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Are Computer, Video and Arcade Games Affecting Children's Behavior? |
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An Empirical Study |
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Larry D. Rosen, Ph.D. |
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California State University, Dominguez Hills & Byte Back, LLC |
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Michelle M. Weil, Ph.D. |
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Human-Ware, LLC |
Overview
STUDY 1: A sample of 914 young people, aged 10 through 25 were surveyed in Southern California. The survey form consisted of four major sections:
Sample Demographics
STUDY 1
The sample consisted of 914 young residents of Southern California. Ninety-two upper division students at a local state university recruited 10 young residents each, 5 male and 5 female, living in their local neighborhood. Given that the student population has been seen to represent the local Southern California area in other studies, there is strong reason to assume that we have collected data on a cross-section of this area. For reasons of anonymity for the portion of the sample under 18, it was decided not to ask any items about ethnic background. It is, however, assumed from previous studies of the same area that the population is multi-ethnic in its makeup.
The sample reflected nearly equal numbers of male (n=452) and female (n=454) subjects (eight subjects neglected to indicate gender) and a mean age of nearly 18 years (17.91). The majority (56%) lived with both mother and father in the home, while 17% lived with the mother only, 4% lived with their father only and 14% lived on their own. An additional 9% had some other living arrangement.
Instructions indicated that the ADHD Rating Scale was to be completed by “someone who knows the subject of this study.” Overall, these responses were collapsed into two groupings: close relative (parent or spouse) and friend (roommate, friend and other). In all, 35% of the ADHD Rating Scales were completed by close relatives and the reminder by friends.
STUDY 2
The sample included 682 young residents of the Southern California area. Seventy-five upper division students at the same university as in Study 1 recruited 10 young residents each, 5 male and 5 female, living in their neighborhood. The sample reflected equal percentages of males and females with a mean age of 13.46. Ages were further divided into ages 7-9 (n=68), ages 10-12 (n=194) and ages 13-17 (420). Ethnic backgrounds included Black/African American (25%), Asian-American (16%), Caucasian (20%), Hispanic (28%) and Other, Don't Know or missing (11%).
Results -- Study 1
What Entertainment Technologies do Young People Use?
Each young person was asked to rate his/her use of entertainment technologies on two separate scales. Based on a high correlation between these items from the two scales, it was decided to keep just the scale which indicated the number of hours per day each technology was used. These items were subjected to a Factor Analysis which indicated that young people used three separate categories of entertainment technology:
How Much Do Young People Use Entertainment Technologies Each Day?
The following table shows the hours played on a daily basis by three different age groups: Pre-Teens (10-12), teens (13-17) and young adults (18-25).
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TYPE OF ENTERTAINMENT TECHNOLOGY |
HOURS PER DAY |
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Pre-Teens 10 – 12 years old |
Teens 13-17 years old |
Young
Adults 18
– 25 years old |
| GAMES: |
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| Computer Games |
1 |
1 |
.5 |
| Games Attached to an Television Set |
1 |
1 |
.5 |
| Handheld Games |
1 |
0 |
.5 |
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|
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TOTAL HOURS PER DAY PLAYING GAMES -----> |
3 hours per day |
2 hours per day |
1.5 hours per day |
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| INTERNET: | |||
| World Wide Web Surfing |
.5 |
1 |
1 |
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.5 |
1 |
1 |
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TOTAL HOURS PER DAY USING THE INTERNET-----> |
1 hour per day |
2 hours per day |
2 hours per day |
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|
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| ENTERTAINMENT: | |||
| Television |
3.5 |
3.5 |
2 |
| Music |
2 |
3.5 |
3.5 |
| Telephone |
1 |
2 |
2 |
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TOTAL HOURS PER DAY USING TECHNOLOGY FOR ENTERTAINMENT-----> |
6.5 hours per day |
9 hours per day |
7.5 hours per day |
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TOTAL HOURS PER DAY USING ALL ABOVE TECHNOLOGIES*-----> |
10.5 hours per day |
13 hours per day |
11 hours per day |
Several findings are evident from the table above.
Given that both groups must sleep and that Pre-Teens and Teens must go to school, it is amazing that so much of their day is occupied with technology. It must be noted, however, that many of the subjects are engaging in multiple activities at the same time so the actual total time is not the sum of the three activity times.
Who Uses Technology More or Less?
The following indicates the statistically significant differences when boys and girls in the three different age groups were compared:
How Do Young People Feel About Technology?
An item on the Demographic survey asked how the young people felt about new technology. This item is the same as one used in Rosen and Weil’s 49-Month Study of Business Attitudes Toward Technology. The survey item generates a categorization of the subject as either an Eager Adopter, Hesitant “Prove It,” or Resister as described in the business study referred to above. Results indicated that there was no difference between age groups on attitudes toward technology, but the chart below show the differences in attitude toward technology between males and females. Girls tended to be Hesitant "Prove Its" while boys were equally split between Eager Adopters and Hesitant "Prove Its." These results were the same for each age group.
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GENDER |
Eager Adopters |
Hesitant “Prove Its” |
Resisters |
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Male |
43% |
49% |
8% |
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Female |
19% |
69% |
11% |
How Do Technology Use and Attitude Toward Technology Relate to Behavior?
The Attitude About Using Technology survey yielded a reasonable reliability index (Cronbach's alpha = .71) as did the Misbehavior Scale (alpha = .93). A correlation was then computed between these two scales and games, Internet and Entertainment use with the following results:
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BOYS AND GIRLS |
Playing Games |
Surfing the Internet |
Using Entertainment Technologies |
| Misbehavior | |||
ALL BOYS AND GIRLS: |
.27*** |
.08* |
.09** |
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.23* |
ns |
.20* |
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.14* |
-.16* |
ns |
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.16* |
ns |
ns |
|
ns |
ns |
ns |
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.25** |
ns |
.27** |
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.14* |
ns |
ns |
| Attitudes Toward Technology | |||
| ALL BOYS AND GIRLS: |
-.15*** |
-.10*** |
.09** |
|
ns |
-.17* |
ns |
|
ns |
ns |
.21** |
|
ns |
-.15** |
.13* |
|
ns |
ns |
ns |
|
ns |
-.17* |
ns |
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-.16** |
-.14* |
ns |
| *p<.05, **p<.01, ***p<.001 | |||
The table above clearly shows that:
The survey for Study 1 also asked about the relationship between the person completing the form and the subject. These were divided into close relatives (father, mother, spouse) and all others (friend, roommate, other). When the correlations for the close relatives are computed, the data in the top half of the table above becomes even more striking as seen below:
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BOYS AND GIRLS |
Playing Games |
Surfing the Internet |
Using Entertainment Technologies |
| Misbehavior | |||
ALL BOYS AND GIRLS: |
.31*** |
ns |
.18*** |
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.24* |
-29* |
.26* |
|
ns |
ns |
ns |
|
ns |
ns |
ns |
|
.32* |
ns |
ns |
|
.28* |
ns |
.37** |
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.40*** |
ns |
ns |
| *p<.05, **p<.01, ***p<.001 | |||
According to the table above, when you only examine the misbehavior ratings completed by someone close to the subject, the following striking results emerge:
What Best Predicts Misbehavior?
We have established the role of several variables in relationship to misbehavior. In this section we examine which of these is/are most important in predicting misbehavior. A Hierachrical Multiple Regression was performed with age, gender, attitudes toward computers, and relationship to subject entered first. Next, playing games, surfing the Internet and using entertainment technologies were entered to determine if any of them could add a significant predictability.
Results indicated that each of these 7 variables did indeed predict who would misbehave more. However, more telling, when the games, Internet and entertainment technologies were added last, they each added a unique, statistically significant prediction of misbehavior. Overall, the beta weights are listed in the table below. Beta weights show the relative predictability of each variable and as seen, age is the top predictor of misbehavior, followed by game playing and attitudes toward technology and gender.
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PREDICTOR OF MISBEHAVIOR |
BETA WEIGHT |
| Age |
-.20*** |
| Game Playing |
.16*** |
| Attitudes Toward Technology |
.15*** |
| Gender |
-.13*** |
| Relationship to Subject |
.08* |
| Using Entertainment Technologies |
.08* |
| Surfing the Internet |
.07* |
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| *p<.05, **p<.01, ***p<.001 | |
What Computer and Video Games Do Children Play?
Among many variables, this study investigated several indices of computer and video game playing among boys and girls ages 7 to 17. One question asked the subject to identify his or her favorite computer game (played at a computer that has a keyboard) and favorite video game (including handheld games, games attached to television sets or arcade games). The list of the most popular favorite games can be found in the table below:
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FAVORITE GAMES |
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COMPUTER GAMES |
VIDEO GAMES |
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Solitaire and card games (n=106) |
Super Mario (n=67) |
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Math Blaster (n=19) |
Tony Hawk (n=39) |
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Starcraft (n=17) |
Pokemon (n=28) |
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Sims (n=14) |
World Wrestling Federation (n=23) |
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Quake (n=13) |
NFL Football (n=23) |
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Tetris (n=13) |
Mario Racers (n=14) |
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Pinball (n=12) |
Crash Bandicot (n=14) |
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Diablo (n=11) |
Mortal Kombat (n=14) |
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Doom (n=10) |
Street Fighter (n=13) |
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PacMan (n=8) |
James Bond (n=13) |
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Carmen San Diego (n=8) |
Tetris (n=13) |
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Roller Coaster Tycoon (n=8) |
Pac Man, Sonic Hedgehog and Marvel vs. .... (all n=13) |
The Video Game Rating Act of 1994 established a commission to provide a rating system for video and computer games unless the game industry established a voluntary system with one year. Since that time, two ratings systems have been established. The Entertainment Software Rating Board (ESRB) produced a system in which game products are evaluated by independent raters. A rater can assign one of five categories:
A second rating system has been created by the Recreational Software Advisory Council (RSAC), a nonprofit organization, which rated each product on a 0 (lowest) to 4 (highest)in three areas: (1) violence, (2) nudity/sex, and (3) language.
Since the ratings done by the ESRB are indexed by age, it seemed more appropriate to categorize computer and video games by that system. Overall, 64% of the subjects listed a computer game as their favorite and 72% listed a favorite video game. The tables below show the breakdown across all age groups and then within each age group for computer games (first table) and video games (second table). Note that the age breakdown is 7-12 and 13-16 (not 17 as in Study 1) since these fit the ESRB ratings system and that the squares marked with red indicate children listing their favorite game as one that is not appropriate for their ages.
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AGE GROUP |
ESRB RATINGS OF COMPUTER GAMES |
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ALL SUBJECTS |
73% |
14% |
13% |
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BOYS 7-12 |
71% |
14% |
14% |
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BOYS 13-16 |
43% |
31% |
26% |
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GIRLS 7-12 |
96% |
3% |
1% |
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GIRLS 13-16 |
86% |
12% |
2% |
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AGE GROUP |
ESRB RATINGS OF VIDEO GAMES |
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ALL SUBJECTS |
60% |
31% |
9% |
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BOYS 7-12 |
59% |
30% |
12% |
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BOYS 13-16 |
47% |
43% |
10% |
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GIRLS 7-12 |
86% |
12% |
2% |
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GIRLS 13-16 |
59% |
30% |
11% |
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Noting the boxes in red, results indicate that:
Overall, it is apparent that, particularly boys, and more specifically young boys, are playing computer and video games that are age inappropriate.
What Activities Do Young Boys and Girls Enjoy?
A 12-question survey asked these young children and teenagers to rate various activities on a "fun" scale from 0 (no fun at all) to 100 (the most fun possible). The table below shows the data for all subjects and then lists the the TOP 5 for each gender and age group.
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ALL SUBJECTS |
TOP 5 CHOICES |
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YOUNG BOYS |
TEEN BOYS |
YOUNG GIRLS |
TEEN GIRLS |
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Watching Television |
Playing Video Games |
Playing Sports |
Playing Video Games |
Talking on the Telephone |
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Playing Video Games |
Playing Sports |
Playing Video Games |
Reading a Book |
Watching Television |
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Playing Sports |
Watching Television |
Watching Television |
Watching Television |
Reading a Book |
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Talking on the Telephone |
Playing Computer Games |
Surfing the Internet |
Talking on the Telephone |
Surfing the Internet |
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Surfing the Internet |
Surfing the Internet |
Talking on the Telephone |
Playing Sports |
Sending/Receiving E-Mail |
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Reading a Book |
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Playing Computer Games |
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Sending/Receiving E-Mail |
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Being in Class at School |
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Writing With Pen or Pencil |
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Writing With Word Processor |
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Reading a Computer Screen |
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The table above clearly indicates that
Who Starts Using Computers at a Younger Age?
One item on the questionnaire for this study asked at what age did the subject first use a computer. A two-way Analysis of Variance was conducted to determine whether there were any age or gender differences. Results indicated that both boys and girls had their first computer experiences at 8 years old. Further, there were no differences between boys and girls at any age group.
However, there were striking differences between age groups. 7 to 9 year olds had their first computer experience at 5.9 years of age which was not different from 10-12 year olds (6.5 years). Both these groups started using computers at a much younger age then the Teens who started at 9 years old. This is quite a difference and most likely parallels that rapid rise of computer and video games for children, teens and young adults.
Summary and Conclusions
Major conclusions can be drawn from the following areas in this study:
Overall, this study supported the common notion that children, teens and young adults are using technology for entertainment. Several controversial findings emerged.
Increased computer and video game playing was related to increased misbehavior. Why do young people, who appear to be able to "attend" for hours in front of a video game, find it so difficult to attend in class? The simple answer lies in the environment. A video game or computer game is fast-paced, interactive and enticing. Kids are literally drawn in to the environment and then captured by its "holding power" (Turkle, 1984). In fact, we adults suffer from the same problem. How often do we say to our loved one, "I'll just be a minute. I've got to check my e-mail (or stocks, or the Internet, or whatever draws us to the computer) only to have hours pass by until we resurface?
For children, this "holding power" is so positive that they find the school environment has what we refer
to as "disengaging power." School, with its focus on group and individual paper-and-pencil activities
is clearly less enticing than the video game environment that the child plays many hours per day. Thus, the child
removes him/herself from the task through a process called disengaging. Literally, the child seeks a different
environment, one that more nearly approximates the richness of their computer game world. For many, that world
exists inside the mind. For others, there is no such world available during school time so one of frenetic activity
is created instead.
This study has also given us a hint about what environment might be used in the school to avoid having the child
disengage. Since Internet and World Wide Web use was related to increased good behavior, we might assume that an
environment, patterned after web pages, would help entice children and keep them interested. With increased use
of animation and interactive web participation, children could just as easily be drawn into a web-like environment
as they are into a computer game and many behavioral problems could be avoided.
We welcome your comments through the links below.
© 2001 Larry D. Rosen, Ph.D. and Michelle M. Weil, Ph.D.
More information on related topics can be found at either Dr. Weil's or Dr. Rosen's web sites.
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