Improving the Behavioural Impact of Air Quality Alerts

September 23, 2021 updated by: King's College London

Improving the Behavioural Impact of Air Quality Alerts in London

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.

Study Overview

Status

Completed

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.

Study Type

Interventional

Enrollment (Actual)

225

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (ADULT, OLDER_ADULT)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: PREVENTION
  • Allocation: RANDOMIZED
  • Interventional Model: FACTORIAL
  • Masking: SINGLE

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
NO_INTERVENTION: 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.
EXPERIMENTAL: 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.
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.
NO_INTERVENTION: 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.
EXPERIMENTAL: 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.
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Adoption of Protective Behaviour at 4 Weeks
Time Frame: Baseline and 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 Outcome Measures

Outcome Measure
Measure Description
Time Frame
Considered Making Permanent Changes
Time Frame: at 4 weeks
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
Actual Behaviour Change in Response to a Real Air Quality Alert
Time Frame: At 3 weeks
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
Intentions to Adhere to Health Advice Associated With a Hypothetical High Air Pollution Scenario
Time Frame: Baseline and at 4 weeks
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (ACTUAL)

July 23, 2017

Primary Completion (ACTUAL)

September 8, 2017

Study Completion (ACTUAL)

September 8, 2017

Study Registration Dates

First Submitted

May 15, 2018

First Submitted That Met QC Criteria

June 8, 2018

First Posted (ACTUAL)

June 11, 2018

Study Record Updates

Last Update Posted (ACTUAL)

October 22, 2021

Last Update Submitted That Met QC Criteria

September 23, 2021

Last Verified

May 1, 2018

More Information

Terms related to this study

Other Study ID Numbers

  • LRS-16/17-4286

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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