Advances in Psychological Science ›› 2023, Vol. 31 ›› Issue (1): 127-144.doi: 10.3724/SP.J.1042.2023.00127
• Regular Articles • Previous Articles Next Articles
Received:
2021-12-02
Online:
2023-01-15
Published:
2022-10-13
Contact:
CHI Lizhong
E-mail:Chilizh3804@163.com
CLC Number:
MIAO Haofei, CHI Lizhong. Cognitive neural characteristics of professional action video game players[J]. Advances in Psychological Science, 2023, 31(1): 127-144.
文献 | 分组(n) | 认知范式(指标) | 差异量 | 显著性 | 效应量 |
---|---|---|---|---|---|
2020 | 职业选手(14), 业余玩家(16) | 注意持续(波动率) | 20.00% | p = 0.04 | Hedges’s g = 0.75 |
注意持续(正确数) | 9.88% | p = 0.03 | Hedges’s g = 0.81 | ||
空间广度 | 17.95% | p = 0.002 | Hedges’s g = 1.27 | ||
数字广度 | 15.93% | p = 0.04 | Hedges’s g = 0.82 | ||
Stroop | - | p > 0.05 | - | ||
MOT (速度阈限) | 未报告 | p = 0.03 | 未报告 | ||
汉诺塔(正确率) | - | p = 0.08 | - | ||
拼图 | - | p > 0.05 | - | ||
2012 | 专业玩家(23), 新手(21) | 转换任务(交互作用) | 未报告 | p = 0.005 | η2 p = 0.18 |
Flanker | - | p > 0.05 | - | ||
2018 | 职业选手(10), 青训选手(10), 业余玩家(20) | Flanker | - | p > 0.05 | - |
MOT (追踪数量) | 未报告 | p = 0.04 | 未报告 | ||
2020 | 专业玩家(19), 业余玩家(19) | AB (T2正确率) | 约10% | p < 0.001 | d = 2.43 |
2020 | 精英职业选手(12), 一般职业选手(43) | 伦敦塔(反应时) | 16.90% | p < 0.001 | Hedges’s g = 1.30 |
心理旋转(正确率) | 6.50% | p = 0.001 | Hedges’s g = 1.70 | ||
2020 | 专业玩家(35), 业余玩家(35) | 任务转换(错误率) | 3.79% | p < 0.001 | 未报告 |
任务转换(转换代价) | 1.97% | p = 0.020 | d = 0.57 | ||
CPT (命中率) | 3.74% | p = 0.003 | η2 p = 0.12 | ||
CPT (误报率) | 10.26% | p = 0.005 | η2 p = 0.11 | ||
2018 | 专业玩家(15), 业余玩家(14) | UFOV (反应时) | 11.33% | p < 0.001 | Hedges’s g = 2.67 |
2013 | 职业选手(17), 新手(33) | SWM (正确率) | 5.70% | p = 0.02 | 未报告 |
2020 | 专业玩家(18), 业余玩家(19) | SWM (2个组块-正确率) | 2% | p = 0.006 | Hedges’s g = 0.87 |
SWM (4个组块-正确率) | 4% | p = 0.007 | Hedges’s g = 0.94 | ||
SWM (8个组块-正确率) | 8% | p = 0.002 | Hedges’s g = 1.12 |
文献 | 分组(n) | 认知范式(指标) | 差异量 | 显著性 | 效应量 |
---|---|---|---|---|---|
2020 | 职业选手(14), 业余玩家(16) | 注意持续(波动率) | 20.00% | p = 0.04 | Hedges’s g = 0.75 |
注意持续(正确数) | 9.88% | p = 0.03 | Hedges’s g = 0.81 | ||
空间广度 | 17.95% | p = 0.002 | Hedges’s g = 1.27 | ||
数字广度 | 15.93% | p = 0.04 | Hedges’s g = 0.82 | ||
Stroop | - | p > 0.05 | - | ||
MOT (速度阈限) | 未报告 | p = 0.03 | 未报告 | ||
汉诺塔(正确率) | - | p = 0.08 | - | ||
拼图 | - | p > 0.05 | - | ||
2012 | 专业玩家(23), 新手(21) | 转换任务(交互作用) | 未报告 | p = 0.005 | η2 p = 0.18 |
Flanker | - | p > 0.05 | - | ||
2018 | 职业选手(10), 青训选手(10), 业余玩家(20) | Flanker | - | p > 0.05 | - |
MOT (追踪数量) | 未报告 | p = 0.04 | 未报告 | ||
2020 | 专业玩家(19), 业余玩家(19) | AB (T2正确率) | 约10% | p < 0.001 | d = 2.43 |
2020 | 精英职业选手(12), 一般职业选手(43) | 伦敦塔(反应时) | 16.90% | p < 0.001 | Hedges’s g = 1.30 |
心理旋转(正确率) | 6.50% | p = 0.001 | Hedges’s g = 1.70 | ||
2020 | 专业玩家(35), 业余玩家(35) | 任务转换(错误率) | 3.79% | p < 0.001 | 未报告 |
任务转换(转换代价) | 1.97% | p = 0.020 | d = 0.57 | ||
CPT (命中率) | 3.74% | p = 0.003 | η2 p = 0.12 | ||
CPT (误报率) | 10.26% | p = 0.005 | η2 p = 0.11 | ||
2018 | 专业玩家(15), 业余玩家(14) | UFOV (反应时) | 11.33% | p < 0.001 | Hedges’s g = 2.67 |
2013 | 职业选手(17), 新手(33) | SWM (正确率) | 5.70% | p = 0.02 | 未报告 |
2020 | 专业玩家(18), 业余玩家(19) | SWM (2个组块-正确率) | 2% | p = 0.006 | Hedges’s g = 0.87 |
SWM (4个组块-正确率) | 4% | p = 0.007 | Hedges’s g = 0.94 | ||
SWM (8个组块-正确率) | 8% | p = 0.002 | Hedges’s g = 1.12 |
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