The Dark Side of Leisure Time: Analysis of the Predictive Effects Between Boredom, Internet Usage Habits, and Gambling Behaviors
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Study Design and Procedures
2.3. Assessment Tools
- The Leisure Boredom Scale (LBS), a standardized questionnaire developed by Iso-Ahola and Weissinger (1990) [27], measures individual differences in boredom perception during leisure time. The validity and reliability study of the Turkish version for adult adaptation was conducted by Kara, Gürbüz, and Öncü (2014) [28]. The Turkish version used in this study consists of 10 items targeting two subdimensions, each containing 5 items. The “Boredom” subdimension reflects an individual’s negative attitude toward leisure activities (e.g., “I usually don’t enjoy what I do in my leisure time, but I don’t know what else to do”). Conversely, the “Satisfaction” subdimension showcases an individual’s positive perspective on leisure time (e.g., “The idea of leisure time excites me” or “Leisure time energizes me”). A 5-point Likert scale was employed to evaluate responses, ranging from (1) “strongly disagree” to (5) “strongly agree”, with (3) representing “neither agree nor disagree.” The Cronbach’s alpha coefficient for internal consistency of the scale in this study was calculated to be 0.74.
- The Leisure Internet Usage Scale (LIUS), developed by Şimşek and Çevik [29], was employed in this study. The dimensions of the LIUS were designed by considering leisure activities viewed as enjoyable forms of internet use (e.g., information and personal development, shopping, multimedia sources, and social interaction). It includes items that cover the factors influencing these usage patterns. The scale is a 5-point Likert-type scale, where (1) means “strongly disagree” and (5) means “strongly agree”, with (3) indicating “neither agree nor disagree”, and consists of 4 dimensions with a total of 16 items. In this study, the Cronbach’s alpha coefficient for the internal consistency of the scale was calculated to be 0.72.
- The Gambling Motives Scale, developed by Lee et al. (2007) [30], was utilized to understand participants’ motivations for gambling. This scale employs a 5-point Likert-type format ranging from (1) “strongly disagree” to (5) “strongly agree”, with (3) indicating “neither agree nor disagree.” It assesses four subdimensions of gambling motivation: socialization, entertainment/excitement, escapism, and money-making. The scale comprises a total of 35 items, and scores in each subdimension reflect individuals’ attitudes toward that specific motivation. The Turkish adaptation of the scale was conducted by Arcan and Karancı [31]. The Cronbach’s alpha coefficient for internal consistency of the scale in this study was calculated to be 0.94.
2.4. Data Analysis
3. Results
4. Discussion
4.1. Limitations and Future Directions of the Study
4.2. The Practical Implications of the Study
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Scale | Factor | Gender | n | X | SD | t | p |
---|---|---|---|---|---|---|---|
Leisure Boredom | Boredom | Female | 96 | 2.42 | 0.815 | 0.274 | 0.78 |
Male | 214 | 2.40 | 0.767 | ||||
Satisfaction | Female | 96 | 3.66 | 0.617 | 2.218 | 0.03 * | |
Male | 214 | 3.48 | 0.716 | ||||
Leisure Internet Usage | Social İnteraction | Female | 96 | 3.58 | 0.827 | 2.594 | 0.01 * |
Male | 214 | 3.31 | 0.864 | ||||
Shopping | Female | 96 | 3.19 | 0.896 | 6.158 | 0.00 * | |
Male | 214 | 2.50 | 0.922 | ||||
Multimedia Usage | Female | 96 | 3.44 | 0.831 | 5.144 | 0.00 * | |
Male | 214 | 2.89 | 0.886 | ||||
İnformation/Self-improvement | Female | 96 | 3.74 | 0.708 | −1.671 | 0.09 | |
Male | 214 | 3.88 | 0.687 | ||||
Gambling Motives | Amusement/Excitement | Female | 96 | 2.16 | 0.919 | −0.569 | 0.56 |
Male | 214 | 2.23 | 0.948 | ||||
Avoidance | Female | 96 | 1.98 | 0.869 | −0.129 | 0.89 | |
Male | 214 | 1.99 | 0.833 | ||||
Monetary Gains | Female | 96 | 2.06 | 0.939 | 0.635 | 0.52 | |
Male | 214 | 1.99 | 0.856 | ||||
Socialization | Female | 96 | 2.10 | 0.956 | −1.095 | 0.27 | |
Male | 214 | 2.23 | 0.925 |
Scale | Factor | Leisure Type | N | Mean | SD | F | p |
---|---|---|---|---|---|---|---|
Leisure Boredom | Boredom | Rest | 99 | 2.73 | 0.875 | 14.118 | 0.00 * |
Physical Activity | 83 | 2.33 | 0.705 | ||||
Social/Cultural Activity | 128 | 2.21 | 0.669 | ||||
Rest | 99 | 3.40 | 0.614 | 2.828 | 0.06 | ||
Satisfaction | Physical Activity | 83 | 3.61 | 0.728 | |||
Social/Cultural Activity | 128 | 3.60 | 0.712 | ||||
Leisure Internet Usage | Social İnteraction | Rest | 99 | 3.64 | 0.827 | ||
Physical Activity | 83 | 3.19 | 0.852 | 6.892 | 0.00 * | ||
Social/Cultural Activity | 128 | 3.33 | 0.853 | ||||
Shopping | Rest | 99 | 3.04 | 0.947 | |||
Physical Activity | 83 | 2.71 | 0.926 | 10.530 | 0.00* | ||
Social/Cultural Activity | 128 | 2.46 | 0.940 | ||||
Multimedia Usage | Rest | 99 | 3.37 | 0.895 | 10.279 | 0.00 * | |
Physical Activity | 83 | 3.04 | 0.943 | ||||
Social/Cultural Activity | 128 | 2.84 | 0.819 | ||||
İnformation/Self-improvement | Rest | 99 | 3.78 | 0.726 | 4.182 | 0.01 * | |
Physical Activity | 83 | 3.70 | 0.707 | ||||
Social/Cultural Activity | 128 | 3.96 | 0.645 | ||||
Gambling Motives | Amusement/Excitement | Rest | 99 | 2.22 | 1.032 | 1.568 | 0.21 |
Physical Activity | 83 | 2.34 | 0.975 | ||||
Social/Cultural Activity | 128 | 2.11 | 0.828 | ||||
Avoidance | Rest | 99 | 2.14 | 0.978 | 5.243 | 0.00 * | |
Physical Activity | 83 | 2.07 | 0.866 | ||||
Social/Cultural Activity | 128 | 1.81 | 0.671 | ||||
Monetary Gains | Rest | 99 | 2.08 | 0.969 | 4.956 | 0.00 * | |
Physical Activity | 83 | 2.21 | 0.945 | ||||
Social/Cultural Activity | 128 | 1.84 | 0.729 | ||||
Socialization | Rest | 99 | 2.18 | 1.027 | 2.043 | 0.13 | |
Physical Activity | 83 | 2.36 | 0.959 | ||||
Social/Cultural Activity | 128 | 2.09 | 0.832 |
Scale | Factor | Age | N | Mean | SD | F | p |
---|---|---|---|---|---|---|---|
Leisure Boredom | Boredom | 30 years old and under | 108 | 2.59 | 0.854 | 5.008 | 0.00 * |
Between 31 and 45 years old | 71 | 2.37 | 0.885 | ||||
46 years old and above | 130 | 2.27 | 0.619 | ||||
30 years old and under | 108 | 3.65 | 0.604 | 3.070 | 0.04 | ||
Satisfaction | Between 31 and45 years old | 71 | 3.59 | 0.760 | |||
46 years old and above | 130 | 3.44 | 0.685 | ||||
Leisure Internet Usage | Social İnteraction | 30 years old and under | 108 | 3.81 | 0.696 | ||
Between 31 and 45 years old | 71 | 3.32 | 0.838 | 24.181 | 0.00 * | ||
46 years old and above | 130 | 3.09 | 0.854 | ||||
Shopping | 30 years old and under | 108 | 3.17 | 0.866 | |||
Between 31 and 45 years old | 71 | 2.90 | 0.933 | 35.419 | 0.00 * | ||
46 years old and above | 130 | 2.24 | 0.840 | ||||
Multimedia Usage | 30 years old and under | 108 | 3.68 | 0.717 | 65.917 | 0.00 * | |
Between 31 and 45 years old | 71 | 3.08 | 0.796 | ||||
46 years old and above | 130 | 2.55 | 0.770 | ||||
İnformation/Self-improvement | 30 years old and under | 108 | 3.82 | 0.689 | 2.574 | 0.07 | |
Between 31 and 45 years old | 71 | 3.99 | 0.620 | ||||
46 years old and above | 130 | 2.95 | 0.726 | ||||
Gambling Motives | Amusement/ Excitement | 30 years old and under | 108 | 2.53 | 0.985 | 10.197 | 0.00 * |
Between 31 and 45 years old | 71 | 2.00 | 1.000 | ||||
46 years old and above | 130 | 2.05 | 0.793 | ||||
Avoidance | 30 years old and under | 108 | 2.30 | 0.975 | 12.158 | 000 * | |
Between 31 and 45 years old | 71 | 1.82 | 0.841 | ||||
46 years old and above | 130 | 1.82 | 0.636 | ||||
Monetary Gains | 30 years old and under | 108 | 2.42 | 0.964 | 19.893 | 0.00 * | |
Between 31 and 45 years old | 71 | 1.83 | 0.863 | ||||
46 years old and above | 130 | 1.78 | 0.688 | ||||
Socialization | 30 years old and under | 108 | 2.45 | 1.018 | 6.732 | 0.00 * | |
Between 31 and 45 years old | 71 | 2.00 | 0.949 | ||||
46 years old and above | 130 | 2.08 | 0.809 |
Variables | Leisure Boredom | Leisure Internet Usage | Gambling Motives | |
---|---|---|---|---|
Leisure Boredom | r | 1 | 0.335 ** | 0.379 ** |
p | 0.001 | 0.001 | ||
Leisure Internet Usage | r | 0.335 ** | 1 | 0.330 ** |
p | 0.001 | 0.001 | ||
Gambling Motives | r | 0.379 ** | 0.330 ** | 1 |
p | 0.001 | 0.001 |
Model | B | SD | β | T | p | Binary | Partial | Tolerance | VIF | Durbin–Watson |
---|---|---|---|---|---|---|---|---|---|---|
Constant | −0.617 | 0.326 | −1.893 | 0.059 | 1.690 | |||||
Leisure Boredom | 0.577 | 0.104 | 0.303 | 5.550 | 0.001 | 0.379 | 0.302 | 0.888 | 1.127 | |
Leisure Internet Usage | 0.311 | 0.074 | 0.229 | 4.201 | 0.001 | 0.330 | 0.233 | 0.888 | 1.127 | |
R = 0.436, R2 = 0.190 F = 36.101, p < 0.001 |
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Emir, E.; Akça, E.; Badau, A.; Badau, D. The Dark Side of Leisure Time: Analysis of the Predictive Effects Between Boredom, Internet Usage Habits, and Gambling Behaviors. Brain Sci. 2025, 15, 598. https://doi.org/10.3390/brainsci15060598
Emir E, Akça E, Badau A, Badau D. The Dark Side of Leisure Time: Analysis of the Predictive Effects Between Boredom, Internet Usage Habits, and Gambling Behaviors. Brain Sciences. 2025; 15(6):598. https://doi.org/10.3390/brainsci15060598
Chicago/Turabian StyleEmir, Esra, Elif Akça, Adela Badau, and Dana Badau. 2025. "The Dark Side of Leisure Time: Analysis of the Predictive Effects Between Boredom, Internet Usage Habits, and Gambling Behaviors" Brain Sciences 15, no. 6: 598. https://doi.org/10.3390/brainsci15060598
APA StyleEmir, E., Akça, E., Badau, A., & Badau, D. (2025). The Dark Side of Leisure Time: Analysis of the Predictive Effects Between Boredom, Internet Usage Habits, and Gambling Behaviors. Brain Sciences, 15(6), 598. https://doi.org/10.3390/brainsci15060598