Investigation of Constraints that Occur during Participation in Leisure Activities by High School Students: A Sample of Turkey

Abstract

The aim of this research was to determine the factors that may prevent high school students from participating in recreational activities and to investigate whether these factors differ within the scope of various variables. This study consisted of 1459 (681 women and 778 men) student volunteers who are educated to high school level. The easy sampling method was preferred in the present study. The face-to-face survey method was used to collect the data. The “Leisure Constraints Scale” developed by Alexandris and Carroll (1997) and adapted to Turkish by Gürbüz, Öncü, and Emir (2012) was used to determine the factors that might prevent individuals from participating in leisure activities. The data obtained for the research were first transferred to a computer and then analyzed by the SPSS program. The error margin level in the study was taken as p < 0.05. The Cronbach alpha of the study was found to be 0.91. As a result, it was found that women participated in leisure activities more than men. It was also observed that the participants met with more leisure constraints in Turkey’s eastern regions.

1. Introduction

Today’s education system is aimed not just at future professions. Schools are obliged not only to provide information but also to socialize the individual. In this respect, leisure education is given importance by education institutions regarding evaluation of non-school hours of students. Where leisure education is not emphasized, individuals face various obstacles and use time inefficiently.

Time is a process in which events follow each other from the past to the future and continue uninterrupted beyond the control of the individual [1]. Karaküçük (2005) emphasized that time is life, and that the passage of time is equivalent to the passing of life [2]. Leisure time is defined as the period not spent for sleeping, eating, and doing other compulsory jobs for the individual [3,4,5]. This time, which one can freely use for participation in recreational activities, must be outside of work time and compulsory needs [6]. Time availability and time management are critical to the organization of leisure [7]. Sivan (1997) defined this time as “a lifelong learning process that helps people achieve through socially acceptable leisure activities their fullest leisure potential and desirable quality of life.” [8]. Time can be manipulated according to our needs [9]. The need for recreational activities has an essential place among these needs. Leisure time is becoming increasingly important and at the center of almost everybody’s life. Increasing levels of social welfare and better living conditions increase the leisure time of individuals in the society [10]. According to Demir and Demir (2007), leisure and recreational activities are a serious problem for every segment of society [11]. According to Kenioua and Boumasjed, (2016), students participate in recreational activities, improve their mental health as well as their positive contribution to behavior and personality [12]. Leisure activities provide students with positive social behaviors and a quality lifestyle, as well as protecting the young population from harmful habits [13,14,15]. The process of training of the young generation to target proactive behaviors and attitudes is one of the primary goals of promoting leisure activities based on diversification of motivation, improvement of physical fitness and enhancement of motor skills [16,17,18]. Despite these positive contributions to recreational activities, it is observed that individuals do not participate in such activities, for reasons that are very important for them, or they cannot attend due to various obstacles [19].

The notion of “barriers” as expressed here refers to the reasons that prevent or restrict the individual’s participation in leisure activities during leisure time and are encountered by the individual [19]. It is possible to talk about many social aspects in understanding the factors that prevent individuals from participating in leisure activities. These factors have been interpreted differently by different scientists. For example, regarding attendance to recreational events, Alexandris and Carroll (1997) found age, Gratton (2000) found income level, Ekinci et al. (2014) found gender as constraints [20,21,22].

The literature is full of analysis extolling the role of schools, colleges, and universities in promoting leisure education and developing the leisure attitudes, values, and skills of young people [23,24]. Yet the potential of school systems to constrain the pursuit of leisure remains an unexplored frontier [25]. Considering this information, the aim of this study is to determine the factors that may prevent high school students from participating in leisure activities and examine them in terms of various variables.

2. Materials and Methods

This section includes the model, the group, the data collection tool, analyses, methods, and techniques related to the data.

2.1. Research Model

The research was based on quantitative research design and a descriptive cross-sectional study. A general screening model was applied to arrive at a general judgment about the population, in which the whole population, or a sample taken from it, was scanned [26].

2.2. Research Sample

The research sample consisted of total 1459 (681 women and 778 men) student volunteers who have been educated to high school level in seven different regions of Turkey. The average age of participants was 16.48 ± 1.16 years. The participants were from the Aegean region (13.2%), Southeastern Anatolia region (12.4%), Mediterranean region (12.7%), Black Sea region (14.8%), Marmara region (15.5%), Central Anatolia region (16.1%), and Eastern Anatolia region (15.3%) in Turkey. All participants were informed of the research procedures, purposes of the investigation, and gave their written consent prior to participation. There are approximately 3,798,000 students attending formal education in Turkey [27]. According to Yazicioglu and Erdoğan (2004), the evaluation of a population of 1 million people can be evaluated with a sample group of 384 people. In this respect, the population of our study is in line with the sample [28]. The research sample of the current study was chosen according to the Nomenclature of Territorial Units for Statistics [29].

2.3. Data Collection Tools

In this study, the “Leisure Constraints Scale” developed by Alexandris and Carroll (1997) and adapted to Turkish by Gürbüz, Öncü, and Emir (2012) was used to determine the factors that might prevent individuals from participating in leisure activities [20,30]. It is an 18-item and 4-point Likert-type measure evaluating the factors that prevent participation in recreational activities. For each question, options were: 1: “Absolutely insignificant”; 2: “Insignificant”; 3: “Important”; 4: “Very Important” and participants were asked to select the most appropriate option from the research group. The Leisure Time Constraints Scale is collected under 6 sub-scales. Cronbach alpha reliability coefficients for the total scale was found to be 0.85. The Cronbach alpha reliability was found to be 0.91 in the current study.

2.4. Analysis of Data

For the data obtained in the study, the SPSS package program was used and frequency (f) and percent (%) distributions of the variables were calculated. The histograms, Skewness and Kurtosis values were checked to ensure normal distribution of the data. Skewness and Kurtosis were valued to be −2 to +2 [31]. Therefore, the t-test and the ANOVA test were used. The Scheffe test was used for multiple comparisons. Significance was set at p < 0.05 and results were considered significant with 95% confidence interval.

3. Results

In this section, findings about variables of the study are included. Findings showing the distributions of the participant students according to their personal qualities were examined and interpreted.

Table 1. t-Test results of students according to gender status variable.

Leisure Constraints Scale	Gender	N	$\overline{\mathbf{x}}$	Sd.	t	p
Individual Psychology	Women	681	2.80	0.68	6.05	0.00 **
	Men	778	2.58	0.74
Lack of Information	Women	681	2.81	0.75	4.54	0.00 **
	Men	778	2.63	0.78
Facilities/Service	Women	681	2.82	0.62	4.06	0.00 **
	Men	778	2.68	0.69
Lack of Friends	Women	681	2.62	0.79	3.59	0.00 **
	Men	778	2.48	0.78
Time	Women	681	2.77	0.71	4.84	0.00 **
	Men	778	2.59	0.71
Lack of Interest	Women	681	2.65	0.81	4.88	0.00 **
	Men	778	2.45	0.82

** p < 0.01.

shows that there was a statistically significant difference between gender variables and sub-scales of the leisure constraints scale (individual psychology, lack of information, facilities/service, lack of friends, time, lack of interest) (p < 0.05). It was determined that the average scores in all sub-scales for women was higher than men.

Table 2. Difference analysis of the regional variables of the students.

		Sum of Squared	df.	Mean Squared	F	p	Post-Hoc Test Results
Individual Psychology	Between Groups	327.49	6	54.58	6.79	0.000 **	D-B, D-G, E-B, E-F, E-G
	Within Group	11,669.98	1452	8.04
	Total	11,997.46	1458
Lack of Information	Between Groups	394.05	6	65.67	4.45	0.000 **	E-A, E-B, E-C
	Within Group	21,428.96	1452	14.76
	Total	21,823.01	1458
Facilities/Service	Between Groups	814.95	6	135.83	4.94	0.000 **	E-B, E-C, E-G F-B, F-G
	Within Group	39,871.33	1452	27.46
	Total	40,686.28	1458
Lack of Friends	Between Groups	144.96	6	24.16	4.35	0.000 **	E-A, E-B, E-C, E-D, E-G
	Within Group	8048.79	1452	5.54
	Total	8193.74	1458
Time	Between Groups	195.35	6	32.56	4.04	0.001 **	E-B, E-C, E-G
	Within Group	11,695.81	1452	8.05
	Total	11,891.16	1458
Lack of Interest	Between Groups	114.12	6	19.02	3.18	0.004 **	B-F
	Within Group	8671.23	1452	5.97
	Total	8785.35	1458

A: Aegean Region; B: Southeast Anatolia Region; C: Mediterranean Region; D: Black Sea Region; E: Marmara Region; F: Central Anatolia Region; G: Eastern Anatolia Region. ** p < 0.01.

shows the results of the ANOVA test according to the region variable of participants. According to the region, it was found that there was a statistically significant difference sub-scales of the leisure constraints scale (individual psychology, lack of information, facilities/service, lack of friends, time, lack of interest) (p < 0.05).

Table 3. Difference analysis of the leisure time variable of students per week.

		Sum of Squared	df.	Mean Squared	F	p	Post-Hoc Test Results
Individual Psychology	Between Groups	144.12	4	36.03	4.42	0.001 **	E-A, E-B
	Within Group	11,853.34	1454	8.15
	Total	11,997.46	1458
Lack of Information	Between Groups	240.65	4	60.16	4.05	0.003 **	B-E
	Within Group	21,582.36	1454	14.84
	Total	21,823.01	1458
Facilities/Service	Between Groups	388.86	4	97.22	3.50	0.007 **	C-E
	Within Group	40,297.42	1454	27.71
	Total	40,686.28	1458
Lack of Friends	Between Groups	27.41	4	6.85	1.22	0.300	-
	Within Group	8166.33	1454	5.62
	Total	8193.74	1458
Time	Between Groups	31.85	4	7.96	0.97	0.419	-
	Within Group	11,859.31	1454	8.16
	Total	11,891.16	1458
Lack of Interest	Between Groups	46.80	4	11.70	1.94	0.100	-
	Within Group	8738.55	1454	6.01
	Total	8785.35	1458

A: 1–5 h; B: 6–10 h; C: 11–15 h; D: 16–20 h; E: 21 h and over. ** p < 0.01.

shows the results of the ANOVA test according to the weekly leisure time variance of participants. According to this, there was a statistically significant difference between students having weekly leisure time and individual psychology, lack of information and facilities/service sub-scales (p < 0.05).

Table 4. Difference analysis of variance of welfare level felt by students.

		Sum of Squared	df.	Mean Squared	F	p	Post-Hoc Test Results
Individual Psychology	Between Groups	46.93	4	11.73	1.42	0.223	-
	Within Group	11,950.54	1454	8.22
	Total	11,997.46	1458
Lack of Information	Between Groups	110.13	4	27.53	1.84	0.118	-
	Within Group	21,712.88	1454	14.93
	Total	21,823.01	1458
Facilities/Service	Between Groups	198.32	4	49.58	1.78	0.130	-
	Within Group	40,487.96	1454	27.85
	Total	40,686.28	1458
Lack of Friends	Between Groups	57.78	4	14.44	2.58	0.036*	C-E
	Within Group	8135.97	1454	5.60
	Total	8193.74	1458
Time	Between Groups	43.10	4	10.78	1.32	0.259	-
	Within Group	11,848.06	1454	8.15
	Total	11,891.16	1458
Lack of Interest	Between Groups	16.08	4	4.02	0.66	0.615	-
	Within Group	8769.27	1454	6.03
	Total	8785.35	1458

A: Very bad; B: Bad; C: Normal; D: Good; E: Very good. * p < 0.05.

shows the ANOVA test results according to the level of welfare level felt by the participants. According to this, there is a statistically significant difference between the level of prosperity felt by the students and the lack of friendship sub-scale.

According to

Table 5. Results of t-test according to the students’ sports participation.

Leisure Constraints Scale	Sport Participation	N	$\overline{\mathbf{x}}$	Sd.	t	p
Individual Psychology	Yes	892	2.66	0.72	−1.46	0.14
	No	567	2.71	0.71
Lack of Information	Yes	892	2.72	0.77	0.70	0.47
	No	567	2.69	0.78
Facilities/Service	Yes	892	2.74	0.65	−0.06	0.94
	No	567	2.74	0.68
Lack of Friends	Yes	892	2.55	0.79	0.10	0.91
	No	567	2.54	0.79
Time	Yes	892	2.68	0.71	0.84	0.39
	No	567	2.65	0.72
Lack of Interest	Yes	892	2.52	0.83	−1.65	0.09
	No	567	2.59	0.80

, there was not a statistically significant difference between the sports participation of the students and sub-scales of the leisure constraints scale (individual psychology, lack of information, facilities/service, lack of friends, time, lack of interest) (p > 0.05).

4. Discussion

In this study, determining the factors that may prevent students from participating in recreational activities, these constraints have been investigated under various variables. In this context, high school students who study in 7 different regions of Turkey have been examined to observe whether there is a significant difference between leisure constraints scale and gender, living area, welfare level and sport participation status.

Many factors affect participation in recreational activities. Gender, one of these factors, is an important part of the social activity that restricts the participation of individuals in recreational activities [32] and plays an important role in participation in leisure activities [33].

When the results of the t-test were analyzed according to the gender variable of the participants, it was found that there were significant differences between all the sub-scales of leisure constraints scale, and women participants had the highest constraints score in all sub-scales.

There are many existing studies that have reported a significant difference in leisure constraints based on gender, and it has been found that women are more likely to experience constraints than men [34,35,36,37,38,39,40]. When the related studies are examined, it is seen that women face more constraints than men in the same situation in the direction of the results of this study. It is thought that this may be because families do not give enough support for girls’ participation in recreational activities, because society represses girls and girls cannot participate in activities freely [41,42,43].

When the analysis results were examined according to the region variable of the participants, significant differences were found between all the sub-scales of the leisure constraints scales and region. This result has different causes. In western regions, recreation education is given more importance than in eastern regions. Western regions have more facilities for leisure activities than the eastern regions [44]. As there are cultural differences between regions, and attitudes towards recreation is changing. Individuals living in the eastern regions face more barriers to recreational facilities than those living in western regions. This is thought to be because the land in rural areas is less suitable than the urban areas in terms of facilities and that the number of people living in rural areas is lower than those living in urban areas. This is because the rural areas are less favorable in terms of facilities [45,46,47]. According to Arbel et al. (2009), Participation in recreational activities in areas with low income levels was less due to facility costs [48]. When the results were analyzed according to the weekly leisure time of the participants, significant differences were found in the individual psychology, lack of information and facility, which are sub-scales of the leisure constraints scale. In the individual psychology and lack of information sub-scales, the highest constraint score is reached in individuals who do not have enough free time each week (6–10 h). Since leisure time activities have positive effects on the mental health of the individual [49,50,51], participants with sufficient leisure time are thought to have lower scores of individual psychological barriers than other participants. It was thought that the constraints score for lack of information sub-scale was high in participants with limited free time, which might have been because attendees did not attend recreation education due to lack of time.

When the ANOVA analysis results were analyzed according to the welfare level of the participants, it was determined that scale of leisure constraints had a significant difference in the lack of friends sub-scale. As the level of welfare declines, it is seen that the barrier scores for lack of friends sub-scale increased. There were significant differences in individual psychology, lack of information, time, lack of interest, and facility sub-scales in some studies conducted in the related literature [41,52]. In some studies, it has been found that the level of income for participation in recreational activities is significant. It can be said that the living standards of the individuals with high income level increase directly or indirectly [19,21,53]. It is seen that the results in related literature do not show similar results with this study. It is suggested that this is because other studies are applied to age groups that are different from the age groups applied in this study. When results were analyzed according to participants’ sporting situations, it was determined that there was no significant difference in individual psychology, lack of information, lack of time, and lack of interest, which are sub-scales of leisure constraints scales. The study conducted by Alexandris and Carroll (1997) on university students is the result of a lack of knowledge by participants of sporting events [20]. In the study conducted by Soyer et al. (2017), there was a significant difference in the lack of interest sub-scale of leisure constraints scale [54]. In the study carried out by Emir (2012), there was a significant difference between the individual psychology and lack of interest sub-scales of the leisure time scale [55]. The results in the relevant studies do not seem to match the results of this study in terms of the relevant variables. According to the results of this research, women participants seem to be much more constrained than men. Therefore, to remove these obstacles, the following should be provided: (i) enough information about leisure activities with women participants; (ii) the necessary facilities by various institutions to achieve female participation regularly; and (iii) to give the opportunity for families to participate in these activities.

5. Conclusions

The barrier that participants experience to their leisure time is increasing towards the eastern regions. In the regions located in the east, increasing the number of necessary facilities, raising awareness of the mental and physical benefits of leisure activities of the people in the community, and raising awareness in this regard can significantly reduce the factors that prevent individuals from participating in leisure activities. This study was applied to a large audience in Turkey, regarding the reduction or elimination of constraints to participation in recreational activities. In particular, the literature will contribute to increasing recreational facilities, making them more accessible, and enabling all segments of society to benefit from these activities.