Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

Impact of an Australian state-wide active travel campaign targeting primary schools

Active travel can have health and environmental benefits. This study evaluated the impact of a month-long (October 2015) campaign encouraging primary school children in Victoria, Australia to engage in active school travel. With support from local councils, schools participated in the campaign by monitoring active school travel and delivering promotional activities. A longitudinal study evaluated campaign impact. Carers (n = 715) of Victorian primary school children were recruited via social media and completed online surveys at baseline (T1; 0 wk) and during (T2; +2 wks) and after the campaign (T3; +6 wks). Carers reported their child's travel behaviour over the last five school days, and whether their child and/or their child's school participated in the campaign. Separate generalised linear models were used for T2 and T3 outcomes adjusting for T1 values and potential confounders. A greater proportion of children who participated in the campaign engaged in any active school travel at T2 (OR = 2.49, 95% CI = 1.63, 3.79) and T3 (1.62, 95% CI = 1.06, 2.46) compared with non-participating children. Similarly, these children had a higher frequency of active school travel at T2 (IRR = 1.60, 95% CI = 1.29, 1.97) and T3 (IRR = 1.45, 95% CI = 1.16, 1.80). Campaign participation resulted in small, short-term increases in active school travel. Keywords: Walking, Cycling, Active travel, Young people, Intervention, Schoo