Table 1

Correlation between PRECEDE model variables, intervention conditions, demographics, and self reported helmet use

Predictor variablesTime 1: helmet use before intervention (n=384)Time 2: helmet use immediately after intervention (n=363)Time 3: helmet use 1 month after intervention (n=351)
*p<0.05; **p<0.01; ***p<0.001; †p<0.0001.
Note: Dependent variable, helmet use, is self reported by children. In parent-child condition, parent reported per cent of child's helmet use did match their child's self report (18%). Variable coded dichotomously as yes/no for helmet use: 1=yes; 2=no. All predictors except helmet use and assignment to intervention condition measured preintervention. Of the 330 students who completed questionnaires at all three times 188 self identified as white, 89 as Hispanic, and 17 as black.
Intervention conditions
Parent and classroom−0.101*−0.483***−0.388***
Control group0.0720.483***0.329***
Classroom only0.0340.0400.077
Demographics
Ethnicity: 1=whites (188); 2=other (142)−0.131**−0.123**−0.053
Gender: 1=boy; 2=girl−0.004−0.0240 .016
Helmet ownership (1=yes owns; 2=no)−0.257†−0.838†−0.679***
Predisposing factors
A helmet doesn't protect your head0.030−0.0440.000
Very bad head injuries can change you forever−0.0510.0200.105*
I can control my bike so well that I will not be hurt0.0340.0760.094
Whether or not you get hurt in a bike accident is just a matter of luck0.036−0.0390.023
If someone has a bad head injury they will be back at school or work in a few days−0.035−0.0990.002
Enabling
I see bicycle helmets or advertisements for bicycle helmets in the stores0.105*0.138**0.084
Helmets cost too much−0.0530.0000.046
Reinforcing
Mom is the one person who most often says you should wear a helmet0.111*0.226†0.172***
Do you personally know someone who has had a bad head injury?−0.0850.054−0.002