Improving the Behavioural Impact of Air Quality Alerts

NCT ID: NCT03552198

Last Updated: 2021-10-22

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 225 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2017-07-23
• Study Completion Date: 2017-09-08

Brief Summary

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.

Detailed Description

According to data released in 2014, in 2012 around 3.7 million people died prematurely in the world as a result of exposure to ambient air pollution ((WHO), 2014). Evidence has shown the negative short- and long-term effects of air pollution on both premature mortality and morbidity from cardiopulmonary disease (for an overview, see (Kelly & Fussell, 2015)). This is particularly a problem in London (Samoli et al., 2016), where levels of air pollution are quite worrying. In the UK monitoring networks measure the levels of different air pollutants, and these measurements are provided by the Department for Environment, Food & Rural Affairs (DEFRA) in the form of daily air quality indices (AQIs), together with separate health advice for at-risk groups and the general population. A recently published systematic review (D'Antoni, Smith, Auyeung, & Weinman, 2017) has found suboptimal adherence levels to health advice associated with air quality alerts, and identified several facilitators and barriers of adherence. Some of the facilitators included beliefs that air pollution can have negative health effects (i.e. perceived severity), outcome expectancies (e.g., beliefs that something can be done to reduce smog), beliefs about the health benefits of AQI adoption (i.e. response efficacy), and receiving advice from health care professionals. Barriers to adherence included: lack of understanding of the indices, being exposed to health messages that reduced both concern about air pollution and perceived susceptibility, as well as perceived lack of self-efficacy/locus of control, reliance on sensory cues and lack of time to make behavioural changes. The findings of this systematic review have informed the current research study, which aimed to improve the behavioural impact of existing air quality alerts. In particular, alternative health messages were developed based on the psychosocial factors identified in the systematic review. The purpose of the study was to test whether these theory and evidence-based alternative communication formats, compared to the official messages sent in association with the UK AQIs, maximise the behavioural impact of existing alert systems.

Methods

Design:

This was a randomised control trail using a 2-way factorial design, with target population (2 levels: general population vs. individuals with a pre-existing health condition) and message format (2 levels: usual message format vs. alternative format) as between-factors. Qualitative data were also collected to understand the reasons for actual adherence and non-adherence.

• Theoretical framework and targeted psychosocial predictors:

The COM-B model (Michie, van Stralen, & West, 2011) was used as a theoretical framework to guide in the understanding of the facilitators and barriers to behaviour change in response to air quality alerts. The control groups received usual air quality alerts and health advice based on the UK AQI messages, and the intervention groups received alternative health messages targeting knowledge about the health impact of exposure to air pollution, perceived severity of air pollution, perceived susceptibility, perceived efficacy of protective behaviours, self-efficacy, perceived negative consequences associated with protective behaviours, reliance on sensory cue, and action planning. In addition, study participants who reported having a pre-existent respiratory condition and who were randomly allocated in the intervention group, also received specific additional messages targeting beliefs about efficacy and side effects of inhalers, and medication self-efficacy.

• Targeting message specificity:

Specificity refers to the extent to which a message provides a detailed description of the recommended behaviour. A meta-analysis of 18 studies (O'Keefe, 1997) found that messages providing health recommendations with a more specific description seem to be significantly more persuasive than generic recommendations (r=.10, k=18, N=11,105). Participants in the control group received the usual UK AQI message format containing less specific recommendations (e.g. advice for at risk individuals in case of high air pollution: 'Adults and children with lung problems, and adults with heart problems, should reduce strenuous physical exertion, particularly outdoors'). On the other hand, the intervention group received more specific recommendations ('Adults and children with lung problems, adults with heart problems, and older people, should reduce levels and length of physical activity outdoors. Where possible, change: travel route or exercise location (e.g. use our app to find less polluted roads or parks) or time (e.g. mornings or less polluted times)').

Control and intervention groups were compared in intended and actual behaviour change outcome measures. We predicted that the alternative format would be associated with higher behaviour change, compared to the usual format.

Conditions

Pollution; Exposure; Health Behavior

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: FACTORIAL
• Primary Study Purpose: PREVENTION
• Blinding Strategy: SINGLE

Study Groups

General public/usual health advice

Healthy participants with a self-reported existing health condition were randomised to receive the usual UK Air Quality Indices health advice.

Group Type: NO_INTERVENTION

No interventions assigned to this group

General public/alternative health advice

Generally healthy participants were randomised to receive targeted health advice about the adoption of protective behaviours in an alternative format.

Group Type: EXPERIMENTAL

Alternative health advice

Intervention Type: BEHAVIORAL

These messages targeted specific beliefs about air pollution and protective actions aimed at reducing exposure to air pollution. In addition, message specificity was targeted, which means that compared to the usual messages, the alternative messages reported more detailed health recommendations.

At risk group/usual health advice

Participants with a self-reported pre-existing health condition were randomised to receive the usual UK Air Quality Indices health advice.

Group Type: NO_INTERVENTION

No interventions assigned to this group

At risk group/alternative health advice

Participants with a self-reported existing health conditions were randomised to receive targeted health advice (based on their health condition) about the adoption of protective behaviours in an alternative format.

Group Type: EXPERIMENTAL

Alternative health advice

Intervention Type: BEHAVIORAL

These messages targeted specific beliefs about air pollution and protective actions aimed at reducing exposure to air pollution. In addition, message specificity was targeted, which means that compared to the usual messages, the alternative messages reported more detailed health recommendations.

Interventions

Alternative health advice

These messages targeted specific beliefs about air pollution and protective actions aimed at reducing exposure to air pollution. In addition, message specificity was targeted, which means that compared to the usual messages, the alternative messages reported more detailed health recommendations.

Intervention Type: BEHAVIORAL

Eligibility Criteria

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.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Institute for Health Research, United Kingdom

OTHER_GOV

Sponsor Role: collaborator

Public Health England

OTHER_GOV

Sponsor Role: collaborator

King's College London

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Donatella D'Antoni

Role: PRINCIPAL_INVESTIGATOR

King's College London

Locations

King' College London

London, , United Kingdom

Countries

United Kingdom

References

(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.

Reference Type: BACKGROUND

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.

Reference Type: BACKGROUND

PMID: 28938911 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 26040976 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 21513547 (View on PubMed)

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

Reference Type: BACKGROUND

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.

Reference Type: BACKGROUND

PMID: 26884048 (View on PubMed)

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

LRS-16/17-4286

Identifier Type: -

Identifier Source: org_study_id