(Version 2.2)

This Ethical Review Form should be completed for every research study that involves human participants or personally identifiable personal data and should be submitted to ethics@tue.nl. For more information about how this process works please click here. Please check if you are using the correct form: Ethical Review Form (version 2.2). Please click here to obtain this latest version.

Part 1: General Study Information
1	Project title / Study name	AI chat tool to relieve stress and/or loneliness
2	Name of the researcher / student	Bridget Ariese (1670115), Marie Bellemakers (1739530), Mila van Bokhoven (1754238), Sophie de Swart (2047470), Maarten van der Loo (1639439), Bram van der Heijden (1448137)
3	Email of the researcher / student	b.ariese@student.tue.nl, s.a.m.d.swart@student.tue.nl, m.m.v.bokhoven1@student.tue.nl, m.a.a.bellemakers@student.tue.nl, m.g.a.v.d.loo@student.tue.nl, b.v.d.heijden1@student.tue.nl
4	Supervisor(s) name(s) Additional explanation: Please write down the name of your direct supervisor. You can mention several supervisors if appropriate, but at least one supervisor should be mentioned.	Dr. Ir. Emilia Barakova Dr. Ir. Raymond Cuijpers
5	Supervisor(s) email address(es) Additional explanation: Please give the email address of the supervisor(s) mentioned in question 4.	e.i.barakova@tue.nl r.h.cuijpers@tue.nl
6	Department / Group Additional explanation: Please specify group if relevant e.g. JADS or HTI
7	What is the purpose of this application?	☐ Scientific study ☑ Bachelor education. Course: 0LAUK0 Project robots everywhere ☐ Master education. Course:………………. ☐ Other (e.g. external, following external regulations):…………………………….…
8	Research location Additional explanation: Where will the data collection take place? On campus, in a company, in public space, online, etc.	☑ Eindhoven University of Technology campus ☐ Other, name organization(s):………………… ☐ Public space ☐ Online
9	Start date data collection Additional explanation: Please state when your data collection will start. Please note that you do not have to provide information about your complete (PhD) project, but only on this particular sub-study that you are submitting for approval in this form.	10-03-2025
10	End date data collection	31-03-2025
11	Does your project receive external funding (e.g., NWO, relevant for special regulations from funders)?	☐ Yes. Name Funder: ☑ No
12	Which internal and external parties are involved in the study? Think about sharing data or information between TU/e and other universities, commercial companies, hospitals, etc. Additional explanation: Describe all internal and external parties that are involved in the study or project, including: researchers or research groups at the TU/e who participate in the study; (Researchers at) other universities/institutions that provide data/services, help analyzing the data, etc.;	Internal parties Supervisor: Dr. Ir. Emilia Barakova, Dr. Ir. Raymond Cuijpers

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(commercial) partners, companies, government bodies, municipalities, consultancy firms, hospitals or care institutions that provide data (e.g., contact details of participants, data for further analysis). Indicate which role each party plays: who defines the means and purposes in the study, who will supply the data (external parties?), who will process/handle the data, who will be able to access the data during and after research (only researchers at TU/e or also others)?
13	Have any special agreements already been made with an external party, such as a Non-Disclosure Agreement (NDA) or a data sharing agreement?	☐ Yes, namely: ☑ No
14	Has your proposal already been approved by an external Ethical Review Board or Medical Ethical Review Board? Additional explanation: For example, when you are collaborating with another university and the project has been approved by their Ethical Review Board, or when you received a WMO-waiver from a Medical Ethical Review Board.	☐ Yes ☑ No
15	If yes: Please provide the name, date of approval and contact details of the ERB. Please also include the registered number for your project approval. Additionally, please send in the Ethical Review Form upon which ethical approval was granted together with this form.
16	If you process personal data that are likely to result in high privacy risks for participants, you need to perform a Data Protection Impact Assessment (DPIA). Have you done this for this or a very similar project? Please read the information below: a DPIA is not the same as a regular privacy impact assessment. More detailed questions on privacy will follow in the section below. Additional explanation: A Data Protection Impact Assessment (DPIA) is a formal document that must be drafted under the guidelines of the General Data Protection Regulation (GDPR). Think of research with vulnerable people, high-risk medical research, The Dutch DPA (Autoriteit Persoonsgegevens) and our website provides more information about a DPIA.	☑ Not applicable (no high privacy risks) ☐ Yes (the form is attached to the application) ☐ No
Part 2: Medical study
1	Does the study have a medical scientific research question or claim? Additional explanation: Medical/scientific research is research which is carried out with the aim of finding answers to a question in the field of illness and health (etiology, pathogenesis, signs/symptoms, diagnosis, prevention, outcome or treatment of illness), by systematically collecting and analyzing data. The research is carried out with the intention of contributing to medical knowledge which can also be applied to populations outside of the direct research population. If your research contains questions about health and health related parameters (such as well-being, vitality, feelings of anxiety or stress) but your research question is not primarily medical, then you can answer ‘no’ to this question.	☐ Yes* ☑ No *If yes or in doubt, please contact Susan Hommerson via s.m.hommerson@tue.nl

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Part 3: Use of (medical) devices in the study
1	Does your research include a device? Additional explanation: A device is a complete piece of physical hardware that is used to compute or support computer functions within a larger system. Devices can be divided into input-, output-, storage-, internet of things-, or mobile device.	☐ Yes, not self-made ☐ Yes, self-made ☑ No
2	Please describe your device or link to an online description of the device
3a	Will you use a device that is ‘CE’ certified for unintended use (meaning you will use existing CE certified devices for other things than they were originally intended for) or use a device that is not ‘CE’ certified? Additional explanation: You can find more information about CE certification here	☐ Yes No
3b	If no: Please explain to what extent the device was assembled according to relevant standards and provide a risk assessment Additional explanation: You can find more information about a risk assessment here
3c	If yes: Do you use a device or software that has a medical purpose such as diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of disease or injury?	☐ Yes, my device or software currently has a medical purpose ☐ Yes, my device or software could have a medical purpose in the near future ☐ No ☐ I’m not sure
Part 4: Information about the study
1	What are your main research questions? Additional explanation: You need to provide at least one clear research question.	What is the demand for an AI chat tool to relieve stress and/or loneliness among university students? What aspects of such an AI chat tool do students like and perceive to be useful and/or effective? What aspects of such an AI chat tool could make the tool unattractive to students?
2a	Please check the box that indicates the relevant study population Additional explanation: Please select which persons are eligible for your study.	☑ Students ☐ General healthy population ☐ General population with specific feature, e.g., pregnancy, specifically ........... ☐ Patients, specifically ……...... ☐ Other, specifically ……………
2b	Age category of participants	☐ Younger than 12 years of age ☐ Older than 11 and younger than 16 years of age ☑ 16 years or older
3	Description of the research method (select all that applies)	☑ (Semi-structured) interviews ☐ Surveys

Additional explanation: Please specify your research method. Note that you need to provide information about the research method in an additional file that you attach to the ERB form. E.g., for interviews you provide the interview questions, for surveys you provide the survey questions, etc.	☐ Group workshops/roundtable discussios ☐ Diary studies ☐ Behavioral observations ☐ Building sensor data ☐ Wearable device (e.g. Fitbit watch, on-skin sensors) ☐ User testing ☐ Pilot study ☐ GPS tracking/location data ☐ Living Lab ☐ Other, namely ................
4	Description of the measurements and/or stimuli/treatments Additional explanation: Think about your outcome measures and the variables you will be collecting and describe them in a way such that another person understands what the participant will experience. For example: Participants will perform task A and see pictures from database B, and we measure validated Scale 1.	Participants will be shown the AI chat tool developed by the research team and informed about its uses and how it works. Participants will then be asked about their opinion on the tool (what they find effective, what they think could be improved, whether they would be open to using it). For clarity: participants will not actually use the tool, they will not put in their personal experiences.
5	Describe and justify the number of participants you need for this study. Also justify the number of observations you need, taking into account the risks and benefits. Additional explanation: Think about if you need 3 or 30 participants for example, and why? Do they need to provide their input once, or several times, and why? If relevant, specify the duration of the study per participant and the compensation that is needed for the study.	Each group member will conduct 2 interviews, which means 12 interviews will be conducted in total. With 12 participants, we believe we will have enough data to get valuable (different) insights. Each participant will only be interviewed once.
6	Explain why your research is societally important. What benefits and harm to society may result from the study? Additional explanation: What benefit will the results of your study have to society in general?	Students often experience stress and/or loneliness, but the threshold to seek out professional help is often too large (or waiting lists for said help are too long). With this study we want to look into how an AI chat tool could be put to use to help tackle this problem.
7	Describe the way participants will be recruited Additional explanation: How will you recruit participants for your study? For example, by using flyers, personal network, panels, etc.	☐ Survey link posted online, e.g., social media platforms ☐ On campus flyers ☑ Personal network ☐ Via a company, namely …………….. ☐ Via a hospital, namely …………….. ☐ Via an organization …………… ☐ By a Consortium Partner, namely ……………. ☐ Other, namely ………..
8	Provide a brief statement of the risks you expect for the participants or others involved in the study and explain. Also take into consideration any personal data you may gather and associated privacy issues. Additional explanation: Risks for the participants can be anything from risk of data breach to risk of safety or well-being (think about stress, extreme emotions, visual or auditory discomfort). Describe these possible risks and describe the way these risks are mitigated.	Participants are not exposed to risks.

Part 5: Self-assessment checklist
Note: answers in the blue boxes indicate that your research is eligible for fast-track approval	Yes	No
1a	Does the study involve human material? (e.g., surgery waste material derived from non- commercial organizations such as hospitals)	X
1b	Will blood or other (bio)samples be obtained from participants? (e.g., hair, sweat, urine or other bodily fluids or secretions, also external imaging of the body)	X
2	Will the participants give their consent – on a voluntary basis – either digitally or on paper? Or have they given consent in the past for the purpose of education or for re-use in line with the current research question?	X
3	Are the participants, outside the context of the research, in a dependent or subordinate position to the investigator? Additional explanation: Think about doing research on your own students or on your own employees. When there is a dependency or power imbalance between you and the research participants, you need to answer ‘yes’ to this question.	X
4	Does the study involve participants who are particularly vulnerable or unable to give informed consent? (e.g., children (<16 years of age), people with learning difficulties, patients, people receiving counselling, people living in care or nursing homes, people recruited through self- help groups)	X
5	Will participating in the research be burdensome? (e.g., requiring participants to wear a device 24/7 for several weeks, to fill in questionnaires for hours, to travel long distances to a research location, to be interviewed multiple times)?	X
6	May the research procedure cause harm or discomfort to the participant in any way? (e.g., causing pain or more than mild discomfort, stress, anxiety or by administering drinks, foods, drugs, or showing explicit visual material)	X
7	Will financial inducement (other than reasonable expenses and compensation for time) be offered to participants? Additional explanation: For an explanation of what is considered a reasonable compensation, see the topic participant fees from the HTI group	X
8a	Will it be necessary for participants to take part in the study without their knowledge and consent at the time? (e.g., covert observation of people)	X
8b	If yes: Will you be observing people without their knowledge in public space? (e.g. on the street, at a bus-stop)	X
9	Will the study involve actively deceiving the participants? (e.g., will participants be deliberately falsely informed, will information be withheld from them, or will they be misled in such a way that they are likely to object or show unease when debriefed about the study)	X
10	Will participants be asked to discuss or report sexual experiences, religion, alcohol or drug use, suicidal thoughts, or other topics that are highly personal or intimate? Additional explanation: Think about your research population. For some participants, particular topics can be considered sensitive or intimate, whereas the same topics will not be perceived as such by other participants.	X
11	Elaborate on all boxes answered outside of the blue boxes in part 5. Describe how you safeguard any potential risk for the research participant.
Part 6: Self-assessment on privacy The following questions (1-11) concern privacy issues, as laid down in the General Data Protection Regulation (GDPR). The Data Stewards and – if necessary – privacy team of TU/e will assess these questions. In some cases, more information is required to assess the privacy risks. If this is the case, you will be notified that the Data Stewards team will contact you. The GDPR defines ‘personal data’ as any information relating to an identified or identifiable natural person (‘data subject’). Personal data also includes data that indirectly reveals something about a natural person. Personal data can lead to the physical, physiological, genetic, mental, economic, cultural or social identity of a natural person. There are two main categories of personal data: regular personal data and special category personal data. If you are not sure whether some of these questions below should be answered with a Yes or No, please contact a Data Steward first through rdmsupport@tue.nl.
Note: answers in the blue boxes indicate that your research is eligible for fast-track approval	Yes	No
1	Will the study involve discussion/collection/processing of regular personal data, or will you collect and (temporarily) store video or voice recordings for the purpose of conducting interviews? Additional explanation: For example, name, address, phone number, email address, IP address, gender, age, video or interview recordings? If you are not sure whether your data contains personal data, please contact the Data Stewards Team (rdmsupport@tue.nl).	X
1A	If yes: Please describe which regular personal data you will collect in this study?	Interview recordings, age, study
2	Will the study involve discussion/collection/processing of special category personal data or other sensitive data? Additional explanation: Examples of special category personal data are race, religion, health information, political views, genetic or biometric data for the unique identification of a person, sexual preference, etc. Health information concerns personal data of the physical or mental health of persons, including the provision of health care. Examples of other sensitive data is information such as communication data, financial records or credit scores, camera surveillance data, location/GPS data, internet-of-things data, employee monitoring, observing or influencing behaviour, criminal records, data of vulnerable persons (children, people with disabilities, refugees), BSN number etc. Please be aware that the use of special category personal data in research requires extra security measurements in order to safeguard the privacy of data subjects and to comply with the GDPR. Processing of this special category data is prohibited, except for specific purposes and under certain circumstances. If you need to process special category data, please consult the data stewards at rdmsupport@tue.nl.	X
2A	If yes: Please describe which special-category personal data and/or sensitive data you will collect in this study?
If you answered yes to either question 1 or 2, please answer the questions below. If you answered no to both questions, you can skip this part and continue onto part 7. Also, if an answer to any of the following questions is ‘yes’, please contact a Data Steward at rdmsupport@tue.nl
Yes	No
3	Will your project involve the processing of personal data on a large scale? Additional explanation: In general, any processing that involves more than 10.000 data subjects should be considered “large scale”. However, if the data of approximately 1000 persons (or more) are involved, the data processing may still be considered large scale. In that case, besides the number of persons involved in the study, one should also assess (i) the amount of data collected from these persons taking into account the type/risk level of the personal data, (ii) the duration of the data processing, (iii) the geographic scope or extent of the processing. For example, if you would collect and process data across several European countries with 10+ socio-economic data items of 1200 individual persons for several years in a row, that is likely “large-scale processing”. Other examples of a large-scale processing activity are: Monitoring driving behavior of road users on Dutch highways Collecting data of Covid patients A hospital that processes patient data as part of its usual operations	X

A transport company that processes travel information of people who travel by public transport in a certain city. For example, by tracking them through travel maps.
4	Does this processing activity involve the use of new or innovative technologies? Examples of a new technology: combining fingerprints and facial recognition for physical access control, the use of bodycams in public spaces, the use of new technical methods in conducting research such as AI. This question also refers to new technologies that have not been deployed by TU/e so far.	X
5	Does your study involve systematic (c.q. automated) monitoring of persons? Additional explanation: Consider data processing activities that have the purpose of observing, monitoring or controlling individuals, for example in circumstances where the individuals are not aware by whom their personal data is collected and how it is used. Examples of such activities are using camera systems to monitor driving behavior on highways, monitoring email inactivity or employee phone use, certain applications of machine learning and artificial intelligence.	X
6	Does the study involve collaborations (with third parties) in which data are shared or exchanged in order to link or combine data? Additional explanation: This may often apply in a collaboration between the university and a commercial party, contract research, etc. It is important to assess this for all data in the entire project, not just your own data. An important consideration in this situation is whether the person whose data is involved could have expected that data from these different databases or sources of information were to be combined. For example, it is less likely for data subjects to expect that databases from different parties will be combined and the results are used for different purposes than one could reasonably expect; this may apply for example in a collaboration between the university and a commercial party.	X
7	Will the study include data processing activities that prevent data subjects from exercising their rights or using a service or contract? Additional explanation: Examples include processing operations carried out in public places that people cannot avoid (train station, airport, shopping mall, public university premises, etc.) or processing operations whose purpose is to allow or not allow data subjects to use a service or enter into a contract (examples: by refusing to pay a benefit, not being able to apply for a loan, etc.).	X
8	Will the study process personal data to score, rank or profile persons? Additional explanation: Examples: monitoring (highway) roads to give road users a “score” based on their detected driving behavior, a bank assessing its customers based on their creditworthiness, or an organization building behavioral and marketing profiles based on use of their website or navigating their website.	X
9	Does your data processing include activities that involves composing “blacklists” – and, in particular, in relation to sensitive or special category data, such as communication data, financial records or credit scores, genetic data, biometric data, health data, camera surveillance data, location/GPS data, internet-of-things data, employee monitoring, observing or influencing behaviour, etc. Additional explanation: This situation will not be a common occurrence in research, but you may indirectly be involved in this. In general, this typically concerns processing operations involving personal data relating to criminal convictions and offences, data relating to unlawful acts, data concerning unlawful or annoying behaviour or data concerning bad payment behaviour by companies or individuals are processed and shared with third parties (blacklists or warning lists, as used, for example, by insurers, hospitality companies shopping companies, telecom providers as well as blacklists relating to unlawful behavior of employees, for example in the healthcare sector or by employment agencies, etc.).	X
10	Will personal data be transferred or shared outside the EU/EEA? EU data protection rules apply to the European Economic Area (EEA), which includes all EU countries and non-EU countries Iceland, Liechtenstein and Norway. Additional explanation: The GDPR has drafted additional requirements for transfers data outside of the EU/EEA. Typically, additional safeguards must be implemented to protect the personal data of residents in the European Union. For example, if you collaborate with an American, Indian or Chinese university or other third party outside the EU/EEA, you must first check whether this is allowed and under which conditions this is allowed. Another typical example is storage of data on American providers of cloud (storage) services. Please contact the data stewards first to discuss this.	X
11	Will any raw or anonymized personal data or any other sensitive data or research results from the project possibly be transferred to a high-risk country*? *High risk countries: China, Russia, Iran, Turkey, and North Korea. If personal data or other potentially sensitive data is exchanged with one of these countries, or if part of the data processing takes place in one of these countries: an advice from the Data Protection Officer, the kennisveiligheidsteam (Knowledge Security team), and the CISO (Chief Information Security Officer) is ALWAYS required.	X

Part 7a: Processing of research data
1	Is consent your legal basis for processing the personal data in your study? Additional explanation: What is a legal basis? One of main principles in the GDPR is to ensure that personal data is processed lawfully, fairly, and transparently. To comply with this principle, the processing of personal data also requires that you have a valid legal basis for the personal data processing activity. In research projects, the legal basis is often but not always consent. However, it is possible that it is not clear or not possible to establish whether to use consent as a legal basis. Some examples where consent may not be applicable as legal basis are covert research, data collection in public spaces, secondary data analysis of existing data, data that are transferred to you by a third party, consent is not possible or would require disproportionate effort, etc. In that case, please indicate which legal basis you think that applies or (preferably) contact a data steward first.	☑ Yes and it will be obtained via an informed consent form An informed consent template* is attached to this application. ☐ No, I will use another legal basis to process the data. Namely, …….. * You can download a suitable template here.
2	Where will the data come from?	☐ Data obtained from another party (secondary data use) ☑ New data collected only by my research team ☐ New data collected together with collaborators
3	Which of the following tools will you use to process personal data?	Surveys ☐ Qualtrics ☐ Limesurvey ☐ MS Forms ☐ Other, namely ……………..
Interview/workshop recordings ☑ Voice/video recorder ☐ Phone in a flight mode ☑ MS Teams ☐ Other, namely ………………
Transcription ☑ Manual transcription ☑ Microsoft Office software (e.g. Word, Teams)
☐ Other, namely ……………
Statistical analysis ☐ SPSS ☐ R ☐ Other, namely ……………
Other tools, specifically……………….
4	Where will the data and in particular the personal data be stored during and after completion of the study? If you have already uploaded your Data Management Plan, you can refer to your Data Management Plan.	☑ Onedrive ☐ Research Drive ☐ Network Drive

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Additional explanation: University supported-storage facilities are SURF Research Drive, Ceph, departmental drives (this includes BE Project Drive), and the TU/e instance of Microsoft OneDrive. For most personal data, the use of SURF Research Drive or departmental drives (including BE Project Drive) is required.	☐ Research Manager ☐ Other, namely ………
Part 7b: Safety and security measures
1	Will you pseudonymize/anonymize the data? Additional explanation: Anonymization: remove all direct identifiers (name, address, telephone number etc.) but also indirect identifiers (age, place of birth, occupation, salary) that, linked with other information, can lead to a person’s identification. Anonymization to the point that a data subject is no longer identifiable means that the anonymized data is not considered to be personal data anymore. Pseudonymization: replacing the unique identifier of a data subject with an artificial pseudonym. This means that identification is still possible with the identification key. The identification key needs to be stored securely and separately from the pseudonymized data. If the data subject can be identified by combining data with additional information, the data is also called pseudonymous.	☑Yes ☐ No If yes, describe how: We do not ask for any direct identifiers. We do ask for two indirect identifiers (age, study), but we will only check age to ensure participants are within the target demographic and check study to ensure participant diversity. After this check, these identifiers will be taken out of the data (i.e. out of the interview recordings and transcripts).
2	Is access to (personal) data restricted? (Select all that apply)	☐ No ☐ Yes, via access control ☑ Yes, via password protection ☑ Yes, access only given to TU/e research team ☐ Yes, access only given to research team, including non-TU/e collaborators ☐ Other, specify……….
3	Who will have access to the data during and after completion of the project? (Select all that apply)	☐ Main researcher ☑ TU/e supervisor(s) ☐ External supervisors ☑ TU/e research team ☐ Other, specify……….
4	Will you store data for future research?	☑ No ☐ Yes, in a public data repository ☐ Yes, in a public data repository under restricted access ☐ Yes, in a TU/e-recommended storage (SURF Research Drive, Network Drive)
5	Will you share data outside the TU/e?	☑ No ☐ Yes, in a fully anonymized form ☐ Yes, raw or pseudonymized data* *If you selected this box, make sure that a suitable data agreement is put in place. You can contact the Data Stewards for support in preparing such an agreement
6	How long will data be stored after the end of the project?	Data will be stored until the group has received the final grade. If the grade is sufficient the data will be deleted right away. If the grade is insufficient the group would need to do more work on the research and thus need the data still. The data is then deleted after this further work on the research is completed.

Part 8: Closures and Signatures
1	Enclosures (tick if applicable and attach to this form):	☑ Informed consent form ☐ Informed consent form for other agencies when the research is conducted at a location (such as a school) ☐ Text used for ads (to find participants) ☐ Text used for debriefings ☐ Approval other research ethics committee ☐ The survey the participants need to complete, or a description of other measurements ☐ Data Protection Impact Assessment checked by the privacy officer ☐ Data Management Plan checked by a data steward
2	Signature(s)	Signature(s) of applicant(s) Bridget Ariese Marie Bellemakers Mila van Bokhoven Sophie de Swart Maarten van der Loo Bram van der Heijden Date: 25/02/2025 Signature research supervisor : Date:26/02/25