ClinicalTrials.gg
CompletedNCT03431012Updated Dec 16, 2019Results posted

Improving Communication During a Pandemic Flu Outbreak

An interventional study of Agency Assignment framing and Attribute framing in Healthy, sponsored by King's College London. Completed. Open to participants aged 18 Years to 65 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2019-12-16.

Sponsored by King's College London · Not applicable, Interventional, and Prevention

From the registry’s dates

  • Registered 1 year 7 months after the study started (first participant enrolled May 2016, registered Jan 2018).
Phase
Not applicable
Study type
Interventional
Enrollment
349
Allocation
Randomized
Ages
18 Years to 65 Years
Sex
All
01

Study summary

During the last pandemic influenza antivirals were prescribed both as prophylaxis and treatment. However, adherence rates were suboptimal. This study assessed the effect of theory-based and evidence-based health messages, which promoted the use of antivirals as prophylaxis for pandemic influenza, on intentions to use antivirals. Using hypothetical scenarios, the investigators tested whether written health communications about pandemic flu and recommended preventative medication (i.e. a prophylactic treatment with antivirals) had an effect on study participants' beliefs about the pandemic flu and the advice received, and their intention to adhere to the recommendation. In particular, the investigators assessed the behavioural impact of health messages presented in four different linguistic formats, defined by a 2×2 (agency assignment × attribute framing) factorial design. The originality of this study relies on the attempt to maximise the behavioural impact of written health messages by combining the agency assignment and attribute framings, which have never been tested together, and by systematically targeting specific predictors of adherence intentions through these messages. The findings of this study may be used to improve the behavioural impact of health communications to the general public in case of a pandemic flu outbreak in the UK.

Read the detailed description

Background: In 2009, a new strain of influenza virus, called pandemic influenza A(H1N1)pdm09, was detected in humans. During the pandemic in 2009/2010, antiviral medications were prescribed both as prophylaxis and treatment for influenza. However, many people, including those with chronic health conditions, did not used the antivirals as prescribed. This study focused on adherence to antivirals used as prophylaxis, as this is a key preventative stage before any vaccine can be available to the public. To ensure protection of public health during public health emergencies, such as pandemic flu, it is essential that the general public follow the health advice received. Therefore, future risk communications about the use of antivirals for pandemic influenza will need to address the barriers and facilitators of adherence.

This study investigated the effect of theory-based and evidence-based health messages, which promoted the use of antivirals as prophylaxis for pandemic influenza, on intentions to use antivirals. In particular, using hypothetical scenarios, the investigators tested whether written health communications about pandemic flu and recommended preventative medication (i.e. a prophylactic treatment with antivirals) had an effect on study participants' beliefs about the pandemic flu and the advice received, and their intention to adhere to the recommendation.

The linguistic manipulation used in the present study was based on an adaptation of a successful manipulation carried out by McGlone et al. (2013), who found that using the virus agency assignment in medical factsheets increased students' perception of susceptibility to and worry about the virus A/H1N1, perception of the severity of the consequences of catching the virus, perception of efficacy of the vaccine and reported intention to get the vaccine compared to the human agency assignment. The investigators wanted to test whether these results could be replicated in the context of taking antivirals for pandemic flu, using a more representative sample of the general population and controlling for baseline intentions.

For what concerns the framing of the side effects, research shows that the way information on medication side-effects is presented affects people's intentions to accept the recommended medications. The same side-effect likelihood can be expressed in a positively framed message (i.e. 90% of people will not develop side-effects) or in negatively framed message (i.e. 10% of people will develop side-effects). Although a previous meta-analysis (Moxey et al. 2003) found no significant framing effect on either actual immunization or behavioural intention, it found that positively framed information increased positive attitudes toward immunization and perception of the benefits of immunization, decreased expectation of side-effects and led to a more realistic understanding of the side-effects of influenza vaccines.

In addition, the health messages used in this study targeted specific variables, which have been in the past associated with higher adherence to antivirals for pandemic influenza. In particular, a recently published systematic review (Smith et al. 2016) investigated the factors affecting adherence to antivirals for influenza, including pandemic flu. They included 26 studies, of which 23 assessed pandemic influenza. Although many of the reviewed studies had serious methodological flaws, the review identified several psychosocial factors associated with adherence to antivirals prescribed as prophylaxis for pandemic flu. In particular, 11 studies investigated actual adherence to prophylactic antivirals. These studies showed that actual adherence was associated with previous adherence to other preventative measures for pandemic flu, beliefs that the recommended prophylactic measures were necessary and having discussed taking oseltamivir, a commonly used antiviral, with someone who had not experienced side effects. Although only one study found that the presence of side-effects was a significant predictor of non-adherence, the occurrence of side-effects was the most commonly self-reported reason for the discontinuation of oseltamivir. The review also included 8 studies investigating psychosocial predictors of intention to adhere: for instance, higher perceived susceptibility to the pandemic flu, higher perceived severity of pandemic flu, knowledge of pandemic flu, higher self-efficacy and response efficacy, and having previously accepted the flu vaccine were all associated with higher adherence intentions.

Methods: In May/June 2016 the investigated conducted an online experiment. After reading a hypothetical pandemic flu scenario, 349 adult UK residents were randomly allocated to one of four conditions, defined by a 2x2 (agency assignment × attribute framing of side effects) factorial design. Each condition presented messages describing the pandemic flu using linguistic expressions that assigned agency to either the humans (HA: human agency) or the virus itself (VA: virus agency), whilst describing the antivirals side effects in terms of the chances of either experiencing (NF: negative framing) or not experiencing side effects (PF: positive framing). Although presented with different framings the health messages provided equivalent information that targeted specific predictors of adherence. Participants were blinded to group assignment. Intentions to use the antivirals and potential mediating factors were measured. The aim was to understand the potential behavioural impact of the four health messages developed and to better understand the factors influencing adherence intentions.

02

Conditions studied

  • Healthy

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Keywords

  • Adherence, medication
  • Pandemic Influenza
03

In context

Medication Adherence

937 studies on the registry are indexed under Medication Adherence; 159 are open to participants now.

This study's enrollment of 349 is above the median of 120 across 768 interventional studies indexed under Medication Adherence.

Browse Medication Adherence studies →

Lead sponsor

King's College London is the lead sponsor of 520 studies on the registry; 126 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 65 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • To be eligible to participate, respondents had to be members of the UK general public in the adult age range (18-65 years), and be fluent in English.

Exclusion criteria

Exclusion Criteria:

  • non-UK residents
  • younger than 18 or older than 65
  • not fluent in English
05

Study design

Phase
Not applicable
Primary purpose
Prevention
Allocation
Randomized
Intervention model
Factorial assignment
Masking
Single (Participant)
Enrollment
349 participants (actual)

Study arms

  • Experimental
    Virus Agency/Negative Attribute Framing

    Participants in this condition, after reading a hypothetical scenario, received health messages describing the pandemic flu and the efficacy of the antivirals using linguistic expressions that assigned transmission to the pandemic flu virus itself (Virus Agency Assignment framing), whilst describing the side effects of the antivirals in terms of chances of experiencing side effects after using them (Negative Framing).

    Other: Agency Assignment framing · Other: Attribute framing

  • Experimental
    Human Agency/Negative Attribute Framing

    Participants in this arm, after reading a hypothetical scenario, received a health message describing the pandemic flu and the efficacy of the antivirals using linguistic expressions that assigned transmission to humans (Human Agency Assignment framing), whilst describing the side effects of the antivirals in terms of chances of experiencing side effects after using them (Negative Framing health messages).

    Other: Agency Assignment framing · Other: Attribute framing

  • Experimental
    Human Agency /Positive Attribute Framing

    Participants in this arm, after reading a hypothetical scenario, received a health message describing the pandemic flu and the efficacy of the antivirals using linguistic expressions that assigned transmission to humans (Human Agency Assignment framing), whilst describing the side effects of the antivirals in terms of chances of not experiencing side effects after using them (Positive Framing).

    Other: Agency Assignment framing · Other: Attribute framing

  • Experimental
    Virus Agency /Positive Attribute Framing

    Participants in this arm, after reading a hypothetical scenario, received a health message describing the pandemic flu and the efficacy of the antivirals using linguistic expressions that assigned transmission to the pandemic flu virus itself (Virus Agency Assignment framing), whilst describing the side effects of the antivirals in terms of chances of not experiencing side effects after using them (Positive Framing).

    Other: Agency Assignment framing · Other: Attribute framing

Interventions

  • OtherAgency Assignment framing

    Linguistic framing used in written health messages. Each version of the messages described the pandemic flu and the efficacy of the antivirals using linguistic expressions that assigned transmission to either humans (HA: 'You can contract the virus when you touch...') or the pandemic flu virus itself (VA: 'It can infect you when you touch...')

    Also known as: Framing effect on behavioural intentions

  • OtherAttribute framing

    Linguistic framing used in written health messages. Each message described the side effects of the antivirals in terms of chances of either experiencing (negative framing: 'Uncommon side effects (10% of people will be affected)') or not experiencing side effects (positive framing: 'Uncommon side effects (90% of people will not be affected)') after using them.

    Also known as: Framing effect on behavioural intentions

06

What researchers measure

Primary outcomes

  1. Change in Intentions to Take Antivirals for Pandemic Flu

    Mean adherence intentions post- exposure to the health information in the 4 groups. Intentions were measured by self-report items: participants were asked to agree with three statements about their intentions to take antivirals as recommended in the hypothetical scenario (on 9-point scale, where 1=strongly disagree to 9=strongly agree). The scores reported below represent a composite variable 'change in intentions', which reflects the average of the three items that compose it.

    Time frame: Straight after exposure to the health messages

Secondary outcomes

  1. Worry of the Pandemic Flu Threat

    Measured by self-report items adapted from Witte et al. (2001): participants were asked to agree with two statements about their perceived worry on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of reported worry about pandemic flu threat. This is a composite variable reflecting the average of the items that compose it.

    Time frame: At 20 minutes (i.e. straight after exposure to the health messages)

  2. Perceived Susceptibility to the Pandemic Flu

    Measured by self-report items: participants were asked to state how likely they were to get sick with pandemic flu, had they not taken prophylactic medication o a 9-point scale, where 1=not likely at all, to 9=extremely likely.

    Time frame: At 20 minutes (i.e. straight after exposure to the health messages)

  3. Perceived Severity of the Pandemic

    Measured by one self-report item (adapted from Witte et al. (2001): participants were asked to agree with a statement about their perception of the severity of the pandemic flu on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of perceived severity of the pandemic flu threat.

    Time frame: At 20 minutes (i.e. straight after exposure to the health messages)

  4. Perceived Self-efficacy

    Measured by one self-report item (adapted from Witte et al. (2001): participants were asked to agree with a statement about their perceived ability to take the antivirals as recommended on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of reported self-efficacy.

    Time frame: At 20 minutes (i.e. straight after exposure to the health messages)

  5. Perceived Efficacy of the Antivirals

    Measured by two self-report items (adapted from Godinho et al. (2016): participants were asked to agree with two statements about their perception of the efficacy of the antivirals against pandemic flu on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of perceived efficacy of the antivirals. This is a composite variable reflecting the average of the items that compose it.

    Time frame: At 20 minutes (i.e. straight after exposure to the health messages)

  6. Perceived Response Costs

    Measured by self-report items adapted from Godinho et al. (2016): participants were asked to agree with four statements about their beliefs about the side effects and negative consequences of using antivirals on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of perceived response costs. This is a composite variable reflecting the average of the items that compose it.

    Time frame: At 20 minutes (i.e. straight after exposure to the health messages)

07

Results

Posted Dec 16, 2019

Participant flow

Participant flow — Overall Study
MilestoneVirus Agency/Negative Attribute FramingHuman Agency/Negative Attribute FramingHuman Agency /Positive Attribute FramingVirus Agency /Positive Attribute Framing
Started47605653
Completed47605653
Not completed0000

Outcome measures

PrimaryChange in Intentions to Take Antivirals for Pandemic Flu

Mean adherence intentions post- exposure to the health information in the 4 groups. Intentions were measured by self-report items: participants were asked to agree with three statements about their intentions to take antivirals as recommended in the hypothetical scenario (on 9-point scale, where 1=strongly disagree to 9=strongly agree). The scores reported below represent a composite variable 'change in intentions', which reflects the average of the three items that compose it.

Time frame:
Straight after exposure to the health messages
Reported as:
Mean · score on a scale
Change in Intentions to Take Antivirals for Pandemic Flu
score on a scaleVirus Agency/Negative Attribute FramingHuman Agency/Negative Attribute FramingHuman Agency /Positive Attribute FramingVirus Agency /Positive Attribute Framing
Change in Intentions to Take Antivirals for Pandemic Flu8.29 ± 0.128.16 ± 0.128.23 ± 0.128.35 ± 0.11
Statistical analysis
  • Virus Agency/Negative Attribute Framing vs Human Agency/Negative Attribute Framing vs Human Agency /Positive Attribute Framing vs Virus Agency /Positive Attribute Framing · ANCOVA · p = >.05 (Sidak corrections were used to adjust for multiple analyses.)ANCOVAs, setting baseline intentions as a covariate, were performed to determine whether post-exposure mean intentions differed between groups.
SecondaryWorry of the Pandemic Flu Threat

Measured by self-report items adapted from Witte et al. (2001): participants were asked to agree with two statements about their perceived worry on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of reported worry about pandemic flu threat. This is a composite variable reflecting the average of the items that compose it.

Time frame:
At 20 minutes (i.e. straight after exposure to the health messages)
Reported as:
Mean · score on a scale
Worry of the Pandemic Flu Threat
score on a scaleHuman AgencyVirus Agency
Worry of the Pandemic Flu Threat6.06 ± 0.196.50 ± 0.20
Statistical analysis
  • Human Agency vs Virus Agency · MANOVA · p = =.113 (Sidak corrections were used to adjust for multiple analyses.)
SecondaryPerceived Susceptibility to the Pandemic Flu

Measured by self-report items: participants were asked to state how likely they were to get sick with pandemic flu, had they not taken prophylactic medication o a 9-point scale, where 1=not likely at all, to 9=extremely likely.

Time frame:
At 20 minutes (i.e. straight after exposure to the health messages)
Reported as:
Mean · score on a scale
Perceived Susceptibility to the Pandemic Flu
score on a scaleHuman AgencyVirus Agency
Perceived Susceptibility to the Pandemic Flu6.32 ± 0.146.37 ± 0.15
Statistical analysis
  • Human Agency vs Virus Agency · MANOVA · p = =.809 (Sidak corrections were used to adjust for multiple analyses)
SecondaryPerceived Severity of the Pandemic

Measured by one self-report item (adapted from Witte et al. (2001): participants were asked to agree with a statement about their perception of the severity of the pandemic flu on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of perceived severity of the pandemic flu threat.

Time frame:
At 20 minutes (i.e. straight after exposure to the health messages)
Reported as:
Mean · score on a scale
Perceived Severity of the Pandemic
score on a scaleHuman AgencyVirus Agency
Perceived Severity of the Pandemic5.92 ± 0.196.59 ± 0.21
Statistical analysis
  • Human Agency vs Virus Agency · MANOVA · p = 0.025 (Sidak corrections were used to adjust for multiple analyses.)
SecondaryPerceived Self-efficacy

Measured by one self-report item (adapted from Witte et al. (2001): participants were asked to agree with a statement about their perceived ability to take the antivirals as recommended on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of reported self-efficacy.

Time frame:
At 20 minutes (i.e. straight after exposure to the health messages)
Reported as:
Mean · score on a scale
Perceived Self-efficacy
score on a scaleHuman AgencyVirus Agency
Perceived Self-efficacy8.23 ± 0.128.45 ± 0.13
Statistical analysis
  • Human Agency vs Virus Agency · MANOVA · p = =0.199 (Sidak corrections were used to adjust for multiple analyses.)
SecondaryPerceived Efficacy of the Antivirals

Measured by two self-report items (adapted from Godinho et al. (2016): participants were asked to agree with two statements about their perception of the efficacy of the antivirals against pandemic flu on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of perceived efficacy of the antivirals. This is a composite variable reflecting the average of the items that compose it.

Time frame:
At 20 minutes (i.e. straight after exposure to the health messages)
Reported as:
Mean · score on a scale
Perceived Efficacy of the Antivirals
score on a scaleNegative FramingPositive Framing
Perceived Efficacy of the Antivirals6.45 ± 0.156.59 ± 0.14
Statistical analysis
  • Negative Framing vs Positive Framing · MANOVA · p = =0.484 (Sidak corrections were used to adjust for multiple analyses.)
SecondaryPerceived Response Costs

Measured by self-report items adapted from Godinho et al. (2016): participants were asked to agree with four statements about their beliefs about the side effects and negative consequences of using antivirals on 9-point scale, from 1=strongly disagree to 9=strongly agree. Higher scores indicate higher levels of perceived response costs. This is a composite variable reflecting the average of the items that compose it.

Time frame:
At 20 minutes (i.e. straight after exposure to the health messages)
Reported as:
Mean · score on a scale
Perceived Response Costs
score on a scaleNegative FramingPositive Framing
Perceived Response Costs3.53 ± 0.173.70 ± 0.17
Statistical analysis
  • Negative Framing vs Positive Framing · MANOVA · p = =0.494 (Sidak corrections were used to adjust for multiple analyses.)

Adverse events

Non-serious events are listed at a 0% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
Virus Agency/Negative Attribute Framing———
Human Agency/Negative Attribute Framing———
Human Agency /Positive Attribute Framing———
Virus Agency /Positive Attribute Framing———

Baseline characteristics

Age, Customized
Age, Customized(Participants)Virus Agency/Negative Attribute FramingHuman Agency/Negative Attribute FramingHuman Agency /Positive Attribute FramingVirus Agency /Positive Attribute FramingTotal
Age Range — 18-24 years2225211583
Age Range — 25-34 years1621242182
Age Range — 35-49 years71471341
Age Range — 50+ years204410
Sex: Female, Male
Sex: Female, Male(Participants)Virus Agency/Negative Attribute FramingHuman Agency/Negative Attribute FramingHuman Agency /Positive Attribute FramingVirus Agency /Positive Attribute FramingTotal
Female28353328124
Male1925232592
Race/Ethnicity, Customized
Race/Ethnicity, Customized(Participants)Virus Agency/Negative Attribute FramingHuman Agency/Negative Attribute FramingHuman Agency /Positive Attribute FramingVirus Agency /Positive Attribute FramingTotal
Ethnicity — White29514243165
Ethnicity — Other189141051
Baseline Intentions to take the antivirals as recommended
Baseline Intentions to take the antivirals as recommended(units on a scale)Virus Agency/Negative Attribute FramingHuman Agency/Negative Attribute FramingHuman Agency /Positive Attribute FramingVirus Agency /Positive Attribute FramingTotal
Mean8.16 ± 0.217.93 ± 0.197.95 ± 0.198.26 ± 0.208.08 ± 0.10
08

Study locations

No study locations are listed for this record.

09

References and documents

Publications

  • McGlone MS, Bell RA, Zaitchik ST, McGlynn J 3rd. Don't let the flu catch you: agency assignment in printed educational materials about the H1N1 influenza virus. J Health Commun. 2013;18(6):740-56. doi: 10.1080/10810730.2012.727950. Epub 2012 Dec 5. PubMed 23216010 ↗
  • Moxey A, O'Connell D, McGettigan P, Henry D. Describing treatment effects to patients. J Gen Intern Med. 2003 Nov;18(11):948-59. doi: 10.1046/j.1525-1497.2003.20928.x. PubMed 14687282 ↗
  • Smith LE, D'Antoni D, Jain V, Pearce JM, Weinman J, Rubin GJ. A systematic review of factors affecting intended and actual adherence with antiviral medication as treatment or prophylaxis in seasonal and pandemic flu. Influenza Other Respir Viruses. 2016 Nov;10(6):462-478. doi: 10.1111/irv.12406. Epub 2016 Aug 8. PubMed 27397480 ↗

Individual participant data

Plan to share: No

10

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reachedSimilar studies: half by the dot; the band is the middle halfHalf of similar studies reached it by the dot; the band is the middle half, from a quarter to three quarters

Ran from May 2016 to primary completion in Jun 2016, 0 months.

Results were first posted in Dec 2019, 3 years 6 months after primary completion.

Of 425 non-industry interventional studies with no phase under Medication Adherence, half reached primary completion within 22 months of starting (the median), counting those still running; a quarter within 11 and three quarters within 42. This study's 0 months is below that.

Counting every sponsor, half of 442 studies reached it within 21 months; a quarter within 11 and three quarters within 41.

How these figures are worked out, and which studies are left out of them.

Registered
Jan 17, 2018
First posted
Feb 13, 2018
StartActual
May 26, 2016
Primary completionActual
Jun 8, 2016
CompletionActual
Jun 8, 2016
Results first posted
Dec 16, 2019
Last update
Dec 16, 2019
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on Dec 16, 2019, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
11

Registry details

Key details

Study ID
NCT03431012
Collaborators
National Institute for Health Research, United Kingdom, Public Health England
Responsible party
Sponsor
First posted
Feb 13, 2018
Start date
May 26, 2016
Primary completion
Jun 8, 2016
Completion
Jun 8, 2016
Results posted
Dec 16, 2019
Last update
Dec 16, 2019

Study contacts

Donatella D'Antoni
principal investigator · King's College London

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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