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Do people reduce compliance with COVID-19 guidelines following vaccination? A longitudinal analysis of matched UK adults

15 Apr 2021-medRxiv (Cold Spring Harbor Laboratory Press)-
TL;DR: In the UK COVID-19 Social Study, this article found that compliance with social distancing increased between October 2020 and March 2021, regardless of vaccination status or month of vaccination.
Abstract: IntroductionCOVID-19 vaccines do not confer immediate immunity and vaccinated individuals may still be at risk of transmitting the virus. Governments have not exempted vaccinated individuals from behavioural measures to reduce the spread of COVID-19, such as practicing social distancing. However, vaccinated individuals may have reduced compliance with these measures, given lower perceived risks. MethodsWe used monthly panel data from October 2020 - March 2021 in the UK COVID-19 Social Study to assess changes in compliance following vaccination. Compliance was measured with two items on compliance with guidelines in general and compliance with social distancing. We used matching to create comparable groups of individuals by month of vaccination (January, February, or not vaccinated by February) and fixed effects regression to estimate changes in compliance over the study period. ResultsCompliance increased between October 2020 - March 2021, regardless of vaccination status or month of vaccination. There was no clear evidence that vaccinated individuals decreased compliance relative to those who were not yet vaccinated. ConclusionThere was little evidence that sample members vaccinated in January or February reduced compliance after receiving vaccination for COVID-19. Continued monitoring is required as younger individuals receive the vaccine, lockdown restrictions are lifted and individuals receive second doses of the vaccine.

Summary (2 min read)

Correspondence to

  • Liam Wright, Institute of Education, University College London, London WC1H 0AL, UK; liam.
  • Given the risk of vaccinated individuals catching and transmitting the virus, understanding whether people comply less following vaccination is important for managing the pandemic.
  • The study commenced on 21 March 2020 and involves online weekly (from August 2020, monthly) data collection from participants for the duration of the COVID-19 pandemic in the UK.
  • Participants were recruited using three primary approaches.
  • There have been a several changes to government rules across this period.

Measures

  • Compliance was measured with two questionnaire items, which the authors analysed separately.
  • The authors reverse code this item so high scores indicate greater compliance and code those who did not leave them home or meet with others as the highest level of compliance (range 1–5).

Statistical analysis

  • First, the authors split their sample into three groups: individuals who first reported being vaccinated in the January wave; individuals who first reported being vaccinated in the February wave and individuals who did not report being vaccinated by February.
  • More detail on these variables is given in the online supplemental information.
  • The authors assessed match quality as bias <0.1 SD for each covariate, Rubin’s B <0.25, Rubin’s R of 0.5–5, and visual inspection of the distributions for variables used in the Mahalanobis distance matching step.
  • In the third step, the authors estimated fixed effects regression models for each matched sample, separately, comparing within- person changes in compliance behaviour by wave of data collection across vaccination groups.
  • Due to stipulations set out by the ethics committee, data will be made available at the end of the pandemic.

RESULTS Descriptive statistics

  • Descriptive statistics for the full sample are displayed in online supplemental table S1.
  • Differences were markedly smaller following matching (online supplemental table S2).
  • Figures showing standardised mean differences in the study variables across matched and unmatched samples are displayed in online supplemental figures S2–S4.
  • Matching in the January vs February vaccination comparison group was successful, but there were notable differences in the distributions of age and survey date in the January vs nonvaccinated and February vs non- vaccinated groups, respectively.
  • As the UK entered a second wave, there were increases in both compliance measures, though with some decrease in social distancing over December.

Vaccinations and compliance behaviour

  • The results of the fixed effects regressions are displayed in figure 2.
  • There were no statistically significant differences in either compliance measure following vaccination in any matched sample group.
  • To explore this, figure 3 displays bar plots for compliance levels at each interview in the January vs February vaccination matched sample.
  • In fact, as shown in online supplemental table S2, average compliance levels increased among all groups between October and February in line with the increase in compliance seen in the wider population.

Sensitivity analyses

  • Given that fixed effects regressions compare within- person changes in compliance levels across vaccination groups, the authors also repeated the model in (1) using mixed effects modelling, interpreting the term ui as a normally distributed random intercept.
  • These regressions tested differences in compliance levels by vaccination status and wave.
  • The results are shown in online supplemental figure S10 and are qualitatively similar to those shows in figure 2.

DISCUSSION

  • Using panel data from 5 months of the pandemic in the UK, the authors found no clear evidence that receiving a COVID-19 vaccine reduced compliance behaviour.
  • Second, their sample was not representative and, moreover, was comprised of individuals who comply more than on average.33.
  • The authors results suggest that there is no immediate cause for concern of widespread non- compliance among vaccinated individuals.
  • It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer- reviewed.

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Citations
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Posted ContentDOI
10 Nov 2021-medRxiv
TL;DR: In this article, the authors studied vaccination willingness, speed of vaccination uptake, side effects, and changes in social contact behavior after vaccination in people with primary ciliary dyskinesia.
Abstract: Primary ciliary dyskinesia (PCD) is a rare genetic disease that causes recurrent respiratory infections. People with PCD may be at high risk of severe COVID-19 and vaccination against SARS-CoV-2 is therefore important. We studied vaccination willingness, speed of vaccination uptake, side effects, and changes in social contact behavior after vaccination in people with PCD. We used data from COVID-PCD, an international participatory cohort study. A questionnaire was e-mailed to participants in May 2021 that asked about COVID-19 vaccinations. 423 participants from 31 countries replied (median age: 30 years; 261 (62%) female). Vaccination uptake and willingness was high with 273 of 287 adults (96%) being vaccinated or willing to be in June 2021; only 4% were hesitant. The most common reasons for hesitancy were fear of side effects (reported by 88%). Mild side effects were common but no participant reported severe side effects. Half of participants changed their social contact behaviour after vaccination by seeing friends and family more often. The high vaccination willingness in the study population might reflect the extraordinary effort taken by PCD support groups to inform people about COVID-19 vaccination. Clear and specific public information and involvement of representatives is important for high vaccine uptake.
References
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Journal ArticleDOI
TL;DR: Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a 'behaviour system' at the hub, encircled by intervention functions and then by policy categories, and a new framework aimed at overcoming their limitations is developed.
Abstract: Improving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how well they serve this purpose. This paper evaluates these frameworks, and develops and evaluates a new framework aimed at overcoming their limitations. A systematic search of electronic databases and consultation with behaviour change experts were used to identify frameworks of behaviour change interventions. These were evaluated according to three criteria: comprehensiveness, coherence, and a clear link to an overarching model of behaviour. A new framework was developed to meet these criteria. The reliability with which it could be applied was examined in two domains of behaviour change: tobacco control and obesity. Nineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a 'behaviour system' involving three essential conditions: capability, opportunity, and motivation (what we term the 'COM-B system'). This forms the hub of a 'behaviour change wheel' (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health's 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence's guidance on reducing obesity. Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a 'behaviour system' at the hub, encircled by intervention functions and then by policy categories. Research is needed to establish how far the BCW can lead to more efficient design of effective interventions.

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TL;DR: This article posits a revised explanatory model which incorporates self-efficacy into the Health Belief Model, and predicts that the new formulation will more fully account for health-related behavior than did earlier formulations, and will suggest more effective behavioral interventions than have hitherto been available to health educators.
Abstract: The Health Belief Model, social learning theory (recently relabelled social cognitive theory), self-efficacy, and locus of control have all been applied with varying success to problems of explaining, predicting, and influencing behavior. Yet, there is conceptual confusion among researchers and practitioners about the interrelationships of these theories and variables. This article attempts to show how these explanatory factors may be related, and in so doing, posits a revised explanatory model which incorporates self-efficacy into the Health Belief Model. Specifically, self-efficacy is proposed as a separate independent variable along with the traditional health belief variables of perceived susceptibility, severity, benefits, and barriers. Incentive to behave (health motivation) is also a component of the model. Locus of control is not included explicitly because it is believed to be incorporated within other elements of the model. It is predicted that the new formulation will more fully account for health-related behavior than did earlier formulations, and will suggest more effective behavioral interventions than have hitherto been available to health educators.

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TL;DR: A large international community sample was recruited to complete measures of self-perceived risk of contracting COVID-19, fear of the virus, moral foundations, political orientation, and behavior change in response to the pandemic, and the only predictor of positive behavior change was fear of COVID -19, with no effect of politically relevant variables.
Abstract: In the current context of the global pandemic of coronavirus disease-2019 (COVID-19), health professionals are working with social scientists to inform government policy on how to slow the spread of the virus. An increasing amount of social scientific research has looked at the role of public message framing, for instance, but few studies have thus far examined the role of individual differences in emotional and personality-based variables in predicting virus-mitigating behaviors. In this study, we recruited a large international community sample (N = 324) to complete measures of self-perceived risk of contracting COVID-19, fear of the virus, moral foundations, political orientation, and behavior change in response to the pandemic. Consistently, the only predictor of positive behavior change (e.g., social distancing, improved hand hygiene) was fear of COVID-19, with no effect of politically relevant variables. We discuss these data in relation to the potentially functional nature of fear in global health crises.

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Frequently Asked Questions (6)
Q1. What contributions have the authors mentioned in the paper "Do people reduce compliance with covid-19 guidelines following vaccination? a longitudinal analysis of matched uk adults" ?

The authors used monthly panel data from October 2020 to March 2021 in the UK COVID-19 Social Study to assess changes in compliance following vaccination. The authors used matching to create comparable groups of individuals by month of vaccination ( January, February or not vaccinated by February ) and fixed effects regression to estimate changes in compliance over the study period. 

Seven hundred sixty- eight thousand individuals were vaccinated in England by 27 December 2020, 6.3 million by 28 January 2020 and 14.9 million by 25 February 2020 (1.4%, 11.4%, 27.0% of the population, respectively). 

in the UK, citizens have expressed difficultly keeping abreast of latest rules,11–14 due to variations in rules across areas and over time and (speculatively) due to ‘lockdown fatigue’. 

The authors used matching in this analysis and excluded participants with missing data on any variable used (n=827; 3.6% of the eligible sample). 

Their hypothesis was that, compared with non- vaccinated individuals, compliance would be lower among vaccinated individuals in the months that they were vaccinated, and, given that vaccination does not confer immediate immunity, progressively lower thecopyright. 

by exploiting the longitudinal nature of their sample, the authors were able to use compliance in months prior to vaccination as a placebo test.