56 research outputs found

    The necessity for monitoring insurance companies and the reasons for developing Iranian accounting standard No. 28

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    Nowadays, it is essential for Iranian insurance companies to provide monthly online reports on the performance, including the issued insurance policies and paid losses to the Central Insurance. The purpose of sending reports is to ensure compliance with the approved rates from insurance companies as well as other relevant regulations (see tariff control). All insurance companies are required to use the approved rates issuing the insurance contracts based on tariff control. In these circumstances there will be no possibility of competition between insurance companies. To attract more customers, adjustment of rates to change the contents of the contract is not possible. On the other hand, as the increase in market size happens, the insurance regulatory body oversees tariff uses and it is not able to monitor individually the rates of the insurance companies. Therefore, it is forced to limit their monitoring to the insurance rates which are high. Therefore, the secret violations and errors of insurance companies grow. To address the above problem, the Audit Organization of Iran with the help of Central Insurance issued accounting standard No. 28in 2006. The standard financial control has been replaced by a tariff control. This paper attempts to review the literature related to the current control of the insurance industry. The Iranian Accounting Standard No. 28 will also be extensively analysed

    The necessity for monitoring insurance companies and the reasons for developing Iranian accounting standard No. 28

    Get PDF
    Nowadays, it is essential for Iranian insurance companies to provide monthly online reports on the performance, including the issued insurance policies and paid losses to the Central Insurance. The purpose of sending reports is to ensure compliance with the approved rates from insurance companies as well as other relevant regulations (see tariff control). All insurance companies are required to use the approved rates issuing the insurance contracts based on tariff control. In these circumstances there will be no possibility of competition between insurance companies. To attract more customers, adjustment of rates to change the contents of the contract is not possible. On the other hand, as the increase in market size happens, the insurance regulatory body oversees tariff uses and it is not able to monitor individually the rates of the insurance companies. Therefore, it is forced to limit their monitoring to the insurance rates which are high. Therefore, the secret violations and errors of insurance companies grow. To address the above problem, the Audit Organization of Iran with the help of Central Insurance issued accounting standard No. 28in 2006. The standard financial control has been replaced by a tariff control. This paper attempts to review the literature related to the current control of the insurance industry. The Iranian Accounting Standard No. 28 will also be extensively analysed

    Socioeconomic Status Index to Interpret Inequalities in Child Development

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    How to Cite This Article: Ahmadi Doulabi M, Sajedi F, Vameghi R, Mazaheri MA, Akbarzadeh Baghban AR. Socioeconomic Status Index to Interpret Inequalities in Child Development. Iran J Child Neurol. Spring 2017; 11(2):13-25.AbstractObjectiveThere have been contradictory findings on the relationship between Socioeconomic Status (SES) and child development although SES is associated with child development outcomes. The present study intended to define the relationship between SES and child development in Tehran kindergartens, Iran.Materials & Methods This cross-sectional survey studied 1036 children aged 36-60 month, in different kindergartens in Tehran City, Iran, in 2014-2015.The principal factor analysis (PFA) model was employed to construct SES indices. The constructed SES variable was employed as an independent variable in logistic regression model to evaluate its role in developmental delay as a dependent variable.Results The relationship between SES and developmental delay was significant at P=0.003. SES proved to have a significant (P<0.05) impact on developmental delay, both as an independent variable and after controlling risk factors.Conclusion There should be more emphasis on developmental monitoring and appropriate intervention programs for children to give them higher chance of having a more productive life.  1. Haghdoost AA. Complexity of the Socioeconomic Status and its Disparity as a Determinant of Health. Int J Prev 2012; 3(2):75. 2. Behavioral and social sciences research. Measuring Socioeconomic Status. e-Source 2013; Available from:http://www.esourceresearch.org 3. Bradley RH, Corwyn RF. Socioeconomic status and child development. Annu Rev Psychol 2002;53(1):371-99. 4. de Moura DR, Costa JC, Santos IS, Barros AJ, Matijasevich A, Halpern R, et al. Risk factors for suspected developmental delay at age 2 years in a Brazilian birth cohort. Paediatr Perinat Epidemiol 2010;24(3):211-21. 5. Feinstein L. Inequality in the early cognitive development of British children in the 1970 cohort. Economica 2003;70(277):73-97. 6. Anderson LM, Shinn C, Fullilove MT, Scrimshaw SC, Fielding JE, Normand J, et al. The effectiveness of early childhood development programs: A systematic review. Am J Prev Med 2003;24(3):32-46. 7. Health CoSDo. Early child development: a powerful equalizer: final report for the World Health Organization’s Commission on the Social Determinants of Health. 2007. 8. Sadock BJ, Sadock VA. Kaplan and Sadock’s synopsis of psychiatry: Behavioral sciences/clinical psychiatry: Lippincott Williams & Wilkins; 2011. 9. Vameghi R, Hatamizadeh N, Sajedi F, Shahshahanipoor S, Kazemnejad A. Production of a native developmental screening test: the Iranian experience. Child Care Health Dev 2010;36(3):340-5. 10. Radomski MV, Latham CAT. Occupational therapy for physical dysfunction: Lippincott Williams & Wilkins; 2008.P.197. 11. Myers K.M. & Collett B. Psychiatric Rating Scales, In: Cheng K. & Myers K.M. Child and Adolescent Psychiatry, Lippincott Williams & Wilkins, Baltimore, Maryland: The Essentials; 2007 .P.17-40. 12. Siddiqi A, Hertzman E, Irwin LG, Hertzman C. Early child development: A powerful equalizer. Improving equity in health by addressing social determinants. 2012:115-141. Avaliable from : www.who.int 13. Marmot M, Friel S, Bell R, Houweling TA, Taylor S, Health CoSDo. Closing the gap in a generation: health equity through action on the social determinants of health. The Lancet 2008;372(9650):1661-9. 14. Commission on Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of health (final report). Geneva: World Health Organization, 2008. 15. Regalado M, Halfon N. Primary care services promoting optimal child development from birth to age 3 years: review of the literature. Arch Pediatr Adolesc Med 2001;155(12):1311-22.16. Kershaw P, Warburton B. A Comprehensive Policy Framework for Early Human Capital Investment in BC. 2009. Available from : www.vancouversun.com 17. Grantham-McGregor S, Cheung YB, Cueto S, Glewwe P, Richter L, Strupp B, et al. Developmental potential in the first 5 years for children in developing countries. The lancet 2007;369(9555):60-70. 18. Andraca Id, Pino P, La Parra Ad, Rivera F, Castillo M. Factores de riesgo para el desarrollo psicomotor en lactantes nacidos en óptimas condiciones biológicas. Rev Saude Publica 1998;32(2):138-47. 19. Lima M, Eickmann S, Lima A, Guerra M, Lira P, Huttly S, et al. Determinants of mental and motor development at 12 months in a low income population: a cohort study in northeast Brazil. Acta Paediatr 2004;93(7):969-75. 20. Walker SP, Wachs TD, Gardner JM, Lozoff B, Wasserman GA, Pollitt E, et al. Child development: risk factors for adverse outcomes in developing countries. The lancet 2007;369(9556):145-57. 21. Guo G, Harris KM. The mechanisms mediating the effects of poverty on children’s intellectual development. Demography 2000;37(4):431-47. 22. Chilton M, Chyatte M, Breaux J. The negative effects of poverty & food insecurity on child development. Indian J Med Res 2007;126(4):262. 23. Miller JE. Developmental screening scores among preschoolaged children: The roles of poverty and child health. J Urban Health 1998;75(1):135-52. 24. Glascoe FP. Early detection of developmental and behavioral problems. Pediatr Rev 2000;21(8):272-80. 25. Rydz D, Srour M, Oskoui M, Marget N, Shiller M, Birnbaum R, et al. Screening for developmental delay in the setting of a community pediatric clinic: a prospective assessment of parent-report questionnaires. J Pediatr 2006;118(4):e1178-e86. 26. Glascoe F. Early detection of developmental and behavioral problems. Pediatr Rev 2000;21(8):272-80. 27. Sajedi F, Vameghi R, Habibollahi A, Lornejad H, Delavar B. Standardization and validation of the ASQ developmental disorders screening tool in children of Tehran city. Tehran Univ Med J 2012;70(7). 28. Shahshahani S, Vameghi R, Azari N, Sajedi F, Kazemnejad A. Validity and Reliability Determination of Denver Developmental Screening Test-II in 0-6 Year– Olds in Tehran. Iran J Pediatr 2010;20(3):313. 29. Afraz F, Ahmadi M, Sajedi F, Akbarzadeh bagheban A. Development Status of 4-24 Months Children Born to Teenage Mothers Referred to Health Care Centers in Yasuj, 2013. YUMSJ 2015;20(3):253-63. 30. Shahshahani S, Vameghi R, Azari N, Sajedi F, Kazemnejad A. Comparing the Results of Developmental Screening of 4-60 Months Old Children in Tehran Using ASQ & PDQ. Iran Rehab J 2011;9:3-7. 31. Shaahmadi F, Khushemehri G, Arefi Z, Karimyan A, Heidari F. Developmental Delay and Its Effective Factors in Children Aged 4 to12 Months. Int J Pediatr 2015;3(1.1):396-402. 32. Karami K AL, Moridi F, Falah F, Bayat Z, Pourvakhshoori N. Evaluation criteria and factors associated with the development of one year old children in Khorramabad. J Pediatr Nurs 2015. 2015;1(3):57-64. 33. Dorre F, Fattahi Bayat G. Evaluation of children’s development (4-60mo) with history of NICU admission based on ASQ in Amir kabir Hospital, Arak. J Ardabil Univ Med Sci 2011;11(2):143-50. 34. Sajedi F,Doulabi M, Vameghi R, Baghban A, Mazaheri MA, Mahmodi Z, Ghasemi E. Development of Children in Iran: A Systematic Review andMeta-Analysis. Glob J Health Sci 2016; 8(8): 145–161. 35. Tervo RC. Identifying patterns of developmental delays can help diagnose neurodevelopmental disorders. Clin Pediatr (Phila) 2006;45(6):509-17. 36. Sajedi F, Vameghi R, Kraskian Mujembari A. Prevalence of undetected developmental delays in Iranian children. Child Care Health Dev 2014;40(3):379-88. 37. Spencer N. Social, economic, and political determinants of child health. Pediatrics 2003;112(Supplement 3):704- 6. 38. Rafiey H VM, Sajjadi H, Ghaed, Amini Gh. Family Income and Child Health in Iran: Recognition of Intermediary Variables’ Role using Sructured Equation Models. Hakim Res J 2015(3).2010-2014 39. Poon JK, Larosa AC, Pai GS. Developmental delay: timely identification and assessment. Indian Pediatr 2010;47(5):415-22. 40. Conger RD, Conger KJ, Martin MJ. Socioeconomic status, family processes, and individual development. J Marriage Fam 2010;72(3):685-704. 41. Sajedi F, Vameghi R, Mohseni Bandpei MA et al. Motor developmental delay in 7500 Iranian infants: Prevalence and risk factors. Iran J Child Neurol 2009;3(3):43-50. 42. Potijk MR, Kerstjens JM, Bos AF, Reijneveld SA, de Winter AF. Developmental delay in moderately preterm-born children with low socioeconomic status: risks multiply. J Pediatr 2013;163(5):1289-95. 43. Brooks-Gunn J, Duncan GJ. The effects of poverty on children. Future Child 1997:55-71. 44. CatL-TEoP. Children and the Long-Term Effects of Poverty. The connecticut commission on children. 2004. June .Available from :https://www.cga.ct.gov. 45. Komro KA, Flay BR, Biglan A, Consortium PNR. Creating nurturing environments: A science-based framework for promoting child health and development within high-poverty neighborhoods. Clin Child Fam Psychol Rev 2011;14(2):111-34. 46. Canadian Institute for Health Information and Canadian Population Health Initiative,. Improving the Health of Canadians. Summary Report [electronic Resource]. Canadian Institute for Health Information.2004. Available from :https://www.cihi.ca 47. Evans GW. The environment of childhood poverty. Am Psychol. 2004;59(2):77.92 48. Elbers J, Macnab A, McLeod E. Article originale. Can J Rural Med 2008;13(1).9-14 49. Richter J, Janson H. A validation study of the Norwegian version of the Ages and Stages Questionnaires. Acta Paediatr 2007;96(5):748-52. 50. Glascoe FP. Screening for developmental and behavioral problems. Ment Retard Dev Disabil Res Rev 2005;11(3):173-9. 51. Squires J, Bricker D, Potter L. Revision of a parent-completed developmental screening tool: Ages and Stages Questionnaires. J Pediatr Psychol 1997;22(3):313- 28. 52. Lindsay NM, Healy GN, Colditz PB, Lingwood BE. Use of the Ages and Stages Questionnaire to predict outcome after hypoxic - ischaemic encephalopathy in the neonate. J Paediatr Child Health 2008;44(10):590-5. 53. Yu LM, Hey E, Doyle LW, Farrell B, Spark P, Altman DG, et al. Evaluation of the Ages and Stages Questionnaires in identifying children with neurosensory disability in the Magpie Trial follow - up study. Acta Paediatr 2007;96(12):1803-8. 54. Vameghi R, Sajedi F, Mojembari AK, Habiollahi A, Lornezhad HR, Delavar B. Cross-cultural adaptation, validation and standardization of Ages and Stages Questionnaire (ASQ) in Iranian children. Iran J Public Health 2013;42(5):522. 55. Fukuda Y, Nakamura K, Takano T. Municipal socioeconomic status and mortality in Japan: sex and age differences, and trends in 1973–1998. Soc Sci Med 2004;59(12):2435-45. 56. Morasae EK, Forouzan AS, Majdzadeh R, Asadi-Lari M, Noorbala AA, Hosseinpoor AR. Understanding determinants of socioeconomic inequality in mental health in Iran’s capital, Tehran: a concentration index decomposition approach. Int J Equity Health 2012;11(1):1-13. 57. Rohani-Rasaf M, Moradi-Lakeh M, Ramezani R, Asadi- Lari M. Measuring socioeconomic disparities in cancer incidence in Tehran, 2008. SN:1513-7368 (Print); 1513- 7368 (Linking).Asian Pac J Cancer Prev 2012;13(6):2955- 60. 58. Moradi-Lakeh M, Ramezani M, Naghavi M. Equality in safe delivery and its determinants in Iran. Arch Iran Med 2007;10(4):446-51. 59. Krefis AC, Schwarz NG, Nkrumah B, Acquah S, Loag W, Sarpong N, et al. Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana. Malar J 2010;9(1):201. 60. Najafianzadeh M, Mobarak-Abadi A, Ranjbaran M, Nakhaei M. Relationship between the Prevalence of Food Insecurity and Some Socioeconomic and Demographic Factors in the Rural Households of Arak, 2014.Iran J Nutr Sci Food Technol 2015;9(4):35-44. 61. de Onis M, Blössner M, Villar J. Levels and patterns of intrauterine growth retardation in developing countries. Eur J Clin Nutr 1998;52:S5-15. 62. Paiva GSd, Lima ACVMd, Lima MdC, Eickmann SH. The effect of poverty on developmental screening scores among infants. Sao Paulo Med J 2010;128(5):276-83. 63. Najman JM, Aird R, Bor W, O’Callaghan M, Williams GM, Shuttlewood GJ. The generational transmission of socioeconomic inequalities in child cognitive development and emotional health. Soc Sci Med 2004;58(6):1147-58. 64. Evans GW, Kim P. Childhood poverty and health cumulative risk exposure and stress dysregulation. Soc Sci Med 2007;18(11):953-7. 65. Duncan GJ, Brooks-Gunn J. Consequences of growing up poor: Russell Sage Foundation; 1999.p . 132-189. 66. Duncan GJ, Yeung WJ, Brooks-Gunn J, Smith JR. How much does childhood poverty affect the life chances of children? Am Sociol Rev 1998:406-23. 67. Aber JL, Jones S, Cohen J. The impact of poverty on the mental health and development of very young children. 2nd ed. New York, NY, US: Guilford Press; 2000. p. 113- 128. 68. Stein AD, Behrman JR, DiGirolamo A, Grajeda R, Martorell R, Quisumbing A, et al. Schooling, educational achievement, and cognitive functioning among young Guatemalan adults. Food & Nutrition Bulletin 2005;26(Supplement 1):46S-54S. 69. Sigman M, McDonald MA, Neumann C, Bwibo N. Prediction of cognitive competence in Kenyan children from toddler nutrition, family characteristics and abilities. J Child Psychol Psychiatry 1991;32(2):307-20. 70. Paxson C, Schady N. Cognitive development among young children in Ecuador the roles of wealth, health, and parenting. J Hum Resour 2007;42(1):49-84. 71. Hart B, Risley TR. Meaningful differences in the everyday experience of young American children: Paul H Brookes Publishing Meaningful differences in the everyday experience of young American children; 1995. 268. p 72. Lejarraga H, Pascucci MC, Krupitzky S, Kelmansky D, Bianco A, Martínez E, et al. Psychomotor development in Argentinean children aged 0–5 years. Paediatr Perinat Epidemiol 2002;16(1):47-60. 73. Najman J, Bor W, Morrison J, Andersen M, Williams G. Child developmental delay and socio-economic disadvantage in Australia: a longitudinal study. Soc Sci Med 1992;34(8):829-35. 74. Nicholson JM, Lucas N, Berthelsen D, Wake M. Socioeconomic inequality profiles in physical and developmental health from 0–7 years: Australian National Study. J Epidemiol Community Health 2010:jech. 2009.103291. 75. Berger SE, Theuring C, Adolph KE. How and when infants learn to climb stairs. Infant Behav Dev 2007;30(1):36-49. 76. Sajedi F, Barati H. The effect of Perceptual Motor Training on Motor Skills of preschool children.Iran Rehab J 2014;12(19):30-40. 77. Eickmann SH, Lima AC, Guerra MQ, Lima MC, Lira PI, Huttly SR, et al. Improved cognitive and motor development in a community-based intervention of psychosocial stimulation in northeast Brazil. Dev Med Child Neurol 2003;45(08):536-41. 78. Garrett P, Ng’andu N, Ferron J. Poverty experiences of young children and the quality of their home environments. Child Dev 1994;65(2):331-45. 79. Walker SP, Chang SM, Powell CA, Grantham-McGregor SM. Effects of early childhood psychosocial stimulation and nutritional supplementation on cognition and education in growth-stunted Jamaican children: prospective cohort study. The Lancet 2005;366(9499):1804-7. 80. Thompson RA, Nelson CA. Developmental science and the media: Early brain development.Am Psychol 2001;56(1):5. 81. Jednoróg K, Altarelli I, Monzalvo K, Fluss J, Dubois J, Billard C, et al. The influence of socioeconomic status on children’s brain structure. PLoS One 2012;7(8):e42486. 82. Hackman DA, Farah MJ. Socioeconomic status and the developing brain. Trends Cogn Sci 2009;13(2):65-73. 83. Otero GA. Poverty, cultural disadvantage and brain development: a study of pre-school children in Mexico. Electroencephalogr Clin Neurophysiol 1997;102(6):512- 6. 84. Otero G, Pliego-Rivero F, Fernández T, Ricardo J. EEG development in children with sociocultural disadvantages: a follow-up study. Clin. Neurophysiol 2003;114(10):1918-25. 85. Hackman DA, Farah MJ, Meaney MJ. Socioeconomic status and the brain: mechanistic insights from human and animal research. Nat Rev Neurosci 2010;11(9):651-9. 86. Hamadani J, Grantham-McGregor S. Report of the family care indicators project: Validating the family psychosocial indicators in rural Bangladesh. Report to UNICEF Early Child Development Desk. 2004.87. Baker-Henningham H, Powell C, Walker S, Grantham- McGregor S. Mothers of undernourished Jamaican children have poorer psychosocial functioning and this is associated with stimulation provided in the home. Eur J Clin Nutr 2003;57(6):786-92. 88. Paxson CH, Schady NR. Cognitive development among young children in Ecuador: the roles of wealth, health and parenting: World Bank Policy Research Working, 2005 May. Paper 3605 Available from : http://econ.worldbank. org . 89. Foster MA, Lambert R, Abbott-Shim M, McCarty F, Franze S. A model of home learning environment and social risk factors in relation to children’s emergent literacy and social outcomes. Early Child Res Q 2005;20(1):13-36. 90. Evans GW. A multimethodological analysis of cumulative risk and allostatic load among rural children. Dev Psychol 2003;39(5):924. 91. Lupien SJ, King S, Meaney MJ, McEwen BS. Can poverty get under your skin? Basal cortisol levels and cognitive function in children from low and high socioeconomic status. Dev Psychopathol 2001;13(03):653-76. 92. McEwen BS, Gianaros PJ. Stress-and allostasis-induced brain plasticity. Annu Rev Med 2011;62:431. 93. Blair C. Stress and the Development of Self-Regulation in Context. Child Dev Perspect 2010;4(3):181-8. 94. Liston C, McEwen B, Casey B. Psychosocial stress reversibly disrupts prefrontal processing and attentional control. Proc Natl Acad Sci 2009;106(3):912-7. 95. Lupien SJ, Maheu F, Tu M, Fiocco A, Schramek TE. The effects of stress and stress hormones on human cognition: Implications for the field of brain and cognition.Brain Cogn 2007;65(3):209-37. 96. McEwen BS, Gianaros PJ. Central role of the brain in stress and adaptation: links to socioeconomic status, health, and disease. Ann N Y Acad Sci 2010;1186(1):190- 222. 97. Jack S, Philips D. From neurons to neighborhoods: The science of early childhood development. National Academy Press Washington, DC; press; 2000.p.289. 98. Sajedi F, Alizad V, Malekkhosravi G, Karimlou M, Vameghi R. Depression in mothers of children with cerebral palsy and its relation to severity and type of cerebral palsy. Acta Med Iranica 2010;48(4):250-4. 99. Murray L, Cooper PJ. Effects of postnatal depression on infant development. Arch Dis Child 1997;77(2):99-101. 100. Evans GW, Boxhill L, Pinkava M. Poverty and maternal responsiveness: The role of maternal stress and social resources. Int J Behav Dev 2008;32(3):232-7. 101. DiPietro JA. Baby and the brain: Advances in child development. Annu Rev Public Health 2000;21(1):455- 71. 102. Evans GW. Child development and the physical environment. Annu Rev Psychol 2006;57:423-51. 103. McKenzie DJ. Measuring inequality with asset indicators. J Popul Econ 2005;18(2):229-60. 104. Ranjbaran M, Soori H, Etemad K, Khodadost M. Relationship between Socioeconomic Status and Health Status and Application of Principal Component Analysis. Journal of Jiroft University of Medical Sciences 2014;1(1):9-19. 105. Kolenikov S, Angeles G. Socioeconomic status measurement with discrete proxy variables: Is principal component analysis a reliable answer?Rev Income Wealth 2009;55(1):128-65

    Living with Multiple Sclerosis: A Phenomenological Study of Worries, Concern and Psychological Problems in Iranian Patients with MS

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    Multiple sclerosis (MS), as a progressive and degenerative illness, has an impact on different aspects of individual lives and may lead to difficulties, concerns, and worries in patients. The aim of the present study was to investigate concerns, worries and problems in patients with MS. We used a descriptive phenomenological qualitative approach. Participants were volunteers purposively selected based on their availability. We carried out deep interviews with 15 MS patients and analyzed the detailed information obtained from these interviews by using Colaizzi’s method. We extracted six essential themes and thirty-four sub-themes associated with MS from the content of the interviews. The main themes were labelled “Confronting existential concerns,” “Crisis of facing up with the illness,” “Suffering from the illness,” “Relationship,” “Confrontation with spirituality and religion,” “Searching for tranquility.” Results of the present study also reiterated the following: Patients with MS seem to lose meaning of life and this together with problems in dealing with existential concerns, may lead to the “disintegration of self,” hence resulting in considerable psychological disturbance and distress. It is concluded that the illness evokes psychological injury such as existential anxiety, relationship disturbance and hopelessness, and these psychological injuries can lead to relapsing of MS

    Health Behavior Constructs Scale (HBCS) for Breast Cancer Screening: Development, Validity and Reliability

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    Introduction: Given the importance of screening as one of the health behaviors in breast cancer, the aim of this research is to develop and evaluate the psychometric characteristics of Health Behavior Constructs Scale (HBCS) for breast cancer screening.Methods: In this cross sectional study, 376 women who referred to Javaheri Health Center during the study period due to health problems, were selected through convenience sampling method. Then, the instrument was developed and its content and face validities were examined. To ensure divergent and convergent validity, Depression Anxiety Stress Scale (DASS-21) was used. Internal consistency method (Cronbach's alpha) was used to determine the reliability of the questionnaire. Finally, confirmatory factor analysis was used to assess the construct validity of the Health Behavior Constructs Scale and SPSS and LISREL software were applied for analyzing data.Results: The findings of this study provided strong supports, which confirmed the content and face validities. Regarding the convergent and divergent validity, perceived vulnerability, perceived severity and deterioration, and perceived barriers have a direct and significant relationship with the three variables of depression, anxiety, and stress. On the other hand, perceived self-efficacy and perceived motivation had a significant inverse correlation with all three variables of depression, anxiety, and stress. The results of the Cronbach's alpha indicated the appropriate internal consistency of the whole questionnaire and its components. Cronbach's alpha for the whole questionnaire was 0.75. According to confirmatory factor analysis, the goodness of fit indicators of proposed model were confirmed and all paths were significant.Conclusion: HBCS is a reliable and valid tool for measuring the screening behavior of breast cancer in Iranian women and it appears to be a comprehensive and useful instrument for assessing women's beliefs related to breast cancer and breast cancer screening

    Relationship of Mothers’ Psychological Status with Development of Kindergarten Children

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    How to Cite This Article: Firoozeh Sajedi F, Ahmadi Doulabi M, Vameghi R, Mazaheri MA, Akbarzadeh Baghban AR. Relationship of Mothers’ Psychological Status with Development of Kindergarten Children. Iran J Child Neurol. Summer 2016; 10(3):61-72. AbstractObjectiveGiven the importance of children’s development and the role of psychological status of mothers in this regard, this study investigated the relationship of mothers’ psychological status (stress, anxiety and depression) with the development of children aged 36-60 months.Materials & MethodsThis descriptive study was performed on 1036 mothers and their children, aged 36 to 60 months, in different kindergartens in Tehran City, Iran, in 2014-2015.Participants were selected through multi-stage random sampling. The following instruments were used in this study: A demographic and obstetric specification questionnaire, children specification questionnaire, the Beck Depression Inventory, Spiel Berger Test, Perceived stress questionnaire and the Ages and Stages Questionnaire to determine the status of the children’s development.Data were analyzed using SPSS20 software, Mann-Whitney; independent t-test and logistic-Regression model were used.ResultsThe prevalence of developmental delay in children aged 36-60 months was 16.2%. The independent t-test showed a relationship between maternal stress and developmental delay in children. The Mann-Whitney test revealed a significant relation between mothers’ depression level and developmental delay in their children. There was a significant relation between trait anxiety and developmental delay in children. Moreover, a significant relation was found between maternal stress and developmental delay in fine motor skills.The logistic regression model showed a significant relationship of child gender, economic and social states with developmental delay.ConclusionThis study showed mothers’ psychological status probably is an effective factor in developmental delay. The assessment of mothers’ psychological status is suggested for early interventions. ReferencesIrwin LG, Siddiqi A, Hertzman C. Early child development: a powerful equalizer. Final report to the WHO Commission on social determinants of health, Geneva. 2007.Guralnick MJ. Early Intervention for Children with Intellectual Disabilities: Current Knowledge and Future Prospects. J Appl Res Intellect Disabil 2005;18(4):313-24.Marmot M, Friel S, Bell R, Houweling TA, Taylor S. Commission on Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of health. Lance 2008 Nov 14;372(9650):1661-1669.Boyle CA, Boulet S, Schieve L, Cohen RA, Blumberg SJ, Yeargin-Allsopp M, Visser S, Kogan MD. Trends in the Prevalence of Developmental Disabilities in US Children, 1997–2008. Pediatrics 2011; 27: 1034-1042.Sherr EH, Shevell MI. Global developmental delay and mental retardation/ intellectual disability. In: Swaiman KF, Ashwal S, Ferriero DM, Schor NF.eds Pediatric neurology:principles and practice. 5th ed. Philadelphia: Elsevier Saunders, 2012:554–74.Al-Naddawi M, Ibraheem MF, Alwan SH, Causes of Global Developmental Delay in Children Welfare Teaching Hospital-Baghdad. IPMJ 2013;12(3):383-9.Vohr BR, O’Shea M, Wright LL, editors. Longitudinal multicenter follow-up of high-risk infants: why, who, when, and what to assess. Seminars in Perinatology; 2003: Elsevier.Rydz D, Srour M, Oskoui M, Marget N, Shiller M, Birnbaum R, et al. Screening for developmental delay in the setting of a community pediatric clinic: a rospective assessment of parent-report questionnaires. PEDIATRICS 2006;118(4):e1178-e86.Glascoe FP. Early detection of developmental and behavioral problems. Pediatr Rev 2000;21(8):272-80.Potijk MR, Kerstjens JM, Bos AF, Reijneveld SA, de Winter AF. Developmental delay in moderately preterm-born children with low socioeconomic status: risks multiply. Pediatrics 2013;163(5):1289-95.de Moura DR, Costa JC, Santos IS, Barros AJ, Matijasevich A, Halpern R, et al. Risk factors for suspected developmental delay at age 2 years in a Brazilian birth cohort. Paediatr Perinat Epidemiol 2010;24(3):211-21.Poon JK, Larosa AC, Pai GS. Developmental delay: timely identification and assessment. Indian Pediatr 2010;47(5):415-22.Tervo RC. Identifying patterns of developmental delays can help diagnose neurodevelopmental disorders. Clin Pediatr 2006;45(6):509-17.Afraz S, Ahmadi M, Sajedi F, Akbarzadeh Baghban A. 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    خصوصیات اپیدمیولوژیک فوت شدگان ناشی از سوانح ترافیکی موتورسواری شهر دزفول در سال 1399

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    Background and Objectives: Although there are no exact statistics on the number of motorcycles in Iran, apparently due to the danger and increasing use of motorcycles, the incidence of motorcycle-related traffic accidents in Iran is rapidly increasing. Therefore, the present study aims to determine the epidemiological status of accidents leading to death in motorcyclists in Dezful, Iran. Materials and Methods: The present study was a descriptive-analytical and cross-sectional study that was conducted in 2021. The statistical population included the deaths due to motorcycle traffic accidents, whose burial certificates were issued by the office of legal medicine in Dezful. The samples were selected as a census from legal medicine statistics during the years 2015-2018. The data were confidentially entered into a researcher-made checklist without mentioning the name of the deceased and then analyzed using SPSS 24. Results: The highest number of victims was under 30 years old and the lowest number was 40-50. The cause of death was due to head injuries (63.8 percent), multiple trauma (26.2 percent), bleeding (5.7 percent), and other reasons (4.3 percent). Most of the deaths were related to men and due to traffic accidents that occurred in September, October, and November months. Also, 50.4 percent of the accidents occurred in the city and 49.6 percent on suburban roads. Conclusion: Most of the traffic accidents among motorcyclists are related to the youth age group. Therefore, it is imperative to pay attention to this group in order to reduce casualties. Therefore, appropriate traffic culture should be promoted and measures should be taken to reduce the occurrence of accidents by strictly enacting and enforcing the laws. How to cite this article: Eghtedari MA, Mazaheri M, Grami A, Shoush A. Epidemiologic characteristics of traffic injury mortality among motorcycle users in Dezful in 2020.  Irtiqa Imini Pishgiri Masdumiyat. 2022;10(2): 116-23.سابقه و هدف: اگرچه آمار دقیقی از تعداد موتورسیکلت در سطح کشور وجود ندارد، اما ظاهراً به علت ماهیت غیر ایمن و افزایش روزافزون استفاده از آن، بروز سوانح ترافیکی مرتبط با موتورسیکلت در کشور به‌سرعت رو به افزایش باشد، لذا مطالعه حاضر باهدف تعیین وضعیت اپیدمیولوژیک حوادث ترافیکی منجر به مرگ در موتورسواران شهر دزفول انجام شد. روش بررسی: پژوهش حاضر از نوع توصیفی-تحلیلی و مقطعی بود که در سال ۱۳۹۹ انجام شد. جامعه آماری شامل فوت‌شدگان ناشی از حوادث ترافیکی با موتورسیکلت بودند که گواهی دفن آن‌ها توسط پزشکی قانونی شهرستان دزفول صادرشده بود. نمونه‌های موردبررسی به‌صورت سرشماری از آمار پزشکی قانونی و طی سال‌های ۱۳۹۷-۱۳۹۴ انتخاب شدند. داده‌ها به‌صورت محرمانه در چک‌لیستی محقق ساخته بدون ذکر نام متوفی وارد شد و سپس با استفاده از نرم‌افزار SPSS ویرایش ۲۴ تجزیه‌وتحلیل شدند. نتایج: بیشترین قربانیان را افراد زیر ۳۰ سال و کمترین افراد را ۵۰-۴۰ ساله‌ها تشکیل می‌دادند. علت مرگ در 63.8 درصد موارد ضربه به سر، 26.2 درصد مولتیپل تروما، 5.7 درصد خونریزی و 4.3 درصد سایر علل بود. بیشتر فوتی‌ها مربوط به مردان و ناشی از سوانح ترافیکی مربوط به شهریور، مهر و آبان بود. همچنین 50.4 درصد حوادث در شهر و 49.6 درصد حوادث در جاده‌های برون‌شهری اتفاق افتاده بود. نتیجه‌گیری: اکثر حوادث ترافیکی در موتورسواران مربوط به گروه سنی جوانان می‌باشد، بنابراین توجه به این گروه در جهت کاهش تلفات اهمیت زیادی دارد. لذا بایستی فرهنگ‌سازی مناسب صورت پذیرد و با وضع و اجرای سخت‌گیرانه قوانین، اقداماتی جهت کاهش رخداد سوانح انجام شود. How to cite this article: Eghtedari MA, Mazaheri M, Grami A, Shoush A. Epidemiologic characteristics of traffic injury mortality among motorcycle users in Dezful in 2020.  Irtiqa Imini Pishgiri Masdumiyat. 2022;10(2): 116-23

    Marital Satisfaction and Depression in Mothers of 3-4 Year Old Children with Developmental Delay in Comparison with Mothers of Normal Children

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    ObjectivesThe present study evaluated the depression and marital satisfaction in mothers of 36-48 months old children with developmental delay in comparison with mothers of normal children.Materials & MethodsThis cross-sectional study was performed on 616 mothers and their children, aged 36 - 48 months, from Apr 2015 to Feb 2016, in some kindergartens in Tehran, Iran. Participants were selected through multi-stage random sampling. The children were divided according to the developmental status into two groups of normal development and developmental delay. The following instruments were used: A demographic and children specification questionnaire, marital satisfaction scale, the Beck Depression Inventory, and the Ages and Stages Questionnaire.  The data were analyzed using SPSS16 software. Independent t-test and Pearson correlation were employed at significance level of 0.05.Results The mean age of children with developmental delay and normal development was 41.94±4.48 and 42.17±5.02 months, respectively. The prevalence of developmental delay in children aged 36-48 months was 17.4% and in normal development children was 82.6%. Developmental delay in boys was 23%. The highest incidence of developmental delays was in fine motor skills. Independent t-test revealed a significant difference between mothers' depression and marital satisfaction with and without developmental delays (P=0.0001). In addition, the correlation was observed between the mother’s depression and marital satisfaction (P=0.0001).ConclusionMothers of children with developmental delay suffer more from depression and have less marital satisfaction compared to mothers of healthy children. Interventional studies to reduce depression and increase marital satisfaction and its impact on development status should be conducted.Keywords: Depression; Developmental delay; Marital status; Satisfactio

    CN2F: A Cloud-Native Cellular Network Framework

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    Upcoming 5G and Beyond 5G (B5G) cellular networks aim to improve the efficiency and flexibility of mobile networks by incorporating various technologies, such as Software Defined Networking (SDN), Network Function Virtualization (NFV), and Network Slicing (NS). In this paper, we share our findings, accompanied by a comprehensive online codebase, about the best practice of using different open-source projects in order to realize a flexible testbed for academia and industrial Research and Development (R&D) activities on the future generation of cellular networks. In particular, a Cloud-Native Cellular Network Framework (CN2F) is presented which uses OpenAirInterface's codebase to generate cellular Virtual Network Functions (VNFs) and deploys Kubernetes to disperse and manage them among some worker nodes. Moreover, CN2F leverages ONOS and Mininet to emulate the effect of the IP transport networks in the fronthaul and backhaul of real cellular networks. In this paper, we also showcase two use cases of CN2F to demonstrate the importance of Edge Computing (EC) and the capability of Radio Access Network (RAN) slicing
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