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The effect of evidence and theory-based health advice accompanying smartphone air quality alerts on adherence to preventative recommendations during poor air quality days: A randomised controlled trial

Publication date: 

1 Feb 2019

Ref: 

https://doi.org/10.1016/j.envint.2019.01.002

Author(s): 

Donatella D'Antonia, Vivian Auyeung, Heather Walton, Gary W.Fuller, Andrew Grieve, John Weinman.

Publication type: 

Article

Abstract: 

Although poor air quality can have a negative impact on human health, studies have shown suboptimal levels of adherence to health advice associated with air quality alerts. The present study compared the behavioural impact of the UK Air Quality Index (DAQI) with an alternative message format, using a 2 (general population vs. at-risk individuals) X 2 (usual DAQI messages vs. behaviourally enhanced messages) factorial design. Messages were sent via a smartphone application. Eighty-two participants were randomly allocated to the experimental groups. It was found that the enhanced messages (targeting messages specificity and psychosocial predictors of behaviour change) increased intentions to make permanent behavioural changes to reduce exposure, compared to the control group (V = 0.23). This effect was mediated by a reduced perception of not having enough time to follow the health advice received (b = −0.769, BCa CI [−2.588, 0.533]). It was also found that higher worry about air pollution, perceived severity, perceived efficacy of the recommended behaviour and self-efficacy were predictive of self-reported behaviour change at four weeks. In response to a real moderate air quality alert, among those with a pre-existing lung condition, more respondents in the intervention group reported to have used their preventer inhaler compared to the control group (V = 0.49). On the other hand, the two message formats performed similarly when intentions were collected in relation to a hypothetical high air pollution scenario, with all groups showing relatively high intentions to change behaviours. This study expands the currently limited understanding of how to improve the behavioural impact of existing air quality alerts.