Articles de revues : « Poor rates »

1

Ash, Arlene. « Identifying Poor-Quality Hospitals with Mortality Rates ». Medical Care 34, n^o 8 (août 1996) : 735. http://dx.doi.org/10.1097/00005650-199608000-00001.

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BERTMAN, JONATHAN, et NEIL SKOLNIK. « Poor Usability Keeps EHR Adoption Rates Low ». Family Practice News 40, n^o 8 (mai 2010) : 54. http://dx.doi.org/10.1016/s0300-7073(10)70596-x.

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Holt, Lynda. « Fracture rates between poor and affluent children ». Emergency Nurse 7, n^o 10 (mars 2000) : 6. http://dx.doi.org/10.7748/en.7.10.6.s5.

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Tan, Xiaoping, et Wanlong lin. « Can poor farmers afford higher micro-credit interest rates than the un-poor ? » China Agricultural Economic Review 8, n^o 1 (1 février 2016) : 100–111. http://dx.doi.org/10.1108/caer-07-2013-0095.

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Purpose – The purpose of this paper is to test whether there is higher return rate of investment for poor farmers than for un-poor farmers and to discuss its implication for poverty reduction microcredit rate policy. Design/methodology/approach – By using the household-level data of six provinces of China, farmer household production function is used in this paper to estimate the investment return rate of farmer. Findings – The paper indicates that regardless which kind of grouping standard is adopted, the investment return rates of poor farmer households in general are far lower than the non-poor. In general, the richer a farmer household, the higher is the return rate of his household productive operations. Practical implications – The study of this paper reminds policy makers that poverty reduction microcredit rate should really take endurance capacity of poor farmers for credit rate into accounting because of the low return rate of their family investment. Exorbitant credit rate should be avoided to protect the credit right of poor farmers. Originality/value – There is seldom study on the comparison of return rates of family operation investment between poor and un-poor farmers; there is also unenough empirical study on the rationality of high interest rate on poor households from the return rate of investment point of view. The authors expect this paper will have some contribution on these two points.

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Arehart-Treichel, Joan. « Surprising Finding Characterizes Depression Rates in Poor Regions ». Psychiatric News 46, n^o 20 (21 octobre 2011) : 17. http://dx.doi.org/10.1176/pn.46.20.psychnews_46_20_17_1.

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Cohn, A. « Readmission rates are a poor marker of quality ». BMJ 348, jan29 1 (29 janvier 2014) : g1148. http://dx.doi.org/10.1136/bmj.g1148.

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BRUNK, DOUG. « Influenza Vaccine Rates Poor Among High-Risk Adolescents ». Internal Medicine News 41, n^o 4 (février 2008) : 34. http://dx.doi.org/10.1016/s1097-8690(08)70214-2.

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Dixon, Bruce K. « Poor Physician Communication Faulted for Colon Screening Rates ». Family Practice News 36, n^o 8 (avril 2006) : 54. http://dx.doi.org/10.1016/s0300-7073(06)73042-0.

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Nakamura, Yui. « Policies for increasing school completion rates for the poor ». International Journal of Asian Social Science 13, n^o 9 (1 septembre 2023) : 263–70. http://dx.doi.org/10.55493/5007.v13i9.4873.

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Human capital accumulated through education is a key factor in increasing individual income. Therefore, policies that aid in increasing school enrollment and completion rates among the poor are essential for poverty alleviation. Despite the fact that primary school enrollment rates in developing countries have increased, there remains a significant gap in school completion rates. This study focuses on the decisions individuals make regarding completing their education to obtain future job-related skills. We clarify factors that increase school enrollment and completion rates and indicate the effectiveness and priority of policies to increase the rates through a simple model. Our findings suggest that school policies have limited impact on increasing school enrollment and completion rates, particularly among the poor, who tend to have a high discount rate for the future and focus on the current situation. Therefore, policies that aim to reduce their discount rate should be prioritized. Moreover, we found that extending learning hours at school has a negative impact on the school completion rates of students from poor families. Therefore, policies aimed at improving individual learning environments are effective in increasing rates, especially for the poor. These findings have important implications for policymakers and education practitioners seeking to improve education outcomes and alleviate poverty, especially in developing countries.

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Colombo, Richard A., et Donald G. Morrison. « Blacklisting Social Science Departments with Poor Ph.D. Submission Rates ». Management Science 34, n^o 6 (juin 1988) : 696–706. http://dx.doi.org/10.1287/mnsc.34.6.696.

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Deaton, Angus, et Olivier Dupriez. « Purchasing Power Parity Exchange Rates for the Global Poor ». American Economic Journal : Applied Economics 3, n^o 2 (1 avril 2011) : 137–66. http://dx.doi.org/10.1257/app.3.2.137.

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The global poverty count uses a common global poverty line, often referred to as the dollar-a-day line, currently $1.25 at 2005 international prices, whose construction and application depends on purchasing power parity (PPP) exchange rates for consumption. The price indexes that underlie the PPPs used for this purpose are constructed for purposes of national income accounting, using weights that represent patterns of aggregate consumption, not the consumption patterns of the global poor. We use household surveys from 62 developing countries to calculate global poverty-weighted PPPs and to calculate global poverty lines and new global poverty counts. (JEL C43, E21, F31, I32, O15)

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Cochran, Richard A., Mark L. Jutras et Mary T. Jutras. « Delivery rates in poor responders that decline cycle cancellation ». Fertility and Sterility 78 (septembre 2002) : S141. http://dx.doi.org/10.1016/s0015-0282(02)03759-7.

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Langley, M., D. Marek, L. Weiand, C. Auger, K. M. Doody et K. J. Doody. « Predictability of Poor Blastulation Rates in Repeat IVF Cycles ». Fertility and Sterility 74, n^o 3 (septembre 2000) : S211. http://dx.doi.org/10.1016/s0015-0282(00)01343-1.

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Schneider, Mary Ellen. « Readmission Rates Are Still Poor But Vary by Region ». Caring for the Ages 14, n^o 4 (avril 2013) : 4. http://dx.doi.org/10.1016/j.carage.2013.03.013.

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de Oliveira, Paulo Murilo Castro. « Rich or poor : Who should pay higher tax rates ? » EPL (Europhysics Letters) 119, n^o 4 (1 août 2017) : 40007. http://dx.doi.org/10.1209/0295-5075/119/40007.

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Goldfarb, James M. « Cumulative pregnancy rates in women with poor ovarian response ». Fertility and Sterility 109, n^o 6 (juin 2018) : 1004–5. http://dx.doi.org/10.1016/j.fertnstert.2018.02.011.

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Kapoor, M., A. J. Polotsky, M. P. Leondires, S. Richlin, L. Chi et J. M. Hurwitz. « Letrozole in combination with gonadotropins improves implantation rates, ongoing pregnancy rates and decreases cancellation rates in poor responders ». Fertility and Sterility 90 (septembre 2008) : S33—S34. http://dx.doi.org/10.1016/j.fertnstert.2008.07.474.

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Marcuse, Edgar K. « POOR CHILDREN IN RICH COUNTRIES ». Pediatrics 83, n^o 6 (1 juin 1989) : A46. http://dx.doi.org/10.1542/peds.83.6.a46.

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The industrial countries in the world have a higher standard of living than at any time in history, but within the wealthy countries, there are still a number of children who live in poverty. The United States, which is the wealthiest country of six studied (Australia, Canada, Sweden, United States, United Kingdom, West Germany), had the highest poverty rate among children and the second highest poverty rate among families with children. From 1970 to 1987, the poverty rate for children in the United States increased from 15 to 20%. . . Child poverty rates vary enormously by the structure of the child's family. In every country [of the six studied], child poverty rates are at least twice as high, and usually much higher, in single-parent families than in two-parent families. . . . Perhaps the most striking figures are those that show the percentage of all children and of all poor children who are living in families with incomes below the 75% of the US poverty line. Here we find that US poor children are the worst off of children in any country [of the six studied] including Australia, with almost 10% existing at an income level at least 25% below the official US poverty standard. . . .In the United States, black families with children are particularly economically disadvantaged relative to white (non-black and non-Hispanic) families. The poverty rates among black children are three times as high as the rates of white children. Poverty rates of Hispanic children in the United States are double those of white children as well, But the poverty rate of US white children is still 11.4%. . .higher than the poverty rate of all children in [the] other [five] countries except Australia. . . Heterogeneity does matter; poverty rates are different for different populations and US poverty rates are high, due in part to its social and ethnic diversity. But this diversity does not matter enough to explain fully the high poverty of US children in general or even white children in particular. . . . One of the reasons why many children in the United States are poor is that 27% of all poor families with children and 23% of single-parent families receive no public income support. . . . In every other country, at least 99% of both types of families that were defined as poor by the Us poverty line definition receive some type of income support. . . . All the countries, except the United States, have child allowances that reach at least 80% of poor children. . . . Another reason why the United States does less well . . . is because the poverty gap is larger in the United States. . . . The larger the poverty gap, the more income is needed to remove a family from poverty. And the United States, which has the biggest gap for these families, provides the least income support per family. . . . Every country's welfare and other tax transfer programs reflect their own cultural and social philosophies. . . . Any change in the tax and transfer policies must be done within the national context of the country's social philosophy. But international comparisons of the poverty of today's children raise long-term questions. To the extent that poverty of children is related to poverty as adults, the quality of our future work force may be affected by the present poverty of our children. And the poverty of our children today may affect our long-term competitiveness with other wealthy countries who tolerate much less child poverty than does the United States.

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Posel, Dorrit, et Michael Rogan. « Measured as Poor versus Feeling Poor : Comparing Money-metric and Subjective Poverty Rates in South Africa ». Journal of Human Development and Capabilities 17, n^o 1 (10 décembre 2014) : 55–73. http://dx.doi.org/10.1080/19452829.2014.985198.

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Hofer, Timothy P., et Rodney A. Hayward. « Can Early Re-Admission Rates Accurately Detect Poor-Quality Hospitals ? » Medical Care 33, n^o 3 (mars 1995) : 234–45. http://dx.doi.org/10.1097/00005650-199503000-00003.

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21

Cui, W. « Poor nutrition is increasing rates of overweight in developing countries ». BMJ 342, mar22 2 (22 mars 2011) : d1787. http://dx.doi.org/10.1136/bmj.d1787.

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Tanne, J. H. « US abortion rates rise among poor women but fall overall ». BMJ 342, jun02 1 (2 juin 2011) : d3413. http://dx.doi.org/10.1136/bmj.d3413.

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23

Western, Bruce, et Christopher Muller. « Mass Incarceration, Macrosociology, and the Poor ». ANNALS of the American Academy of Political and Social Science 647, n^o 1 (5 avril 2013) : 166–89. http://dx.doi.org/10.1177/0002716213475421.

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The U.S. prison and jail population has grown fivefold in the 40 years since the early 1970s. The aggregate consequences of the growth in the penal system are widely claimed but have not been closely studied. We survey evidence for the aggregate relationship among the incarceration rate, employment rates, single-parenthood, public opinion, and crime. Employment among very low-skilled men has declined with rising incarceration. Punitive sentiment in public opinion has also softened as imprisonment increased. Single-parenthood and crime rates, however, are not systematically related to incarceration. We conclude with a discussion of the conceptual and empirical challenges that come with assessing the aggregate effects of mass incarceration on American poverty.

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Haney, Karen E., Linh Nguyen, Tong Han Chung, Yen-Chi Le, Hannah Reygaerts, Xochitl Olguin et Abigail S. Zamorano. « 54 Poor self-rated mental health affected cervical cancer screening rates during the COVID-19 pandemic ». Gynecologic Oncology Reports 48 (août 2023) : S27—S28. http://dx.doi.org/10.1016/s2352-5789(23)00275-8.

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Webber, Don J., Gail A. Webber, Sebastian Berger et Peter Bradley. « Explaining productivity in a poor productivity region ». Environment and Planning A : Economy and Space 50, n^o 1 (16 octobre 2017) : 157–74. http://dx.doi.org/10.1177/0308518x17735103.

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Productivity is the preferred measure of firm-level efficiency and perceived to reflect resource use rates. Semi-structured interviews with restaurant managers in a tourism-dominated low productivity rural area reveal that they are motivated to supply products that they believe in and to sustain a quality of life that meets their needs rather than striving to achieve higher productivity. Pricing strategies, managerial objectives and local market characteristics are found to radically influence the area’s productivity value. An area’s productivity value might not be an indicator of resource use rates or productive efficiency, and could instead reflect resident managers’ motivations towards money and the presence of opportunities to achieve scale economies.

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Cheema, Aftab Ahmad, et Muhammad Hussain Malik. « Income-Specific Inflation Rates in Pakistan ». Pakistan Development Review 25, n^o 1 (1 mars 1986) : 73–84. http://dx.doi.org/10.30541/v25i1pp.73-84.

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In this paper an attempt has been made to find the inflation rates which were faced by households belonging to different income brackets and living in different areas. The results of this study do not show any consistent pattern of inflation being higher or lower for the rich or the poor households. During 1971-72 and between 1978-79 and 1980-81, households in the lower income brackets were found to be facing lower inflation rates. These were the years when food prices rose at lower rates than those of the prices of non-food items. These differences, however, disappeared in 1981-82 when food prices rose sharply, resulting in a higher inflation rate for the poor than for the rich. The numerical magnitudes of the differences were, however, not very high.

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McCarthy, M. « Obesity rates dip slightly among some poor children in the US ». BMJ 347, aug08 2 (8 août 2013) : f5011. http://dx.doi.org/10.1136/bmj.f5011.

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Lin, Sheng‐Chiao, Yaoh‐Shiang Lin, Bor‐Hwang Kang, Chun‐Hao Yin, Kuo‐Ping Chang, Chao‐Chuan Chi, Ming‐Yee Lin et al. « Sarcopenia results in poor survival rates in oral cavity cancer patients ». Clinical Otolaryngology 45, n^o 3 (25 mars 2020) : 327–33. http://dx.doi.org/10.1111/coa.13481.

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Jensen, Tina Kold, Elisabeth Carlsen, Niels Jørgensen, Jørgen G. Berthelsen, Niels Keiding, Kaare Christensen, Jørgen Holm Petersen, Lisbeth B. Knudsen et Niels E. Skakkebæk. « Poor semen quality may contribute to recent decline in fertility rates ». Human Reproduction 17, n^o 6 (juin 2002) : 1437–40. http://dx.doi.org/10.1093/humrep/17.6.1437.

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Christie, B. « High vCJD rates in Scotland could be due to poor diet ». BMJ 323, n^o 7313 (15 septembre 2001) : 590. http://dx.doi.org/10.1136/bmj.323.7313.590.

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Cruz-Hervert, L. P., L. Garcia-Garcia, L. Ferreyra-Reyes, M. Bobadilla-del-Valle, B. Cano-Arellano, S. Canizales-Quintero, E. Ferreira-Guerrero et al. « Tuberculosis in ageing : high rates, complex diagnosis and poor clinical outcomes ». Age and Ageing 41, n^o 4 (19 mars 2012) : 488–95. http://dx.doi.org/10.1093/ageing/afs028.

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Kaye, L. A., M. C. Antero, A. F. Bartolucci, L. Engmann, C. A. Benadiva et J. C. Nulsen. « Pregnancy rates after euploid embryo transfer for poor responders in IVF ». Fertility and Sterility 107, n^o 3 (mars 2017) : e34. http://dx.doi.org/10.1016/j.fertnstert.2017.02.064.

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KENDIRLI, Selcuk, Sedat KUSGOZOGLU et M. Sakir BASARAN. « Expansion for Who, Markets or The Poor ? » Journal of Economic Development, Environment and People 3, n^o 4 (20 décembre 2014) : 59. http://dx.doi.org/10.26458/jedep.v3i4.86.

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In this study we examine the impacts of expansionary monetary policies executed by the Federal Reserve on poverty in the United States of America. It has been discussed in various studies that the Fed’s expansionary monetary policies create a less positive impact on economy as a whole than financial sector. In this study, the expansionary effects of expansionary policies on the poor living in America will be discussed. The main thesis of the study is that the poor living in the United States benefited less from expansionary monetary policies than either financial sector or the US economy as a whole. When discussing the thesis of the study both employed and unemployed poor will be discussed. Therefore, it will be questioned that the decrease in the unemployment rate is the indicator of the fight against poverty.Indicators such as indices and interest rates in the financial markets, and indicators such as growth rates and unemployment rates in the overall economy are regarded as essential indicators but as for poverty it’s hard to find such regarded indicators. Unfortunately, there are not too many statistics about the poor living in the United States in the reports of the international organizations. Thus the main trouble of the study is that international comparisons are almost impossible. Therefore, various indicators produced by the U.S. government agencies of various indicators will be used in this study.

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Taniyama, A., Y. Watanabe, Y. Nisino et T. Inoue. « 205 INCREASED PREGNANCY RATES OF POOR QUALITY BOVINE EMBRYOS BY ASSISTED HATCHING ». Reproduction, Fertility and Development 19, n^o 1 (2007) : 219. http://dx.doi.org/10.1071/rdv19n1ab205.

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Embryo transfer after superovulation is commonly used for efficient embryo and animal production and for genetic improvement in cattle. However, the quality of collected embryos varies greatly, which affects pregnancy rate. Usually, poor quality embryos are related to low pregnancy rates after embryo transfer and low viability after cryopreservation. Therefore, it is important to improve chances for survival of poor quality embryos after embryo transfer. The objective of this experiment was to improve pregnancy rates by applying the assisted hatching technique to poor quality embryos. Embryos were collected from Japanese Black cows after superovulation on Day 7 post-insemination. After being washed, embryos were morphologically classified. Embryos having more than 30% degenerated cells were assigned as poor quality embryos. The assisted hatching of embryos (cutting the zona pellucida) was performed under a stereoscope or an inverted microscope by making a cutting slit on the zona pellucida for about 20% of its circumference using a micromanipulator equipped with a cutting needle and holding pipette. After cutting, single or two embryos were transferred fresh to one uterine horn of recipient cows on Day 7 of the estrous cycle. Pregnancy and calf production rates were compared between 2 embryo transfer groups composed of fresh zona-cut embryos (ZC group) or fresh embryos with non-cut zonae pellucidae (NZC group). Pregnancy rates were determined by rectal palpation on Day 45, and calf production rates were calculated by the following formula: number of calves born/number of pregnancies. Statistical analysis was carried out using the chi-square test. Pregnancy rates of poor quality embryos in the double ET ZC group (60.3%; 44 pregnancies/73 transfers) were significantly higher (P < 0.05) than those in the single ET NZC group (25.0%; 6 pregnancies/24 transfers) and in the single ET ZC group (44.0%; 37 pregnancies/84 transfers). Calf production rates were 67.3%, 45.5%, and 35.6% for the double ET ZC group, the double ET NZC group, and the single ET ZC group, respectively. Pregnancy rates of poor quality bovine embryos after double ET were remarkably improved by assisted hatching compared with those of single ET with non-assisted hatching. These results suggest that the combined methods of assisted hatching and double ET may be beneficial to produce calves from poor quality embryos.

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Tittelbach-Helmrich, Dietlind, Christian Thurow, Stephan Arwinski, Christina Schleicher, Ulrich T. Hopt, Dirk Bausch, Oliver Drognitz et Przemyslaw Pisarski. « Poor organ quality and donor-recipient age mismatch rather than poor donation rates account for the decrease in deceased kidney transplantation rates in a Germany Transplant Center ». Transplant International 28, n^o 2 (14 novembre 2014) : 191–98. http://dx.doi.org/10.1111/tri.12478.

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Lee, C., M. Stockler, V. Gebski, A. Coates et R. J. Simes. « Outcomes of first-line chemotherapy for advanced breast cancer in women with good versus poor quality of life at baseline ». Journal of Clinical Oncology 27, n^o 15_suppl (20 mai 2009) : 1036. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.1036.

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1036 Background: Health-related quality of life (QL) is an established predictor of outcome in advanced breast cancer. The benefits and harms of chemotherapy in women with poor QL are unclear. Methods: We used data from 378 women receiving classical CMF in the control arms of 3 randomized trials. QL was rated at baseline by patients with linear analogue self-assessment scales (LASA) for physical well-being (PWB), mood, appetite, pain, nausea/vomiting, and overall QL; and by physicians with Spitzer's Quality-Of-Life Index (QL-I). Patients were divided into 3 groups according to their baseline QL scores: good (LASA 0–25, QL-I 5–7), intermediate (LASA 26–65, QL-I 8–10) or poor (LASA 66–100, QL-I 11–15). The main outcomes were overall survival (OS), progression-free survival (PFS), objective tumor response (OTR = CR or PR), weight loss, and grade 3 or 4 adverse events (AE). Results: All aspects of QL, except nausea/vomiting, were significant univariable predictors of OS and PFS. PWB, mood, appetite and QL-I were independently significant predictors of OS in a multivariable model with biomedical factors. Only patient's self-rated poor QL had lower rates of OTR, and higher rates of nonhematological AE than those with good QL (see Table), but rates of hematological AE were similar. Weight loss occurred more frequently in those with poor appetite (OR 5.8, p=0.05) or poor PWB (OR 4.9, p=0.05). Conclusions: Less than 25% of women with poor baseline QL responded to first line CMF but over 25% had severe non-hematological toxicity. Baseline QL predicts these outcomes beyond biomedical factors. [Table: see text] No significant financial relationships to disclose.

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Spurlock, Carl W., M. Ward Hinds, Joseph W. Skaggs et Calixto E. Hemandez. « Infant Death Rates Among the Poor and Nonpoor in Kentucky, 1982 to 1983 ». Pediatrics 80, n^o 2 (1 août 1987) : 262–69. http://dx.doi.org/10.1542/peds.80.2.262.

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The mortality rates of infants born in Kentucky during 1982 and 1983 were analyzed to determine whether there were differences between poor and nonpoor infants. We used computer matching with the Social Insurance Food Stamp files and with the Aid for Families With Dependent Children files to define poor and nonpoor Kentucky resident families. The crude death rate for poor infants was 13.7/1,000 births, and the nonpoor death rate was 10.8/1,000 births. After adjusting for several important variables, we found that the poor infant was at a significantly greater risk for death than the nonpoor infant but only during the postneonatal period (relative risk 2.04, P = .0003). Some differences by sex and race were noted. Sudden infant death syndrome and infections were largely responsible for the poor infants' higher postneonatal mortality risk.

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Kapoor, M., J. M. Hurwitz, A. J. Polotsky, S. S. Richlin, L. Chi et M. P. Leondires. « Letrozole in combination with gonadotropins decreases cancellation rates and improves ongoing pregnancy rates per transfer in poor responders ». Fertility and Sterility 88 (septembre 2007) : S100. http://dx.doi.org/10.1016/j.fertnstert.2007.07.325.

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Jansen, Taylor, Richard Chunga, Chae Man Lee, Shuangshuang Wang, Haowei Wang, Frank Porell, Nina Silverstein et Beth Dugan. « Mental Health Issues in Massachusetts, New Hampshire, and Rhode Island : Findings From the Healthy Aging Data Reports ». Innovation in Aging 4, Supplement_1 (1 décembre 2020) : 95. http://dx.doi.org/10.1093/geroni/igaa057.312.

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Abstract Mental health issues in older adults are prevalent, yet often undetected or untreated and can contribute to poor physical health, increased disability, and higher mortality rates. The current study describes state and local community rates of mental health indicators of older adults 65+ in MA, NH, and RI. Data sources used to calculate rates were: the American Community Survey (2009-2013 RI, 2012-2016 MA and NH), the Medicare Current Beneficiary Summary File (2012-2013 RI, 2015 MA and NH), and the Behavioral Risk Factor Surveillance System (2012-2014 RI, 2013-2015 MA, and 2014-2016 NH). Small area estimation techniques were used to calculate age-sex adjusted community rates for more than 150 health indicators. This research examines disparities in rates for 3 mental health indicators depression, self-reported poor mental health, and self-reported poor/fair health status. Depression rates: MA 31.5% (19.91-48.82%), RI 30% (19.7-38.5%), and NH 28.8% (18.26-40.56%). Self-reported poor mental health: RI 7.5% (4.8-12.5%), MA 7.0% (2.10-16.59%), and NH 6.9% (3.42-10.13%). Self-reported fair/poor health: RI 20.4% (8.6-38.8%), MA 18.0%, (7.2-34.38%), and NH 16.5% (13.31-21.60%). Results showed variability in rates across states. MA had the highest rates of depression, the greatest differences in rates, and access to the most mental health providers. RI had the highest community rates for poor physical and mental health, and the highest percentage of residents age 85+. Understanding the distribution of community rates makes disparities evident, and may help practitioners and policymakers to allocate resources to areas of highest need. Research funded by the Tufts Health Plan Foundation.

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Baştuğ, Muhammet. « How do fluent and poor readers' endurance differ in reading ? » Cypriot Journal of Educational Sciences 12, n^o 4 (30 décembre 2017) : 157–66. http://dx.doi.org/10.18844/cjes.v12i4.2492.

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It was observed in this research that how endurance status of fluent readers and poor readers changed as the text became longer. 40 students who were attending the primary school 4th-grade, 20 of whom were fluent readers and other 20 were poor readers, participated in the research. A narrative text was utilized in the data collection process. Students' oral readings were recorded with a voice recorder and their cores of reading rates and reading accuracy percentages were obtained by listening to the readings. The scores were analyzed with the Friedman and Nemenyi tests. At the end of the analysis, it was seen that fluent readers' reading rates did not differ significantly from the beginning to end of the text whereas poor readers' reading rates differed in favor of the first parts of the text. Accordingly, while the fluent readers read the text at the same rate all the way, the poor readers' reading rates significantly dropped from the beginning towards to the end of the text. Furthermore, fluent readers' reading accuracy percentages differed significantly from the beginning towards the end of the text in favor of the last parts while poor readers' reading accuracy percentages differed in favor of the first parts. As per the finding, whereas fluent readers' reading accuracy percentages gradually increased, poor readers' percentages gradually dropped. In other words, as the reading time and volume increased, poor readers' reading errors increased, too. These results were discussed in the light of the literature.

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Rind, P. « Poor Health Care Leads to African Women's High Rates of Uterine Rupture ». International Family Planning Perspectives 17, n^o 1 (mars 1991) : 34. http://dx.doi.org/10.2307/2133219.

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De Cock, K. M. « Tuberculosis control in resource-poor settings with high rates of HIV infection. » American Journal of Public Health 86, n^o 8_Pt_1 (août 1996) : 1071–73. http://dx.doi.org/10.2105/ajph.86.8_pt_1.1071.

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Apte, Gauri, Natalie Pierre-Joseph, Jessica L. Vercruysse et Rebecca B. Perkins. « Could Poor Parental Recall of HPV Vaccination Contribute to Low Vaccination Rates ? » Clinical Pediatrics 54, n^o 10 (3 juin 2015) : 987–91. http://dx.doi.org/10.1177/0009922815590115.

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Bailit, Jennifer L., Joanne M. Garrett, William C. Miller, Michael J. McMahon et Robert C. Cefalo. « Hospital primary cesarean delivery rates and the risk of poor neonatal outcomes ». American Journal of Obstetrics and Gynecology 187, n^o 3 (septembre 2002) : 721–27. http://dx.doi.org/10.1067/mob.2002.125886.

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Messner, Steven F. « GEOGRAPHICAL MOBILITY, GOVERNMENTAL ASSISTANCE TO THE POOR, AND RATES OF URBAN CRIME ». Journal of Crime and Justice 9, n^o 1 (1 janvier 1986) : 1–18. http://dx.doi.org/10.1080/0735648x.1986.9721320.

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Simfukwe, P., P. W. Hill, B. A. Emmett et D. L. Jones. « Soil classification provides a poor indicator of carbon turnover rates in soil ». Soil Biology and Biochemistry 43, n^o 8 (août 2011) : 1688–96. http://dx.doi.org/10.1016/j.soilbio.2011.04.014.

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Hendriks, Dave J., Egbert R. te Velde, Caspar WN Looman, László FJMM Bancsi et Frank JM Broekmans. « Expected poor ovarian response in predicting cumulative pregnancy rates : a powerful tool ». Reproductive BioMedicine Online 17, n^o 5 (janvier 2008) : 727–36. http://dx.doi.org/10.1016/s1472-6483(10)60323-9.

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Elford, K. J., et A. Leader. « Ganirelix, a GnRH antagonist, significantly reduces IVF cancellation rates in ‘poor responders’. » Fertility and Sterility 76, n^o 3 (septembre 2001) : S176—S177. http://dx.doi.org/10.1016/s0015-0282(01)02520-1.

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Confino, Edmond, Xingqi Zhang et Ralph Kazer. « GnRH flare improves pregnancy rates only in a subset of poor responders ». Fertility and Sterility 78 (septembre 2002) : S179. http://dx.doi.org/10.1016/s0015-0282(02)03873-6.

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Davies, R. R., R. Butts, M. Bano, R. D. Jaquiss et R. C. Kirk. « Regional Variation in Donor Refusal Rates Correlates with Poor Wait List Outcomes ». Journal of Heart and Lung Transplantation 38, n^o 4 (avril 2019) : S21—S22. http://dx.doi.org/10.1016/j.healun.2019.01.036.

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Articles de revues sur le sujet « Poor rates »

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