Shuyang Qu, Iowa State University, squ@iastate.edu
Tori Bradley, University of Florida, toriraebradley@ufl.edu
Joy N. Rumble, University of Florida, jnrumble@ufl.edu
Abstract
Lower socioeconomic groups may not learn as quickly or retain as much knowledge as higher socioeconomic groups because higher socioeconomic groups often have easier access to the relevant resources. With many health benefits associated with blueberry consumption, this study examined consumers’ knowledge level of blueberry benefits, and investigated whether a knowledge gap existed among high and low socioeconomic groups and among different demographic groups. An online survey using non-probability sampling was distributed to grocery shoppers from 31 states in the United States. Post-stratification weighting of data was used to adjust the bias resulted from non-probability sampling. The respondents answered on average more than half of the questions correctly about blueberrybenefits. A knowledge gap exists between those with some college education or a college degree and those with a high school degree or lower education. While respondents demonstrated acceptable knowledge of blueberry benefits, an opportunity exists to increase the awareness of the health benefits of blueberries, especially among those with lower levels of education. Future research should determine the relationship between knowledge gap and a broader range of factors such as motivation and social contacts.
Introduction
In the United States (U.S.), blueberry production proved to be a growing industry from 2013 to 2014. Nationalblueberry production increased by 5% from the 2013 season, reaching 5.67 million pounds in 2014 (U.S. Department ofAgriculture, 2014). It is estimated that total fresh and processed blueberries provide an economic value of $824.9 million (National Agricultural Statistics Service, 2015). Blueberries are grown in several states including Alabama, Arkansas, California, Florida, Georgia, Indiana, Michigan, Mississippi, New Jersey, New York, North Carolina, Oregon, and Washington (U.S. Department of Agriculture, 2014). The variety of growing states allows for a vast availability of blueberries in the U.S. The market introduction of blueberries from other countries such as Chile, Canada, Mexico, and Argentina at varying times (Evans & Ballen, 2014), allows the national blueberry market to be stocked year-round.
The increase in U.S. blueberry production was met with an increase in the demand for blueberries in 2014. According to the U.S. Highbush Blueberry Council (2014a), the number of households that reported buying blueberries once in the past month doubled from 2008 to 2014. The increasing supply of blueberries in the U.S. is not only important to satiate consumers’ high demand for blueberries, but also provide unique health benefits to consumers. The U.S. Highbush Blueberry Council cites several studies that discuss blueberry attributes that address a wide range of health issues (U.S. Highbush Blueberry Council, 2014b).
Blueberries have been attributed to having high antioxidant properties, which help to protect the heart and brain and may also act as anti-cancer agents (Bornsek et al., 2012). The Centers for Disease Control and Prevention citesheart disease and cancer as being the two leading causes of death by a large margin over any other causes of death(Centers for Disease Control and Prevention, 2015). The decline in functional mobility of older adults may be counteracted when blueberries are consumed daily (Schrager, Hilton, Gould, & Kelly, 2015). Functional mobility improvements include assessments of grip strength, reaction time, and the number of errors in steps while walking. Studies citing that blueberries may be a contributing factor to reducing risk for these causes of death are promising forboth producers and sellers of berries, but also for people who may be at increased risk for these diseases. The antioxidants in blueberries may also protect eyes from aging caused by light-induced damage (Liu et al., 2012). Brain function has also been shown to improve with adding blueberries to diets. In a study of children between the ages ofseven and nine, those who were given blueberries in the form of a milkshake “produced significantly better performance in delayed word recognition sustained over each test period” than those children who did not receive theblueberry drink (Whyte & Williams, 2012, p. 637). Additionally, supplementing blueberries into the diets of adults with an increased risk for dementia has significantly improved memory function (Krikorian et al. 2010). The U.S. Department of Agriculture has also referenced these nutritional benefits of blueberries on its websites and educational materials (e.g. USDA SNAP-Ed Connection, 2017, USDA National Institute of Food and Agriculture, 2016; Yan, 2014).
While a direct link between the knowledge of the health benefits of blueberries and increased consumption has not been proven, previous literature has linked health-related knowledge with behavior changes such as decreased smoking, less alcohol consumption, and increased exercise (Kenkel, 1991). Even though a gap exists between knowledge learned and related behavior, transmitting knowledge is the first step to make related behavior change (Sligo, & Jameson, 2000).
Although all people may benefit from learning about the health benefits of blueberries, certain socioeconomic groups may not receive information related to the health benefits of blueberries as quickly as other groups (Tchicaya, Lorentz, Demarest, & Beissel, 2018; Tichenor, Donohue, & Olien, 1970). This paper sought to discover consumerknowledge related to the health benefits of blueberries and if this knowledge varies by demographic groups. In the eventthat more people are made aware of the health benefits of blueberries, demand may continue to rise as it did from 2008 to 2014 (U.S. Highbush Blueberry Council, 2014a). This increase in awareness will only come from increased communication with the lesser-reached groups. With the information gained from this research comes the opportunity to strategically communicate with the audiences that have yet to be reached with the information that is already available. If knowledge does vary between groups of people, the existing messages can be tailored to reach these groups while new, targeted information can be developed to penetrate these groups further.
Theoretical Framework
The originally proposed knowledge gap hypothesis states that as information flows into a social system, people with higher socioeconomic status would acquire the information at a faster rate and retain more knowledge than people with lower socioeconomic status (SES) (Tichenor et al., 1970). Viswanath, Kahnm, Finnegan, Hertog, and Potter (1993) concluded from a number of studies that the acquisition of information among social groups was persistently unequal. Despite the concerns of the original hypothesis that mass media would widen the knowledge gap, some scholars (e.g. Ettema & Kline, 1997) suggested that such a gap may begin to narrow as more functional information flows into the social system, motivating individuals to seek information.
SES is usually measured by individuals’ education, income, occupation, or a composite of these indicators (Fretz, Schneider, McEvoy, Hoogeveen, Ballantyne, Coresh, & Selvin, 2016; Winkleby, Jatulis, Frank, & Fortmann, 1992). Five specific factors have been identified to be responsible for the knowledge gap: communication skills, prior knowledge, relevant social contacts, selective use, acceptance and storage of information, and structure of the media system (Bonfadelli, 2002). Research has identified that education level is one of the components leading to differing levels among these knowledge gap factors (Kiviniemi, Orom, Waters, McKillip, & Hay, 2018; Lovrich & Pierce, 1984; Turrell & Kavanagh, 2006). Higher SES individuals have better communication management skills, and are able to better use and interpret media messages than those with lower SES; higher SES individuals also have broader social and/or local contacts that provide additional interpersonal information sources and they tend to actively seek information more frequently. Additionally, the media system provides rich information that can be more sufficiently used by higher SES individuals than lower SES individuals (Gaziano, 2017; Lovrich & Pierce, 1984).
SES indicators were found to be significantly related to individuals’ knowledge of food and nutrition (e.g., Campbell, Abbott G, Spence, Crawford, McNaughton, & Ball, 2013; Giskes, Avendaňo, Brug, & Kunst, 2010; De Irala-Estevez, Groth, Johansson, Oltersdorf, Prattala, & Martínez-González, 2000; Giskes, Turrell, Patterson, & Newman, 2002). Individuals with lower levels of income and education were found to have lower levels of nutrition knowledge and make food choices less consistent with dietary guideline recommendations compared with their more affluent or educated counterparts (Campbell et al., 2013; De Irala-Estevez et al., 2000; De Vriendt, Matthys, Verbeke,Pynaert, & De Henauw, 2009; Giskes et al., 2002; Giskes et al., 2010; Hendrie, Coveney, & Cox, 2008; Turrell & Kavanagh, 2006). Higher SES groups were found to adhere more to plant-based and alcohol/salad food patterns, while lower SES groups were tied more to sweets/fats and southern food patterns (Kell, Judd, Pearson, Shikany, & Fernández, 2015). Some research studies have argued that the knowledge gap was not solely attributable to education(e.g., Ettema & Kline, 1977; Chew & Palmer, 1994). Individuals’ motivation has also significantly influenced people’s knowledge acquisition capability (Ettema & Kline, 1977; Mead, Cohen, Kennedy, Gallo, & Latkin, 2015), thus directly impacting their knowledge level. Similarly, Chew and Palmer (1994) found that the gap of knowledge regardingnutrition between people with higher interest and lower interest remained constant and significant. Interest predicts knowledge gain resulting from information exposure more strongly than education (Chew & Palmer, 1994; Rotgans & Schmidt, 2017).
Kwak (1999) proposed that education and motivation were not necessarily independent from one another and developed a contingency model of knowledge gap phenomena. In an examination of an individual’s involvement in a political campaign and its influence on his or her knowledge, Kwak (1999) found that respondents’ television viewing of the campaigns significantly reduced the knowledge gap between higher and lower educated respondents. Viswanath et al. (1993) examined the level of motivation and education in acquiring cancer and diet information in a communitythat received a health campaign for one year. The research found a significant knowledge gap among different education level groups. Furthermore, despite other studies that showed motivation could overcome a knowledge gap resulting from education levels, this study found that an education-based knowledge gap consistently existed within more- motivated groups.
Demographic characteristics were also found to be relevant to knowledge level regarding nutrition and diet (e.g., Hendrie et al., 2008; De Vriendt et al., 2009). Hendrie et al., (2008) used multiple regression analysis and determined that gender, age, education level, and employment status were significant predictors of nutrition knowledge level. Similarly, De Vriendt et al. (2009) used a linear regression model and found significant association of women’s knowledge of nutrition with education level, age, occupation type, smoking behavior, and work status.
Infusion of mass media information in a social system is able to widen the knowledge gap, as well as close it, between people with different education levels (Ettema, Brown, & Luepker, 1983). Previous research found television to be an effective medium to gain knowledge for those with less background knowledge and weaker cognitive skills(Neuman, Just, & Crigler, 1992; Prior, 2005), and therefore narrow the knowledge gap between the less informed and well informed (Grabe et al., 2009; Holbrook, 2002; Liu & Eveland, 2005). Ho (2012) found attention to newspapers and television news about H1N1 influenza positively influenced public knowledge about the flu pandemic. Individuals who paid a high amount of attention to television news about H1N1 tended to possess greater H1N1-related knowledge than those who paid a low amount of attention.
Internet engagement has been found to be positively related to education level (Lee, 2009; Shim, 2008). Shim (2008) indicated that those with high education levels would gain more health knowledge than those with low education when their frequency of using Internet is the same, thus suggesting the Internet could widen the knowledge gap between people with high and low education levels. However, Cacciatore, Scheufele, and Corley (2014) argued thatthe Internet could also close the knowledge gap. Cacciatore et al., (2014) found that the number of days a week that respondents spent online was significantly related to knowledge levels about nanotechnology. Since online sources had the capability to tailor information to specific audiences, which traditional media was incapable of, Cacciatore et al. (2014) concluded that the Internet had such a distinct effect among low-educated groups that it “appears capable of eliminating the education- based gaps entirely” (p. 12). Kim (2008) suggested that people may find an issue interesting or important from traditional media such as reading a newspaper or watching television, and then go to the Internet for further information.
Today, more consumers use new media to receive and seek information than ever before. About two-thirds of the Americans own a smartphone, and many of these smartphones are the owners’ key access to the online world (Smith, 2015). Most smartphone owners have also used their phones to look up health-related information (Smith, 2015). Blueberry-related content has also been increasing on the Internet (Attaway, Clark, & Hummel, 2012) and consumers have demonstrated their interest in receiving such information from a variety of sources through their social networks (Attaway, Clark, & Hummel, 2012). Attaway et al. (2012) suggested the Cooperative Extension Service should utilize social networks to build connections with their consumers. Additionally, previous research (e.g. Griffiths, Calear, Banfield & Tam, 2009; Meier, Lyons, Frydman, Forlenza, & Rimer, 2007) has suggested that online interpersonal support groups and social media groups have created opportunities for seeking and offering health information.
Purpose and Objectives
The purpose of this research was to examine knowledge of the health benefits of blueberries between grocery consumers with different socio-economic, age, and gender characteristics to determine if a knowledge gap exists to strategically communicate with the audiences that have yet to be reached with the information that is already available. The specific objectives of this research were:
- Describe consumers’ knowledge of the health benefits of blueberries.
- Determine if a knowledge gap regarding health benefits of blueberries exists between respondents with different education and income levels.
- Determine if a knowledge gap regarding health benefits of blueberries exists between respondents within different age and gender groups.
Methods
An online survey was used to collect data from adults in states that received shipments of Florida-grown blueberries in the year proceeding data collection. The population was limited to adults in these 31 states because this study was part of a larger project related to improving the marketing of Florida blueberries. The respondents were recruited by an external online survey company, Qualtrics, using non-probability sampling. Non-probability sampling has become an acceptable alternative to probability sampling and has been used to gather data from consumer populations in social science research because of coverage and non-response challenges encountered with probabilitysampling (Baker et al. 2013). Non-probability samples, including the one used is this study, are often gathered online byidentifying and recruiting panels of individuals who are willing to complete surveys (Baker et al. 2013). However, selection, exclusion, and non- participation biases are a limitation to using non-probability sampling. For example, participants of the study must have access to an Internet accessible computer, tablet, or smartphone, which is a limitation because it excluded people without such access. To address these limitations, post- stratification weighting of the data was completed before data analysis (Baker et al., 2013; Kalton & Flores-Cervantes, 2003). The data were weighted according to the 2010 United States’ Census population estimates for the following regions: South Atlantic (FL, GA, SC, NC, VA, WV, MD, DE), Mid Atlantic (PA, NY, NJ, CT), New England (NH, VT, ME, MA, RI), East South Central (AL, MS, TN, KY), East North Central (OH, IN, IL, MI, WI), West South Central (AR, LA), West North Central (MN, IA, MO). The states included in the West South Central and West North Central regions were adapted to include only the states where Florida-grown blueberries were shipped and respondents resided. A total of 3,100 respondents started the survey. However, only 2,100 respondents provided complete and usable responses, resulting in a participation rate of 67.7%. One attention filter was included in the survey to help ensure that respondents were reading the questions and not just clicking responses. The attention filter asked respondents to “select strongly disagree.” Respondents who selected an option other than “strongly disagree” were terminated from the survey.
Questions regarding respondents’ knowledge of the health benefits of blueberries and demographics were of interest for this study. Respondents were tested on their knowledge of the health benefits of blueberries through a series of seven statements that were presented to each respondent in the same order. Respondents were asked to indicate whether the statements were true or false. Five of the statements were true (e.g. Blueberries can improve memory, Blueberries help reduce the effects of aging) and two of the statements were false (e.g. Blueberries help achy joints, Blueberries limit hearing loss). If respondents answered a question correctly, they received a score of one for that item. If they answered a question incorrectly, they received a score of zero for that item. Therefore, eachrespondent could receive a total knowledge score ranging from zero (answered all knowledge questions incorrectly) to seven (answered all knowledge questions correctly).
Respondents were asked to answer demographic questions regarding their education, income, age, and gender. Respondents could select their education level from the options of less than 12th grade (did not graduate high school),high school graduate (includes GED), some college (no degree), 2-year college degree, 4-year college degree, andgraduate or professional degree. For data analysis, education data were recoded into three groups: high school graduate or less, some college (no degree), and college degree. Respondents could select their annual household income from the options of less than $30,000 to more than $100,000, at $10,000 increments between $30,000 and $100,000. For data analysis, income data were recoded into three groups: $30,000 or less, $30,000 – $59,999, and $60,000 – More. Respondents reported their age by indicating their year of birth. For data analysis, respondents were grouped into age groups by generation. Those born before 1946 were grouped into the GreatestGeneration, also known as the Silent Generation. Those born between 1946 and 1964 were classified as Baby Boomers.The Generation X group included those born between 1965 and 1981. Those born between 1982 and 2004 were classified as Millennials (Bump, 2014). Due to a small percentage of respondents representing the Greatest Generation, the Greatest Generation was grouped with the Baby Boomers for analysis to increase power of the statistical test. The larger survey included additional questions such as importance and satisfaction of several blueberry traits, seasonality knowledge, and questions regarding perceptions of Florida blueberries.
Prior to data collection, the survey instrument was validated by a panel of experts including a professor, and two assistant professors specializing in social sciences in agriculture as well as a professional working in the fruit andvegetable industry. Following data collection and weighting, data were analyzed for descriptive statistics. Additionally,a one-way ANOVA was used to analyze data for objectives two and three. A one-way ANOVA is a statistical test that compares the mean of two or more groups (Field, 2013). The statistical significance was set at 95% confidence.
Results
Of the 2,100 respondents, most were female (74.6%), and 25.4% were male (Table 1). Most of the respondents were Baby Boomers (36.9%), followed by Generation X (32.9%), Millennials (25.4%), and Greatest Generation (4.8%). Just under half of respondents (44.3%) had a college degree, while 27.9% had a high school education or less, and 27.8% had some college education. The highest percentage of respondents (37.5%) had an annual household income between $30,000 and $59,999.
Table 1 Demographic Characteristics of the Respondents
| Demographic Categories | f | % |
|---|---|---|
| Gender | ||
| Female | 1567 | 74.6 |
| Male | 533 | 25.4 |
| Generations | ||
| Millennials | 533 | 25.4 |
| Generation X | 691 | 32.9 |
| Baby Boomers | 775 | 36.9 |
| Greatest Generation | 101 | 4.8 |
| Education | ||
| High School graduate or less | 586 | 27.9 |
| Some college (no degree) | 583 | 27.8 |
| College degree | 930 | 44.3 |
| Annual Income | ||
| Less than $30,000 | 717 | 34.1 |
| $30,000 – $59,999 | 788 | 37.5 |
| $60,000 – More than $100,000 | 595 | 28.3 |
Objective 1: Describe Consumers’ Knowledge of the Health Benefits of Blueberries.
Seven specific statements about the health benefits of blueberries were presented to the respondents in the survey. Five out of the seven statements were true, and two of the statements were false. Respondents were asked to determine whether each statement was true or false. The number of correct responses among all seven statements varied greatly. Over 80% of respondents correctly identified that the statements “Blueberries help ward off heartdisease” and “Blueberries lower risks to cancer” were true. Less than half of the respondents correctly identified that the statement “Blueberries help with achy joints” was false (Table 2). The mean overall knowledge score for the respondents was 4.55 (SD = 1.22), which indicates respondents correctly answered 64.9% of the questions.
Table 2 Knowledge Statements about the Health Benefits of Blueberries
| Knowledge Statements | True or False | correct n | correct % |
|---|---|---|---|
| Blueberries help ward off heart disease | T | 1748 | 83.2 |
| Blueberries lower risks to cancer | T | 1713 | 81.6 |
| Blueberries decrease hearing loss | F | 1382 | 65.8 |
| Blueberries help revert aging | T | 1366 | 65.0 |
| Blueberries can improve memory | T | 1335 | 63.6 |
| Blueberries strengthen eyesight | T | 1087 | 51.7 |
| Blueberries help with achy joints | F | 916 | 43.6 |
Objective 2: Determine if a Knowledge Gap Regarding Blueberries Exists Between Respondents with Different Education and Income Levels.
The analysis of knowledge among education groups revealed that some college (M = 4.60, SD = 1.26) andcollege graduate (M = 4.60, SD = 1.18) groups had higher knowledge of the health benefits of blueberries than the high school graduate or less group (M = 4.42, SD = 1.24) (Table 3). The assumption of equal variances was found violated thus the mean knowledge scores for education level were compared using Welch ANOVA instead of one-way ANOVA. The Welch ANOVA showed a significant difference between education groups (F (2, 2096) = 4.06, p = .018). However, the effect size for knowledge level (ω2 = .003) was small according to Cohen’s guidelines (1988) (Table 3). Therefore, only .3% of variance in knowledge level was due to education. A follow-up test, using planned contrasts, revealed that there were significant differences between the high school graduate or less group and the college graduate group (t = – 2.62, p = .009) as well as between the high school graduate or less group and the some college (no degree) group (t = -2.38, p = .017) (Table 4). There was not a significant difference between the some college (no degree) and college graduate groups (Table 4).
Table 3 Welch ANOVA Test of Respondents’ Knowledge Level among Different Education levels
| Education level | n | M | SD | ω2 | F | p |
|---|---|---|---|---|---|---|
| High school or less | 586 | 4.42 | 1.24 | 0.003 | 4.06 | .02* |
| Some college | 583 | 4.60 | 1.26 | |||
| College graduate | 930 | 4.59 | 1.18 |
Table 4 Planned Contrasts of the Differences of Knowledge Level among Different Education Levels
| (I) Group | (J) Group | ∆M (I-J) | t | SE | p |
|---|---|---|---|---|---|
| High school or less | Some college | -.17 | -2.38 | .07 | .017* |
| College graduate | -.17 | -2.62 | .06 | .009** | |
| Some college (no degree) | High school or less | .172 | .38 | .07 | .017* |
| College graduate | .01 | .081 | .06 | .94 | |
| College graduate | High school or less | .172 | .62 | .06 | .009** |
| Some college | -.01 | -.081 | .06 | .94 |
The analysis of knowledge among income groups revealed the following mean knowledge scores shown in the Table 5. The mean knowledge scores for income level were compared using a one-way ANOVA. The result did not show a significant difference between income groups (F (2, 2096) = 1.94, p = .14) (Table 5).
Table 5 One Way ANOVA Test of Respondents’ Knowledge Level among Different Income levels
| Education level | n | M | SD | F | p |
|---|---|---|---|---|---|
| Less than $30,000 | 717 | 4.48 | 1.26 | 1.94 | .14 |
| $30,000 to $59,999 | 788 | 4.60 | 1.19 | ||
| More than $60,000 | 595 | 4.55 | 1.21 |
Objective 3: Determine if a Knowledge Gap Regarding Blueberries Exists Between Respondents within Different Generations and Gender Groups.
The mean knowledge score for females was 4.58 (SD = 1.22), which was slightly higher than the mean score for males (M = 4.46, SD = 1.20). The one-way ANOVA did not show a significant difference in the mean knowledge score between gender groups (F (1, 2097) = 3.60, p = .06) (Table 6).
Table 6 One Way ANOVA Test of Respondents’ Knowledge Level among Different Gender Groups
| Gender | n | M | SD | F | p |
|---|---|---|---|---|---|
| Male | 533 | 4.46 | 1.20 | 3.60 | .06 |
| Female | 1567 | 4.58 | 1.22 |
The mean knowledge score of the Millennial generation was 4.56 (SD = 1.20). For Generation X, the mean was 4.56 (SD = 1.20). For the combined group of Baby Boomers and Greatest Generation, the mean was 4.53 (SD = 1.24). A one-way ANOVA test did not show a significant difference in the mean knowledge scores between generations (F (2, 2096) = .186, p = .83) (Table 7).
Table 7 One Way ANOVA Test of Respondents’ Knowledge Level among Different Generation Groups
| Generation | n | M | SD | F | p |
|---|---|---|---|---|---|
| Millennial | 533 | 4.56 | 1.20 | .186 | .83 |
| Generation X | 691 | 4.56 | 1.20 | ||
| Baby Boomers and Greatest Generation | 876 | 4.53 | 1.24 |
Conclusion
Overall, consumers were able to correctly answer more than half of the blueberry benefit knowledge questions, indicating an acceptable level of knowledge about these benefits. However, there is still room for improvement considering the gaps that were found among different aspects of knowledge. Specifically, the majority of respondentsanswered questions relating to cancer and heart disease correctly, but were not as accurate in their knowledgeconcerning eyesight and joints. The high percentage of respondents correctly identifying blueberries as deterrents for cancer and heart disease may be related to the high awareness of these two diseases. The Centers for Disease Controland Prevention’s (2015) findings that these are the two leading causes of death in America may have led to more personal research related to preventing the diseases, leading to the respondents being exposed to these findings more than other benefits. Personal motivation and interest may be the key to the cancer and heart disease related questionsreceiving the highest mean knowledge scores for all respondents (Ettema & Kline, 1977).
Research concerning the anti-aging properties of blueberries (Schrager et al., 2015; Liu et al., 2012) suggests that these anti-aging properties span a spectrum of aging characteristics from protecting eyes from damage over time (Liu et al., 2012) to increasing the mobility of the elderly (Schrager et al., 2015). Just more than half of respondents correctly identified that blueberries could reduce the effects of aging, despite the research suggesting several aging benefits. Additionally, the benefit of improving memory was found to apply to both children (Whyte & Williams, 2012, p. 637) and adults (Krikorian et al. 2010). Improvement in memory was one of the three lowest the health benefits of blueberries to be correctly identified. This suggests there is still work to be done to disseminate thisinformation to all age groups about the memory and aging benefits. This lower level of knowledge may be related to personal interest and being more concerned about leading causes of death than aging or memory loss. Achy joints were the least correctly identified, meaning that respondents incorrectly believed that blueberries help with achy joints.
In terms of education and income affecting the knowledge level of blueberry benefits, education was found to have a significant effect on knowledge, while income did not. Those with some college or more education were found to have higher levels of knowledge than those with high school or less education, even though only small amount ofdifferences were due to education. Education’s effect is consistent with previous literature, while income not having an effect is inconsistent with other findings (Tichenor et al., 1970; Viswanath et al., 1993; Winkleby et al., 1992). These research findings have been consistent in that the more educated groups, and presumably higher SES group, receive and retain more information about the benefits of blueberries. Though lower SES individuals do not receive informationas quickly or retain as much of the information, those with lower levels of education did have some knowledge of the health benefits of blueberries.
Following research by Lovrich and Pierce (1984), individuals in higher SES groups may be at an advantage because of their higher levels of education leading to their ability to interpret
messages they receive about blueberry benefits better than those with lower education levels. They may also have better contacts with professionals or like-minded individuals that seek out the information about nutrition benefits, leading to their higher knowledge level (Lovrich & Pierce, 1984). This could include better access to healthcare or health education programs. Education’s effect on overall nutritional knowledge is researched widely (De Irala-Estevez et al., 2000; De Vriendt et al., 2009; Giskes et al., 2002, Giskes et al., 2010; Hendrie et al., 2008; Turrell & Kavanagh, 2006). Education has a significant effect on the level of nutritional knowledge, including knowledge of blueberry benefits. However, it has been shown that education alone cannot explain differences in knowledge (Ettema & Kline, 1977). The respondents’ individual motivation and interest may also be impacting their knowledge of the health benefits ofblueberries. Those with family histories of diseases such as heart disease or cancer may have a greater incentive to protect themselves and may be more likely to seek out information about prevention. While motivation and interest were not measured in this study, they may be helpful indicators of how to close the knowledge gap of blueberry benefits, as interest has been found to predict knowledge better than education (Chew & Palmer, 1994) and motivation is correlated with education (Kwak, 1999) in identifying knowledge gaps.
Both gender and age were not found to be significant in accounting for differences in the knowledge aboutblueberry benefits, which is inconsistent with the literature (Hendrie et al., 2008, Vriendt et al., 2009). Though this study did not predict individuals’ knowledge with a regression analysis based on education, age, and gender (among other factors), these factors were found in previous studies to be indicative of different knowledge levels. Had age been treated as a continuous variable and been used in a regression model to predict mean scores, it may have been a significant predictor of knowledge. However, the researchers of this study chose to utilize generational groups in orderto have a more defined target audience if significant differences were found. The average overall knowledge score of 4.55 out of seven, is promising for both the blueberry industry and the health of consumers, but there is still work to be done to spread the benefits to people of all SES classes.
Recommendations
Consumers presented a higher level of familiarity with the blueberry benefits concerning cancer and heart disease than other benefits such as reducing the effects of aging, improving memory, and strengthening eyesight. Therefore, agricultural extension faculty, health communicators, and practitioners should emphasize the lesser-known health benefits when promoting blueberries. This will help the public to gain a more comprehensive understanding of the health benefits of blueberries and increase the possibility that they will consume more blueberries to capture these benefits. Increased communication about the health benefits may also welcome new blueberry consumers who had not previously known about the health benefits of blueberries or encourage existing blueberry consumers to purchase more.
The ultimate purpose of increasing the knowledge level and closing the knowledge gap of the health benefits of blueberries is to encourage more people from all social groups to consume more blueberries. Effective blueberry promotion and communication strategies should be used to enhance the public’s knowledge about the health benefits of blueberries. Blueberry organizations
throughout blueberry growing states and the nation should provide effective marketing tools to help famers and marketers with promotion of their blueberries, as well as communication of the health benefits of blueberries. Extension faculty and blueberry producers should create opportunities such as blueberry tastings or blueberry u-picks during blueberry season to disseminate information about the health benefits of blueberries, especially among people with high school education or lower.
Literature has shown that television campaign viewing has the potential to close gaps between high and low education level groups (Ettema et al., 1983; Ho, 2012; Kwak, 1999). Additionally, Cacciatore et al. (2014) stated that the Internet has allowed its users to tailor information to different audiences and its ability of closing knowledge gaps. To close the knowledge gap regarding the health benefits of blueberries, agricultural and health communicators and related organizations should consider using the Internet or televised Public Service Announcements to increase the public’s knowledge level of the health benefits of blueberries, while hopefully narrowing the knowledge gap. However, before investing in a communication channel, extension faculty and health communicators should ensure that their target audience, perhaps a low education audience, can be reached through that communication channel.
This research investigated the influence of socio-demographic characteristics on overall knowledge of the health benefits of blueberries. Further analysis of potential knowledge gaps of individual health benefits of blueberries should be explored. Researchers should consider additional knowledge questions or alternative measures of knowledge, such as open-ended responses graded by a rubric, to determine the breadth and consistency of the knowledge gap observed related to the health benefits of blueberries. Future research should also analyze other aspects that have been formerly suggested to attribute to the knowledge gap, including level of motivation, prior knowledge, use of information, relevant social contacts, communication skills, and structure of the media system (Bonfadelli, 2002). In terms of the influence of motivation on knowledge level, it is worthwhile to explore what activities, lifeexperiences or family backgrounds influence people’s motivation to acquire health information such as the health benefits of blueberries. These findings could inform communicators in creating effective activities and messages to boost their audience’s motivation to seek out blueberry-related information. In addition, this information would help communicators to use storytelling as a strategy to engage target audiences by tying communication to relevant life experiences and family backgrounds.
To develop effective communication strategies to promote blueberries, future research should examine how consumers currently seek and receive blueberry-related content. The use of new media (including smartphone, social media, and interpersonal online social network) for nutritional information should also be analyzed as new media has become an important outlet for health-related information (Smith, 2015). Researchers should further investigate individual’s information processing patterns regarding health-related information. For example, research could test how different message appeals (e.g. rational appeal, emotional appeal, and social appeal) impact populations with different education levels in the acceptance and storage of blueberry health benefit knowledge.
Research studies regarding health education have shown positive, encouraging, inspiring messaging are more persuasive and would be more likely to make long lasting impact to health behavior change (McKinnon, 2007; Ybarra, Holtrop, Prescott, & Strong, 2014). Researchers should create positive messages about the blueberry benefits and test the message effectiveness. Effective messages could be used for cancer and heart health campaign in addition to blueberry promotion and marketing.
In terms of social contacts and communication skills, researchers could utilize focus groups with only high blueberry knowledge participants and only low blueberry knowledge participants to discuss how social contacts and communication skills influence individuals’ knowledge acquisition about blueberries. Themes from different knowledge level groups could be compared to inform strategies to enhance blueberry knowledge acquisition through social events or communication trainings. Further research is needed to identify what media channels consumers frequently use to seek nutrition-related information among audiences with different education levels. The findings will assist agricultural and health communicators in identifying the most appropriate channel to target their audiences.
This study focused solely on the health benefits of blueberries. The methods and model used in this study could be applied to the study of vegetables, grains, or other fruits. Researchers should expand the research scope and examinewhether knowledge gap of health benefits exist for other foods. Such studies could help educators and communicators todevelop materials to advance the health and nutrition education of their target audiences.
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