## 6 Conclusions  
The current study showed that experts' expectations do not always match the sentiment analysis or the participants' answers. Although there are cases where there is complete agreement between experts, sentiment analysis, and participants, there are also cases where the dominant emotion was not easy to predict. Having said that, in all cases, the experts and the participants agreed on whether the experience was predominantly positive or negative. More specifically, there were 6 images (out of 14) that the participants, experts, and algorithms agreed on regarding the main emotion depicted. Participants agreed with the sentiment analysis tool 8 times (8 images out of 14). Participants agreed with the experts 10 times (10 images out of 14). Trying to further understand these discrepancies and the reasons for occurring, we believe that two elements might be important: 1. algorithms in the sentiment analysis tool are trained by younger people; 2. algorithms in the sentiment analysis tool are trained by computer experts and not social sciences experts. Of course, thesample in the current study does not allow further speculation on the matter since it was not the scope of the present work to validate the sentiment analysis tool with the input of older individuals, but it was used to find the right images for the experiment that covered a vast spectrum of emotions. A future study could study this issue in detail. To create meaningful and inclusive experiences in virtual reality for people of all ages, including people over 65, it is important to focus on issues of content design, as well as technology design. Content development for VR is demanding and requires resources, making it essential to design it following accessibility guidelines, including physical, emotional, and cognitive accessibility. The present work allowed participants to participate in experiences that evoked emotions and engage in group discussions on historical events, also building on past research [35; 36]. This age group seems to be hesitant with the use of technology either because they believe they lack technical skills or because they are skeptical overall about the use of novel technologies. As mentioned above, issues of ethics emerged frequently during the data collection session. Even if using technology acceptance models is important with all types of users, with this age group, it is essential. The current study moved beyond the existing literature, which has provided data on younger individuals [17], and showed clear differences in the technology acceptance between older and younger users of VR. Regarding content requirements, designers should avoid unnecessary details in the material used for VR and AR content since there seem to be cognitive capacity limitations and a slower processing speed. Dark colors seem to trigger negative emotional reactions, and in fact, this was mentioned by most participants when the images were analyzed. Cultural content should provide connections to personal experiences and allow room for the recollection of personal memories and reflection. As they also mentioned, _\"as the end of life is getting closer, we need to feel optimistic about the future\"_. Considering this aspect, cultural content needs to include elements of hope and triggers of positive emotional reactions. The current study builds on previous works [25; 26; 27; 28; 29; 30; 31; 32] that recognized cognitive limitations in people over 65. In fact, we also observed cognitive capacity limitations and slower processing speed of older individuals when they analyzed the images presented to them. Regarding hardware requirements, VR applications for older adults could be offered in a simple form, e.g., desktop applications, VR cardboards, etc., that is more accessible and cheaper without being intimidating for older adults (not being afraid to destroy the equipment).