Cardiovascular Diseases — The Nueva Ecija Cardiovascular Risk Experiment
Citation(s)
Attanasio OP, Meghir C, Vera-Hernández, AM (2005). Elicitation, validation, and use of probability distributions of future income in developing countries. University College; London: 2005. [unpublished working paper]
Attanasio, OP (2009) Expectations and Perceptions in Developing Countries: Their Measurement and Their Use, American Economic Review, 99 (2): 87-92.
Baltussen, G , Post, G. T., Van Den Assem, M. J., & Wakker, P. P. (2012). Random incentive systems in a dynamic choice experiment. Experimental Economics, 15(3), 418-443.
Camerer, C F., Hogarth, R. M., Budescu, D. V., & Eckel, C. (1999). The effects of financial incentives in experiments: A review and capital-labor-production framework. In Elicitation of Preferences (pp. 7-48). Springer Netherlands.
Cooney MT, Dudina AL, Graham IM Value and limitations of existing scores for the assessment of cardiovascular risk: a review for clinicians. J Am Coll Cardiol. 2009 Sep 29;54(14):1209-27. doi: 10.1016/j.jacc.2009.07.020. Review.
Delavande A, Giné X, McKenzie D (2011a) Measuring Subjective Expectations in Developing Countries: A Critical Review and New Evidence. Journal of Development Economics, 94:151-163,
Delavande A, Giné X, McKenzie D (2011b) Eliciting Probabilistic Expectations with Visual Aids in Developing Countries: How sensitive are answers to variations in elicitation design? Journal of Applied Econometrics, 26(3):479-497.
Delavande A, Kohler HP Subjective expectations in the context of HIV/AIDS in Malawi. Demogr Res. 2009 Jun 23;20:817-874.
Delavande, A and Kohler, H-P. (2015) HIV/AIDS-related Expectations and Risky Sexual Behaviour in Malawi. Review of Economic Studies, 83: 118-64.
Department of Health (2012a) Implementing Guidelines on the Implementation of Philippine Package of Essential NCD Interventions (PHIL PEN) on the Integrated Management of Hypertension and Diabetes for Primary Care Facilities, Administrative Order No. 2012-0029. Manila: Department of Health.
Dimmock SG, Kouwenberg R, Mitchell OS, Peijnenburg K Estimating ambiguity preferences and perceptions in multiple prior models: Evidence from the field. J Risk Uncertain. 2015 Dec;51(3):219-244. Epub 2015 Dec 16.
Ezzati, M, et al (2004). Comparative quantification of health risks. Global and regional burden of disease attributable to selected major risk factors. Volume 1. Geneva: World Health Organization.
Gale CR, Cooper C, Sayer AA Framingham cardiovascular disease risk scores and incident frailty: the English longitudinal study of ageing. Age (Dordr). 2014;36(4):9692. doi: 10.1007/s11357-014-9692-6. Epub 2014 Aug 2.
Gaziano TA, Young CR, Fitzmaurice G, Atwood S, Gaziano JM Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: the NHANES I Follow-up Study cohort. Lancet. 2008 Mar 15;371(9616):923-31. doi: 10.1016/S0140-6736(08)60418-3.
Harris AJ, Hahn U Unrealistic optimism about future life events: a cautionary note. Psychol Rev. 2011 Jan;118(1):135-54. doi: 10.1037/a0020997.
Hemming K and Marsch J (2013) A menu-driven facility for sample-size calculations in cluster randomized controlled trials. The Stata Journal 13(1): 114-135.
Hill, RV (2009) Using Stated Preferences and Beliefs to Identify the Impact of Risk on Poor Households. Journal of Development Studies, 45(2): 151-171.
Kahneman, D , & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica: Journal of the econometric society, 263-291.
Kariuki JK, Stuart-Shor EM, Leveille SG, Hayman LL Evaluation of the performance of existing non-laboratory based cardiovascular risk assessment algorithms. BMC Cardiovasc Disord. 2013 Dec 28;13:123. doi: 10.1186/1471-2261-13-123. Review.
Laibson D (1997) Golden eggs and hyperbolic discounting. Quarterly Journal of Economics 112(2): 443-477.
Lindström J, Tuomilehto J The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care. 2003 Mar;26(3):725-31.
Littenberg B, MacLean CD Intra-cluster correlation coefficients in adults with diabetes in primary care practices: the Vermont Diabetes Information System field survey. BMC Med Res Methodol. 2006 May 3;6:20.
Otgontuya D, Oum S, Buckley BS, Bonita R Assessment of total cardiovascular risk using WHO/ISH risk prediction charts in three low and middle income countries in Asia. BMC Public Health. 2013 Jun 5;13:539. doi: 10.1186/1471-2458-13-539.
Pandya A, Weinstein MC, Gaziano TA A comparative assessment of non-laboratory-based versus commonly used laboratory-based cardiovascular disease risk scores in the NHANES III population. PLoS One. 2011;6(5):e20416. doi: 10.1371/journal.pone.0020416. Epub 2011 May 31.
Parker DR, Evangelou E, Eaton CB Intraclass correlation coefficients for cluster randomized trials in primary care: the cholesterol education and research trial (CEART). Contemp Clin Trials. 2005 Apr;26(2):260-7.
Paula Á ,Gil S, and Todd PE (2014). How beliefs about HIV status affect risky behaviors: evidence from Malawi. Journal of Applied Econometrics, 29: 944-964.
Prelec, D (1998). The probability weighting function. Econometrica, 497-527.
Radcliffe, N M., & Klein, W. M. P. (2002). Dispositional, unrealistic, and comparative optimism: Differential relations with knowledge and processing of risk information and beliefs about personal risk. Personality and Social Psychology Bulletin, 28, 836-846.
Rosenstock IM Why people use health services. Milbank Mem Fund Q. 1966 Jul;44(3):Suppl:94-127.
Singh J, Liddy C, Hogg W, Taljaard M Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and management in primary care practices. BMC Res Notes. 2015 Mar 20;8:89. doi: 10.1186/s13104-015-1042-y.
Tversky, A , & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and uncertainty, 5(4), 297-323.
World Health Organization (2016) HEARTS: Technical package for cardiovascular disease management in primary care. Geneva: World Health Organization.
Yikona JI, Wallis EJ, Ramsay LE, Jackson PR Coronary and cardiovascular risk estimation in uncomplicated mild hypertension. A comparison of risk assessment methods. J Hypertens. 2002 Nov;20(11):2173-82.
The Nueva Ecija Cardiovascular Risk Experiment: An Evaluation of the Impact of Risk Information and Screening on Primary Prevention of Cardiovascular Disease
Interventional studies are often prospective and are specifically tailored to evaluate direct impacts of treatment or preventive measures on disease.
Observational studies are often retrospective and are used to assess potential causation in exposure-outcome relationships and therefore influence preventive methods.
Expanded access is a means by which manufacturers make investigational new drugs available, under certain circumstances, to treat a patient(s) with a serious disease or condition who cannot participate in a controlled clinical trial.
Clinical trials are conducted in a series of steps, called phases - each phase is designed to answer a separate research question.
Phase 1: Researchers test a new drug or treatment in a small group of people for the first time to evaluate its safety, determine a safe dosage range, and identify side effects.
Phase 2: The drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.
Phase 3: The drug or treatment is given to large groups of people to confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug or treatment to be used safely.
Phase 4: Studies are done after the drug or treatment has been marketed to gather information on the drug's effect in various populations and any side effects associated with long-term use.
