Control ( 20)
The training period was 4–24 weeks (mean = 11.49; S.D. = 6.88). One study by Lee et al. had two length periods and total hours because the study examined video game training of two types. The total training hours were 16–90 h (mean = 40.63; S.D. = 26.22), whereas the training intensity was 1.5–10.68 h/week (mean = 4.96; S.D. = 3.00). One study did not specify total training hours. Two studies did not specify the training intensity. The training periods and intensities are in Table 8 .
Periods and intensities of video gaming intervention.
Author | Year | Length (Week) | Total Hours | Average Intensity (h/Week) |
---|---|---|---|---|
Gleich et al. [ ] | 2017 | 8 | 49.5 | 6.2 |
Haier et al. [ ] | 2009 | 12 | 18 | 1.5 |
Kuhn et al. [ ] | 2014 | 8 | 46.88 | 5.86 |
Lorenz et al. [ ] | 2012 | 8 | 28 | 3.5 |
Lee et al. [ ] | 2015 | 8–11 * | 27 | n/a |
Martinez et al. [ ] | 2013 | 4 | 16 | 4 |
Roush [ ] | 2013 | 24 | ns | n/a |
West et al. [ ] | 2017 | 24 | 72 | 3 |
West et al. [ ] | 2018 | 8.4 | 90 | 10.68 |
The training length was converted into weeks (1 month = 4 weeks). ns, not specified; n/a, not available; * exact length is not available.
Of nine eligible studies, one study used resting-state MRI analysis, three studies (excluding that by Haier et al. [ 40 ]) used structural MRI analysis, and five studies used task-based MRI analysis. A study by Haier et al. used MRI analyses of two types [ 40 ]. A summary of MRI analyses is presented in Table 9 . The related resting-state, structural, and task-based MRI specifications are presented in Table 10 , Table 11 and Table 12 respectively.
MRI analysis details of eligible studies.
MRI Analysis | Author | Year | Contrast | Statistical Tool | Statistical Method | Value |
---|---|---|---|---|---|---|
Resting | Martinez et al. [ ] | 2013 | (post- > pre-training) > (post>pre-control) | MATLAB; SPM8 | TFCE uncorrected | <0.005 |
Structural | Haier et al. * [ ] | 2009 | (post>pre-training) > (post>pre-control) | MATLAB 7; SurfStat | FWE corrected | <0.005 |
Kuhn et al. [ ] | 2014 | (post>pre-training) > (post>pre-control) | VBM8; SPM8 | FWE corrected | <0.001 | |
West et al. [ ] | 2017 | (post>pre-training) > (post>pre-control) | Bpipe | Uncorrected | <0.0001 | |
West et al. [ ] | 2018 | (post>pre-training) > (post>pre-control) | Bpipe | Bonferroni corrected | <0.001 | |
Task | Gleich et al. [ ] | 2017 | (post>pre-training) > (post>pre-control) | SPM12 | Monte Carlo corrected | <0.05 |
Haier et al. * [ ] | 2009 | (post>pre-training) > (post>pre-control) | SPM7 | FDR corrected | <0.05 | |
Lee et al. [ ] | 2012 | (post>pre-training) > (post>pre-control) | FSL; FEAT | uncorrected | <0.01 | |
Lorenz et al. [ ] | 2015 | (post>pre-training) > (post>pre-control) | SPM8 | Monte Carlo corrected | <0.05 | |
Roush [ ] | 2013 | post>pre-training | MATLAB 7; SPM8 | uncorrected | =0.001 |
* Haier et al. conducted structural and task analyses. + Compared pre-training and post-training between groups without using contrast. TFCE, Threshold Free Cluster Enhancement; FEW, familywise error rate; FDR, false discovery rate.
Resting-State MRI specifications of eligible studies.
Author | Year | Resting State | Structural | ||||||
---|---|---|---|---|---|---|---|---|---|
Imaging | TR (s) | TE (ms) | Slice | Imaging | TR (s) | TE (ms) | Slice | ||
] | 2013 | gradient-echo planar image | 3 | 28.1 | 36 | T1-weighted | 0.92 | 4.2 | 158 |
Structural MRI specifications of eligible studies.
Author | Year | Imaging | TR (s) | TE (ms) |
---|---|---|---|---|
Kuhn et al. [ ] | 2014 | 3D T1 weighted MPRAGE | 2.5 | 4.77 |
West et al. [ ] | 2017 | 3D gradient echo MPRAGE | 2.3 | 2.91 |
West et al. [ ] | 2018 | 3D gradient echo MPRAGE | 2.3 | 2.91 |
Task-Based MRI specifications of eligible studies.
Author | Year | Task | BOLD | Structural | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Imaging | TR (s) | TE (ms) | Slice | Imaging | TR (s) | TE (ms) | Slice | |||
Gleich et al. [ ] | 2017 | win–loss paradigm | T2 echo-planar image | 2 | 30 | 36 | T1-weighted | 2.5 | 4.77 | 176 |
Haier et al. [ ] | 2009 | Tetris | Functional echo planar | 2 | 29 | ns | 5-echo MPRAGE | 2.53 | 1.64; 3.5; 5.36; 7.22; 9.08 | ns |
Lee et al. [ ] | 2012 | game control | fast echo-planar image | 2 | 25 | ns | T1-weighted MPRAGE | 1.8 | 3.87 | 144 |
Lorenz et al. [ ] | 2015 | slot machine paradigm | T2 echo-planar image | 2 | 30 | 36 | T1-weighted MPRAGE | 2.5 | 4.77 | ns |
Roush [ ] | 2013 | digit symbol substitution | fast echo-planar image | 2 | 25 | 34 | diffusion weighted image | ns | ns | ns |
All analyses used 3 Tesla magnetic force; TR = repetition time; TE = echo time, ns = not specified.
This literature review evaluated the effect of noncognitive-based video game intervention on the cognitive function of healthy people. Comparison of studies is difficult because of the heterogeneities of participant ages, beneficial effects, and durations. Comparisons are limited to studies sharing factors.
Video gaming intervention affects all age categories except for the children category. The exception derives from a lack of intervention studies using children as participants. The underlying reason for this exception is that the brain is still developing until age 10–12 [ 52 , 53 ]. Among the eligible studies were a study investigating adolescents [ 40 ], six studies investigating young adults [ 41 , 42 , 43 , 47 , 49 , 51 ] and two studies investigating older adults [ 48 , 50 ].
Differences among study purposes underlie the differences in participant age categories. The study by Haier et al. was intended to study adolescents because the category shows the most potential brain changes. The human brain is more sensitive to synaptic reorganization during the adolescent period [ 54 ]. Generally, grey matter decreases whereas white matter increases during the adolescent period [ 55 , 56 ]. By contrast, the cortical surface of the brain increases despite reduction of grey matter [ 55 , 57 ]. Six studies were investigating young adults with the intention of studying brain changes after the brain reaches maturity. The human brain reaches maturity during the young adult period [ 58 ]. Two studies were investigating older adults with the intention of combating difficulties caused by aging. The human brain shrinks as age increases [ 56 , 59 ], which almost invariably leads to declining cognitive function [ 59 , 60 ].
Three beneficial outcomes were observed using MRI method: grey matter change [ 40 , 42 , 50 ], brain activity change [ 40 , 43 , 47 , 48 , 49 ], and functional connectivity change [ 41 ]. The affected brain area corresponds to how the respective games were played.
Four studies of 3D video gaming showed effects on the structure of hippocampus, dorsolateral prefrontal cortex (DLPFC), cerebellum [ 42 , 43 , 50 ], and DLPFC [ 43 ] and ventral striatum activity [ 49 ]. In this case, the hippocampus is used for memory [ 61 ] and scene recognition [ 62 ], whereas the DLPFC and cerebellum are used for working memory function for information manipulation and problem-solving processes [ 63 ]. The grey matter of the corresponding brain region has been shown to increase during training [ 20 , 64 ]. The increased grey matter of the hippocampus, DLPFC, and cerebellum are associated with better performance in reference and working memory [ 64 , 65 ].
The reduced activity of DLPFC found in the study by Gleich et al. corresponds to studies that showed reduced brain activity associated with brain training [ 66 , 67 , 68 , 69 ]. Decreased activity of the DLPFC after training is associated with efficiency in divergent thinking [ 70 ]. 3D video gaming also preserved reward systems by protecting the activity of the ventral striatum [ 71 ].
Two studies of puzzle gaming showed effects on the structure of the visual–spatial processing area, activity of the frontal area, and functional connectivity change. The increased grey matter of the visual–spatial area and decreased activity of the frontal area are similar to training-associated grey matter increase [ 20 , 64 ] and activity decrease [ 66 , 67 , 68 , 69 ]. In this case, visual–spatial processing and frontal area are used constantly for spatial prediction and problem-solving of Tetris. Functional connectivity of the multimodal integration and the higher-order executive system in the puzzle solving-based gaming of Professor Layton game corresponds to studies which demonstrated training-associated functional connectivity change [ 72 , 73 ]. Good functional connectivity implies better performance [ 73 ].
Strategy gaming affects the DLPFC activity, whereas rhythm gaming affects the activity of visuospatial working memory, emotional, and attention area. FPS gaming affects the structure of the hippocampus and amygdala. Decreased DLPFC activity is similar to training-associated activity decrease [ 66 , 67 , 68 , 69 ]. A study by Roush demonstrated increased activity of visuospatial working memory, emotion, and attention area, which might occur because of exercise and gaming in the Dance Revolution game. Results suggest that positive activations indicate altered functional areas by complex exercise [ 48 ]. The increased grey matter of the hippocampus and amygdala are similar to the training-associated grey matter increase [ 20 , 64 ]. The hippocampus is used for 3D navigation purposes in the FPS world [ 61 ], whereas the amygdala is used to stay alert during gaming [ 74 ].
Change of the brain structure and function was observed after 16 h of video gaming. The total durations of video gaming were 16–90 h. However, the gaming intensity must be noted because the gaming intensity varied: 1.5–10.68 h per week. The different intensities might affect the change of cognitive function. Cognitive intervention studies demonstrated intensity effects on the cortical thickness of the brain [ 75 , 76 ]. A similar effect might be observed in video gaming studies. More studies must be conducted to resolve how the intensity can be expected to affect cognitive function.
Almost all studies used inclusion criteria “little/no experience with video games.” The criterion was used to reduce the factor of gaming-related experience on the effects of video gaming. Some of the studies also used specific handedness and specific sex of participants to reduce the variation of brain effects. Expertise and sex are shown to affect brain activity and structure [ 77 , 78 , 79 , 80 ]. The exclusion criterion of “MRI contraindication” is used for participant safety for the MRI protocol, whereas exclusion criteria of “psychiatric/mental illness”, “neurological illness”, and “medical illness” are used to standardize the participants.
Some concern might be raised about the quality of methodology, assessed using Delphi criteria [ 45 ]. The quality was 3–9 (mean = 6.10; S.D. = 1.69). Low quality in most papers resulted from unspecified information corresponding to the criteria. Quality improvements for the studies must be performed related to the low quality of methodology. Allocation concealment, assessor blinding, care provider blinding, participant blinding, intention-to-treat analysis, and allocation method details must be improved in future studies.
Another concern is blinding and control. This type of study differs from medical studies in which patients can be blinded easily. In studies of these types, the participants were tasked to do either training as an active control group or to do nothing as a passive control group. The participants can expect something from the task. The expectation might affect the outcomes of the studies [ 81 , 82 , 83 ]. Additionally, the waiting-list control group might overestimate the outcome of training [ 84 ].
Considering the sample size, which was 20–75 (mean = 43.67; S.D. = 15.63), the studies must be upscaled to emphasize video gaming effects. There are four phases of clinical trials that start from the early stage and small-scale phase 1 to late stage and large-scale phase 3 and end in post-marketing observation phase 4. These four phases are used for drug clinical trials, according to the food and drug administration (FDA) [ 85 ]. Phase 1 has the purpose of revealing the safety of treatment with around 20–100 participants. Phase 2 has the purpose of elucidating the efficacy of the treatment with up to several hundred participants. Phase 3 has the purpose of revealing both efficacy and safety among 300–3000 participants. The final phase 4 has the purpose of finding unprecedented adverse effects of treatment after marketing. However, because medical studies and video gaming intervention studies differ in terms of experimental methods, slight modifications can be done for adaptation to video gaming studies.
Several unresolved issues persist in relation to video gaming intervention. First, no studies assessed chronic/long-term video gaming. The participants might lose their motivation to play the same game over a long time, which might affect the study outcomes [ 86 ]. Second, meta-analyses could not be done because the game genres are heterogeneous. To ensure homogeneity of the study, stricter criteria must be set. However, this step would engender a third limitation. Third, randomized controlled trial video gaming studies that use MRI analysis are few. More studies must be conducted to assess the effects of video gaming. Fourth, the eligible studies lacked cognitive tests to validate the cognitive change effects for training. Studies of video gaming intervention should also include a cognitive test to ascertain the relation between cognitive function and brain change.
The systematic review has several conclusions related to beneficial effects of noncognitive-based video games. First, noncognitive-based video gaming can be used in all age categories as a means to improve the brain. However, effects on children remain unclear. Second, noncognitive-based video gaming affects both structural and functional aspects of the brain. Third, video gaming effects were observed after a minimum of 16 h of training. Fourth, some methodology criteria must be improved for better methodological quality. In conclusion, acute video gaming of a minimum of 16 h is beneficial for brain function and structure. However, video gaming effects on the brain area vary depending on the video game type.
We would like to thank all our other colleagues in IDAC, Tohoku University for their support.
PRISMA Checklist of the literature review.
Section/Topic | # | Checklist Item | Reported on Page # |
---|---|---|---|
Title | 1 | Identify the report as a systematic review, meta-analysis, or both. | 1 |
Structured summary | 2 | Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number. | 1 |
Rationale | 3 | Describe the rationale for the review in the context of what is already known. | 1, 2 |
Objectives | 4 | Provide an explicit statement of questions being addressed related to participants, interventions, comparisons, outcomes, and study design (PICOS). | 2 |
Protocol and registration | 5 | Indicate if a review protocol exists, if and where it is accessible (e.g., Web address), and if available, provide registration information including registration number. | 2 |
Eligibility criteria | 6 | Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale. | 2 |
Information sources | 7 | Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched. | 2 |
Search | 8 | Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated. | 2 |
Study selection | 9 | State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and if applicable, included in the meta-analysis). | 3 |
Data collection process | 10 | Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators. | 3 |
Data items | 11 | List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made. | 3 |
Risk of bias in individual studies | 12 | Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis. | 2 |
Summary measures | 13 | State the principal summary measures (e.g., risk ratio, difference in means). | - |
Synthesis of results | 14 | Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I ) for each meta-analysis. | - |
Risk of bias across studies | 15 | Specify any assessment of risk of bias that might affect the cumulative evidence (e.g., publication bias, selective reporting within studies). | - |
Additional analyses | 16 | Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified. | - |
Study selection | 17 | Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram. | 3,5 |
Study characteristics | 18 | For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations. | 5-11 |
Risk of bias within studies | 19 | Present data on risk of bias of each study, and if available, any outcome level assessment (see item 12). | 5,6 |
Results of individual studies | 20 | For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot. | 4 |
Synthesis of results | 21 | Present results of each meta-analysis done, including confidence intervals and measures of consistency. | - |
Risk of bias across studies | 22 | Present results of any assessment of risk of bias across studies (see Item 15). | - |
Additional analysis | 23 | Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]). | - |
Summary of evidence | 24 | Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers). | 12,13 |
Limitations | 25 | Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias). | 13 |
Conclusions | 26 | Provide a general interpretation of the results in the context of other evidence, and implications for future research. | 14 |
Funding | 27 | Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review. | 14 |
For more information, visit: www.prisma-statement.org .
D.B.T., R.N., and R.K. designed the systematic review. D.B.T. and R.N. searched and selected the papers. D.B.T. and R.N. wrote the manuscript with R.K. All authors read and approved the final manuscript. D.B.T. and R.N. contributed equally to this work.
Study is supported by JSPS KAKENHI Grant Number 17H06046 (Grant-in-Aid for Scientific Research on Innovative Areas) and 16KT0002 (Grant-in-Aid for Scientific Research (B)).
None of the other authors has any conflict of interest to declare. Funding sources are not involved in the study design, collection, analysis, interpretation of data, or writing of the study report.
Negative effects of video games, video games as a neutral factor, future studies.
Most of the popular video games in the market are characterized by their ability to allow players to role-play in various situations, unfortunately, most of these situations normally involve violence. There has been unease at the effect that this exposure could have on children, considering that video games are fast becoming a favorite past time for most children in the developed world. Studies have suggested the existence of a relationship between youth violence and video games and this could apply to children too.
The evidence that video games increase violence among children is overwhelming. For example, a study in 2001 found that a high number of violence cases in high schools and universities were orchestrated by persons who confessed to playing violent games regularly. An explanation for this is that aggression is mainly based on the learning function of the brain and as such, each violent episode is in essence one more learning opportunity, hence violence is increased with increased exposure to video games.
One of the factors that make video games prone to leading to violence is the high level of engagement and concentration required of gamers. Studies show that children who were exposed to violent video games engage in fantasy plays in which they emulate the actions of the violent characters. This effectively demonstrates that the high involvement of video games results in youths desiring to play out the violent actions in real life.
A logical consequence of exposure to violence is desensitization, a process whereby the cognitive, emotional, and even behavioral response to violence is eliminated in a gradual process. Therefore, engaging in violent video games results in an increase for tolerance of violent behavior in real life.
While advocates for video games argue that video games represent violence as âcool and fashionableâ, it should be noted that video games are no the only media through which such notions arise from. Violence is an aspect of the mainstream media and hence violence in children should take into consideration these various media platforms.
Opponents of media violence point to the rise in crime wave during the 1970s and 1980s, which was largely attributed to violence in television. They say that the same could happen due to video game violence. This is a fallacy as statistics indicate that violent crimes in the US fell in the 1990s, a time when violent video games became popular.
While video games are meant to be educational or entertaining, content analysis shows that 89% of these contain some violent content. Since video games are so common among children, the effect of video games would be significant. It has been said that a relation exists between video game violence and real life violence, however, this is no absolute reality.
Proponents argue that violent children prefer to play violent video games. Research suggests otherwise, therefore we can conclude that while violent games are played by violent children, the aggression levels increase due to the exposure.
This paper examined the effects of violent video games on children and their inclination to violent behavior. From the study, it is evident that video games have an effect on the behavior of children.
Future studies should look at other forms of violence, not necessarily physical as children are likely to engage on these on a regular basis.
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IMAGES
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COMMENTS
This essay will explore the detrimental impacts of video games on individuals and society, focusing on physical health, mental well-being, and social interactions. By understanding these adverse effects, we can better navigate the complex relationship between video games and our daily lives.
We need on average around 7-9 hours of sleep but an average gamer gets a minimum of 101 minutes delayed. According to the website Science Daily," gamers delayed going to bed 36 percent of the nights they played video games. Average game playing was 4.6 nights per week.
Negative Effects of Video Games on Teenagers - 700 Word Long Essay. Physical Health Problems. Poor Sleeping Habits. Problem With Concentration. Social Anxiety, Stress, and Depression. Lack of Motivation. The Negative Effects of Video Games on Children Essay - 300 Word Short Custom Essay. FAQs.
Conclusion. Altogether, videogames have both positive and negative effects on children. They might precondition the development of chronic diseases and extra weight, high anxiety, and depression levels, along with the changes in brain functioning. The highly-addictive nature increases the risks of spending too much time in games.
One of the most significant concerns regarding the harmful effects of video games is their impact on mental health. Research has shown that excessive gaming can lead to addictive behaviors, with individuals becoming so engrossed in the virtual world that they neglect other aspects of their lives. This can result in increased levels of stress ...
Performance in schools. Playing video games has negative impacts on a child's education. Studies have shown that out of four children, playing video games interferes with the academic performance of one child. Some children spend most of their time playing games to the extent of not sparing some time to do their homework.
Supporting Argument 3: Playing video games may lead to low self-esteem and depression problems (van den Eijnden, et al., 2018). Detail: Many modern online games include communication via chat in a toxic atmosphere. Detail: Children often go through sensitive stages of development, and negative feedback from teammates could trigger depression.
It is a widespread concern that violent video games promote aggression, reduce pro-social behavior, and increase interfere with the understanding as well as the mood of its players. (Gallinat, 2018). Violent video gamers like teenagers love to focus on more action games rather than on intellectual games that increase your brain power.
Positive Effects Article 2: "Game Reward Systems: Gaming Experiences and Social Meanings". Researchers Hao Wang and Cheun-Tsai Sun use examples of rewards systems from many popular and iconic video games from various genres to support their argument that these systems have positive social effects on players.
Video games: advantages and disadvantages. Firstly, it is argued by many that video games can cause a lot of health problems. For instance, looking at the screen for long hours can harm eyes and cause vision impairment because the cornea and iris of the eyes are not intended for viewing electronic devices for a long time. Moreover, using video games for too long may also cause headaches ...
One of the most significant negative effects of excessive gaming is the sedentary lifestyle it promotes, which can lead to obesity and associated health problems. Children who spend long hours playing video games have less time for physical activity, leading to a lack of exercise, weight gain, and health risks such as heart disease, diabetes ...
The effects of video games on health. There are many effects of video games on the eyes, such as headaches, eyestrain, blurred vision, etc. Above all, we should be wary of blue light from screens as it is toxic to the retina! đ. Another physical effect of video games is obesity. When not accompanied by regular physical activity, video games ...
Commercial Video Games and Mental and Behavioral Health. The research literature connecting exposure to video games (or video game genres) and the mental and behavioral health of teens is continually evolving. The early research on video gaming largely focused on identifying its negative impacts.
Moreover, in line with the literature, the core values to prevent a negative impact of video games should be focused on a few rules to be proposed with assertiveness and authority: 1. set a clear time limit to play, 2. prefer games that can also be played with family, 3. alternate video games with other games and activities, 4. avoid highly ...
Studies indicate that video games, especially those that are violent, reshape the behavior of children. Moreover, video games could contain some sort of competition and aggression, which affect the reasoning of children. In the current society, the rate at which conflicts occur in society has increased.
The Negative Effects of Video Games on Mental Health. While video games offer numerous advantages, it's essential to acknowledge the potential negative consequences on mental health. Excessive gaming, in particular, poses significant risks. Gaming addiction, or gaming disorder, involves a loss of control over gaming habits, which can lead to ...
The advent of video games raised new questions about the potential impact of media violence, since the video game player is an active participant rather than merely a viewer. 97% of adolescents age 12-17 play video gamesâon a computer, on consoles such as the Wii, Playstation, and Xbox, or on portable devices such as Gameboys, smartphones, and tablets.
Play has always been an essential part of childhood, but it looks different for modern children, who increasingly engage in virtual play. More than 90% of children older than 2 years play video games, and three-quarters of American households own a video game console. Children 8 to 17 years of age spend an average of 1.5 to 2 hours daily playing video games. Recent developments framed by ...
This essay discusses the adverse impacts of playing digital games on computer devices by youngsters and suggests some measures to reduce its negative effects. Concerning the adverse impacts of young children playing video games, the most devastating one is the addiction these games create.
The addiction to video games has been classified as a distinct behavioral addiction characterized by compulsive or excessive use of video games which in the long run interfere with one's everyday activities and life. One of the health problems is insomnia, this phenomenon is found to occur to people who tend to lack sleep.
Hundreds of studies have examined the impact of violent video game play. The most comprehensive meta-analysis so far [8], summarizing the effects of 381 effect sizes with more than 130,000 participants, found that the relationship between violent video game consumption and aggressive behavior is r = .19, which is a small to medium effect.In addition, playing violent video games reduces ...
The game genres examined were 3D adventure, first-person shooting (FPS), puzzle, rhythm dance, and strategy. The total training durations were 16-90 h. Results of this systematic review demonstrated that video gaming can be beneficial to the brain. However, the beneficial effects vary among video game types.
Negative Effects of Video Games. The evidence that video games increase violence among children is overwhelming. For example, a study in 2001 found that a high number of violence cases in high schools and universities were orchestrated by persons who confessed to playing violent games regularly. An explanation for this is that aggression is ...