Data from: CoAct Citizen Science chatbot explores social support networks in mental health based on lived experiences

A data set on lived experiences in the context of social support in mental health, created within a Citizen Social Science project. 

Societies around the world increasingly encounter wicked and complex problems, such as those related to mental health, environmental justice, and youth employment. CoAct as a EU-funded global effort addresses these problems by deploying Citizen Social Science. 

Citizen Social Science is understood here as participatory research co-designed and directly driven by citizen groups sharing a social concern. This methodology wants to give citizen groups an equal ‘seat at the table’ through active participation in research, from the design to the interpretation of the results and their transformation into concrete actions. Citizens thus act as co-researchers and are recognised as in-the-field competent experts. 

In Barcelona, a group of 32 co-researchers work together with the OpenSystems group, Universitat de Barcelona, the Catalan Federation of Mental Health (Federació Salut Mental Catalunya), and with the help of many others on a better understanding of informal social support networks in mental health in the project CoActuem per la Salut Mental (lit. “We act together for mental health”). The co-researchers, who are either persons with a personal history of mental health problems or are family members of the latter, contributed their personal experiences related to social support in the form of 222 micro-stories, each shorter than 400 characters, and most accompanied by an illustration by Pau Badia.

Those micro-stories form the heart of the first co-created Citizen Science chatbot, the code of which is open on https://github.com/Chaotique/CoActuem_per_la_Salut_Mental_Chatbot.git . The Telegram chatbot sends them to participants on a daily basis over the course of a year and asks them either, whether they and/ or their close surrounding lived this experience, too (stories of type C), or, how they would or would have reacted in the presented situation (stories of type T). The answers of each participant can be contrasted with the individual participants’ answer to a 32-questions socio-demographic survey. Further, the timing of the messages is included to allow for a broader analysis.  

The chatbot is still running, hence this data set will still be updated. For further information on the project CoAct, see https://coactproject.eu/. For further details on the co-creation process and purpose of the chatbot CoActuem per la Salut Mental, take a look on https://coactuem.ub.edu/. Please direct your questions regarding the data set to coactuem[at]ub.edu.

Acknowledgements

The CoAct project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number 873048. We especially thank the co-researchers for the passion and time invested.