The tool’s general aim is to contribute to scientific data collection, allowing a new way of gathering data and information from society at large. The chatbot sends text contents written by humans. The texts are general contents written by the research team and microstories written by Co-Researchers (see Tool: Research Diary). The chatbot then collects the answers from the participants in a database. Based on these data, the research results are then analyzed collectively (see Tool: Collective Data Interpretation) and will be openly accessible.In CoAct, the tool specifically aims at a better understanding of informal support networks in mental health including the perspectives of a variety of people. The chatbot also wants to raise awareness and empathy regarding the daily life of persons with mental health problems and communicate their concerns. It constitutes a horizontal, private and safe space where personal microstories can be shared and listened to . It wants to give a co-created, rich, and elaborated data set into the hands of citizens who can use it to underpin their political demands. Co-creating a digital tool for collecting data on a personal concern of the citizens also advances digital democratization. SDGs that are addressed are Goals 3, 4, and 5.
Citizens from different countries and with different profiles, motivated by mental health improvement can subscribe to the chatbot currently available in 4 languages (Catalan, Spanish, English and German). These Citizen Scientists, after signing an Informed Consent, can participate in this collective and anonymized conversation until they answer the 222 microstories currently inside the chatbot. They can also stop their participation at any time. The participants can answer the questions when it is most convenient for them, thus integrating research participation into their daily routines. As the Telegram application that hosts the chatbot can be installed on smartphones and desktops, the participants can answer in private and safe surroundings. The participants can thus take their time to answer, collectively nourishing a rich and well-thought-out dataset of answers.
The chatbot co-creation phase has involved Co-Researchers and Knowledge Coalition – who filled the chatbot with life and criticized and improved the design. The Co-Researchers are citizens with mental health problems and family members and caregivers of persons with mental health problems. The Knowledge Coalition members represent local and international associations in the field of mental health.
The chatbot runs on a University server that naturally has to be online day and night and satisfies GDPR European regulation. Further, printed flyers and posters, videos, digital materials promoted the chatbot. The chatbot is accompanied by a website that gives further context and shows media actions and Co-Researcher’s testimonials. The chatbot contains an Informed Consent, approved by the Ethics Committee of the University and available in the four languages.
Write a Data Management Plan (DMP), with special focus on privacy. Write a prototype python code. Feed in the contents contributed by the different stakeholders and revise the DMP. Let Co-Researchers test the prototype and incorporate their suggestions in the design. Start the final chatbot on a stable and safe server. Continuously launch different advertisements in a large variety of media (radio, printed press, e-mail, social media, etc.). Continuously tackle technical issues and address participants’ questions. Harvest the data and give it into the hands of the citizens (See toolkit “Collective Data Interpretation”).
