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Models employed in exercise psychology highlight the role of reflective processes for explaining behavior change. However, as discussed in social cognition literature, information-processing models also consider automatic processes (dual-process models). To examine the relevance of automatic processing in exercise psychology, we used a priming task to assess the automatic evaluations of exercise stimuli in physically active sport and exercise majors (n = 32), physically active nonsport majors (n = 31), and inactive students (n = 31). Results showed that physically active students responded faster to positive words after exercise primes, whereas inactive students responded more rapidly to negative words. Priming task reaction times were successfully used to predict reported amounts of exercise in an ordinal regression model. Findings were obtained only with experiential items reflecting negative and positive consequences of exercise. The results illustrate the potential importance of dual-process models in exercise psychology.
According to the results of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) published in 2009, only 5% to 8% of the 15-17-year-old adolescents reach the current recommendations on health-enhancing physical activity This result (besides others in the survey) rests on data measured with the 25-item physical activity questionnaire for children and adolescents (MoMo-AFB). The present study compares two different methods of assessing physical activity with the purpose of testing the validity of the MoMo-AFB self-report. First, we measured the physical activity status of 73 15 to 18-year-old pupils (32 boys and 41 girls) over seven days via objective accelerometry (ActiGraph GT1M), then the pupils completed the MoMo-AFB for the same (previous) period. Results show that using the MoMo-AFB leads to higher levels of self-reported physical activity than measuring it with accelerometers. Furthermore, only the MoMo-AFB subscale MVPA (moderate-to-vigorous physical activity), that uses two single items to decide whether the health-enhancing physical activity recommendation is reached or failed, corresponds statistically significantly with the accelerometry data. For all other subscales (e.g. school- or leisure time activity), we found no agreement. Further research, first of all on the measurement quality of the MoMo-AFB but also on the physical (in)activity status of children and adolescents, is needed.