*8.3. Influence of Topics on Participants' Utterance Time*

In order to investigate whether the topic of the questions influence the verbal participation time of the participants, we calculated the mean of the utterance time of the participants in each topic. The results were as follows: In the one-robot scenario, the utterance time of the topic of travel, health, and childhood were 11.9 s (SD = 21.3), 6.8 s (SD = 5.1), and 14.7 s (SD = 27.4). In the two-robot scenario, the utterance time of the topic of travel, health, and childhood were 9.3 s (SD = 10.5), 9.2 s (SD = 11.5), and 12.0 s (SD = 12.7). We analyzed the results using two-way mixed ANOVA, which

has scenario factor and topic factor. The results showed that there was no main effect in the scenario factor (F(1,20) = 0.01, *p* = 0.920), no main effect in the topic factor (F(2,40) = 2.094, *p* = 0.136), and no interaction between the two factors (F(2,40) = 0.933, *p* = 0.402). Therefore, it is unlikely that differences in topics had a systematic effect on utterance time.

Because the variance of the utterance time is very large, the influence of the topic of the question on the utterance time appeared to be considerably dependent on the individual. As an interesting example, we found that a topic stimulated participants' memory and the participants began to talk about their life for a long time. Specifically, participant 2 spent about 2 min talking about her initial visit to the nursing home when the robot asked, "Have you ever had a honeymoon?". Moreover, in response to the question, "What class did you like in elementary school?" she had talked about her childhood struggles for about 3 min. Participant 18 spent about 3 min talking about their experiences during World War II when asked "Have you lived around here since you were a child?". Their utterance times were quite long considering that usual answers of other participants were only one or two sentences. More surprisingly, even the caregivers, who have been interacting with the participants in their daily lives, did not know the stories of the participants until that time. These examples are interesting from the aspect of robots being potentially able to elicit a much deeper story from the elderly if the robot chooses topics adjusted to the individual.
