Knowledge Gaps, Cognition and Media Learning: Designing Tailored Messages to Address COVID-19 Communication Inequalities

1

Abstract

Various health and crisis studies have demonstrated support for the existence of knowledge gaps—a hypothesis suggesting that information will reach those in the lower socioeconomic status last, worsening health disparities. At the point at which COVID-19 vaccines were becoming widely accessible, the present study surveyed 651 Black Americans to understand vaccine hesitancy, intentions, and media learning variations after exposure to different types of social media posts about the COVID-19 vaccine. Although exposure to any of the message conditions in our study resulted in a decrease in vaccine hesitancy, we found mixed support for the knowledge gap hypothesis. Results show that lack of knowledge because of socioeconomic status is not a key factor driving vaccine hesitancy among Black Americans. Instead, public communication (government) campaigns may consider focusing on strategies to target Black American communities by age to improve media learning, and consider increasing social control and communal message functions to increase cognitive processing of pro-vaccine messages, and over the longer term, influence COVID-19 vaccine hesitancy and uptake.

Why were Black Americans getting vaccinated for COVID-19 at much slower rates than other groups? This question was either explicit or implied in media coverage of the pandemic when vaccines became widely available by mid-2021. Noting differences in COVID-19 vaccine acceptance across racial and ethnic backgrounds, Black Americans were often highlighted as least likely to accept the COVID-19 vaccine (Malik, McFadden, Elharake, & Omer, 2020). As the vaccine was being rolled out, 43% of Black adults reported intentions to “wait and see” how it was working out for others before deciding to get vaccinated themselves (Hamel et al., 2021). This reluctance is referred to as vaccine hesitancy - a “delay in acceptance or refusal of vaccination despite the availability of vaccination services” (MacDonald & SAGE Working Group on Vaccine Hesitancy, 2015, p. 4163).

Individuals’ vaccination decisions are complex and influenced by a variety of determinants, including historical and sociopolitical factors (Dubé et al., 2013; MacDonald & SAGE Working Group on Vaccine Hesitancy, 2015). Black Americans’ vaccine hesitancy is fueled, at least in part, by a lack of trust and confidence in medical and government institutions (Freimuth, Jamison, An, Hancock, & Quinn, 2017; Quinn, Jamison, Musa, Hilyard, & Freimuth, 2016), including concerns about the motives of government entities for “pushing” vaccines (Quinn, Jamison, Musa, Hilyard, & Freimuth, 2016) and about the trustworthiness of historically oppressive systems (Momplaisir et al., 2021). Limited sources to translate vaccine science and lack of visible Black American influential figures leading vaccination efforts have also been associated with vaccine hesitancy (Harrison & Wu, 2020; Kricorian, Turner, & Camacho-Rivera, 2021). In addition, sociodemographic factors, such as age, political affiliation, and income, have been predictive of Black American trust in vaccines (Freimuth, Jamison, An, Hancock, & Quinn, 2017).

The knowledge gap hypothesis posits that information will flow to those in high socioeconomic status first, and to those in the lower socioeconomic status later, which will result in worsening disparities in health (Tichenor, Donohue, & Olien, 1970). Results from various health studies have demonstrated consistency with the knowledge gap hypothesis (Lachlan, Spence, & Eith, 2007; Lee & Ho, 2015; Viswanath & Finnegan, 1996), and there has been the suggestion that the COVID-19 context would be similarly supported by empirical findings (Viswanath, Lee, & Pinnamaneni, 2020).

Health communication has two main imperatives: to translate scientific information utilizing appropriate media and language so that it is understandable across multiple audiences; and to make this information available to all, no matter one’s socioeconomic status or other background factors (Viswanath, 2006). Although extant research has indicated that Black Americans are hesitant about receiving the COVID-19 vaccine, little is understood about health messaging that can help address Black American vaccine hesitancy to prepare for possible future infectious disease outbreaks.

In the current study, we aimed to address this gap by conducting a message design experiment to understand the ideal information sources and functions that might have influenced cognitive processing of COVID-19 pro-vaccine messages, decreased vaccine hesitancy, and improved media learning among Black Americans. We hypothesized that messages that went beyond informational and instrumental functions to include community-based sources and messages (norms and social support) would be most effective in increasing media learning and vaccine intentions, and reducing vaccine hesitancy. We also questioned the ideal source of the message for this population—government or influencer.

Literature Review

By the time the vaccines were becoming available to the general public, misinformation about them had begun rapidly spreading on social media (van der Linden, Dixon, Clarke, & Cook, 2021). Social media platforms have emerged as key sources of information for individuals during the pandemic, presenting both benefits and challenges to health communicators (Cuello-Garcia, Pérez-Gaxiola, & van Amelsvoort, 2020; Shearer & Mitchell, 2021). Ali et al. (2020) found that in a nationwide examination of COVID-19 information sources, almost 75% of individuals report using social media to find information about the pandemic. Social media became a breeding ground for COVID-19 conspiracy theories, mis- and dis-information, ultimating contributing to what has been dubbed an “infodemic” by public health officials (Viswanath, Lee, & Pinnamaneni, 2020; Zarocostas, 2020). Those who rely on social media, as opposed to other sources, for COVID-19 information have the lowest likelihood of following COVID-19 news closely (Mitchell, Jurkowitz, Oliphant, & Shearer, 2020). Additionally, these individuals were the least knowledgeable about the COVID-19 pandemic (Mitchell, Jurkowitz, Oliphant, & Shearer, 2020).

Despite these challenges, social media has allowed for the rapid dissemination of COVID-19 information from both formal (i.e., government) and informal (e.g., celebrities, influencers) sources, making this information more accessible to the general public (Chan, Nickson, Rudolph, Lee, & Joynt, 2020). Campaigns led by nonprofit organizations and government entities have harnessed social media in attempts to address vaccine inequities, working with “influencers” to address mis- and dis-information about vaccines and spreading information to hesitant populations (To Save, 2022).

Knowledge Gaps

In addition to sources of news, indicators of socioeconomic status (e.g., education level, income) are related to COVID-19 vaccine acceptance (Joshi et al., 2021; Malik, McFadden, Elharake, & Omer, 2020, 2020). Socioeconomic status, broadly, is the best predictor of knowledge gaps since it is associated with literacy, social capital, access to and type of media channels, motivation, and prior knowledge (Spence, Lachlan, & Burke, 2011). Race, education, and sex are commonly used as proxy indicators of socio-economic status-related differences in information seeking and media learning (Lachlan, Spence, & Eith, 2007). Age has been shown to predict disparities in health and behavior (Lachlan, Spence, & Eith, 2007; Spence, Lachlan, & Westerman, 2009). In a recent study, COVID-related information seeking was found to mediate the relationship between sociodemographic factors, including age and education, and engaging in protective behaviors, underscoring the importance of encouraging media literacy among older and less educated populations in order to reduce health disparities (Yang & Cao, 2022).

Knowledge Gaps and Media Learning

The extent to which information is portrayed accurately on the internet has implications for individuals’ media learning, as well as their beliefs, attitudes, and health decision-making (Carcioppolo, Lun, & McFarlane, 2021). In an examination of clickbait headlines, Carcioppolo, Lun, and McFarlane (2021) found that recognition and comprehension, two key indicators of media learning, were highest for individuals who read a health-related article in full that had an accurate headline, compared to those who were exposed to exaggerated headlines and did not read the entire article. Additionally, the researchers found that being exposed to a clickbait headline had a detrimental impact on individuals’ media learning—even if they were subsequently exposed to accurate information within the news article (Carcioppolo, Lun, & McFarlane, 2021). While the internet is an important resource for health information, the way in which information is presented can either contribute to an individual’s understanding or mislead them, which has potential negative consequences in terms of their attitudes toward and understanding of certain health behaviors (Carcioppolo, Lun, & McFarlane, 2021). Therefore, we aimed to understand the validity of the knowledge gap hypothesis in the context of COVID-19, and the relationship with media learning, after exposing Black Americans to social media posts:

Hypothesis 1a:

H1a: Black Americans with higher socioeconomic status will have higher learning about COVID-19 than will those with lower socioeconomic status.

Hypothesis 1b:

H1b: Age will be associated with COVID-19 media learning such that higher age will predict higher learning, and lower age will predict lower COVID-19 media learning among Black Americans.

Functions of Health Communication

The four primary functions of health communication include social control, communal, informational, and instrumental (Viswanath, 2006). The informational function is centered on facilitating learning and knowledge acquisition about health issues through various channels including the media. Messages that serve the informational function include those that educate the public about disease prevention, detection, and treatment. The instrumental function consists of the inclusion of information that enables or facilitates action on the part of the receiver, such as providing a link to locate a vaccine clinic. The social control function includes communication that seeks to establish or reinforce norms surrounding health behaviors. These types of messages use social influence to define the acceptability of certain health behaviors. Health communication that serves the communal function focuses on creating and fostering a sense of community; these messages frame health and wellbeing as a collective effort (Viswanath, 2006). Given the important role of vaccination in ending the pandemic and improving public health, it is important to understand the message functions and sources that would be most effective for the Black American population. We hypothesized that exposure to these functions should predict positive outcomes:

H2:

H2: Exposure to health communication message functions will directly predict decreased vaccine hesitancy and increased vaccination intentions.

Cognition

One’s elaborative processes-meaning the extent to which one connects new information to previously acquired information and personal experiences-enhances knowledge, retention, and recall (Eveland, 2001). Ho, Peh, and Soh (2013) found connections between elaboration and not only media learning, but also intentions to adopt precautionary behaviors. This indicates that one’s motivation influences their comprehension, which in turn can influence behavioral outcomes in health contexts.

H3:

H3: Elaboration will predict media learning, vaccine hesitancy, and intentions.

Social Control and Communal Message Functions and the Effect on Media Learning

While a clear association is often made with the social determinants of health (e.g., employment, health insurance, and geographic location Williams & Cooper, 2020), there has been limited exploration of the role of communication inequalities in contributing to COVID-19 related health disparities. Communication inequality is defined as “the differences among social groups in their ability to generate, disseminate, and use information at the macro level and to access, process, and act on information at the individual level” (Viswanath, 2006, p. 222). The COVID-19 pandemic is known to disproportionately affect communities of color in the United States. Beyond socioeconomic status, ethnicity and culture are important to consider in the expansion of understanding of the knowledge gap hypothesis (Spence, Lachlan, & Burke, 2011). To effectively decrease health disparities, acknowledging and centralizing culture and identity should be a critical part of current communication strategies and message design (Airhihenbuwa et al., 2020).

Standard public health campaign messages tend to focus on the informational and instrumental functions, and less emphasis is placed on the social control (Kricorian, Turner, & Camacho-Rivera, 2021) and communal functions (Airhihenbuwa & Obregon, 2000; Airhihenbuwa, 1995) that are cited as critical for increasing motivation and learning in Black Americans. Considering the social control function specifically, it is known that health threats (e.g., from the news) tend to motivate individuals to both seek and share information in interpersonal contexts (Duong, Van Nguyen, Julian McFarlane, Nguyen, & Nguyen, 2021; Southwell & Yzer, 2009). Individuals may utilize discussions to gauge others’ attitudes about a particular issue, in order to evaluate their own (Southwell & Yzer, 2009). These conversations may also influence individuals’ perceptions about norms pertaining to specific health behaviors; in the context of COVID-19, perceived norms about mask wearing are positively associated with intentions to wear a mask (Duong, Van Nguyen, Julian McFarlane, Nguyen, & Nguyen, 2021), and discussions with important others about vaccination are associated with increased vaccination intentions (Francis, Mason, & Occa, 2022).

In fact, communities must receive information from important others who look like them, to validate government sources (Spence, Lachlan, & Burke, 2007), even though this may cause a delay in enacting a recommended behavior (Fothergill, Maestas, & Darlington, 1999; Lindell & Perry, 2003). Knowledge about COVID-19 varies significantly by source; those who use government sources know more about COVID-19 compared to those who use social media (2020). While diverse, public audiences have ranked the Centers for Disease Control (CDC) as the top source of information about COVID-19 vaccination (Joshi et al., 2021), it is unclear how information from the CDC is received by vaccine hesitant populations when compared to information from important community members. Given that government sources have also harnessed social media for the dissemination of COVID-19 information (Wong, Ho, Olusanya, Antonini, & Lyness, 2021), the source of the information shared on social media might be influential on individuals’ attention, recall, and knowledge of COVID-19 information. Considering this we sought to understand:

Research question 1: Is a governmental source more credible than an influencer source in increasing intentions to vaccinate and reducing vaccine hesitancy?

In addition, appealing to the communal layer in message design is effective (Davis & Resnicow, 2012; Larkey & Hill, 2012). Messages that encourage individuals to “do your part” in ending the COVID-19 pandemic are an effective strategy for encouraging the public to engage in recommended preventative behaviors (Noar & Austin, 2020). Therefore, considering the primary functions of health communication proposed by Viswanath (2006), we sought to understand the additive effect of social control and communal messages compared to only standard information and instrumental message types:

Hypothesis 4:

H4: Black Americans exposed to social control-communal messages will have higher intentions to vaccinate, and lower vaccine hesitancy than those exposed to the informational-instrumental conditions.

We also sought to understand the additive effect of social control and communal messages, compared to standard informational and instrumental messages, in predicting improved elaboration and media learning:

Hypothesis 5:

H5: Black Americans exposed to the social control-communal message will have higher (a) elaboration and (b) media learning than those exposed to the informational-instrumental condition only.

Methods

Participants

Black American adults aged 18–65 were recruited via Qualtrics and the final sample included 651 participants. Qualtrics is a large research company providing survey services with access to over 90 million participants nationwide. Data collection took place in spring 2021 when vaccines were becoming widely available.

This study employed stratified random sampling to have a representative sample of Black American demographics in terms of age, income, and education level. We targeted Black Americans who are currently US residents, users of social media, at least 50% of participants having less than high school education and 50% of participants being considered below lower-middle class ($32,048–$53,413) and 50% having more than a high school education. People who had been vaccinated and those who do not use any social media platform were not included in the study.

The final 651 participants have an average age of 34 years old (SD = 12.96). Among the participants, 361 (55.50%) were females, 282 (43.3%) males, 6 (.90%) were reported non-binary, and 2 (.30%) preferred not to report. In terms of participants’ education levels, 31 (4.8%) had less than high school education, 234 (35.9%) had high school graduate or equivalent education, 147 (22.6%) had some college education, 63 (10.6%) had an associate degree, 109 (16.7%) had a college degree, 6 (.9%) had some graduate school education, and 55 (8.4%) had a graduate school degree. Regarding income levels, 331 (50.8%) had an annual income below $45,000, 67(10.3%) had an annual income between $45,000 and $54,999, 177 (27.2%) had an annual income between $55,000 and $139,999, 56 (9.5%) an annual income higher than $140,000, and 14 (2.2%) were not to answer. Participants’ political affiliation was reported, 41 (6.3) were republicans, 370 (56.8%) were democrats, 151 (23.2%) were independents, 81 (12.4%) did not answer, and 8 (1.2%) were reported as “other.”

Stimuli Development

To test a between subject 2 (message source: government vs. influencer) x2 (message type: informational-instrumental vs. social control-communal) experimental conditions in this study, four types of materials were developed based on a composite of existing social media posts by the National Institute of Health (NIH) in 2021. Previous literature suggested the importance of messaging about the credibility, safety, and effectiveness of vaccines when targeting minority populations (Kricorian, Turner, & Camacho-Rivera, 2021). Similarly, messages were designed and shown to study participants as realistic, short social media posts.

For the indication of the message source, either CDC’s logo or Tyler Perry’s face was used in the social media post. Tyler Perry was chosen as an influencer for this study because he is one of the well-known Black American celebrities in the US and has been an active advocate of health and social issues in the Black American community (Buckley, 2021; NewsOne Staff, 2021). Perry encouraged black community to get vaccinated by discussing cultural barriers and misinformation on the Black Entertainment Television (BET) show (Buckley, 2021) and his own YouTube channel (TylerPerryStudios, 2021). The two social media message types(1) informational-instrumental message containing information-based instructions about how to get the vaccine and (2) one with additional social control-communal message containing friendly encouragement to get the vaccine incorporating Black American cultural context—were designed by researchers (see appendix A).

Procedure

Participants received a web link to complete the survey questions on their own computers at home. Participants first agreed to the informed consent statement to join the online experimental study and they were randomly assigned to one of the four conditions to answer a set of questions about demographic information and variables including preexisting vaccine hesitancy, covid experience, and preexisting attitudes toward the assigned message source (CDC vs. Tyler Perry). After participants were exposed to the experimental conditions, they responded to outcome variables such as elaboration, media learning-recognition, and comprehension as well as vaccine hesitancy and vaccine intention. Upon completion of the online questionnaire, they saw a closing statement informing the experimental stimuli were fictitious and received compensation.

Measures

COVID Experience

A single-item measure was used to capture participants’ experience by asking, “has your family member contracted the COVID virus?” Participants answered yes (n = 200, 30.7%) or no (n = 451, 69.3%).

Elaboration

The construct was assessed using a modified 3-item measure developed by (2016) on a 10-point Likert scale. Examples of items were, “After I encountered this information on COVID-19, I stopped to think about it,” “I related what I learnt from this information on COVID-19 to other things I know,” “I carefully analyzed the information given about COVID-19” (M = 6.35, SD = 2.36, α = .76).

Control Variable

Attitudes

To control for preexisting attitudes toward the message sources (Centers for Disease Control and Prevention (CDC) and Tyler Perry), this study measured each attitude toward CDC by a five-item scale (M_CDC = 4.99, SD_CDC = 1.55, α_CDC=.86) and Tyler Perry by a four-item scale with a 7-point semantic differential scale (M_TP = 5.87, SD_TP = 1.33, α_TP=.80).

Outcome Variables

Vaccine Hesitancy

Vaccine hesitancy measured attitudes to vaccination (Xu, Margolin, & Niederdeppe, 2020) using a modified five-item scale with a 7-point Likert scale (M = 3.84, SD = 1.88, α = .91). The items include, “bad–good, foolish-wise, unnecessary–necessary, negative-positive, harmful–beneficial.

Vaccine Intention

Two items were adapted to measure vaccine intention on a 5-point Likert scale from a previous study (Sampson et al., 2001). Examples of the items include, “I intend to get vaccinated once it is available” and “I want to get vaccinated once it is available” (M = 3.18, SD = 1.47, α = .96).

Media Learning - Recognition and Comprehension

Media learning was measured in two outcome variables—recognition and comprehension in this study guided by the cognitive mediation model. Previous studies (e.g., Carcioppolo, Lun, & McFarlane, 2021; Jensen, 2011) have also assessed recognition and comprehension for media learning to measure the extent to which one recalls and accurately understands given context or issue.

Recognition. The variable was measured in a set of five multiple-choice questions. The questions were adapted from the previous study (Jensen, 2011) and modified to social media messages in this study context. We asked participants to answer true or false on each question and coded the correct answer as 1 and incorrect answer as 0 to sum up the total score to form a single scale (M = 2.64, SD = 1.473). Higher score indicated more questions were answered correctly (e.g., a participant’s score of 4 indicates the participant answered 4 questions correctly). Examples of questions were, “Medical experts and scientists created the vaccine [True],” “The COVID-19 vaccine is not free of cost to individuals [False]” (M = 2.64, SD = 1.47).

Comprehension. The variable was assessed using five multiple-choice questions that were modified from the previous study (Jensen, 2011) to fit the social media posts. The comprehension questions tested whether participants could apply information from the post to new situations. Examples of questions were, “Vaccines, including the COVID-19 vaccine, are an important part of staying healthy [True],” “Even if most people get vaccinated, vaccines cannot end a pandemic [False]”(M = 2.41, SD = 1.44).

Data Analysis

For data analysis, SPSS 25 was utilized to conduct a series of statistical analyses including t-tests, ANOVA, and regressions.

Results

Knowledge Gap Hypothesis and Media Learning

First, to test the validity of the knowledge gap hypothesis in the context of COVID-19 public health vaccination campaign messages, we entered income, education, and age into a linear regression model, to understand the impact of these socio-demographic factors on media learning, vaccine intentions, and hesitancy. There were no differences observed for income and education, but there were significant differences by age¹ in media learning and vaccine hesitancy (Tables 1, 2 and 3). Hypothesis 1 was therefore partially confirmed.

Table 1. Linear regression analyses: Demographic predictors of media learning, vaccine hesitancy, vaccine intentions, standardized regression coefficients for demographic predictors

Predictor	Model 1 (Media Learning)		Model 2 (Vaccine Hesitancy)	Model 3 (Vaccination Intentions)
	Recognition	Comprehension
Income	−.029	−.054	.023	.013
Education	.054	.045	−.022	−.037
Age	.256*	.206*	−.124*	−.048
Covid Experience	.085*	−.040	−.562	.051

*p<.05. **p<.01. ***p<.001.

Table 2. Anova results for mean comparisons by age in media learning

Media Learning Variables	Age	Mean	F (p)
Recognition	18–24	2.22	19.357 (.000)
	25–44	2.66
	45–65	3.16
Comprehension	18–24	2.05	13.439 (.000)
	25–44	2.47
	45–65	2.82

Table 3. Anova results for mean comparisons by age in vaccine hesitancy

Outcome variable	Age	Mean	F (p)
Vaccine Hesitancy	18–24	4.08	3.50(.03)
	25–44	3.81
	45–65	3.56

Functions of Health Communication

Second, we conducted a paired samples t-test to understand the effect of exposure to any of the message functions (across all participants) on intentions to vaccinate and vaccine hesitancy (H2). By the end of participating in the study, there was no change in intentions t(650) = 1.77, p = .08, however, all participants had a statistically significant decrease in vaccine hesitancy (pretest M = 3.84, SD = 1.90; posttest M = 3.63, SD = 2.00), t(650) = 4.90, p < .001. Hypothesis 2 was therefore partially confirmed.

Cognition

Third, simple linear regression tests were carried out to understand if elaboration would predict media learning (recognition and comprehension), vaccine hesitancy and intentions (H3). It was found that elaboration significantly predicted recognition (β1 = 1.60, p < .001), comprehension (β1 = 1.36, p < .001), vaccine hesitancy (β1 = 2.11, p < .001) and intentions (β1 = 4.64, p < .001). The results of the regression indicated that the models explained 6.8% (recognition), 7.3% (comprehension), 18.4% (hesitancy), and 15.1% (intentions) of the variance and that the models were significant, F(1,649) = 48.06, p < .001, F(1,649) = 51.38, p < .001, F(1,649) = 145.91, p < .001, F(1,649) = 115.52, p < .001, respectively. H3 was therefore confirmed.

Social Control and Communal Message Functions and the Effect on Media Learning

Next, we questioned whether a government source would be more credible than an influencer source in increasing vaccination intentions and reducing vaccine hesitancy (RQ1). We conducted an independent samples t-test to understand the differences between groups exposed to each message source. There was a significant difference in the vaccine hesitancy scores for the government (M = 4.21, SD = 2.00) and influencer (M = 4.52, SD = 1.91) sources; t(649)=-2.04, p = .04. There was also a significant difference in the vaccine intentions scores for government (M = 3.25, SD = 1.48) and influencer (M = 3.02, SD = 1.39) conditions; t(649) = 2.05, p = .04. These results suggest that government sources are more credible than influencer sources at reducing COVID-19 hesitancy and increasing intentions to vaccinate.

Then, to understand the impact of message functions (H4), we used univariate analysis of covariance tests to determine the relationship between the message conditions and intentions to vaccinate and vaccine hesitancy. The analysis showed that, although significance was found before controlling for preexisting attitudes toward the government source (CDC) and the Black American influencer (Perry), after controlling for attitudes there were no significant differences for intentions to vaccinate and hesitancy and intention scores, F(3, 608) = .39, p = .76, η² = .00 or vaccine hesitancy F(3, 608) = .50, p = .72, η² = .00 at the end of the study. Hypothesis 3 was therefore not supported.

Finally, we used a multivariate general linear model to determine the relationship between the message conditions and (a) elaboration and (b) media learning (H5), controlling for preexisting attitudes toward the government source (CDC) and the Black American influencer (Perry). Results demonstrated statistically significant differences in elaboration based on message condition exposure (see Table 4). Specifically, participants exposed to the social control-communal message with a government source saw the highest elaboration Wilks’ Lambda = 1, F (3,608) = 3.45, p = .02, η² = .02. However, other message types and sources were only approaching significance in elaboration. No differences were observed between groups in media learning. Hypothesis 5 was therefore partially supported.

Table 4. Univariate message effects on elaboration, media learning

Dependent variables	F	df	p	Partial eta squared (η^2)	Mean scores by message types-sources**
					I-I(Gov)	S-C (Gov)	I-I(In)	S-C (In)
Elaboration*	3.45	3,608	.02	.02	6.14	6.84	6.51	6.33
Recognition	1.12	3,608	.34	.01	2.72	2.66	2.72	2.59
Comprehension	2.34	3,608	.07	.01	2.45	2.5	2.55	2.35

*Elaboration is measured with a 7-point scale

**I-I(Gov)= Informational-Instrumental message (Government source); S-C (Gov)= Social control-Communal message (Government source); I-I(In)= Informational-Instrumental message (Influencer source); S-C (In) Social control-Communal message(InfluencerSource).

Post Hoc Analyses

An analysis of variance test revealed that those who had personally experienced COVID-19 had higher recognition scores (no COVID experience M = 2.37, had COVID experience M = 2.50, p = .05), but statistically significant differences were not observed for comprehension scores.

Discussion

Broadly, we hypothesized that for Black American populations, messages that go beyond informational and instrumental functions to include community-based sources and messages (norms and social support) would be most effective in increasing media learning and vaccine intentions and reducing vaccine hesitancy. We questioned the ideal source of the message for this population—government or influencer.

Knowledge Gap Hypothesis

First, we found no differences across socioeconomic status in media learning, vaccine hesitancy, or vaccine intentions. While this finding goes against the main tenet of the knowledge gap hypothesis, some studies suggest that for specific behaviors, such as vaccination, socioeconomic status does not explain lack of uptake (Spence, Lachlan, & Burke, 2011). On the other hand, we found significant differences in media learning (both recognition and comprehension) and vaccine hesitancy by age. This finding is supported by literature pointing to differences in outcomes among Black American populations by age (Lachlan, Spence, & Eith, 2007; Spence, Lachlan, & Westerman, 2009), although the findings have been mixed, depending on the health topic. In some studies, younger people were less likely to engage with traditional media and relied more on interpersonal networks (Lachlan, Spence, & Eith, 2007; Spence, Lachlan, & Burke, 2007). In other studies, older persons were more likely to remain informed and to access information, for example, in 2015 during the MERS-CoV outbreak (Bawazir, Al-Mazroo, Jradi, Ahmed, & Badri, 2018). Much of the variance is predicated by the type of media and the usage (Spence, Lachlan, & Burke, 2011). The current study suggests that new media may have utility in targeting older populations, which is a significant finding given the limited evidence in crisis communication (Spence, Lachlan, & Burke, 2011).

Health Communication Message Functions

Cognition

In addition, results demonstrated statistically significant differences in elaboration (thinking about the messages) based on message condition exposure. Specifically, participants exposed to the social control-communal message with a government source saw the highest elaboration, although no differences were found in media learning. Government sources (the CDC) maintained credibility over and above other sources of information, which is well espoused in related literature (Ali et al., 2020; Kazi Abdul & Khandaker Mursheda, 2020; van der Meer & Jin, 2020). However, this study elucidates the fact that Black Americans engage in more active cognitive message processing when the government uses messages that explicitly acknowledge identity, including Black American group norms and values (social control and communal messages). Public communication campaigns may therefore consider increasing social control and communal message functions to increase engagement with pro-vaccine messages.

Intentions and Vaccine Hesitancy

Then, looking at differences by exposure to varying message functions and sources in our study, results also indicated no statistical differences in intentions or vaccine hesitancy between government and influencer sources. However, significant effects were present before controlling for preexisting attitudes toward the government source (CDC) and the Black American influencer (Tyler Perry). Specifically, there were significant effects of government sources with social control-communal messages on intentions. This indexes the influence of sources in attitudes toward vaccines (Clendenin, 2017, 2017; Rabin, 2022; Spence, Lachlan, & Burke, 2011, 2011) and may partially explain what influences behavior in this community beyond socioeconomic factors. Exposure to any of the message conditions in our study resulted in a statistically significant decrease in vaccine hesitancy, highlighting that, at a minimum, reaching audiences with targeted health promotion messages is the first opportunity to change attitudes (Hornik, 2002).

Media Learning

Those who had personally experienced COVID-19 had higher recognition scores, but not higher comprehension scores. This demonstrates the audiences’ ability to index campaign messages because of personal experiences, but not necessarily translate scientific messages as expected. Theoretically, media learning, including both recognition and comprehension, may be an important antecedent to COVID-19 behavior change.

But what is “holding back” COVID-19 comprehension, if there is recognition of the facts? Trust in science may impact an individuals’ ability to comprehend science, that is, to be able to recognize and apply knowledge to new scenarios, such as COVID-19. Trust in science influences whether or not individuals will acquiesce to COVID-19 public health behavior recommendations (Agley, 2020; Barry, Han, & McGinty, 2020; Plohl & Musil, 2021). Mistrust of the healthcare system is particularly evident among ethnic and racial minorities, and it is not unfounded, since institutions have historically mistreated these populations (Gamble, 1993). One of the most common references to this fact is the heinous offenses committed in the Tuskegee Syphilis trials, which targeted Black Americans; the legacy of mistrust because of this trial is still present today (Katz et al., 2008). The opportunity here is to understand this gap between basic messages for recognition and to design messages that lead to comprehension and behavior change. Messages that address cultural interpretations and other cultural factors informing decision-making in this specific context would be appropriate. In other words, develop “advanced risk communication strategies, built on evidence that people listen to information that matches their preexisting cultural expectations or preferred aesthetics, aspire to identify and counteract ‘ungrounded’ vaccine fears in the population” (Harrison & Wu, 2020, p. 326). To move from vaccine hesitancy to “vaccine confidence,” COVID-19 systemic barriers must also be addressed (Harrison & Wu, 2020, p. 326).

Limitations

Trust is a key driver of vaccine intentions among the studied population and yet this is not central to this study’s design, however we controlled for attitudes to government and influencer to account for trust. Future studies may test if health communication functions predict trust, which then predicts increased elaboration and outcomes. In addition, a significant limitation of the current study was its cross-sectional design. Following this cohort of participants in a longitudinal research design may have demonstrated delayed media learning (especially comprehension) or vaccination intentions in the weeks following the study.

Conclusion

The COVID-19 pandemic has been marked by uncertainty, misinformation, and inequality. Black Americans have been disproportionately impacted by COVID-19, yet their vaccine uptake has been low in comparison to other racial groups. Our findings question the existence of knowledge gaps in the COVID-19 context and provide an impetus for designing and testing nuanced messaging in risk and crisis communication, particularly those messages from government sources, to underserved populations in times of crisis.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Ethics Approval

Approval was granted by the University of Georgia (04/08/2021; PROJECT00003725).

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/10810730.2023.2208049.

Additional information

Funding

This work was supported by internal funding from the Department of Communication Studies at the University of Georgia.

Notes

¹ The US Census Bureau categories were used to group age groups https://www.census.gov/prod/cen2010/briefs/c2010br-03.pdf.