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
5
Introduce a case (please select one among the ones presented in the IRECs module on the topic of the session). Ask participants to identify the main ethical issues in the case (the aim to increase awareness of the issues related with the topic introduced in the session). You can use the following question to encourage conversation among participants:
- What are the main ethical issues in this case?
'''<u><span lang="EN-US">Trainer Tip</span></u>''' <span lang="EN-US">Allow for a brief open discussion but keep it focused to ensure you stay within the allocated time.</span> +
Start a dialogue about trainees' personal experiences with biobanking as citizens, allowing them to reflect on ethical issues from a citizen's perspective.
Divide the group in subgroups and invite them to reflect for 10-15 minutes on the following questions (projected on a slide):
*What is your own experience with biobanking as a citizen?
*Have you ever donated blood cells or anything else?
*Do you know what they do with your samples and personal information?
*What would be important to you in terms of privacy, storage and use of data and material – if it was your saliva, urine or blood sample?
Summarize with a plenary wrap-up, inviting trainees to share the key points of their discussions. Building on the previous exercise, continue adding ethical issues to the digital board, including any new ones brought up during the wrap-up. You can ask the trainees: "''What can you conclude based on the last issues we added to the mind map?''" +
Participants are invited to engage in a conversation about the presented case. Playing the role of experts, they are invited to have a dialogue and learn from each other's perspectives. The aim is to formulate advice for the executive board. The following questions can support reflection and stimulate dialogue. These are questions that each expert might ask from their own specific perspective:
<div>
<div>
'''Healthcare professional'''
*How will HealthAI affect your day-to-day work?
*<span lang="EN-US">How will HealthAI affect your relationship with the patient?</span>
*<span lang="EN-US">Do you have concerns about informed consent? According to HealthAI, all patient data will be used for this AI system.</span>
*Are there any conditions / what is needed to implement Health AI? ''' '''
'''<span lang="EN-US">Representative of HealthAI</span>'''
</div><div>
*<span lang="EN-US">Who takes care of responsibilities when errors have been made?</span>
*A comment to bring to the table: The system prevents a lot of human errors.
'''Representative of patient rights advocacy'''
</div><div>
*<span lang="EN-US">How to ensure that patients have a good understanding of how HealthAI will handle their data?</span>
*<span lang="EN-US">May patients refuse or give preference to another treatment suggested by HealthAI?</span>
*<span lang="EN-US">Can data security be fully guaranteed?</span>
'''Medical ethicist'''
</div><div>
*<span lang="EN-US">From early experience with AI systems, we have seen that the AI system can hallucinate and that biases (e.g. against certain patient groups) can be built into the algorithm. To what extent are these assumptions corrected in the system or by a healthcare professional?</span>
*<span lang="EN-US">What ethical dilemmas or concerns could you foresee? How can we deal with them?</span>
'''<span lang="EN-US">Representative of Human Resources of the hospital</span>'''
</div><div>
*<span lang="EN-US">What kind of expertise do we need to have in our hospital to successfully implement HealthAI? Do we need to recruit new employees, or what training should be organized by whom?</span>
*What kind of impact may it have on the reputation of the hospital?
'''Representative of a health insurance company'''
</div><div>
*<span lang="EN-US">How will this affect health insurance? Should we offer different types of insurance?</span>
*<span lang="EN-US">If a cheaper and perhaps better AI system for health care becomes available outside our nation, can we recommend it and put it into practice?</span>
</div></div>
Participants are invited to engage in a conversation about the presented case. Playing the role of experts, they are invited to have a dialogue and learn from each other's perspectives. The aim is to formulate advice for the executive board. The following questions can support reflection and stimulate dialogue. These are questions that each expert might ask from their own specific perspective:<div><div>
'''Healthcare professional'''
*How will HealthAI affect your day-to-day work?
*<span lang="EN-US">How will HealthAI affect your relationship with the patient?</span>
*<span lang="EN-US">Do you have concerns about informed consent? According to HealthAI, all patient data will be used for this AI system.</span>
*Are there any conditions / what is needed to implement Health AI? ''' '''
'''<span lang="EN-US">Representative of HealthAI</span>'''
</div><div>
*<span lang="EN-US">Who takes care of responsibilities when errors have been made?</span>
*A comment to bring to the table: The system prevents a lot of human errors.
'''Representative of patient rights advocacy'''
</div><div>
*<span lang="EN-US">How to ensure that patients have a good understanding of how HealthAI will handle their data?</span>
*<span lang="EN-US">May patients refuse or give preference to another treatment suggested by HealthAI?</span>
*<span lang="EN-US">Can data security be fully guaranteed?</span>
'''Medical ethicist'''
</div><div>
*<span lang="EN-US">From early experience with AI systems, we have seen that the AI system can hallucinate and that biases (e.g. against certain patient groups) can be built into the algorithm. To what extent are these assumptions corrected in the system or by a healthcare professional?</span>
*<span lang="EN-US">What ethical dilemmas or concerns could you foresee? How can we deal with them?</span>
'''<span lang="EN-US">Representative of Human Resources of the hospital</span>'''
</div><div>
*<span lang="EN-US">What kind of expertise do we need to have in our hospital to successfully implement HealthAI? Do we need to recruit new employees, or what training should be organized by whom?</span>
*What kind of impact may it have on the reputation of the hospital?
'''Representative of a health insurance company'''
</div><div>
*<span lang="EN-US">How will this affect health insurance? Should we offer different types of insurance?</span>
*<span lang="EN-US">If a cheaper and perhaps better AI system for health care becomes available outside our nation, can we recommend it and put it into practice?</span>
</div></div>
[[File:Data.png|center|frameless|600x600px]]
Researchers access biobanks’ collections of samples to conduct a wide range of studies, including genetic research, biomarker discovery, disease modelling, and the development of personalized medicine approaches. The diversity of biological samples allows for comprehensive investigations into the complexities of human health and diseases.
In addition to collecting biospecimens from donors, biobanks also collect a wide variety of health-related data. The types of data collected and stored may be categorized into 4 main categories.
Drag and drop the types of health-related data that may be collected by biobanks into the relevant column. It's important to note that the specific data collected can vary depending on the focus and objectives of the biobank. The contextual information provided by clinical, demographic, and lifestyle data enhances the scientific utility of biospecimens. Researchers can correlate genetic details with health histories, enabling insights into disease mechanisms, personalized treatments, and biomarker discovery. Longitudinal data aids in tracking disease progression, contributing to better prognostics. Collecting comprehensive data alongside biospecimens ensures the quality, relevance, and ethical use of stored samples, fostering advancements in precision medicine and therapeutic development. +
[[File:Yes or no buttons.jpg|alt=yes or no buttons|center|frameless|600x600px|yes or no buttons]]
Read the following opinions, decide who you most agree with, and then move to the next page to see what the Declaration of Helsinki has to say.
==Case Study Review==
Read the following opinions, decide who you most agree with, and then move to the next step to see what the Declaration of Helsinki has to say.
{| class="wikitable"
|[[File:Irecs 1.png|link=Special:FilePath/Irecs_1.png]]
|'''Sonia'''
This study provides very high-quality evidence for the efficacy of ipilimumab. The findings have the potential to benefit many patients. All the participants knew what was involved and consented to participate. Hence the study is ethical.
|-
|[[File:Irecs 2.png|link=Special:FilePath/Irecs_2.png]]
|'''David'''
This study is unethical because the control group should not have been given placebo. Why wasn’t the new drug compared with an existing treatment like interferon alpha? Those in the placebo group effectively went without treatment for three years.
|-
|[[File:Irecs 3.png|link=Special:FilePath/Irecs_3.png]]
|'''Beth'''
There are times when, even though there is an existing treatment available, it is ethically permissible to test new treatments against a placebo because this gives a more realistic idea of the effect size and is more useful in the long run.
|} +
To develop and improve methods of gene editing, both germline and somatic, research on human embryos is currently necessary, although it may be possible in the future through generating germ cells in vitro. Research with human embryos raises moral objections for many, not least because the embryos will be destroyed when used for research.
Some countries have enacted outright bans on certain types of embryo research, such as research involving the creation of embryos solely for research purposes or research aimed at modifying the human germline. Consensus does not exist regarding the moral status of an embryo, and many people oppose research on embryos categorically.
Regulations for embryo research often impose limits on the duration embryos can be cultured for research purposes. For example, some jurisdictions allow research only on embryos up to 14 days old, as this is when the primitive streak (an early stage of nervous system development) typically forms. However, an extension of the 14-day rule for embryo research (which is legally binding in some countries) has been under discussion for many years. The International Society for Stem Cell Research (ISSCR) relaxed its guideline on this limit in 2021.
Therein, it is suggested that studies proposing to grow human embryos beyond the two-week mark be considered on a case-by-case basis, involving institutional or national bodies as well as extensive public engagement. Allowing embryos to grow past 14 days might improve understanding of human development and many health-related questions, for example, why many pregnancies fail. +
[[File:Ex-tech6.png|center|frameless|600x600px]]
The hardware needed for VR and AR experiences, can vary depending on the complexity of the application and the level of immersion desired.
Click on the hotspots on the image below to find out more about the types of hardware used for VR. +
[[File:Bio2Image5.png|center|frameless|600x600px]]
Use the links below to access and read the UK Biobank’s information sheet and consent form.
[https://www.ukbiobank.ac.uk/media/ei3bagfb/participant_information_leaflet-baseline.pdf Example of a biobank information sheet from the UK Biobank]
[https://www.ukbiobank.ac.uk/media/t22hbo35/consent-form.pdf Example of a biobank consent form from the UK Biobank]
'''Feedback'''
Broad consent models are commonly used by biobanks to streamline sample collection for diverse research purposes. These models allow participants to consent to a wide range of potential future studies, facilitating efficient research while maintaining ethical standards. However, ensuring transparency and understanding among participants regarding the scope of research remains paramount for ethical practice.
What type of consent model is UK Biobank using in these examples? +
Ever wondered about the ethical compass guiding scientific discovery? This video highlights the long history of teaching and learning, tracing it all the way back to Plato's Academy. While the specific subjects taught have evolved over time, the underlying ethical questions remain relevant. Ethics in research is not merely about compliance but also about moral reflection. Drawing on real-world examples, our training module aims to provide guidance and support for researchers in navigating ethical considerations. +
[[File:Ext.Image6.png|center|frameless|600x600px]]
The use of XR also poses risks to mental health and wellbeing, inducing new problems and/or exacerbating existing concerns. Psychological impacts, including addiction and the need for a resting period after extended XR use, underscore the mental health dimensions associated with immersive technologies. However, it must be stressed that many of the alleged risks to mental health and wellbeing are currently tentative. Being a fairly new field of application and research, the evidence for harms and benefits is relatively scant.
Consequently, it is difficult to predict who precisely is at risk of harm, in what circumstances, and how this is best addressed. Nevertheless, adherence to the precautionary principle would entail that proactive measures to prevent harm are taken, even in the absence of conclusive scientific evidence. Click on the images to read more about some of the primary concerns for mental health and wellbeing that have been identified to date.
From a psychological perspective, there is ongoing debate about the welfare of children using immersive technologies. Children are identified as a highly vulnerable group and, as this module shows, there are many potential harms. Additionally, the long-term impacts upon psychological and emotional development are unknown. They necessitate careful examination to ensure the healthy growth and development of young XR users. +
<span lang="EN-GB">Given the already determined elements, the outputs of a baseline scenario should be elaborated, i.e. the practical outputs to be achieved if the identified stakeholders work effectively together, by use of the identified intervention points, towards the joint achievement of the set objectives under the given circumstances. These tangible outputs can include concrete products, such as educational materials or communication events, but also cover less material accomplishments, such as increased information exchange or a mutual learning process. </span>
<span lang="EN-GB">The scenario-building methodology uses design thinking to develop fresh ideas and an out-of-the-box perspective: You can start to think of a worst-case or a best-case scenario to trigger your creativity and vision. Our instruction uses the most feasible scenario as a starting point, i.e. a realistic plan to achieve, considering the crucial key variables. This initial brainstorming on the most strategic options for a scenario supports further idea generation towards a best-case and worst-case scenario. The best-case should deliberately go beyond what is really under the current conditions and aim to define outputs that are to be achieved in the future when the present assumptions and underlying enabling factors favourably change. The worst-case should serve as a reminder what could happen, if no action is taken or the well-intended initiatives to enhance trust in science are not properly planned or encounter insurmountable structural or organisational barriers.</span>
<span lang="EN-GB">· Most feasible scenario: What are the outputs to be realistically achieved given the current enabling and hindering conditions? </span>
<span lang="EN-GB">· Best-case scenario: What are the results to be ultimately aimed for when all the circumstances are ideal to apply the recommendation? </span>
<span lang="EN-GB">· Worst-case scenario: What can happen in case, e.g. the recommendation is applied to an inadequate context, stakeholders are not well-informed or well-addressed, no action can be taken, or the implementation is inadequately planned?</span>
Vulnerabilities increase during pandemics. Where possible, research approaches should be adapted to ensure the ethical inclusion of persons in vulnerable situations – with adequate protections – rather than adopting patronizing or convenience exclusions. +
Doing research with communities affected by climate change: Climate-conscious methodologies matrix (for students and citizen scientists) +
Use you own research to '''reflect on the cards''' questions
OR use the scenario described above to:
*'''Reflect''' on how the question applies in this setting.
*'''Identify''' possible tensions or risks (e.g., exclusion, harm, extractivism).
*'''Propose''' a climate-just, community-informed course of action. +
The purpose of the third exercise is for participants to easily gain an overall understanding of the differences between the two types of innovation by answering 10 True or False questions. +
In this lecture, Panagiotis Kavouras addresses the researcher's responsibility for the quality of data collection, processing, and storage. The first segment outlines the principles of responsibility and research quality. Subsequently, the lecture elaborates on the research cycle and highlights best practices critical to maintaining high standards in research.
'''Watch the lecture and then answer the questions.'''
'''Further reading:'''
Center for Open Science. “What is open science?” https://www.cos.io/open-science
Hofmann, B. (2022). Open Science Knowledge Production: Addressing Epistemological Challenges and Ethical Implications. Publications, 10(3), Article 3. https://doi.org/10.3390/publications10030024
Nosek, B. A., Hardwicke, T. E., Moshontz, H., Allard, A., Corker, K. S., Dreber, A., Fidler, F., Hilgard, J., Struhl, M. K., Nuijten, M. B., Rohrer, J. M., Romero, F., Scheel, A. M., Scherer, L. D., Schönbrodt, F. D., & Vazire, S. (2022). Replicability, Robustness, and Reproducibility in Psychological Science. Annual Review of Psychology, 73(Volume 73, 2022), 719–748. https://doi.org/10.1146/annurev-psych-020821-114157 +
Designed for researchers, publishers, and funders, these specialised courses deliver both theoretical knowledge and practical tools to enhance reproducible research practices.
Our comprehensive training program explores the core principles, methodologies, and discipline-specific challenges of research reproducibility, providing actionable strategies that participants can implement in their work.
Currently, three specialised modules are available online:
*Reproducibility primer for publishers
*Reproducibility primer for funders
*Reproducibility primer for qualitative research
*Reproducibility primer for AI-driven research
Additional modules covering epistemic diversity studies, tools and best practices, and more will be released soon to complete our training program.
Getting started is simple:
#Create a [https://openplato.eu/login/index.php free account] on the OpenPlato platform
#Enrol in either the comprehensive [https://openplato.eu/course/view.php?id=543 TIER2 Reproducibility Training Course] or individual modules based on your interests
#Learn at your own pace with the interactive content +
Doing research with communities affected by climate change: Climate-conscious methodologies matrix (for researchers and ethics reviewers) +
Use you own research to '''reflect on the cards''' questions
OR use the scenario described above to:
*'''Reflect''' on how the question applies in this setting.
*'''Identify''' possible tensions or risks (e.g., exclusion, harm, extractivism).
*'''Propose''' a climate-just, community-informed course of action. +
Introduction to the evaluation of the effectiveness of Research Ethics and Integrity (REI) training +
The table below outlines all the tools and provides evaluations of their functionality, feasibility, scale, term of effect as well as the potential impact of AI for their use. It is important to consider whether the measurement is vulnerable to unintended/undesirable use of AI especially in those cases when authentic learning tasks are utilised as indicators of training effect. There may also be cases in which AI use is neutral or even recommended along with instructions to learners to be mindful of the challenges with AI-created content and using any such content critically.
The table includes an assessment of appropriate level of training effectiveness (according to Praslova 2010/Kirkpatrick 1959), functionality, suggested instruments of analysis, feasibility, temporal dimension and potential manipulativeness by AI.
[[File:Tab1.png|center|frameless|500x500px]]
[[File:Tab2.png|center|frameless|500x500px]]
[[File:Tab3.png|center|frameless|500x500px]]
[[File:Tab4.png|center|frameless|500x500px]]
Measuring training effectiveness has two components: the tool to collect learning outputs (preferably one that also has a pedagogical function) and an instrument to analyse the collected information. We will start with analysis instruments as they can be used for analysis collected with different tools. +
Statistic is an easy measure for counting answers and identified topics. Learning analytics tools (especially those designed into an application) usually calculate the averages and divisions of responses and display them in graphs. Statistics tools like MS Excel, Google sheets or even SPSS (not to mention R) could be used to analyse the collected numerical data.
For example, ProLearning app creates ratios of students’ and teacher’s answers (figure 6):
[[File:Img13.png|center|frameless|350x350px]]
Figure 6. Students’ and teacher’s answers to the same question asked in 6 training sessions.
It is possible to count the answers given by learners (figure 7):
[[File:Img14.png|center|frameless|500x500px]]
Figure 7. Responses to various ethical analysis steps.
Even group dynamics can be displayed by counting the turn-taking of learners (as done by CoTrack app) (figure 8):
[[File:Img15.png|center|frameless|500x500px]]
Figure 8. Turn-taking of four learners (right) and the corresponding group dynamics display (left) (from Tammeleht et al., 2022).
In addition, the learning process can be displayed on a graph to illustrate the development of understanding (SOLO levels 0-4) (figure 9):
[[File:Img16.png|center|frameless|400x400px]]
Figure 9. Development of 5 topics during 4 group-tasks and an oral presentation. Section +
