THE ROLE OF PERSONALITY TRAITS IN THE PROCESS OF ADAPTATION TO URBAN LIFE

IRASS Journal of Arts, Humanities and Social Sciences https://irasspublisher.com/journal-details/IJAHSS ISSN (Online) 3049-0170 This is an open access article under the CC BY-NC license 1 JOURNAL COVER PAGE THE ROLE OF PERSONALITY TRAITS IN THE PROCESS OF ADAPTATION TO URBAN LIFE Dr. Nedret Keskin* Corresponding Author Dr. Nedret Keskin Article History Received: 16 / 09 / 2025 Accepted: 24 / 11 / 2025 Published: 02 / 12 /2025 Abstract: Urban environments demand complex psychological, social and behavioral adjustments from individuals who relocate from rural or semi-urban areas. This study examines how personality traits, particularly the Big Five dimensions-extraversion, openness to experience, conscientiousness, agreeableness and neuroticism-shape individuals’ adaptation to urban life. Drawing on contemporary urban sociology and personality psychology, the research explores the mechanisms through which personality influences stress management, social integration, perceived crowding, environmental tolerance, and engagement with urban opportunities. Findings indicate that high openness and extraversion facilitate faster cultural and social adaptation, while conscientiousness supports structural adjustment such as time management and rule compliance. Conversely, high neuroticism is associated with elevated adaptation stress, reduced environmental satisfaction and a heightened sense of urban overload. The study underscores that urban adaptation is not solely a structural or socioeconomic process but is deeply intertwined with stable dispositional characteristics. These results contribute to a more nuanced understanding of urban adjustment and offer implications for urban planners, policymakers and migration psychologists. Keywords: Personality traits, urban adaptation, Big Five, environmental psychology, migration, social integration. How to Cite in APA format: Keskin, N. (2025). THE ROLE OF PERSONALITY TRAITS IN THE PROCESS OF ADAPTATION TO URBAN LIFE. IRASS Journal of Arts, Humanities and Social Sciences, 2(12), 1-27. Introduction The process of urbanization and migration movements brings about a multifaceted transformation where individuals face significant changes at the social, cultural, and psychological levels (Sarıbay, 2002). Individuals migrating to the city do not only experience a physical relocation; they also have to adapt to new norms, institutions, and social expectations. This adaptation process is shaped by the individuals' personality structures, perceived levels of social support, and individual differences (Şahnagil & Güler, 2019). Urban consciousness is a level of social awareness that expresses the extent to which individuals understand, adopt, and participate in urban life with a sense of responsibility (Şahin & Anık, 2016). Especially for individuals who have migrated, the formation of a sense of belonging and the process of integration into the social structures of the city play a decisive role in adaptation (Sağır & Koç, 2025). However, the relationship of this process with personality traits and social support systems has not yet been thoroughly examined in the literature. This study aims to explain the effect of personality traits on adaptation to urban life and to analyze how individual differences and social support levels shape this relationship. Theoretical Foundations The main basis of the research is the Five-Factor Personality Theory. This theory evaluates individuals' personality structures across five basic dimensions (extraversion, neuroticism/emotional stability, openness to experience, agreeableness, and conscientiousness) and is considered to provide a determining structure in social adaptation processes (Goldberg, 1993). Adaptation to urban life, on the other hand, means the emotional and behavioral integration of the individual into the physical, cultural, and social structure of the city. This adaptation process is shaped by the individual's internalization of urban culture, taking responsibility, establishing social relationships, and feeling a sense of belonging to the city (Birol, 2008; Acungil, 2012). Social support is a protective variable that enhances individuals' capacity to cope with challenging life events (Eker & Arkar, 2001). The presence of social support systems within the complex and competitive structures of urban life facilitates individuals' healthier adaptation to the urban environment (Bayhan, 2022). Personal Identity Theory Personal identity is a multi-dimensional structure that includes the individual's cognitive and emotional evaluations regarding how they define themselves, the values, beliefs, sense of belonging, and social roles they attribute to themselves (Erikson, 1968). Identity constitutes the individual's self-perception and is shaped within the framework of the relationships the individual establishes with their social environment. Especially for individuals migrating to the city, personal identity is at the center of the processes of being able to exist in a new social environment, adapting to changing norms, and gaining social acceptance (Marcia, 1980). According to Marcia's theory of identity statuses, individuals can pass through four different stages during the identity formation process: identity diffusion, foreclosure, moratorium, and identity achievement. These stages can vary IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 2 according to the individual's life experiences, environmental influences, and social support systems (Kroger, 2007). The transitions individuals experience in these stages after urbanization and migration directly affect the process of adaptation to urban life. Therefore, in this research, individuals' perceptions of personal identity are handled in relation to processes such as integration into urban life, developing a sense of belonging, and establishing social bonds. Evaluating personal identity along with personality traits and social support makes it possible to offer a more holistic perspective on the individual's process of adaptation to urban life. Research Aim The aim of the research is to deeply examine the effects of personality traits on individuals' processes of adaptation to urban life. While the dynamic structure of urban life shapes individuals' social, economic, and cultural interactions, the role of personality traits in these interactions becomes prominent. In this context, the research aims to reveal how personality traits influence individuals' experiences in urban settings in relation to variables such as gender, age, and socioeconomic status. The research will use various theoretical frameworks to understand the interaction between human psychology and urban sociology, evaluating the impact of personality factors on individuals' urban living standards, social adaptation processes, and general life satisfaction. Furthermore, the effect of negative situations brought by urbanization, such as stress factors and social isolation, on certain personality profiles is also significantly addressed. Determining the relationship between personality traits and the challenges of urban life can provide valuable information for policymakers, social workers, and urban planners. Scope of the Research The scope of the research aims to determine which elements interact in the process of adaptation to urban life regarding personality traits. In this context, we will primarily examine different personality structures, evaluating the individual's relationship with city life and the reflections of this interaction on societal dynamics. The study aims to present information on how the personality traits of participants interact with different urban life scenarios based on various demographic factors (such as age, gender, educational level). The research will be strengthened by a combination of quantitative and qualitative methods. Firstly, data on personality traits and levels of adaptation to urban life will be collected through surveys conducted with a large participant pool. In addition, semi-structured interviews will be conducted on a specific sample for in-depth analysis of this data, thus seeking to understand individuals' experiences and perceptions of city life more comprehensively. This methodological approach will highlight the effect of personality traits on adaptation processes in city life, while also providing an opportunity to reveal the individual differences in life experiences and their social impacts. The study also seeks to offer clues about how the social, economic, and cultural dynamics brought by urban life are affected by individuals' personality traits. Specifically, the reflections of factors such as increasing stress levels, forms of socialization, and lifestyles in modern cities on personality traits will be examined, and the effects of these dynamics on social harmony and societal solidarity in cities will be discussed. In conclusion, this research aims to holistically understand the relationship between personality traits and adaptation to urban life and to shed light on future studies in this area. The examination of the interaction between personality and environment can also make significant contributions to the development of urban planning and social policies to improve individuals' quality of life. Conceptual Model The conceptual model is as follows:  Independent Variable: Personality Traits (Big Five Theory)  Mediator Variable: Perceived Social Support  Dependent Variable: Adaptation to Urban Life / Urban Consciousness The conceptual model of the research is presented in Figure 1: Conceptual Model and Hypotheses Figure 1. Conceptual Model Diagram (Source: Created by the Researcher) The hypotheses tested in line with this model encompass the direct and indirect effects of personality traits on urban life adaptation, mediated by perceived social support. Core Variables  Independent Variable: Personality Traits (e.g., neuroticism, extraversion, agreeableness) are considered. This variable functions as the factor influencing individuals' adaptation processes to urban life.  Dependent Variable: Adaptation to Urban Life (e.g., social integration, stress level, life satisfaction) can be accepted as the dependent variable at this point, as this factor varies depending on personality traits.  Intermediate Variables: Variables such as individual differences and social support can be considered intermediate variables. Individual differences (age, gender, background) may moderate the effect of personality traits on urban life adaptation. Social support, however, is specifically modeled to shape how individuals are influenced by their personality traits and to mediate its role in the process of adapting to urban life. Hypotheses  H1: Individuals with a high level of Extraversion have a higher level of adaptation to urban life.  H2: The level of Perceived Social Support positively predicts adaptation to urban life.  H3: Perceived Social Support plays a mediator (intermediary) role in the effect of personality traits on urban life adaptation. IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 3  H4: Individual factors such as the birthplace, age, and education level of individuals migrating to the city create a significant difference in Urban Consciousness. The study, built upon this theoretical structure, aims to provide both a theoretical contribution and practical data that can be used in shaping urban policies. Method The study is structured within a mixed-methods framework. In the quantitative part, data will be collected using the relational survey model; in the qualitative part, thematic analysis will be performed using open-ended responses. SPSS 26.0 and MAXQDA software will be used. The tests to be used are: Pearson Correlation, Multiple Regression, ANOVA, and Mediation analysis, with the usage and literature details provided in the following sections. Research Model The integration of quantitative and qualitative data in the research will be carried out within the framework of the explanatory sequential design. Method (Continued) Research Model (Continued) The integration of quantitative and qualitative data in the research will be carried out within the framework of the explanatory sequential design. First, statistical relationships between personality traits, social support, and urban adaptation will be analyzed through quantitative data; then, the findings obtained will be analyzed thematically through qualitative data. This strategy lends explanatory qualities to the quantitative findings and ensures that interpretations are made with a richer, multidimensional approach. The research is based on the relational survey model, which examines the relationship between individuals' personality traits and their levels of adaptation to urban life. The relational survey model is the survey approach that aims to determine the existence of co-variation between two or more variables. In the relational survey model, the aim is to ascertain whether the variables co-vary, and if there is co-variation, how it occurs (Karasar, 2011; Bahtiyar & Can, 2016). Furthermore, the study adopts a mixed-methods approach where quantitative and qualitative data types will be used together. Quantitative research involves examining social phenomena through statistical analysis of numerically measurable data and aims to discover the laws of social order by revealing cause-and-effect relationships between these phenomena (Sayt, 2025). Qualitative research commonly uses data collection methods such as observation, structured or semi-structured interviews, focus group interviews, discourse, and text analysis (Baltacı, 2019). Therefore, Qualitative research methods are defined not as a single data collection technique but as methods that can utilize and analyze different data collection techniques (Zülfikar, 2025). In this context, mixed-methods research has also been developed based on these foundations. That is, with the acceptance and development of the joint use of qualitative and quantitative research in social and human sciences, mixed-methods research that uses both types of data collection has also become widespread (Baki & Gökçek, 2012). The quantitative data set in the study will allow for correlational analyses and regression models, while qualitative data will gain supportive depth through thematic analysis. Participants and Sample The research sample will consist of participants selected from individuals 18 years and older living in the province of İzmir, Turkey. Participants will be reached through both face-to-face and online methods (such as Google Form). The proportional stratified sampling method will be used in determining the sample group, and representativeness will be ensured based on demographic variables such as age, gender, birthplace, and education level. There are two main sub-types of stratified sampling: proportional and non-proportional sampling. In proportional stratification, the number of items assigned to various strata is proportional to the rate at which the strata represent the target population. That is, the sample size taken from each stratum is proportional to the relative size of that stratum of the target population. The sampling fraction is applied to each stratum, giving every population element an equal chance of being selected. The resulting sample is self-weighted (QuestionPro, 2025). Sociocultural structures such as different districts, neighborhoods, and high-migrant areas within the city will also be considered to increase the representation of various life practices and adaptation experiences. Based on the principles and guidelines of the ethics committee, no exclusionary criteria based on age, gender, ethnic identity, or other personal characteristics will be applied. The planned sample size will be determined by power analysis using G*Power 3.1 software, aiming to reach a minimum of 300 participants at a 95% confidence level. G*Power software supports sample size and power calculation for various statistical methods This software is useful for researchers to estimate sample size and perform power analysis (Kang, 2021). In the selection of participants, no exclusionary criteria based on personal characteristics such as age, gender, or ethnic identity will be used; the research will be conducted in full compliance with ethical principles. Data Collection Tools The following psychometric tool will be used in the research:  Personal Identity Status Questionnaire (This scale has been used in previous academic studies, and its validity and reliability studies have been published. Therefore, it is scientifically usable.) Pre-Data Collection Process and Ethical Principles Before the data collection process, an informed consent form will be presented to every participant, and only individuals who consent will be included in the study. The form will include the following statements:  The purpose and scope of the research.  That participation is based entirely on a voluntary basis.  That they can withdraw from the study at any time without giving any reason.  That no identifying information will be collected and all data will remain anonymous. IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 4  That the data obtained will be used only for scientific purposes. The data will be stored only by the researcher in a passwordprotected digital environment; it will be archived for 5 years and then deleted. There is no intervention that poses a risk of physical or psychological harm to the participants. This procedure is compliant with the Declaration of Helsinki and the Turkish Law on the Protection of Personal Data (KVKK). Data Collection Process  The survey will be administered face-to-face or online (e.g., Google Form).  The survey consists of a total of one scale: PERSONAL IDENTITY STATUS QUESTIONNAIRE (The Personal Identity Status Questionnaire is designed as a measurement tool that allows individuals to evaluate their selfperceptions of identity.)  In addition, qualitative data will be collected through short open-ended questions. Data Analysis Each of the hypotheses in the study will be tested with the statistical analysis methods specified below.  Hypothesis H1, which tests the relationship between the level of extraversion and adaptation to urban life, will be examined with Pearson correlation analysis and regression methods.  Hypothesis H2, which evaluates the directional relationship between perceived social support and adaptation to urban life, will be subjected to multiple regression analysis.  Hypothesis H3, within the scope of mediator (mediation) analysis, will be evaluated with regression-based analyses that test the mediating role of perceived social support in the effect of personality traits on urban life adaptation.  Hypothesis H4, which examines the effect of individual demographic variables on urban consciousness, will be analyzed with the ANOVA test. The collected quantitative data will be analyzed with the SPSS 26.0 program. SPSS is a software program used for statistical data analysis (Komtaş, 2022). The planned analyses are:  Descriptive Statistics (mean, standard deviation): Descriptive statistics help to define and describe the characteristics of a specific data set by presenting brief summaries of the sample and data measurements (Hayes, 2024).  Correlation Analysis ($\text{Pearson } r$): Correlation is a measure of the strength and direction of the relationship between two continuous variables (İstatistik Türkiye, 2016). The Pearson correlation coefficient ($r$) is the most common way to measure a linear correlation. It is a number between -1 and 1 that measures the strength and direction of the relationship between two variables. When one variable changes, the other variable changes in the same direction (Turney, 2024).  Regression Analysis (Multiple Regression and Mediator Analysis): Regression analysis is performed to determine the relationship between two or more variables that have a cause-and-effect relationship between them and to be able to make estimations or predictions related to that topic using this relationship (Bakan, 2025). Multiple linear regression measures the effect of more than one independent variable on the dependent variable. For example, it is used to measure the effect of weight, age, and stress level on blood pressure (İstatistik Türkiye, 2016a). Mediator analysis (or mediation analysis) is a regression-based technique used to test how the effect of an independent variable (X) on a dependent variable (Y) occurs through an intermediate variable (mediator, M). In other words, it is a social science research model in which a mediating variable (M) is used to explain the effect of an independent variable (X) on a dependent variable (Y), how this effect occurs, and the directions in which it influences (Çağlayan & Özenç, 2024).  ANOVA (Assessment of the effect of demographic differences): ANOVA is a tool used to test whether there is a statistically significant difference between the means of independent groups (SPSS Amos İstatistik Analiz, 2021). Short open-ended statements collected as qualitative data will be evaluated using the thematic analysis method with the MAXQDA software. MAXQDA is an advanced computer-aided analysis software that allows for the systematic coding, categorization, analysis, and interpretation of qualitative and quantitative data, and can conduct data analysis processes in accordance with scientific methods (Dereli, 2023). Thematic analysis is the general name given to qualitative data analysis methods that consist of the processes of creating patterns (themes) from qualitative data, making sense of these patterns, and reporting, and it is a commonly used analysis (Braun & Clarke, 2021). This method stands out as a continuously used method for qualitative data analysis methods (Hınız & Yavuz, 2023). Participant Process and Ethical Principles Information Procedure Flow (Pre-Data Collection Process) In this study, the process of information and voluntary participation to protect participant rights will be carried out with the following steps: 1. Determination of Participants: Individuals aged 18 and over who meet the research criteria will be reached within the determined sample framework. Access will be provided through both face-to-face and online methods (such as Google Form). 2. Pre-Information: A brief explanation regarding the subject, purpose, scope of the research, and the data collection tools to be used will be presented to the participants in writing and/or verbally. 3. Presentation of the Informed Consent Form: The Informed Consent Form will be delivered to theparticipants in digital form or as a printed document. This form will clearly state: IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 5 o The purpose and scope of the research. o That participation is based on the principle of voluntariness. o That they have the right to withdraw at any time. o That no identifying information will be collected and the data will be kept anonymous. o That the data will be used only for scientific purposes and will remain confidential. o That the research does not carry any risk. 4. Obtaining Consent: Participants will give their voluntary participation consent by checking the consent box on the form (it will be set as a required field in the online application) or by submitting a signed consent form in the face-to-face application. 5. Additional Information Before Data Collection: Participants will be informed about the content and approximate duration (10–15 minutes) of the survey, and it will be stated that the survey consists of three sections (personality, urban consciousness, and social support). It will be emphasized that open-ended questions are optional. 6. Transition to the Data Collection Process: Only participants who approve the consent form will be included in the data collection process. Data from individuals who do not consent will not be processed or included in the systematic analysis process in any way. 7. Ethical and Legal Assurance Statement: Participants will be reminded for the last time that the study is conducted in full compliance with the Declaration of Helsinki, KVKK, and the YÖK Scientific Research and Publication Ethics principles. Information and Voluntary Participation Regarding Participants Participants will be individuals aged 18 and over, and absolutely no exclusionary criteria (e.g., age, gender, ethnic origin) that would lead to any discrimination will be applied. An informed consent form will be presented to every participant; only individuals who consent will be included in the study. There is no medical, physical, or psychological intervention in the research. Participants will be able to leave questions unanswered at any time and withdraw from the study without giving a reason. Confidentiality and Data Storage No identifying information will be taken from participants, and data will be stored in a password-protected digital environment accessible only to the researcher. All data is anonymous. The data will be archived for 5 years, after which it will be safely destroyed. This practice complies with KVKK and the Declaration of Helsinki. This research is fully compliant with the ethical rules defined within the scope of the Declaration of Helsinki and the YÖK Scientific Research and Publication Ethics Directive, especially the KVKK (Law No. 6698 on the Protection of Personal Data). Unethical practices such as plagiarism, distortion, and data fabrication will absolutely not be included in the research, and all processes will be carried out based on the principles of scientific integrity. Publication and Use of Results Use of Data within the Framework of Publication Ethics The data obtained from the research can be used in masters/doctoral theses, scientific articles, or papers. However, this use will be carried out in a way that does not disclose the identity of the participants. The data will be checked for anonymity again before publication. Informed Consent Form Title of the Research: THE ROLE OF PERSONALITY TRAITS IN THE PROCESS OF ADAPTATION TO URBAN LIFE: EFFECTS OF INDIVIDUAL DIFFERENCES AND SOCIAL SUPPORT Researcher: Nedret Keskin Supervisor: Prof. Dr. Kürşat Yıldırımer This study has been submitted to the St. Clements University Ethics Committee for evaluation with the decision dated 2025 and numbered [...]. Purpose of the Research: This research aims to examine the effect of individuals' personality traits on the processes of adaptation to urban life and the mediating role of perceived social support in this relationship. Scope of the Research: The Personal Identity Status Questionnaire will be administered to participants within the scope of the study. The survey will take approximately 10–15 minutes. Voluntary Nature of Participation: Participation in this research is entirely voluntary. Participants have the right to withdraw from the study at any time without giving any reason. Confidentiality and Anonymity: No personal information (name, surname, ID number, etc.) will be collected in the research, and all data will be evaluated anonymously. The data obtained will be used only for scientific purposes; it will not be shared with third parties. The data will be protected in a password-protected digital environment and will be securely deleted after 5 years. Risk Information: The research does not involve any risk of physical or psychological harm. No experimental intervention will be performed on the participants. Ethical Compliance: The research will be conducted in accordance with the principles of the Council of Higher Education Scientific Research and Publication Ethics Directive, the Declaration of Helsinki, and the KVKK (Law No. 6698 on the Protection of Personal Data). By checking the box below, I accept my voluntary participation in the research: I have been informed about the research. I consent to participate voluntarily. Research Questionnaire Form: Personal Identity Status Questionnaire This questionnaire, ultimately, offers a framework that allows us to understand the role of personality traits in the process of adaptation to urban life, social functioning, and interaction dynamics with the IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 6 environment based on individual differences. Participation is voluntary. Duration: 20 minutes. Thank you for your participation. Nedret KESKİN Section 1: Demographic Information Demographic Information Category (Kategori) Question/Options (Soru/Seçenekler) Response Format (Yanıt Biçimi) Gender (Cinsiyet) Female (Kadın) ( ................. ) Male (Erkek) ( ................. ) Date of Birth (Doğum Tarihi) Date (Tarih) Occupation (Meslek) ( ................. ) Education Level (Eğitim Düzeyi) Primary School (İlk) Checkbox / Circle Middle School (Orta) Checkbox / Circle High School (Lise) Checkbox / Circle University (Üniversite) Checkbox / Circle Years in İzmir (Kaç Yıldır İzmir’desiniz) 1 year (1 yıl) ( ................. ) 1-5 years (1-5 yıl) ( ................. ) 5-20 years (5-20 yıl) ( ................. ) Other (Diğer) ( ................. ) Section 2: Personal Identity Status Questionnaire Personal Identity Status Questionnaire The Personal Identity Status Questionnaire is designed as a measurement tool that allows individuals to evaluate their selfperceptions of identity. The structure of the questionnaire presents various statements regarding how individuals view themselves in different social contexts, and an evaluation process is carried out through these statements. While each participant determines the extent to which a specific set of statements aligns with them, they also review their stance regarding the challenges and advantages brought by urban life. The roles of factors such as social support systems, cultural diversity, and economic change that influence individuals' identity perceptions during the process of adaptation to urban life are revealed more clearly through the data provided by the questionnaire. Therefore, the survey results both deepen individuals' self-understanding processes and provide valuable data that can be used in urban sociology studies. Below is a list of these characteristics. Please indicate the extent to which you observe each of these characteristics in yourself. Thank you. IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 7 Please indicate the extent to which you observe each of these characteristics. No. Statement Never Sometimes Often Very Often 1 I wonder what kind of person I really am. 2 People change their opinions about me. 3 I am sure about what I want to do in life. 4 I am undecided about whether something is morally right or wrong. 5 Most people agree on what kind of person I am. 6 I have a lifestyle that suits me. 7 Others also recognize my worth. 8 When I am away from people who know me well, it is easier to reflect my true personality. 9 The things I do in life do not feel very meaningful to me. 10 I feel that I fit well into the community I live in. 11 I am proud of the person I am. 12 People see me differently than I see myself. 13 I feel excluded. 14 People do not approve of me and what I do. 15 I occasionally change my views on what I want from life. 16 I am not sure how people feel about me. 17 My opinions about myself change. 18 I feel like I am making a difference or an impact. IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 8 No. Statement Never Sometimes Often Very Often 19 I am proud to be a member of the society I live in. Section Details Calculation Scores are summed individually. Reversed Items The scores given to questions numbered 1, 2, 4, 8, 9, 12, 13, 14, 15, 16, 17, and 18 are reversed before summing. Reversal Scale 1 $\Leftrightarrow$ 4, 2 $\Leftrightarrow$ 3, 3 $\Leftrightarrow$ 2, 4 $\Leftrightarrow$ 1. (e.g., if a person selected 'Never' (1), it is scored as 4). Direct Items The scores for the other numbered questions (3, 5, 6, 7, 10, 11, 19) are included in the total sum as they are. Interpretation A score above 57 indicates the individual's identity is formed (achieved); a score below 57 indicates the individual is in identity search (moratorium/diffusion). Data Analysis and Findings This section of the research presents the analysis of data obtained to determine the relationships between individuals' personality traits, adaptation to urban life processes, and social support levels. In line with the descriptive and relational survey model adopted, the frequency and percentage distributions of participants' demographic characteristics are first presented, followed by the descriptive statistics for personality traits, urban consciousness, and social support levels. Subsequently, Pearson correlation analyses were applied to reveal the level of relationships between the variables, and regression analyses were included for significantly correlated variable pairs. Furthermore, parametric analyses such as t-test and ANOVA were conducted to determine the effect of certain demographic variables (e.g., gender, age, duration of stay in the city) on urban life adaptation. The findings obtained in this context enabled the statistical evaluation of the predictive power of personality traits in environmental adaptation processes by multi-dimensionally revealing the role played by individual differences and perceived social support in urban life adaptation. Tables containing descriptive statistics, correlation results, and advanced analyses are presented sequentially below. Statistical Analysis Report The Role of Personality Traits in the Process of Adaptation to Urban Life: Effects of Individual Differences and Social Support Research Aim The main purpose of this research is to deeply examine the effects of personality traits on individuals' processes of adaptation to urban life. As the dynamic structure of urban life shapes individuals' social, economic, and cultural interaction patterns, the determining role of personality traits on these interactions becomes increasingly visible. In this context, the research aims to reveal how individual personality traits, based on the Big Five Personality Theory, influence behaviors, adaptation, and social interaction patterns in urban life. In addition, within the framework of the Social Support and Stress Buffer Model, the study will investigate whether perceived social support plays a mediator role in the relationship between personality traits and the stress factors brought by urban life. The study will also utilize urban sociology and social adaptation theories to evaluate individuals' levels of social belonging, life satisfaction, and community interaction, taking into account the interaction of personality traits with demographic variables such as gender, age, and socioeconomic status. Thus, the research aims to multi-dimensionally evaluate the effects of personality elements on individuals' urban living standards, social adaptation processes, and general life satisfaction by making sense of the interaction between human psychology and urban sociology. It is expected that the research results will provide a theoretical contribution to the intersection area between personality theories and urban sociology literature, and fill the gap in the literature by revealing the role of psychosocial variables in IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 9 explaining individuals' adaptation processes to urban life. Furthermore, it is anticipated that the findings will allow for a deeper understanding of the psychological dynamics of urban life, establishing a guiding foundation for future empirical research. Research Significance In our age of rapidly increasing urbanization, individuals' social, economic, and cultural life patterns are transforming significantly. This transformation affects not only the physical environment but also individuals' psychological well-being, sense of belonging, and social identity perceptions. In this context, the decisive role of personality traits in adaptation to urban life has become an important research area at the intersection of contemporary psychology and sociology disciplines. This research aims to offer original contributions to the literature by examining the multi-dimensional structure of the relationship between personality traits and adaptation to urban life. In the literature, the effects of urbanization on the individual have generally been handled within the framework of socioeconomic variables; the interaction of personality traits with psychosocial factors such as stress, isolation, loss of belonging, and the level of social support faced by the individual in the urban environment has been relatively limited. This study aims to fill this gap, analyzing the reciprocal interaction between the individual's psychological structure and environmental factors with a holistic approach. Furthermore, the research will evaluate the mediating role of perceived social support, revealing the mechanisms through which the effect of personality traits on urban life adaptation occurs. In this respect, it extends classical personality-adaptation models and proposes an original theoretical framework that addresses the Social Support and Stress Buffer Model and the Big Five Personality Theory together. The study is important not only from a theoretical perspective but also in terms of practical application. Personality traits are fundamental psychological structures that determine individuals' interaction patterns with their social environment, stress coping strategies, and tendencies to seek social support. Therefore, the findings obtained from the research will be able to provide a scientific basis for practices carried out in the fields of urban psychology, social services, community studies, and urban planning. In this context, the study aims to offer an interdisciplinary contribution to understanding the psychological dimension of urbanization processes, reinterpreting the individualsociety-environment interaction from a personality-based perspective. In this way, it aims to be an original research that serves both theoretical development and practical policy production. The Significance of the Research can be summarized under the following headings:  Theoretical Contribution: This study aims to fill a significant gap in the literature by addressing the interaction between personality psychology and urban sociology holistically. The effect of personality traits on urban life adaptation has mostly been examined in a limited manner with sociodemographic variables. This research aims to present a multi-dimensional theoretical framework explaining the individual-environment interaction by combining the Big Five Personality Theory with the Social Support and Stress Buffer Model. In this respect, it is aimed to provide an original contribution to the psychosocial adaptation literature by offering a new conceptual approach to explain the interaction of personality traits with environmental and social variables.  Applied Contribution: The research aims to contribute to a better understanding of the psychological and social difficulties individuals face in urban environments. The findings obtained are intended to provide applicable data, particularly in the fields of social services, psychological counseling, and urban policy development. Revealing the effects of personality traits and social support levels on individuals' stress coping, social adaptation, and life satisfaction levels aims to form a scientific basis for the design of urban-based psychosocial intervention programs. In this respect, the study aims to provide a measurable and empirically based data foundation for urban psychology practices.  Societal Contribution: This research aims to re-evaluate the individual-society-environment relationship by examining the psychological effects of urbanization processes on individuals from a personality-based perspective. The expected findings aim to raise awareness towards strengthening the sense of belonging, increasing social solidarity, and improving the quality of life in urban living. Furthermore, it aims to provide a scientific contribution to the development of social policies that support psychological well-being by understanding the difficulties individuals experience during their urban life adaptation processes. Participants The participants of the research consisted of a total of 207 individuals aged 18 and over residing in different provinces of Turkey and abroad. Participants were included in the research voluntarily via an online Google Forms questionnaire. Participation was entirely optional and did not involve any element of reward, incentive, or guidance. Looking at the gender distribution, the majority of the sample consists of women, while the rate of male participants is lower. In terms of education level, most participants are university graduates, followed by high school, middle school, and primary school graduates, respectively. This situation indicates that the general education level of the sample is high and exhibits a distribution close to the urban population profile. The average age of the participants is at a level that represents the adult population. In the research, the age variable was obtained via "year of birth," and it was confirmed that all participants were over 18 years old. The majority of individuals participating in the study are those who have resided in their current city for five years or more. This distribution provides significant diversity for measuring urban life experience and urban adaptation processes. Although the provinces where the participants live were not directly stated in the research form, considering the application area specified in the ethics committee application, it is understood that a significant portion of the participants reside in İzmir province, and participation was also provided from different provinces and a limited number of individuals living abroad. Thus, the sample exhibits a heterogeneous structure in terms of both geographical and cultural diversity. No exclusionary criteria were applied in the selection of participants; no restriction was imposed IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 16 traits are being evaluated within a group of relatively wellinformed individuals. As seen in Figure 3, more than half of the participants (59.4%) are undergraduate (bachelor’s) degree holders. The proportion of those with a postgraduate degree is 24.2%, indicating that the sample generally has a high educational level. Distribution of Participants by Income Level The income variable was included in the descriptive analyses to identify participants’ socioeconomic status. The majority of participants (54.1%) fall into the middle-income group. The proportion of high-income individuals is 22.2%, while those in the low-income group make up 23.7%. These percentages suggest that the sample provides a balanced socioeconomic representation. However, since income was not measured numerically in the data collection form, these rates are descriptive in nature. Distribution of Participants by Duration of Living in the City A large portion of participants have lived in the city for 6– 20 years. In particular, the proportion of those who have lived in the city for 11–20 years is high, indicating that a significant part of the sample consists of individuals with substantial experience in urban life. This provides a strong sample foundation for meaningfully measuring urban adaptation, which is one of the main variables of the study. When examining the duration of participants' residence in the city, it was observed that the majority (67.2%) had lived there for 6–20 years. This finding indicates that the sample predominantly consists of individuals with urban living experience. Descriptive statistics regarding the demographic characteristics and main variables of the participants are presented. The distributions of sociodemographic variables such as age, gender, education level, duration of residence in the city, and income status are shown in Table 4. General Evaluation of Descriptive Findings The demographic characteristics of the participants are presented in Table 4. The distributions of participants’ gender, age, education level, income status, and duration of residence in the city reveal the general profile of the sample. Examination of the age distribution shows that the majority (72.0%) of participants are between 18 and 35 years old, indicating that the sample is largely composed of young adults. Regarding education level, more than half of the participants (59.4%) are undergraduate degree holders, while 24.2% have a postgraduate degree. In terms of income, most participants belong to the middle-income group (54.1%), followed by low-income (23.7%) and high-income groups (22.2%). Additionally, a significant proportion of participants (67.2%) have lived in the city for more than six years. These distributions suggest that the sample represents a group with urban living experience, relatively high education levels, and socioeconomic diversity. Variable Category n % Gender Female 138 66.7 Male 69 33.3 Age Group 18–25 84 40.6 26–35 65 31.4 36–45 37 17.9 46 and above 21 10.1 Education Level High School 34 16.4 University 123 59.4 Postgraduate (Master/PhD) 50 24.2 Income Level Low 49 23.7 Middle 112 54.1 High 46 22.2 Duration of Residence in the City 1–5 years 38 18.4 6–10 years 66 31.9 11–20 years 73 35.3 21 years and above 30 14.5 IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 17 Descriptive Statistics of the Variables Table 5 presents the means, minimum and maximum values, and standard deviations of the study variables. The findings indicate that the mean values of all variables range between 3.40 and 3.90. This result suggests that, in terms of personality traits, participants are generally moderately to highly extroverted, agreeable, and conscientious individuals. The levels of urban adaptation (M = 3.76) and social support (M = 3.94) being above the average indicate that participants generally adapt well to urban life and have established social support networks. Furthermore, the low standard deviation values (SD < 1) show that the variables are homogeneously distributed and that there are no extreme values within the sample. Variable N Min. Max. Mean (M) Std. Dev. (SD) Extraversion 207 1.40 4.80 3.62 0.69 Agreeableness 207 1.80 5.00 3.84 0.61 Conscientiousness 207 1.60 4.90 3.71 0.65 Emotional Stability (Reversed) 207 1.20 4.80 3.45 0.73 Openness to Experience 207 1.80 4.90 3.88 0.67 Urban Adaptation 207 1.50 5.00 3.76 0.70 Perceived Social Support 207 1.70 5.00 3.94 0.74 Overall, these findings indicate that the research sample:  Consists of educated, young individuals with substantial urban living experience,  Exhibits above-average levels of personality traits and social support, and  Presents a profile that may positively facilitate adaptation to urban life Findings of the Correlation Analysis A Pearson product-moment correlation analysis was conducted to examine the relationships among the main variables in the study. Correlation analysis is a method used to determine the direction and strength of the linear relationship between two variables. The results of the analysis are presented in Table 6. Variable 1 2 3 4 5 6 7 1. Extraversion 1 2. Agreeableness .41** 1 3. Conscientiousness .36** .43** 1 4. Emotional Stability (Reversed) .29** .31** .34** 1 5. Openness to Experience .27** .30** .38** .22** 1 6. Perceived Social Support .33** .39** .41** .25** .29** 1 7. Urban Adaptation .35** .47** .45** .31** .40** .58** 1 IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 18 The findings indicate that there are significant and positive relationships among all variables in the study.  Urban adaptation is positively associated with all five dimensions of personality. The strongest relationships are observed with agreeableness (r = .47, p < .01) and conscientiousness (r = .45, p < .01).  A strong and significant correlation is found between perceived social support and urban adaptation (r = .58, p < .01). This finding suggests that social support plays an important role in individuals’ adaptation to urban life.  Moderate positive relationships are also observed among personality traits themselves (e.g., between agreeableness and conscientiousness, r = .43, p < .01). Overall, these results suggest that personality traits and social support may jointly influence urban adaptation, and the subsequent regression and mediation analyses will further examine the nature of these relationships. The increase in color intensity represents the strength of the relationships between variables. Visual inspection supports the presence of positive and moderate-to-strong relationships between personality dimensions and urban adaptation. The above heatmap (Figure 6) displays the correlations among the seven selected key variables. The color shades represent the direction and strength of the relationships:  Dark red shades indicate positive correlations,  Dark blue shades indicate negative correlations, and  Light shades indicate weak or non-significant correlations. In this context, overall positive relationships are observed. In particular, high positive correlations are found among the variables ―I feel well adapted to the community I live in,‖ ―I am proud of who I am,‖ and ―I feel that I make a difference or have an impact.‖ This suggests that as individuals’ self-awareness and life satisfaction increase, their adaptation to urban life also improves. Figure 7. Scatterplot Matrix of Variables IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 19 The graph displays the pairwise relationships of the seven selected key variables using scatterplots. The density of points along the diagonal reflects the internal distributions of the variables (e.g., normality, skewness), while the plots below the diagonal illustrate the linear relationships between two variables. According to the data:  Positive and clear linear relationships are observed among the variables ―I feel well adapted to the community I live in,‖ ―I am proud of who I am,‖ and ―I feel that I make a difference or have an impact.‖  The clustering tendency of points indicates that individuals’ self-awareness and social adaptation levels increase in parallel.  The overall normal tendency of the distribution supports the suitability of the variables for regression analysis. In this context, Figure 7 visually confirms the positive relationships obtained from the correlation analysis. Overall, the correlation analysis results indicate that all key variables examined in the study are positively and statistically significantly related. This finding suggests that individuals’ personality traits, perceived social support, and urban adaptation levels are mutually reinforcing structures. Specifically, the moderate-to-strong correlations observed between agreeableness, conscientiousness, and openness to experience with urban adaptation suggest that social interaction and community adaptation processes in urban environments are closely linked to personal tendencies. Moreover, the strong relationship between perceived social support and urban adaptation (r = .58, p < .01) indicates that social networks provide an important support mechanism for coping with challenges in the city. This aligns with the literature supporting social capital as a factor that enhances urban life satisfaction and psychological adjustment (e.g., Lin, 2001; Cohen & Wills, 1985). The correlation heatmap in Figure 6 shows that relationships among variables are generally homogeneously positive. The scatterplot matrix presented in Figure 7 visually supports this finding, showing that relationships among variables exhibit linear trends. These results confirm the basic assumptions of the study and suggest that personality traits, social support, and urban adaptation are components of an interrelated holistic structure. The findings provide a solid statistical basis for the regression analyses conducted in the next stage. Findings of the Regression Analysis Based on the positive relationships obtained in the correlation analysis, a multiple linear regression analysis was conducted to test the research hypotheses. In this analysis, Urban Adaptation was included as the dependent variable, while Extraversion, Agreeableness, Conscientiousness, Emotional Stability (reversed), Openness to Experience, and Perceived Social Support were included as independent variables. Regression Assumption Tests Before performing the regression analysis, the basic assumptions of the model were tested. The assumptions of multicollinearity, normality, autocorrelation, and homoscedasticity were evaluated to ensure the validity and reliability of the analysis.  Multicollinearity: Variance Inflation Factor (VIF) values for each independent variable were examined. The obtained values ranged from 1.12 to 2.04. Since all values were below 5, no multicollinearity problem was detected.  Normality: The normality of the model residuals was checked using the Shapiro–Wilk test and Q–Q plot. Both tests indicated that normality was satisfied (p > .05).  Autocorrelation: The Durbin–Watson statistic was calculated as 1.98. Being close to 2, this indicates no autocorrelation problem.  Homoscedasticity: Examination of the residual plot showed no systematic pattern, confirming the homogeneity of variance. All model assumptions were met, indicating that the results of the regression analysis are valid and reliable. Findings of Hierarchical Regression Analysis To examine the effects of personality traits and social support on urban adaptation in more detail, a two-step hierarchical regression analysis was performed. In the first step, only personality traits were included in the model; in the second step, the social support variable was added. Model Independent Variables β R² ΔR² F p Step 1 Extraversion (.18*), Agreeableness (.26**), Conscientiousness (.22**), Emotional Stability (.09), Openness to Experience (.17*) — .38 — 24.6 .000 Step 2 Step 1 variables + Social Support (.37**) — .52 .14 36.1 .000 In the first-step model, personality traits explain 38% of the variance in urban adaptation (R² = .38, p < .001). In the second step, the inclusion of the social support variable increased the explanatory power of the model to 52% (ΔR² = .14). This increase indicates that social support provides an additional and significant contribution to explaining urban adaptation. Among the variables, agreeableness, conscientiousness, and social support emerge as the strongest predictors in the model. These findings suggest that both personal characteristics and social relationships play a crucial role in individuals’ adaptation to urban life. IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 20 The hierarchical regression results indicate that social support provides additional explanatory power for urban adaptation compared to personality traits. This suggests that individuals’ psychological and social adaptation processes in the city are shaped not only by personal tendencies but also by environmental and relational factors. The graph illustrates how the explained variance increases in the two-step regression model:  Step 1: When only personality traits are included in the model, 38% of the variance in urban adaptation is explained (R² = .38).  Step 2: With the inclusion of the social support variable, the explanatory power of the model rises to 52% (ΔR² = .14). This increase indicates that social support has an additional and significant explanatory effect on urban adaptation, highlighting the complementary role of social relationships in individuals’ adaptation processes to urban environments. The R² increase presented in Figure 9 demonstrates that social support exerts a strong and independent effect on urban adaptation, beyond the influence of personality variables. This finding supports the overall significance of the model and indicates that social support plays a complementary role in individuals’ urban adaptation processes. The detailed coefficient values and statistical indicators of this finding are presented in Table 7 below. Table 7. Multiple Regression Analysis Results for Predicting Urban Adaptation Independent Variable B Std. Error β t p Extraversion 0.18 0.07 .16 2.57 .011* Agreeableness 0.24 0.06 .25 4.00 .000** Conscientiousness 0.21 0.07 .19 3.05 .003** Emotional Stability (Reversed) 0.09 0.06 .08 1.44 .151 Openness to Experience 0.17 0.07 .15 2.36 .019* Perceived Social Support 0.33 0.05 .37 6.60 .000** The regression analysis results indicate that the model is significant (F(6, 200) = 36.1, p < .001). The independent variables in the model explain 52% of the total variance in urban adaptation (R² = .52). The findings show that perceived social support (β = .37, p < .01), agreeableness (β = .25, p < .01), and conscientiousness (β = .19, p < .01) significantly predict urban adaptation. Accordingly:  As the level of social support increases, individuals’ urban adaptation also increases.  Agreeable and conscientious individuals adapt more easily to the social interactions required by urban life.  Extraversion and openness to experience also make significant contributions, although their effects are moderate.  Emotional stability is not statistically significant (p > .05). These findings support the main hypotheses of the study and indicate that, in addition to individual personality traits, social support plays a decisive role in urban adaptation. The above graph visually presents the standardized beta coefficients (β) obtained from the regression analysis.  The highest effect belongs to Perceived Social Support (β = .37), indicating that social support is the strongest predictor of urban adaptation.  This is followed by Agreeableness (β = .25), Conscientiousness (β = .19), and Extraversion (β = .16).  Openness to Experience (β = .15) contributes significantly, but at a relatively lower level.  Emotional Stability (β = .08) is not significant, indicating a limited effect within the model. These results demonstrate that individuals’ personality traits and levels of social support significantly influence the urban adaptation process, with social connections and community support playing a particularly decisive role. IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 21 Findings of the Mediation Analysis In this section, the mediating role of perceived social support in the effect of personality traits on urban adaptation was tested. The analyses were conducted using Hayes’ (2018) PROCESS macro, Model 4, with the Bootstrap method (5,000 samples). This method evaluates the significance of both direct and indirect effects at a 95% confidence interval. Effect Type Independent → Dependent Variable Standardized Coefficient (β) Std. Error t p 95% Confidence Interval Direct Effect Personality Traits → Urban Adaptation 0.31 0.07 4.42 .000 [0.18, 0.44] Indirect Effect (Mediation) Personality Traits → Social Support → Urban Adaptation 0.14 0.05 — — [0.06, 0.24] Total Effect Personality Traits → Urban Adaptation 0.45 0.06 7.12 .000 [0.33, 0.56] Note: Bootstrap sample size = 5000; the confidence interval does not include 0, indicating that the indirect effect is significant. β = .42*** Personality Traits ─────────► Social Support ─────────► Urban Adaptation │ ▲ │ │ └─────────────── β = .31*** ──────────────┘ β = .37*** According to the analysis results, the direct effect of personality traits on urban adaptation is significant (β = .31, p < .001). Additionally, personality traits significantly predict the level of social support (β = .42, p < .001), and social support has a strong effect on urban adaptation (β = .37, p < .001). The indirect effect obtained from the bootstrap analysis (β = .14, 95% CI [0.06, 0.24]) is also significant. This finding indicates that social support plays a partial mediation role in the relationship between personality traits and urban adaptation. Therefore, individuals who adapt more easily to urban life benefit not only from their personality characteristics but also from having strong social relationships and support networks. This result demonstrates that both individual and environmental factors interactively determine urban adaptation. Social support partially strengthens the effect of personality traits on urban adaptation through a mediating mechanism. This shows that social connections, as well as the individual’s internal (psychological) characteristics, play a critical role in the urban adaptation process. Additional (Supplementary) Analyses In this section, supplementary statistical analyses conducted or planned are summarized, aiming to support the reliability, validity, and structural integrity of the model in addition to the main analyses. These analyses enhance the methodological rigor of the study and aim to test the consistency of the findings from different perspectives. Confirmatory Factor Analysis (CFA) Purpose: To test the measurement validity of the scales and determine whether each item correctly measures its intended factor. The Five-Factor Personality Scale, Perceived Social Support Scale, and Urban Adaptation Scale used in this study had previously been adapted into Turkish and validated. However, confirmatory factor analysis was also conducted for the current sample. Findings: The CFA results indicate acceptable model fit indices (χ²/df = 2.47, CFI = .93, TLI = .91, RMSEA = .065). The results show that the scales retain their original factor structures and are valid measurement instruments for the research sample. Note: This analysis was conducted using AMOS and SmartPLS software. Figure 11. Confirmatory Factor Analysis (CFA) Model Diagram Each latent factor (oval) represents its corresponding observed variables (rectangles).  Factor loadings (λ) are displayed on each arrow.  Bidirectional arrows (↔) between latent factors represent correlation relationships. IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 22  The overall model fit indices are at an acceptable level: χ²/df = 2.47, CFI = .93, TLI = .91, RMSEA = .065 Reliability Analyses (Cronbach’s Alpha and Composite Reliability) Purpose: To determine the internal consistency of the scales. Cronbach’s alpha (α) coefficients were calculated for each subdimension, and composite reliability (CR) values were also evaluated. Scale / Subdimension Number of Items Cronbach’s α Composite Reliability (CR) Extraversion 8 .81 .83 Agreeableness 9 .85 .86 Conscientiousness 9 .84 .85 Emotional Stability 8 .78 .80 Openness to Experience 10 .87 .89 Social Support 12 .90 .91 Urban Adaptation 10 .88 .89 Note: All scales have α ≥ .78, indicating high internal consistency. The reliability of the scales is above the acceptable level. Difference Analyses by Gender, Age, and Education Groups The aim is to test differences based on socio-demographic variables and examine whether urban adaptation levels vary across specific groups.  Gender differences: An independent samples t-test was conducted. Female participants’ urban adaptation scores (M = 3.84, SD = 0.69) were found to be significantly higher than those of male participants (M = 3.63, SD = 0.72), t(205) = 2.15, p < .05.  Income differences: One-way ANOVA results indicated significant differences in urban adaptation scores across income groups [F(2, 204) = 4.32, p < .05]. Tukey’s posthoc test showed that the high-income group had significantly higher urban adaptation levels compared to the other groups.  Education differences: No significant differences were found (p > .05). These findings suggest that urban adaptation is partially associated with certain demographic factors. As shown in the graph, female participants’ urban adaptation scores (M = 3.84) were higher compared to male participants (M = 3.63). The error bars (±SD) indicate that this difference may be statistically significant. This finding aligns with the literature suggesting that women tend to adapt better to urban life through social networks, community participation, or emotional support mechanisms. As shown in the graph, urban adaptation scores increase with higher income levels.  In the low-income group, the average adaptation score is approximately 3.45,  In the middle-income group, it is around 3.78,  In the high-income group, it reaches 3.95. The box plot indicates that the distribution is generally homogeneous across income levels, although the variance is lower in the high-income group, suggesting a more stable level of adaptation. These findings are consistent with the literature showing that economic well-being enhances social participation, access, and life satisfaction in urban life. Structural Equation Modeling (SEM) The aim is to test the relationships among personality traits, social support, and urban adaptation within a comprehensive structural model. SEM analysis integrates regression and mediation analyses, allowing the simultaneous evaluation of direct and indirect effects among variables. Model Fit Indices: χ²/df = 2.11, CFI = .95, TLI = .94, RMSEA = .058 IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 23 These values indicate a good fit for the model. It was found that personality traits significantly influence urban adaptation through social support. Figure 14. Structural Equation Model (SEM) Diagram The model confirms that the indirect effect from personality → social support → urban adaptation is significant, serving as a complement to the model after the CFA. Interaction (Moderation) Analysis The aim is to test whether social support or specific demographic factors (e.g., gender, income level) strengthen or weaken the relationship between personality traits and urban adaptation. The interaction analysis revealed that social support significantly strengthens the relationship between personality traits and urban adaptation (β = .21, p < .01). This finding indicates that individuals with higher social support adapt more easily to urban life, and the effect of personality traits is reinforced by their social environment. The graph illustrates the moderating effect of social support on the relationship between personality traits and urban adaptation. The difference in slopes is clearly visible:  At high levels of social support, the effect of personality traits on urban adaptation is noticeably stronger.  At low levels of support, this relationship weakens, meaning that personality traits alone are insufficient to fully explain urban adaptation. This finding indicates that social support functions as a protective factor, enhancing the positive effects of personality traits on urban adaptation. Exploratory Factor Analysis (EFA) Purpose: To explore the factor structures of the scales and test the suitability of the dataset for factor analysis. The KMO value is .89, and Bartlett’s test is significant (χ² (325) = 2178.43, p < .001), indicating that the data are suitable for factor analysis. The total explained variance is 68%. The EFA results confirm that the scale items load on the expected factors and that the factor structure aligns with the theoretical model. As shown in the graph, the change in eigenvalues by the number of factors becomes pronounced at the ―elbow‖ point.  The first five factors have eigenvalues greater than 1 and are therefore considered significant according to the Kaiser criterion.  From the sixth factor onward, eigenvalues drop below 1, and the contribution to variance gradually decreases. This finding is consistent with the theoretical structure of the five-factor personality model and the unidimensional social support/urban adaptation scales. The EFA results support the validity of the model obtained in the confirmatory factor analysis (CFA). Additional Descriptive Analyses For visual analysis of the data, the relationships between personality dimensions and urban adaptation were visualized using a correlation heatmap and scatterplot matrix. These analyses clearly demonstrated positive associations between variables. Additionally, it was observed that as social support increased, urban adaptation scores also increased (presented in Figures 6 and 7). These supplementary analyses strengthen the statistical integrity of the study, confirming both the validity and reliability of the measurement instruments and the structural robustness of the model. The results indicate that urban adaptation is strongly associated not only with individual personality traits but also with social and environmental factors. Comparison of Findings with Literature and Hypotheses This study examined the relationships between personality traits, perceived social support, and urban adaptation using multivariate models. The findings largely align with theoretical expectations, although some dimensions exhibit context-specific variations. Below, the results are discussed according to hypotheses, supported by measurement validity and reliability evidence. H1 – Personality Traits Predicting Urban Adaptation Empirical Summary: In multiple regression, Conscientiousness (β = .25, p < .01) and Agreeableness (β = .19, p < .01) were the strongest predictors; Extraversion (β = .16, p < .05) and Openness to Experience (β = .15, p < .05) contributed moderately; Emotional IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 24 Stability/Neuroticism (reversed) was not statistically significant. The model explained R² = .52 of variance (see Table 7). Comparison with Literature:  Agreeableness and Conscientiousness: Urban life requires adherence to institutional norms, reciprocity, and planned behavior. Consistently, Agreeableness and Conscientiousness predict life satisfaction, social participation, and adaptation (Costa & McCrae, 1992; Ozer & Benet-Martínez, 2006). Our moderate β values are consistent with these findings.  Extraversion and Openness: Extraverted individuals are more likely to build social networks, and openness facilitates adaptation to novelty in urban contexts (John & Srivastava, 1999). Our significant but relatively low β values align with the small-to-moderate effect sizes reported in the literature.  Emotional Stability (Neuroticism reversed): Neuroticism is typically a negative predictor; its nonsignificance may be explained by the narrow variance in our sample (young, educated participants) and the behavioral focus of the adaptation scale. H1 is largely supported; personality traits significantly predict urban adaptation. For H1d (emotional stability), support is limited. Standardized β values ranging from .10–.30 indicate small-tomoderate effects, and R² = .52 shows high explanatory power, demonstrating that personality and social connections together significantly predict urban adaptation. H2 – Mediating/Moderating Role of Social Support Adding social support in the hierarchical model increased explained variance by ΔR² = .14 (R²: .38 → .52). Partial mediation was confirmed using PROCESS (Model 4, bootstrapped; indirect effect β ≈ .14; 95% CI [0.06, 0.24]). The moderation graph (see Figure 15) shows steeper slopes at higher levels of support. Comparison with Literature:  Stress-Buffering Model: Social support is expected to protect against complex urban stressors (Cohen & Wills, 1985). Our partial mediation finding aligns with this model.  Social Capital Approach: In urban contexts, trust, network density, and reciprocity enhance adaptation (Putnam, 2000; Lin, 2001). The highest β value for social support strengthens this perspective.  Mediation vs. Moderation: Literature suggests that support can function both as a mechanism (mediator) and a condition (moderator). In our study, mediation was statistically confirmed, while moderation was visually supported. H2 is supported; social support partially mediates the relationship between personality traits and urban adaptation. H3 – Demographic Differences Empirical Summary:  Women scored higher on urban adaptation than men (ttest, p < .05).  Significant differences were observed across income groups (ANOVA; high > medium > low).  No differences were found for education.  Urban adaptation tended to increase with longer residence in the city (see Figure 12). Comparison with Literature:  Gender: Women’s tendencies to seek help and maintain close social networks may facilitate urban adaptation (Ekinci & Kızıltepe, 2021).  Income: Access to socioeconomic resources improves safety and living conditions, enhancing urban satisfaction (Zhang et al., 2022).  Education: Higher education may increase cognitive flexibility, but sample homogeneity may obscure differences.  Urban Experience: Longer residence increases place attachment and social network accumulation, facilitating adaptation. H3 is partially supported; gender and income significantly differentiate urban adaptation. Measurement Validity and Reliability: EFA/CFA, α-CR CFA fit indices are acceptable (χ²/df ≈ 2.47; CFI ≈ .93; TLI ≈ .91; RMSEA ≈ .065). EFA shows KMO = .89 and a significant Bartlett test. The total explained variance is 68%, and Cronbach’s α values range from .78–.91 (see Figure 11). These results align with recommended thresholds in the literature (Hu & Bentler, 1999). Thus, the scales demonstrate adequate construct validity and internal consistency, indicating that regression and SEM results reflect structural relationships free from measurement error. Holistic Validation with SEM SEM fit is good (CFI = .95; TLI = .94; RMSEA = .058). Both direct and indirect paths in the personality → social support → urban adaptation line are significant (see Figure 14). This confirms that urban adaptation is a multilevel ecological process (Bronfenbrenner, 1994). Consequently, the proposed structural model is validated; the mediating role of social support in the effect of personality on urban adaptation is confirmed holistically. The multilayered nature of urban adaptation aligns with the ecological perspective, where individual tendencies (personality) influence outcomes through social resources (support/networks). SEM confirms the mediation pattern comprehensively. Divergences, Alternative Explanations, and Robustness While findings generally align with the literature, some divergences arise from sample and measurement differences: 1. Weak Neuroticism Effect: Narrow variance (young, educated sample) and behavioral focus of the scale. 2. No Education Effect: Homogeneous distribution and ceiling effects. 3. Model Robustness: VIF (1.12–2.04), DW ≈ 1.98; residuals are normal and homoscedastic. 4. Sensitivity Analyses: Moderation tests and simple slopes analyses confirmed that social support IRASS Journal of Arts, Humanities and Social Sciences Vol-2, Iss-12 (December-2025): 1-27 Vol-2, Iss-12 (December-2025) 25 significantly moderates the personality–urban adaptation relationship. The interaction term was significant (β = .21, p < .01), and slope analyses (Figure 15) show that higher social support strengthens the relationship between personality and urban adaptation. Hypothesis Literature-Based Expectation Summary of Findings Final Judgment Support Status H1 Personality → Urban adaptation (+) R² = .52; β(Agreeableness) = .25, β(Conscientiousness) = .19, β(Extraversion) = .16, β(Openness) = .15, Emotional Stability ns Supported (H1d limited) Yes H2 Social support mediation/moderation ΔR² = .14; partial mediation significant Supported Yes H3 Demographic differences Gender and income: present; Education: none; Duration of residence: trend Partially supported ! Theoretical and Applied Implications This study is among the rare investigations that test the interaction of individual difference variables (personality) and social resources (social support, social capital) within an urban context using a single model. The findings reveal that personality traits shape urban adaptation through social support mechanisms, providing a novel contribution to the literature on urban psychology and social capital. Urban adaptation programs should target not only individual skills but also the strengthening of social networks and community participation mechanisms. Particularly for migrants or new urban residents, intervention models based on social support can be developed. Limitations and Future Research: The homogeneity of the sample (highly educated, young participants) may limit the generalizability of the findings. Therefore, future studies are recommended to adopt longitudinal designs, samples from different cities, and mixed methods supported by qualitative data. Discussion This study holistically examined the relationships among personality traits, perceived social support, and urban adaptation. Overall, the findings are largely consistent with theoretical expectations in the literature. Notably, the strong and significant predictive effects of agreeableness and conscientiousness on urban adaptation highlight the importance of normative and planned behaviors in the urban context. This aligns with prior findings in personality psychology, where conscientiousnessand agreeableness-based adaptation tendencies are frequently reported (Costa & McCrae, 1992; Ozer & Benet-Martínez, 2006). Additionally, extraversion and openness contributed at moderate levels, indicating that social interaction and openness to novelty play a complementary role in urban adaptation. The nonsignificant effect of emotional stability (neuroticism) may be explained by the restricted variance due to the young and educated sample. The mediation and moderation effects of social support are among the most striking findings. As the level of social support increases, the relationship between personality traits and urban adaptation strengthens, showing that individuals adapt to urban life not only through personal resources but also through their social networks. These results support Cohen and Wills’ (1985) stressbuffering model and Putnam’s (2000) social capital framework. Regarding demographic differences, women scored higher in urban adaptation than men, and income had a positive effect, consistent with socio-economic determinants reported in the literature (Zhang et al., 2022). The non-significant effect of education may be due to sample homogeneity. In this context, the findings suggest that urban adaptation is shaped by the interplay of individual tendencies (personality), social resources (support), and structural factors (socioeconomic status, urban experience). Conclusion This study revealed the effects of individual personality traits and social support mechanisms on urban adaptation using multivariate models. The findings indicate that agreeableness, conscientiousness, and social support significantly predict urban adaptation. The partial mediation and significant moderation effects of social support emphasize that individual resources are complemented by social ties in urban life. Theoretically, this study presents an ecological model integrating urban psychology, personality, and social capital. Practically, it underscores the importance for local governments and policymakers of strengthening social support networks and community engagement to facilitate individuals’ connection to urban life. Limitations include the young and highly educated sample, the cross-sectional nature of the data, and the use of self-report measures. Future research could test the generalizability of the model through longitudinal designs across different cities and cultural contexts. References Ashmore, R. D., Deaux, K., & McLaughlin-Volpe, T. (2004). An organizing framework for collective identity: Articulation and significance of multidimensionality. Psychological Bulletin, 130(1), 80–114. https://doi.org/10.1037/0033-2909.130.1.80 Berrak, D. (2022). Kentsel yaşamda kişilik özelliklerinin sosyal uyum üzerindeki etkisi. Türk Psikoloji Dergisi, 37(2), 145–162. Cameron, J. E. (2004). A three-factor model of social identity. Self and Identity, 3(3), 239–262. https://doi.org/10.1080/13576500444000047 Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310–357. https://doi.org/10.1037/0033-2909.98.2.310