atys Turismo y Sociedad Rev. turis.soc 2346-206X 0120-7555 Universidad Externado de Colombia 10.18601/01207555.n36.02 00002 Research articles EVALUATION OF FACTORS HINDERING PARTICIPATION IN LEISURE AND RECREATIONAL ACTIVITIES IN TOURISM DESTINATIONS EVALUACIÓN DE LOS FACTORES QUE DIFICULTAN LA PARTICIPACIÓN EN ACTIVIDADES DE OCIO Y RECREATIVAS EN DESTINOS TURÍSTICOS Ünal Aydin * Doğan Yunus ** Çilesiz Emre *** Õrgün Emrah **** Doctor por la Facultad de Turismo Universidad de Balikesir, Sinop University. Turquía [aydin-unal@hotmail.com.tr] Universidad de Balikesir Facultad de Turismo Universidad de Balikesir Turquía aydin-unal@hotmail.com.tr Doctor por la Facultad de Turismo Universidad de Nevsehir Haci Bektas Veli, Universidad de Mersin. Turquía [yunus.dogan23@hotmail.co'm] Universidad de Nevsehir Haci Bektas Veli Facultad de Turismo Universidad de Nevsehir Haci Bektas Veli Turquía yunus.dogan23@hotmail.com Doctor por la Facultad de Turismo Universidad de Atatürk, Sinop University. Turquía [em recilesiz@gmail.com] Universidad de Atatürk Facultad de Turismo Universidad de Atatürk Turquía recilesiz@gmail.com Doctor por la Facultad de Turismo Universidad de Gazi, Sinop University. Turquía [eorgun@sinop.edu.tr] Universidad de Gazi Facultad de Turismo Universidad de Gazi Turquía eorgun@sinop.edu.tr Jan-Jun 2025 36 49 67 22 04 2024 27 06 2024 05 07 2024 This is an open-access article distributed under the terms of the Creative Commons Attribution License Abstract

The aim of this study is to determine the factors that hinder participation in leisure and recreational activities in tourist destinations. Within this framework, an attempt was made to reach out to the local residents living in the Sinop destination and determine their opinions through a prepared questionnaire. During the data collection process, a total of 431 questionnaires were collected using the convenience sampling method. The collected data were analyzed using appropriate statistical programs. As a result of the analysis, it was determined that the local residents consider time restraints, transportation problems, inadequacy of facilities, individual psychology, lack of companionship and lack of information as obstacles to their participation in leisure and recreational activities. It was found that the majority of local residents have 6-10 hours of leisure time per week, sometimes find it difficult to use their leisure time, and spend most of their leisure time participating in household activities and social events. The majority of the participants in the study consider the recreational facilities of the Sinop destination to be partially sufficient, use the recreational facilities of their destination for 1-5 hours per week, and spend most of their leisure time outside the destination. In addition, the results of the analysis were interpreted within the framework of theoretical and practical contributions, and some recommendations were made for the industry and future research.

 Keywords: Theory of Planned Behavior Tourism and Destination Leisure Recreation 1. Introduction

This study aims to determine and evaluate the factors hindering the participation of the local residents of Sinop destination in leisure and recreational activities, with the scientific framework of the Theory of Planned Behavior (TPB). Understanding the development process of individuals' travel and recreational motivation behaviors is crucial for researchers in the tourism field. In the context of holidays and leisure activities, it is essential to understand which motivational factors influence individuals' decisions, as well as how attitudes are formed and how the behavior of various reference groups affects them. Therefore, TPB provides insights into individuals' motivations regarding recreational activities in destinations (Hsu & Huang, 2012).

Literature reviews reveal that attitudes within the scope of planned action theory and planned behavior theories have been examined by various researchers in terms of revealing individuals' behaviors (Kil et al., 2014). In a study by Tarrant and Green (1999), it was mentioned that outdoor recreational activities affect individuals' behaviors through ecological attitudes. Another study by Berns and Simpson (2009) attempted to establish the relationship between demographic characteristics and ecological behavior in recreational activities. Kil et al. (2014) examined individuals' environmental-friendly behaviors to determine their recreational motivations. As a final example, Song et al. (2012) attempted to determine individuals' perceptions regarding exhibiting environmentally friendly behavior in decision-making situations in outdoor activities.

As evidenced by the studies mentioned above, the behavioral dimensions exhibited by individuals in recreational activities have been examined by various researchers. Therefore, it is deemed necessary, based on the literature reviews, to investigate the negative behaviors of individuals participating in recreational activities within the framework of the TPB model. Due to the TPB model's role in individuals' decision-making and the enactment of these decisions into behaviors, it is reached through the definitions made in the literature that this model plays a significant role. Therefore, the study has been planned and designed in line with the purpose of using the TPB model.

The sample of the research includes Sinop province, which is located in the Black Sea Region of Turkey and stands out with its historical, cultural, and natural beauties. In terms of tourism and recreational activities, Sinop province is one of Turkey's significant tourism attractions due to its historical richness, natural beauties, sea tourism, and cultural heritage. Additionally, in terms of recreation and outdoor sports, Sinop's natural areas provide suitable environments for activities such as trekking, mountain biking, and camping. With these features, Sinop ranks among the top 10 in terms of tourist arrivals in Turkey (Turkish Statistical Institute, 2023). The aim is to examine, within the framework of the TPB model, the reasons why individuals living in Sinop province do not participate in leisure activities they allocate for themselves in their lives. In this regard, a questionnaire tailored to the nature of the study was prepared and presented to individuals living in Sinop province, and the necessary data were collected. Subsequently, statistical analyses were conducted based on the obtained data to yield results.

 2. Theoretical Background

Conceptually, theories of human behavior serve as frameworks used to interpret the reasons behind individuals' actions based on the decisions they make. Models and theories developed to elucidate behavioral examinations of individuals are located within the field of social psychology. The emergence of the concept dates back to ancient times in written history. In the 1860s, psychologists began to put forward theories to elucidate how attitudes affect individual behaviors (Yuzhanin & Fisher, 2016). Looking at the development process of the concept, it is accepted that many theories were put forward by researchers in the true sense in 1918 and 1925. Historically, it can be seen that theories of "attitude" were developed in the 19th century literature. Attitude, one of these theories, elucidates the reasons for individuals' actions (Ajzen & Fishbein, 1980). Many studies in social psychology (Ajzen, 2002; Armitage, 2001) and tourism (Hsu, 2012; Yamada & Fu, 2012) fields extensively refer to the Theory of Planned Behavior (TPB) model to understand individuals' behavioral intentions and motivational influences they exhibit.

The "Theory of Reasoned Action" (TRA), developed by Ajzen and Fishbein (1970), attempted to explain this concept but was later deemed inadequate and insufficient. Subsequently, the deficiencies of the model were addressed, and the concept of "Perceived Behavioral Control" was added to create the Theory of Planned Behavior (TPB). It is acknowledged that the limitations of TRA in examining behaviors under individual control led to the emergence of TPB as an extension of TRA (Ajzen & Fishbein, 1980). The TPB model, thus formed, is considered to include the belief factor related to the individual's possession of the necessary resources and opportunities to exhibit the behavior. It is argued that it expands the scope of the TRA model. As a result of developments, within the framework of the model, it is suggested that in addition to the evaluative judgment of individuals, perceived behavioral control and the social influences individuals possess are crucial in explaining a person's behavior (Choo et al., 2016).

When looking at the two explained models, their commonality lies in encapsulating individuals' intentions to perform behaviors within specific frameworks. Accordingly, it is believed that the motivation factor plays a role in individuals' intentions when exhibiting a behavior. The effort individuals put into exhibiting a behavior is considered a factor indicating their planning in exhibiting that behavior (Ajzen & Fishbein, 1980). Generally accepted, an individual's attitude towards a behavior is associated with their desire to perform that behavior. In this regard, individuals' performance of behaviors is assumed only when they have control over these behaviors (Ajzen, 1991). The concept of intention is of high importance in various fields within the framework of behavior, such as technology, health, politics, marketing, and psychology (Cheon et al., 2012).

The attitude concept contained within the model is considered as individuals' personal evaluation as a positive or negative disposition they hold towards exhibiting a behavior (Ajzen, 1985). As can be understood from the explanations, the importance of individuals' attitudes in their behaviors has been emphasized. Not only attitude but also various opportunities and possibilities such as money, time, and skills are considered influential factors in affecting behaviors. The TPB model has been illustrated in the visual below, indicating the influences on behavior. Therefore, the reason for an individual's exhibiting a behavior is predicted by three variables; these variables are explained as the individual's Attitude Toward the Behavior, Subjective Norms (SN), and Perceived Behavioral Control (PBC). Ultimately, these three concepts lead to the formation of the behavioral intention affecting behavior (Ajzen, 2002).

Another factor observed within the TPB is the presence of the Special Norm. The Special Norm entails the pressure felt by individuals when exhibiting a behavior in the presence of significant people in their social circle (such as family, relatives, close friends, and colleagues), whom they consider important (Baker and White, 2010). This situation is construed as stemming from the influence heavily reliant on the need for approval from others in the individual's environment whose opinions they value (Ajzen, 1991). Conversely, it also encompasses the evaluation of adverse situations encountered by individuals. It is suggested that individuals with a high motivation to conform to pressure emphasize the significance of the Subjective Norm role (Mathieson, 1991). Evolving over time, the theory has incorporated the concept of Perceived Behavioral Control in addition to the Special Norm and Attitude Toward Behavior. The notion of Perceived Behavioral Control is reflected in literature as the attitudes individuals hold regarding the ease or difficulty they perceive in performing behaviors (Ajzen and Fishbein, 2008).

Within the framework of these descriptions, it is accepted that individuals are motivated by Attitudes and Subjective Norms when exhibiting behavior, alongside various organizational conditions also exerting influence. Accordingly, organizational conditions play a role in individuals' behaviors and their intentions (Azjen, 1991). A direct relationship between attitude and behavior is acknowledged among the factors in the model. In addition to this relationship, researchers assert that the concept of Behavioral Intention Towards Action is also a factor influencing this relationship (Azjen and Fishbein, 1977). Looking at the factors within the TPB model, in addition to Attitude Toward Behavior, Subjective Norms, and Behavioral Intention Towards Action, it is also influenced by Perceived Behavioral Control (Ajzen and Fishbein, 2008).

TRA broadly defines individuals' attitude toward a behavior as the "degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question." Generally, the more positive the attitude towards a behavior is, the stronger the individual's intention to perform the behavior (Ajzen, 1991). In this context, individuals' decisionmaking and actions are influenced by various situations in their lives. These influencing situations are observed in various aspects of life, one of which is considered to be tourism movements. Within tourism movements, individuals' destination choices are included in the scope of this study.

Various definitions of the destination concept exist in tourism literature. For example, it is described as a mixture of tourism products offering intertwined experiences to consumers (Buhalis, 2000). In addition to this definition found in the literature, it is defined within the framework of the Turkish Language Association as "the place to be reached." Another perspective defines the destination concept as geographical regions where tourists can experience personal experiences based on travel (Rathee and Rajain, 2022). When examined within the scope of these definitions, the characteristics that individuals possess when making destination choices also hold importance. When examining the importance in destination selection, it is found that there is a relationship between individuals' ability and opportunities to travel and their destination selection in terms of perceived behavioral points. It is stated that individuals play an important role in their travel behaviors at this point (Martin et al., 2011). The TPB not only concludes the individuals' destination preferences but also holds importance in their engagement in recreational behaviors at their preferred destinations (Lam and Hsu, 2006).

Conceptually, it is considered as the time allocated by individuals and freely available for their use. Additionally, it is described as a period in which individuals are free from their responsibilities towards themselves and their surroundings, and they can freely evaluate it (Broadhurst, 2001). Recreational activities are carried out to provide various psychological or physical benefits to individuals. As a result of this situation, it can be said that there are motivating factors for individuals in participating in any recreational activity. For example, individuals involved in recreational movement in their private lives may experience characteristics of their cities such as crowdedness, stress, and excessive noise that negatively affect human life. Due to this situation, individuals develop a desire to spend time for themselves, make efforts to spend time with their surroundings and family members, and create motivations to participate in recreational activities (Wellman, 1979; Manfredo, 1996). In addition to the explanations provided, when studies conducted within the recreational framework are examined, it is seen that the studies mainly examine the reasons why individuals need to participate in recreational activities, why they do not, what the main motivations directing individuals to these activities are. It is known that these studies began to draw attention to the concept of leisure motivation in the eighties (Kim et al., 2011).

In line with the explanations provided above, according to Carroll and Alexandris (1997), the motivation of the individual is composed of internal and external stimuli. It is conveyed through studies that the individual plays an important role in participating in their leisure activities with these stimuli and internal motives. The theories used to elucidate the reasons behind individuals' behaviors generally play a decisive role in determining the reasons behind destination selection and the recreational activities they will engage in at these destinations.

 3. Method <italic>3.1. Population and Sample</italic>

In order to test the hypotheses formulated within the scope of the research objective, a preliminary field study was conducted. Within this context, the population of the research consists of the entirety of the local population living in the Sinop destination who could be accessed during the data collection process. As of the start of the data collection process on May 1, 2023, the population of the research was determined to be 220,799 individuals (TÜÍK, 2023). The research sample consists of the local population that could be reached in the Sinop destination during the data collection process (May 1, 2023 - October 1, 2023). However, the exact number of people living in the Sinop destination during the data collection process could not be determined. In this context, it is stated in various sources that a sample size of 384 would represent the population in terms of both qualitative and quantitative aspects in cases where the sample size cannot be determined exactly (Altuniçik et al., 2007). To ensure an acceptable sample size for the population size, a questionnaire prepared for this purpose was administered to the local population living in the Sinop destination.

 <italic>3.2. Data Collection Process and Scales</italic>

The survey technique was utilized in the data collection process of the research. A questionnaire consisting of four sections and 36 statements was used in this study. The first section of the questionnaire consists of four statements aimed at identifying the participants and their demographic characteristics, along with multiple-choice options for the respondent to choose from. The second section of the questionnaire consists of six statements aimed at determining the participants' leisure time utilization and recreational tendencies, along with multiple-choice options for the respondent to choose from. The third section of the questionnaire consists of 25 statements aimed at identifying the characteristics that hinder participants' participation in leisure and recreational activities, using a five-point Likert scale (Five-Very Important and One-Very Unimportant). The fourth and final section of the questionnaire aims to identify the factors that hinder participants' participation in leisure and recreational activities through a statement and multiple-choice options for the respondent to choose from. The demographic and Likert-type statements in the questionnaire were prepared based on the study by Çoruh (2013).

 <italic>3.3. Data Analysis</italic>

Firstly, descriptive statistical tests were conducted on the collected data in line with the research objective. Subsequently, confirmatory factor analysis was conducted in this study to determine the reliability and validity of the scale used to identify the factors hindering participation in leisure and recreational activities, as utilized in the study by Çoruh (2013). Additionally, analyses were conducted to determine the differences between each dimension of the relevant scale (lack of time and interest, lack of knowledge, individual psychology, lack of friends, inadequate facilities, and transportation problems) and demographic variables, and the hypotheses identified in the relevant literature were tested.

 <italic>3.4. Research Hypotheses</italic>

This study, conducted with quantitative methods, is descriptive and explanatory in nature, and the assumed research hypotheses are provided below:

H1: There is a significant difference in the level of participation in leisure and recreational activities among the local population based on gender.

H1a: The levels of factors hindering participation in leisure and recreational activities, such as lack of time and interest, show significant differences based on gender.

H1b: The levels of factors hindering participation in leisure and recreational activities, such as individual psychology, show significant differences based on gender.

H1c: The levels of factors hindering participation in leisure and recreational activities, such as lack of knowledge, show significant differences based on gender.

H1d: The levels of factors hindering participation in leisure and recreational activities, such as transportation problems, show significant differences based on gender.

H1e: The levels of factors hindering participation in leisure and recreational activities, such as inadequate facilities, show significant differences based on gender.

H1f: The levels of factors hindering participation in leisure and recreational activities, such as lack of friends, show significant differences based on gender.

H2: There is a significant difference in the level of participation in leisure and recreational activities among the local population based on age.

H2a: The levels of factors hindering participation in leisure and recreational activities, such as lack of time and interest, show significant differences based on age.

H2b: The levels of factors hindering participation in leisure and recreational activities, such as individual psychology, show significant differences based on age.

H2c: The levels of factors hindering participation in leisure and recreational activities, such as lack of knowledge, show significant differences based on age.

H2d: The levels of factors hindering participation in leisure and recreational activities, such as transportation problems, show significant differences based on age.

H2e: The levels of factors hindering participation in leisure and recreational activities, such as inadequate facilities, show significant differences based on age.

H2f: The levels of factors hindering participation in leisure and recreational activities, such as lack of friends, show significant differences based on age.

H3: There is a significant difference in the level of participation in leisure and recreational activities among the local population based on the place of residence.

H3a: The levels of factors hindering participation in leisure and recreational activities, such as lack of time and interest, show significant differences based on the place of residence.

H3b: The levels of factors hindering participation in leisure and recreational activities, such as individual psychology, show significant differences based on the place of residence.

H3c: The levels of factors hindering participation in leisure and recreational activities, such as lack of knowledge, show significant differences based on the place of residence.

H3d: The levels of factors hindering participation in leisure and recreational activities, such as transportation problems, show significant differences based on the place of residence.

H3e: The levels of factors hindering participation in leisure and recreational activities, such as inadequate facilities, show significant differences based on the place of residence.

H3f: The levels of factors hindering participation in leisure and recreational activities, such as lack of friends, show significant differences based on the place of residence.

H4: There is a significant difference in the level of participation in leisure and recreational activities among the local population based on where they spend the majority of their lives.

H4a: The levels of factors hindering participation in leisure and recreational activities, such as lack of time and interest, show significant differences based on where they spend the majority of their lives.

H4b: The levels of factors hindering participation in leisure and recreational activities, such as individual psychology, show significant differences based on where they spend the majority of their lives.

H4c: The levels of factors hindering participation in leisure and recreational activities, such as lack of knowledge, show significant differences based on where they spend the majority of their lives.

H4d: The levels of factors hindering participation in leisure and recreational activities, such as transportation problems, show significant differences based on where they spend the majority of their lives.

H4e: The levels of factors hindering participation in leisure and recreational activities, such as inadequate facilities, show significant differences based on where they spend the majority of their lives.

H4f: The levels of factors hindering participation in leisure and recreational activities, such as lack of friends, show significant differences based on where they spend the majority of their lives.

 4. Findings <italic>4.1. Demographic Findings</italic>

Among the local participants in the study, 62.18% are aged 50 and below, and 53.13% are females. Additionally, 77.96% of the surveyed locals are home-based, and 58.24% spend the majority of their lives in the city. About 36.66% of the participants have 6-10 hours of leisure time weekly. 67.29% of the locals sometimes find it difficult to utilize their leisure time. It was observed that 50.35% of the locals engage in social activities to spend their leisure time, while 45.94% participate in indoor activities. Moreover, 37.12% of the participants partially consider the recreational areas in Sinop destination to be sufficient. 83.52% of the locals use Sinop's recreational areas for 1-5 hours weekly. Furthermore, 46.17% of the participants mainly spend their leisure time outside the city (Table 1).

Demographic Characteristics of Participants
Demographic Characteristics Number (n) Percentage (%)
Age 50 years and Below 268 62,18
51 years and Above 163 37,82
Gender Female 229 53,13
Male 202 46,87
Residence With Friends 24 5,57
Own Home 336 77,96
With Family 71 16,47
Place Mostly Spent Life Rural/Town 81 18,79
City 251 58,24
Metropolitan 99 22,97
Weekly Leisure Time 1-5 Hours 77 17,80
6-10 Hours 158 36,66
11-15 Hours 98 22,77
16 Hours and Above 98 22,77
Frequency of Difficulty in Leisure Activities Never 43 9,98
Sometimes 290 67,29
Always 98 22,77
Method of Leisure Activity Participation Participation in Indoor Activities 198 45,94
Participation in Physical Activities 96 22,28
Participation in Social Activities 217 50,35
Participation in Cultural-Artistic Activities 132 30,63
Participation in Outdoor Activities 128 29,70
Other 123 28,54
Adequacy of Recreational Areas in Sinop Definitely Inadequate 89 20,65
Inadequate 102 23,67
Partially 160 37,12
Adequate 69 16,01
Definitely Adequate 11 2,55
Frequency of Using Recreational Areas in Sinop (Weekly) 1-5 Hours 360 83,52
6-10 Hours 59 13,69
11-15 Hours 8 1,86
16 Hours and Above 4 0,93
Place Mostly Spent Leisure Time Within the City 195 45,25
Within the City 199 46,17
Other 37 8,58
Total 431 100,00

<italic>4.2. Confirmatory Factor Analysis Results for the Scale Determining Factors Hindering Participation in Leisure and Recreational Activities</italic>

Confirmatory Factor Analysis (CFA) was conducted to determine the structural validity of the "Scale for Determining Factors Hindering Participation in Leisure and Recreational Activities," which was adapted into Turkish by Karaküçük and Gürbüz (2006) and subjected to reliability and validity tests by Çoruh (2013). The secondary level CFA fit indices obtained from the analysis are presented in Table 2. Through DFA analysis, model fit indices were examined, and it was concluded that the model created within the scope of the research is "compatible and acceptable" with the collected data, as the model fit indices demonstrate "good fit."

Secondary Level CFA Fit Indices for the Scale Determining Factors Hindering Participation in Leisure and Recreational Activities
Measurement (Fit Statistics) Good Fit Acceptable Fit Values Conclusion
CFI ≥ 0,95 0,94-0,90 0,95 Good Fit
IFI ≥ 0,95 0,94-0,90 0,95 Good Fit
RMSEA ≤ 0,05 0,06-0,08 0,06 Acceptable Fit
NFI ≥ 0,95 0,94-0,90 0,92 Acceptable Fit
NNFI (TLI) ≥ 0,95 0,94-0,90 0,93 Acceptable Fit
(x2/df) ≤3 ≤4-5 2,82 Good Fit
AGFI ≥ 0,90 0,89-0,80 0,87 Acceptable Fit
GFI ≥ 0,90 0,89-0,85 0,91 Good Fit

Table 3 displays the factor loadings, CR (composite reliability), AVE (average variance extracted), and reliability values related to the scale for identifying factors that impede participation in leisure and recreational activities. Hair et al. (2017) have stated that factor loadings should be above 0.70. Upon examination of the values in Table 3, it is evident that all expressions included in the analysis exceed this threshold. Additionally, when scrutinizing the Cronbach Alpha coefficients of the dimensions constituting the scale for identifying factors that hinder participation in leisure and recreational activities, it is found that the coefficients are as follows: "lack of time and interest dimension" is 0.865; "individual psychology dimension" is 0.898; "transportation problem dimension" is 0.823; "facility inadequacy dimension" is 0.825; "lack of information dimension" is 0.820; and "lack of friends dimension" is 0.874. With CR coefficients ranging from 0.819 to 0.892, it is acknowledged, according to Hair et al. (2017), that internal consistency validity is achieved. Moreover, the range of factor loadings from 0.715 to 0.907 and AVE coefficients ranging from 0.570 to 0.735 indicate the establishment of convergent validity.

Factor Loadings, CR, AVE, and Reliability Values of the Scale for Determining Factors Affecting Participation in Leisure and Recreation Activities
Dimensions Statements Factor Loadings Factor Loadings CR AVE Cronbach Alpha
LTI LTI1 ,846 10.70 0,879 0,646 0,865
LTI2 ,849 9,19
LTI3 ,743 8,74
LTI4 ,771 9,36
IP IP1 ,750 10,94 0,859 0,570 0,898
IP2 ,785 7,98
IP3 ,771 8,93
IP4 ,748 10,30
IP5 ,715 9,88
TP TP1 ,858 9,12 0,837 0,632 0,823
TP2 ,753 9,07
TP3 ,770 8,91
FI FI1 ,743 9,71 0,819 0,602 0,825
FI2 ,817 8,17
FI3 ,766 10,27
LI LI1 ,714 7,90 0,823 0,614 0,820
LI 2 ,907 7,18
LI 3 ,801 9,25
LF LF1 ,840 7,56 0,892 0,735 0,874
LF2 ,864 7,90
LF3 ,867 9,22

LTI: Lack of Time and Interest, IP: Individual Psychology, TP: Transportation Problem, FI: Facility Insufficiency, LI: Lack of Information, LF: Lack of Friends.

 <italic>4.3. Hypothesis Test Results</italic>

Before proceeding to hypothesis testing in this study, the normality of the data was examined. According to the results of the normality test applied, the Skewness value ranged from -0.495 to 0.141, and the Kurtosis value ranged from 0.693 to -0.108. Finding these values within the range of -1.5 to +1.5 indicates that the research scale follows a normal distribution (Tabachnick & Fidell, 2013). Following the normality test, independent sample T-tests and ANOVA analyses were conducted to assess differences in dimensions and relevant hypotheses for the research. An independent sample T-test was employed to determine whether the dimensions included in the study exhibited differences based on the gender variable of the local population. According to the test results, significant differences were not detected between the gender variable of the local population and the research dimensions, except for the ZIE dimension (0.009; p < 0.05), ULS dimension (0.021; p < 0.05), BIP dimension (0.011; p < 0.05), and ARE dimension (0.041; p < 0.05). In the ZIE dimension, it was found that female participants (M = 4.46) experienced more shortcomings and perceived more barriers to participation in leisure and recreational activities compared to male participants (M = 4.41). In the ULS dimension, female participants (M = 4.40) experienced more shortcomings and perceived more barriers compared to male participants (M = 4.18). In the BIP dimension, male participants (M = 4.38) experienced more shortcomings and perceived more barriers compared to female participants (M = 4.18). Similarly, in the ARE dimension, male participants (M = 4.32) experienced more shortcomings and perceived more barriers compared to female participants (M = 4.24) (Table 4). Based on these results, hypotheses H1, H1a, H1b, H1d, and H1f were accepted, while hypotheses H1c and H1e were rejected.

T-Test Analysis Results Regarding the Gender of the Local Population
Test of Equality of Variances
Faktör Groups x Levene p t P
LTI Female 4,46 ,433 ,665 2,968 ,009
Male 4,41
TP Female 4,40 ,501 ,432 2,567 ,021
Male 4,18
IP Female 4,18 ,413 ,505 3,012 ,011
Male 4,38
LF Female 4,24 ,351 ,389 2,158 0,41
Male 4,32

LTI: Lack of Time and Interest, TP: Transportation Problem, IP: Individual Psychology, LF: Lack of Friends

The dimensions included in the study were analyzed for differences based on the age variable of the local population using independent sample T-tests. According to the test results, significant differences were not detected between the age variable of the local population and the research dimensions, except for the ARE dimension (0.018; p < 0.05), BIP dimension (0.006; p < 0.05), and BIE dimension (0.026; p < 0.05). In the ARE dimension, it was found that local residents aged 51 and above (M = 4.48) experienced more shortcomings and perceived more barriers to participation in leisure and recreational activities compared to local residents aged 50 and below (M = 4.38). In the BIP dimension, local residents aged 51 and above (M = 4.44) experienced more shortcomings and perceived more barriers compared to local residents aged 50 and below (M = 4.24). Similarly, in the BIE dimension, local residents aged 51 and above (M = 4.40) experienced more shortcomings and perceived more barriers compared to local residents aged 50 and below (M = 4.18) (Table 5). Based on these results, hypotheses H2, H2b, H2c, and H2f were accepted, while hypotheses H2a, H2d, and H2e were rejected.

T-Test Analysis Results Regarding the Age of the Local Population
Test of Equality of Variances
Factor Groups x Levene p t P
LF 50 years and Below 4,38 ,441 ,587 2,158 ,018
51 years and Above 4,48
IP 50 years and Below 4,24 ,378 ,495 4,566 ,006
51 years and Above 4,44
LI 50 years and Below 4,18 ,644 ,512 3,108 ,026
51 years and Above 4,40

LF: Lack of Friends, IP: Individual Psychology, LI: Lack of Information.

The study applied one-way analysis of variance (ANOVA) to determine whether the dimensions included in the research exhibited differences based on the variable of the residential locations of the local population. The analysis revealed significant differences in the BIE dimension (0.028; p < 0.05), ARE dimension (0.006; p < 0.05), and BIP dimension (0.023; p < 0.05) concerning the residential locations of the local population. In the BIE dimension, local residents residing in their own homes (M = 4.44) experienced more shortcomings and perceived more barriers to participation in leisure and recreational activities compared to those residing with friends (M = 4.32) and with family (M = 4.24). In the ARE dimension, local residents residing in their own homes (M = 4.40) experienced more shortcomings and perceived more barriers compared to those residing with friends (M = 4.28) and with family (M = 4.32). Similarly, in the BIP dimension, local residents residing in their own homes (M = 4.44) experienced more shortcomings and perceived more barriers compared to those residing with friends (M = 4.40) and with family (M = 4.28) (Table 6). Based on these results, hypotheses H3, H3b, H3c, and H3f were accepted, while hypotheses H3a, H3d, and H3e were rejected.

ANOVA Analysis Results Regarding the Residential Locations of the Local Population
Test of Equality of Variances
Factor Groups x Levene p F P
LI With Friends 4,32 ,434 ,458 ,546 ,028
Own Home 4,44
With Family 4,24
IP With Friends 4,40 ,668 ,663 ,766 ,006
Own Home 4,44
With Family 4,28
LF With Friends 4,28 ,306 ,429 ,882 ,023
Own Home 4,40
With Family 4,32

LI: Lack of Information, IP: Individual Psychology, LF: Lack of Friends.

The study conducted one-way analysis of variance (ANOVA) to determine whether the dimensions included in the research exhibited differences based on the variable of the places where the local population spent most of their lives. The analysis revealed significant differences in the ZIE dimension (0.040; p < 0.05), US dimension (0.003; p < 0.05), TEY dimension (0.011; p < 0.05), and ARE dimension (0.018; p < 0.05) concerning the variable of the places where the local population spent most of their lives. In the ZIE dimension, it was found that local residents who spent most of their lives in rural areas (M = 4.42) experienced more shortcomings and perceived more barriers to participation in leisure and recreational activities compared to those who spent most of their lives in urban (M = 4.34) and metropolitan (M = 4.28) areas. In the US dimension, local residents who spent most of their lives in rural areas (M = 4.44) experienced more shortcomings and perceived more barriers compared to those who spent most of their lives in urban (M = 4.38) and metropolitan (M = 4.36) areas. Similarly, in the ARE dimension, local residents who spent most of their lives in rural areas (M = 4.38) experienced more shortcomings and perceived more barriers compared to those who spent most of their lives in urban (M = 4.34) and metropolitan (M = 4.20) areas. In the TEY dimension, it was found that local residents who spent most of their lives in metropolitan areas (M = 4.40) experienced more shortcomings and perceived more barriers compared to those who spent most of their lives in urban (M = 4.26) and rural (M = 4.18) areas concerning leisure and recreational participation (Table 7). Based on these results, hypotheses H4, H4a, H4d, H4e, and H4f were accepted, while hypotheses H4b and H4c were rejected.

ANOVA Analysis Results Regarding the Places Where the Local Population Spent Most of Their Lives
Test of Equality of Variances
Factor Groups x Levene p F P
LTI Rural/Town 4,42 ,238 ,357 1,003 ,040
City 4,34
Metropolitan 4,28
TP Rural/Town 4,44 ,348 ,447 ,988 ,003
City 4,38
Metropolitan 4,36
FI Rural/Town 4,18 ,334 ,508 ,448 ,011
City 4,26
Metropolitan 4,40
LF Rural/Town 4,38 ,809 ,301 ,704 ,018
City 4,34
Metropolitan 4,20

LTI: Lack of Time and Interest, TP: Transportation Problem, FI: Facility Insufficiency, LF: Lack of Friends.

 5. Results, discussion, and recommendations

Leisure time is defined as the time individuals allocate to themselves without bearing any responsibilities. Studies on leisure activities indicate that they have a positive impact on quality of life (Broadhurst, 2001; London et al., 1977; Lloyd and Aduld, 2002; Lewis et al, 2001). Hence, research aimed at identifying the barriers to engaging in leisure activities may guide individuals in enhancing their quality of life. Following this notion, surveys were conducted among the local population in Sinop province from May 1, 2023, to October 1, 2023, involving 384 participants to identify barriers to leisure activities. The survey results revealed differences among participants' demographic variables and the barriers hindering their engagement in recreational activities.

When examining the level of participation in leisure and recreation activities based on gender, significant differences were found in dimensions such as lack of time and interest, individual psychology, transportation issues, and lack of companionship. According to the research findings, female participants reported encountering more obstacles related to lack of time and interest and transportation issues compared to male participants. On the other hand, male participants indicated facing more barriers related to individual psychology and lack of companionship compared to females. Similar results were partially obtained in studies conducted by Ayhan et al. (2018) and Shaw (1994), which revealed that female participants face more barriers compared to males. Considering these results, it is evident that various factors influence participation in recreational activities, with gender being one of the significant factors restricting participation.

The study results indicated significant differences between participants' ages and the barriers they face regarding recreational activities. Participants aged 51 and above were observed to have more obstacles related to lack of companionship, lack of information, and individual psychology compared to participants at lower age levels. It was found that as individuals grow older, they experience more deficiencies and perceive more barriers to participation in leisure and recreation activities. These findings align with previous studies by Lakot (2015) and Demirtas. and imamoglu (2018), which found significant variations in leisure barriers based on age.

When examining whether there is a difference between participants' place of residence and barriers to recreational activity participation, it was found that the place of residence influences individuals' participation in recreational activities. Participants residing in their own homes reported encountering more obstacles such as lack of information, lack of companionship, and individual psychology compared to those living with friends or family. Another result of the research is the significant differences in barriers to recreational activities based on individuals' places of residence. Responses from participants indicated that individuals living in rural areas or smaller settlements perceive more barriers such as lack of time and interest, transportation issues, and lack of companionship compared to those living in urban areas. Conversely, individuals living in major cities reported facing more barriers related to facility inadequacy compared to those living in cities or villages.

<italic>5.1. Recommendations</italic>

Female participants, especially, are more affected by factors such as lack of time and interest and transportation issues. Therefore, special support programs and activities targeting women can be organized to increase their participation in recreational activities. Additionally, programs targeting women, such as guided nature walks or social events, can be planned, which are expected to help alleviate the barriers for female participants in engaging in recreational activities.

Participants aged 51 and above encounter specific barriers to a greater extent. Suitable activities to encourage participation in recreational activities can be organized for this age group. Additionally, psychological support and motivation-enhancing practices can be provided to overcome psychological barriers to recreational participation among older participants. Cultural activities, walking groups, or sports programs tailored to the elderly can be established.

It was identified that factors such as lack of information and lack of companionship are prominent among participants. Therefore, local authorities or businesses can organize more informative campaigns and awareness-raising activities regarding recreational opportunities. Additionally, social platforms or groups supporting participation in recreational activities can be established to provide assistance to participants.

Participants living in major cities are more affected by factors such as facility inadequacy. Hence, more emphasis should be placed on the development of recreational areas and facilities in the urban planning process. Local authorities should make efforts to increase and improve recreational areas such as urban parks, sports facilities, and community centers. In densely populated areas, where facilities fail to meet the needs of the population, it is recommended that local authorities address this issue.

On the other hand, individuals living in rural areas or small settlements encounter more barriers such as lack of time and interest, transportation issues, and lack of companionship compared to urban dwellers. In this context, local authorities and businesses can collaborate to enhance and diversify recreational opportunities in rural areas. Projects supporting initiatives such as the establishment of nature walk routes and the promotion of historical and cultural sites in rural areas can be encouraged.

These recommendations may assist local authorities, businesses, and academics in developing various strategies to increase participation in recreational activities. With the implementation of these strategies, participation in recreational activities among the local population can be enhanced, consequently improving quality of life and well-being.

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