This paper uses UNICEF’s Multiple Indicators Cluster Surveys cross-country data to shed light on unequal investments in the wellbeing of children (boys and girls) within the household. The paper proposes a new methodology to measure the extent of gender intrahousehold inequality and its contribution to overall levels of inequality using an L-Theil index decomposition. The individual and joint distribution of inequality in four key indicators of child wellbeing is analyzed: stunting, birth registration, school attendance, and time spent on work and chores (working hours) in the search for evidence of gender bias. Evidence from various separate county studies had shown that the direction of the gender bias is not universal. Such conclusion holds when using a consistent methodology and comparable cross-country datasets; this paper shows that disparities inside households do not follow the same bias toward one or the other gender in all countries and the direction of the bias is not the same across indicators of wellbeing. While progress in improving child wellbeing has occurred in many countries, inequalities remain. Intrahousehold inequalities might still be considered a priority in an agenda focused on closing these progress gaps. Collective models of household behavior, that explicitly incorporate the interactions that occur within households in the determination of the internal resource allocation, are useful to explain the presence of different outcomes for different household members, particularly children and along gender lines. Still, many empirical measures of wellbeing have treated households as if their members enjoy an equal share of all household resources. For analytical convenience, most policy analysis assumes that, within households, individual wellbeing is the adult-equivalent average of the household to which the individual belongs; this can lead to an underestimation of overall poverty and inequality . When hoExamining and tackling the differences that occur within households is important for ensuring children’s wellbeing and the realization of their rights. Unequal household investments in children tend to carry over into adulthood. Although other factors can still affect wellbeing over the life-course, systematic biases against boys or girls during childhood are linked to poverty traps and to the intergenerational transmission of poverty .Girls and women are believed to bear a heavy share of the burden of poverty, yet good data and detailed analysis for a wide range of countries are needed to corroborate this claim . PrefereDespite this wide range of country evidence on gender biases, systematic evaluations of cross-country evidence of the extent and the direction of the bias of intrahousehold inequality in child wellbeing are uncommon. In addition, inequalities in different dimensions may balance each other out, for example when parents compensate underinvestment in one area with overinvestment in another. The aim of this paper is to use existing cross-country data to shed light on unequal investments in the wellbeing of children (boys and girls) within the household. The individual and joint distribution of inequality in four key indicators of child wellbeing is analyzed: stunting, birth registration, school attendance, and time spent on work and chores (working hours). Knowing more about inequalities inside households, as well as about inequalities occurring across multiple aspects of wellbeing would be of great value to enhance our understanding of the magnitude and nature of child poverty and gender inequality. The next section briefly reviews the key measurement issues that this article engages with, namely the measurement of multidimensional wellbeing, of multidimensional inequality, and of intrahousehold inequality. Section 2(a)The first point of departure for this study is an interest in measuring inequality in child wellbeing from a multidimensional perspective. New ground was broken in the measurement of child poverty and wellbeing with UNICEF’s ‘Global Study on Child Poverty and Disparities’ , which cThe use of household-level data not only conceals differences between household members, particularly children, but also poses an additional problem: if child poverty is made equivalent to overall household poverty, policy responses may address the main underlying causes of poverty but fail to account for child-specific concerns and experiences as well as for intrahousehold inequalities. In the multidimensional poverty context, A crucial discussion then concerns the space in which to measure gender inequalities in child wellbeing. Some spaces may be more problematic than others. For example, measuring inequality in income poverty may be suitable for comparing households but less so for capturing intrahousehold distributions. A monetary metric would be even more unfit for the focus on children. This paper measures inequality in a multidimensional space. This follows the multidimensional definition of child wellbeing set by the 1990 Convention on the Rights of Child (CRC) and the tradition of child wellbeing studies since the aforementioned UNICEF and Bristol studies. A key difference arises from the concern for intrahousehold inequality, which requires the measurement to be carried at the individual level.(b)A key issue in the debates over how to measure gender inequality is whether composite indicators add value . This isAn intermediate approach considers the correlation between dimensions explicitly but without aggregating them. A well known example of this type of analysis is (c)Section A first data limitation, is the absence of individual-level data. Many indicators used to capture the different dimensions of child wellbeing are not cardinal but instead are either ordinal or binary . In this case, even if individual-level data are available, gender inequality cannot be computed as the gap in the outcomes of boys and girls. In this case, it is common to use a regression in which the different outcomes are regressed on a gender dummy. Finally, the interest in this paper is to show the contribution of intrahousehold inequality to overall inequality in child wellbeing. A method which is relevant to capture not only the direction of the bias but also the extent of intrahousehold inequality, is to use a summary inequality measure such as the Gini coefficient or the General Entropy (GE) measures. The advantage is that an aggregate inequality index can be broken down into two components: within-household and between-household inequality, allowing to distinguish the extent of inequality occurring within and between households respectively. 3In this paper, intrahousehold inequality is presented in two ways. The first is the share of households with a gender bias: that is, households that display higher outcomes for either boys or girls. This is derived from household ratios of the achievement of girls to that of boys in each of the indicators. A ratio of one indicates complete parity; ratios greater than one indicate that girls’ achievements are higher than boys’ achievements, and vice versa for ratios lower than one. A bias for girls is evident when girls have more favorable outcomes than boys .This paper follows The method used is to obtain two cardinal values for each household out of the original binary indicators, so that an inequality index can be applied and then de-constructed to assess the contribution of its components, particularly to capture the share of within-household inequality.g = , n is the number of individuals above/below the deprivation threshold and N the total number of individuals.Binary variables are recalculated as the share of girls and boys within a household above a certain threshold.within a household, so the outcome of this transformation is two household-level variables separately representing the outcomes of girls and boys in each household.The units of analysis are the girls or boys Only households that have at least one boy and one girl are kept in the sample for analysis, limiting the number of observations and reducing the sample considerably.9This method proves useful for the gender analysis but it is not able to account for other biases that may occur simultaneously inside households. An important one relates to age. Because child age patterns within each household may affect the level of intrahousehold inequality—for example, older children are likely to work more hours—indicators are ‘cleaned’ of the age effect before using them for the analysis. This would result in a more accurate reflection of gender differences. In a logit regression that uses each outcome as the dependent variable and the age of the child as the only independent variable, the residual—the part that is not explained by age—is used as the clean indicator.10N is the entire sample size, jN is the sample size in each household j, jy is the average for household j, and jL is the inequality (mean log deviation) of each household j. The first term corresponds to the within-group component and the second, to the between-group component. Following With the household-level recalculated variables, a GE index can be computed for each indicator. This study uses an L-Theil index (GE(0)) or mean log deviation, which is a summary measure of the difference between the  shares of the wellbeing measure and the shares of population. It reflects the extent to which the distribution of wellbeing between groups differs from the distribution of the population in those groups. When all the groups have a share of wellbeing equal to their population share, the distribution is completely equal . It also gives a higher weight to the lower end of the distribution, giving higher relevance to those who are more deprived, and is sub-group decomposable. Equation Because the Theil index is unbounded and depends on the unit of measurement, it is difficult to interpret in absolute terms and to make meaningful comparisons of inequality levels across variables measured in different units as is the case in child wellbeing. On the other hand, a Gini coefficient, which ranges from zero to one, gives an indication of the extent of overall levels of inequality, placing higher weight to the middle of the distribution. However, unlike the Theil index, the Gini coefficient is not perfectly decomposable,t-test is used to assess the statistical significance of the changes in inequality and its components across the two periods. A test of proportions (F-test with a 95% significance level) is used to assess the difference between the shares of households favoring boys or girls for each indicator.Inequality measures and corresponding standard errors are computed taking into account sample design, using the sample weights designed and incorporated into each survey by UNICEF. Computations are made with the Distributive Analysis Stata Package (DASP)  in StataData are obtained from UNICEF’s Multiple Indicators Cluster Surveys (MICS). As in the Bristol approach, the dimensions relevant to measuring child wellbeing in this study are defined drawing from the CRC. The dimensions analyzed are restricted to those that can be measured at the individual level and for boys and girls separately in MICS surveys. Some indicators are measured at the individual level, but only for one child in the household, rendering them insufficient for analysis. This has some data shortcomings: of the 17 dimensions of child wellbeing in the CRC, data constraints restrict this study’s analysis to only four of them: nutrition, education, birth registration/nationality, and some components of leisure and child labor. These indicators are measured only for children of a relevant age range, following UNICEF’s standards for global reporting  with infWhile the data source restricts the dimensions of child wellbeing that it is possible to analyze, MICS surveys are a comprehensive and comparable cross-country data source for developing countries and is consequently a good starting point for systematically measuring inequalities in multidimensional child wellbeing across developing countries. In fact, alongside Demographic and Health Surveys (DHS), MICS are used at the global level to track the achievement of the child-related indicators of the global development goals. A total of 20 countries are available to be analyzed see . The metChildren can be deprived in one or many of the dimensions of wellbeing and thus inequality can be measured individually or jointly. As a first instance, this paper analyzes the distribution of each dimension separately, opting for a dashboard approach to the measurement of inequality. In addition, it also aims to find systematic patterns of disadvantage, and thus it needs to look at the joint distribution of inequalities. The paper takes into consideration possible correlations between the various dimensions of welfare by considering joint distributions of the dimensions of wellbeing to see whether there is a systematic gender bias, but without integrating them into a single index.P statistic) for each pairing of indicators  is calculated using the household ratios of achievement of girls to boys. These ratios show whether there is a bias against boys or girls or none in each household. Given that the sample size is reduced with each additional indicator,A measure of association ,Comparisons across countries are not straightforward for another two reasons: firstly, as noted, differences in average household sizes in particular may affect the assessment of inequality. Secondly, the definition and measurement of indicators, although mostly standardized by UNICEF, are not always kept, especially in earlier rounds of the surveys, leading to differences in the way the information is captured for some countries. The results for individual countries can be found in tables in Total inequalities between girls and boys across indicators of child wellbeing are of varying magnitude. On average, across all countries and years the Gini coefficient for working hours is 0.85, showing a large degree of inequality. Inequality in stunting is similarly high: on average, the Gini coefficient is 0.78 for this indicator. The Gini coefficient for birth registration and for school attendance is 0.47. Intrahousehold inequalities are also quite different across indicators and countries. Sections (a)A strong body of evidence shows the detrimental effects of undernutrition. It is a risk factor for poor motor and cognitive child development . Althoug16On average, for all 15 countries and periods in the sample, 24% of boys and 23% of girls are stunted  in both periods, the within-household component contributes to more than 20% of the total inequality, reaching 41% in Lao PDR.In six of the 15 countries with stunting data, overall inequality measured by the Theil index increases between the two periods; in four countries, it decreases; and in five countries, it remains virtually unchanged. But overall, as seen in (b)Unregistered children are deprived of their right to have an identity and may not be able to claim services and protections on an equal basis with other children. Birth registration is costly and difficult for some families. In some countries, parents need to pay a fee to register their children; in others, late registration carries a sanction that can place a heavy economic burden on the family, or may involve other external costs incurred through travel or accommodation and loss of earnings and work time. Sometimes the barriers are not monetary. For example, in Bhutan, children whose father is unknown cannot be registered, and in Indonesia, a marriage certificate is required to register a child’s birth . It is pOn average, for the 19 countries analyzed, 53% of girls and 54% of boys are registered, but with large differences across countries, ranging from 2% in Trinidad and Tobago (2006) to 90% in Guyana (2006–07). On average, the percentage of children registered increases for girls and boys alike, from 50% in the first year in which registration was measured, to about 57% in the second. Again the actual rates differ in each country, but the similar trend for boys and girls is common. Disparities inside the household in terms of ratios of registration for girls and boys occur in about 98% of households, and in most countries there is a bias favoring girls (about 65% of cases on average). Only in Iraq does the bias run in the opposite direction, with less than a quarter of households favoring girls.The between-household component accounts for 78% of total inequality, whereas the remaining 22% corresponds to inequality within households. There is a 20% or higher share of within-household inequality in both periods in Togo, Iraq, Mongolia, and Guyana. For eight countries, the share is below 20% in both periods while for the remaining seven countries, it fluctuates above and below 20% across the two time periods.With the general increase in birth registration rates, overall inequality falls over the two periods. Of the 19 countries with birth registration data, overall inequality between the two periods decreases in eight countries but increases in two (Lao PDR and Swaziland) . In the (c)Education is critical to strengthening people’s capabilities and freedoms . EducatiThe school attendance indicator refers to the number of children reported going to school  during the year of the survey. It is a gross attendance rate, because it includes all children regardless of whether they are attending the appropriate level of education for their age. It does not control for attrition levels or the quality of education, which can vary substantially. Further indicators would be needed to incorporate these important aspects of children’s right to education, where starker inequalities could be present.Several factors can restrict access to education for some children. These range from affordability and physical access barriers  to social and cultural barriers, which can play differently for boys and girls. Reducing distance to school, for example, had a significant effect in increasing girls’ attendance in secondary schools in rural Tanzania, although it had less of an impact for boys . SimilarOn average, school attendance exceeds 80% for both boys and girls for the 18 countries with data, but again the range is wide across the sample. For boys, the range is from 44% in Gambia to 96% in Cameroon, while for girls the range is from 45% to 94% for the same two countries, respectively. In half the number of countries school attendance rates increase between the two periods for girls and boys alike. Once controlling for the different age composition of households, most households have some bias in the distribution of schooling and, interestingly, it runs in favor of girls in both periods for 11 of the 18 countries see . HoweverThere is no clear pattern between average progress in school attendance and either total or within-household inequality , in contIn fact, for this indicator, the share of within-household inequality is 45%, meaning that the within-household component accounts for almost half of the total inequality. For three countries , the within-household component makes the largest contribution to inequality in both periods.On average, total inequality falls over the two periods. In 8 of the 18 countries with schooling data, overall inequality decreases .17 In on(d)Many children engage in work activities. Some work to ‘help their families in ways that are neither harmful nor exploitative, but others are put to work in ways that interfere with their education, drain their childhood of joy and crush their right to normal physical and mental development’ . Most chChild labor is typically measured with reference to a threshold of hours a child is engaged in economic activity; the thresholds to classify work as child labor vary with children’s age. However, such cut-offs can be arbitrary. They carry assumptions about an ideal minimum age of work as well as the amount of time children should have free for education and leisure. For this reason, this study does not use this definition of child labor, preferring instead to measure it by the total number of hours that children spend on these activities. Arguably, this still does not capture the extent to which child work is harmful for child wellbeing , for exaOn average, across all 12 countries girls spend more hours a week (12 h) working and doing chores compared to boys (10 h),The longer hours worked by girls is also reflected when looking at the share of households who show a bias for boys in this indicator see . On averWorking hours follow a similar pattern to stunting. The higher the average number of hours worked by children, the lower the total inequality, but within-household inequality is of a fairly similar magnitude across countries . For exaMost inequality in working hours is accounted for by inequality across households; only 8% of inequality occurs within them. For this indicator, other group-based inequalities, such as location , economic conditions and regional differences may be more important in explaining inequalities. Only for Vietnam is this not the case: within household inequality is 34% in the first period and 14% in the second.Although the number of working hours decreases over the two periods, inequality increases slightly. The Gini index on average is 0.81 in the first year and 0.89 in the second. In fact, total inequality increases in eight of the 12 countries and decreases only in one (Gambia). Within-household inequality on the other hand, falls in absolute and relative terms in six countries  and increases in none .1919(e)Although the sample of countries and indicators is limited in many respects, the analysis of household survey data is illustrative of the presence of inequalities in four dimensions of child rights and wellbeing. Analyzing when such differences exist within households in the realization of children rights is an important aspect of identifying the barriers to ‘leaving no one behind’ and eliminating child poverty.The analysis of the four variables of child wellbeing used here shows that small aggregate differences between girls and boys often obscure intrahousehold inequalities. In the aggregate, inequality is particularly high for stunting and working hours. The decomposition of the inequality index (L-Theil) shows that a large amount of inequality can occur within households, but with significant variation by country and indicator. In some areas, mainly work time, inequality occurs mostly between households. In contrast, inequalities inside households are particularly high for school attendance. They account for close to half of total inequality (over 40%) in 13 out 18 of countries, and in a further three countries, for more than half of total inequality in at least one of the periods. Within-household inequality in stunting and birth registration accounts for around one-fifth of total inequality on average for both periods.The results show that intrahousehold inequality represents between six and 48% of total inequality across the four indicators when looking at averages across all countries. The variability by countries and years is high: the contribution of intrahousehold inequality is lowest in Gambia, Swaziland, and Mongolia (1% in the distribution of school in Gambia and of work time in Swaziland and Mongolia), and highest in Albania (79% in the distribution of birth registration).(f)Previous sections presented a detailed analysis of inequality for each indicator separately. It shows that for most countries, the bias in some indicators favors girls, and in others, it favors boys. Thus, at the country level, it is hard to conclude that there is a systematic bias against either gender. This section analyzes their joint distribution: in other words, it checks whether households tend to favor girls (or boys) in all areas of wellbeing, or rather to compensate for underinvestment in one area with overinvestment in another.The four outcomes presented here are likely to be connected to each other. A birth certificate or identity card is often an administrative requirement for accessing essential services of health and education, so biases in this indicator are expected to be correlated with those in schooling and malnutrition. Similarly, the links between nutrition and education have been widely explored . But outP statistic indicates a preference for boys, the absolute difference between the P statistic for boys and for girls is relatively small (below 0.20). In some cases, the proportion of households favoring girls is considerable. It is 71% for stunting and birth registration; 52% for stunting and school attendance; 33% for stunting and work; 74% for birth registration and school; 75% in birth registration and work; and 58% in school and work.On average, fewer households favor girls in two indicators at the time, but it is noticeable that in three of the cases where the P statistic is 0.71, but this ranges from 0.52 in Mongolia to 0.91 in Nigeria. Similarly, the bias for boys in school attendance and work time ranges from 0.76 in Vietnam to 0.96 in Swaziland.These results vary across countries , with soP statistic for boys and for girls ranges from 0.24 in Kazakhstan to 0.02 in Belize, showing that in the first country there is stronger evidence for boy preference than in the latter. In Albania and Nigeria, the same number of pairings favors girls and boys, but on average, most households favor girls in Albania, whereas most favor boys in Nigeria.In Lao PDR and Trinidad and Tobago, most pairings favor girls, while in the remaining 15 countries, most pairings favor boys.As mentioned in the Introduction, previous studies have produced varying evidence on intrahousehold distributions and the directions of biases, and this study seems to confirm the evidence by systematically examining cross-country data. While there is some overall bias for boys, this is not universal across indicators nor countries. In particular, it is possible that some household characteristics are systematically associated with a more unequal distribution of resources between boys and girls. However, it is likely that these patterns vary across countries and indicators of child wellbeing. The variability in intrahousehold inequality across countries indicators found in this study suggests that biases may respond to different aspects in different countries and may relate to different social gender norms and household institutions. A more in-depth analysis would be needed to uncover the specific mechanisms that drive intrahousehold inequalities in each of the dimensions of child wellbeing presented in this study.5Progress in improving many child wellbeing dimensions has occurred across the globe . HoweverFirst, assessing inequality, and in particular that which occurs within households, is important, even in the context of country progress toward the realization of child rights and wellbeing. When comparing averages between girls and boys, while small differences are noted in many areas of wellbeing, some important disparities remain. Across the sampled countries (12–19 depending on the indicator), the average Gini coefficient for school attendance and for birth registration is 0.47; it is 0.78 for stunting, and 0.85 for working hours. To close the gap between girls and boys, it is important to know where these disparities are located.Second, by using a decomposable measure of inequality (the Theil index) it is shown that significant inequalities occur within households. Between-household inequality in working hours is relatively large  and thus addressing barriers to reduce inequality across households appear to be a priority for closing the gap in this indicator of child wellbeing. For the remaining variables, within-household inequalities are considerable. For stunting and birth registration they are close to a fifth of total inequality, and for school attendance, despite impressive progress, over 40% of gender inequalities occur within households.Third, even when they are lower in absolute terms, intrahousehold inequalities might still be considered a priority in terms of an agenda focused on ‘leaving no one behind’. Although the relatively small timeframe (around five years) and country sample are perhaps insufficient to capture long-term global trends in inequality, looking at how inequality stands for countries at different levels of wellbeing can be illustrative of these trends. Where average levels of child wellbeing increase and total inequality falls, within-household inequalities are more important in relative terms, accounting for a larger share of the total inequality. For example, the analysis shows that intrahousehold inequality in birth registration and school attendance tends to be higher in countries where total inequality is lower, suggesting that the gaps that are more difficult to address may be located inside households. These results indicate that it is not possible to eliminate child poverty and secure the rights of all children unless disparities within households are addressed. A further avenue for research would examine these trends alongside other country characteristics that have been pointed in the literature as mechanisms for the perpetuation of gender biases inside households.Fourth, evidence from a multiplicity of separate county studies had shown that the direction of the gender bias is not universal. Using data from a wider yet diverse set of developing counties the present study is useful to confirm that such conclusion holds when using a consistent methodology and dataset; disparities inside households do not follow the same bias toward one or the other gender and that the direction of the bias is not the same across indicators of wellbeing. For example, in stunting and work hours, most households have a bias for boys while in school attendance and birth registration, most households tend to favor girls. When looking at pairs of indicators, in five of the possible six combinations the majority of households show a preference for boys, and in only one there is an overall preference for girls. Even then, for some pairings, a considerable proportion of households show a preference for girls. The methodology presented in this paper is able to show correlations between dimensions of wellbeing, but is not sufficient to suggest a channel of causality.Fifth, the gender bias is varied across countries, with some showing a more distinctive preference pattern than others. This has been found elsewhere and suggests that biases respond to different social norms and household institutions. Institutions and norms surrounding gender roles, patterns of inheritance, marriage, and divorce, all matter to understand the varying degree and direction of intrahousehold inequality bias. Yet these too are likely to differ across countries. Quantitative analysis to examine what drives intrahousehold inequality on a cross-country basis could contribute to future research. It may be necessary to complement this research with the already flourishing literature that explores on a country basis the social values and norms, as well as the economic logic, which underpin these inequality patterns.This paper is an important contribution to measuring the extent of such inequalities using a systematic methodology and data for 20 developing countries. As pointed out 25 years ago, the neglect of intrahousehold inequality affects the assessment of the levels of poverty, and could lead to a skewed view of the patterns of progress . As withWhile the number of indicators available to carry out a multidimensional analysis is relatively limited compared to what the CRC defines as the dimensions of child wellbeing, it is a good starting point to go beyond the measurement of a single dimension or using a summary indicator of child wellbeing. The methodology presented in the paper could be applied to more complete national-level datasets in future applications. Furthermore, additional cross-country data which allows for this type of distributional analysis with a broader range of indicators would be a valuable contribution to future research. The release of UNICEF’s next round of MICS surveys could be the starting point for this.The varying and sometimes large amount of intrahousehold inequality found in most countries poses difficulties for policy-making. Interventions to address inequalities in child wellbeing may need to be targeted more specifically at individuals or sub-groups within households rather than at households in general , and at


It has been a long time since there were many elderly people in Japan. The medical care and costs for the elderly are enormous, and research to lower the mortality rate of the elderly is needed. We retrospectively investigated the prognostic factors for the survival of elderly patients who were hospitalized in the medical ward of our hospital. In total, 277 patients who were hospitalized between 1 January 2014 and 31 May 2017, were included in the retrospective study. Univariate and multivariate analyses of items  were performed, and significant differences between the survival group and death group were subjected to receiver operating characteristic curve analysis. Serum urea nitrogen levels and serum albumin levels provided a relatively high area under the curve (AUC). However, there was no item for which AUC exceeded 0.70, and setting the cutoff value in this study was difficult. For treating the elderly, it is important to carefully evaluate each patient’s prognostic factors, including the demented state, renal function, and nutritional state; personalized treatment of each patient is also important. The number of Japanese deaths in 2016 was 1,377,748, an increase of 17,304 from 1,294,444 in the previous year, and the death rate (per 1000 people) was 10.5, which was higher than the previous year’s 10.3. The rising trend of this mortality rate is due to the increase in the proportion of elderly people whose mortality rate is higher than other age groups due to the progress of aging. There are some prognostic factors for the survival of elderly patients. For example, an accurate estimation of the length of life for older hospitalized persons may be made using clinical information available from the medical chart plus a brief interview with the patient or surrogate  to determine the risk of malnutrition  [CONUT is an assessment tool to judge nutritional status from serum albumin values, total lymphocyte counts, and total cholesterol blood sampling results ,10. BecaThe results of univariate and multivariate analyses are shown in In the univariate analysis in this study, gender was not involved in the prognostic factors. With regard to age, a significant difference was observed in vital prognosis in multivariate analysis. This suggests that chronological age plays an important role, as does biological age and physical fitness, and the passage of chronological age increases the risk of death and disease in the elderly.Poor prognosis for malignant tumors, cerebral vessels, and cardiovascular disease complications has been reported in respiratory diseases , and ourIn this study, the prognosis of the group with good self-reliance was significantly better, and a tendency for a poor prognosis in the low activity group was observed. This indicates the physical and functional status of the elderly as a prognostic factor.AUC is defined by the ROC curve and is a tool for judging the usefulness of the prognostic factor . In geneGenerally, it is known that factors such as low activity state, anorexia, inflammatory response, and the like have great influences on life prognosis in elderly people with chronic diseases.The older people’s mortality index was developed by four variables extracted from PCA , including BI (Barthel Index), age, hemoglobin, and mid-arm circumference . NutritiSerum high-sensitivity CRP values at admission are predictors of short-term mortality at hospital admission in elderly multimorbid patients . InflammSeverity assessment of dementia is reflected in the prognosis . HoweverIn this study, we could use information obtained by our daily work and apply it to all patients regardless of patient background or illness. With regards to confounding factors, significant information was missing on the charts for variables such as the participants’ socioeconomic status and intervention of rehabilitation, and these could not be analyzed. The use of automated calculation processing via routine assessment by occupational staff other than physicians led to a decreased burden of this study work. Whether the results from this study will result in prognostic improvement is currently unknown and prospective cohort studies are needed in the future. In the study of the elderly prognostic factors in each country and each hospital, there are significant factors and there is a need to unify conditions and to accumulate and compare studies of elderly prognostic factors in each country and each hospital. Overall, for the treatment of the elderly, it is important to carefully evaluate each patient’s prognostic factors including demented state, renal function, and nutritional state, and in the actual clinical practice personalized treatment according to each elderly patient’s needs, the patient’s conditions and above data are also important because there are some differences in the importance of prognostic factors among past reports.


Journal of Educational Evaluation for Health Professions, JEEHP) has been evaluated for inclusion in Scopus by the Content Selection & Advisory Board (CSAB). The review of this title is now complete and the CSAB has advised that the title will be accepted for inclusion in Scopus.”On the morning of January 6, 2019, I received an email from the Scopus Title Evaluation Team stating that “The title mentioned above , adopted in an English-only policy, and became an online-only journal without publication frequency [December 2006: The journal changed its official title to English from Korean  Title of ‘The Korean Journal of ...’ is preferable.(2) Too broad of an area is covered in the journal.(3) The author instructions need to be described more in detail(4) Only one issue is published per year. The number of articles is small.(5) There is no international diversity among authors.(6) Citedness is below expectations. It is weak in the international rankings.(7) The journal covers poor quality of presented research.I and the editorial team have done our best to overcome the above weaknesses. Turning to the above-listed recommendations, it would be difficult to change the title to ‘The Korean Journal of ...’ because JEEHP has already become widely known throughout the world under its present title. Furthermore, authors from Korea accounted for only 21.1% of the articles and reviews published from 2015 to 2018. The top-ranking country of authors is the United States (31.3%). The 147 articles and reviews published during this period were from 48 countries . TherefoEvaluation and the Health Professions, deals with evaluations; however, in addition to educational evaluations, its scope extends to health programs, teaching and training services, and products. However more precise description of the scope was added such as adoption of measurement theory to medical health education.Each journal should have its own specific scope, and the scope of JEEHP is limited to educational evaluations in the field of medical health education. There is no other title in Scopus that has the same scope. One title in Scopus, https://jeehp.org).The author instructions were revised to contain a full description, including general information, research and publication ethics, manuscript preparation, manuscript submission, article processing charge, the peer review and publication process, principles of transparency and best practice of scholarly publishing, copyright information, open access policy, open access license agreement, and contact address, and are available at the journal homepage  XML . Second,I am proud to have been invited to be an editor of this journal, published by a public organization, the Korea Health Professions Licensing Examination Institute, where my senior physician and researcher colleagues have worked and carried out leadership roles with great devotion. I and the editorial team will strive to make the journal more readable and to be well-appreciated by medical and health instructors throughout the world.


Health holds an important position in maintaining economic development since it is both a prerequisite for and an outcome of economic development. This means that health contributes greatly to the attainment of sustainable development and health outcomes. The importance of health is demonstrated in the Millennium Development Goals (MDGs) where three of the eight goals are aimed at improving health outcomes. Despite progress made by other middle-income countries in achieving health-related MDGs, South Africa is still worse off in respect of health outcomes and experiences a challenge in attaining positive outcomes for these goals. This study’s main focus was to identify the association between public health expenditure and health outcomes in South Africa’s nine provinces from 2002 to 2016. The study implemented fixed effects and a random effects panel data estimation technique to control for time effects and individual provincial heterogeneity. This was followed by employing the Hausman specification test to identify the fixed effects model as the appropriate estimator for the study. The study also employed the seemingly unrelated regression (SUR) model and the least squares dummy variable (LSDV) model to examine the impact of public health expenditure on each province separately. The findings elucidated that the relationship between public health expenditure and health outcomes in South Africa varied across provinces depending on provincial management and infrastructure availability. The democratic South African government in 1994 had one task, among many, to provide primary healthcare (PHC) for every South African. The government’s central task was to address the disempowerment, discrimination, and underdevelopment that had weakened the healthcare system over the past few decades . The AfrThe South African constitution is binding to the state in the realisation of the right to basic health care, and yet the burden of HIV/AIDS resulted in some erosion of the aforementioned post-1994 gains and improvements in public healthcare. Despite the 1994 health reforms, the burden of diseases increased fourfold from non-communicable diseases/chronic diseases to communicable diseases such as HIV/AIDS and sexually transmitted infections (STIs). Additionally, violence and injury led to increased mortality rates, which resulted in the loss of healthy lives [Literature has, to some extent, discussed the relationship between public health expenditure and related health outcomes. Panel data estimation techniques have mostly been used in the literature to investigate this aforementioned relationship. However, this has primarily been implemented at country level. Thus, this paper sought to investigate the impact of public health expenditure on health outcomes at a provincial level in South Africa using panel data analysis. Moreover, this study used robust estimators (SCC and FGLS) to econometrically investigate this impact and to also ensure consistent and efficient inferences. For efficient provincial analysis, this paper used SUR and LSDV.The 2017 South African Health Review (SAHR) has captured several points of view on various programmatic activities that were intended to strengthen the health system . Among tPublic health expenditure has been increasing provisionally over the past decade, and the reason behind that was solely towards improving health access to previously disadvantaged South Africans . There iBy the end of the 2014 financial year, the total public health expenditure was measured at 9% of gross domestic product and has since been continuously increasing [The effects of the 2008 recession were delayed in South Africa until around 2011/12 where a sluggish growth in expenditure is displayed in One of the reasons why increased public health expenditure is not reflected by health outcomes is due to control of personnel costs by the government. As elucidated by , personnIt has also been reported  that theThe 2016/17 annual report of the KwaZulu-Natal (KZN) department of health highlighted that despite the challenges that the province faced pertaining to healthcare, considerable levels of success in reducing the burden of disease were registered . SignifiThe Gauteng provincial 2016/17 annual report noted a mixed bag of challenges and successes in their health department. The increased expenditure for the Gauteng province as depicted in The theoretical framework utilized in the paper is the principal-agent problem and the Grossman’s (1972) model of health as derived demand. The Grossman (1972) model is derived from the model of optimal control, where health capital is a consumption good as well as an investment good and it has been argued to be amongst the major contributors to the theoretical framework of health economics . This moEfficiency and equity theories were also reviewed in this study. These are the two main criteria which are usually employed in economic analysis to guide the way in which resources are being allocated and used. The desire for efficiency is derived from the desire to change and improve the world . This imIn the context of healthcare, equity means a fair distribution of health and healthcare amongst the population, and in addition, fairness should be included in the burden of financing healthcare . Though There is limited number of studies that specifically focus on the impact that public health expenditure has on health outcomes in both developed and developing countries. However, with the available literature, there is, to some extent, consensus in terms of the need for improvement of public healthcare sector performance. Most developed countries like Italy have experienced problems with governance, disorganisation, and uncontrolled spending, and these have resulted in the failure of the systems they have put in place. The failure of the local government to carry out decisions which have been taken at national level caused disparities, which have in turn been reflected in poor health outcomes in Italy. Amongst competitive, rich countries, the USA has been reported to have the poorest health outcomes even though their health expenditure is twice as much as other developed countries. Another reported causality for poor US health outcomes is the scarcity of equipped and trained physicians who have the ability to utilise their advanced technological health equipment. It is important to focus on social determinants of health or factors that shape people’s health past their lifestyle choices and medical treatment . This inMost of the challenges exhibited in developing countries, as revealed in literature, include a lack of finances to improve health, a lack of medical personnel  and also their health is bedeviled by the poor environment in which they live. Most countries in the developing world, such as Brazil, have been faced with outdated healthcare systems which affect their ability to carry out all health-related expectations of their citizens. Moreover, major issues in most of these countries include management issues and underfunding of health institutions. In addition to this factor, there is insufficient investment in health by countries in the developing world and this makes it impossible to carry out some of their legislative intents towards making healthcare a universal right .South Africa is faced with an unequal distribution of healthcare services as well as challenges of disease burden and a limited number of medical personnel . With reit is the error term.To examine the impact that public health expenditure has on health outcomes, this study adopted and modified Anyanwu’s model . AnyanwuHea) and it is explained by the shift in variables which are public health expenditure (Phe), provincial gross domestic product (GDP), human immunodeficiency virus (HIV), and the ratio of physicians per province (RoP). The model is specified as follows:i is to capture the nine South African provinces  for the period (t) 2002 to 2016.The explained variable in this study is health outcomes , random effects (RE) and pooled OLS), one was the appropriate estimator for the study and others were not, depending on the type of data or N and T dimensions employed in this study, all of which is presented in this section. In addition to the pooled OLS, FE, and RE, robust standard error estimates are presented towards the end of this section.p-value of 0.0001. These results led to the decision of rejecting the null hypothesis that the pooled OLS is the appropriate estimator for the study. This suggests that the BP/LM test favored the random effects model as the appropriate estimator. Moreover, to detect the appropriate estimator between the fixed effects and the random effects models, the study employed the Hausman test. The random effect regression is only consistent and efficient when errors are not correlated with explanatory variables. Thus, to detect whether errors are correlated with the regressor or not, the paper used the Hausman test. The Hausman test regression results showed a p-value of 0.0054, which is less than 5% (0.05) and a test statistic of 14.70. With the p-value being less than 5% (0.05), the null hypothesis that random effect is the appropriate model for the study could be rejected. Therefore, the fixed effects method became the appropriate estimator for the study. The time-invariant characteristic of the fixed effects model is one of the most important assumptions of the model, thus making it the best model for the study in this regard [Moreover, the diagnostic check assisted in the identification of the correct, robust standard error estimator for this study. The regression results for pooled, FE, and RE estimators are presented in s regard .Although the fixed effect is the appropriate estimator, diagnostic checks were done to check if heteroscedasticity, serial, and cross-sectional correlation exist within the model. Therefore, the paper employed robust estimators  to control for violation of the assumptions of the linear regression. p-value showed statistical significance. A 1 unit increase in Phe would lead to a 0.3% decrease in U5MR. In the FE model, public health expenditure is statistically significant at the 1% level of significance. As aforementioned, in the chosen FE model, the public health expenditure variable has an elasticity of −0.284 suggesting that a 1% increase in public health would lead to about a 0.3% decrease in the under-five mortality rate in South Africa, ceteris paribus. In other words, public health positively influences improvements in the under-five mortality rate. This finding is consistent with [Taking into account that the fixed effects is the appropriate estimator for the model, the public health expenditure variable (variable of interest) has the expected sign, and the ent with ,8. The eent with , which wAlthough the ratio of physician’s variable has the expected sign, it was discovered to have a statistically insignificant impact on U5MR. This outcome shows that it seems like there is no statistically significant relationship between the ratio of physicians and the under-five mortality rate. This finding suggests that there are other factors that impact on the under-five mortality rate that play a greater role in the improvement of this health outcome than the ratio of physicians. An example of this would be the impact that public health expenditure has on the under-five mortality rate. Moreover, HIV and AIDS: Antenatal has the expected sign as depicted in p-value of 0.0007 and a t-value of 19.30 for the life expectancy at birth model. Moreover, the Hausman specification test failed to reject the fixed effects model as a proffered estimator to the random effects model. Public health expenditure (Phe) being the main explanatory variable for this study displayed statistical significance. In column three of Considering the fixed effects model as the appropriate estimator for this study, the ratio of physician’s variable has the expected sign. However, it is a statistically insignificant influencer of life expectancy at birth. Moreover, although statistically insignificant, the regression results for life expectancy at birth under the FE model showed that a 1% increase in HIV and AIDS for total population would lead to a 0.04% decrease in life expectancy at birth. Regarding provincial GDP, it was discovered that there is a 5% significant relationship between GDP and the variable of interest as shown in It is interesting to discover that the chosen FE results reveal that although there is a statistical significance at 5% significance level for GDP, the sign is not as expected. This finding might be due to the indirect relationship between variables. Nevertheless, the results warranted further investigation into the relationship between life expectancy at birth and provincial GDP.In summary, the results have shown that the under-five mortality rate is strongly influenced by public health expenditure. It is interesting to have discovered that the regression results showed no statistical significance between the ratio of physicians and the under-five mortality rate as this relationship has been reported ,23 to beThe seemingly unrelated regression (SUR), Driscoll Kraay (SCC), least squares dummy variables (LSDV) and feasible generalized least of squares (FGLS) were employed for consistent and efficient inferences. To check for the appropriate estimator for the study, the Hausman specification test was employed, and it indicated that the fixed effects estimator is the appropriate estimator for this paper. To analyze the provincial impact of public health expenditure on health outcomes, the SUR was utilized. The main objective of this study was to assess the impact of health expenditure on health outcomes at the provincial level in South Africa. Therefore, In With the consideration that the constant is included in the model, LSDV dropped the output for province (1) in the regression process as depicted in It can also be noted in On the other hand, Policy recommendations and implications are drawn from the empirical results of this study as presented in the preceding section. Empirical findings in this regard indicated that the impact of public health expenditure on health outcomes varies across provinces based on the responsiveness of investigated factors and governance. The South African healthcare sector adopted strategies that include limiting personnel numbers, prioritizing primary healthcare, and a temporary reduction on infrastructure spending . LimitinJust as in the US healthcare system, the South African healthcare system faces challenges that include inefficiencies, healthcare quality, access, and results . These aMost reported under-five mortality rate cases are due to the prevalence of HIV and AIDS, pneumonia and diarrhea. The prevention of mother-to-child transmission has proved to be one of the most significant ways of decreasing U5MR in SA . PolicieThe ability to reduce U5MR represents an important health sector and societal goal at a global and national level . The polIn most developing countries, a significant proportion of death that breeds reduced life expectancy is due to non-communicable diseases such as hypertension, cerebrovascular accident, coronary heart disease, diabetes mellitus, chronic renal disease, and cancer, among others . The latThe key factor that affects life expectancy, as alluded to by other scholars , is econThe most important finding in this study is that empirical results showed a significant relationship between public health expenditure and health outcomes in both models. The SUR individual provincial analysis in this regard showed that this impact varies across provinces. This suggests that there is something that certain provinces are doing well, that leads to a significant relationship between these variables that other provinces are not achieving. The National Department of Health and policymakers need to identify the similarities and differences between the provinces of South Africa in order to be able to enact policies that will benefit each province positively and that are tailored to their specific needs. While trying to find policies that work individually for each province, it is also important to factor in the issue of governance in each province because it is through proper governance that policies can be implemented successfully.


Indeed an important step towards the ultimate goal: a 25% reduction in cases of uncontrolled hypertension on this continent by 2025, as set out in the PASCAR Roadmap on Hypertension.’1This is how the outcome can be described of the first continental meeting in Nairobi, where a delegation of more than 30 key opinion leaders in hypertension and cardiology from Britain, Ireland, India and Africa deliberated for two days to review and Africanise the successful and relevant Indian Certificate Course in the Management of Hypertension (ICCMH*). This emerged during a media conference held at the meeting.Representatives of the Public Health Foundation of India (PHFI) in New Delhi, the International Society of Hypertension (ISH), the British and Irish Hypertension Society (BIHS), the Centre for Chronic Disease Control (CCDC) in New Delhi and the Pan-African Society of Cardiology (PASCAR) gathered in Nairobi to discuss the expansion and customisation of the ICCMH to the African region.The main objective of the course is to train doctors, nurses and community healthcare workers on the continent to diagnose and manage hypertension as effectively as possible at the primary care level, by early diagnosis and better hypertension control, based on guidelines adapted for the African continent and different ethnic groups. This will free the few hypertension specialists on the continent to manage complicated hypertension cases at a tertiary level. The following key aspects were highlighted at the media conference.In excess of 10 million people around the world die each year of hypertension-related diseases, mainly cardiovascular diseases, including stroke. It kills more people in the world than any other communicable disease, said Prof Francesco P Cappuccio, president of the BIHS.The African Union considers hypertension the most important challenge on the continent after HIV/AIDS, but up to now, experts have not succeeded in translating these political decisions into important actions that could change cardiovascular health on the continent, explained Prof Saad Subahi, cardiologist and president of PASCAR’s National Council. This is where PASCAR entered four years ago and initiated the PASCAR Roadmap on Hypertension.A recent situation analysis revealed that hypertension affects one-third (150 million) of the adult population in Africa, but only one-tenth (about 15 million) of these people are aware of the disease, and when they are aware, only one in five people (about three million) is treated. When they are treated, only one in 14 (about 215 000) is treated to such an extent that their risk for renal disease, heart disease or stroke, or dying from hypertension are reduced. This is a dire situation, Prof Subahi said.In the first attempt to increase awareness, more than 20 African countries took part in a huge global initiative in 2017 to screen people for hypertension. This will now be followed by the Africanisation, translation and roll out of the Indian hypertension-education programme in Africa over the next two years, said Prof Neil Poulter, president of the ISH.‘It is our duty to fill a gap. A 25% reduction in undiagnosed, uncontrolled hypertension will mean saving the lives of millions of people every year. It will also reduce morbidity by millions,’ Cappucino reiterated.Following the meeting in Nairobi, the priority actions, as identified in the PASCAR Roadmap on Hypertension, will be implemented to overcome the identified roadblocks. These key elements were highlighted at the media conference:Training and education to increase awareness: PASCAR will roll out the adapted training programme to train the trainers across the African region in the coming months; to ultimately train 250 000 community health workers, 50 000 nurses and 25 000 certified general physicians.Create and customise easy-to-use treatment protocols for different ethnic groups within a proper referral linkage pattern. Poulter shed more light on the possible treatment protocols: ‘The CREOLE trial‘We expect the CREOLE trial to show that a diuretic and a calcium channel blocker (CCB) will be the most effective anti-hypertensive drugs for black patients, but we don’t know yet what combination will be best: a CCB and a diuretic, or a CCB plus angiotensin converting enzyme inhibitor (ACEI), or a diuretic plus an ACEI. If we get this information, it will be a big leap forward. We would like to reproduce the CREOLE trial in South Asia and the Far East, to determine which two drugs are the best for each ethnic group.’High-quality generic anti-hypertensive drugs will be produced and delivered cost effectively by non-profit-making companies. These efforts will hopefully lead to more countries in Africa joining the initiative. Currently only 25% of countries in Africa have a government policy and guidelines to treat and reduce the burden of hypertension,’ Poulter said.


Despite the success of tissue engineered medical products (TEMPs) in preclinical translational research, very few have had success in the clinical market place. This gap, referred to as the “valley of death” is due to the large number of ventures that failed to attract or retain investor funding, promotion, and clinical acceptance of their products. This loss can be attributed to a focus on a bench to bedside flow of ideas and technology, which does not account for the multitude of adoption, commercial, and regulatory constraints. The implementation of an alternative bedside to bench and back again approach permits investigators to focus on a specific unmet clinical need, defining crucial translation related questions early in the research process. Investigators often fail to accurately identify critical clinical adoption criteria due to their focus on improved patient outcomes. Other adoption criteria  can cause a product to fail despite improved patient outcomes. By applying simplified business principles such as the build-measure-learn loop and the business model canvas to early-stage research projects, investigators can narrow in on appropriate research topics and define design constraints. Additionally, 86% of all clinical trials fail to result in Federal Drug Administration approval, resulting in significant economic burdens. On the reverse side, approval through the European Medical Agency is widely considered to be more direct but has its challenges. The Committee for Advanced Therapies within the European Medical Agency has received 22 market authorization applications for advanced therapy medicinal products, of which only 10 received authorization. A thorough understanding of the various regulatory pathways permits investigators to plan for future regulatory obstacles and potentially increase their chances of success. By utilizing a bedside to bench and back again approach, investigators can improve the odds that their research will have a meaningful clinical impact. The last two decades have seen several successful clinical applications of tissue engineered medical products (TEMPs). Autologous cell-based therapies, such as Carticel , have been the most successful  autologous cells harvested from a patient tissue, (2) donor-derived allogeneic cells, and (3) cross-species transplanted xenogeneic cells. While cell-based products will possess some level of risk for immune rejection, the appropriate design controls regarding cell sourcing, processing, and characterization can limit immunogenic uncertainty. Broadly, autologous cells do not require immunosuppressive therapy upon implantation due to their inherent Hellman, . Good maHellman, .in vivo tissue environment are challenging to normalize  the source of tissues and cells, (2) the donation process, and (3) the manipulation of cells to generate the TEMP  as a way of designing products using customer input. Although the BML model is often criticized for difficulty in translation to the TEMP field, there are multiple methodologies within it that investigators can apply early-on to research that will allow them to avoid obstacles. The minimum-valued-product (MVP) is the product that includes its most essential functions, as hypothesized by the inventors, but is not necessarily a totally streamlined product. The MVP can be released to a sample group of customers, who provide feedback that either validates the inventor's hypothesis or prompts them to pivot and redesign their product. An MVP cannot be applied for use in human clinical trials because the system is too inflexible and expensive. However, investigators can and should employ the MVP early on their experimental process, especially in the in-vitro and in-vivo models. The crucial step here is to avoid the bench to bedside approach where an investigator has developed a product and begins to search for a relevant market, but instead has defined a clinical need and begins to develop a TEMP to address that need. This bedside to bench and back again approach allows researchers to define clinically essential criteria in early hypotheses and then utilize the BML to shed extraneous experiments and focus the research on developing a product. A drawback to this approach is that many investigators are not trained to do market research as academia, including the grant funding processes, rarely address these skills. As such, there have been several state and federal programs developed over the past several years the focus of which is to enhance the translation of academic research to the market place.Osterwalder originally proposed the business model canvas (BMC) in 2008, and over the past 10 years, has grown and developed into a useful tool often applied before founding a company  in the US, has both regional and national program components. The express goal of the program is to increase the translation of research to products, a gap identified by Congress who began asking the questions of how research dollars directly benefits the taxpayers who provide them. The I-Corps program focuses on the notion of teaching investigators how to complete market research and providing incentive funds that allow them to leave the lab to execute the market analysis. The programs highlight four components of the BMC; the value proposition, the customer segment, customer relations, and the channels upon which their product will reach their customer. Regional programs usually include small incentives, $1,000–$3,000, and include doing 10–30 interviews. The national I-Corps requires either funding by an NSF grant or participation in a regional I-Corps program. National I-Corps participants are required to conduct over 100 interviews and receive $50,000 to use for travel related to interviews and mentoring sessionsThe creation of a startup company is a daunting task even for the most seasoned entrepreneur, and often overwhelming to academic researchers who wish to translate their ideas. Many investigators fall back on the strength of their research and the corresponding product, expecting that companies will spring up around the product. As discussed above, most pre-clinical research has a long path to travel to reach clinical trials and requires a talented and dedicated entrepreneurial team. Often, the lead investigators of these teams do not wish to give up control of their research. However, academic investigators are rarely motivated to ensure the success of a start-up; already having established careers, well-paying jobs, and many conflicting responsibilities. In these cases, the investigators are better positioned to be Chief Technology Officers or members of the company's advisory board. From there, the investigator is still positioned to give input to the burgeoning company without changing their career path. Often underutilized resources that can greatly benefit a company are post-doctoral students and recently graduated Ph.D. students. At that start of their career, these trainees do not have as many pressures and demands upon their time, and they are intimately familiar with the potential project. They are uniquely positioned to lead the spinout team but should be counterbalanced with an experienced team member. It is essential for all researchers contemplating starting a biotechnology company to understand their own limitations. Rarely do researchers have the necessary background to fill executive positions within the startup. Outside hiring for positions such as the Chief Executive Officer and consulting firms could make the difference between success and failure, regardless of the market strength of the product.The core of any technology-based startup is its intellectual property and patent protection. Patents allow startup companies to maintain a competitive advantage over entrenched competitors as the startup grows. Patentable technology arising from any academic institution or federally funded research falls under the Bayh-Dole Act, passed in 1980. Within the act, the federal government retains several rights but assigns ownership to the institution that the inventor works for Stevens, . It alsoGiven the current globalization of medical affairs, startups should also be looking at international markets. Patenting laws will vary by country, but any patenting within the United States will start a countdown of a year, after which the ability to pursue a patent in other countries will become limited. As one of the largest markets for TEMPs, Europe represents a key area for biotechnology companies to file for patents. It is possible to file in the individual countries, each with their own rules and processes, but it is cheaper to file under the European Patent Convention (EPC). Under the EPC, TEMP patents have similar requirements to the U.S. patent process, namely novelty, the inventive step, and industrial applicability , the Center for Biologics Evaluation and Research (CBER), and the Center for Drug Evaluation and Research (CDER). In the past, a medical product would fall under one of three possible classifications: a device, a biologic, or a drug, and be sent to the appropriate center. With the advent of TEMPs, it is no longer as easy of a task to make those distinctions. Now, a product may be a novel scaffold that releases a drug at a controlled rate or a combination therapy that includes both stem cells and drug treatment. The Office of Combination Products (OCP) was founded to help solve this problem by offering guidance to companies on determining which center they should approach for approval. The critical consideration for investigators is understanding that choice of Center for regulation can significantly affect the time to market. On average, devices are the quickest to be approved (~6 years) while drugs take the longest (~11 years) and biologics fall in between (~9 years)  pathway. The 510(k) pathway requires proving that the device is similar in usage, risk, and efficacy to products available before 1976. The final classification is a class III device, which constitutes products of the highest risk. These devices require premarket approval, the most stringent regulation process in the CDRH and include preclinical and clinical trials. There has been a recent trend toward companies attempting to utilize the 510(k) pathway to avoid the burden of clinical trials  applications. Moreover, the CAT is also responsible for developing new guidelines for the classification of ATMPs, which are published monthly on EMA's website. The application for MA begins with the submission of a comprehensive dossier to CAT that provides details of the product to be reviewed. Scientific specialists at CAT review the quality, safety, and efficacy of ATMPs and prepare a draft opinion based on the non-clinical and clinical data provided by the developers  a cartilage cell-based product, was the first ATMP to be approved in 2009, followed by a gene therapy product called Glybera®  in 2012. Holoclar®  became the first stem cell therapy to be approved by EMA in 2015  required for the development of ATMPs , heart valves, artificial grown livers, and growing cartilage. This pipeline involved a $17 million annual R&D budget, of which ATS saw little return due to multiple failed products. At the same time, revenue from the few successful products failed to meet projections that ATS had set for them. After FDA approval for Dertmagraft in 2001, ATS projected only $7.5 million in revenue in 2002, and $12 million in 2003, much lower than the initial projections used for the original justification of the R&D budget , Smith & Nephew Plc., and Shire Plc. to make Dermagraft profitable despite significant investment. Pangarkar et al. published a case study of ATS in 2010, highlighting several of the key concerns discussed in this article  to their marketing partner, Smith & Nephew, for $12 million as part of their chapter 11 filing. Smith & Nephew would sell Dermagraft and TransCyte® to Advanced Bio-Healing in 2007 for an undisclosed amount. In 2014, Organogenesis purchased Dermagraft for $300 million from Shire, who in turn had acquired Advanced Bio-Healing for $750 million in 2011 (Fikes, The path from the bench to human application is potentially long with many unexpected turns and potentially full of minefields, where each decision can have far-reaching consequences. In order to increase the likelihood of clinical success, investigators need to look beyond the benchtop and consider the direction their research will follow and allow those considerations to guide and shape their research plans. This approach includes identifying and developing a clear understanding of a clinical need and establishing a research program to address that human need. Bedside to bench and back again not only increases the likelihood for the successful transition to the clinic but also impacts benchtop research. By understanding how their research can fit into the future, investigators can develop effective impact statements, increased the relevance and applicability of their research, and develop strategic partnerships. By moving beyond scientific constraints that prevent clinical translation of TEMPs, investigators can develop strategies for developing successful technologies.BO was involved in the conception, writing, drafting, and editing of this article. CI was involved in the writing and figure making of this article. OM was involved in the writing of this article. BB was involved in the conception and editing of this article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


It included aspects related to reasons for choosing the course, institutional integration, use of self-regulation strategies, and intention to drop out. Data analysis allowed the identification of satisfaction with the course chosen and appropriate study skills acquired in secondary education as predictors of expectations of academic persistance, with some differences in terms of gender. Other strategies such as class attendance or going deeply into course content did not figure. These results are at odds with the principles underlying the EHEA and show that they have not yet been interiorized by the students, who continue to perceive their studies more traditionally.The implementation of the European higher education area (EHEA) is a true paradigm change in university education in which the student, with particular consideration given to autonomous work, takes the place of the teacher as the central element of the teaching-learning process. In this autonomous work, the strategies the students regularly use become particularly important, given the supposition that doing that work will lead to academic success. The objective of this study is to analyze the variables that influence students’ expectations of success, measured through their intention to persist on the course they are doing. A questionnaire designed  The continuous, rapid technological, and social advances in the last fifty years have led to the new social paradigm of the “knowledge society” , basing Universities play a fundamental role in this context, as they are the prime bodies for the production of knowledge through scientific research, transmission of knowledge through education and training, and diffusion of knowledge by different channels .If we add to that the growing process of globalization, it is no surprise that in education at the European level there is a plan for convergence that would allow universities to join forces, and unite educational policies. This has given us the European higher education area (EHEA), with the objective of modernizing higher education teaching and institutions across Europe .The European Higher Education Area is not only about structural and organizational change, but rather a real paradigm shift with implications in the way we understand the teaching-learning process  which afOne of the most significant changes is the consideration of the student as the central element of the teaching-learning process. The teacher, up to now the fundamental pillar of teaching from the more behavioral point of view, cedes ground to the student, who is established as an autonomous, self-regulated learner. So students are the protagonist, responsible for their own educational process, in line with the constructivist paradigm .This autonomous character, present in the educational tenets of the EHEA, was most fully realized in the adoption of the European credit transfer system (ECTS) as the unit of measure for academic credit. ECTS credit system gives importance to classroom activities but also take into account offsite activities. So, for example, a subject with 6 ECTS credits will include in the plan 60 h of classroom work and 90 h of autonomous student work, making up the 150 actual hours of work in the subject, as generally 1 ECTS credit equals 25 hours of effective student work Art. 4. . BoletínIn this context, educational quality is a principal aim for European Higher Education institutions. In this sense, quality is mainly assed in terms of graduation rates, quality of instruction and excellence of research . Thus, sAcademic performance is a fundamental variable in student progress in an institution , especiaKnowledge and application of appropriate study techniques have also been shown to directly influence the decision to continue with a course of study , as has Most of these variables are indicators of self-regulation of learning . Hence, Faced with this, it is worth asking ourselves whether the cause may be found in a lack of preparation (in terms of prior knowledge or study habits) or whether it is a consequence of a discrepancy between students’ perceptions of study requirements and reality, or an insufficient understanding of those requirements. In the context of the EHEA, variables that are traditionally considered to be influential in academic performance and success, such as regular class attendance, gain particular importance, as the indications teachers gather from students in those sessions are essential to orient autonomous work, as demonstrated in research by The aim of this study is to analyze the influence of the variables outlined above on expectations of academic persistence. A better fit between prior achievement and subsequent achievement may function as a predictor of satisfaction with results and continuation with the course of study .To that end, the objective of this study is to examine the possible influence that study habits and personal baggage may have on students’ expectations of their academic success and persistence on the institution. Specifically, we aim to see whether those variables related to the implementation of EHEA are perceived by students as precursors of satisfactory academic progress and persistence. Thus, we draw two hypothesis:H1:There will be higher expectations of persistence, in those students who consider their prior training (in terms of prior knowledge of and mastery of study techniques) to be sufficient to the demands of the course that they are on.H2:The students will consider those variables related to self-regulated learning behaviors important for they academic persistence.SD = 4.17). The sampling method used was non-probability intentional selection, based on the working-group teachers’ access to the sample.The sample was made up of 1037 first-year students in the University of Oviedo. The majority (73.9%) were women, and the average age was 19.94 years old (1); English; Chemistry; Speech Therapy; Physics; Physics and mathematics (double degree1); and business and marketing.The students were doing various undergraduate degree courses. The most common were primary education (22.6% of the students), nursing (22.2%), infant education (16.9%), and psychology (12%). Students were doing other degree courses to a lesser extent (less than 10% of students on each course): Economics; Law; Law, Management and Business Administration .The rest of the questionnaire corresponded to 8 dimensions that contain 66 items about: (1) reason for choosing the program; (2) prior knowledge; (3) finances; (4) current situation; (5) interest in the program; (6) integration; (7) institutional variables; and (8) self-regulation strategies.Apart from the classification variables, which were dichotomous, multiple choice or open response questions, the responses for the remaining dimensions were via a five-point Likert-type scale with the following scoring: (1) completely disagree; (2) disagree; (3) neither agree nor disagree; (4) agree; and (5) completely agree.The questionnaire process began initially with contact with teachers who were signed up to a university teaching innovation project, This teaching innovation project sought to analyze the motivations behind drop-out intentions and university students’ self-regulation strategies.The questionnaires were administered, on paper, in the classroom to be completed in the teachers’ own classes by freshmen, 3 months after starting the course. This was to allow an evaluation before the first exams in the school year.The procedure include written consent of participation in the study and agree with the criteria stablished by our university ethics committee.In order to examine the possible relationships between student self-regulatory behavior and expectations of academic persistance we ask students about their persistence intentions. Thus, through students’ intentions to continue on the course that they started, we looked into students expectations of success. We used categorical regression techniques to evaluate the impact that the variables described previously could have on the probability that a student would stay on their current course or drop out.Independent variables included in the analysis were categorical so we applied a categorical regression model were students expectations of persist on the program was the dependent variable and there were nine independent variables; prior knowledge, adequacy of prior acquired study techniques, interest in study, satisfaction with the chosen program, class attendance, daily study, interest in course content, performance orientation, and deepen in course contents.Data analysis were performed using the IBM SPSS Statistics v.24 package.The categorical regression model was applied first, given that it is the best fit to the mix of ordinal Likert-type variables making up the questionnaire and the dichotomized criterion variable. This model explains 22.3% of the variance in the participants’ expectations of remaining on their current program.p < 0.005), ensure its validity [F(21) = 15.0713447].The analysis of variance of the model, which is significant  than positive opinions about proper study techniques .Only two variables significantly contribute to the model: the opinion that study techniques used to date are adequate, and satisfaction with the choice of program. 2 = 30.865; df = 4; p < 0.000; VCramer = 0.173).We found statistically significant differences in the first predictor (related to students’ appropriate use of study techniques), such that those students who were thinking of dropping out tended to respond more negatively to the item (completely disagree and disagree) than those who were not thinking of dropping out. This means that using appropriate study techniques prevent students’ intentions of droping out. Nonetheless, in regard to p < 0.000;VCramer = 0.446).Similarly, with the second predictor (satisfaction with choice of program), there were also significant differences. Students who were considering dropping out were less satisfied with their choices  than those who were not thinking of dropping out (completely agree). Following the guidelines of Following the results in the contingency tables, we carried out a correspondence analysis to visualize where the differences lay, including the gender variable. We found that while differences in the variable about study techniques were inter-gender and the differences in the satisfaction variable were intra-gender.For the first variable (use of appropriate study techniques) we found the values shown in With the second variable (satisfaction with the chosen degree), the results are shown in As The process of transition from secondary education to university is not an easy one for students, as it requires adaptation to an unknown, demanding environment regardless of what they might have been taught in prior educational and guidance processes. In this context, academic performance and expectations surrounding it are particularly interesting variables .In particular, in the European context, the EHEA brings along the requirement for students to develop an autonomous learning . Thus, iTherefore, in this study we analyzed those variables which, according to student expectations, influence academic persistance. Thus, we assumed that it will be those expectations which can condition their behavior for proper performance.Our results provide evidence, in line with research in this field, of the importance students place on study techniques, an indicator which is widely related to satisfactory achievement . In our It does seem paradoxical that student’s perceptions and expectations of persistence are not related to other variables of significant learning and self-regulation, which does not support our second hypothesis. EHEA sift the educational paradigm, giving more protagonism to the student, who is supposed to be an autonomous learner. This is particularly important to bear in mind that when planning subjects, as can be seen in any teaching guide that follows the premises of EHEA, one must consider not only classroom activities such as lectures, practical classes, laboratory classes and tutorial groups, but also non-classroom activities such as individual and team work that occasionally require more time, and always the added need to learn autonomously and with self-regulation Art. 4. .Thus, some of the variables that we have studied – like class attendance or daily study- are important to succeed in the EHEA . DespiteThese results seem to show that the postulates that gave rise to the creation and implementation of the EHEA, particularly the ECTS system of credits, have not yet been interiorized by students, who continue to perceive their study more traditionally. It is necessary to continue improving effective interventions regarding learning self-regulation; in this sense training programs in higher education such eTRAL  or MetatFinally, future research should be aimed at increasing sample heterogeneity in different university years to understand whether these results apply to other programs or knowledge areas and whether there are significant differences between them. Intervention policies may be proposed to provide a better student guidance, able to guarantee a better adjustment to the context and demands of EHEA.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by the Secretaría General de la Universidad de Oviedo. The patients/participants provided their written informed consent to participate in this study.All authors contributed to the writing of the manuscript and development of the research. AB organized the sample gathering and designed the research instrument. ME and RC helped to design the research instrument and gather the sample. AC and FH coded the data and performed the analysis.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.