Text (Instruction Step Text)
From The Embassy of Good Science
Describe the actions the user should take to experience the material (including preparation and follow up if any). Write in an active way.
- ⧼SA Foundation Data Type⧽: Text
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During the session, participants analyse a case using role play. In subgroups (up to 6 participants in each group) they each impersonate a member of an expert group who has been formed by the executive board of a prestigious institution to examine a difficult case and provide advice. <div>
Every participant plays one of following roles: Healthcare professional (physician); R<span lang="EN-US">epresentative of “HealthAI”;</span> <span lang="EN-US">Patient rights advocacy</span>; <span lang="EN-US">Medical ethicist;</span> <span lang="EN-US">Representative of human resources of the hospital</span><span lang="EN-US">;</span> <span lang="EN-US">Representative of a health insurance company</span>.
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The experts are invited to have a dialogue and to learn more from each other’s perspectives. The aim is to formulate an advice for the executive board.
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Before starting the exercise, it can be useful to emphasize that the groups are invited to engage in [https://embassy.science/wiki-wiki/index.php/Theme:6217d06b-c907-4b09-af4e-b4c8a17b9847 dialogue] rather than debate.
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To encourage the dialogue a list of questions has been prepared (see step 5).
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<span lang="EN-US">The aim of this activity is to invite participants to '''reflect''' on their '''expectations'''. This is useful both for trainers and participants.</span>
<span lang="EN-US">'''Trainers can pick between two possible activities:'''</span>
<span lang="EN-US">'''OPTION 1:'''</span>
<span lang="EN-US">''Mind map activity → small group activity: in sub-groups participants create a mind map of their current knowledge on the topic.''</span>
<span lang="EN-US">The following steps can support trainers in organizing this activity:</span>
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*<span lang="EN-US">Divide participants into subgroups.</span>
*<span lang="EN-US">Provide each group with a digital (or physical) board.</span>
*<span lang="EN-US">Ask them to brainstorm and write down the words that come to mind when they think of "gene editing."</span>
*<span lang="EN-US">Ask them to divide the terms into:</span>
-Topics they want to learn more about.
<span lang="EN-US">-Topics they are already familiar with.</span>
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*<span lang="EN-US">After 6-7 minutes of discussion in sub-groups, ask all groups share their maps with the group. Together with the group select the most common unknown topics.</span>
<span lang="EN-US">'''OPTION 2:'''</span>
<span lang="EN-US">''Learning goals with Mentimeter''</span> <div>
*<span lang="EN-US">Prepare and share a Mentimeter (or similar tool) with the following question: ''after this session I expect to be able to…''</span>
*<span lang="EN-US">Ask participants to submit two goals, project the results and discuss them with the group.</span>
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<span lang="EN-US">Trainers should develop specific learning goals for their session.</span> The learning objectives for these sessions should align with those of the e-learning modules. General expected outcomes at the end of these sessions include the following:
*Participants should be knowledgeable on relevant literature, developments and regulations with regards to the topic addressed
*They should be able to indicate what ethical issues are pressing regarding research concerning specific technologies
*They should be able to apply relevant ethical concerns on realistic cases
*<span lang="EN-US">They should be aware how learning materials are relevant for their professional/academic context</span> +
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*Start explaining the topic in a short way. You can help yourself with a slide, but this is not necessary. An example of the content you can use as an introduction is below:
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''Gene editing is a transformative and evolving technology that has great potential for addressing problems in healthcare, agriculture, among other areas. However, it also raises critical ethical questions since it can have severe and long-term societal and environmental consequences. Since the CRISPR-Cas9 became a reality, many debates about human enhancement and justice issues regarding access to the technology have surrounded gene editing.''
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''This training session is designed to equip participants with the knowledge and tools to navigate the complex ethical issues that arise from gene editing. By exploring and discussing real cases, participants will develop a deeper understanding of the challenges and responsibilities associated with gene editing.''
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<u>Trainer Tip</u>: Use this moment to create a welcoming and open environment, emphasizing that the session wants to encourage ethical reflection in an open and safe space.
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To assess trainees' current knowledge of ethical issues in biobanking practices, have them create a mind map. This can be done individually, in pairs, or in larger subgroups.
'''Assignment''': Write ''biobanking'' and ''ethical issues'' in the middle of a piece of paper and spend 5 minutes writing down associated words that come to mind. Use keywords to label overarching concepts and draw connecting lines to illustrate relations.<div>
Discuss in plenary the content of the mind maps. You can initiate a conversation among participants by asking: ''What surprises you if you look at other mind maps? Does anything you see raise questions for you?''
<u>Trainer tip</u>: Encourage trainees to add words to the mind map during the training session.
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<span lang="EN-US">The aim of this activity is to invite participants to '''reflect''' on their '''expectations'''. This is useful both for trainers and participants.</span>
<span lang="EN-US">'''Trainers can pick between two possible activities:'''</span>
<span lang="EN-US">'''OPTION 1:'''</span>
<span lang="EN-US">''Mind map activity → small group activity: in sub-groups participants create a mind map of their current knowledge on the topic.''</span>
<span lang="EN-US">The following steps can support trainers in organizing this activity:</span><div>
*<span lang="EN-US">Divide participants into subgroups.</span>
*<span lang="EN-US">Provide each group with a digital (or physical) board.</span>
*<span lang="EN-US">Ask them to brainstorm and write down the words that come to mind when they think of "gene editing."</span>
*<span lang="EN-US">Ask them to divide the terms into:</span>
-Topics they want to learn more about.
<span lang="EN-US">-Topics they are already familiar with.</span>
</div>
*<span lang="EN-US">After 6-7 minutes of discussion in sub-groups, ask all groups share their maps with the group. Together with the group select the most common unknown topics.</span>
<span lang="EN-US">'''OPTION 2:'''</span>
<span lang="EN-US">''Learning goals with Mentimeter''</span>
<div>
*<span lang="EN-US">Prepare and share a Mentimeter (or similar tool) with the following question: ''after this session I expect to be able to…''</span>
*<span lang="EN-US">Ask participants to submit two goals, project the results and discuss them with the group.</span> </div><div></div> +
This clip explains the basics of benefit sharing, which is an instrument to increase justice in international research and cross-border access to resources. In the context of the UN Convention on Biological Diversity, benefit sharing is contribution-based, i.e. those who contribute to a project or research should benefit from its outcomes. In the context of the UNESCO Universal Declaration on Bioethics and Human Rights, the benefits of research should be shared with all of society, independent of contribution. +
In times of crisis, policy-makers urgently need advice from researchers. Can such advice take ethical values into consideration? [https://prepared-project.eu/ PREPARED] developed an ethics brief format around fairness, respect, care and honesty and launched a first brief with [https://www.nature.com/articles/d41586-023-01014-z NATURE coverage] in April 2023. The PREPARED team met at the UNESCO headquarters in Paris in early June. Watch this annotated video and learn more about bringing ethics into policy making.
Click below to watch the annotated video. +
[[File:Donating Samples.png|center|frameless|600x600px]]
Alison, a 42-year-old woman in robust health, was invited to contribute to scientific advancement by donating biological material along with health-related information (data) to a biobank. Alison explained to her friends and family that she wanted to contribute to medical research ‘to give something back’ after seeing her father’s successful treatment for cancer.
The biobank provided Alison with detailed information about the purpose of the biobank, the types of samples and data needed, risks and potential benefits related to the donation to biobanking and the right to withdraw consent.
Alison then gave her consent to the donation process, acknowledging her understanding and agreement to participate.
Before donating the samples, Alison underwent a thorough screening process which included a review of her medical history and a physical examination.
The samples were carefully labelled, processed, and stored in secure, controlled environments. Storage conditions also comply with stringent ethical and privacy protocols, ensuring the preservation of Alison’s privacy and confidentiality.
Alison was told that her personal information would be de-identified or pseudonymized to protect her identity. As part of the consent process, Alison also gave permission for the biobank to contact her in the future to follow up on her health as she ages and potentially invite her to participate in further studies beyond the scope of her original donation. Maintaining contact with donors is crucial for biobanks when samples are used for longitudinal studies or when follow-up health information is needed.
Alison's donation is now part of a valuable resource for researchers studying various health conditions, including genetic predispositions and disease markers. Her contribution will allow scientists to conduct longitudinal studies, advancing the understanding of health and potential breakthroughs in personalized medicine. Alison's decision exemplifies the vital role individuals can play in shaping the future of medical research through biobank donations.
[[File:Mexican town hall.jpg|alt=mexican town hall|center|frameless|600x600px|mexican town hall]]
What ethics issues can you identify in the cases mentioned in this short video? You can download the text if you wish to help you formulate your thoughts. +
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In November 2018, an international news story broke about a scientist in China who had genetically altered a gene in human embryos that had resulted in the birth of IVF twins, Lulu and Nana. The gene editing involved the use of CRISPR-Cas9 technology to disable the CCR5 gene with the aim that this would lead to HIV resistance. The scientist, He Jiankui, introduced the CRISPR technology very soon after the embryos were created when they were formed of only one cell each. He Jiankui’s actions were widely condemned as unethical, and the news sparked intense debate about the potential impacts upon the children.
How might this genetic modification affect the development, the health and the wellbeing of Lulu and Nana? In the years since their birth there have been many rumours and suggestions about the impacts, including that the twins have enhanced memories and learning abilities, and others that their lives will be shortened. We don’t yet know what attributes can be attributed to the gene editing. +
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VR and AR are used in a very wide range of applications across various industries. +
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What is Hunter syndrome?
Hunter syndrome is a rare genetic disorder that primarily affects males. It is part of a group of diseases known as mucopolysaccharidoses or MPS, which are caused by the body's inability to break down certain complex sugars called glycosaminoglycans or GAGs. For people with Hunter syndrome, a lack of the enzyme iduronate-2-sulfatase or IDS, means that GAGs build up inside the body leading to a wide variety of symptoms including developmental issues, physical problems and mental decline. For example:
*Physical development impacts like coarse facial features, thickened skin, enlarged tongue, and joint stiffness.
*Developmental delays in children affecting motor skills, speech, and learning.
*Respiratory problems with frequent respiratory infections, sleep apnoea, and other breathing difficulties.
*Hearing loss.
*Enlarged liver and spleen, leading to abdominal distension.
*Heart problems with heart valve abnormalities and other cardiac issues.
*Skeletal abnormalities like joint stiffness, short stature, and abnormal bone development.
The onset of the disease is usually between the ages of 2 and 4 years and developmental decline is usually evident between the ages of 18 and 36 months.
There is currently no cure for Hunter syndrome, but treatments can help to manage the symptoms and improve quality of life. Options include:
#Enzyme replacement therapy (ERT). Regular, often weekly, infusions of a synthetic version of the missing enzyme can help reduce the buildup of GAGs. However, the enzyme is not able to pass the blood-brain-barrier, so this form of treatment does not help to protect against brain damage.
*Symptomatic treatments for specific issues including physical therapy for joint problems, medications for respiratory and heart problems, and surgical interventions for specific complications.
Despite treatment, those with severe disease usually die in their teens. Those with a milder form of Hunter syndrome might live with more gradual deterioration in health until middle age.
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'''Issues relating to consent to donate biomaterials and data to biobanks'''
Clear procedures enabling biobank donors to give their informed consent to donate biological materials and health-related information are vital to ensure that they fully understand how their samples and data will be used. Donors should be made aware that biobanks do not routinely provide individual diagnoses, so that they are not falsely reassured when they do not receive results from the analysis of their biospecimens and data. RECs must assess the clarity and comprehensibility of consent forms, addressing any potential risks and benefits.
[https://www.wma.net/policies-post/wma-declaration-of-taipei-on-ethical-considerations-regarding-health-databases-and-biobanks/ The WMA’s Declaration of Taipei] sets out the following criteria for informed consent for multiple and indefinite uses of biomaterials stored in a biobank, stating that consent is only valid if the concerned individuals have been adequately informed about: the purpose of the health database or biobank; the risks and burdens associated with collection, storage and use of data and material; the nature of the data or material to be collected; the procedures for return of results including incidental findings; the rules of access to the health database or biobank; how privacy is protected; the governance arrangements of the biobank;
That if the data and material are made non-identifiable the individual may not be able to know what is done with their data/material and that they will not have the option of withdrawing their consent;
Their fundamental rights and safeguards established in the Declaration; and when applicable, commercial use and benefit sharing, intellectual property issues and the transfer of data or material to other institutions or third countries. +
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Malaria remains one of the leading causes of morbidity and mortality in Sub-Saharan Africa, particularly in rural regions. Despite significant efforts to curb transmission, the disease persists, with complex transmission patterns that vary based on environmental, social, and biological factors. With the recent rise of artificial intelligence (AI) and big data analytics, new tools are now available to understand and predict disease outbreaks more precisely.
'''Principal Investigators'''
Professor Smith (based in the US) and Dr Jones (based in the EU).
'''Aims'''
This project proposes to use AI and machine learning (ML) algorithms to analyse large datasets of malaria transmission in rural regions of Sub-Saharan Africa. Data will be collected on environmental variables, human behaviour, and mosquito population dynamics to build predictive models. The goal is to use AI to identify hotspots of malaria transmission, optimise intervention strategies, and contribute to global malaria eradication efforts.
'''Research Objectives'''
#To develop AI-driven predictive models of malaria transmission in rural regions of Sub-Saharan Africa based on environmental, behavioural, and biological factors.
#To collect and analyse large datasets on malaria incidence, mosquito populations, and environmental variables (e.g., temperature, humidity, rainfall).
#To provide recommendations to international health organisations on optimal malaria intervention strategies based on AI-predicted transmission patterns.
'''Research Questions'''
#How can AI and machine learning be used to predict malaria transmission patterns in rural Sub-Saharan Africa?
#What environmental, social, and biological factors are most strongly correlated with malaria transmission in these regions?
#How can AI models optimise intervention strategies for malaria control in low-resource settings?
'''Methodology'''
This study will employ AI and machine learning techniques to analyse large-scale data on malaria transmission. Data will be collected from remote rural areas in Sub-Saharan Africa, specifically focusing on regions in Tanzania, Uganda, and Mozambique, where malaria prevalence is high.
'''Ethics'''
Ethics approval is being sought from both Professor Smith’s and Dr Jones’ home institutions in the US and in the EU.
'''Phase 1: Data Collection'''
*Environmental Data: Remote sensing and satellite data will be used to gather information on environmental variables such as temperature, rainfall, and vegetation patterns.
*Human Behaviour Data: Survey data on human behaviour related to malaria prevention (e.g., use of bed nets, travel patterns) will be collected through short field visits conducted by external researchers.
*Biological Data: Data on mosquito populations and malaria incidence will be collected through partnerships with local healthcare facilities and mosquito trapping activities.
'''Phase 2: AI Model Development'''
*Machine Learning Algorithms: AI algorithms, including neural networks and decision trees, will be used to analyse the datasets and identify the key factors driving malaria transmission.
*Predictive Modelling: AI models will be trained to predict malaria outbreaks based on the environmental, social, and biological data collected.
'''Phase 3: Reporting and Recommendations'''
*The AI models will be used to provide recommendations for optimising malaria interventions (e.g., bed net distribution, insecticide spraying) in the study regions.
*Results will be published in high-impact international journals and shared with international health organisations.
'''Expected Outcomes'''
#Publication of Results: The research team expects to publish multiple papers in high-impact journals on the application of AI for malaria control, potentially advancing careers in academia and international research.
#Recommendations to International Organisations: AI-driven recommendations on malaria interventions will be shared with global health organisations like the WHO and major NGOs working in malaria control, without direct engagement with local policymakers or healthcare systems.
'''Timeline'''
*Months 1-3: Initial literature review, AI model development, and planning for data collection trips.
*Months 4-9: Data collection in Tanzania, Uganda, and Mozambique.
*Months 10-15: AI model training, data analysis, and predictive model development.
*Months 16-18: Reporting, writing, and submission of research papers.
'''Budget'''
The total estimated budget for this project is $1.2 million, covering:
*Travel expenses for international researchers conducting field visits.
*Equipment for data collection, including satellite imagery access, mosquito traps, and environmental sensors.
*AI development and data analysis software.
*Compensation for local healthcare workers and logistical support in the field.
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Let’s find out more about the proposed study. While working through the presentation, make a note of any points or questions that arise for you about the potential benefits and risks associated with this study. +
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The primary issues related to Extended Reality data processing concern privacy and confidentiality, data security and breaches, the volume of data extracted, and the lack of clarity around the sharing of information.
'''Feedback'''
XR platforms and applications can collect many different types of personal data from users. This includes biometric information (such as facial expressions or eye movements), location data and device identifiers, as well as potentially sensitive content from personal conversations, or confidential information that is shared within virtual environments.
As the technology develops, so new types of data are being processed. For instance, eye tracking technology has the potential to gather highly sensitive data about individuals, including their gaze patterns, attentional focus, and emotional responses. This can be used to reveal personal preferences (including sensitive areas like sexual preferences), and certain health conditions, like autism and attention-deficit/hyperactivity disorder (ADHD). +
<span lang="EN-GB">Define the broader (socio-economic, political) and narrower (institutional) context of the problem to be solved. Consider all background issues that can have a direct or indirect influence on the successful implementation of the recommendation. List general assumptions that you can make about the recommendation, i.e. list all those educated premises that you consider as a starting point for an effective application scenario. These assumptions are the starting points on which further reasoning and development of the scenario can be built. These assumptions can vary in nature and might relate to specific contexts like economics or social interactions.</span>
<span lang="EN-GB">· What is the core problem that needs to be solved to foster trust in science? What are the basic assumptions on which the application scenario can be built on?</span>
<span lang="EN-GB">· What are the socio-economic, political, and cultural aspects that fundamentally shape the implementation of the recommendation?</span>
<span lang="EN-GB">· What are the main organisational or institutional settings that potentially affect the implementation of the recommendation?</span> +
Research coordination and cooperation are essential to avoid the unnecessary duplication of studies, which could place unfair burdens on participants and waste time and resources. +
