Trends in Video Game Play through Childhood, Adolescence, and Emerging Adulthood
Table 1
Results of multilevel model predicting video gaming habits from study variables.
Days/week played
School/work day hours/day played
Nonschool/work day hours/day played
Problem play (PVGP)
Year-level variables:
Age (linear)
1.86***
1.51***
1.37**
0.42***
Age (quadratic)
−1.37***
−0.59a
−0.99*
−0.29*
Caffeinated drinks/day
0.27**
0.29**
0.36**
−0.06
Caffeine problem use
−0.06
0.02
−0.04
0.18***
Soda/junk food consumption
0.65***
0.32***
0.68***
0.18***
Attending 2yr or 4yr college
0.02
−0.14*
−0.08
0.01
Holding full-time job
0.04
−0.15*
−0.17
0.02
Living in student housing
−0.08
0.003
−0.05
0.01
Living away from home
−0.20*
−0.13
−0.04
−0.03
Participant-level variables:
Race: Black
0.27*
0.29+
0.41**
−0.02
Race: Latino
0.65***
0.64***
0.64***
0.11*
Race: Asian
0.11
0.01
−0.02
0.11*
Race: Other/multiracial
0.41***
0.41**
0.50***
−0.03
Gender: Female
−0.71***
−0.59***
−0.61***
−0.17***
Personality: Sensation-seeking
0.18
0.26
0.21
0.04
Personality: Shyness
0.07
0.09
0.12
0.09*
Personality: Sociability
0.14
0.19
0.02
0.04
Age at time of interview
−0.03
−0.20
−0.15
−0.05
Model characteristics:
Intraclass correlation
0.48
0.45
0.55
0.67
-squared within
0.12***
0.17***
0.13***
0.09***
-squared between
0.14***
0.08***
0.08***
0.07***
CFI and TLI > .999, RMSEA and SRMR < .001. Coefficients are standardized. Because model fit statistics, intraclass correlations, and -squared values are not available in MPlus for models including count dependent variables, these model fit statistics and the italicized -squared values are taken from an alternative model (also run using MPlus) in which days played and hours/day played were specified as continuous dependent variables. , , , and . aThis coefficient was significant in models that did not include life-course indicators.
