Development and Psychometric Validation of the Hypertension Beliefs Assessment Tool Among Adult Population in Northwest Ethiopia

References

• Hermida RC, Ayala DE, Fernandez JR, Mojon A, Smolensky MH. Hypertension: new perspective on its definition and clinical management by bedtime therapy substantially reduces cardiovascular disease risk. Eur J Clin Invest. 2018;48(5):e12909. doi:10.1111/eci.12909
   PubMed Web of Science ®Google Scholar
• Bromfield S, Muntner P. High blood pressure: the leading global burden of disease risk factor and the need for worldwide prevention programs. Curr Hypertens Rep. 2013;15(3):134–136. doi:10.1007/s11906-013-0340-9
   PubMed Web of Science ®Google Scholar
• Nguyen TN, Chow CK. Global and national high blood pressure burden and control. Lancet. 2021;398(10304):932–933. doi:10.1016/S0140-6736(21)01688-3
   PubMed Web of Science ®Google Scholar
• Bozkurt B, Aguilar D, Deswal A, et al. Contributory risk and management of comorbidities of hypertension, obesity, diabetes mellitus, hyperlipidemia, and metabolic syndrome in chronic heart failure: a scientific statement from the American Heart Association. Circulation. 2016;134(23):e535–e578.
   PubMed Web of Science ®Google Scholar
• Drozdz D, Kawecka-Jaszcz K. Cardiovascular changes during chronic hypertensive states. Pediatr Nephrol. 2014;29(9):1507–1516. doi:10.1007/s00467-013-2614-5
   Web of Science ®Google Scholar
• US Department of Health Human Services; National Institutes of Health; National Heart, Lung, and Blood Institute; 2003. Your Guide to Lowering Blood Pressure. Available from: https://www.nhlbi.nih.gov/files/docs/public/heart/hbp_low.pdf. Accessed November 17, 2021.
   Google Scholar
• Maryon-Davis A, Press V. Easing the pressure: Tackling hypertension toolkit. National Heart Forum; 2005. Available from: https://www.heartforum.org.uk/Publications_NHFreports_HypertensionToolkit.aspx. Accessed November 17, 2021.
   Google Scholar
• Non-communicable diseases news. World Health Organization; Pan American Health Organization; 2016. Previously available from: https://www3.paho.org/hq/index.php?option=com_content&view=article&id=12757:ncd-risc-high-blood-pressure-affects-113-billion&Itemid=4327&lang=pt.
   Google Scholar
• Emerging Public Health Problems in Ethiopia: Chronic Non-Communicable Diseases. Ethiopian Public Health Association; 2012. Available from: https://www.etpha.org/publications/other-publications.html?download=385:other-publications. Accessed November 17, 2021.
   Google Scholar
• Tiruneh SA, Bukayaw YA, Yigizaw ST, Angaw DA. Prevalence of hypertension and its determinants in Ethiopia: a systematic review and meta-analysis. PLoS One. 2020;15(12):e0244642. doi:10.1371/journal.pone.0244642
   PubMed Web of Science ®Google Scholar
• Gudina EK, Michael Y, Assegid S. Prevalence of hypertension and its risk factors in southwest Ethiopia: a hospital-based cross-sectional survey. Integr Blood Press Control. 2013;6:111. doi:10.2147/IBPC.S47298
   PubMedGoogle Scholar
• Mekonnen AS, Yemane B, Alemayehu W, Assefa G. Prevalence and associated factors of hypertension: a crossectional community based study in Northwest Ethiopia. PLoS One. 2015;10(4):e0125210. doi:10.1371/journal.pone.0125210
   Web of Science ®Google Scholar
• Mensah GA. Epidemiology and Global Burden of Hypertension. Oxford University Press; 2019.
   Google Scholar
• Elevating hypertension on the public health agenda: World Heart Federation; May 17, 2018. Available from: https://www.world-heart-federation.org/news/elevating-hypertension-public-health-agenda/. Accessed November 9, 2021.
   Google Scholar
• Tefera YG, Abegaz TM, Abebe TB, Mekuria AB. The changing trend of cardiovascular disease and its clinical characteristics in Ethiopia: hospital-based observational study. Vasc Health Risk Manag. 2017;13:143.
   PubMed Web of Science ®Google Scholar
• Rubinstein A, Colantonio L, Bardach A, et al. Estimation of the burden of cardiovascular disease attributable to modifiable risk factors and cost-effectiveness analysis of preventative interventions to reduce this burden in Argentina. BMC Public Health. 2010;10(1):627. doi:10.1186/1471-2458-10-627
   Web of Science ®Google Scholar
• Tocci G, Sciarretta S, Volpe M. Development of heart failure in recent hypertension trials. J Hypertens. 2008;26(7):1477–1486. doi:10.1097/HJH.0b013e3282fe1d3d
   PubMed Web of Science ®Google Scholar
• Erkabu SG, Agedie Y, Mihretu DD, Semere A, Alemu YM. Ischemic and hemorrhagic stroke in Bahir Dar, Ethiopia: a Retrospective Hospital-Based Study. J Stroke Cerebrovasc Dis. 2018;27(6):1533–1538. doi:10.1016/j.jstrokecerebrovasdis.2017.12.050
   PubMed Web of Science ®Google Scholar
• Deresse B, Shaweno D. Epidemiology and in-hospital outcome of stroke in South Ethiopia. J Neurol Sci. 2015;355(1–2):138–142. doi:10.1016/j.jns.2015.06.001
   PubMed Web of Science ®Google Scholar
• Temesgen TG, Teshome B, Njogu P. Treatment outcomes and associated factors among hospitalized stroke patients at shashemene referral hospital, Ethiopia. Stroke Res Treat. 2018;2018:1–5. doi:10.1155/2018/8079578
   Web of Science ®Google Scholar
• Bikila G, Takele M, Tesfaye B, Hailu A. Assessment of risk factors and treatment outcome of stroke admissions at St. Paul’s teaching hospital, Addis Ababa, Ethiopia. J Neurol. 2017;8:03.
   Google Scholar
• Alemayehu CM, Birhanesilasie SK. Assessment of stoke patients: occurrence of unusually high number of haemorrhagic stroke cases in Tikur anbessa specialized hospital, Addis Ababa, Ethiopia. Clin Med Res. 2013;2(5):94–100. doi:10.11648/j.cmr.20130205.11
   Google Scholar
• Mattila R. Effectiveness of a Multidisciplinary Lifestyle Intervention on Hypertension, Cardiovascular Risk Factors and Musculoskeletal Symptoms. University of Kuopio; 2009.
   Google Scholar
• WHO. Global status report on noncommunicalble diseases; 2014: Attaining the Nine Global Noncommunicable Diseases Targets; a Shared Responsibility. Available from: https://apps.who.int/iris/handle/10665/148114. Accessed November 17, 2021.
   Google Scholar
• Law M, Morris J, Wald N. Use of blood pressure lowering drugs in the prevention of cardiovascular disease: meta-analysis of 147 randomised trials in the context of expectations from prospective epidemiological studies. BMJ. 2009;338(may19 1):b1665. doi:10.1136/bmj.b1665
   PubMed Web of Science ®Google Scholar
• Ettehad D, Emdin CA, Kiran A, et al. Blood pressure lowering for prevention of cardiovascular disease and death: a systematic review and meta-analysis. Lancet. 2016;387(10022):957–967. doi:10.1016/S0140-6736(15)01225-8
   PubMed Web of Science ®Google Scholar
• Antonakoudis G, Poulimenos I, Kifnidis K, Zouras C, Antonakoudis H. Blood pressure control and cardiovascular risk reduction. Hippokratia. 2007;11(3):114.
   Google Scholar
• Carey RM, Whelton PK. Prevention, detection, evaluation, and management of high blood pressure in adults: synopsis of the 2017 American college of cardiology/American heart association hypertension guideline. Ann Intern Med. 2018;168(5):351–358. doi:10.7326/M17-3203
   PubMed Web of Science ®Google Scholar
• Fernandez S, Tobin JN, Cassells A, Diaz-Gloster M, Kalida C, Ogedegbe G. The counseling African Americans to control hypertension (CAATCH) trial: baseline demographic, clinical, psychosocial, and behavioral characteristics. Implement Sci. 2011;6(1):100. doi:10.1186/1748-5908-6-100
   Web of Science ®Google Scholar
• Addressing the Impact of Noncommunicable Diseases And Injuries In Ethiopia: A Collaboration with the Global Lancet Commission on Reframing NCDIs for the Poorest Billion. Addis Ababa: Federal Democratic Republic of Ethiopia Ministry of Health; 2018.
   Google Scholar
• Samuel AL, Yohannes AS, Laemengo GF. Hypertension and its associated factors in Hosanna town, Southern Ethiopia: community based cross-sectional study. BMC Res Notes. 2018;11(1):306. doi:10.1186/s13104-018-3435-1
   Google Scholar
• Animut Y, Assefa AT, Lemma DG. Blood pressure control status and associated factors among adult hypertensive patients on outpatient follow-up at University of Gondar Referral Hospital, Northwest Ethiopia: a retrospective follow-up study. Integr Blood Press Control. 2018;11:37. doi:10.2147/IBPC.S150628
   Web of Science ®Google Scholar
• Teshome DF, Demssie AF, Zeleke BM. Determinants of blood pressure control amongst hypertensive patients in Northwest Ethiopia. PLoS One. 2018;13(5):e0196535. doi:10.1371/journal.pone.0196535
   PubMed Web of Science ®Google Scholar
• Long E, Ponder M, Bernard S. Knowledge, attitudes, and beliefs related to hypertension and hyperlipidemia self-management among African-American men living in the southeastern United States. Patient Educ Couns. 2017;100(5):1000–1006. doi:10.1016/j.pec.2016.12.011
   Web of Science ®Google Scholar
• Veerapu N, Baer PRK, Kudumula M. Health beliefs about hypertension among hypertensive elderly people in Khammam urban locality: health belief model. Int J Community Med Public Health. 2020;7(10):3892.
   Google Scholar
• Puspita RC, Tamtomo D, Indarto D. Health belief model for the analysis of factors affecting hypertension preventive behavior among adolescents in Surakarta. J Health Promot Behav. 2017;2(2):183–196. doi:10.26911/thejhpb.2017.02.02.08
   Google Scholar
• Khatib R, Schwalm J-D, Yusuf S, et al. Patient and healthcare provider barriers to hypertension awareness, treatment and follow up: a systematic review and meta-analysis of qualitative and quantitative studies. PLoS One. 2014;9(1):e84238. doi:10.1371/journal.pone.0084238
   PubMed Web of Science ®Google Scholar
• Okwuonu CG, Ojimadu NE, Okaka EI, Akemokwe FM. Patient-related barriers to hypertension control in a Nigerian population. Int J Gen Med. 2014;7:345. doi:10.2147/IJGM.S63587
   PubMedGoogle Scholar
• Osamor PE, Ojelabi OA. Health belief model and hypertension treatment compliance.
   Google Scholar
• Setiyaningsih R, Tamtomo D, Suryani N. Health belief model: determinants of hypertension prevention behavior in adults at community health center, sukoharjo, central java. J Health Promot Behav. 2016;1(3):160–170. doi:10.26911/thejhpb.2016.01.03.03
   Google Scholar
• Naanyu V, Vedanthan R, Kamano JH, et al. Barriers influencing linkage to hypertension care in Kenya: qualitative analysis from the LARK hypertension study. J Gen Intern Med. 2016;31(3):304–314. doi:10.1007/s11606-015-3566-1
   PubMed Web of Science ®Google Scholar
• Labaran K, Mohammed M, Sa’eed S, Wada A, Mustapha S. Relationship between patients’ beliefs about their antihypertensives and adherence in a secondary hospital in northern Nigeria. Bayero J Pure Appl Sci. 2017;10(1):276–279. doi:10.4314/bajopas.v10i1.55S
   Google Scholar
• Al-Noumani H, Wu J-R, Barksdale D, Sherwood G, Alkhasawneh E, Knafl G. Health beliefs and medication adherence in patients with hypertension: a systematic review of quantitative studies. Patient Educ Couns. 2019;102(6):1045–1056. doi:10.1016/j.pec.2019.02.022
   PubMed Web of Science ®Google Scholar
• Kressin NR, Wang F, Long J, et al. Hypertensive patients’ race, health beliefs, process of care, and medication adherence. J Gen Intern Med. 2007;22(6):768–774. doi:10.1007/s11606-007-0165-9
   Web of Science ®Google Scholar
• Edwards MM. Beliefs about hypertension among people with uncontrolled hypertension; 2015.
   Google Scholar
• Goldmann E, Jacoby R, Finfer E, et al. Positive health beliefs and blood pressure reduction in the DESERVE study. J Am Heart Assoc. 2020;9(9):e014782. doi:10.1161/JAHA.119.014782
   Web of Science ®Google Scholar
• Karen G, Donald B. The role of behavioral science theory in development and implementation of public health interventions. Annu Rev Public Health. 2010;31:399–418. doi:10.1146/annurev.publhealth.012809.103604
   Web of Science ®Google Scholar
• Janz NK, Becker MH. The health belief model: a decade later. Health Educ Q. 1984;11(1):1–47. doi:10.1177/109019818401100101
   PubMedGoogle Scholar
• Woringer M, Nielsen JJ, Zibarras L, et al. Development of a questionnaire to evaluate patients’ awareness of cardiovascular disease risk in England’s national health service health check preventive cardiovascular programme. BMJ Open. 2017;7(9):e014413. doi:10.1136/bmjopen-2016-014413
   PubMed Web of Science ®Google Scholar
• Juárez-García DM, de Jesús García-solís M, Téllez A. Adaptation and validation of the health belief model scale for breast self-examination in Mexican women. Value Health Reg Issues. 2020;23:30–36. doi:10.1016/j.vhri.2019.11.006
   PubMedGoogle Scholar
• Mohamed NC, Moey S-F, Lim B-C. Validity and reliability of health belief model questionnaire for promoting breast self-examination and screening mammogram for early cancer detection. Asian Pac J Cancer Prev. 2019;20(9):2865. doi:10.31557/APJCP.2019.20.9.2865
   Google Scholar
• Tsangari H, Petro-Nustas W. The psychometric properties of the Greek version of champion’s health belief model scale. J Nurs Meas. 2012;20(3):244–257. doi:10.1891/1061-3749.20.3.244
   Google Scholar
• Dewi TK. Validation of the Indonesian version of champion’s health belief model scale for breast self-examination. Psychol Res Behav Manag. 2018;11:433. doi:10.2147/PRBM.S177124
   Web of Science ®Google Scholar
• Avci IA, Altinel B. The validity and reliability of health belief scale for testicular cancer self-examination. Am J Mens Health. 2018;12(3):531–538. doi:10.1177/1557988315611226
   Web of Science ®Google Scholar
• Soleymanian A, Niknami S, Hajizadeh E, Shojaeizadeh D, Montazeri A. Development and validation of a health belief model based instrument for measuring factors influencing exercise behaviors to prevent osteoporosis in pre-menopausal women (HOPE). BMC Musculoskelet Disord. 2014;15(1):1–8. doi:10.1186/1471-2474-15-61
   Web of Science ®Google Scholar
• Dean-Barr S. Development of an instrument to measure the health beliefs of individuals with arthritis; 1991. Available from: https://ecommons.luc.edu/cgi/viewcontent.cgi?article=3755&context=luc_diss. Accessed November 17, 2021.
   Google Scholar
• Kartal A, Özsoy SA. Validity and reliability study of the Turkish version of health belief model scale in diabetic patients. Int J Nurs Stud. 2007;44(8):1447–1458. doi:10.1016/j.ijnurstu.2007.06.004
   PubMed Web of Science ®Google Scholar
• Vazini H, Barati M. The health belief model and self-care behaviors among type 2 diabetic patients. Iran J Diabetes Obes. 2014;6(3):107–113.
   Google Scholar
• Oruganti R, Paidipati S, Dinaker M. The health beliefs scale for hypertensive patients: construction and psychometric testing. J Nurs Health Sci. 2018;7(6):34–43.
   Google Scholar
• Rosenstock IM. The health belief model and preventive health behavior. Health Educ Monogr. 1974;2(4):354–386. doi:10.1177/109019817400200405
   Google Scholar
• Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191. doi:10.1037/0033-295X.84.2.191
   PubMed Web of Science ®Google Scholar
• Neelakandan BV, Gopalakrishnan S, Ramachandran H, Anuradha R, Gopichandran V. Health beliefs regarding uptake of hypertension screening in an urban setting: a population segmentation strategy. Int J Med Public Health. 2018;8:1. doi:10.5530/ijmedph.2018.1.3
   Google Scholar
• Medina-Shepherd R, Kleier JA. Spanish translation and adaptation of Victoria champion’s health belief model scales for breast cancer screening-mammography. Cancer Nurs. 2010;33(2):93–101. doi:10.1097/NCC.0b013e3181c75d7b
   Web of Science ®Google Scholar
• Saadat M, Ghalehtaki R, Sadeghian D, Mohammadtaheri S, Meysamie A. Can we create a reliable and valid short form of champion health belief model questionnaire? Arch Breast Cancer. 2016;3:19–23.
   Google Scholar
• Taherdoost H, Sahibuddin S, Jalaliyoon N. Exploratory Factor Analysis; Concepts and Theory. WSEAS; 2014.
   Google Scholar
• Haan NS-D, Wel M, Schoenmakers G, et al. Thirty-minute compared to standardised office blood pressure measurement in general practice. Br J Gen Pract. 2011;61(590):e590–e597.
   Web of Science ®Google Scholar
• Stojanovic M. IS 30 minutes interval enough for analyzing? Ambulatory blood pressure monitoring? J Hypertens. 2018;36(p e71). doi:10.1097/01.hjh.0000539162.42022.d8
   Web of Science ®Google Scholar
• Carmines EG, Zeller RA. On establishing the empirical dimensionality of theoretical terms: an analytical example. Political Methodol. 1974;1:75–96.
   Google Scholar
• Brian E, Anders S. The Cambridge Dictionary of Statistics. Cambridge University Press Cambridge; 2002.
   Google Scholar
• Zijlmans EA, Tijmstra J, van der Ark LA, Sijtsma K. Item-score reliability in empirical-data sets and its relationship with other item indices. Educ Psychol Meas. 2018;78(6):998–1020. doi:10.1177/0013164417728358
   PubMed Web of Science ®Google Scholar
• Henrysson S. Correction of item-total correlations in item analysis. Psychometrika. 1963;28(2):211–218.
   Web of Science ®Google Scholar
• Yang B. Factor analysis methods. In: Research in Organizations: Foundations Methods of Inquiry. Berrett-Koehler Publishers, Inc.; 2005:181–199.
   Google Scholar
• Habing B. Exploratory Factor Analysis. University of South Carolina; O2003. Available from: https://people.stat.sc.edu/habing/courses/530EFA.pdf. Accessed November 17, 2021.
   Google Scholar
• Goodwin LD, Leech NL. Understanding correlation: factors that affect the size of r. J Exp Educ. 2006;74(3):249–266. doi:10.3200/JEXE.74.3.249-266
   Web of Science ®Google Scholar
• Kaiser HF, Rice J. Little jiffy, mark IV. Educ Psychol Meas. 1974;34(1):111–117. doi:10.1177/001316447403400115
   Web of Science ®Google Scholar
• Shirkey EC, Dziuban CD. A note on some sampling characteristics of the measure of sampling adequacy (MSA). Multivariate Behav Res. 1976;11(1):125–128. doi:10.1207/s15327906mbr1101_9
   PubMedGoogle Scholar
• Bartlett MS. A note on the multiplying factors for various χ2 approximations. J R Stat Soc Series B. 1954;16(2):296–298.
   Google Scholar
• Andy F. Discovering Statistics Using SPSS for Windows: Advanced Techniques for the Beginner/Andy Field. London: Sage Publications; 2000.
   Google Scholar
• Yong AG, Pearce S. A beginner’s guide to factor analysis: focusing on exploratory factor analysis. Tutor Quant Methods Psychol. 2013;9(2):79–94. doi:10.20982/tqmp.09.2.p079
   Google Scholar
• Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16(3):297–334. doi:10.1007/BF02310555
   Web of Science ®Google Scholar
• Cronbach LJ, Meehl PE. Construct validity in psychological tests. Psychol Bull. 1955;52(4):281–302. doi:10.1037/h0040957
   PubMed Web of Science ®Google Scholar
• Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Market Res. 1981;18(1):39–50. doi:10.1177/002224378101800104
   Web of Science ®Google Scholar
• Chin WW, Newsted PR. Structural equation modeling analysis with small samples using partial least squares. Stat Strategies Small Sample Res. 1999;1(1):307–341.
   Google Scholar
• Parsa P, Kandiah M, Mohd Nasir M, Hejar A, Nor Afiah M. Reliability and validity of champion’s health belief model scale for breast cancer screening among Malaysian women. Singapore Med J. 2008;49(11):897.
   PubMed Web of Science ®Google Scholar
• Kirag N, Kızılkaya M. Application of the champion health belief model to determine beliefs and behaviors of Turkish women academicians regarding breast cancer screening: a cross sectional descriptive study. BMC Womens Health. 2019;19(1):1–10. doi:10.1186/s12905-019-0828-9
   Web of Science ®Google Scholar
• Hashemian M, Amin Shokravi F, Lamyian M, Hassanpour K, Akaberi A. Reliability and validity of the champion’s health belief model scale for mammography among Iranian women with family history of breast cancer. Health Educ Promot Pract. 2013;1(3):19–31.
   Google Scholar