Health Behavior Clinical Trial
Official title:
Improving the Behavioural Impact of Air Quality Alerts in London
Verified date | May 2018 |
Source | King's College London |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
The evidence shows that adherence to air quality advice to adopt protective behaviours during pollution episodes is suboptimal, and that the traditional strategy of simply informing people about high pollution episodes is not effective. The aim of the present study was to investigate how to improve the behavioural impact of existing air quality alert messages through a systematic manipulation of key communication variables, including perceived susceptibility, self-efficacy, response efficacy, planning, message specificity, etc. Users of an existing air quality alert smartphone application in London, who agreed to take part in the study, were randomly allocated to a control group (i.e. receiving usual health advice associated with the official UK Air Quality Index) or an intervention group receiving health advice associated with air quality alerts in an alternative format (i.e. targeting key variables). Both intended and actual adherence behaviours were investigated. Qualitative data were also collected to understand the reasons for not adopting protective behaviours in response to receiving a real air pollution alert. Implications of this study include the potential to increase protective behaviours in the general population during air pollution episodes through the development of more effective communication strategies provided via existent air quality alert systems.
Status | Completed |
Enrollment | 225 |
Est. completion date | September 8, 2017 |
Est. primary completion date | September 8, 2017 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - To be eligible to participate, participants had to be members of the general public in the adult age range (>18 years), be fluent in English, working or living in Greater London, and being new or old users of a specific air quality alert smartphone application. Exclusion Criteria: - younger than 18 years - not working or living in Greater London - no longer users of the air quality alert smartphone application. |
Country | Name | City | State |
---|---|---|---|
United Kingdom | King' College London | London |
Lead Sponsor | Collaborator |
---|---|
King's College London | National Institute for Health Research, United Kingdom, Public Health England |
United Kingdom,
(WHO), W. H. O. (2014). Burden of disease from air pollution. Retrieved from http://www.who.int/phe/health_topics/outdoorair/databases/FINAL_HAP_AAP_BoD_24March2014.pdf?ua=1.
D'Antoni D, Smith L, Auyeung V, Weinman J. Psychosocial and demographic predictors of adherence and non-adherence to health advice accompanying air quality warning systems: a systematic review. Environ Health. 2017 Sep 22;16(1):100. doi: 10.1186/s12940-017-0307-4. Review. — View Citation
Daniel J. O'Keefe (1997) Standpoint Explicitness and Persuasive Effect: A Meta-Analytic Review of the Effects of Varying Conclusion Articulation in Persuasive Messages, Argumentation and Advocacy, 34:1, 1-12, DOI: 10.1080/00028533.1997.11978023
Kelly FJ, Fussell JC. Air pollution and public health: emerging hazards and improved understanding of risk. Environ Geochem Health. 2015 Aug;37(4):631-49. doi: 10.1007/s10653-015-9720-1. Epub 2015 Jun 4. Review. — View Citation
Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011 Apr 23;6:42. doi: 10.1186/1748-5908-6-42. Review. — View Citation
Samoli E, Atkinson RW, Analitis A, Fuller GW, Green DC, Mudway I, Anderson HR, Kelly FJ. Associations of short-term exposure to traffic-related air pollution with cardiovascular and respiratory hospital admissions in London, UK. Occup Environ Med. 2016 May;73(5):300-7. doi: 10.1136/oemed-2015-103136. Epub 2016 Feb 16. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Adoption of Protective Behaviour at 4 Weeks | Differences between conditions in actual adoption of protective behaviours at 4 weeks. Outcome measures were collected via self-reports: The question was: 'In the past 4 weeks, how often have you taken action to reduce exposure to air pollution, in response to hearing or reading an air quality forecast?' Measures: from 1 'Not at all' to 9 'all of the time' (answers 'N/A, I am not aware of any forecast' were excluded from analyses). | Baseline and at 4 weeks | |
Secondary | Considered Making Permanent Changes | Differences between conditions in planning the adoption of protective behaviours at 4 weeks. Outcome measures were collected via self-reports: The question was: 'In the past 4 weeks, have you considered making permanent changes to daily travel route or exercise location/time?' possible answers were 'yes' or 'no'. 'unsure' answers were treated as system missing. | at 4 weeks | |
Secondary | Actual Behaviour Change in Response to a Real Air Quality Alert | Differences between conditions in self-reported actual behaviour change in response to receiving a real air quality alert. Behavioural outcomes were collected via a questionnaire asking participants to respond 'yes/no' to whether they had changed a series of behaviours in response to receiving the alert. In this case it was a 'moderate' alert | At 3 weeks | |
Secondary | Intentions to Adhere to Health Advice Associated With a Hypothetical High Air Pollution Scenario | Differences between conditions in intentions to adhere to the health advice received in association with a hypothetical high air pollution alert scenario. Intentions were measured by a self-report item: participants were asked to agree with a statement about their adherence intentions on 9-point scale, where 1=strongly disagree to 9=strongly agree. | Baseline and at 4 weeks |
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