Trial Review

Technical difficulties have been reported by some users of the search function and is being investigated by technical staff. Thank you for your patience and apologies for any inconvenience caused.

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this information for consumers
Trial registered on ANZCTR


Registration number
ACTRN12620001355965
Ethics application status
Approved
Date submitted
8/12/2020
Date registered
16/12/2020
Date last updated
24/03/2021
Date data sharing statement initially provided
16/12/2020
Date results information initially provided
24/03/2021
Type of registration
Prospectively registered

Titles & IDs
Public title
Optimising COVID-19 testing intentions and behaviour with enhanced messaging
Scientific title
Does enhanced messaging increase COVID-19 testing intentions and behaviour in Australian citizens, compared to the current government information?
Secondary ID [1] 302762 0
Nil
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
COVID-19 319871 0
Condition category
Condition code
Public Health 317810 317810 0 0
Health promotion/education
Infection 318003 318003 0 0
Other infectious diseases
Respiratory 318004 318004 0 0
Other respiratory disorders / diseases

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
This study is testing the effects of two interventions (enhanced messaging and enhanced action planning), all conducted online through a survey platform. Participants will be recruited via Dynata, a market research company experienced in panel survey sampling with whom we have a strong track record of collaboration. Dynata has an extensive database of participants (over 600,000 Australian adults) who are willing to be involved in online research. Participants will be directed to the landing page where they can read the PIS and Consent Form before accessing the survey.

The survey itself will be hosted on the survey platform Qualtrics, where it is possible to track adherence to the intervention, such that we can see at what point participants left the survey, if they did not complete it.

Participants will answer demographic questions and then will be randomised to receive either the education intervention or a control. This will take about 5 minutes to complete. Immediately following this, they will be asked our outcome questions, and then will be randomised again, to either the action intervention or a control condition. This part will also take about 5 minutes to complete. Therefore the complete survey will take about 10 minutes in total.

Participants are told in the PIS that the results of the study will be posted on our website (https://sydneyhealthliteracylab.org.au).


EDUCATION INTERVENTION:
Enhanced messaging:
Relevant COVID-19 testing information from an Australian government website (NSW Health COVID-19 FAQ: https://www.health.nsw.gov.au/Infectious/covid-19/Pages/frequently-asked-questions.aspx#4 ) will be run through a specialised editor developed by the Sydney Health Literacy Lab (the SHLL Editor). This is a new tool that identifies issues like complex language and long sentences and suggests alternatives to improve understandability. This text will be accompanied by an image – demonstrating the community benefits of COVID-19 testing – to increase salience of the message.
This uses the behaviour change techniques of: instruction on how to perform a behaviour, information about health consequences, and salience of consequences (from the Behaviour Change Technique Taxonomy).

ACTION INTERVENTION
Enhanced action planning:
A series of action plans will be developed and tested with a consumer representative based on the top 10 barriers to testing found in our nationally representative survey in November 2020. These action plans will use if-then statements paired with icon images. For example, ‘IF I feel I don’t have time to get tested, THEN I will remind myself that getting tested helps to protect the community’.
Our previous work has shown if-then plans improve behaviour change amongst people with varying levels of health literacy.
Participants will be provided with a brief description of the action plans. They will select the barrier/s most relevant to them, and shown a corresponding action plan. If the plan is rated as too hard, users will be prompted to create a different plan.
This uses the behaviour change techniques of action planning, behavioural substitution and problem solving (from the Behaviour Change Technique Taxonomy).
Intervention code [1] 319163 0
Prevention
Intervention code [2] 319164 0
Behaviour
Comparator / control treatment
Education intervention control: NSW Health COVID-19 FAQ
COVID-19 testing information on Australian Government website (NSW Health COVID-19 FAQ: https://www.health.nsw.gov.au/Infectious/covid-19/Pages/frequently-asked-questions.aspx#4 ). Questions include ‘Is it safe to get tested for COVID-19?’ ‘Is COVID-19 testing painful?’ ‘Is COVID-19 testing free?’

Action intervention control: Healthdirect Symptom Checker
The federal government’s ‘Coronavirus (COVID-19) Symptom Checker’ available via the Healthdirect website : https://www.healthdirect.gov.au/symptom-checker/tool/basic-details. Users select any symptom/s that they are experiencing. The symptom checker helps people to understand their symptoms and guides users to appropriate healthcare action, including what to do and where to go.
Control group
Active

Outcomes
Primary outcome [1] 325687 0
Intention to undergo COVID-19 testing if symptomatic – measured using a 7 point Likert scale strongly agree-strongly disagree for the question ‘Over the next 4 weeks, I plan to get tested if I have COVID-19 symptoms’. Specifically, we will investigate the effect of the intervention on the proportion of “strongly agree” responses.
Timepoint [1] 325687 0
This will be measured after the education intervention, and before the second round of randomisation, in the initial survey
Secondary outcome [1] 389270 0
Intentions about other COVID-19 prevention behaviours – measured using a 7 point Likert scale strongly agree-strongly disagree with answers averaged across the following questions – ‘Over the next 4 weeks, I plan to stay home if I have COVID-19 symptoms’; ‘Over the next 4 weeks, I plan to stay 1.5m away from others that I don’t live with where I can’; ‘Over the next 4 weeks, I plan to wash my hands or use sanitiser to protect me and others from COVID-19’; ‘Over the next 4 weeks, I plan to wear a mask in crowded indoor areas’; 'If I get tested for COVID-19, I plan to isolate until I get my test results'
Timepoint [1] 389270 0
Measured after education intervention, and before the second round of randomisation, in the initial survey
Secondary outcome [2] 389271 0
Understanding of messaging - measured using the sum of participants’ correct answers to the following 4 questions:-
Can you name 3 symptoms that are associated with COVID-19?
When I have signs that I might have COVID-19 (e.g. a cough or a sore throat), I will… (pick all the answers you think are correct) – wait until my symptoms are bad enough; get tested straight away; self-isolate at home
If I do get tested for COVID-19, I will go... (pick all the answers you think are correct) – to the emergency department; to my GP; to a COVID testing centre
If I do get tested for COVID-19 and I need groceries, I will ... (pick all the answers you think are correct) – ask someone to get them for me; wear a mask; order online
Timepoint [2] 389271 0
Measured after education intervention, and before the second round of randomisation, in the initial survey
Secondary outcome [3] 389272 0
Risk perceptions – measured using the newly developed COVID-19 Own Risk Appraisal Scale (CORAS), from Jaspal, Fino and Breakwell (2020). This contains the following items:
What is your gut feeling about how likely you are to get infected with COVID-19? (from 1 (extremely unlikely) to 5 (extremely likely))
Picturing myself getting COVID-19 is something I find... (from 1 (very hard to do) to 5 (extremely easy to do))
I am sure I will NOT get infected with COVID-19 (from 1 (strongly disagree) to 5 (strongly agree))
I feel I am unlikely to get infected with COVID-19 (from 1 (strongly disagree) to 5 (strongly agree))
I feel vulnerable to COVID-19 infection (from 1 (strongly disagree) to 5 (strongly agree))
I think my chances of getting infected with COVID-19 are... (from 1 (zero) to 5 (very large))
Some of the above must be reverse-scored, and following this an average will be taken for each participant across these questions.
Timepoint [3] 389272 0
Measured after education intervention, and before the second round of randomisation, in the initial survey
Secondary outcome [4] 389273 0
Social stigma – measured using items from the Stigma Scale, developed by King et al (2007), focusing on those that look at others’ perceptions and changing it to look at COVID-19 (the original measure looks at stigma of mental health). The measure uses a 7 point Likert scale strongly agree-strongly disagree, and we will be averaging answers across the following items:-
The general public is understanding of people who test positive for COVID-19
Other people would think less of me if I test positive for COVID-19
I would worry about telling people if I test positive for COVID-19
I would feel the need to hide being COVID-19 positive from my friends
People would insult me because of testing positive for COVID-19
I would be discriminated against by my employers because of being COVID-19 positive
I would be scared of how other people will react if they found out I was COVID-19 positive
Timepoint [4] 389273 0
Measured after education intervention, and before the second round of randomisation, in the initial survey
Secondary outcome [5] 389274 0
Self-efficacy – measured using Hamilton et al’s measure of self-efficacy for social distancing due to COVID-19 (2020), and altering it to reflect self-efficacy of getting tested. The measure uses a 7 point Likert scale strongly agree-strongly disagree, and we will be averaging answers across the following items:-
It is mostly up to me whether I get tested for COVID-19
I have complete control over whether I get tested for COVID-19
It would be easy for me to get tested for COVID-19
I am confident that I could get tested for COVID-19
Timepoint [5] 389274 0
Measured after education intervention, and before the second round of randomisation, in the initial survey
Secondary outcome [6] 389275 0
Intention to undergo COVID-19 testing if symptomatic – measured using a 7 point Likert scale strongly agree-strongly disagree for the question ‘Over the next 4 weeks, I plan to get tested if I have COVID-19 symptoms’ (repeat measure of primary outcome).
Timepoint [6] 389275 0
Measured after the action plan intervention in the initial survey, and 4 weeks after the intervention
Secondary outcome [7] 389276 0
Self-reported COVID-19 testing behaviour – measured using the question ‘I got tested for COVID-19 in the last 4 weeks’ (yes/no)
Timepoint [7] 389276 0
Measured 4 weeks post-intervention

Eligibility
Key inclusion criteria
Live in Australia, aged 18 or over
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
Yes
Key exclusion criteria
Live outside Australia, aged under 18. Also quota sampling based on age, gender and education groups, so that these groups are nationally representative, so participants will be excluded from the study if quotas are filled for their age/gender/education category.

Study design
Purpose of the study
Prevention
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
We will recruit participants using an online sample via Dynata, a market research company experienced in panel survey sampling. Dynata has an extensive database of participants (over 600,000 Australian adults) who are willing to be involved in online research. Participants will be directed to the landing page where they can read the PIS and Consent Form before accessing the survey questions.
The survey itself will be hosted on the Qualtrics platform, which allows randomisation of participants such that participants are evenly randomised to each given condition.
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
The Qualtrics platform includes a “Randomizer” tool to evenly allocate participants to each condition . We will conduct two stages of randomisation: 1) randomised to government FAQs (control) or enhanced text with salient image (intervention); and then 2) randomised to government symptom checker (control) or enhanced action plan tool (intervention).
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?



Intervention assignment
Factorial
Other design features
Phase
Not Applicable
Type of endpoint/s
Statistical methods / analysis
Our hypotheses are:
1. Compared to control (gov FAQs: group 1 & 2) the enhanced intention intervention (SHLL version: group 3 & 4) will result in:
a) Higher intentions to get tested if symptomatic (Likert scale)
b) Higher understanding of COVID-19 (more symptoms identified, less myths identified)
c) Higher risk perceptions (average across Likert scales)
d) Higher self efficacy (average across Likert scales)
e) No effect on social stigma (average across Likert scales)
f) No effect on other behaviours

2. Compared to control (symptom checker: group 1 & 3) the enhanced behaviour intervention (action plan: group 2 & 4) will result in:
g) Higher self-reported COVID-19 tests over the past 4 weeks (yes/no)
h) No effect on other behaviours or intentions

Statistical analysis will be conducted using planned contrasts between the intervention arm and control arm, implemented in regression models. Analyses will control for baseline testing intentions. The influence of age, gender, language, health literacy, trust, and living alone will be examined by including appropriate interaction terms within the regression models. The total sample size required is 1430. This is based on the primary outcome of intention, with the assumption that in the control arm for intention (group 1 & 2), only 50% will have strong positive testing / self-isolation intention, and that the intervention (group 3 & 4) will increase this to 65%. This equates to odds ratios of ~1.5 for either intervention component. Detection of odds ratios of 1.5 for each intervention component (with 80% power and 5% alpha level) requires a total sample size of n=812 (i.e., 203 randomly to each study arm). Allowing for up to 20% loss to follow-up, a total of n=1016 should be recruited. To account for multiple comparisons using an adjusted alpha level of 0.013 requires n=1144, increased to 1430 to account for dropout.

Recruitment
Recruitment status
Completed
Date of first participant enrolment
Anticipated
18/01/2021
Actual
27/01/2021
Date of last participant enrolment
Anticipated
Actual
11/02/2021
Date of last data collection
Anticipated
Actual
22/03/2021
Sample size
Target
1430
Accrual to date
Final
1366
Recruitment in Australia
Recruitment state(s)
NSW

Funding & Sponsors
Funding source category [1] 307181 0
University
Name [1] 307181 0
Marie Bashir Institute at the University of Sydney
Country [1] 307181 0
Australia
Primary sponsor type
University
Name
Marie Bashir Institute at the University of Sydney
Address
Westmead Institute for Medical Research, 176 Hawkesbury Road, Westmead NSW 2145
Country
Australia
Secondary sponsor category [1] 307932 0
None
Name [1] 307932 0
Address [1] 307932 0
Country [1] 307932 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 307294 0
Human Research Ethics Committee, The University of Sydney
Ethics committee address [1] 307294 0
Administration Building (F23)
The University of Sydney
NSW
2006
Ethics committee country [1] 307294 0
Australia
Date submitted for ethics approval [1] 307294 0
04/11/2020
Approval date [1] 307294 0
28/11/2020
Ethics approval number [1] 307294 0
2020/781

Summary
Brief summary
COVID-19 response in Australia relies on people getting tested should they experience symptoms; however, national data indicate suboptimal uptake.
This study aims to improve the uptake of COVID-19 testing by addressing peoples’ specific reasons for not getting tested. We will test the following research questions:
(1) Can we improve understanding of government testing messages, by making the messages simpler?
(2) Can we improve peoples’ intention to get tested by tailoring prevention information to their specific testing barriers, and making the messaging more persuasive?
(3) Can we increase the number of people getting tested using action plans tailored to their specific testing barriers?
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 106722 0
Prof Kirsten McCaffery
Address 106722 0
Edward Ford Building A27, The University of Sydney, NSW, 2006, Australia
Country 106722 0
Australia
Phone 106722 0
+61 2 9351 7220
Fax 106722 0
Email 106722 0
kirsten.mccaffery@sydney.edu.au
Contact person for public queries
Name 106723 0
Dr Carissa Bonner
Address 106723 0
Edward Ford Building A27, The University of Sydney, NSW, 2006, Australia
Country 106723 0
Australia
Phone 106723 0
+61 2 9351 7125
Fax 106723 0
Email 106723 0
Carissa.bonner@sydney.edu.au
Contact person for scientific queries
Name 106724 0
Dr Carissa Bonner
Address 106724 0
Edward Ford Building A27, The University of Sydney, NSW, 2006, Australia
Country 106724 0
Australia
Phone 106724 0
+61 2 9351 7125
Fax 106724 0
Email 106724 0
Carissa.bonner@sydney.edu.au

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
Yes
What data in particular will be shared?
Anonymous quantitative data on outcomes for each group - individual participant data regarding the primary and secondary outcomes
When will data be available (start and end dates)?
2021-2023
Available to whom?
Any researchers who wish to access the data
Available for what types of analyses?
quantitative analysis
How or where can data be obtained?
University of Sydney repository, accessed by emailing the principal investigator, Carissa Bonner (carissa.bonner@sydney.edu.au)


What supporting documents are/will be available?

Doc. No.TypeCitationLinkEmailOther DetailsAttachment
9875Study protocol    380916-(Uploaded-26-11-2020-15-52-13)-Study-related document.docx



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.