Please read the following information carefully before deciding to participate in this research study. You can keep/download this letter in case you might wish to follow-up about the research.

What is the research study about?

This research studies the effect of an artificial intelligence (AI) assistant on the diagnostic reasoning of doctors, we will present doctors & trainee doctors with hypothetical but realistic patient conditions and ask them to come to a diagnosis. Half of these participants will receive an AI chatbot assistant, half will not. We will assess the impact of the AI through the diagnostic reasoning of participants.

Who can be contacted about this research study?

This research is conducted as part of the research programme at the School of Business and Economics, Maastricht University. The research team consists of:

• Prof. Dr. Mark Levels, Professor, Maastricht University, m.levels@maastrichtuniversity.nl (primary contact)
• Dr. Marie-Christine Fregin, Project Leader, Maastricht University
• Nicholas Rounding, PhD Candidate, Maastricht University

How will the research study be conducted? 

You will be asked to participate in an experiment where you will be asked to come to a diagnosis from a hypothetical patient story and to take part in a survey. We may also ask you to take part in an interview, but another informed consent document will be provided for this.

Experiment

• We will conduct the experiment in a controlled laboratory setting, you will be asked to complete up to 4 patient vignettes. These are hypothetical patient stories with the information required to come to a diagnosis. The experiment will be executed via Qualtrics.
• The AI assistant will be randomly assigned to half of the participants. If you are assigned the AI assistant, you will also have access to an AI chatbot. This chatbot will be executed using an interface designed by researchers at Maastricht University and will use GPT-4, provided by OpenAI. No personal information will be sent to OpenAI. The chat logs will be linked to the Qualtrics data via a personal identifier.

Survey

• After the completion of the experiment, you will be provided with a survey to complete. This survey will be executed via Qualtrics. 

What are the conditions of participating? Are there potential risks?

You are taking part on a voluntary basis and may stop whenever you want without negative consequences. You do not need to answer any questions or provide any information that you do not want to provide. There are no physical, legal, or economic risks involved with participation in this research. 

How will you be compensated for your participation?         

There is no payment or compensation for taking part in this research.

What personal data do we process as part of the research and why?

Personal information for research purposes: 

• Participant ID: A randomly generated participant ID will be used to identify the survey responses, this will also be linked to any chat logs generated via the chat interface.
• Demographic characteristics: gender; age; and working experience will be collected
• Chat logs: For participants that receive AI assistance we will also collect and analyse the chat logs. This data may be retained by OpenAI and processed in line with their data regulations. More information may be found here: https://openai.com/policies/privacy-policy

We collect this information to investigate the research objectives. Any reporting of this data in scientific publications cannot be traced back to you as an individual. We will achieve this by reporting on no demographic groups with lower than 5 observations. 

Storage and data retention 

The personal information you provide will be pseudonymized. All research data is collected via Maastricht University IT infrastructure. Data in the Netherlands will be stored securely in Maastricht University’s IT infrastructure. Data. Data sent to OpenAI via the chatbot interface may be retained by OpenAI. No data submitted via Qualtrics will be sent to OpenAI. At Maastricht University, all research data and consent documentation, collected during the project will be retained for at least 10 years in agreement with Maastricht University guidelines. In accordance with Open Science practices, the researchers at Maastricht University will publish the gathered, pseudonymized data on DataverseNL for re-use. 

The results of this experiment will only be used for scientific analysis, they will not be used to contribute to any grades for any qualification provided by Maastricht University.

Data subject rights

If you have any general enquiries about your rights as a data subject, you can learn about this by going to https://www.maastrichtuniversity.nl/about-um/um-general-privacy-statement. If you want to exercise your rights as a data subjects, you contact the research team, or you can do so by going to https://www.maastrichtuniversity.nl/about-um/um-general-privacy-statement/your-rights.

Doelstelling van het onderzoek

Het doel van dit wetenschappelijk onderzoek is te bestuderen hoe studiekiezers hun studiekeuze hebben gemaakt. Het onderzoek wordt uitgevoerd door het Researchcentrum voor Onderwijs en Arbeidsmarkt (ROA), een onderzoeksinstituut van de Maastricht University School of Business and Economics.
Het onderzoek wordt gefinancierd door het Instituut Gak.

Hoe gaan we te werk?

Het onderzoek zal bestaan uit een anonieme enquête op het Qualtrics-platform.
De datamanager van Maastricht University (ROA) ontvangt alleen de anonieme antwoorden en bewaart de gegevens veilig op servers van Maastricht University (ROA). Een anonieme dataset wordt alleen beschikbaar gesteld aan het onderzoeksteam van Maastricht University (ROA).

In dit onderzoek werkt het ROA samen met het Centraal Bureau voor de Statistiek (CBS). Het ROA verzamelt de gegevens namens het CBS en het ROA. Het CBS krijgt naast de verzamelde gegevens ook veel bestanden van andere instellingen. Hierin staan bijvoorbeeld gegevens over bevolking en onderwijs. Die informatie voegt het CBS samen. Daardoor hoeft er zo weinig mogelijk informatie uitgevraagd te worden. Het ROA krijgt van het CBS toegang tot deze samengevoegde informatie om statistieken te maken. Persoonlijke gegevens zijn daar nooit in te herkennen.

Vertrouwelijkheid van informatie

De anonieme gegevens zullen alleen toegankelijk zijn en gebruikt worden door het onderzoeksteam van Maastricht University (ROA). Het onderzoeksteam van Maastricht University (ROA) zal nooit rapporteren over individuele antwoorden op enquêtes; de minimale groep antwoorden voor rapportage is vijf. De onderzoeksgegevens worden 10 jaar bewaard.

Mogelijke risico's en ongemakken

Er zijn geen fysieke, juridische of economische risico's verbonden aan uw deelname aan het onderzoek.

Vrijwillige basis

Deelname aan het onderzoek is vrijwillig. Als je niet wilt deelnemen, dan hoef je daarvoor geen reden te geven. Ook als je besluit om deel te nemen, kun je op elk gewenst moment stoppen met het invullen van de vragenlijst. Wij zullen je antwoorden dan niet gebruiken voor het onderzoek. 

Je vragen en rechten

Voor vragen over het onderzoek kun je contact opnemen met het onderzoeksteam van Maastricht University (ROA) door een e-mail te sturen naar surveyresearch-roa@maastrichtuniversity.nl. Als je algemene vragen hebt over je rechten als deelnemer, kun je hierover meer informatie vinden op https://www.maastrichtuniversity.nl/nl/over-de-um/algemene-privacyverklaring-um. Als je je rechten als deelnemer wilt uitoefenen, neem dan contact op met het onderzoeksteam, of gebruik deze link https://www.maastrichtuniversity.nl/nl/over-de-um/algemene-privacyverklaring-um/jouw-rechten. Specifieke vragen over de omgang met persoonsgegevens kun je ook stellen aan de Functionaris Gegevensbescherming van Maastricht University door een e-mail te sturen naar fg@maastrichtuniversity.nl. Je kunt ook een klacht indienen bij het College Bescherming Persoonsgegevens.

Purpose

Human capital investments made at the regional level are important to match labour supply and demand, and to stimulate labour force participation, productivity, innovation and growth. Many regional policy makers are challenged by:

• A lacking responsiveness of the regional educational system to new economic and technological developments.
• Demographic transitions in the form of increasing migration flows and population ageing, with a declining or more diverse inflow of young people joining the workforce.
• An insufficient regional pool of up-to-date qualified and highly-able teachers.

These challenges differ between central (‘Randstad’) regions on the one hand and peripheral (‘Randland’) regions on the other, with the latter often being border areas that are more prone to demographic shrinkage. Employers, schools, local governments and private and public employment services can improve the transition between (vocational) education and the labour market by cooperating at the regional level.

Research themes

• Regional push and pull factors with respect to working and living for people at the higher, intermediate and lower educational level in both the Randstad and Randland areas.
• Geographic mobility of workers regarding commuting and internal and international migration.
• Regional educational infrastructure of vocational schools and higher education institutes.
• Impact of demographic transitions (shrinkage and growth, ageing, migration) on regional labour markets, including the teacher labour market.
• Barriers for international and cross-border mobility, including differences in tax, pension and social security systems, inefficient diploma recognition, poor cross-border public transport and road connections, language and cultural differences.
• Labour force participation of vulnerable groups at the regional and local level, such as migrants, low-skilled and disabled people.

Purpose

In both research and policy, there is a growing attention for the cognitive and non-cognitive skills that allow workers to perform their tasks at work in an optimal way. An important challenge is to better understand what drives the dynamics in the demand for and the supply of skills in relation to the growing flexibility of the labour market, the growing complexity of work, and internationalisation and automation that affect the nature of workers’ tasks.

This program has three main themes:

Labour market information, and occupational and recruitment choices

• Technological development/innovation on expected demand for supply for skills in the medium term.
• The educational choices of youngsters, and occupational sorting over life course.
• Adjustments in labour supply over the career.
• Changes in the workers’ tasks and how it affects the demand for skills.
• Commonality of tasks between jobs and the transfer of skills across occupations.
• Relation between work and wage dynamics.
• recruitment.

Lifelong learning and employability

• Trends, determinants and effects of lifelong learning
• Sustainable employability and reintegration of groups with a weak labour market position.
• Effects of HRD and HRM for organization and employees at the organization and sector level.
• Sustainable employability from a multidisciplinary perspective (change in tasks, skills, workload and health) and how this is anticipated or recovered.
• Training policies and learning cultures in firms.
• Impact of New Ways of Working.

Older workers and retirement

• Labour market for the elderly and retirement decisions.
• Skills and retirement.
• Employability of the low-skilled and the elderly.
• Relation between skill obsolescence, training, employability, productivity. and labour participation.
• Replacement processes in firms.