# Public knowledge, attitudes, and perceptions toward genetically modified foodsin Lebanon

Hussein F. Hassan, Hasan Yassine, Ahlam Chaaban, Zeinab Skaineh, Nagham Cherri, Sahar Moussawi, Nour Baytamouni, Philippe Hussein Kobeissy, José Noel Ibrahim, Ahmad Chehaitly, et al.

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## ► To cite this version:

Hussein F. Hassan, Hasan Yassine, Ahlam Chaaban, Zeinab Skaineh, Nagham Cherri, et al. Public knowledge, attitudes, and perceptions toward genetically modified foodsin Lebanon. GM Crops and Food, 2025, 16 (1), pp.144-155. 10.1080/21645698.2025.2450852. hal-05029224

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Submitted on 16 Apr 2025

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# Public knowledge, attitudes, and perceptions toward genetically modified foods in Lebanon

Hussein F. Hassan, Hasan Yassine, Ahlam Chaaban, Ahmad Chehaitly, Zeinab Skaineh, Nagham Cherri, Sahar Moussawi, Nour Baytamouni, Philippe Hussein Kobeissy, Hani Dimassi & José-Noel Ibrahim

**To cite this article:** Hussein F. Hassan, Hasan Yassine, Ahlam Chaaban, Ahmad Chehaitly, Zeinab Skaineh, Nagham Cherri, Sahar Moussawi, Nour Baytamouni, Philippe Hussein Kobeissy, Hani Dimassi & José-Noel Ibrahim (2025) Public knowledge, attitudes, and perceptions toward genetically modified foods in Lebanon, GM Crops & Food, 16:1, 144-155, DOI: 10.1080/21645698.2025.2450852

**To link to this article:** https://doi.org/10.1080/21645698.2025.2450852

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© 2025 The Author(s). Published with license by Taylor & Francis Group, LLC.

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Published online: 15 Jan 2025.

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# Public knowledge, attitudes, and perceptions toward genetically modified foods in Lebanon

Hussein F. Hassan<sup>a*</sup>, Hasan Yassine<sup>b*</sup>, Ahlam Chaaban<sup>b</sup>, Ahmad Chehaitly<sup>c</sup>, Zeinab Skaineh<sup>b</sup>, Nagham Cherri<sup>b</sup>,
Sahar Moussawi<sup>b</sup>, Nour Baytamouni<sup>b</sup>, Philippe Hussein Kobeissy<sup>b</sup>, Hani Dimassi<sup>d</sup>, and José-Noel Ibrahim<sup>b</sup>

<sup>a</sup>Department of Nutrition and Food Science, School of Arts and Sciences, Lebanese American University, Beirut, Lebanon; <sup>b</sup>Department of Biological Sciences, School of Arts and Sciences, Lebanese American University, Beirut, Lebanon; <sup>c</sup>U1179 INSERM, END-ICAP, UFR des Sciences de la Sante-Simone Veil, Universite de Versailles Saint-Quentin-en-Yvelines, Montigny-le-bretonneux, France; <sup>d</sup>School of Pharmacy, Lebanese American University, Byblos, Lebanon

## ABSTRACT

Genetically modified foods (GMFs) have garnered significant attention due to their implications for health, agriculture, and food security. Understanding knowledge and perceptions of GMFs is essential, as these factors influence acceptance and attitudes. This study, the first of its kind in Lebanon, aimed to assess the knowledge, attitudes, and perceptions regarding GMFs and to explore their association with socio-demographic characteristics. A cross-sectional study was conducted with 1,001 participants who completed a 50-item questionnaire, followed by a 15-minute educational session on GMFs. Statistical analysis was performed using SPSS. Prior to the educational session, participants had an average knowledge score of 60.3 ± 17.4%, which significantly increased to 83.0 ± 15.8% afterward. Attitude and perception scores improved from an average of 30.3 ± 25.1% pre-intervention to 38.9 ± 12.4% post-intervention. Females demonstrated significantly higher knowledge scores, and educational attainment was positively correlated with knowledge levels both pre- and post-intervention. Younger participants and those in health-related fields scored higher before the intervention, while unemployed individuals scored lower. Additionally, higher educational levels and health-related educational backgrounds were linked to better attitudes and perceptions pre-intervention, while unemployment correlated with lower scores. Interestingly, multivariate regression analysis indicated that being under 35 years of age, having a health-related educational background, and holding a university degree were predictors of higher GMF knowledge. Consequently, individuals with initially lower knowledge level benefited the most from the educational intervention, exhibiting the greatest knowledge increases post-education. Our findings underscore the importance of targeted educational initiatives to bridge knowledge gaps and address misconceptions regarding GMFs.

## ARTICLE HISTORY

Received 7 November 2024
Revised 10 December 2024
Accepted 3 January 2025

## KEYWORDS

Acceptance; attitude;
education; food safety; GMO;
knowledge; perception

## 1. Introduction

Genetic modification refers to biological techniques associated with the change of the genome and genetic machinery of living organisms.¹ According to the World Health Organization (WHO), genetically modified organisms (GMOs) are plants, animals, or microorganisms whose genetic material (DNA) has been modified in a manner that does not happen naturally through reproduction or natural genetic exchange.² Therefore, “GM foods” (GMFs) refer to foods produced from GM plants or animals, such as golden rice, arctic apples, and *Bacillus thuringiensis* corn.³ In the last three decades, the usage of GMOs has increased by more than

a hundredfold.⁴,⁵ Indeed, GMFs offer many advantages over organic crops, including resistance to pathogens, drought tolerance, and increased economic benefits.⁶ Nevertheless, an international concern pertinent to the risks associated with GMOs to both environmental and human health has been raised.⁷ As such, a need for regulating the usage and spread of GMOs was depicted by the Cartagena Protocol on Biosafety, which took effect in 2003.⁸

Different governments and unions have responded to the perceived risks of GMOs in various ways, primarily through diverse legislation

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measures. For instance, the EU is considered to have one of the strictest GMO regulations based on the assumption that GMFs are more dangerous than their organic counterpart.⁹ However, the attitude of Indonesian scientists toward GMOs was more positive due to the familiarity with the technology.¹⁰ Uganda consumers, similar to Indonesia, tend to have a more positive attitude toward GM bananas, valuing their added nutritional value, affordability, and quality over its presumed potential health risks.¹¹ In Kenya, a cross-sectional survey of 216 participants showed that over half believe GMFs are safe, have low threats to health, and are a solution to food insecurity in Africa.³ Interestingly, in China, findings concerning GMO commercialization are controversial and somehow contradictory. For instance, a study conducted among urban consumers in developed areas of China showed minimal resistance to GMFs due to the majority of them being familiar with GMOs.¹² On the contrary, a nationwide study exploring the public perception of GMFs revealed that most consumers were either neutral or negative toward GMFs, mainly because of being unfamiliar with GM technology or receiving negative information from the internet or media.¹³ Lastly, the MENAT (Middle East, North Africa, and Turkey) region tends to exhibit negative attitudes toward GMFs due to the poor knowledge of the technology.¹⁴ Therefore, it seems that consumer attitudes toward GMFs are complex and intertwine with the knowledge of the technology, perceptions of risks and benefits, and individual lifestyle and moral beliefs.

Although Lebanon is not a producer of GMOs, the country has addressed the issue by developing a biosafety framework.¹⁵ Interestingly, the country has a national legislation concerning GMO imports under Article 6 of the “Plant Quarantine and Phytosanitary Measures” Law # 778 dated 28/11/2006.¹⁶ Previous research has indicated that GMFs, particularly soybeans, have been present in the Lebanese market.¹⁵ Nonetheless, no studies have explored the Lebanese individuals’ knowledge of GMFs and its impact on their attitudes and perceptions of the risks, benefits, purchase intentions, and consumption of GMFs.

Due to the rising global food security challenges and the ongoing decade-long debates on GMFs, the

present study aims to investigate the knowledge, attitudes, and perceptions of the general population in Lebanon toward GMFs. Moreover, it intends to explore the effects of education and advertisement on the public knowledge and, consequently, its influence on their attitudes and acceptance levels of GMFs. The findings will reflect the public's stance, behavior, and response as to whether GMF production and consumption should be legalized in Lebanon.

## 2. Materials and Methods

### Study Design and Population

This study was conducted according to the Declaration of Helsinki and approved by the Institutional Review Board of the Lebanese American University (IRB #: LAU.SAS.JI1.17/Jan/2024). The sample consisted of Lebanese individuals aged between 18 and 65 years old. The sample size was estimated according to the Institutional Effectiveness and Assessment Board, which recommends a sample of 1,000 to ensure the representativeness of the sample in large populations.¹⁷

A total of 1,500 individuals from across Lebanon were conveniently approached to participate in the study, ensuring a proportional distribution across the governorates based on population size in each (Figure 1). Approximately 10% (N = 151) did not accept to participate in the study, mainly due to lack of motivation, interest in the research topic, or time availability.

Face-to-face meetings were arranged with individuals interested in participating based on their availability. After explaining the nature and purpose of the research, respondents were asked to provide their written consent to participate voluntarily in the research project. However, 349 individuals lost interest mid-survey and failed to complete the questionnaire, hence making the final sample size of 1,001 participants.

### Questionnaire

Data were collected between January and August of 2024 using a 50-item structured questionnaire designed based on previous studies and adapted for the Lebanese context.¹⁸,¹⁹ The
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<figure><img src="image_17.png" /><figcaption>**Figure 1.** Map of the study area showing the distribution of the participants across the different governorates.</figcaption></figure>

questionnaire was thoroughly reviewed and approved by multiple experts who have considerable expertise in the field before being translated into Arabic and then back-translated by bilingual experts to ensure accuracy. Both language versions were pilot-tested to gather feedback on the clarity of instructions, comprehension of questions, and difficulty in answering them. The questionnaire was then completed in either Arabic or English, depending on the participants' preference. The first part of the questionnaire focused on the socio-demographic characteristics, including age, sex, education, residence, and occupation. The

following sections explored the participants' subjective and objective knowledge of GMFs, perceived risks and benefits, attitudes, and willingness to buy and consume GMFs. Subjective knowledge was assessed using a 5-point Likert scale [1=Not knowledgeable at all, 2=Somehow unknown/e knowledgeable, 3= Neutral, 4=Somehow knowledgeable, 5=Extremely knowledgeable]. Participants were then asked seven "true" and "false" questions to assess their objective knowledge on GMFs. The correct answer was scored "1" and the incorrect answer was given a "0." Perceived risks, benefits, attitudes, and acceptance of GMFs were assessed using a 5-point
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Likert scale [1=Strongly disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly agree]. Correct answers were summed up and both knowledge and attitudes/perceptions scores were converted over 100%.

## Educational Session

At the end of the questionnaire, participants received a 15-minute educational session on GMFs, narrated by trained interviewers under the guidance of the principal investigator. The purpose aimed to improve participants' objective knowledge and to assess how their increased knowledge would impact their perceptions and attitudes toward the use and consumption of GMFs. The content of the educational session was developed using different scientific resources.²⁰,²¹ It included definitions and examples of GMFs, as well as their benefits on health and the environment, and potential associated risks.¹⁸,¹⁹ After completing the session, the participants were asked how informative the educational session was using a 5-point Likert scale [1=Not informative at all; 2=Not that informative; 3=Neutral; 4=Somehow informative; 5=Extremely informative]. In addition, their objective knowledge, perceived risks and benefits, and attitudes were assessed, and scores were computed and compared to those obtained before the educational session.

## Data Confidentiality

Information obtained from the survey was de-identified and kept anonymous. To preserve privacy, information collected from the questionnaire was linked to a secret code. Participants' names were only recorded on the informed consent form. The informed consent and hard copy records were carefully protected in a locked file cabinet, with access limited to the principal investigator and authorized personnel. Electronic copies were saved in an Excel sheet on the laptop of the principal investigator secured with a password.

## Statistical Analysis

Data collected were coded and entered into SPSS software, version 29, for analysis. Knowledge

scores were computed by summing responses to knowledge-based questions both before and after the educational intervention. Perception scores were calculated similarly. To assess differences in knowledge and perception scores by participants' characteristics, independent samples t-tests and one-way ANOVA were employed, with assumptions of normality verified prior to analysis. Pearson's correlation coefficient (r) was used to measure the strength and direction of relationships between numerical scores. Two linear regression models were constructed to evaluate the independent effects of participants' characteristics on knowledge scores at baseline and on changes in knowledge scores post-intervention. Statistical significance was set at *p* < 0.05.

# 3. Results and Discussion

## Demographic Characteristics of the Study Population

A total of 1,001 valid questionnaires were included in the study. Of the respondents, 63.6% were females, 34.1% from the capital Beirut and its suburbs, 70.5% holding a university degree, 66.7% below 35 years old, 20.5% having health-related degree, and 65.0% single (Table 1).

## Knowledge of GMFs

Seven questions were asked to assess participants' knowledge of GMFs, with pre- and post-educational responses presented in Table 2. Most participants in our study (91%) were aware of GM technology, aligning with findings by Catherine et al.,³ who reported 100% awareness in Kenya. Additionally, 62.0% and 60.0% of our participants knew that GMFs are not produced but are present in Lebanon, respectively. In contrast, 91.7% of participants in Kenya indicated that GMFs are available in the market, while in Saudi Arabia, majority of the respondents (73.4%) were not aware of GMFs in the market.²² Furthermore, 25.0% of participants in Kenya considered GM technology harmful, whereas in our study, 41.4% believed GMFs contain hazardous chemicals, and 69.1% thought
<figure><img src="image_19.png" /><figcaption>**Table 1.** Demographic characteristics of the study population (N = 1,001).</figcaption></figure>

<table><thead><tr><th>Demographic Characteristics</th><th>N</th><th>%</th></tr></thead><tbody><tr><td><strong>Gender</strong></td><td></td><td></td></tr><tr><td>Male</td><td>364</td><td>36.4</td></tr><tr><td>Female</td><td>637</td><td>63.6</td></tr><tr><td><strong>Residential Governorate</strong></td><td></td><td></td></tr><tr><td>Beirut & suburbs</td><td>341</td><td>34.1</td></tr><tr><td>Mount Lebanon</td><td>239</td><td>23.9</td></tr><tr><td>Bekaa/Baalbeck-Hermel</td><td>198</td><td>19.8</td></tr><tr><td>South Lebanon/Nabatieh</td><td>184</td><td>18.4</td></tr><tr><td>North Lebanon/Akkar</td><td>39</td><td>3.9</td></tr><tr><td><strong>Educational Level</strong></td><td></td><td></td></tr><tr><td>Below elementary</td><td>24</td><td>2.4</td></tr><tr><td>Elementary/Primary school or equivalent</td><td>43</td><td>4.3</td></tr><tr><td>High school diploma or equivalent</td><td>228</td><td>22.8</td></tr><tr><td>Bachelor's degree</td><td>564</td><td>56.3</td></tr><tr><td>Master's degree</td><td>105</td><td>10.5</td></tr><tr><td>Doctorate degree</td><td>37</td><td>3.7</td></tr><tr><td><strong>Monthly household income ($)</strong></td><td></td><td></td></tr><tr><td>&lt;50</td><td>29</td><td>2.9</td></tr><tr><td>50-200</td><td>109</td><td>10.9</td></tr><tr><td>200-999</td><td>343</td><td>34.3</td></tr><tr><td>1000-2999</td><td>239</td><td>23.9</td></tr><tr><td>≥3000</td><td>166</td><td>16.6</td></tr><tr><td>Missing</td><td>115</td><td>11.5</td></tr><tr><td><strong>Age</strong></td><td></td><td></td></tr><tr><td>18-24</td><td>560</td><td>55.9</td></tr><tr><td>25-34</td><td>108</td><td>10.8</td></tr><tr><td>35-44</td><td>95</td><td>9.5</td></tr><tr><td>45-54</td><td>116</td><td>11.6</td></tr><tr><td>55-64</td><td>76</td><td>7.6</td></tr><tr><td>65 and above</td><td>46</td><td>4.6</td></tr><tr><td><strong>Major of study</strong></td><td></td><td></td></tr><tr><td>Health-related</td><td>205</td><td>20.5</td></tr><tr><td>Non-health related</td><td>330</td><td>33.0</td></tr><tr><td>Not applicable (due to educational level)</td><td>270</td><td>27.0</td></tr><tr><td>Missing/Not specified</td><td>196</td><td>19.6</td></tr><tr><td><strong>Area of residence</strong></td><td></td><td></td></tr><tr><td>City</td><td>679</td><td>67.8</td></tr><tr><td>Town</td><td>195</td><td>19.5</td></tr><tr><td>Village</td><td>127</td><td>12.7</td></tr><tr><td><strong>Family status</strong></td><td></td><td></td></tr><tr><td>Single</td><td>651</td><td>65.0</td></tr><tr><td>Having kids</td><td>310</td><td>31.0</td></tr><tr><td>Not having kids</td><td>38</td><td>3.8</td></tr><tr><td>Missing</td><td>2</td><td>0.2</td></tr><tr><td><strong>Working status</strong></td><td></td><td></td></tr><tr><td>Unemployed/Retired</td><td>194</td><td>19.4</td></tr><tr><td>Student</td><td>504</td><td>50.3</td></tr><tr><td>Employed/Self-employed</td><td>301</td><td>30.1</td></tr><tr><td>Missing</td><td>2</td><td>0.2</td></tr><tr><td><strong>Field of work</strong></td><td></td><td></td></tr><tr><td>Health-related</td><td>31</td><td>3.1</td></tr><tr><td>Non-health related</td><td>199</td><td>19.9</td></tr><tr><td>Not applicable (not employed)</td><td>191</td><td>19.1</td></tr><tr><td>Not applicable (student)</td><td>504</td><td>50.3</td></tr><tr><td>Missing/Not specified</td><td>78</td><td>7.8</td></tr></tbody></table>

that consuming GMFs could modify human genes. Finally, only 31% of our sample knew that there is a law that regulates GMF production and consumption, which is in agreement with data reported in Saudi Arabia (31%).²² Interestingly, the percentage of correct answers increased across all seven questions following the educational component.

The mean knowledge scores improved significantly ($p < 0.001$), rising from 60.3 ± 17.4% before to 83.0 ± 15.8% after the educational component. Females scored significantly higher than males ($p < 0.05$), and a higher educational level was associated with a significant increase in mean knowledge scores both before ($p < 0.001$) and after ($p = 0.017$) the educational component. Younger participants and those studying health majors scored higher before the intervention ($p < 0.001$), while unemployed individuals and those working in non-health related fields scored lower ($p < 0.001$ and $p = 0.017$ respectively) (Table 3).

The significant effect of education on the GMF knowledge confirms that education can effectively enhance understanding of complex topics like GMF. Interestingly, females scored significantly higher than males. This can be attributed to the fact that women often show a strong interest in health topics due in part to the broader representation of women in health-related and life sciences fields, where GMO topics are frequently covered. Additionally, since women traditionally play a significant role in food purchasing and meal preparation within households, they may encounter GMO information on food labels or through media focused on food safety. This consumer role likely increases their awareness and understanding of GMOs. Moreover, women are sometimes more engaged in public health campaigns and community discussions addressing health issues, which may further enhance their knowledge in this area. Research also suggests that women generally exhibit greater concern regarding food safety risks, leading them to seek information on GMOs to assess potential health and environmental impacts.²³

On the other hand, unemployed participants and those in non-health-related fields scored significantly lower on GMF knowledge for a few key reasons. First, individuals in non-health-related fields may have less exposure to scientific discussions about GMFs, as their academic and professional backgrounds might not cover biotechnology, food safety, or public health topics where GMOs are frequently addressed. Second, unemployed participants may have fewer opportunities to engage
<figure><img src="image_20.png" /><figcaption>**Table 2.** GMF knowledge questions/answers before and after the educational session.</figcaption></figure>

<table><thead><tr><th rowspan="2">GMF Knowledge Question (correct option is shown in bold)</th><th colspan="2">Before</th><th colspan="2">After</th></tr><tr><th>N</th><th>%</th><th>N</th><th>%</th></tr></thead><tbody><tr><td><strong>GM foods exist</strong></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>TRUE</strong></td><td>911</td><td>91.0</td><td>991</td><td>99.0</td></tr><tr><td>FALSE</td><td>90</td><td>9.0</td><td>10</td><td>1.0</td></tr><tr><td><strong>GM foods contain hazardous chemicals</strong></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>TRUE</strong></td><td>587</td><td>58.6</td><td>180</td><td>18.0</td></tr><tr><td><strong>FALSE</strong></td><td>414</td><td>41.4</td><td>821</td><td>82.0</td></tr><tr><td><em>Eating GM foods will modify a person's genes</em></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>TRUE</strong></td><td>309</td><td>30.9</td><td>122</td><td>12.2</td></tr><tr><td><strong>FALSE</strong></td><td>692</td><td>69.1</td><td>879</td><td>87.8</td></tr><tr><td><em>It is possible to transfer genes from microorganisms to plants</em></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>TRUE</strong></td><td>637</td><td>63.6</td><td>845</td><td>84.4</td></tr><tr><td>FALSE</td><td>364</td><td>36.4</td><td>156</td><td>15.6</td></tr><tr><td><em>Currently, GM foods are produced in Lebanon</em></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>TRUE</strong></td><td>380</td><td>38.0</td><td>164</td><td>16.4</td></tr><tr><td><strong>FALSE</strong></td><td>621</td><td>62.0</td><td>837</td><td>83.6</td></tr><tr><td><em>GM foods are available in the Lebanese market</em></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>TRUE</strong></td><td>601</td><td>60.0</td><td>641</td><td>64.0</td></tr><tr><td>FALSE</td><td>400</td><td>40.0</td><td>360</td><td>36.0</td></tr><tr><td><em>In Lebanon, there is a law that regulates GM food production and consumption</em></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>TRUE</strong></td><td>310</td><td>31.0</td><td>844</td><td>84.3</td></tr><tr><td>FALSE</td><td>691</td><td>69.0</td><td>157</td><td>15.7</td></tr></tbody></table>

with educational materials or professional networks where new information on GMOs is shared. Employment in health or science-related fields often provides access to industry updates, seminars, and other learning opportunities that keep professionals informed on topics like GMOs. Furthermore, without a professional or academic incentive to stay informed about health and food safety topics, these participants may have limited motivation to seek out information on GMOs independently. This was reported previously in food science studies in Lebanon assessing knowledge and attitudes.²⁴⁻³³

Notably, younger participants and those studying health-related fields scored significantly higher in the pre-educational phase (Table 3), potentially indicating preexisting exposure or interest in GMF within health-related curricula. This goes in line with the results of the multiple regression on the mean knowledge pre-educational intervention score, which showed that younger age (below 35), health-related educational background, and graduate studies are predictors of better GMF knowledge (Table 4). However, the absence of significant differences among these groups post-education suggests that the educational component successfully bridged initial knowledge disparities, bringing participants to a more uniform level of understanding. This was further supported by the results of the multiple regression analysis (Table 5) showing

that the mean knowledge score increased 6–8 times among participants aged above 35, 5–8 times among those without graduate studies, and 4 times among non-health background, following the educational intervention.

These findings underscore the role of education in promoting informed perspectives on GMFs and highlight the value of tailoring educational content to fill knowledge gaps across different demographics. Future educational interventions could further explore tailored approaches to address preexisting disparities, ensuring that knowledge enhancements are both widespread and enduring.

## Attitudes and Perceptions Toward GMFs

Seven questions were designed to evaluate participants' attitudes and perceptions regarding GMFs, with pre- and post-educational responses summarized in Figure 2. Overall, our participants displayed positive attitudes and perceptions toward GMFs, aligning with findings in the literature by Ghoochani et al. (2018)³⁴, Ghanian et al. (2016)³⁵, Prokop et al. (2013)³⁶, Zammit-Mangion et al. (2012)³⁷, and Heiman et al. (2011)³⁸. Also, a meta-analysis of 25 studies on GMFs showed that consumers in various countries placed 42–23% higher value for GMF compared to non-GMF.³⁹ In our study, 50.8% of participants agreed that GM technology increases yield, consistent with Catherine et al.³ who reported that 48% of study participants in Kenya
<figure><img src="image_21.png" /><figcaption>**Table 3.** Relations between demographic characteristics and mean GMF knowledge score before and after the educational session.</figcaption></figure>

<table><thead><tr><th rowspan="2">Demographic Characteristics</th><th colspan="2">Before</th><th colspan="2">After</th></tr><tr><th>Mean</th><th>SD</th><th>Mean</th><th>SD</th></tr></thead><tbody><tr><td><strong>Gender</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>58.6</td><td>16.7</td><td>81.6</td><td>17.0</td></tr><tr><td>Female</td><td>61.3</td><td>17.6</td><td>83.6</td><td>15.0</td></tr><tr><td>Sig.</td><td></td><td>0.02</td><td></td><td>0.04</td></tr><tr><td><strong>Residential Governorate</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Beirut & suburbs</td><td>60.6</td><td>16.5</td><td>82.0</td><td>16.6</td></tr><tr><td>Mount Lebanon</td><td>63.3</td><td>18.2</td><td>82.8</td><td>15.5</td></tr><tr><td>Bekaa/Baalbeck-Hermel</td><td>57.6</td><td>17.6</td><td>84.2</td><td>14.3</td></tr><tr><td>South Lebanon/Nabatieh</td><td>59.0</td><td>17.4</td><td>84.3</td><td>16.2</td></tr><tr><td>North Lebanon/Akkar</td><td>59.7</td><td>16.7</td><td>81.7</td><td>15.4</td></tr><tr><td>Sig.</td><td></td><td>0.01</td><td></td><td>0.39</td></tr><tr><td><strong>Educational Level</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Uneducated</td><td>45.8</td><td>13.3</td><td>73.8</td><td>13.8</td></tr><tr><td>Elementary/Primary school or equivalent</td><td>54.5</td><td>16.3</td><td>81.7</td><td>16.6</td></tr><tr><td>High school diploma or equivalent</td><td>56.5</td><td>17.5</td><td>81.6</td><td>15.1</td></tr><tr><td>Bachelor's degree</td><td>61.8</td><td>16.6</td><td>83.7</td><td>16.0</td></tr><tr><td>Master's degree</td><td>63.9</td><td>18.2</td><td>85.4</td><td>15.1</td></tr><tr><td>Doctorate degree</td><td>67.2</td><td>19.0</td><td>83.0</td><td>17.1</td></tr><tr><td>Sig.</td><td></td><td>&lt;0.001</td><td></td><td>0.017</td></tr><tr><td><strong>Age</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>18-24</td><td>62.3</td><td>16.5</td><td>82.7</td><td>16.5</td></tr><tr><td>25-34</td><td>63.4</td><td>17.9</td><td>83.5</td><td>15.0</td></tr><tr><td>35-44</td><td>58.8</td><td>18.7</td><td>86.3</td><td>14.7</td></tr><tr><td>45-54</td><td>58.0</td><td>18.6</td><td>84.5</td><td>12.6</td></tr><tr><td>55-64</td><td>51.9</td><td>16.8</td><td>80.8</td><td>16.6</td></tr><tr><td>65 and above</td><td>51.2</td><td>14.3</td><td>79.5</td><td>16.1</td></tr><tr><td>Sig.</td><td></td><td>&lt;0.001</td><td></td><td>0.08</td></tr><tr><td><strong>Major of study</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Health-related</td><td>67.4</td><td>15.4</td><td>86.4</td><td>14.8</td></tr><tr><td>Non-health related</td><td>60.5</td><td>16.7</td><td>84.4</td><td>15.2</td></tr><tr><td>Sig.</td><td></td><td>&lt;0.001</td><td></td><td>0.136</td></tr><tr><td><strong>Area of residence</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>City</td><td>60.2</td><td>17.2</td><td>82.2</td><td>15.8</td></tr><tr><td>Town</td><td>63.1</td><td>16.7</td><td>86.2</td><td>14.9</td></tr><tr><td>Village</td><td>56.5</td><td>18.5</td><td>82.7</td><td>16.6</td></tr><tr><td>Sig.</td><td></td><td>0.004</td><td></td><td>0.008</td></tr><tr><td><strong>Working status</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Unemployed/Retired</td><td>54.9</td><td>16.6</td><td>82.1</td><td>14.6</td></tr><tr><td>Student</td><td>62.4</td><td>16.7</td><td>82.8</td><td>16.2</td></tr><tr><td>Employed/Self-employed</td><td>60.2</td><td>18.2</td><td>84.1</td><td>15.8</td></tr><tr><td>Sig.</td><td></td><td>&lt;0.001</td><td></td><td>0.356</td></tr><tr><td><strong>Field of work</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Health-related</td><td>68.2</td><td>18.0</td><td>88.5</td><td>14.0</td></tr><tr><td>Non-health related</td><td>59.9</td><td>18.0</td><td>84.4</td><td>15.7</td></tr><tr><td>Sig.</td><td></td><td>0.017</td><td></td><td>0.177</td></tr></tbody></table>

viewed GM technology as important for boosting agricultural productivity. In contrast, 32.4% of our sample believed that GMFs require fewer herbicides, insecticides, and fertilizers, compared to 68.5% in Kenya. Moreover, 48.8% felt that GMFs do not taste as good as natural foods, while 50% of Kenyan participants reported enhanced taste, flavor, and appearance in GMFs. Furthermore, 36.8% of our participants believed that GM technology improves quality, compared to 47.7% in the Kenyan study, and 36.8% viewed GMFs as more affordable, versus 43.1% in Kenya. Lastly, 59.9% of our participants agreed that GMFs have major negative side effects on humans, whereas, in Israel, GMFs were perceived to be

healthier than their conventional counterparts by the majority of participants.⁴⁰ Remarkably, the percentage of participants who showed a positive attitude or perception toward GMFs increased across all questions following the educational component.

The mean attitude/perception scores improved significantly (*p* < 0.001), increasing from 30.3% ± 25.1 before to 38.9% ± 12.4 after the educational session. Indeed, before the educational intervention, higher educational levels were significantly associated with higher mean attitude/perception scores (*p* < 0.001), while unemployment correlated with lower scores (*p* = 0.027). On the other hand, participants with a health-related educational
<figure><img src="image_22.png" /><figcaption>**Table 4. Predictors of knowledge on GMF.**</figcaption></figure>

<table><caption>**Table 5. Multivariate analysis of change in knowledge on GMF.**</caption><thead><tr><th></th><th>B</th><th>Std. Error</th><th>p-value</th></tr></thead><tbody><tr><td>(Constant)</td><td>50.67</td><td>2.50</td><td>&lt;0.001</td></tr><tr><td>Gender (ref. Male)</td><td></td><td></td><td></td></tr><tr><td>Female vs Male</td><td>1.07</td><td>1.12</td><td>0.339</td></tr><tr><td>Governorate (ref. Mount Lebanon)</td><td></td><td></td><td></td></tr><tr><td>Beirut</td><td>-3.01</td><td>1.40</td><td>0.032</td></tr><tr><td>Bekaa/Baalbeck hermel</td><td>-4.40</td><td>1.61</td><td>0.007</td></tr><tr><td>South Lebanon Nabatieh</td><td>-3.49</td><td>1.64</td><td>0.033</td></tr><tr><td>North Akkar</td><td>-3.00</td><td>2.88</td><td>0.297</td></tr><tr><td>Age (ref. 55+)</td><td></td><td></td><td></td></tr><tr><td>Age = 18-24</td><td>8.57</td><td>1.75</td><td>&lt;.0001</td></tr><tr><td>Age = 25-34</td><td>8.20</td><td>2.31</td><td>&lt;0.001</td></tr><tr><td>Age = 35-44</td><td>4.21</td><td>2.34</td><td>0.072</td></tr><tr><td>Age = 45-54</td><td>4.09</td><td>2.19</td><td>0.061</td></tr><tr><td>Education (ref. Non university)</td><td></td><td></td><td></td></tr><tr><td>Education=Bachelor's degree</td><td>2.92</td><td>1.29</td><td>0.024</td></tr><tr><td>Education=Master's degree</td><td>7.29</td><td>2.05</td><td>&lt;0.001</td></tr><tr><td>Education=MD, PhD</td><td>8.49</td><td>3.07</td><td>0.006</td></tr><tr><td>Major (ref. Non-health related)</td><td></td><td></td><td></td></tr><tr><td>Health-related</td><td>6.27</td><td>1.40</td><td>&lt;0.001</td></tr></tbody></table>

<table><thead><tr><th></th><th>B</th><th>Std. Error</th><th>p-value</th></tr></thead><tbody><tr><td>(Constant)</td><td>11.04</td><td>2.29</td><td>&lt;0.001</td></tr><tr><td>Age (ref. 34 and below)</td><td></td><td></td><td></td></tr><tr><td>35-44</td><td>8.06</td><td>2.24</td><td>&lt;0.001</td></tr><tr><td>45-54</td><td>6.70</td><td>2.08</td><td>0.001</td></tr><tr><td>55-64</td><td>8.05</td><td>2.52</td><td>0.001</td></tr><tr><td>65 and above</td><td>7.03</td><td>3.32</td><td>0.034</td></tr><tr><td>Education (ref. Graduate level)</td><td></td><td></td><td></td></tr><tr><td>Below elementary</td><td>6.19</td><td>4.67</td><td>0.185</td></tr><tr><td>Elementary/Primary or equivalent</td><td>7.00</td><td>3.67</td><td>0.057</td></tr><tr><td>High school diploma or equivalent</td><td>8.12</td><td>2.24</td><td>&lt;0.001</td></tr><tr><td>Bachelor's degree</td><td>4.65</td><td>1.95</td><td>0.017</td></tr><tr><td>Major (ref. Health-related)</td><td></td><td></td><td></td></tr><tr><td>Non-health related</td><td>3.79</td><td>1.44</td><td>0.008</td></tr><tr><td>Governorate (ref. Mount Lebanon)</td><td></td><td></td><td></td></tr><tr><td>Beirut</td><td>2.31</td><td>1.67</td><td>0.167</td></tr><tr><td>Bekaa/Baalbeck hermel</td><td>5.49</td><td>1.93</td><td>0.004</td></tr><tr><td>South Lebanon Nabatieh</td><td>5.73</td><td>1.95</td><td>0.003</td></tr><tr><td>North Akkar</td><td>2.76</td><td>3.46</td><td>0.425</td></tr></tbody></table>

<figure><img src="image_23.png" /><figcaption>**Figure 2.** Comparison of pre-educational and post-educational attitudes and perceptions regarding GMFs. *Correct attitude</figcaption></figure>
<figure><img src="image_24.png" /></figure>

background scored significantly higher (p < 0.001) only on the pre-educational assessment. Interestingly, the mean attitude/perception scores increased following the educational component irrespective of the independent variables (Table 6).

The significant improvement in mean attitude/perception GMF scores from 30.3% to 38.9% following the educational component highlights the effectiveness of targeted education in shaping more informed and positive attitudes toward GMFs. This aligns with existing literature, which demonstrates that educational interventions can reduce misunderstandings and improve acceptance of scientific topics like GMOs.³⁸ Notably, before the educational intervention, higher educational levels were

associated with more favorable attitudes, suggesting that individuals with more advanced education may be better equipped to interpret scientific information, including the benefits and risks associated with GMOs. In agreement with these findings, our data showed a positive moderate correlation (r = 0.347; p < 0.001) between knowledge scores before education and mean attitudes/perceptions scores. These results further support the positive influence of knowledge and educational level on the individuals' attitudes/perceptions toward GMFs, but also highlight the contribution of other factors, such as culture, beliefs, and government trust, to developing a positive attitude/perception and a better acceptance rate to consume GMFs.¹³,¹⁹,⁴¹ Conversely, unemployed

<table><caption>**Table 6.** Relations between demographic characteristics and mean GMF attitudes/perceptions score before and after the educational session.</caption><thead><tr><th rowspan="2">Demographic Characteristics</th><th colspan="2">Before</th><th colspan="2">After</th></tr><tr><th>Mean</th><th>SD</th><th>Mean</th><th>SD</th></tr></thead><tbody><tr><td><strong>Gender</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>28.9</td><td>24.6</td><td>38.9</td><td>13.2</td></tr><tr><td>Female</td><td>31.0</td><td>25.3</td><td>38.9</td><td>11.9</td></tr><tr><td>Sig.</td><td colspan="2">0.22</td><td colspan="2">0.97</td></tr><tr><td><strong>Residential Governorate</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Beirut & suburbs</td><td>32.0</td><td>24.1</td><td>40.2</td><td>13.1</td></tr><tr><td>Mount Lebanon</td><td>32.3</td><td>26.1</td><td>37.4</td><td>12.9</td></tr><tr><td>Bekaa/Baalbeck-Hermel</td><td>28.3</td><td>25.6</td><td>40.6</td><td>10.3</td></tr><tr><td>South Lebanon/Nabatieh</td><td>26.9</td><td>25.1</td><td>37.8</td><td>11.9</td></tr><tr><td>North Lebanon/Akkar</td><td>28.6</td><td>22.0</td><td>33.7</td><td>12.5</td></tr><tr><td>Sig.</td><td colspan="2">0.088</td><td colspan="2">&lt;0.001</td></tr><tr><td><strong>Educational Level</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Uneducated</td><td>14.9</td><td>24.0</td><td>33.9</td><td>16.2</td></tr><tr><td>Elementary/Primary school or equivalent</td><td>20.9</td><td>25.0</td><td>39.2</td><td>12.9</td></tr><tr><td>High school diploma or equivalent</td><td>26.3</td><td>22.9</td><td>38.5</td><td>11.5</td></tr><tr><td>Bachelor's degree</td><td>32.2</td><td>25.7</td><td>39.2</td><td>12.5</td></tr><tr><td>Master's degree</td><td>33.9</td><td>23.4</td><td>38.4</td><td>11.6</td></tr><tr><td>Doctorate degree</td><td>35.9</td><td>25.8</td><td>41.7</td><td>13.2</td></tr><tr><td>Sig.</td><td colspan="2">&lt;0.001</td><td colspan="2">0.262</td></tr><tr><td><strong>Age</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>18-24</td><td>32.1</td><td>25.9</td><td>39.3</td><td>12.1</td></tr><tr><td>25-34</td><td>29.0</td><td>24.1</td><td>39.0</td><td>13.0</td></tr><tr><td>35-44</td><td>25.4</td><td>24.6</td><td>39.9</td><td>14.4</td></tr><tr><td>45-54</td><td>31.4</td><td>23.8</td><td>36.5</td><td>10.7</td></tr><tr><td>55-64</td><td>25.0</td><td>24.0</td><td>39.5</td><td>12.3</td></tr><tr><td>65 and above</td><td>27.3</td><td>20.6</td><td>37.3</td><td>13.6</td></tr><tr><td>Sig.</td><td colspan="2">0.052</td><td colspan="2">0.245</td></tr><tr><td><strong>Major of study</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Health-related</td><td>32.1</td><td>25.9</td><td>38.8</td><td>10.8</td></tr><tr><td>Non-health related</td><td>29.0</td><td>24.1</td><td>39.4</td><td>11.9</td></tr><tr><td>Sig.</td><td colspan="2">&lt;0.001</td><td colspan="2">0.571</td></tr><tr><td><strong>Area of residence</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>City</td><td>30.5</td><td>24.7</td><td>39.1</td><td>12.4</td></tr><tr><td>Town</td><td>32.0</td><td>26.2</td><td>39.6</td><td>10.4</td></tr><tr><td>Village</td><td>26.5</td><td>25.1</td><td>37.0</td><td>14.6</td></tr><tr><td>Sig.</td><td colspan="2">0.151</td><td colspan="2">0.166</td></tr><tr><td><strong>Working status</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Unemployed/Retired</td><td>26.4</td><td>22.6</td><td>37.3</td><td>11.9</td></tr><tr><td>Student</td><td>31.9</td><td>26.3</td><td>39.3</td><td>12.1</td></tr><tr><td>Employed/Self-employed</td><td>30.2</td><td>24.3</td><td>39.3</td><td>13.1</td></tr><tr><td>Sig.</td><td colspan="2">0.027</td><td colspan="2">0.136</td></tr><tr><td><strong>Field of work</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Health-related</td><td>34.1</td><td>26.5</td><td>40.1</td><td>13.0</td></tr><tr><td>Non-health related</td><td>31.6</td><td>23.0</td><td>39.6</td><td>12.5</td></tr><tr><td>Sig.</td><td colspan="2">0.58</td><td colspan="2">0.848</td></tr></tbody></table>
<figure><img src="image_25.png" /></figure>

participants scored lower on attitudes and percep-
tions, which could indicate limited exposure to
structured learning environments where such topics
are discussed, underscoring the importance of acces-
sible educational outreach. It is worth highlighting
that 25.3% and 52.1% of the participants stated their
willingness to eat GMFs before and after the educa-
tional intervention, respectively. This shows the
importance of education in changing the percep-
tions of the public to GMFs, and subsequently
their acceptability toward GMF purchasing and
consumption.

Strengths of our study include a comprehensive
50-item questionnaire adapted to the Lebanese
context, ensuring relevance and accuracy, and
bilingually translated and pilot tested, enhancing
the clarity and validity of responses. Additionally,
while a notable portion of participants who were
initially approached dropped out of the study, our
sample of 1,001 participants from various Lebanese
governorates is still considered representative,
increasing the generalizability of the findings
across the Lebanese population. Furthermore, the
inclusion of a structured educational session
allowed the study to assess the impact of education
on participants' knowledge, attitudes, and percep-
tions of GMF, providing valuable insights into the
effectiveness of information dissemination. By
evaluating participants' responses before and after
the educational component, the study effectively
measured changes in understanding and attitudes,
highlighting areas where knowledge gaps were
bridged. Finally, this study addresses a gap in
GMF research within the Arab region, specifically
Lebanon, where such information is limited. It
would be interesting to explore in the future the
sources of information on GMFs and the factors
that influence individuals' perceptions and atti-
tudes, such as media exposure, ethical concerns,
and cultural beliefs, as these could provide addi-
tional context for our findings.

4. Conclusion

This study, the first-of-its-kind in Lebanon,
assesses knowledge, attitudes, and perceptions
regarding GMFs, shedding light on critical socio-
demographic disparities. Our findings demonstrate

that tailored educational interventions can signifi-
cantly improve knowledge and positively influence
attitudes toward GMFs, particularly among groups
with initially lower knowledge level, such as older
individuals, those without graduate studies, and
people with non-health-related educational back-
grounds. These results emphasize the importance
of targeted educational initiatives to bridge knowl-
edge gaps and address misconceptions about
GMFs. The implications of this study extend
beyond Lebanon, providing valuable insights for
other countries, particularly those in similar socio-
economic and cultural contexts. Nations with
diverse demographic profiles or limited public
understanding of GMFs can adopt similar educa-
tional strategies to enhance awareness and promote
evidence-based perspectives. By addressing socio-
demographic factors that influence knowledge and
attitudes, policymakers and educators can design
more inclusive and effective programs tailored to
their populations. Ultimately, this study under-
scores the transformative potential of education
in fostering informed decision-making about
GMFs, contributing to better public health policies
and informed consumer choices. Further research
is recommended to explore long-term retention of
knowledge and to evaluate the effectiveness of edu-
cational interventions across different regions and
cultural settings.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Funding

The author(s) reported there is no funding associated with the work featured in this article.

ORCID

José-Noel Ibrahim http://orcid.org/0000-0002-3507-0119

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