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Objective(s): Divorce as an important social harm has always been the focus of investigators and policymakers as it affects women compared to males. Therefore, considering the importance and prominent role of women in the family and society, the present article aimed to examine the most important determinants of the first marriage survival of divorced women with children. Methods: In a cross-sectional survey conducted by the Civil Registry Organization in 2017-2018, the information of those who referred to the offices of the provincial centers for divorce registration was collected using a questionnaire. Considering the large number of predictors and the ineffectiveness of classic survival analysis methods in big data modeling, the present study investigated the most important factors, including women and their spouses, their families and provincial macro variables, affecting the first marriage survival of 756 women with children using survival forests using R software. Results: Based on the highest value of Harrell's coordination index (0.8412), the lowest mean prediction error (0.0885) and the lowest value of integrated Brier score (0.038), the algorithm of random survival forest with log rank split rule (RSF1) in investigating factors affecting the first marriage survival of these women was more efficient. The findings showed that based on variable importance and minimum depth indicators, the first child’s age was the most important variable in examining their first marriage survival. Conclusions: Since big data are analyzed in many medical and social studies, survival forests can be used as an efficient method to identify the most important predictors and reduce their dimensions, and then use classical survival analysis methods for modeling.

Background: Addressing the evolving dynamics of family structures, the parent-employment conflict (PEC) emerges as a significant conundrum of the current century. This article seeks to delve into the intricate factors influencing PEC among employed parents in Tehran, Iran. Methods: This study employed a stratified random sampling method across various regions within Tehran province, in 2017. A structured questionnaire, encompassing demographic details, the history of fertility, and attitudes towards childbearing, alongside the delineation of conflicts between professional responsibilities and parental duties used to collect 449 employed parents. Since PEC was an ordinal variable with three categories of low (6-12), middle (12-18), and high (18-30), an ordinal regression method was applied to some selected covariates. Results: The findings suggest that women comparing to men, those with “secondary and high school” and “diploma” comparing to “master degree and PhD” educational levels, governmental employees comparing to free-lance employees, and those employees working 45 hours and more comparing to employees working less than 40 hours in a week had higher PEC. Conclusion: In general, unless socialization norms and policymakers’ views adopt social realities, PEC will not reduce. Policymakers should pay more attention to institutionalize of social supports and implement family supportive policies.

Background: Total fertility rate (TFR) in Iran decreased from the year 2000 and recently Iran has experienced fertility rates below replacement level. Birth interval is one of the most important determinants of fertility levels and plays a vital role in population growth rate. Due to the importance of this subject, the aim of this study was analyzing three birth intervals using three Survival Recurrent Event (SRE) models. Materials and Methods: In a 2017 cross-sectional fertility survey in Tehran, 610 married women, age 15-49 years, were selected by multi-stage stratified random sampling and interviewed using a structured questionnaire. The effects of selected covariates on first, second and third birth intervals were fitted to the data using the Prentice-Williams- Peterson-Gap Time (PWP-GT) SRE model in SAS 9.4. Results: Calendar-period had a significant effect on all three birth intervals (p

Background: Birth spacing, especially the first birth interval (FBI), is a suitable index to investigate the delayed fertilitythat results in a low fertility pattern. Non-parametric familiar alternatives to the Cox proportional hazard regression(CPH) model include survival trees that can automatically discover certain types of covariate interactions according tothe survival length. The aim of this research is to study FBI influential factors by applying survival trees.Materials and Methods: In this cross-sectional study, 610 married women (aged 15-49 years), were selected fromdifferent regions of Tehran, Iran in the Winter and Spring of 2017. Classification and regression trees (CART) for theFBI survival tree were fitted by taking into consideration the predictors of each woman’s age, age at first marriage,educational level, partner’s educational level, activity, region, house ownership, kinship, partner’s race, marriage timeattitude, and expenditure using R packages.Results: Since the PH assumption of the CPH model was not confirmed for the covariates of age at first marriage (P=0.001),kinship (P=0.000), partner’s race (P=0.001), and marriage time attitude (P=0.042), the results of this model were not valid.Thus, a CART survival tree was fitted. The validity of the fitted model in assessing FBI was confirmed by the significantresult of the log rank test (p

The sports industry is one of the most popular fields between the nations that need to interact with several factors, from stadium security to marketing staff. Today, security and crowd management are more critical than ever. In many events, the lack of proper security management has caused to be a bitter event due to it. It has created serious risks for the investors that have participated in the game. Due to this, maintaining a long-term relationship with them is a severe challenge. Research has shown a positive correlation between security in sporting events and security in the business. However, few studies have examined how this is. This study utilized samples that included 300 sport management experts. The research tool included: "Marketing mix standard" and "researcher-made security" questionnaires, each with 45 items. Using exploratory factor analysis, security determinants related to the marketing mix of sports events, which were related to the marketing mix of the tournament, were identified. The results showed that 12 factors have contributed to security, and 11 elements were involved in the marketing mix. The results showed that security documentation and training should receive special attention along with hardware and software management of venues, management and planning, and physical protection, as well as security services and facilities, to improve the security conditions in soccer matches. Managers must have proper management, which leads to the satisfaction of spectators and prevention of crowded. The sense of security creates a suitable atmosphere for marketing activities in sports events.

Objectives: According to health surveys, population growth and total fertility rate (TFR) are decreasing in Iran. The economic and social factors in addition to the changing values and attitudes in the Iranian society have had a major impact on fertility decisions and the actions of families, especially women towards childbearing. This is an important issue for policymakers and many researchers in demography and public health thus the investigation of factors that affect low TFR is considered as a necessity. Materials and Methods: The classification and regression trees (CART) algorithm, as one of the most applicable classification trees, along with logistic regression was applied to model the tendency of 4898 women for childbearing in provinces with a TFR lower than the replacement level in Iran. The secondary data were then analysed by SPSS version 24.0. Results: Based on these two approaches, it was concluded that despite the CART algorithm, logistic regression suffers from some shortcomings including the difficult interpretation of three levels of interactions while not containing a specific method for handling the outliers. In addition, CART results demonstrated that women’s children ever born (CEB), age, and opinion had significant impacts on their desire to have a child. The groups encompassing "10-39-year-old women with CEB≤2" and "40-49-year-old women with positive attitudes towards childbearing" desired to have more children while "women with CEB ≥3" showed no tendency for childbearing. Conclusions: In general, the results revealed that adopting policies for changing women’s views on childbearing and creating the necessary resources for preventing the delays in marriage are regarded as important actions toward altering fertility rates. Another important conclusion is applying the CART algorithm as a convenient method for classifying demographical data.

Background and objectives: Application of statistical machine learning methods such as ensemble based approaches in survival analysis has been received considerable interest over the past decades in time-to-event data sets. One of these practical methods is survival forests which have been developed in a variety of contexts due to their high precision, non-parametric and non-linear nature. This article aims to evaluate the performance of survival forests by comparing them with Cox-proportional hazards (CPH) model in studying first birth interval (FBI). Methods: A cross sectional study in 2017 was conducted by the stratified random sampling and a structured questionnaire to gather the information of 610, 15-49-year-old married women in Tehran. Considering some influential covariates on FBI, random survival forest (RSF) and conditional inference forest (CIF) were constructed by bootstrap sampling method (1000 trees) using R-language packages. Then, the best model is used to identify important predictors of FBI by variable importance (VIMP) and minimal depth measures. Results: According to prediction accuracy results by out-of-bag (OOB) C-index and integrated Brier score (IBS), RSF outperforms CPH and CIF in analyzing FBI (C-index of 0.754 for RSF vs 0.688 for CIF and 0.524 for CPH and IBS of 0.076 for RSF vs 0.086 for CIF and 0.107 for CPH). Woman’s age was the most important predictor on FBI. Conclusions: Applying suitable method in analyzing FBI assures the results which be used for making policies to overcome decrement in total fertility rate.

Background: Socio-economic factors, in addition to value and attitude changes, have had a major impact on fertility behavior of women toward childbearing. The main purpose of this study is to investigate childbearing desire of 6183 women in provinces with total fertility rate (TFR) lower (TFR ≤ 2) and upper (TFR > 2) than replacement level by classification and regression trees (CART) algorithm, as one of the most applicable classification trees. Method: In this study women’s job, place of residence, age, opinion, marriage age, educational level, and children ever born were investigated as predictors. The accuracy of fitted classification trees for CD in provinces with TFR ≤ 2 and TFR > 2 were 0.68 and 0.72, respectively. Results: As a result, women’s children ever born and age had significant roles on their desire to have a child in all provinces while their opinion toward childbearing had just effect on provinces with TFR ≤ 2. In provinces with TFR ≤ 2, 10 - 39 years old women with 2 children and less CEB were willing to have another child. Women with 2 or less children at the age of 10 - 29 as well as women with 3 or more than 3 children at the age of 20 - 29 had a desire for more children in provinces with TFR > 2. If the women have a positive attitude toward childbearing and their age is not high, they will desire to give birth to a child until they reach the ideal number of their children. Conclusion: Thus, policies in changing their attitudes toward childbearing and creating the necessary facilities to prevent delays in marriage could be an important step in changing fertility rates.

Background & aim: Demands for more children have substantial effects on couple’s fertility behaviors. The ideal number of children for most Iranian’s family is two, so that it is reasonable to study which factors determine women’s decision to have a third child. The main aim of this study was to examine factors affecting the demand for a third child (DTC). Methods: This cross-sectional study was conducted on 6231 Iranian married women from all provinces during autumn 2014. Participants in the study were selected by multistage stratified sampling method. A structured questionnaire was employed to collect the related data. Finally, the analysis included 2272 DTC questionnaires for women with two children by applying a classification tree model. Results: In this study,50.7% of women with two children had no desire for having the third child, out of whom 71.1% (79) were living in the provinces with total fertility rate (TFR) less than 2 and in urban areas, respectively. Most of them with the educational level of diploma or lower (78.2%) had a negative opinion about having the third child (36.1%). Based on the classification and regression tree algorithm, women who were interested in having their third child in provinces with TFR more than 2 included rural women, urban women with positive opinion toward childbearing, and those with educational level of secondary school. However, women who were keen on having their third child in provinces with TFR less than 2 consisted of urban women aged 30-49 with educational level of high school or lower, those younger than 30 years with positive opinion who married in their 20-29, rural women aged less than 30, and rural women aged 30-49 with positive opinion who married in their 20-39. Conclusion: Women’s place of residence and opinion toward childbearing had important effects on their DTC. However, women’s educational level as well as their age and marriage age could affect their DTC in provinces with TFR less than 2 compared to other provinces.

Background: During the last decades, the average gap between attitudinal and behavioral youths’ marriage age has increased due to the changes of Iranian normative system in society and family patterns. This paper devoted to study this increment. Methods: Classification and Regression Trees (CART) algorithm are applied to model marriage age gap (MAG) of 12741 youths selected by multi-stage cluster sampling method from 31 provinces in Iran. Results: Classification accuracies of fitted CART for females’ and males’MAG were equal to 0.62 and 0.60, respectively. The most influential variables on females' and males'MAG were educational level and number of siblings, respectively. Females with "university education", "diploma and less education with 5 and more siblings", and “employed diploma and less education with 3 or 4 siblings" married later than their desired time. Males with "3 and more siblings", "employed with 2 and less siblings and 3 and more ideal number of children", "employed university educated with 2 and less siblings and 1 or 2 ideal number of children", and " employed with 2 and less siblings and 1 or 2 ideal number of children with diploma and less education and negative opinion towards childbearing" also married later than their desired time. Conclusion: If the inevitable experience of modernity doesn’t combined with the convenient policy and the economic and socio-cultural conditions of the community don’t change, negative consequences of such developments would be more than its positive achievements on different social issues specially and more importantly youths marriage age.

Background: A set of economic and social rules and regulations as well as cultural factors influence value of children; however, this value itself could alter fertility behaviors. The present study aimed at investigating the influence of the value of children on fertility behavior through considering the impact of its attitudinal factors on childbearing desire, as one of the most important dimensions of fertility behavior. Method: A cross-sectional study was conducted on 6231 females from 31 provinces of Iran, admitted to public health and treatment centers to vaccinate their children, during year 2014. The data collection tool was a questionnaire, including three value of children dimensions, including cultural (five items), social (seven items), and economic (four items) factors, and also demographic and attitudinal questions. Results: Data were analyzed using SPSS-17 software and the factors influencing childbearing desire (CD) were examined by four SEMs for four age groups in AMOS-22. Goodness of fit models was confirmed by five fit indices. Only cultural factors had a significant direct effect on CD for 30 to 39 and 40 to 49 year-old females (P-values = 0.027, and < 0.001, respectively). Conclusions: Thus, planners and policy makers should consider changes in the cultural value of children to implement successful policies to alter the current decreasing trend of fertility rate.

Background and objectives: Birth spacing is an important variable for identification of fertility acceleration, total fertility rate, and maternal and fetal health. Therefore, special attention has been paid to this issue by researchers in the fields of medical sciences, health, and population. In addition, proper analysis of this concept is of foremost importance. Application of classical analytical techniques with no attention to their assumptions (e.g., independence of events) is associated with inefficient results. As such, this study aimed to present frailty models as effective models for this analysis. Methods: Frailty models consider the dependence between unobserved intervals and dispersions by exerting a random impact on the model. Different types of these models include shared, conditional, correlated and time-dependent frailty, each of which along with their applications were presented in the current research using two examples. Results: In practice, the shared frailty model is highly applied due to its simplicity. Nevertheless, since most of the unknown factors affecting the birth spacing are not common between different births, the shared frailty models must be used with caution. Conclusion: Use of classical statistical methods, such as the Cox proportional hazards model, the important assumption of which is the dependence of events occurred, is not appropriate for the accurate analysis of birth spacing. On the other hand, frailty models consider the correlation between the intervals and are an effective method for analysis of birth spacing, use of which is recommended to researchers in fields of medicine and population.

Background & aim: Despite the success of family planning programs in Iran in the recent decades, considerable proportions of pregnancies are still unintended and can be a cause of poor mental and physical health of the mother and child. The aim of this study was to investigate some important factors affecting uplanned pregnancies among married women in Semnan province, one of the developed provinces of Iran with below replacement fertility level. Methods: The data for this study were drawn from a cross-sectional survey conducted in Semnan province in 2014. A total of 363 married women within the age range of 15-49 years who were pregnant or had the history of at least one delivery were considered. The study sample was selected using multi-stage stratified sampling method. The data were collected using a self-structured questionnaire with 90 items and Cronbach's alpha coefficient of 0.88. Data analysis was performed in SPSS (version 20) using Crammer’s V coefficients and Chi-square tests. Logistic regression analysis was also applied to model the risk of unintended pregnancies based on selected covariates. Results: According to the results, around 18.2% of the pregnancies were unplanned, 7.7% and 10.5% of which were mistimed and unwanted, respectively. Based on the logistic regression analysis, birth cohort, number of children ever born, and contraceptive methods had significant effects on the risk of unintended pregnancies. Furthermore, about 48% of the women experiencing unintended pregnancy were using a traditional contraceptive method before or at the time of the conception. Conclusion: As the findings indicated, the women who used contraceptive method, as well as those with higher number of children and younger birth cohorts had higher risk of unplanned pregnancies. It should be noted that the majority of unplanned pregnancies among the women in younger birth cohort were mistimed pregnancies. So it is recommended to continue offering family planning and health services to these women in order to prevent unplanned pregnancy, unsafe abortion, and many chronic diseases.

Background & Objective: Migration, in any forms and by any motivations or outcomes, as a demographic phenomenon, has various cultural and socio-economic effects on local, regional, national and international levels. On the other hand, fertility plays an important role in health and population studies and researchers have examined its changes and trends in various aspects. The aim of this research was modeling the mean number of children ever born (CEB) for women who have left their cities or villages and migrated to Tehran city using regression tree model. Methods: Data was obtained from 2% of raw data from the census of 2011 and analyzed by regression tree model. Tree models are nonparametric statistical techniques which do not need complicated and unreachable assumptions of traditional parametric ones and have a considerable accuracy of modeling. These models are associated with simple interpretation of results. Therefore, they have been used by researches in many fields such as social sciences. Results: Age, educational level, job status, cause of migration, internet use for urban migrant women and age for rural migrant women were assumed as influential covariates in predicting the mean number of CEB. Conclusion: Regression tree findings revealed that urban migrants who were in higher age groups, lower educational levels, unemployed and have not used internet have had more mean number of CEBs.

Objective (s): In many medical and epidemiological studies, each person can experience several events one after the other sequentially under some circumstances, known as recurrence events. Broad analytical objectives of recurrent events consist of describing event process in an individual, dispersion of events from one person to another, and determination of relations between constant or time-dependent predictors with event time. So the main purpose of this article is to present and interpret advanced statistical models to analyze such events which have been proposed in recent years. Methods: In this article, variance-corrected models including AG, conditional PWP (PWP-TT and PWP-GT) and marginal WLW models for analyzing recurrent events are presented and compared with each other. Results: When the number of events for each individual are small and the risk of a reoccurrence of an event varies between different events, usually conditional PWP models are used, while marginal WLW and the time-dependent AG models are applied to determine frequency of events. Conclusion: Medical and epidemiology studies should consider various factors such as the number of events, relationship between events, the variability of the effect of factors from one event to another, the biological process, and the correlation structure of data to select the valid recurrent models.

Objective (s): First birth interval has received special attention in public health and demographic investigations due to its implication in fertility, and maternal and child health. Study of ideal first birth interval also is a very important issue since it demonstrates people’s attitude towards fertility. The aim of this study was to investigate the factors, which affect ideal first birth interval among pre- marriage youths. Methods: A sample of 12500 pre-marriage male and female youths in all provinces of Iran who visited pre-marriage counseling centers was selected. The sample selection was based on multistage stratified sampling method. Data were collected in year 2014 using a structured questionnaire. The ideal first birth interval as outcome variable was indicated by univariate survival analysis and stratified Cox model while controlling for some independent covariates. Results: Based on univariate survival analysis, age, ideal numbers of children and employment status were found to have significant effects on the mean of ideal first birth interval in all provinces. However by fitting different stratified Cox models to different groups of provinces, different covariates were found to play significant effect. Conclusion: Although there were different factors for influencing ideal first birth interval in different provinces, the differences were in the same direction. In all provinces, ideal first birth interval decreased by increase in age and university students favored longer ideal first birth interval than other participants. Risk of early childbearing for women, people who lived in rural area, had lower educational levels, had greater ideal number of children and had sex preferences were higher compared to the other groups.

Intergenerational transmission is referred to transmission of behaviors, characteristics, and/or tendencies from one generation to the other. In this process, parents of one generation tend to repeat some of their psychological characteristics in their offsprings. The aim of the current study was to predict children’s affective temperament indices based on parental affective temperament characteristics. A total of 207 university students (146 females, 56 males, 5 anonymous) and their parents (207 Fathers, 207 mothers) in Tehran have been collected using convenience sampling method. Participants were asked to complete Positive and Negative Emotionality Scale (PNES). Method of the present descriptive study was correlational. Analysis of the data involved both descriptive and inferential statistics including means, standard deviations, correlation, and mixed model. The results showed a significant correlation between parental and children's affective temperament indices (p

Background: Early and delayed marriage has their own effects on mothers and their children's health and social dimensions. Nowadays, Iran experiences delayed marriage due to several factors; thus, the present study was concocted to investigate the factors affecting youths’ marriage age, and to compare these factors between males and females. Methods: To study demographic, socio-economical, and some atitudinal behavior factors affecting the age of marriage, in the current cross-sectional study, 12741 Iranian pre-married youths including 6381 males and 6360 females from all provinces were selected using multi-stage stratified method and the data was collected using a structured questionnaire in 2014. The questionnaire included demographic, socio-economical, and some atitudinal behavior questions about childbearing. Kaplan-Meier, Log-Rank test, and parametric survival analysis were applied in IBM SPSS Statistics for Windows, Version 22.0., and SAS 9.3 software. Results: Gamma and Log Logistic parametric models were the best fitted models for females’ and males’ marriage age, respectively. Females and males who lived in provinces with TFR

Background and Objective: Discriminant analysis and logistic regression are classical methods for classifying data in several studies. However, these models do not lead in valid results due to not meeting all necessary assumptions. The purpose of this study was to classify the number of Children Ever Born (CEB) using decision tree model in order to present an efficient method to classify demographic data. Methods: In the present study, CART tree model with Gini splitting rule was fitted to classify the number of CEB in fertility behavior of at least once married 15-49 year-old women, in Semnan-2012. 405 women aged 15-49 years old comprised the survey sample. Results: Women in first and second birth cohorts who had married at an early age had 3 CEB while women who had married at an older age had 2 CEB. Women in third birth cohort who had married at an early age and were employed, had 2 CEB while unemployed women in this cohort whose type of marriages were familial and non-familial had 0 and 1 CEB respectively. Women in the third birth cohort who were married in older age had 1 CEB. Conclusion: Among important advantages of CART model are the simplicity in interpretation, using distribution-free measures, considering missing data and outliers for construction trees which has increased the usage of this method. Therefore, this method is a suitable way for classifying demographic data in comparison to other classical modeling methods in the conditions that necessary assumptions are not met.

Background: Socio-economic factors, following psychological factors, affect the value of children in parents’ view and this value itself could influence Ideal Number of Children (INC), which is one of the most important dimensions of fertility behavior. The aim of the present study was to investigate parents’ INC according to the factors influencing the value of children from the viewpoint of men and women, separately. Methods: In a cross-sectional study, multi-stage stratified sampling method was conducted to collect data from 590 males and 610 females in Tehran province, Iran, using a questionnaire including demographic and attitudinal questions. To describe data, SPSS-17, and to examine the factors influencing INC, path analysis was used in AMOS 22 and Goodness of fitted model was approved using the relative chi-square ( , Goodness of Fit Index (GFI), Adjusted GFI (AGFI), and Root Mean Square Error of Approximation (RMSEA) indices. Results: Indices of Goodness of fit confirmed the fitted models ( =2.289, GFI=0.994, AGFI=0.973, and RMSEA=0.047 for males’ model and =0.511, GFI=0.989, AGFI=0.994, and RMSEA=0.020 for females’ model). Negative psychological (males’ coefficient=-0.20 and females’ coefficient=-0.17, P

Aphasia is prevalent in people following stroke, which can have a significant impact on the quality of life of the patients with stroke. One of the new methods for treatment of patients with aphasia is constraint-induced aphasia therapy (CIAT). The aim of this study was to investigate the efficacy of CIAT on naming deficits in individuals with chronic aphasia. This study had a prospective, single-subject study with A-B-A design. The CIAT was administered to two patients with chronic aphasia. Participants were a 57-year-old male and a 45-year-old female and had a stroke 60 and 36 months ago, respectively. In this study, the naming test was used as the outcome measure. The naming test was administered in three baseline sessions with 1 week interval between tests (phase A). Patients received CIAT for four consecutive weeks (3 days/week). Four measurements were taken during the treatment phase (phase B). In follow-up phase (phase A) two other measurements were performed. Visual analysis consisting of level, regression line, and variability were used to determine the effects of CIAT on naming. Both participants increased scores on naming test after phase A and B. The mean of the naming score improved from the baseline to the intervention phase in both participants. There was a positive trend in naming scores during the treatment phase compared with the trend in the baseline demonstrated by both participants. The results of this study showed that the CIAT can be effective in improving the naming deficit in patients with chronic post-stroke aphasia.

Background: Epilepsy is a common, chronic neurological disorder that affects more than 40 million people worldwide. Epilepsy is characterized by interictal and ictal functional disturbances. The presence of interictal epileptiform discharges (IEDs) can help to confirm a clinical diagnosis of epilepsy, and their location and characteristics can help to identify the epileptogenic zone or suggest a particular epilepsy syndrome. The aim of this study is to determine the factors that affect IEDs. Materials and Methods: Poisson marginal model was done on 60 epileptic patients who were referred to Shefa Neurological Research Center, Tehran, for Video-Electroencephalogram (V-EEG) monitoring from 2007 to 2011. The frequency of IEDs was assessed by visual analysis of interictal EEG samples for 2 h. Results: The results show that among age, epilepsy duration, gender, seizure frequency and two common anti-epileptic drugs (Valproic acid and Carbamazepine), only age and epilepsy duration had statistical significant effect on IED frequency. Conclusion: Investigating the factors affecting IED is not only of theoretical importance, but may also have clinical relevance as understanding the evolution of interictal epileptogenesis may lead to the development of therapeutic interventions. Generalized estimating equation is a valid statistical technique for studying factors that affect on IED. This research demonstrates epilepsy duration has positive and age has negative effect on IED which means that IED increases with epilepsy duration and decreases with increasing age. So for monitoring IED, we should consider both age and epilepsy duration of each patient.