|Appears in Collections:||Faculty of Health Sciences and Sport eTheses|
|Title:||Can air quality feedback be an effective tool to encourage parents and caregivers to “take smoking right outside”?|
behaviour change intervention
|Publisher:||University of Stirling|
|Citation:||Dobson R, O’Donnell R, de Bruin M, et al. Using air quality monitoring to reduce second-hand smoke exposure in homes: the AFRESH feasibility study. Tob Prev Cessat 2017;3. doi:10.18332/tpc/74645|
Dobson R, Semple S. “How do you know those particles are from cigarettes?”: An algorithm to help differentiate second-hand tobacco smoke from background sources of household fine particulate matter. Environ Res 2018;166:344–7. doi:10.1016/j.envres.2018.06.019
Dobson R, Rosen L, Semple S. Monitoring secondhand tobacco smoke remotely in real-time: A simple low-cost approach. Tob Induc Dis 2019;17. doi:10.18332/tid/104577
|Abstract:||Second-hand tobacco smoke (SHS) is a serious cause of ill-health, particularly for children. Smoking indoors leads to high concentrations of SHS and behaviour change interventions have been developed to promote smoke-free homes for children’s benefit. Air-quality feedback – giving parents and caregivers personalised information on the effect of smoking on air pollution at home – has been used in several trials with positive results. A qualitative study was conducted comparing attitudes to SHS and outdoor air pollution. Focus group participants and internet commenters viewed outdoor pollution as a serious health risk, suggesting that comparing SHS to outdoor air pollution could be a promising avenue for increasing awareness about the risks from SHS and promoting behaviour change. An air-quality feedback intervention using a low-cost particle counter was developed and piloted, with lessons from this feasibility study used to develop an innovative intervention using mHealth techniques and remote monitoring for use in a larger trial in four centres around Europe. This study of 68 homes resulted in a statistically significant decline of 17% in measured SHS over the intervention period, but resulted in only eight participants making their homes fully smoke-free. An algorithm was developed to detect smoking in homes using low-cost particulate matter sensors. When tested with data from 144 homes in Scotland, 135 were correctly classified (113 smoking homes, 22 non-smoking homes). Similar predictive rates were achieved in a study of 16 homes in Israel demonstrating that it could be used in different environmental conditions. The algorithm did not enable detection of the periods when smoking occurred in homes. Air-quality feedback can play a role in changing smoking behaviour but may require careful targeting at those with the capability and opportunity to make the change. Future research could use these techniques more widely as part of an “endgame” approach to tobacco control.|
|Type:||Thesis or Dissertation|
|PhD Thesis - Ruaraidh Dobson FINAL.pdf||Thesis||6.61 MB||Adobe PDF||View/Open|
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