Microsoft Word - Issue-2_Volume-10_All-Articles.docx 37 Study on the Development of Personality Traits in Children with Language Disorders and Children without Language Disorders Georgeta Pânişoară University of Bucharest Regina Elisabeta 4-12, 030018, Bucharest, Romania Phone: 021 307 7300 georgeta.panisoara@gmail.com Cristina Ghiță University of Bucharest Regina Elisabeta 4-12, 030018, Bucharest, Romania Phone: 021 307 7300 cristina.sandu@fpse.unibuc.ro Iulia Lazăr Vasile Alecsandri University Calea Mărășești 157, 600115, Bacău, Romania Phone: 0234 542 411 iulia48lazar@gmail.com Silvia Făt University of Bucharest Regina Elisabeta 4-12, 030018, Bucharest, Romania Phone: 021 307 7300 silvia.fat@fpse.unibuc.ro Abstract This study aims to investigate possible differences in the formation and development of personality traits for children with various language disorders and children who do not have language disorders from a neuropsychological perspective. The child's personality is a psychological and social construct with strong implications on how to relate it to the surrounding individuals and brain function. During childhood, the individual manifests a variety of typologies of behavior and attitudes depending on the context in which they are, so personality traits are formed as a result of existing interactions and the family and educational context. In the case of children with different language disorders, the personality must be structured in a more secure and stable emotional environment, leading to the development of adaptation capacities to the external environment and an increase in stress resistance. Emotions and moods play a significant role in the development of personality traits. In this sense, we have started the research that aims to analyze the personality traits of children with speech difficulties and those who do not have these difficulties. The participants in this study are 60 children aged 7-12 years old from urban areas. The method used is represented by the HiPIC - Hierarchical Personality Inventory for Children (I Mervielde and Filip de Fruyt), a psychological tool for assessing the personality of children aged 6 to 13 and is based on the established Big Five model. The inventory is a personality HiPIC contains 144 items and allows the evaluation of the emotional, interpersonal, motivational and behavioral style of children based on the five dimensions of personality. Parametric statistical methods were used to identify possible differences between the two groups of participants in research. Also factor loadings and correlations between factors as results of exploratory factor analyses were evaluated. The study outputs confirms existing differences in the development of certain personality traits, the specificity being given by the situations experienced in the educational environment, the family environment and in the context of the process of recovering and improving the language disorders. Keywords: Language Disorders; Personality Traits; Emotional; Children; Neuropsychology; Neuroscience. BRAIN – Broad Research in Artificial Intelligence and Neuroscience Volume 10, Issue 2 (April, 2019), ISSN 2067-3957 38 1. Introduction Personality should be seen as the most important psychological and social structure that an individual builds in relation to others. This could be interpreted by the effectiveness with which a person manages to stimulate positive reactions from others in different situations. Caspi (2000) considers personality as the total sum of the typical ways to act, think, and feel, by which each individual becomes unique. Childhood is a "crucial chance" to shape the individual's emotional predilections, since childhood habits are included in the synaptic networks of neural architecture and are difficult to change later (Goleman, 2001). When we refer to personality development, it involves many changes, restructuring that can be considered vital. An important role at this stage, childhood and personality development is given by new factors such as: increasing personal relationships and experience, developing social knowledge, engaging in their own training process, and entering the life of the school community (Cretu, 2007). Recent research into neuropsychology technology has opened up interesting possibilities for analyzing the neural mechanisms underlying language learning and development. The last decade has seen an increased interest in linking research to learning sciences and cognitive neuroscience on various topics of common interest such as language development, problem solving, learning difficulties (Goswami & Szucs, 2011). According to the literature, Openness is the most significant predictor of psychometric intelligence (Heaven & Ciarrochi, 2012). It is also associated with the acquisition of knowledge composing crystallized intelligence, such as information and vocabulary (Bates & Rock, 2004). People with high scores in Openness are more motivated to participate in different kinds of cognitive activities. The aim of personality neuroscience is to understand both the biological systems that are responsible for the states associated with traits and the parameters of those systems that cause them to function differently in different individuals. DeYoung (2010) defines personality as being ,,individual’s unique variation on the general evolutionary design for human nature, expressed as a developing pattern of dispositional traits, characteristic adaptations, and integrative life stories, complexly and differentially situated in culture’’. From a neurocognitive perspective, personality is focused primarily on traits, which are relatively stable patterns of behavior, motivation, emotion, and cognition. In contrast to traits, characteristic adaptations and life stories describe the individual’s specific responses to his or her particular life circumstances. Norman (2003) stated that there is a strong correlation between Big Five personality factors (neuroticism, extraversion, openness, conscientiousness and acceptability), and children's conflict management strategies. Studies have shown that these five factors have the following descriptions: neuroticism, reflects individual differences as a child perceives and experiences the world as threatening, problematic and dangerous; extraversion, involves an active approach to the social world and includes features such as positive sociability, activity, assertiveness and emotionality; openness to experience, describes the breadth, depth, originality and complexity of the child's mental and experiential life; convenience, includes features such as altruism, tendency, trust and modesty and conscientiousness, describes control of socially prescribed impulses that ease task- oriented behavior, such as thinking before acting, compliance with rules and rules (Atashrooz, Behrooz, 2009). Researchers (Garvey, Fogel, 2007) have defined personality traits as a set of characteristic dispositions that determine emotional, interpersonal, experimental, attitude and motivational styles. Personality dimensions, such as extraversion and neuroticism, have been shown to play an important role in the satisfaction of children's lives (Khosla, 2012). Another significant aspect of children's personalities is given by how they are reflected in their academic achievements. Specialists have described the relationship between individual personal traits and academic achievements through the ability of general social adaptation, which we can call successful / unsuccessful socialization and specific adaptation to diversity (Saarni, 1999). G. Pânişoară, C. Ghiță, I. Lazăr, S. Făt - Study on the Development of Personality Traits in Children with Language Disorders and Children without Language Disorders 39 In the case of children with language disorders, the processes of recovery and education through cognitive stimulation, socialization, personal autonomy, occupational therapy, influence the personality of the individual through the skills they cause at the level of personality. This is supported by the personalization theory, which describes personality as the subject of the interpersonal relationship, being expressed in two psychological spheres: intra-individual (character, temperament, abilities, personality) and inter-individual (space that takes place in a group of relationships and reciprocal interactions). From this perspective, the results of language recovery appear in this dimension of personalization that contributes to the formation of student characteristics, especially in terms of self-esteem and self-image, quantitative and qualitative changes in positive emotions, behavior and attitudes (Novojenova & Sawilowsky, 1999). Positive emotions are an essential component of childhood personality development (Wang, Shi & Li, 2009). Body and emotional changes of the child are essential in the development of the self. ). Regarding the state of well-being and the emergence of positive emotions, there are strong relationships between their existence and the five personality factors: emotional stability, extraversion, benevolence, imagination and consciousness (DeNeve & Cooper, 1998). Individual differences in two emotion regulation processes: implications for affect, relationships, and well- being. One of the most important values that a person develops throughout his life is self-identity, which operates through self-confidence, self-esteem, and self-image in the relationship with the self and others (Horvath, 2012). Emotions guide the child to others by making him become more aware of his self (Gross & John, 2003). The importance of understanding and awareness of each individual's communication capabilities is a significant prerequisite for optimal cognitive adaptation to school and social needs. Various operations of thought, such as analysis, synthesis, or comparison allow each individual to make remarkable social progress, managing to best build those personality traits that are right and specific to their own temperament set (Griffits, 2007). Strategies that teachers and therapists typically use in socializing negative emotions (sadness, anger, shame, fear) at different stages of development (childhood, adolescence) lead to mental health consequences (Saarni, 1999)). Emotional learning starts from the first moments of life and continues throughout childhood. Children develop a base of emotional perspectives and emotional capacity. During this time, strong stress can affect the ability of learning the brain (Goldberg, 1991). 2. Methodology 2.1. Aim Analysis of how to develop and develop personality traits in children with language disorders and children who do not have language problems. Identifying the specific features of children's personality traits from a neuropsychological perspective. 2.1.1. Research Objectives Identifying existing differences between children with language disorders and children without language disorders in terms of developing personality traits. Making the neuropsychology picture of the personality traits of children with language disorders. Making a specific picture of the personality traits of children in the urban environment. 2.1.2. Hypothesis There are statistically significant differences in each personality traits between children with language disorders and those with no language disorders. There is a specific picture of the personality traits of children in the urban environment. BRAIN – Broad Research in Artificial Intelligence and Neuroscience Volume 10, Issue 2 (April, 2019), ISSN 2067-3957 40 2.2. Subjects The sample consisted of 60 children aged 7-12 years old from urban areas. The subjects were both children with different language disorders, as well as children with a normal development of language, from urban areas. Voluntary participants were instructed before applying the questionnaire including on ethical issues in research. 2.3. Data Collection Method The method used is represented by the HiPIC - Hierarchical Personality Inventory for Children (I Mervielde and Filip de Fruyt), a psychological tool for assessing the personality of children aged 6 to 13 and is based on the established Big Five model. The inventory is a personality HiPIC contains 144 items and allows the evaluation of the emotional, interpersonal, motivational and behavioral style of children based on the five dimensions of personality. The five dimensions of the questionnaire are: emotional stability (STAB E), extraversion (EXTR), imagination (IMAG), benevolence (BENEV) and conscientiousness (CONSTIINT). 2.4. Data Analysis The data acquired after the psychological tool for assessing the personality of children aged 6 to 13 were explored through SPSS 13 program package. According to one-sample Kolmogorov- Smirnov test results, the five dimension of personality were establish to be normally distributed. So, the Independent t-test was appropriate for investigate the impact of group characteristic (i.e. presence or absence of language disorders) on personality traits. Exploratory factor analyses (Izquierdo, Olea & Abad 2014) and correlational analyses were used to search the link between personality traits. 3. Results and Discussions 3.1. Descriptive Statistics Collected data was input into the SPSS statistical software. Because of the normal distribution of data (Table 1), we were able to apply the Independent t-test in order to investigate if are statistically significant differences between certain personality traits of children with normal language development and those with different language disorders. Table 1 also shows descriptive statistics of the five personality traits investigated in this research for children with normal language development. As can be seen, the highest scores are obtained at the size of "imagination" and "benevolence". Taking into account the standard scores, we believe that the results obtained by the participants in this category are great, which leads us to build a picture of their personality traits focused on imagination, emotional stability and benevolence. Children who show a dominance of personality traits such as benevolence and imagination are characterized by positive attitude, eager to help, creativity, artistic activities. Table 1. Results for descriptive statistics for five dimensions in children with normal development STAB E EXTR IMAG BENEV CONSTIINT N 30 30 30 30 30 Normal Parametersb,c Mean 45.24 46.79 56.21 60.45 55.69 Std. Deviation 30.652 24.471 25.420 28.149 27.628 Most Extreme Differences Absolute .097 .085 .099 .219 .093 Positive .091 .066 .076 .131 .072 Negative -.097 -.085 -.099 -.219 -.093 Kolmogorov-Smirnov Z .531 .468 .541 1.201 .509 Asymp. Sig. (2-tailed) .941 .981 .932 .111 .958 In Table 2 One-Sample Kolmogorov-Smirnov Test was applied to identify the distribution of the data obtained from the test for children with language disorders. Also Table 2 shows the G. Pânişoară, C. Ghiță, I. Lazăr, S. Făt - Study on the Development of Personality Traits in Children with Language Disorders and Children without Language Disorders 41 descriptive statistics for the five dimensions of the personality analyzed in this study for children with different language deficits. The results presented in the table below show a normal distribution of data because the Asymp. Sig. (2-tailed) are greater than 0.05 which allows us to apply parametric tests for small groups in order to identify the differences between the two groups on personality traits. Table 2. Results for descriptive statistics for five dimensions in children with language disorders STAB E EXTR IMAG BENEV CONSTIINT N 30 30 30 30 30 Normal Parametersb,c Mean 42.03 40.17 37.86 38.79 49.90 Std. Deviation 32.775 29.111 30.936 39.564 37.747 Most Extreme Differences Absolute .135 .116 .173 .207 .168 Positive .135 .116 .173 .207 .155 Negative -.100 -.084 -.123 -.169 -.168 Kolmogorov-Smirnov Z .739 .634 .947 1.133 .918 Asymp. Sig. (2-tailed) .645 .817 .331 .153 .368 What it is interesting to overlook is that, on the one hand, lower scores were recorded for each of the five personality traits, and on the other hand the highest average was obtained at conscientiousness and emotional stability. From this we can extract the idea that, in their case, conscientiousness develops as a dominant personality trait and in the light of the gaps they present at the level of language. Even if they have these language difficulties, these children present a psychological picture of personality traits dominated by conscientiousness, emotional stability and extraversion. 3.2. Comparing the Average Results of the Two Groups Taking into account the first hypothesis launched in this research on the differences between the two groups investigated in terms of personality traits, the Independent t-test was applied. Table 3 describes the Independent t-test results for the differences in the score of personality traits for the two categories of participants. There are statistically significant differences between children with language disorders and those with no language disorders only related to their imagination (F=1.945, p< .05) and benevolence (F=6.827, p< .05) (Table 3). Positive, helpful and benevolent attitude is more common in children with a normal language development than those with language difficulties. Altruism and focusing on the needs of those around them are dominant for children in the first investigated group. Table 3. Independent t-test results to determine the impact of group characteristic on personality traits Levene's Test for Equality of Variances t-test for Equality of Means F Sig. (2- tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper STAB E Equal variances assumed .439 .697 3.207 8.193 -13.193 19.607 Equal variances not assumed .697 3.207 8.193 -13.195 19.609 BRAIN – Broad Research in Artificial Intelligence and Neuroscience Volume 10, Issue 2 (April, 2019), ISSN 2067-3957 42 EXTR Equal variances assumed .805 .344 6.621 6.943 -7.278 20.519 Equal variances not assumed .344 6.621 6.943 -7.287 20.528 IMAG Equal variances assumed 1.945 .015 18.345 7.310 3.712 32.978 Equal variances not assumed .015 18.345 7.310 3.700 32.990 BENEV Equal variances assumed 6.827 .018 21.655 8.865 3.910 39.401 Equal variances not assumed .018 21.655 8.865 3.869 39.442 CONSTIINT Equal variances assumed 7.441 .500 5.793 8.540 -11.303 22.889 Equal variances not assumed .501 5.793 8.540 -11.336 22.922 Figure 1. Graphic on the differences between the two groups - benevolence Figure 2. Graphic on the differences between the two groups – imagination 63% 37% Graphic for benevolence 1 2 61% 39% Graphic for imagination 1 2 G. Pânişoară, C. Ghiță, I. Lazăr, S. Făt - Study on the Development of Personality Traits in Children with Language Disorders and Children without Language Disorders 43 The two figures represent graphically the differences between the two groups of participants in this study for two of the analyzed dimensions, benevolence and imagination. As can be seen in Figure 1, the percentage obtained by children with a normal development of language to size, benevolence is 63% compared to 37% obtained by children with language difficulties. It is necessary to intervene the specialists in the field to alleviate these difficulties, thus building and developing positive and benevolent attitude in the case of children with language deficiencies. The same considerations apply to size, curiosity, where the differences are similar. 3.3. Factor Structure of the Five Personality Traits In this stage we investigated the factor structure of the five personality traits using the results obtained by HiPIC - Hierarchical Personality Inventory for Children (I Mervielde and Filip de Fruyt) psychological tool. Exploratory factor analysis (EFA) (Field 2006) in which principal axis factoring extraction with promax rotation was used to search the structure of the five personality traits (n=60). This analyses revealed that the item-factor structure of the psychological tool is unidimensional. The total variance accounted for one extracted factor with eigenvalues is greater than 1 was 50.558%. Factor loadings (Table 4) and correlations between factors (Table 5) were evaluated based on EFA results. Table 4. Factor loadings (principal axis factoring extraction, promax rotation, one factor, n=60) Factor 1 STAB E .656 EXTR .381 IMAG .744 BENEV .899 CONSTIINT .769 It is observed (Table 4) that the factors with the highest load, which we consider to be the most representative for the model, in order of importance are: benevolence (0.899), consciousness (0.769) and imagination (0.744). 3.4. Correlations between Factors Correlation analysis was performed between the most important psychological traits, i.e. benevolence and consciousness with the condition of constantly maintaining the effect of the extraversion variable on the two analyzed variables (Table 5 and Table 6). Table 5. Correlation between benevolence and conscientiousness for children with normal development BENEV CONSTIINT BENEV Pearson Correlation 1 .604** Sig. (2- tailed) .000 N 30 30 CONSTIINT Pearson Correlation .604** 1 Sig. (2- tailed) .000 N 30 30 BRAIN – Broad Research in Artificial Intelligence and Neuroscience Volume 10, Issue 2 (April, 2019), ISSN 2067-3957 44 Table 6. Correlation between benevolence and conscientiousness for children with language disorders BENEV CONSTIINT BENEV Pearson Correlation 1 .832** Sig. (2- tailed) .000 N 30 30 CONSTIINT Pearson Correlation .832** 1 Sig. (2- tailed) .000 N 30 30 Table 7 and Table 8 highlights that extraversion as control variable has a low influences on relationship between benevolence and conscientiousness, both for children with normal language development and those with language disorders. After isolation the effect of the extraversion variable the correlation between benevolence and conscientiousness increases slightly from 0.604 to 0.606 for children with normal language development and from 0.832 to 0.840 for those with language disorders. The benevolent attitude, the opening to the needs of others and the conscientiousness of personal actions are in a strong connection when the personality factor, extravagance, which is present for these children. Table 7. Partial correlation between benevolence and conscientiousness for children with normal development; extraversion as control variable Control Variables BENEV CONSTIINT EXTR BENEV Correlation 1.000 .606 Significance (2-tailed) . .000 df 0 27 CONSTIINT Correlation .606** 1.000 Significance (2-tailed) .000 . df 27 0 Table 8. Partial correlation between benevolence and conscientiousness for children with language disorders; extraversion as control variable Control Variables BENEV CONSTIINT EXTR BENEV Correlation 1.000 .840 Significance (2-tailed) . .000 df 0 27 CONSTIINT Correlation .840** 1.000 Significance (2-tailed) .000 . df 27 0 Therefore, maintaining constant the influence of extraversion variable we noted a significant positive correlation between conscientiousness and benevolence, both for children with normal language development and those with language disorders. But the effect of consciousness on benevolence is stronger for children with language disorders (r(28)=0.840) than those with normal development (r(28)=0.606). G. Pânişoară, C. Ghiță, I. Lazăr, S. Făt - Study on the Development of Personality Traits in Children with Language Disorders and Children without Language Disorders 45 4. Conclusions The present study was conducted to explore the differences between children with normal language development and those with language difficulties. We also intend to build a psychological picture of personality traits based on a sample of 60 subjects on which has been applied the HiPIC - Hierarchical Personality Inventory for Children. The results of this research allow us to express the following conclusions:  children with a normal development of language have a dominant personality trait, benevolent, which implies open, positive attitude, orientation towards other;  children with language difficulties have the dominant personality trait, the conscientiousness, which is responsibility, perseverance, seriousness in accomplishing the tasks. The strong correlation between the benevolence and consciousness mediated by the extraversion personality factor highlights the essential role that open attitudes, the knowledge of one's own personality, and the building of healthy relationships with people around him, play a sense of conscientiousness, responsibility and orientation towards the needs and feelings of others. Therefore, the specific picture of personality traits developed by children in this study shows a strong focus on extraversion, conscientiousness and emotional stability. This study allows to investigate further hypotheses related to other dominant personality traits for the both subject categories. Our recommendations are materialized by the recognition of programs specialists and activities for building those personality traits that are presented with low scores. Acknowledgements This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS/CCCDI – UEFISCDI, project number PN-III-P2-2.1-PTE-2016-0068. References Atashrooz, J., & Behrooz, K. (2009). The relationship between the big five personality traits and academic achievement, Journal of Iranian psychologists, 16, 367-376. Bates, T. C., & Rock A. (2004). Personality and information processing speed: Independent influences on intelligent performance/ Intelligence, 32(1), 33-46. Caspi, A. (2000). The child is father of the man: personality continuities from childhood to adulthood. Journal of Personality and Social Psychology,78, 158-172. Crețu, T., (2007). Psihologia vârstelor, Polirom, Iași. DeNeve, K. M., & Cooper, H. (1998). The Happy Personality: A meta-analysis of 137 personality traits and subjective well-being. Psychological Bulletin, 124, 197-229. DeYoung, C. (2010). Personality Neuroscience and the Biology of Traits. Social and Personality Psychology Compass, 4/12, 1165–1180. Field, A. (2006). Discovering Statistics using SPSS (Second Edition ed.). London: SAGE Publications Ltd. Garvey, A., & Fogel, A. (2007). Dialogical change processes, emotions, and the early emergence of self. International Journal for Dialogical Science, 2(1), 51–76. Goldberg, L. R. (1991). Language and individual differences: The search for universals in personality lexicons. In L. Wheeler (Ed.), Review of personality and social psychology, 2, 141–165. Beverly Hills, CA: Sage. Goleman, D. (2001). Inteligența emoțională. Cheia succesului în viață. Curtea veche. București. Goswami, U., & Szucs, D. (2011). Educational neuroscience: Developmental mechanisms: towards a conceptual framework. Neuroimage, 57(3), 651-658. Gross, J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85, 348–362. Griffits, C. C. B. (2007). Pragmatic abilities in adults with and without dyslexia: a pilot study. Dyslexia. 13, (14), 276-296. BRAIN – Broad Research in Artificial Intelligence and Neuroscience Volume 10, Issue 2 (April, 2019), ISSN 2067-3957 46 Heaven, P. C., & Ciarrochi, J. (2012). When IQ is not everything: Intelligence, personality and academic performance at school. Personality and Individual Differences, 53(4), 518-522. Horvath, H. A. (2012). Conscience in fragments. Practice and theory in Systems of Education, 7 (1), 37-52. Izquierdo, I., Olea, J., & Abad, F., J. (2014). Exploratory factor analysis in validation studies: Uses and recommendations, Psicothema, 26 (3), 395-400. Khosla, M., (2012). Emotion regulation and well-being. Applied Research Quality Life, 7, 323-325. Norman, W. T. (2003). Toward an adequate taxonomy of personality attributes: Replicated factor structure in peer nominations personality ratings. Journal of Abnormal and Social Psychology, 66, 574–583. Novojenova, R., Sawilowsky, & Sh. S. (1999). Measurement of influence of the teacher personality on students in the classroom. Social Behavior and Personality, 27, 533 – 544. Saarni, C. (1999). Emotional Competence: How Emotions and Relationships Become Integrated. Socioemotional Development, 36, 115-182. Lincoln: University of Nebraska Press. Wang, L., Shi, S., & Li, H. (2009). Neuroticism, extraversion, emotion regulation, negative affect and positive affect: the mediating roles of reappraisal and suppression. Social Behavior and Personality, 37(2), 193-194. Georgeta Pânișoară, Ph.D. (born 1974), is an Associate Professor in Psychology area at Department of Psychology, Habilitated in Educational Sciences, works at Bucharest University. She wrote and coordinated more than 10 books (coordinator The psychology of Modern Child, coordinator 2011, The Childhood and Adolescence. New challenges in developmental Psychology, 2016). She coordinates series of books Child Psychology and Parenting at Polirom Publishing House. She was involved in national and international projects. Co-founder of website www.performante.ro (about education and parenting). Speaker in national media (radio, newspapers, TV). Cristina Ghiță, Ph.D., Lecturer in Education Sciences. Works at the Faculty of Psychology and Educational Sciences at the University of Bucharest. Fields of interest are Psychology of Education, Psychology of Learning and Management of Student Classes. She published two books on persuasive communication and motivation in the educational space. She has written numerous international and national articles in the field of education sciences and psychology and has been a member of research projects. She has participated in a large number of international conferences with works in the field of psychology of education. Iuliana Mihaela Lazăr, graduate of the University of Bucharest, Romania; main field of interest research: study the impact of new digital tools in science education; coordinator and/or member of more than 10 research/development projects, won by national or international competition; publications in ISI and BDI quoted journals that have accumulated more than 200 citations, with a Hirsch index h = 6 (http://www.researcherid.com/rid/B-5974-2011). Silvia Făt is an associate professor at the Faculty of Psychology and Educational Sciences, University of Bucharest. The author has expertise in instructional design and teacher training programs. Its work aims to enhance the use of new technologies in educational practices, especially in the active field of teaching and learning strategies. The research area is defined by many studies conducted in eLearning projects and the scientific review at International Conference on Virtual Learning and International Conference eLearning and Software for Education (Romania).