Tag Archives: Behaviour

Speaking to Hearts Before Minds: Increasing Influenza Vaccine Uptake During COVID-19

In 2019, the UK health secretary Matt Hancock said that he is “open” to making vaccines compulsory, and Labour MP Paul Sweeney argued that failure to vaccinate children should be a “criminal offence”. But mandates are difficult to enforce, and punishments diminish public trust. In addition, people still opt out of mandatory policies, and effectiveness increases when people freely comply.[1] Instead of mandates, we advocate behavioural approaches that preserve individual freedom,[2] and agree with Professor Heidi Larson that additional emphasis should be placed on public perspectives when planning vaccine policies and programmes.[3]

Public health messaging about vaccines is particularly important in light of the COVID-19 pandemic. In April 2020, the United Kingdom’s ‘Vaccine Taskforce’ convened, and, in May 2020, the United States’ ‘Operation Warp Speed’ took off. This speed elicited optimism among some, but handed a megaphone to the anti-vaccination movement. Del Bigtree, founder of the Information Consent Action Network, cautioned that, “You shouldn’t rush to create a product you can inject into perfectly healthy people without doing proper safety studies”. Here, identical factual information – a vaccine is being developed quickly – elicited reasoned responses that were both optimistic and pessimistic. However, intuitions come first and strategic reasoning comes second.[4] Where public health messages do not align with people’s automatic intuitions, factual and reasoned information may fall on deaf ears.

On September 21, we conducted an online experiment to determine if public health messages aligned with people’s political intuitions influenced their intentions to take up the influenza vaccine.[5] Influenza vaccinations have long been important, but are particularly important now in the context of COVID-19 because co-infection increases mortality rates.[6] We recruited 192 participants living in England, aged 50 years+, who had not already vaccinated this season. Half of these participants identified as being affiliated with the Labour party, and half with the Conservative party. Participants viewed a message either aligned or unaligned with their automatic political intuitions (see Figures 1 and 2). Then they stated how much they agreed with a statement about their intentions to take up the influenza vaccine this season on a 7-point scale, where higher numbers indicated more positive intentions.

Fig 1. Left-Wing Message (aligned with Labour)
Fig 2. Right-Wing Message (aligned with Conservative)

Professor Jonathan Haidt describes the automatic intuitions we set out to influence as moral foundations.[4] Typically, people who identify as being more left-wing are most strongly influenced by their care and fairness intuitions (a desire to prevent harm to others and to ensure equality). In contrast, people who identify as being more right-wing are more strongly influenced by the remaining foundations: purity (a desire to avoid contaminants), authority (to preserve traditions), loyalty (to strengthen group bonds), and liberty (to preserve individual freedom).

Research conducted in the United States and Australia has already identified some of the foundations associated with parental vaccine hesitancy, and suggests that public health messages can be framed to increase parents’ intentions.[7,8] For example, a message designed to promote purity might say: Boost your child’s natural defenses against diseases! – Vaccinate! These proposals are a good start, but without evidence that they are likely to be effective, public health practitioners have little reason to prefer them to the messages developed in-house. The messages used in the present study were informed by messages used in a previous study that significantly altered people’s intentions to recycle.[9]

Our main prediction was that our left-wing message would increase labour participants’ intentions, and our right-wing message would increase conservative participants’ intentions. We did not find this. As shown in Figure 3, there was no substantial effect of the messages. One explanation is that the moral foundations used in our advertisements were not relevant in a UK context, which we plan to address in future work. We aim to conduct a general UK survey describing moral foundations in the population and use the survey results to inform a collaborative online workshop with public contributors and health specialists, which is in keeping with Professor Heidi Larson’s calls to involve public perspectives. This pilot study lays the groundwork for such future research.

Fig 3. Results of the study testing the effects of messages on vaccination intentions as measured by average agreement with the statement: “I intend to receive an influenza vaccination this season [2020/21].”

We asked people some follow up questions too. In a free-text box, participants were asked to explain their intentions to (or not to) vaccinate. Their explanations largely fell within five categories, which, in addition to their foundations, may have been influenced by the messages they read: Protect Self, Protect Others, Protect the NHS, Being Eligible/Invited, and Habits. We also asked questions about people’s intentions of taking up a COVID-19 vaccination and wearing a face mask. Similar to recent research,[10] people were more likely to express intentions to take up a future COVID-19 vaccination (72%) than the current influenza vaccination (65%). We suspect that these expressed intentions may be a bit optimistic. Indeed, most participants (89%) also expressed that they would wear a face mask in a store that did not require them to do so, which is higher than our casual observations at the grocery store around the time of the experiment (before additional penalties were introduced). Acquiescence bias may have led our participants to be agreeable in this survey, particularly as participants just saw messages promoting health-related behaviour. But this need not preclude identifying meaningful differences between randomised conditions. Our research team looks forward to better understanding the intuitive influences on vaccination behaviour.

Kelly Ann Schmidtke (Assistant Professor) and Laura Kudrna (Research Fellow)

References:

  1. Salmon DA, et al. Compulsory vaccination and conscientious or philosophical exemptions: past, present, and future. Lancet. 2006;367(9508):436-42.
  2. Sunstein C & Thaler R. Libertarian Paternalism. Am Econ Rev. 2003; 93(2): 175-9.
  3. Larson HJ et al. Addressing the vaccine confidence gap. Lancet. 2011;378:526-35.
  4. Haidt J. The righteous mind: why good people are divided by politics and religion. New York: Pantheon Books; 2012.
  5. U.S. National Library of Medicine. ClinicalTrials.gov Influenza 2020/2021. NCT04546854. 14 September 2020.
  6. Iacobucci G. Covid-19: Risk of death more than doubled in people who also had flu, English data show. BMJ. 2020;370:m3720.
  7. Amin AB, et al. Association of moral values with vaccine hesitancy. Nat Hum Behav. 2017;1(12):873-80.
  8. Rossen I, et al. Accepters, fence sitters, or rejecters: moral profiles of vaccination attitudes. Soc Sci Med. 2019;224(1):23-7.
  9. Kidwell B, et al. Getting Liberals and Conservatives to Go Green: Political Ideology and Congruent Appeals. J Cons Res. 2013; 40(2):350–67.
  10. Boseley S. Coronavirus: fifth of people likely to refuse Covid vaccine, UK survey finds. The Guardian. 24 September 2020.

Walking Through the Digital Door: Video Consultations During COVID-19 and Beyond

The “NHS Long-Term Plan” (2019) is a five-year plan describing how NHS services should be redesigned for the next decade. This plan includes making better use of digital technologies, such as video consultations. While video consultations have potential advantages for patients and hospital systems,[1] they may make patients uncomfortable. If patients do not walk through the ‘digital door’ to attend a video consultation, then potential advantages cannot be realised. Likely the motto of “build it and they will come” is insufficient. Instead, we need to support patients so that they come the first time and return after that. 

What support that patients need is, at least in part, an empirical question that we plan to address in a future study. One way to support attendance may be with the behavioural science principle of ‘defaults’ – people tend to ‘go with the flow’ of pre-set options.[2] Defaults have been used to influence organ donations by adding the word ‘don’t’ to an application, i.e. “If you want to be an organ donor, please check here,” vs. “If you don’t want to be an organ donor, please check here”. In a simulated study, 42% of people opted-in to become organ donors given the original phrasing, and 82% did not opt-out given the second.[3] In other words, the realised organ donation rate nearly doubled by changing the default option. Until April 2020 England had an opt-in system with 38% of people having opted-in to become organ donors. When England’s law changed to an opt-out system in May 2020 the assumed donor rate has increased instantly. Time will tell how many people fill out the form to opt-out, but the present authors suspect the resultant donor rate to remain higher than 38%.

Defaults have been used to influence people’s behaviour in many contexts, e.g. how much money people save for retirement,[4] physicians’ medication use,[5] and purchases of healthy foods.[6] At least three psychological mechanisms are at play: endorsement (believing the proposed default is recommended), endowment (believing the default is normal), and ease (taking up the proposed default is simpler than refusing it).[7,8] Re-framing an invitation to attend an outpatient appointment from ‘in-person’ to ‘video’ creates a new default ‘endorsed’ mode of attendance that is ‘easier’ to accept than refuse. However, if a substantial number of patients refuse an invitation to attend a video consultation, this would suggest that more support is needed to garner people’s acceptance.

An ideal experimental test of the default effect on out-patient appointment attendance would occur in the field setting, similar to our work on influenza vaccination letters.[9] But (without tremendous follow-up efforts) this approach provides a limited ability to explore barriers and facilitators patients believe influence their choices. These beliefs undoubtably influence whether patients attend. To explore how default options and beliefs influence whether patients accept an invitation to attend a video consultation, we will conduct a simulated study with patients from the site Prolific Academic. Prolific Academic contains thousands of people prepared to answer researchers’ questions who can be filtered on criteria such as health status, age, and education. Our research will utilise an online experiment with quantitative and qualitative items. We plan to compare our findings to real hospital data on video consultations before and after COVID-19, which may have provided the impetus for more patients to engage in digital healthcare. 

Conversations with researchers across ARC WM’s themes and with public contributors suggest several barriers and facilitators to the uptake of video consultations. For instance, while the location of in-person consultations was obvious, video consultations require patients to make an additional choice about where they feel comfortable attending. Whether attending from home or work, new privacy concerns arise regarding what other people can overhear across physical and digital space. Our research will show how much such concerns matter to patients, and suggest what additional support should be offered to increase patients’ attendance within their invitation to attend. If COVID-19 hasn’t provided the push that patients need to walk through the digital door, this research will help us understand why. Equally, if it has, we will be better equipped to sustain and expand the shift, and in so doing help realise the NHS Long-Term Plan.

Kelly Ann Schmidtke (Assistant Professor) and Laura Kudrna (Research Fellow)


References:

  1. Greenhalgh T, et al. Virtual Online Consultations: Advantages and Limitations (VOCAL) Study. BMJ Open 2016; 6: e009388. 
  2. Dolan P, et al. Influencing Behaviour: The Mindspace Way. J Econ Psychol. 2012; 33(1): 264-77.
  3. Johnson EJ, Goldstein D. Do Defaults Save Lives? Science. 2003; 302(5649): 1338-9. 
  4. Madrian BC, Shea DF. The Power of Suggestion: Inertia in 401(k) Participation and Savings Behaviour. Q J Econ. 2001; 116(4):1149–87. 
  5. Ansher C, et al. Better Medicine by Default. Med Decis Making. 2014; 34(2):147-58. 
  6. Peters J, et al. Using Healthy Defaults in Walt Disney World Restaurants to Improve Nutritional Choices. J Assoc Consum Res. 2016; 1(1): 92-103.
  7. Jachimowicz JM, et al. When and Why Defaults Influence Decisions: a Meta-Analysis of Default Effects. Behav Public Policy. 2019; 3(2): 159-86. 
  8. Dinner I, et al. Partitioning Default Effects: Why People Choose Not to Choose. J Exp Psychol Appl. 2011; 17(4): 332-41. 
  9. Schmidtke KA, et al. Randomised controlled trial of a theory-based intervention to prompt front-line staff to take up the seasonal influenza vaccine. BMJ Qual Saf. 2020; 29(3): 189-97.

Changing the Message to Change the Response – Psychological Framing Effects During COVID-19

The way in which a government communicates can shape people’s responses. Psychological and behavioural research reveals that the same objective information can elicit different responses when presented in different ways, an effect called ‘framing’.[1] For example, one study compared describing blood donations as either a way to “prevent a death” or “save a life”.[2] While preventing death and saving life are two sides of the same coin, “prevent a death” triggered more donations. These results are explained, at least in part, by a prevalent loss-aversion bias. As Kahneman and Tversky (1979) explain: losses loom larger than gains.[3] 

In 1981, Kahneman and Tversky asked people to imagine that the US was preparing for a disease outbreak that was expected to kill 600 people.[1] Participants were asked to choose between two government programmes. In one scenario, participants considered saving lives: given programme A, 200 lives would be saved; and given programme B, there was a 1/3 probability that 600 lives would be saved and 2/3 probability that no lives would be saved. While mathematically these programmes are equivalent, 72% preferred programme A (109/152 participants). A second group of participants considered preventing deaths: given programme C, 400 would die; and given programme D, there was a 1/3 probability that nobody would die and 2/3 probability that 600 people will die. This time, 78% chose programme D (121/155 participants). Flipping the vocabulary coin flipped people’s preferences. 

In March 2020, we set out to test whether these results would hold when applied to COVID-19. We created two scenarios with identical options to Kahneman and Tversky’s but changed the wording to be about COVID-19 and social/physical distancing. The study was ethically approved and in early July we invited UK participants via Prolific Academic to respond to a randomly allocated scenario. The data were collected in less than two hours. The pattern of results held – participants preferred programme A over B (21/30 = 70%) and D over C (23/30 = 77%). Interesting, but perhaps insufficient to inform the way messages are presented to the public to influence their more personal decisions, such as about visitors at home.

The UK government’s initial messaging strategy about personal decisions emphasised that people needed to say home in order to “save lives”. A later campaign framed this differently, stressing that “people will die” if they go out. Does flipping the vocabulary coin here matter? We, and others, suspect that it does. There have been several opinion pieces on psychologically informed messaging,[4] although we are unaware of any published research results that have tested framing effects in the context of COVID-19. 

We created six further personal scenarios. These scenarios varied across three situations and two frames. Participants were asked whether they would be willing to have a friend over (yes/no), attend a crowded work meeting (yes/no), and download a contact tracing app (yes/no). Each situation was framed in two ways – as about a choice to save lives or prevent deaths. An excerpt from the story about inviting a friend over is provided here: 

Imagine that the town of Pleasantville… is preparing for the outbreak of the Coronavirus (COVID-19), which is expected to kill 600 people. They decide to adopt a social/physical distancing programme to prevent the spread of COVID-19 that is expected to [save 200 lives / prevent 400 deaths]. Social/physical distancing is when people reduce social interaction to stop the spread of a disease, such as by working from home and avoiding gatherings in public spaces. Your good friend calls you and says they want to come over to discuss the announcement… 

What do you say to your friend? Yes, come over / No, don’t come over

If losses loom larger than gains in more personal scenarios, then we should expect messages framed as ‘preventing death’ to have stronger effects across situations. The pilot results are shown in Figure 1. There was no substantial effect of message framing, although the situation made some difference. Nobody was willing to let a friend visit their home, some people said they would attend a work meeting, and the majority would download a contact tracing app.


Fig 1: Results of the study testing framing effects about saving lives versus preventing death

What can explain these results? One possibility is social desirability bias. People may wish to appear as if they would take action to prevent COVID-19 spreading, even if they would not in everyday life. 

Timing may also matter. When we conducted our study, people may have been sufficiently fearful of the consequences of COVID-19 that they were willing to comply with guidelines and recommendations, regardless of the message framing. It is possible that earlier on in the pandemic, we would have found different results.  

Another explanation is that, unlike the government programmes scenarios, the alternative options in the more personal scenarios did not state certain and probabilistic qualities. For the government programme scenarios, when the options were framed as saving lives, participants wanted to secure the safe-but-sure option. One participant explained their response by saying, “The 1/3 probability means the same 200 die but the [other] option appears to guarantee saved lives”. Alternatively, when the options are framed negatively, people wanted to roll the proverbial dice. One participant explained that, “The overall odds are the same but the chance for no one dying is worthwhile”. In contrast, the risk regarding personal decisions is uncertain because many outcomes for COVID-19 are uncertain. It may be that loss aversion is more pronounced when people make policy choices between certain and probabilistic outcomes. 

Our study only scratches the surface of possibilities for message testing. We wonder what research may have shown about alternatives to ‘Stay Alert’. Perhaps some of its criticisms could have been avoided, such as with messages to help manage the anxieties associated with the uncertainty of lifting a lockdown. Certainly, public messages can be efficiently tested before they are publicly disseminated – even during a crisis.

Laura Kudrna (Research Fellow) and Kelly Ann Schmidtke (Assistant Professor)


References:

  1. Tversky A, Kahneman D. The Framing of Decisions and the Psychology of Choice. Science. 1981; 211(4481): 453-8.
  2. Chou EY, Murnighan JK. Life or Death Decisions: Framing the Call for Help. PLoS ONE. 2013; 8(3): e57351.
  3. Kahneman D, Tversky A. Prospect Theory: An Analysis of Decision Under Risk. Econometrica. 1979; 47(2): 263-92.
  4. Halpern SD, Truog RD, Miller FG. Cognitive Bias and Public Health Policy During the COVID-19 Pandemic. JAMA. 2020.

N.B. This blog post has also been cross-posted at: blogs.lse.ac.uk/politicsandpolicy/changing-the-message-to-change-the-response-psychological-framing-effects-during-covid-19/