The digitization of mental health care holds promises of affordable and ubiquitously available treatment, e.g., with conversational agents (chatbots). While technology can guide people to care for themselves, we examined how people can care for another being as a way to care for themselves. We created a self-compassion chatbot (Vincent) and compared between caregiving and care-receiving conditions. Care-giving Vincent asked participants to partake in self-compassion exercises. Care-receiving Vincent shared its foibles, e.g., embarrassingly arriving late at an IP address, and sought out advice. While self-compassion increased for both conditions, only those with care-receiving Vincent significantly improved. In tandem, we offer qualitative data on how participants interacted with Vincent. Our exploratory research shows that when a person cares for a chatbot, the person's selfcompassion can be enhanced. We further reflect on design implications for strengthening mental health with chatbots.

Trust in chatbots can be shaped by various factors such as humanlikeness in terms of visual appearance and conversational content, and conversational performance in terms of the chatbot's ability to avoid conversational breakdown. The literature is inconclusive concerning the effect of humanlikeness and conversational performance on trust, especially their interaction effect. To examine the relations among these variables, we conducted a 2x3 (humanlikeness x conversational performance) factorial experiment with 251 participants, who were asked to perform three tasks with a chatbot for an online bank under one of the six conditions. Participants completed a questionnaire measuring trust and commented on trust factors. Results of between-group analysis showed that for the task with seeded breakdowns there were significant differences in trust across the six groups with the lowest ratings for the two groups experiencing breakdowns without repairs and that humanlikeness did not impact the extent to which the trust level changed. Results of within-group analysis showed significant differences in trust across the tasks but non-significant inter-task correlations on trust for the two groups. These observations challenge the effect of humanlikeness on trust while supporting the notion of trust resilience as the participants did not spill the impaired trust over the subsequent task. Thematic analysis showed that inter-group contrasts could be found for the theme 'underlying functionality' and 'affective responses.' Implications for research, practice and future work were drawn. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI.

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