INTEGRATED HUMAN PRACTICES
A major caveat in synthetic biology applications is their acceptance by society. This aspect is related to the perimeter of ethical rules and a widely spread social skepticism about genetically modified organisms (GMOs). This dramatically limits the conception and implementation of synthetic biology-based applications, especially therapeutic approaches. It is thus important to understand the reasons for social rejection against GMOs to take these concerns into account in the development of new applications. To address this problem, we decided to build a survey. We wanted to reach people our age, with different levels of education. We wanted to produce a survey with our knowledge, to know the thoughts of the population on the various subjects that are addressed in our project, i.e., GMOs, viruses, and cancer in particular. In science, it is necessary to study what the population is thinking to be able to use new therapeutic tools in the future to treat cancer. What we mean is that for several years now, therapeutic GMOs have often been judged poorly by the population, and during this period of COVID-19 it is difficult to use the word virus without people thinking it may be harmful. Our questionnaire was infused with expert psychological design with the help of Florence COUSSON GELIE. She specializes in psychological health and has a long-standing experience with this kind of survey. For instance, she explained to us that it is very important to avoid biases as much as possible. As an example, it was preferable to make a questionnaire in France to limit all the possible biases that we can find in the different laws, the different thoughts, and that the lack of answers could also be a bias. We tried to put more emphasis on the students because they are the ones who will be concerned about our project in the future. Questions were meant to assess the knowledge about synthetic biology (GMOs and phages) and the trust/fear of synthetic biology approaches to cure cancer. Other questions addressed the subjective susceptibility to cancer, survival expectations, or the impact of cancer treatments on the quality of life.
Results of the survey
In total, we had 145 responses to our survey, with which we were able to interpret the results. The first thing we can say is that in these 145 subjects we had only students, with a level of study between baccalaureate and baccalaureate + 6 more years of study or more. Here in France, this means between the first year at university and the first year of a Ph.D.
We tried to find out if this population knows about the 4 main subjects of our project Phagent: GMO, Cancer, Microbiome, and Phages. Among this population, 98% of people had heard of GMOs. To check if they knew what a GMO was, we asked them the question: "What do you think a GMO is?" In these results, we observed that 4% did not know what a GMO was, 0.5% said that could be an organ, 1% replied that they did not know, and 2% said that it was chemical (dangerous for health or in our food) or biochemical as a preservative. When we checked the results in more detail, the 2% of people who have never heard of GMOs knew what a GMO was, we can deduce that these 2% knew what a GMO is, but that 4% may have heard about GMOs in the wrong way. The positive thing about these results is that 96% of the subjects knew what a GMO was: a genetically modified organism.
For the next questions, we asked them about the microbiome and almost 90% knew about it, but out of them, only 30% knew about tumor microbiomes, with 45% considering there may be specific bacteria in tumors.
And we also asked if they know about phages, and almost 53% knew about phages, more than half of our subjects. For cancer, we didn’t ask a specific question about that, because we made a hypothesis that everyone between Bac to Bac+6 knows about cancer. Now we know that at least 1/3 of the population knows about the four main subjects of our project. With those answers, we wanted to know if the education level has a link with those pieces of knowledge. For all the questions that we had, we assigned a score to each answer. For example, we gave a score from 0 to 4 for answers like “I don’t know”, “no”, “probably no”, “probably yes”, and “yes”, or a score of 0 or 1 for “no” or “yes”. Converting answers to scores helped us treat our data quantitatively and estimate if our answers are correlated. To visualize more easily the distribution of the answers, we added a tiny random fraction. This way identical answers can be visualized as clusters instead of identical values (see figure 6 for instance). Thus our scores ranged from -0.1 to 0.1, 0.9 to 1.1, 1.9 to 2.1, and so on. We then conducted Spearman tests to assess correlation.
We first looked at the relationship between the knowledge about phages and education level.
As we can see in this figure, most subjects say that they know or probably know about phages, and for every education level, we can’t see a correlation between those two variables. We also tried to see if there was any correlation between education level and their opinion about the chances of survival in cancer.
There is still no obvious correlation between those variables, they mostly think there is an average chance of survival in cancer. The data suggest that education level does not affect knowledge about cancer or phages. Many things could explain this, such as media consumption or different specialties of study. We did not ask which specialty they are studying; this may be another bias in our study. Future studies should add this question and study how this parameter influences the answers. The goal of this survey was to see if the population would accept our project in the future and if they would be amenable to use our product. For this, we formulated a question to measure the level of “acceptance” to our project: “What is your opinion about treating cancer with a virus that only infects bacteria present in the tumor?” Most answers ranged from “neutral” to “positive” opinion. We wanted to understand which factors could impact this acceptance level. First, we tried to correlate the phage-based therapy (our project), with the acceptance of GMO-based treatments.
With the Spearman test, we obtained a correlation between the positive expectation of page-based therapy and the high level of acceptance towards GMO-based treatments. (Spearman r = 0.3388) We can say the more people are ready to take GMO-based treatments in general, the better they would accept a phage-based treatment. This is expected since Phagent is a specific GMO. Likewise, the acceptance for Phagent correlates with a good awareness of phages, with a Spearman test r =0.3112.
We can say that the more people know about phages and GMOs, the greater chance that they would accept our project. Due to the limited number of subjects being surveyed, correlation does not imply that there is a causality effect. However, it still suggests that education could favor acceptance. This a great encouragement as part of our iGEM outreach included numerous educational projects specifically. It also means that in the future we could continue our mini-series about GMOs, and also add this season in the educational book that we made, and try to raise awareness about GMOs and phages. This could help us to manage the acceptance of our project, but also to help educate the population about other neglected aspects of science in general. On the other hand, acceptance of phage-based therapy does not correlate with estimates of cancer survival rates (Spearman r = 0.01054), as we can see in figure 8.
The subject of cancer is more complicated, we didn’t find a correlation between it and our project, so we need to try another way to approach it. It is interesting because like this we can say that our project could be a new treatment and that the population doesn’t think that could be a problem in cancer survival rate. We also tried to see if there was a correlation between phage-based therapy and how they see the impact of cancer treatment, but any correlation was seen. Those could help us to understand the advantage of a new treatment on patient life, and probably try to improve the acceptance of our project by insisting on those advantages. Finally, to obtain more insights into the mechanisms of fear towards GMO-based treatments, we asked an open question: “What would be your concerns if you were offered a GMO-based treatment?” Figure 9 is a word cloud generated from the answers to this question. The notions that pop up are potential long-term side effects, the fact that the technology is too recent, and there is a lack of knowledge. If we now group the answers, we find that around 14% of people are not or slightly concerned about GMO treatments. But 22% fear potential side effects, and 25% are concerned about the lack of knowledge on these new therapies. Additionally, 26% are afraid of harmful effects (toxicity, genome perturbations, worsening of the disease, and even death).
Conclusions of the survey
This survey helped us to survey current opinions on the technology that powers our project to best navigate its public acceptance. The data suggest that education about phages and GMOs could help this acceptance. However, the methodology of our questionnaire still has avenues for improvement. In principle, this survey could have been done in two steps: a qualitative and a quantitative part. The qualitative part would consist of organizing working groups and debates on the subjects that we want to survey so here: phages, GMOs, cancer, and microbiomes. These discussions would highlight critical questions to ask in the quantitative survey to effectively measure the level of acceptance and other parameters that may be related. But due to the lack of time and the difficulty to hold in-person working groups and debates, we opted to focus solely on the quantitative part. Next year, based on the insights we have obtained, we will augment our survey to include both a qualitative and quantitative part. With the help of those answers, we will further fine-tune a strategy to interact with the public to foster acceptance through education.