessed using the Quality Assessment of Diagnostic Accuracy Studies Criteria (QUADAS-2), which allows for transparent rating of bias and assessment of the applicability of primary diagnostic accuracy studies.18 The domains include patient selection, index test, reference standard, flow, and timing. Each of the articles and risk of biased and applicability was judged as “low”, “high”, or “unclear”. Articles were included if judged as “high” and were excluded if the judgment for both bias and applicability assessment were “high”. For articles judged as “unclear”, the two independent reviewers held discussions about these articles, and a third reviewer resolved final judgment and conflicting opinions.

Data Extraction and Synthesis

After title and abstract screening, we obtained full-text versions of screened articles. Two independent authors reviewed the articles for full-text eligibility based on the inclusion criteria. Eligible studies were assessed for quality using the Assessment of QUADAS-2. Data extracted included: author and publication year, country, study setting, sample size, disease, population and setting, age of participants, language, subscales used, method of administration, scoring system, and psychometric properties. Finally, we synthesized the extracted data following the PRIMSA guidelines, and summarized and presented the results in tables.


Search and Study Selection

Following a systematic search in 5 literature databases, 342 articles were identified, 134 duplicates, leaving 208 de-duplicated articles. These 208 articles were assessed for title and abstract eligibility screening, and 112 records were excluded based on the eligibility criteria. We retrieved full-text versions for articles eligible for full-text review and excluded 46 articles due to the following reasons: Abstract only (n=31), Hill-Bone scale not administered (n=7), full-text not available (n=2), review articles (n=4), dissertation study (n=1), and article not published in English (n=1). Full-text eligibility review yielded 50 articles included in the qualitative narrative synthesis. The PRISMA flowchart is shown in Figure 1.

Figure 1 PRISMA flow chart.

Notes: PRISMA figure adapted from Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. Creative Commons.16

Characteristics of Studies

Fifty studies were included in this review and are presented in Table 1, together with the study design, region, population, setting, scale length (full scale versus subscale), method of administration, scoring system, and psychometric properties. A total of 14,364 participants were represented for all the included citations where the sample size ranged from 9 to 2870. Forty-four (44) studies focused on hypertension, two on type 2 diabetes mellitus (T2DM), three on mental or cognitive impairment, inflammatory bowel disease (IBD), Alzheimer’s, and exacerbation of non-specified conditions. Regarding regional comparison, 22 studies were conducted in the Americas, 11 studies in Europe, eight in the Eastern Mediterranean region, five in Africa, two in Southeast Asia, and two in the Western Pacific Region. Twenty-five studies administered the HBCHBPT scale in its original language (English). The remaining studies translated the scale into Polish (n=6), Persian (n=3), German (n=2), Korean (n=2), Arabic (n=2), Chinese (n=2), Xhosa (n=2), Portuguese (n=1), Greek (n=1), Turkish (n=1), Malay (n=1), Afrikaans and Oshiwamb (n=1). All articles included adult patients; only two studies (4%) administered the instrument to caregivers. Most participants were sourced from the community setting, where data collection took place in primary care clinics, and 14 studies were conducted in hospital-based settings. Four papers did not specify a language, and these studies were conducted in countries with a non-English de facto official language.

Table 1 General Characteristics of Included Studies (N=50)

Of 50 records, 26 were self-administered (1 computer-assisted), and 30 were interviewer-administered (2 via telephone). Additionally, 38 studies used the full scale, while the remainder used specific subscales: medication taking (n=10), salt intake (n=1), and appointment keeping (n=1). Scoring systems were adapted from the original scale, where the following ranges were reported: 9–36 and 14–56. A four-point Likert scale was used in 49 studies where higher scores indicated better adherence. One study used reverse coding on a five-point Likert scoring method. The average Cronbach’s α coefficient was 0.75 (range: 0.43–0.85). In the 21 cases where Cronbach’s α measures were not reported, most authors endorsed internal consistency of the original scale.

Randomized Controlled Trials That Measured Adherence with the HBCHBPT Scale

Table 2 features six randomized controlled trials related to hypertension and diabetes that used the HBCHBPT Scale. The results suggest that in adults with hypertension and diabetes, health behaviors and health outcomes improved specifically related to medication adherence for glycemic and BP control. A 4-arm RCT of 123 community-dwelling adults showed significant treatment compliance differences between the control and intervention groups (P < 0.0001).50 Five RCTs focused on education and technology as methods for improving adherence to treatment and saw favorable outcomes in the intervention groups. Technology tools featured text messages, a self-care application, and a self-management website. The education sessions focused on two main behaviors: medication taking and diet management. Only two studies measured objective outcomes: blood pressure36 and hemoglobin A1c.38 The remaining four studies used psychometric scales such as the HBCHBPT to measure certain self-care behaviors. Although the educational interventions were effective, they focused more on the “medication taking” and “proper diet” items versus the “appointment keeping” domain.

Table 2 Randomized Controlled Trials Measuring Adherence in Hypertension (n=4) and Diabetes (n=2) Treatment


The Hill-Bone Compliance to High Blood Pressure Therapy Scale is one of the most widely used indirect measurements of adherence to hypertension therapy.68 Our systematic review aimed to synthesize evidence on the use of the scale, including its psychometric properties and utility in various patient populations. Although the majority of the articles in this systematic review applied HBCHBPT scales to patients with hypertension, the scales have also been used with other disease conditions such as diabetes, Alzheimer’s’ disease, and inflammatory bowel disease. The Cronbach’s α for studies that reported this statistic ranged from 0.62 to 0.88. In addition, we observed variation in the use of the 14-item scale or the 9-item medication adherence subscale. The HBCHBPT scales have also been used in randomized clinical trials to measure improvements in medication adherence and the prediction of improved blood pressure measurements and control. The high predictive validity of the scale is a distinct strength of this scale and the reason for its popularity.

Hypertension is a leading independent risk factor for cardiovascular diseases, renal disease, stroke, and death.1 Self-report measures of hypertension are strongly associated with adverse cardiac events, including myocardial infarction, coronary heart disease death, and stroke.69 However, there are limitations, such as recall bias and social desirability. One of the most important factors associated with hypertension control is medication non-adherence, which increases the risk of severe cardiovascular disease and death from 50–80%.70 About half of the persons with cardiovascular diseases or major risk factors (ie, hypertension) have poor adherence,71 and only about half of persons with hypertension achieve blood pressure control. The HBCHBPT scale was developed as an indirect method of measuring hypertension medication adherence, including items on medication adherence, appointment keeping, and diet. The brief instrument, which can be administered by self-administration or interview in less than five minutes, is designed to augment care in the clinical setting by assessing for self-reported adherence to hypertension therapy, facilitating the planning of individualized hypertension care, and research design adherence interventions.15

A subsequent version of the original scale, the Hill-Bone Medication Adherence Scale (HBMAS), has recently been derived from the full scale to specifically measure medication adherence.72 The newer instrument includes 9 items assessing medication adherence in the original HBCHBPT scale. Several studies have demonstrated the reliability of the 9-item medication adherence subscale.21,33,73,74

This systematic review revealed that the scales’ utility has expanded from assessing adherence to hypertension and/or cardiovascular disease medication to include other conditions such as diabetes, Alzheimer’s, and inflammatory bowel disease. This is important as medication non-adherence is equally vital in chronic conditions such as stroke, diabetes, and Alzheimer’s disease. For instance, medication adherence in patients with stroke is 64%,75 and about 45% in patients with diabetes,76 about 17–100% in older adults with Alzheimer’s dementia.77 In inflammatory bowel disease, non-adherence has been found to range from 7%-72%78 and varies between 17–74% for chronic kidney disease.79

The reproducibility of the scales in various settings and populations is notable This review showed that the scale was administered in different populations, including adults with various chronic diseases, cognitive impairments, older adults, and African American and Asian populations. Based on these diverse populations, the lowest Cronbach’s α observed among the studies validating the scales in other populations was 0.62, while the highest was 0.88. This range of Cronbach’s α is desirable as extremely high internal consistency ≥ 0.95 reduces sensitivity and room for capturing changes due to an intervention, hence a less desirable feature of an intervention evaluation measure.80,81 This range of Cronbach’s α was compared to that of the full HBCHBPT scale, which was 0.74 and 0.84, and the average interitem correlations of the 14 items of 0.18 and 0.28, respectively.15 In this review, although studies have reported relatively high reliability, validation studies are needed to assess the scales’ appropriateness in various other populations. Additionally, the dearth of data on the optimal recall period limits and the lack of a gold-standard self-report measure limits the process of selecting a medication adherence scale,71 including the HBCHBPT scale. Beyond the HBCHBPT scale, the most widely used validated scales to measure medication adherence are the Morisky Medication Adherence Scale (MMAS-8),82 the Morisky-Green-Levine test,83 the Medication Adherence Self-Efficacy Scale (MASES)84 and The Brief Medication Questionnaire.85

There are various reasons to choose the Hill-Bone scales for use in research and practice. The ease of use and brevity of the scales may have contributed to their administration in various settings. This review showed that the HBCHBPT scales were used in primary health centers, specialty clinics, hospitals, and community health centers. This has significant implications for the clinical use of the scales. Its performance in this myriad of clinical settings suggests stability in its ability to accurately estimate self-reported medication adherence regardless of clinical setting or patient population.

Furthermore, the HBCHBPT scale demonstrated adequate sensitivity to capture any change due to intervention with varying degrees of intensity. The early investment in efforts to establish the predictive validity of the scale by the original developers resulted in valuable measures in both descriptive and intervention research settings.

In addition, the scale permits self-administration; in this review, most of the articles reported self-administration, and fewer were interviewer-administered. This has significance for using these scales in low- and middle-income countries (LMICs) where medication adherence is notably lower due to various factors, including weaker health infrastructure and healthcare access inequality. Thus, there is a need to evaluate medication adherence appropriate to LMICs where the burden of chronic diseases is increasing, and challenges with medication utilization are higher.86 Finally, the scale may be obtained free of charge upon request for permission for their use; this would further improve the scales’ utility, particularly in low-resource settings. This paper offers a global perspective on the use of the scales and how they contribute to addressing global healthcare challenges related to treatment adherence, hamper optimal healthcare outcomes. In particular, this review highlights the usability, translatability, and scalability of the HBCHBPT scales across multiple countries, populations, and cultures. This review also shows that the HBCHBPT scales can be administered by various healthcare work cadres, such as community health workers, etc., among diverse populations and in low resources healthcare settings; thus, presenting important evidence that the scales have been used globally to aid clinical decision-making.

Another major strength of the scale is its high clinical utility in personalized care; the scales have been used to guide personalized intervention based on individual adherence types (intentional vs non-intentional). For instance, educational intervention can be provided to people who are intentionally not taking medications due to myths or insufficient knowledge.74 For people who are missing medications due to unintentional reasons (eg, cognitive decline, busy schedule), habit forming (cognitive-behavioral) intervention was applied.74 The HBCHBT scale has an adequate number of items that allow researchers and clinicians to identify the causes of their adherence barriers. Given that the field is moving to precision health paradigm, the ability of the scale to phenotype adherence is critical and can be a basis for precision and personalized intervention, according to psychosocial phenotyping) to improve adherence to high blood pressure treatment regimen.

This study has revealed some weaknesses of the scale. The appointment-keeping and salt intake subscales suffer from relatively low item-to-total correlations or low Cronbach’s α due to low numbers of items in those subscales. To continue to be a comprehensive adherence measure for high blood pressure self-management support programs, those subscales should be considered to add a few theoretically meaningful and behaviorally relevant items.


The reported validity and reliability measures for the HBCHBPT scales continue to vary slightly across settings, highlighting the need for better psychometric properties. Due to the heterogeneity of the data collection methods, analyses, and follow-up times, we could not obtain an overall effect size through a meta-analysis. Studies varied in terms of treatment groups, follow-up times, and outcomes. Moreover, few RCT studies measured medication adherence as an outcome. Despite these drawbacks, our systematic review has some strengths. To our knowledge, this is the first review providing a systematic evaluation of the use of the HBCHBPT scale across different contexts. We have provided contemporary evidence on the scales’ psychometric properties in studies examining different health conditions and behaviors. Translation of the original English version of the HBCHBPT scale into 25 different languages, did not compromise the clinical utility of the scale. We have also demonstrated the versatility of the scale and reach across six different World Health Organization (WHO) regions.


The Hill-Bone Compliance to Blood Pressure Therapy Scale was created through grant funding from the National Institutes of Health (NIH).


Ms Lauren Smulcer reports being the spouse of an active duty Army officer; her spouse receives salary from the federal government as an active duty soldier. The authors report no other conflicts of interest in this work.


1. Tsao CW, Aday AW, Almarzooq ZI, et al. Heart disease and stroke statistics—2023 update: a report from the American heart association. Circulation. 2023;147(8):e93–e621. doi:10.1161/CIR.0000000000001123

2. Carey RM, Aronow WS, Casey DE, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: executive summary: a report of the American College of Cardiology/American heart association task force on clinical practice guidelines. Nnals Inter Med. 2018;168:1524–4563.

3. Follow up Program Cooperative Grou. Five-year findings of the hypertension detection and follow-up program. I. Reduction in mortality of persons with high blood pressure, including mild hypertension. Hypertension detection and follow-up program cooperative group. JAMA. 1979;242:0098–7484.

4. SHEP Cooperative Research Group. Prevention of stroke by antihypertensive drug treatment in older persons with isolated systolic hypertension. JAMA. 1991;265:0098–7484.

5. Elliott WJ. What factors contribute to the inadequate control of elevated blood pressure? J Clin Hypert. 2008;10:1524–6175.

6. Osterberg L, Blaschke T. Adherence to medication. New Engl J Med. 2005;353:1533–4406.

7. van der Laan DM, Elders PJM, Boons C, Beckeringh JJ, Nijpels G, Hugtenburg JG. Factors associated with antihypertensive medication non-adherence: a systematic review. J Human Hypert. 2017;31:1476–5527.

8. Ogungbe O, Himmelfarb CR, Commodore-Mensah Y. Improving medication adherence in cardiovascular disease prevention: what’s new? J Cardiovasc Nurs. 2020;2020:1550–5049.

9. Ogungbe O, Byiringiro S, Adedokun-Afolayan A, et al. Medication adherence interventions for cardiovascular disease in low- and middle-income countries: a systematic review. Patient Prefer Adher. 2021;2021:1177–889X.

10. Marcum ZA, Sevick MA, Handler SM. Medication nonadherence: a diagnosable and treatable medical condition. JAMA. 2013;309(20):2105–2106. doi:10.1001/jama.2013.4638

11. MacLaughlin EJ, Raehl Cl Fau – Treadway AK, Treadway Ak Fau – Sterling TL, Sterling Tl Fau – Zoller DP, Zoller Dp Fau – Bond CA, Bond CA. Assessing medication adherence in the elderly: which tools to use in clinical practice? Drugs Aging. 2005;22:1170–229X.

12. Wagner JH, Justice Ac Fau – Chesney M, Chesney M, et al. Patient- and provider-reported adherence: toward a clinically useful approach to measuring antiretroviral adherence. J Clinl Epidemiol. 2001;54:0895–4356.

13. Kelly MS, Moczygemba LR, Gatewood SS. Concordance of pharmacist assessment of medication nonadherence with a self-report medication adherence scale. J Pharm Pract. 2016;29:1531–1937.

14. Nguyen TM, La Caze A, Fau – Cottrell N, Cottrell N. What are validated self-report adherence scales really measuring?: a systematic review. Br J Clin Pharmacol. 2014;77:1365–2125.

15. Kim MT, Levine DM. Development and testing of the hill-bone compliance to high blood pressure therapy scale. Prog Cardiov Nurs. 2000;2000:0889–7204.

16. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. doi:10.1136/bmj.n71

17. Veritas health innovation; Available from: Accessed September 01, 2023.

18. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Anna Inter Med. 2011;155:1539–3704.

19. Abel WM, Crane PB, McCoy T. Predictors of depression in black women with hypertension. Issu Ment Health Nurs. 2014;35:1096–4673.

20. Al-daken LI, Eshah NF. Self-reported adherence to therapeutic regimens among patients with hypertension. Clin Exp Hypertens. 2017;39(3):264–270. doi:10.1080/10641963.2016.1247164

21. Alsolami F, Hou X-Y, Correa-Velez I. An Arabic instrument to measure medication adherence in Saudi hypertensive patients. Middle East J Fam Med. 2013;11:17–23. doi:10.5742/MEFM.2014.92409

22. Asadullah IS, Ali H, Ul Haq N, Zarak MS, Nasim A. Assessment of medication adherence among hypertensive patients by using hill-bone compliance scale in tertiary care hospitals quetta. Indo Am J Pharm Sci. 2018;5(5):3796–3803. doi:10.5281/zenodo.1248144

23. Boulware LE, Carson KA, Troll MU, Powe NR, Cooper LA. Perceived susceptibility to chronic kidney disease among high-risk patients seen in primary care practices. J Gen Intern Med. 2009;24(10):1123–1129. doi:10.1007/s11606-009-1086-6

24. Chatziefstratiou A, Giakoumidakis K, Fotos NV, Baltopoulos G, Brokalaki H. Scales for assessing medication adherence in patients with hypertension. Br J Nurs. 2019;28(21):1388–1392. doi:10.12968/bjon.2019.28.21.1388

25. Cheong AT, Tong SF, Sazlina SG. Validity and reliability of the Malay version of the hill-bone compliance to high blood pressure therapy scale for use in primary healthcare settings in Malaysia: a cross-sectional study. Malays Fam Physician. 2015;10(2):36–44.

26. Chudiak A, Jankowska-Polańska B, Uchmanowicz I. Effect of frailty syndrome on treatment compliance in older hypertensive patients. Clin Interv Aging. 2017;12:805–814. doi:10.2147/CIA.S126526

27. Chudiak A, Uchmanowicz I, Mazur G. Relation between cognitive impairment and treatment adherence in elderly hypertensive patients. Clin Interv Aging. 2018;13:1409–1418. doi:10.2147/CIA.S162701

28. Dennison CR, Peer N, Steyn K, Levitt NS, Hill MN. Determinants of hypertension care and control among peri-urban Black South Africans: the HIHI study. Ethn Dis. 2007;17(3):484–491.

29. Dharan DR, Moly KT. Factors influencing compliance to therapeutic regimen among patients with hypertension. Asian J Pharm Clin Res. 2017;10(12):286–289. doi:10.22159/ajpcr.2017.v10i12.21034

30. Etebari F, Pezeshki MZ, Fakour S. Factors related to the non-adherence of medication and nonpharmacological recommendations in high blood pressure patients. J Cardiovasc Thorac Res. 2019;11(1):28–34. doi:10.15171/jcvtr.2019.05

31. Fleig SV, Weger B, Haller H, Limbourg FP. Effectiveness of a fixed-dose, single-pill combination of perindopril and amlodipine in patients with hypertension: a non-interventional study. Adv Ther. 2018;35(3):353–366. doi:10.1007/s12325-018-0675-3

32. Fongwa MN, Nandy K, Qing Y, Hays RD. The facilitators of and barriers to adherence to hypertension treatment scale. J Cardiovasc Nurs. 2015;30(6):484–490. doi:10.1097/JCN.0000000000000206

33. Gerber BS, Cho YI, Arozullah AM, et al. Racial differences in medication adherence: a cross-sectional study of Medicare enrollees. Am J Geriat Pharmacoth. 2010;8:1876–7761.

34. Glasgow RE, Kurz D, King D, et al. Twelve-month outcomes of an internet-based diabetes self-management support program. Patient Educ Couns. 2012;87(1):81–92. doi:10.1016/j.pec.2011.07.024

35. Greer DB, Abel WM. Religious/Spiritual Coping in Older African American Women. Qual Rep. 2017;22(1):237–260.

36. Greer DB, Ostwald SK. Improving adherence in African American women with uncontrolled hypertension. J Cardiovas Nurs. 2015;30:1550–5049.

37. Han H-R, Lee H, Commodore-Mensah Y, Kim M. Development and validation of the hypertension self-care profile: a practical tool to measure hypertension self-care. J Cardiovasc Nurs. 2014;29(3):E11–E20. doi:10.1097/JCN.0b013e3182a3fd46

38. Hill-Briggs F, Gary TL, Yeh HC, et al. Association of social problem solving with glycemic control in a sample of urban African Americans with type 2 diabetes. J Behav Med. 2006;29:0160–7715.

39. Hsu Y-H, Mao C-L, Wey M. Antihypertensive medication adherence among elderly Chinese Americans. J Transcult Nurs. 2010;21(4):297–305. doi:10.1177/1043659609360707

40. Ingram RR, Ivanov LL. Examining the association of health literacy and health behaviors in African American older adults: does health literacy affect adherence to antihypertensive regimens? J Gerontol Nurs. 2013;39(3):22–32; quiz 33. doi:10.3928/00989134-20130201-01

41. Karademir M, Koseoglu IH, Vatansever K, Van Den Akker M. Validity and reliability of the Turkish version of the HillBone compliance to high blood pressure therapy scale for use in primary health care settings. Eur J Gen Pract. 2009;15(4):207–211. doi:10.3109/13814780903452150

42. Kim E-Y, Han H-R, Jeong S, et al. Does knowledge matter? Intentional medication nonadherence among middle-aged Korean Americans with high blood pressure. J Cardiovasc Nurs. 2007;22(5):397–404. doi:10.1097/

43. Koschack J, Marx G, Schnakenberg J, Kochen MM, Himmel W. Comparison of two self-rating instruments for medication adherence assessment in hypertension revealed insufficient psychometric properties. J Clin Epidemiol. 2010;63(3):299–306. doi:10.1016/j.jclinepi.2009.06.011

44. Krousel-Wood M, Muntner P, Jannu A, Desalvo K, Re RN. Reliability of a medication adherence measure in an outpatient setting. Am J Med Sci. 2005;330(3):128–133. doi:10.1097/00000441-200509000-00006

45. Krousel-Wood MA, Islam T, Muntner P, et al. Medication adherence in older clinic patients with hypertension after Hurricane Katrina: implications for clinical practice and disaster management. Am J Med Sci. 2008;336(2):99–104. doi:10.1097/MAJ.0b013e318180f14f

46. Krousel-Wood M, Joyce C, Holt EW, et al. Development and evaluation of a self-report tool to predict low pharmacy refill adherence in elderly patients with uncontrolled hypertension. Pharmacotherapy. 2013;33(8):798–811. doi:10.1002/phar.1275

47. Lambert EV, Steyn K, Stender S, Everage N, Fourie JM, Hill M. Cross-cultural validation of the hill-bone compliance to high blood pressure therapy scale in a South African, primary healthcare setting. Ethn Dis. 2006;16(1):286–291.

48. Mafutha GN, Wright SC. Compliance or non-compliance of hypertensive adults to hypertension management at three primary healthcare day clinics in Tshwane. Curationis. 2013;36(1):E1–E6. doi:10.4102/curationis.v36i1.52

49. Manze MG, Orner MB, Glickman M, Pbert L, Berlowitz D, Kressin NR. Brief provider communication skills training fails to impact patient hypertension outcomes. Patient Educ Couns. 2015;98(2):191–198. doi:10.1016/j.pec.2014.10.014

50. Maslakpak MH, Rezaei B, Parizad N. Does family involvement in patient education improve hypertension management? A single-blind randomized, parallel group, controlled trial. Cogent Med. 2018;5(1):1537063. doi:10.1080/2331205X.2018.1537063

51. Mutneja E, Yadav R, Dey AB, Gupta P. Frequency and predictors of compliance among patients taking antihypertensive medicines. Indian Heart J. 2020;72:136–139. doi:10.1016/j.ihj.2020.03.008

52. Nashilongo MM, Singu B, Kalemeera F, et al. Assessing adherence to antihypertensive therapy in primary health care in Namibia: findings and implications. Cardiovasc Drugs Ther. 2017;31(5–6):565–578. doi:10.1007/s10557-017-6756-8

53. Ndumele CD, Shaykevich S, Williams D, Hicks LS. Disparities in adherence to hypertensive care in urban ambulatory settings. J Health Care Poor Underserved. 2010;21(1):132–143. doi:10.1353/hpu.0.0259

54. Nguyen GC, LaVeist TA, Harris ML, Datta LW, Bayles TM, Brant SR. Patient trust-in-physician and race are predictors of adherence to medical management in inflammatory bowel disease. Inflamm Bowel Dis. 2009;15(8):1233–1239. doi:10.1002/ibd.20883

55. Nogueira-Silva L, Sá-Sousa A, Lima MJ, Monteiro A, Dennison-Himmelfarb C, Fonseca JA. Translation and cultural adaptation of the hill-bone compliance to high blood pressure therapy scale to Portuguese. Rev Port Cardiol. 2016;35(2):93–97. doi:10.1016/j.repc.2015.07.013

56. Rose LE, Sawyer AL, Everett A. Cardiovascular health literacy and treatment adherence in persons with serious mental illness. Issues Ment Health Nurs. 2014;35(2):88–99. doi:10.3109/01612840.2013.843622

57. Sarfo FS, Mobula LM, Burnham G, et al. Factors associated with uncontrolled blood pressure among Ghanaians: evidence from a multicenter hospital-based study. PLoS One. 2018;13(3):e0193494. doi:10.1371/journal.pone.0193494

58. Shawler C, Edward J, Ling J, Crawford TN, Rayens MK. Impact of mother-daughter relationship on hypertension self-management and quality of life: testing dyadic dynamics using the actor-partner interdependence model. J Cardiovasc Nurs. 2018;33(3):232–238. doi:10.1097/JCN.0000000000000448

59. Song Y, Han HR, Song HJ, Nam S, Nguyen T, Kim MT. Psychometric evaluation of hill-bone medication adherence subscale. Asian Nurs Res. 2011;5(3):183–188. doi:10.1016/j.anr.2011.09.007

60. Uchmanowicz I, Jankowska-Polańska B, Chudiak A, Szymańska-Chabowska A, Mazur G. Psychometric evaluation of the polish adaptation of the hill-bone compliance to high blood pressure therapy scale. BMC Cardiovasc Disord. 2016;16(1). doi:10.1186/s12872-016-0270-y

61. Uchmanowicz B, Chudiak A, Mazur G. The influence of quality of life on the level of adherence to therapeutic recommendations among elderly hypertensive patients. Patient Prefer Adherence. 2018;12:2593–2603. doi:10.2147/ppa.S182172

62. Uchmanowicz B, Chudiak A, Uchmanowicz I, Rosińczuk J, Froelicher ES. Factors influencing adherence to treatment in older adults with hypertension. Clin Interv Aging. 2018;13:2425–2441. doi:10.2147/CIA.S182881

63. Uchmanowicz B, Chudiak A, Uchmanowicz I, Mazur G. How may coexisting frailty influence adherence to treatment in elderly hypertensive patients? Int J Hypertens. 2019;2019:1–8. doi:10.1155/2019/5245184

64. Wang X, Robinson KM, Hardin HK. The impact of caregiving on caregivers’ medication adherence and appointment keeping. West J Nurs Res. 2015;37(12):1548–1562. doi:10.1177/0193945914533158

65. Zabihi RE, Ashktorab T, Banaderakhshan H, Zaeri F. Adherence to therapeutic regimens in patients with hypertension. ARYA Atheroscler. 2012;8:S190–S194.

66. Zare S, Rezaee R, Aslani A, Shirdeli M, Kojuri J. Moving toward community based telehealth services using mhealth for hypertensive patients. Int J Technol Assess Health Care. 2019;35(5):379–383. doi:10.1017/S0266462319000655

67. Zwar N, Hermiz O, Halcomb E, Davidson PM, Bodenheimer T. Improving blood pressure control in general practice: a pilot study of the ImPress intervention. Aust Fam Physician. 2017;46(5):306–311.

68. Culig J, Leppée M. From Morisky to Hill-bone; self-reports scales for measuring adherence to medication. Colleg Antropolog. 2014;38:0350–6134.

69. Gehi AK, Ali S, Fau – Na B, Na B, Fau – Whooley MA, Whooley MA. Self-reported medication adherence and cardiovascular events in patients with stable coronary heart disease: the heart and soul study. Arch Inter Med. 2007;167:0003–9926.

70. Hamdidouche I, Jullien V, Laurent S, Azizi M. Detecting nonadherence to antihypertensive treatment. Hypertension. 2017;70(2):257–258. doi:10.1161/HYPERTENSIONAHA.117.09739

71. Kronish IM, Ye S. Adherence to cardiovascular medications: lessons learned and future directions. Prog Cardiov Dis. 2013;55:1873.

72. The hill-bone scales: hypertension and medication adherence scales. Available from: Accessed September 01, 2023.

73. Gabriel A, Zare H, Jones W, et al. Evaluating depressive symptoms among low-socioeconomic-status African American women aged 40 to 75 years with uncontrolled hypertension: a secondary analysis of a randomized clinical trial. JAMA psychiatry. 2021;78:2168–6238.

74. Kim EY, Han HR, Jeong S, et al. Does knowledge matter?: intentional medication nonadherence among middle-aged Korean Americans with high blood pressure. J Cardiovas Nurs. 2007;22:1550–5049.

75. Zhang J, Gong Y, Zhao Y, Jiang N, Wang J, Yin XA-O. Post-stroke medication adherence and persistence rates: a meta-analysis of observational studies. J Neurol. 2021;268:1432–1459.

76. Polonsky WH, Henry RR. Poor medication adherence in type 2 diabetes: recognizing the scope of the problem and its key contributors. Patient Prefer Adher. 2016;2016:1177–889X.

77. Smith D, Lovell J, Weller C, et al. A systematic review of medication non-adherence in persons with dementia or cognitive impairment. PLoS One. 2017;12:1932–6203.

78. Jackson CA, Clatworthy J, Fau – Robinson A, Robinson A, Fau – Horne R, Horne R. Factors associated with non-adherence to oral medication for inflammatory bowel disease: a systematic review. Official J Am Coll Gastroenterol. 2010;105:1572.

79. Mechta Nielsen T, Frøjk Juhl M, Feldt-Rasmussen B, Thomsen T. Adherence to medication in patients with chronic kidney disease: a systematic review of qualitative research. Clin Kidney J. 2018;11:2048–8505.

80. Stewart BJ, Archbold PG. Focus on psychometrics nursing intervention studies require outcome measures that are sensitive to change: part one. Res Nurs Health. 1992;15(6):477–481. doi:10.1002/nur.4770150610

81. Stewart BJ, Archbold PG. Nursing intervention studies require outcome measures that are sensitive to change: part two. Res Nurs Health. 1993;16(1):77–81. doi:10.1002/nur.4770160110

82. Morisky DE, Ang A, Krousel‐Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hyperten. 2008;10:1524–6175.

83. Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reported measure of medication adherence. Medical Care. 1986;1986:0025–7079.

84. Ogedegbe G, Mancuso CA, Allegrante JP, Charlson ME. Development and evaluation of a medication adherence self-efficacy scale in hypertensive African-American patients. JClin Epidemiol. 2003;56(6):520.

85. Basu S, Garg S, Sharma N, Singh MM. Improving the assessment of medication adherence: challenges and considerations with a focus on low-resource settings. Tzu-Chi Medical J. 2019;31:1016–3190.

86. Ackermann M, Verleden SE, Kuehnel M, et al. Pulmonary vascular endothelialitis, thrombosis, and angiogenesis in covid-19. N Engl J Med. 2020;383(2):120–128. doi:10.1056/NEJMoa2015432