Religious Participation and DSM IV Major Depressive Disorder Among Black Caribbeans in the United States

This study examines the relationship between religious involvement and 12-month and lifetime DSM-IV major depressive disorder (MDD) within a nationally rep- resentative sample of Black Caribbean adults. MDD was assessed using the DSM-IV World Mental Health Com- posite International Diagnostic Interview (WMH-CIDI). Religious involvement included measures of religious coping, organizational and nonorganizational involvement, and subjective religiosity. Study findings indicate that religious involvement is associated with 12-month and lifetime prevalence of MDD. Multivariate relationships between religious involvement and MDD indicate lower prevalence of 12-month and lifetime MDD among persons who use religious coping and characterize themselves as being religious (for lifetime prevalence only); persons who frequently listen to religious radio programs report higher lifetime MDD. Lower rates of 12-month and lifetime MDD are noted for persons who attend religious services at least once a week (as compared to both higher and lower levels of attendance), indicating a curvilinear relationship. The findings are discussed in relation to previous research on religion and mental health concerns, conceptual models of the role of religion in mental health (e.g., prevention, resource mobilization) that specify multiple and often divergent pathways and mechanisms of religious effects on health outcomes, and the role of religion among Caribbean Blacks.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107411/1/Religious Participation and DSM IV Major Depressive Disorder Among Black Caribbeans in the United States.pdfDescription of Religious Participation and DSM IV Major Depressive Disorder Among Black Caribbeans in the United States.pdf : Main articl

Are Happiness and Life Satisfaction Different Across Religious groups? Exploring Determinants of Happiness and Life Satisfaction

This study explores whether different religions experience different levels of happiness and life satisfaction and in case this is affected by country economic and cultural environment. Using World Value Survey (from 1981 to 2014), this study found that individual religiosity and country level of development play a significant role in shaping people’s subjective well-being (SWB). Protestants, Buddhists and Roman Catholic were happier and most satisfied with their lives compared to other religious groups. Orthodox has the lowest SWB. Health status, household’s financial satisfaction and freedom of choice are means by which religious groups and governments across the globe can improve the SWB of their citizens. Keywords: happiness; life satisfaction; religion; religious differences; cultur

Patient Disease Perceptions and Coping Strategies for Arthritis in a Developing Nation: A Qualitative Study

<p>Abstract</p> <p>Background</p> <p>There is little prior research on the burden of arthritis in the developing world. We sought to document how patients with advanced arthritis living in the Dominican Republic are affected by and cope with their disease.</p> <p>Methods</p> <p>We conducted semi-structured, one-to-one interviews with economically disadvantaged Dominican patients with advanced knee and/or hip arthritis in the Dominican Republic. The interviews, conducted in Spanish, followed a moderator's guide that included topics such as the patients' understanding of disease etiology, their support networks, and their coping mechanisms. The interviews were audiotaped, transcribed verbatim in Spanish, and systematically analyzed using content analysis. We assessed agreement in coding between two investigators.</p> <p>Results</p> <p>18 patients were interviewed (mean age 60 years, median age 62 years, 72% women, 100% response rate). Patients invoked religious and environmental theories of disease etiology, stating that their illness had been caused by God's will or through contact with water. While all patients experienced pain and functional limitation, the social effects of arthritis were gender-specific: women noted interference with homemaking and churchgoing activities, while men experienced disruption with occupational roles. The coping strategies used by patients appeared to reflect their beliefs about disease causation and included prayer and avoidance of water.</p> <p>Conclusions</p> <p>Patients' explanatory models of arthritis influenced the psychosocial effects of the disease and coping mechanisms used. Given the increasing reach of global health programs, understanding these culturally influenced perceptions of disease will be crucial in successfully treating chronic diseases in the developing world.</p

Is Health Related Quality of Life (HRQoL) a valid indicator for health systems evaluation?

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The purpose of this review is to do a discussion about the use of the HRQoL as a health measure of the populations that enable to analyze its potential use as a measure of development and efficiency of health systems. The principal use of the HRQoL is in health technologies economics evaluation; however this measure can be use in public health when need to know the health state of population. The WHO recognizes its potential use but its necessary to do a discussion about your difficulties for its application and restrictions for its use as a performance indicator for the health systems. The review show the different aspects about the use of HRQoL how a measure of efficiency ot the health system, each aspect identified in the literature is analyzed and discussed, developing the pros and cons of their possible use, especially when it comes as a cardinal measure. The analysis allows recognize that measuring HRQoL in countries could serve as a useful indicator, especially when it seeks to measure the level of health and disease, as do most of the indicators of current use. However, the methodological constraints that do not allow comparability between countries especially when you have large socioeconomic differences have yet to be resolved to allow comparison between different regions.Romero, D.; Vivas Consuelo, DJJ.; Alvis Guzman, NR. (2013). Is Health Related Quality of Life (HRQoL) a valid indicator for health systems evaluation?. SpringerPlus. 2:664-674. doi:10.1186/2193-1801-2-664S6646742Acemoglu D, Johnson S: Disease and development: The effect of life expectancy on economic growth. J Polit Econ 2007, 115(6):925-985. 10.1086/529000Anderson J, Sayles H, Curtis JR, Wolfe F, Michaud K: Converting modified health assessment questionnaire (HAQ), multidimensional HAQ, and HAQII scores into original HAQ scores using models developed with a large cohort of rheumatoid arthritis patients. Arthritis care & research 2010, 62(10):1481-1488. Epub 2010/05/25 10.1002/acr.20265Aristotles : Nicomachean Ethics: Batoche Books Kitchener. 1999. Available from: http://www.efm.bris.ac.uk/het/aristotle/ethics.pdfAugustovski FA, Irazola VE, Velazquez AP, Gibbons L, Craig BM: Argentine valuation of the EQ-5D health states. Value in health 2009, 12(4):587-596. Epub 2009/11/11 10.1111/j.1524-4733.2008.00468.xBernert S, Fernandez A, Haro JM, Konig HH, Alonso J, Vilagut G, et al.: Comparison of different valuation methods for population health status measured by the EQ-5D in three European countries. Value in health 2009, 12(5):750-758. Epub 2009/06/06 10.1111/j.1524-4733.2009.00509.xCervellati M, Sunde U: Life expectancy and economic growth: The role of the demographic transition. Discussion Paper No 2 St. Gallen. Switzerland: Research Center for Ageing, Welfare and Labour Analysis (SCALA); 2009.Cervellati M, Sunde U: Disease and development: The role of life expectancy reconsidered. Econ Lett 2011, 113(3):269-272. 10.1016/j.econlet.2011.08.008Chatters LM: Religion and health: public health research and practice. Annual review of public health 2000, 21: 335-367. Epub 2000/07/08 10.1146/annurev.publhealth.21.1.335Chen B, Mahal A: Measuring the health of the Indian elderly: evidence from National Sample Survey data. Population health metrics 2010, 8: 30. Epub 2010/11/18 10.1186/1478-7954-8-30Cleland JA, Lee AJ, Hall S: Associations of depression and anxiety with gender, age, health-related quality of life and symptoms in primary care COPD patients. Family practice 2007, 24(3):217-223. Epub 2007/05/17 10.1093/fampra/cmm009Cook EL, Harman JS: A comparison of health-related quality of life for individuals with mental health disorders and common chronic medical conditions. Public Health Rep 2008, 123(1):45-51. Epub 2008/03/20Dolan P, Gudex C, Kind P, Williams A: Valuing health states: a comparison of methods. Journal of health economics 1996, 15(2):209-231. Epub 1996/03/08 10.1016/0167-6296(95)00038-0Evans DB, Lauer JA, Tandon A, Murray CJ: Determinants of Health System Performance: Second-Stage Efficiency Analysis. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:693-698.Fayers PM, Machin D: Quality of life The assessment, analysis and interpretation of patient-reported outcomes. 2nd edition. John Wiley & Sons Ltda: West Sussex; 2007.Gulis G: Life expectancy as an indicator of environmental health. European Journal of Epidemiolog 2000, 16(2):161-165. 10.1023/A:1007629306606Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al.: Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5 L). Quality of life research 2011, 20(10):1727-1736. Epub 2011/04/12 10.1007/s11136-011-9903-xHorsman J, Furlong W, Feeny D, Torrance G: The Health Utilities Index (HUI): concepts, measurement properties and applications. Health and quality of life outcomes 2003, 1: 54. Epub 2003/11/14 10.1186/1477-7525-1-54Institute of Medicine, National Academy of Science: Summarizing population health directions for the development and application of population metrics. Washington, D.C: Committee on Summary Measures of Population Health; 1998.Jeremic V, Seke V, Radojicic Z, Jeremic D, Markovic A, Slovic D, et al.: Measuring health of countries: a novel approach. HealthMED 2011, 5(6):1762-1766.Jia H, Moriarty DG, Kanarek N: County-level social environment determinants of health-related quality of life among US adults: a multilevel analysis. Journal of community health 2009, 34(5):430-439. Epub 2009/06/26 10.1007/s10900-009-9173-5Konerding U, Moock J, Kohlmann T: The classification systems of the EQ-5D, the HUI II and the SF-6D: what do they have in common? Quality of life research 2009, 18(9):1249-1261. Epub 2009/09/04 10.1007/s11136-009-9525-8Krabbe PF, Peerenboom L, Langenhoff BS, Ruers TJ: Responsiveness of the generic EQ-5D summary measure compared to the disease-specific EORTC QLQ C-30. Quality of life research 2004, 13(7):1247-1253. Epub 2004/10/12le Hoi V, Chuc NT, Lindholm L: Health-related quality of life, and its determinants, among older people in rural Vietnam. BMC public health 2010, 10: 549. Epub 2010/09/14 10.1186/1471-2458-10-549McDonough CM, Tosteson AN: Measuring preferences for cost-utility analysis: how choice of method may influence decision-making. PharmacoEconomics 2007, 25(2):93-106. Epub 2007/01/26 10.2165/00019053-200725020-00003McHorney CA, Ware JE Jr, Raczek AE: The MOS 36-Item Short-Form Health Survey (SF-36): II Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical care 1993, 31(3):247-263. Epub 1993/03/01 10.1097/00005650-199303000-00006McHorney CA, Ware JE Jr, Lu JF, SCD : The MOS, 36-item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Medical care 1994, 32(1):40-66. 10.1097/00005650-199401000-00004Molla M, Madans J, Wagener D, Crimmins E: Summary measures of population health: Report of findings on methodologic and data issues. Hyattsville, MD: National Center for Health Statics; 2003. [cited 2013. Available from: http://www.cdc.gov/nchs/data/misc/pophealth.pdfMolla M, Madans J, Wagener D, Crimmins E: Summary measures of population health: Report of findings on methodologic and data issues. Hyattsville, MD: National Center for Health Statics; 2003.Murray CJ, Frenk J: A framework for assessing the performance of health systems. Bull World Health Organ 2000, 78(6):717-731. Epub 2000/08/05Mykletun A, Stordal E, Dahl AA: Hospital Anxiety and Depression (HAD) scale: factor structure, item analyses and internal consistency in a large population. The British journal of psychiatry 2001, 179: 540-544. Epub 2001/12/04 10.1192/bjp.179.6.540NAUGHTON MJ, Shumaker SA, Anderson RT, Czajkowski SM: Psychological Aspects of Health-Related Quality of Life Measurement: Tests and Scales. In Quality of Life and Pharmaco economics in Clinical Trials. Edited by: Spilker B. New York: Lippincott-Raven; 1996:117-131.Neumann PJ, Jacobson PD, Palmer JA: Measuring the value of public health systems: the disconnect between health economists and public health practitioners. American journal of public health 2008, 98(12):2173-2180. Epub 2008/10/17 10.2105/AJPH.2007.127134OMS: Official records of the world health organization. Geneva: World Health Organization; 1948. Ginebra: Organización Mundial de la Salud; 1948 [cited 2013 Abril]; Available from: http://www.who.int/library/collections/historical/es/index3.html Ginebra: Organización Mundial de la Salud; 1948 [cited 2013 Abril]; Available from:Paternina D, Melguizo E: Calidad de vida en adultos mayores. Revisión sistemática. V encuentro institucional semilleros de investigación. Cartagena, Colombia: Universidad de Cartagena; 2010.PATRICK D, Erickson P: Health Policy, Quality of Life: Health Care Evaluation and Resource Allocation. New York: Oxford University Press; 1993.Pereira CC, Palta M, Mullahy J, Fryback DG: Race and preference-based health-related quality of life measures in the United States. Quality of life research 2011, 20(6):969-978. Epub 2010/12/25 10.1007/s11136-010-9813-3Poole JL, Steen VD: The use of the Health Assessment Questionnaire (HAQ) to determine physical disability in systemic sclerosis. Arthritis care and research 1991, 4(1):27-31. Epub 1991/03/01 10.1002/art.1790040106Prause W, Saletu B, Tribl GG, Rieder A, Rosenberger A, Bolitschek J, et al.: Effects of socio-demographic variables on health-related quality of life determined by the quality of life index–German version. Human psychopharmacology 2005, 20(5):359-365. Epub 2005/06/28 10.1002/hup.699Prieto L, Sacristan JA: Problems and solutions in calculating quality-adjusted life years (QALYs). Health and quality of life outcomes 2003, 1: 80. Epub 2003/12/23 10.1186/1477-7525-1-80Pyne JM, Sieber WJ, David K, Kaplan RM, Hyman Rapaport M, Keith WD: Use of the quality of well-being self-administered version (QWB-SA) in assessing health-related quality of life in depressed patients. Journal of affective disorders 2003, 76(1–3):237-247. Epub 2003/08/29Roset M, Badia X, Mayo NE: Sample size calculations in studies using the EuroQol 5D. Quality of life research 1999, 8(6):539-549. Epub 1999/11/05 10.1023/A:1008973731515Salomon JA, Murray CJ, Ustün TB, Chatterji S: Health state valuations in summary measures of population health. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:693-698.Sanders BS: Measuring Community Health Levels. American journal of public health and the nation's health 1964, 54: 1063-1070. Epub 1964/07/01 10.2105/AJPH.54.7.1063Tajvar M, Arab M, Montazeri A: Determinants of health-related quality of life in elderly in Tehran Iran. BMC public health 2008, 8: 323. Epub 2008/09/24 10.1186/1471-2458-8-323Tandon A, Lauer JA, Evans DB, Murray CJ: Health system efficiency: Concepts. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:683-692.Thacker SB, Stroup DF, Carande-Kulis V, Marks JS, Roy K, Gerberding JL: Measuring the public's health. Public Health Rep 2006, 121(1):14-22. Epub 2006/01/19Torrance GW: Toward a utility theory foundation for health status index models. Health services research 1976, 11(4):349-369.Vogels T, Verrips GH, Verloove-Vanhorick SP, Fekkes M, Kamphuis RP, Koopman HM, et al.: Measuring health-related quality of life in children: the development of the TACQOL parent form. Quality of life research 1998, 7(5):457-465. Epub 1998/08/06Von Neumann J, Morgenstern O: Theory of games and economic behavior. 3rd edition. New York: Jhon Wiley and Sons; 1967.Wang H, Kindig DA, Mullahy J: Variation in Chinese population health related quality of life: results from a EuroQol study in Beijing, China. Quality of life research 2005, 14(1):119-132. Epub 2005/03/26 10.1007/s11136-004-0612-6Ware JE Jr, Sherbourne CD: The MOS 36-item short-form health survey (SF-36) I. Conceptual framework and item selection. Medical care 1992, 30(6):473-483. Epub 1992/06/11 10.1097/00005650-199206000-00002WHO: WHOQOL: measuring quality of life. 1997. Available from: http://www.who.int/mental_health/media/68.pdfWHO: Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003.Wright DR, Wittenberg E, Swan JS, Miksad RA, Prosser LA: Methods for measuring temporary health States for cost-utility analyses. PharmacoEconomics 2009, 27(9):713-723. Epub 2009/09/18 10.2165/11317060-000000000-00000Zarate V, Kind P, Valenzuela P, Vignau A, Olivares-Tirado P, Munoz A: Social valuation of EQ-5D health states: the Chilean case. Value in health 2011, 14(8):1135-1141. Epub 2011/12/14 10.1016/j.jval.2011.09.00