Validity and Reliability of the Turkish Version of the Acute Coronary Syndrome Response Index

Year 2023, Issue: 2, 23 - 29, 20.07.2023

Meryem Yıldız Ayvaz , Nuray Enç

https://doi.org/10.26650/CURARE.2023.1310542

Abstract

Objective: This research was conducted to determine the validity and reliability of the Turkish version of the Acute Coronary Syndrome (ACS) Response Index, which is used to evaluate patient’s knowledge, attitudes, and beliefs about the symptoms of ACS.

Materials and Methods: The methodologic study was conducted between March-October 2015 in a cardiology service of a research university and constitutes a sample of 165 patients who were diagnosed as having ACS. For linguistic validation, an expert panel of six academicians was formed, with the Turkish form being finalized according to their recommendations. Confirmatory factor analyses were performed for the construct validity.

Results: The Kuder-Richardson 20 formula for the first subscale was determined as 0.73, and Cronbach’s alpha of reliability was 0.83 for the second subscale and 0.66 for the third subscale. The test was repeated to evaluate the invariance of the scale and its subscales with respect to time, with no difference being determined between the two implementations (p > 0.05).

Conclusion: The Turkish version of the ACS Response Index has been found to be a valid and reliable tool for the Turkish population.

Keywords

Acute coronary syndrome, reliability, validity, treatment delay

References

• Riegel B, McKinley S, Moser DK, Meischke H, Doering L, Dracup K. Psychometric evaluation of the acute coronary syndrome (ACS) response index. Research in Nursing and Health, 2007;30(6):584-594. google scholar
• Sevinç S. Vital Decision: Symptom Perception in Acute Myocardial Infarction. Turk J Cardiovasc Nurs, 2014;5(8):56-65. google scholar
• World Health Organisation (WHO), 2023. Cardiovascular diseases. https://www.who.int/health-topics/cardiovascular-diseases #tab=tab_1 Access date: 20.05.2023. google scholar
• Nymark C, Henriksson P, Mattiasson AC, Saboonchi F, Kiessling A. Inability to act was associated with an extended delay prior to care-seeking, in patients with an acute myocardial infarction. European Journal of Cardiovascular Nursing, 2019;18(6):512-520. google scholar
• Wechkunanukul K, Grantham H, Clark RA. Global review of delay time in seeking medical care for chest pain: an integrative literatüre review. Aust Crit Care 2017;30(1):13-20 google scholar
• Arrebola-Moreno M, Petrova D, Garcia-Retamero R, Rivera-Lopez R, Jordan-Martinez L, Arrebola JP et al. Psychological and cognitive factors related to prehospital delay in acute coronary syndrome: a systematic review. International Journal of Nursing Studies, 2020:108, 103613 google scholar
• De Luca GD, Suryapranata H, Ottervanger JP, & Antman EM. Time Delay to Treatment and Mortality in Primary Angioplasty for Acute Myocardial Infarction. Circulation, 2004;109:1223-1225. google scholar
• Cao X, Cao Y, Salamonson Y, DiGiacomo M, Chen Y, Chang S, et al. Translation and validation of the Chinese version of the Acute Coronary Syndrome Response Index (C-ACSRI). International journal of nursing studies, 2012;49(10):1277-1290. google scholar
• McKee G, Mooney M, O’Donnell S, O’Brien F, Biddle MJ, Moser DK. Multivariate analysis of predictors of pre-hospital delay in acute coronary syndrome. Int J Cardiol 2013;168 (3):2706-2713. google scholar
• Mooney M, McKee G, Fealy G, O’Brien F, O’Donnell S, Moser D. A randomized controlled trial to reduce prehospital delay time in patients with acute coronary syndrome (ACS). J Emerg Med 2014;46 (4):495-506. google scholar
• Albarqouni L, Smenes K, Meinertz T, et al. Patients’ knowledge about symptoms and adequate behaviour during acute myocardial infarction and its impact on delay time findings from the multicentre MEDEA study. Patient Educ Couns 2016;99 (11):1845-1851. google scholar
• Farquharson B, Abhyankar P, Smith K, et al. Reducing delay in patients with acute coronary syndrome and other timecritical conditions: a systematic review to identify the behaviour change techniques associated with effective interventions. Open Heart 2019;6:(e000975). google scholar
• Tavşancıl E. Measurement of attitudes and data analysis with SPSS. (3rd Edition). Ankara: Nobel Publication Distribution. 2006;16-80. google scholar
• Gözüm S, Aksayan S. Guidelines for cross-cultural scale adaptation II: Psychometric properties and cross-cultural comparison. Journal of Research and Development in Nursing, 2003;5(1), 3-14. google scholar
• Polit DF, Beck CT. Essentials of nursing research: Appraising evidence for nursing practice. Philadelphia: Lippincott Williams & Wilkins, 2013. google scholar
• Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine, 2000;25(24), 3186-3191. google scholar
• Hooper D., Coughlan J, Mullen M. Structural equation modelling: Guidelines for determining model fit. Articles, 2, 2008. google scholar
• Kenny DA. Measuring model fit. http://davidakenny.net/cm/fit. htm, 2012 Access Date: 01.12.2015 google scholar
• Marsh HW, Balla J. Goodness of fit in confirmatory factor analysis: The effects of sample size and model parsimony. Quality and Quantity, 1994;28(2), 185-217. google scholar
• Hu LT, Bentler PM. fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods, 1998;3(4), 424. google scholar
• Crowley SL, Fan X. Structural equation modeling: Basic concepts and applications in personality assessment research. Journal of personality assessment, 1997;68(3), 508-531. google scholar
• Hair JF Jr, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. Upper Saddle River, NJ: Prentice Hall, 2010. google scholar