Suicide prevention is an important global topic, since suicide is being a worldwide serious health issue for decades. In the meantime, people start to pay more attention to mental health issues and Artificial Intelligence is developed and applied in many different fields. Recently, there are many studies been done on using Conversational Agents for mental illness. There are also applications of preventing suicide with Conversational Agents. In the Netherlands, 10.4 suicides happened per 100 thousand inhabitants in 2019. 113 Suicide Prevention is a Dutch national organization with a mission of pursing zero suicides. They are providing multiple services to help people with suicidal thoughts, including a self-test for evaluating suicidal risks anonymously. Even though, people who have taken the self-test receive some suggestions from the 113 websites, they might not contact the 113 helpline for further help. However, it is significant for people with suicide ideation to disclose their thoughts in order to reduce their intention of committing suicide. Therefore, a conversational agent was designed and developed to upgrade the suicide self-test service, which was aiming to resolve test-takers barriers towards contacting the helpline for human help. With the service, the conversational agent interacts with users to help them take the self-test and persuade them to reach for further help by relieving their worriers. A double-blind mixed designed experiment was conducted with 147 healthy general participants and two conditions (traditional questionnaire and interactive service) to verify the hypotheses and evaluate the service. It was hypothesised that participants would have more motivation to contact a helpline for further professional help after taking the self-test in an interactive way than taking the self-test in a traditional questionnaire way. The results showed a significant increase in the traditional questionnaire condition comparing to the interactive service condition. For participants' satisfaction and perceived usefulness, these are higher in the traditional questionnaire condition than the ones in the interactive service condition. In conclusion, the proposed interactive self-test service did not show an expected potential of increasing people's motivation to contact a helpline for professional help. However, the traditional self-test with a textual barrier intervention section showed the potential to motivate people’s help-seeking behavior comparing to the proposed interactive self-test service based on the experiment.

Objective: This thesis aided the 113 Suicide Prevention (113), the national suicide prevention center for The Netherlands, by investigating technical solutions for the helpline, implementing an e-learning prototype housing six suicidal personas within a conversational agent model, and evaluating and analyzing an experiment on its effect, which entailed interactions with one, two, and three simultaneous chats. Methods: The thesis conducted a participant observation with a total of seven triage-psychologists, organized three focus groups including triage-psychologists, managers, and training personnel with nearly forty participants, and administered an evaluation with thirty participants that included six triage-psychologist and twenty-four counselors regarding a prototype to assist in the training of 113's triage-psychologists. Prototype: The system specification provided a prototype with six personas where triage-psychologists can practice against one or many chatbots, or conversational agents, in different situations that pertain to training for 113. The conversational agents design was based upon the Rose of Leary interpersonal stance and the Beliefs, Desires, and Intentions (BDI) design paradigm. The system focused on how a conversational agent must react to triage-psychologists' inputs with respect to the subtleties in interpersonal communication and negotiation as it pertains to the 113 suicide helpline. Results: Evaluation results indicate that triage-psychologists found the learning environment motivational and the events in the environment as socially realistic. With the additional number of chats, counselors experienced an increase in three measurable areas: 1.) mental effort; 2.) situational awareness demand; and 3.) situational awareness supply; even so, counselors were positive about all learning aspects regarding the new software environment. Conclusion: This work identified the natural language processing, the BDI reasoning model plus natural language generation, and the usability and quality of the prototype as three areas of focus for 113 as they continue to improve their management of the helpline, its training, and research on suicide.