Risk Factors Influencing Cyberbullying Perpetration among Middle School Students in Korea: Analysis Using the Zero-Inflated Negative Binomial Regression Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Participants and Procedures
2.2. Measurements
2.3. Data Analysis
3. Results
3.1. Demographic Characteristics of the Study Participants
3.2. ZINB Model Results for the Perpetration of Cyberbullying
4. Discussion
5. Limitations and Implications
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Item No. | Content |
---|---|
1 | I have sent abusive or harsh words to another person. |
2 | I have spread bad rumors about a person to others. |
3 | I have stalked another person by sending messages, photos, etc. against that person’s will. |
4 | I have sent or secretly delivered another person’s photos, bizarre pictures, images, or videos to others against that person’s will. |
5 | I have made fake accounts by stealing another person’s ID, then portrayed myself as that person in cyberspace. |
6 | I have doxed another person by posting their personal information (e.g., name, age, school, phone number) on the Internet. |
7 | I have extorted game money, game items, and cyber money. |
8 | I have made another person do “Wi-Fi shuttles” or “hot spot shuttles” (i.e., forced them to provide cellphone data for free). |
9 | I have sent sexual messages, obscene photos, or videos against the recipient’s will. |
10 | I have stopped others from leaving Internet chatrooms or repeatedly invited others against their will. |
11 | I have led another person to curse first or made that person appear to have personality issues by deliberately starting a quarrel. |
12 | I have used my smartphone to make another person do things against their will or force them to run (cigarette) errands. |
13 | I have made public online posts to attack another person. |
14 | I have made intensive attacks on another person in cyberspace. |
15 | I have intentionally refused to invite someone to a chatroom or ignored their comments or messages. |
N (%) | Mean (SD) | Range | ||
---|---|---|---|---|
Age | 13.00 (0.13) | 12–14 | ||
Gender Female | 1185 (45.8%) | |||
Male | 1405 (54.2%) | |||
Perceived Economic Status | ||||
Low | 349 (13.4%) | |||
Medium | 1972 (76.3%) | |||
High | 264 (10.2%) | |||
Cyberbullying Perpetration | 1.23 (2.46) | 0–22 | ||
Offline Delinquency | 0.74 (2.24) | 0–38 | ||
Aggression | 11.50 (3.54) | 6–24 | ||
Depression | 17.99 (6.38) | 10–40 | ||
Social Withdrawal | 10.76 (3.75) | 5–20 | ||
Self-Esteem | 29.94 (5.04) | 11–40 | ||
Smartphone Dependency | 30.59 (7.32) | 15–60 | ||
Technology usage | Smartphone Usage on Weekdays | |||
Less than 1 h | 642 (24.8%) | |||
1–3 h | 1409 (54.4%) | |||
Over 3 h | 539 (20.8%) | |||
Smartphone Usage on Weekends | 438 (16.9%) | |||
1–3 h | 1112 (42.9%) | |||
Over 3 h | 1040 (40.2%) | |||
Computer Usage on Weekdays | ||||
Less than 1 h | 1935 (74.7%) | |||
1–3 h | 538 (20.8%) | |||
Over 3 h | 117 (4.5%) | |||
Computer Usage on Weekends | ||||
Less than 1 h | 1497 (57.8%) | |||
1–3 h | 723 (27.9%) | |||
Over 3 h | 370 (14.3%) | |||
Positive Parenting | 39.11 (5.38) | 12–48 | ||
Negative Parenting | 23.96 (6.29) | 12–48 | ||
Relationship with Friends | 40.63 (5.62) | 15–52 | ||
School Satisfaction | ||||
Not satisfied | 360 (14.6%) | |||
Moderate | 952 (38.5%) | |||
Satisfied | 1159 (46.9%) | |||
Perceived Academic Achievement | ||||
Low | 174 (13.0%) | |||
Medium | 497 (37.2%) | |||
High | 666 (49.8%) |
Count Model | Logit Model | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
β | SE | z | p > |z| | 95% CI | β | SE | z | p > |z| | 95% CI | ||
Gender (ref. female) | |||||||||||
Male | −0.006 | 0.092 | −0.07 | 0.944 | −0.186, 0.173 | −0.330 | 0.168 | −1.97 | 0.049 | −0.660, −0.001 | |
Perceived Economic Status (ref. low) | |||||||||||
Medium | 0.046 | 0.102 | 0.45 | 0.650 | 0.154, 0.247 | −0.198 | 0.208 | −0.96 | 0.339 | −0.605, 0.208 | |
High | 0.043 | 0.149 | 0.29 | 0.772 | −0.249, 0.335 | 0.303 | 0.297 | −1.02 | 0.307 | −0.885, 0.279 | |
Offline Delinquency | 0.089 | 0.011 | 8.31 | <0.001 | 0.068, 0.110 | −1.371 | 0.208 | −5.06 | <0.001 | −1.902, −0.840 | |
Aggression | 0.050 | 0.012 | 3.97 | <0.001 | 0.025, 0.074 | −0.109 | 0.026 | −4.24 | <0.001 | −0.159, −0.058 | |
Depression | 0.002 | 0.009 | 0.26 | 0.798 | −0.016, 0.020 | −0.029 | 0.018 | −1.57 | 0.117 | −0.065, 0.007 | |
Social Withdrawal | −0.016 | 0.011 | −1.52 | 0.129 | −0.038, 0.005 | 0.029 | 0.023 | 1.29 | 0.196 | −0.0151, 0.074 | |
Self-Esteem | −0.016 | 0.010 | −1.48 | 0.138 | −0.036, 0.005 | −0.015 | 0.021 | −0.72 | 0.471 | −0.056, 0.026 | |
Smartphone Dependency | 0.014 | 0.006 | 2.48 | 0.013 | 0.003, 0.025 | −0.019 | 0.011 | −1.66 | 0.096 | −0.041, 0.003 | |
Technology usage | Smartphone Usage on Weekdays (ref. less than 1 h) | ||||||||||
1–3 h | −0.025 | 0.120 | −0.21 | 0.83 | −0.261, 0.211 | −0.643 | 0.211 | −3.04 | 0.002 | −1.057, −0.229 | |
Over 3 h | 0.105 | 0.145 | 0.72 | 0.470 | −0.179, 0.0389 | −0.354 | 0.270 | −1.31 | 0.191 | −0.883, 0.176 | |
Smartphone Usage on Weekends (ref. less than 1 h) | |||||||||||
1–3 h | 0.669 | 0.146 | 4.57 | <0.001 | 0.382, 0.955 | 0.589 | 0.274 | 2.16 | 0.320 | 0.051, 1.124 | |
Over 3 h | 0.673 | 0.153 | 4.40 | <0.001 | 0.373, 0.974 | 0.278 | 0.296 | 0.94 | 0.348 | −0.303, 0.859 | |
Computer Usage on Weekdays (ref. less than 1 h) | |||||||||||
1–3 h | 0.031 | 0.099 | 0.31 | 0.757 | −0.163, 0.225 | 0.083 | 0.220 | 0.38 | 0.706 | −0.349, 0.515 | |
Over 3 h | 0.129 | 0.169 | 0.76 | 0.446 | −0.203, 0.461 | 0.439 | 0.374 | 1.17 | 0.240 | −0.294, 1.171 | |
Computer Usage on Weekends (ref. less than 1 h) | |||||||||||
1–3 h | −0.136 | 0.101 | −1.35 | 0.178 | −0.334, 0.062 | −0.430 | 0.207 | −2.08 | 0.038 | −0.836, −0.024 | |
Over 3 h | 0.121 | 0.119 | 1.02 | 0.309 | −0.112, 0.355 | −0.379 | 0.277 | −1.37 | 0.171 | −0.921, 0.163 | |
Positive Parenting | 0.006 | 0.007 | 0.90 | 0.368 | −0.007, 0.020 | −0.004 | 0.015 | −0.28 | 0.776 | −0.034, 0.025 | |
Negative Parenting | 0.001 | 0.007 | 0.21 | 0.835 | −0.012, 0.015 | −0.029 | 0.015 | −2.00 | 0.046 | −0.058, −0.001 | |
Relationship with Friends | 0.007 | 0.007 | 0.91 | 0.362 | −0.008, 0.021 | −0.024 | 0.015 | −1.64 | 0.101 | −0.054, 0.005 | |
School Satisfaction (ref. not satisfied) | |||||||||||
Moderate | −0.133 | 0.160 | −0.83 | 0.407 | −0.448, 0.182 | −0.182 | 0.351 | −0.52 | 0.604 | −0.870, 0.506 | |
Satisfied | −0.158 | 0.150 | −1.05 | 0.293 | −0.453, 0.137 | −0.388 | 0.335 | −1.16 | 0.246 | −1.044, 0.268 | |
Perceived Academic Achievement (ref. low) | |||||||||||
Medium | 0.050 | 0.106 | 0.48 | 0.634 | −0.157, 0.258 | 0.196 | 0.224 | 0.87 | 0.382 | −0.244, 0.636 | |
High | 0.184 | 0.106 | 1.73 | 0.084 | −0.025, 0.392 | 0.090 | 0.226 | 0.040 | 0.690 | −0.353, 0.533 |
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Kang, K.I.; Kang, K.; Kim, C. Risk Factors Influencing Cyberbullying Perpetration among Middle School Students in Korea: Analysis Using the Zero-Inflated Negative Binomial Regression Model. Int. J. Environ. Res. Public Health 2021, 18, 2224. https://doi.org/10.3390/ijerph18052224
Kang KI, Kang K, Kim C. Risk Factors Influencing Cyberbullying Perpetration among Middle School Students in Korea: Analysis Using the Zero-Inflated Negative Binomial Regression Model. International Journal of Environmental Research and Public Health. 2021; 18(5):2224. https://doi.org/10.3390/ijerph18052224
Chicago/Turabian StyleKang, Kyung Im, Kyonghwa Kang, and Chanhee Kim. 2021. "Risk Factors Influencing Cyberbullying Perpetration among Middle School Students in Korea: Analysis Using the Zero-Inflated Negative Binomial Regression Model" International Journal of Environmental Research and Public Health 18, no. 5: 2224. https://doi.org/10.3390/ijerph18052224