Behavioural insights and the evolving COVID-19 pandemic

Bruin, Marijn de; Suk, Jonathan E.; Baggio, Marianna; Blomquist, Sarah Earnshaw; Falcón, María; Forjaz, María João; Godoy-Ramirez, Karina; Leurs, Mariken; Rodríguez‐Blázquez, Carmen; Romay‐Barja, María; Uiters, Ellen; Kinsman, John

doi:10.2807/1560-7917.es.2022.27.18.2100615

Cited by 11 publications

(7 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…BI can uncover behavioral drivers that may act as barriers or facilitators to behaviors. BI can also ensure that interventions that aim to modify behaviors are evidence-driven and designed to address behavioral triggers [ 23 , 24 , 25 ]. This paper describes a qualitative study that used a behavioral framework called the Theoretical Domains Framework (TDF) to identify factors that influence hesitancy and refusal of COVID-19 vaccination among nursing staff in LTCFs in Finland.…”

Section: Introductionmentioning

confidence: 99%

Qualitative Insights into Vaccine Uptake of Nursing Staff in Long-Term Care Facilities in Finland

et al. 2023

View full text Add to dashboard Cite

Vaccine hesitancy and refusal have undermined COVID-19 vaccination efforts of nursing staff. This study aimed to identify behavioral factors associated with COVID-19 vaccine uptake among unvaccinated nursing staff in long-term care facilities (LTCF) in Finland. Methodology: The study was based on the Theoretical Domains Framework. Data were collected through qualitative in-depth interviews among nursing staff and managers of LTCFs. The analysis was based on thematic analysis. We identified seven behavioral domains, with several themes, that reduced the staff’s intention to get vaccinated: knowledge (information overload, inability to identify trustworthy information sources, lack of vaccine-specific and understandable scientific information), beliefs about consequences (incorrect perceptions about the vaccine effectiveness, and lack of trust in the safety of the vaccine), social influences (influence of family and friends), reinforcement (limited abilities of the management to encourage vaccination), beliefs about capabilities (pregnancy or desire to get pregnant), psychological factors (coping with changing opinion), and emotions (confusion, suspicion, disappointment, and fatigue). We also identified three behavioral domains that encouraged vaccine uptake: social influences (trust in health authorities), environmental context and resources (vaccination logistics), and work and professional role (professional pride). The study findings can help authorities to develop tailored vaccine promotion strategies for healthcare workers in LTCFs.

show abstract

Section: Introductionmentioning

confidence: 99%

Qualitative Insights into Vaccine Uptake of Nursing Staff in Long-Term Care Facilities in Finland

et al. 2023

View full text Add to dashboard Cite

show abstract

“…In Spain, compliance with health authorities' recommendations has been high [13], and the vaccination campaign has been a success [14,15]. Even so, compliance with NPIs remains important and will be in the future, as long as new variants continue to be a threat [16]. On the other hand, social, psychological, and economic consequences of the pandemic will continue over time, so the availability of a tool that measures pandemic fatigue is crucial.…”

Section: Introductionmentioning

confidence: 99%

Psychometric Properties of the COVID-19 Pandemic Fatigue Scale: Cross-sectional Online Survey Study

Rodríguez‐Blázquez¹,

Romay‐Barja²,

Falcón³

et al. 2022

JMIR Public Health Surveill

Self Cite

View full text Add to dashboard Cite

Background Pandemic fatigue is defined as feelings of demotivation to follow preventive measures against COVID-19, together with decreased trust in government and frequency of information-seeking behaviors. Objective This study aims to analyze the psychometric properties of the COVID-19–specific pandemic fatigue scale according to classical test theory (CTT) and Rasch model approaches in the general Spanish population. Methods This was a cross-sectional study in a representative sample of 1018 adults who completed an online survey in November 2020 in the framework of the COVID-19 Snapshot Monitoring (COSMO)-Spain project. The assessments included the 6-item COVID-19 Pandemic Fatigue Scale (CPFS) and other COVID-19–related variables: COVID-19 infection, adherence to preventive behaviors, information-seeking behavior, self-efficacy, worry, and cognitive and affective risk perception. Data quality, acceptability, reliability, and validity were analyzed according to CTT, and the fit to the Rasch model, unidimensionality, appropriateness of the response scale, item local independency, reliability (person-separation index [PSI]), and item-person distribution were also calculated. Results The mean CPFS score was 17.06 (SD 5.04, range 6-30), with higher scores for women, younger participants, participants who never seek information on COVID-19, those who think they would contract a mild disease in case of infection, those with higher level of worry about coronavirus/COVID-19, and those who felt depressed or felt the coronavirus/COVID-19 is spreading slowly (all P<.01). The Cronbach alpha for the CPFS was 0.74. In the confirmatory factor analysis, one factor was identified (root mean square error of approximation [RMSEA]=.02; comparative fit index [CFI]=.99; χ25=8.06, P=.15). The CPFS showed good fit to the Rasch model (χ 224=42.025, P=.01, PSI=.642), unidimensionality (binomial 95% CI –.005 to .045), and item local independency. Conclusions Our results suggest that the CPFS has moderate reliability and internal consistency and it is composed of a single dimension. It is a useful tool to ascertain the level of pandemic fatigue in the general population, which may help to guide the communication and information strategies to face the COVID-19 pandemic.

show abstract

“…For the purposes of this work, we considered vaccination as the intervention strategy used to combat disease spread. However, it is important to recognise that other intervention strategies are often used in conjunction such as social distancing and mask-usage in various geographic and social contexts [21, 50]. For instance, antivirals have been used to combat pandemic influenza [51].…”

Section: Discussionmentioning

confidence: 99%

Unifying human infectious disease models and real-time awareness of population- and subpopulation-level intervention effectiveness

Seibel,

Tildesley,

Hill

2024

Preprint

View full text Add to dashboard Cite

BackgroundDuring infectious disease outbreaks, humans often base their decision to adhere to an intervention strategy on their personal opinion towards the intervention, perceived risk of infection and intervention effectiveness. However, due to data limitations and inference challenges, infectious disease models usually omit variables that may impact an individual’s decision to get vaccinated and their awareness of the intervention’s effectiveness of disease control within their social contacts as well as the overall population.MethodsWe constructed a compartmental, deterministic Susceptible-Exposed-Infectious-Recovered (SEIR) disease model that includes a behavioural function with parameters influencing intervention uptake. The behavioural function accounted for an initial subpopulation opinion towards an intervention, their outbreak information sensitivity and the extent they are swayed by the real-time intervention effectiveness information (at a subpopulation- and population-level). Applying the model to vaccination uptake and three human pathogens - pandemic influenza, SARS-CoV-2 and Ebola virus - we explored through model simulation how these intervention adherence decision parameters and behavioural heterogeneity in the population impacted epidemiological outcomes.ResultsFrom our model simulations we found that differences in preference towards outbreak information were pathogen-specific. Therefore, in some pathogen systems, outbreak information types at different outbreak stages may be more informative to an information-sensitive population and lead to less severe epidemic outcomes. In both behaviourally-homogeneous and behaviourally-heterogeneous populations, pandemic influenza showed patterns distinct from SARS-CoV-2 and Ebola for cumulative epidemiological metrics of interest. Furthermore, there was notable sensitivity in outbreak size under different assumptions regarding the population split in behavioural traits. Outbreak information preference was sensitive to vaccine efficacy, which demonstrates the importance of considering human behaviour during outbreaks in the context of the perceived effectiveness of the intervention.ImplicationsIncorporating behavioural functions that modify infection control intervention adherence into epidemiological models can aid our understanding of adherence dynamics during outbreaks. Ultimately, by parameterising models with what we know about human behaviour towards vaccination (and other infection control interventions) adherence, such models can help assist decision makers during outbreaks. Such progress will be particularly important for emerging infectious diseases when there is initially little information on the disease dynamics and intervention effectiveness.

show abstract

Behavioural insights and the evolving COVID-19 pandemic

Cited by 11 publications

References 18 publications

Qualitative Insights into Vaccine Uptake of Nursing Staff in Long-Term Care Facilities in Finland

Qualitative Insights into Vaccine Uptake of Nursing Staff in Long-Term Care Facilities in Finland

Psychometric Properties of the COVID-19 Pandemic Fatigue Scale: Cross-sectional Online Survey Study

Unifying human infectious disease models and real-time awareness of population- and subpopulation-level intervention effectiveness

Contact Info

Product

Resources

About