Virtual Cultural Experiences for the Elderly: Formative Studies and First Findings Regarding Cultural Content

Academic Editor: Douglas O’Shaughnessy Received: 30 November 2024 Revised: 26 January 2025 Accepted: 6 February 2025 Published: 11 February 2025 Citation: Antoniou, A.; Vassilakis, C.; Kantianis, G.; Sylaiou, S.; Kolokithas, G. Virtual Cultural Experiences for the Elderly: Formative Studies and First Findings Regarding Cultural Content. Appl. Sci. 2025,15, 1820. https://doi.org/10.3390/ app15041820 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article Virtual Cultural Experiences for the Elderly: Formative Studies and First Findings Regarding Cultural Content Angeliki Antoniou 1,* , Costas Vassilakis 2, Georgios Kantianis 2, Stella Sylaiou 3and George Kolokithas 4 1Department of Archival, Library & Information Studies, University of West Attica, 12243 Athens, Greece 2Department of Informatics and Telecommunications, University of Peloponnese, 22131 Tripoli, Greece; [email protected] (C.V.); [email protected] (G.K.) 3Department of Surveying Engineering and Geoinformatics, International Hellenic University, 62124 Serres, Greece; [email protected] 4Department of the Elderly, Social Organization Municipality of Patras, 26226 Patras, Greece; [email protected] *Correspondence: [email protected]; Tel.: +30-2105385243 Abstract: In societies with aging populations, the active participation of elders in all aspects of societal life is crucial. Cultural heritage provides a rich vehicle for engaging elders, stimulating both cognitive and affective responses, and keeping human brains active. This study focused on gathering requirements for creating content for virtual cultural experiences. Specifically, participants were shown various images and a film, and their self-reported thoughts and emotions were collected. The images were chosen by experts for the specific emotions they could trigger. The same images were analyzed with sentiment analysis software and finally given to the elders to express their emotions. The results of sentiment analysis, the analysis of experts, and the data from the participants were compared, showing differences between the perceived emotions. Regarding the historical film, the participants discussed the main emotions they experienced. The results were analyzed to extract guidelines for the content creation of VR applications. Keywords: virtual reality; elders; content requirements 1. Introduction The aging population is a reality in most human societies. According to Bloom et al. [ 1 ], people over 60 were estimated at 800 million in 2011 but they are expected to reach 2 billion by 2050, meaning that the elderly population will expand significantly. This large segment of the population cannot remain inactive for social, political, and economic reasons. For example, with the younger workforce reducing, it is a necessity that healthy older adults continue to work and support economies with their consumer power. It is also essential that older people participate in democratic procedures and social life, contribute with their life experiences, knowledge, and wisdom to help younger generations, etc. However, to achieve all these goals, reduce healthcare costs, and keep socially, politically, and economically active, older individuals need to remain healthy. Studies have shown that elders remain healthy for longer when they remain active physically [2] and mentally [3]. Cultural heritage is a great medium to keep people involved since it offers experiences on many levels. For example, cultural heritage provides a sense of identity and belonging, connecting individuals to their roots and heritage [ 4 ], as well as to the societies they belong to by creating common understandings and shared values [ 5 ]. When interacting with heritage and the rich stimulation it offers, cognitive ability is enhanced [ 6 ]. Among the Appl. Sci. 2025,15, 1820 https://doi.org/10.3390/app15041820 Appl. Sci. 2025,15, 1820 2 of 21 many cognitive benefits, learning is widely acknowledged as a part of cultural experiences [ 7 ]. Cultural heritage can also trigger creativity [ 8 ]. In addition, cultural heritage can evoke strong emotions, such as joy, pride, and inspiration, contributing to overall emotional wellbeing [9]. Virtual reality (VR) is a great medium to explore cultural heritage since it can make heritage and knowledge accessible to more people. Technology can also allow the personalization of experiences to match people’s needs and interests [ 10 ], increasing motivation to participate in cultural experiences [11]. Regarding the elderly, research is still scarce regarding VR cultural experiences for this age group. In addition, most studies focus on accessibility, immersion, and presence issues (e.g., [ 12 ]) and/or visitor satisfaction and benefits [ 13 ]. Very few studies, if any, focus on VR cultural content. Usually, content is designed before user testing, and content creation seems to be an intuitive process. Thus, the present work aims to gather content requirements for VR cultural experiences for the elderly. 2. Virtual Reality in Cultural Heritage for the Elderly Over the last few years, virtual reality applications have been used more and more in cultural heritage [ 14 ] to increase engagement and interaction with cultural content. In particular, during the recent COVID-19 pandemic, virtual applications were employed to keep people connected with cultural heritage content, and different approaches to mix the physical and the virtual were explored [ 15 , 16 ]. Moreover, museum visitors, and especially younger individuals, seem to have high levels of acceptance of VR in cultural experiences and there are learning gains while they engage with VR environments [ 17 ]. Visitors also report higher levels of satisfaction with the use of VR in cultural settings [ 18 ]. Immersive VR environments allow users to better understand both tangible and intangible aspects of the experience [ 19 ]. VR can support different types of cultural experiences from storytelling to 360 video [ 12 , 20 ] and games with very positive findings [ 21 ]. It seems that VR can enhance museum learning [ 22 ], and it can be also used to help with the preservation of cultural heritage [ 23 ]. Systematic reviews of the field [ 11 ] reveal the challenges but also show the potential of VR applications in cultural heritage [24]. 2.1. Virtual Reality and the Elderly The potential of VR in increasing the quality of life of older adults is recognized in the literature. In different studies, VR has been used to identify cognitive disorders [ 25 ], assist rehabilitation [ 26 ], and train elders’ cognitive [ 27 , 28 ] and motor skills [ 29 , 30 ], effectively using people’s free time [ 31 ] and increasing satisfaction and wellbeing. In a study by Matsangidou et al. [ 32 ], VR is used to provide rich and emotional experiences for people with mild cognitive impairment or mild dementia, showing the benefits of its use for this group of participants. 2.2. Virtual Reality in Cultural Heritage for the Elderly Currently, most digital heritage ICT applications are designed with the average young, healthy person in mind [ 33 , 34 ]. However, cultural institutions are increasingly aiming to include older adults, including those with mild cognitive impairment. While initiatives like the Museum of Cycladic Art’s (Greece) VR-guided tours for nursing homes are promising, adapting existing VR applications for the elderly presents unique challenges. Older adults often have a deep personal connection to cultural heritage and can enrich the experience by sharing their own stories and memories related to historical sites and monuments. It is crucial to provide opportunities for them to participate in discussions and interpretations, as well as to design virtual experiences that evoke emotional and sensory responses [ 35 , 36 ]. Appl. Sci. 2025,15, 1820 3 of 21 Recent research focused on the therapeutic aspects of combining VR and cultural heritage for the elderly who feel lonely, showing that it could become a powerful tool to increase the wellbeing of this age group [37]. VR is also used to increase social interactions, and people can interact with others in a network in the virtual world [ 38 , 39 ]. However, to reach real networked virtual reality solutions, a few challenges need to be addressed, like the capacity of broadband networks, wireless operation, ultra-low latency, client/network access, system deployment, edge computing/cache, and end-to-end reliability [ 40 , 41 ]. In addition, when multiple users are involved and they need to have real-time experiences, more challenges regarding network performance arise [ 42 ]. Apart from the technical limitations, networked VR also allows for more than one user to interact with the system, raising issues of sociality. The opportunities for social interaction and the dynamics of social interactions within such systems are important elements of networked VR [ 43 ]. Depending on the conditions, users can have low-end, inexpensive devices, like Google Cardboards, or high-end expensive ones, like HTC Vive and Oculus Rift [42]. Regarding cultural heritage, networked virtual reality is a relatively underexplored field. Very few works focus on the intersection of cultural heritage and networked virtual experiences. Among the few is the work of Park et al. [ 44 ], focusing on the design and implementation of network VR experiences for the Gyeongju VR Theater. The VR Theater was designed and built to serve as a flexible public platform showcasing VR technology as a novel medium for interactive storytelling. It aimed to present diverse artistic expressions and virtual heritage to the public. To realize this, NAVER employed a distributed microkernel architecture, which allowed for the integration of 3D virtual spaces with various interfaces and applications. As far as older individuals are concerned, virtual reality has been studied for its potential to be used in medical and/or entertainment services. Shao and Lee [ 45 ] gathered qualitative and quantitative data from 114 elderly people on their experiences after using a social VR application. The results indicated that the elderly participants perceived social VR as a means of augmenting their social opportunities through entertainment and interaction. Furthermore, they recognized its potential to address medical needs, including teleconferencing and cognitive decline. Regarding older individuals, cultural heritage, and virtual reality, the field seems to be relatively new and research is not vast. Thus, the present work will focus on collecting content requirements for the design of virtual reality to support the cultural experiences of older people. This is performed within the framework of a research project that wishes to create virtual cultural heritage experiences for older people. The project is called Firefly and is briefly presented below. 2.3. Firefly Project FIREFLY (fostering virtual heritage experience for elderly, https://firefly.athenarc.gr/, accessed on 1 February 2025) seeks to design, develop, and assess optimized versions of Extended Reality (XR) applications related to cultural heritage (CH). Current XR applications in this field are primarily aimed at the average user, often focusing on younger individuals or those comfortable with digital interfaces. In contrast, FIREFLY is dedicated to creating interfaces specifically tailored for the elderly, informed by research utilizing Brain–Computer Interface (BCI) technology, unified electroencephalography (EEG), and eye-tracking. The project focuses on intelligent, real-time modeling of cognitive abilities in older adults, aiming to advance how cultural experiences can be enhanced for this demographic. Ultimately, FIREFLY will foster the development of personalized, cognition-centered solutions and significantly push forward the research in cognitive modeling to improve cultural heritage Appl. Sci. 2025,15, 1820 4 of 21 access for the elderly, including those who are healthy or experiencing mild cognitive impairment (MCI). Being in its first year, FIREFLY currently focuses on selecting rich data from the end users and understanding the qualitative differences between older and younger users’ cognitive processing capacities. In this framework, in the present study, FIREFLY focused on studying aspects of content, and in particular, cultural content, to proceed with the formulation of design guidelines for VR cultural environments. Thus, from all the above, the main research questions of the project and the present study are formed as follows: 1. What type of images should be used with older individuals in virtual experiences? a. How do older people analyze images and what emotions do these images trigger? b. Is sentiment analysis and/or expert analysis adequate in predicting the type of emotions that images will trigger in older individuals? 2. Are there any cognitive alterations when older people interact with historical content presented with the use of technology? 3. How do older people perceive technologies like AR and VR? Are there any concerns about their use? 3. Method To answer the above research questions, 21 people over 65 were invited to participate in the study. In the following section, we present the methodology used, following the APA style methodology reporting structure. Therefore, we first present the study participants, then the materials used (i.e., sentiment analysis tool, images used, and film used), and finally, the procedure followed. 3.1. Participants The Open Care Centers for the Elderly of the Municipality of Patras were contacted for the participation of their members in the study. After discussing with the responsible social workers of the Municipality, explaining the purpose of the study and the methodology to be used, and presenting the ethics approvals and procedures, it was agreed that a group of elders would participate in the study. The social workers explained the need to keep the study duration under 2 to 3 h. On the day of the study (September 2024), 21 people over 65 years of age, all in good health with no or very mild dementia and intact cognitive abilities, came to the premises of the University of Patras, Human–Computer Interaction Lab. 3.2. Sentiment Analysis Web Application Understanding that creating an engaging cultural venue goes beyond simply arranging exhibits or artworks since it requires a deep understanding of the venue’s purpose and the narrative that unfolds within the space, the University of Peloponnese developed a tool for assessing exhibitions’ potential in triggering specific emotional reactions [ 46 ]. Emotions play a crucial role in how visitors perceive and interpret exhibitions’ messages. According to Norman [ 47 , 48 ], emotional responses to objects and environments can influence user experience, which can be applied to cultural experiences. The Sentiment Analysis Web Application (available at http://hydra-6.dit.uop.gr:3000, accessed on 1 February 2025) facilitates curators and museum staff to evaluate the emotional design of their collections and itineraries, helping to identify potential flaws and areas for improvement. This can be achieved through modifications such as adjusting descriptive texts, changing exhibit sequences, or revising the set of exhibits included in the collections. It allows curators to define collections and populate them with exhibits. Sentiment analysis Appl. Sci. 2025,15, 1820 5 of 21 is employed to identify the emotions conveyed by the exhibit texts, and the results are visualized at both the exhibit and collection/itinerary levels. The Sentiment Analysis Web Application analyzes content based on 6 primary emotions, namely anger, happiness, sadness, fear, surprise, and disgust, based on Ekman’s Basic Emotions Theory [ 49 , 50 ]. In addition, the Sentiment Analysis Web Application also estimates the level of arousal and the emotional intensity following the Circumplex Model of Affect, which categorizes emotions along two dimensions: valence (pleasant vs. unpleasant) and arousal (high vs. low ) [ 51 , 52 ]. The Sentiment Analysis Web Application was used here to test the emotional aspects of the content that would be presented to the study participants for 3 main reasons: 1. To make sure a diverse spectrum of emotions is used. 2. To balance the intensity of the different emotions and have similar intensity of negative and positive emotions during the study phase. 3. To find the right order of presentation avoiding the concentration of negative or positive emotions together, allowing a sequence of positive and negative emotional experiences throughout the presentation. To use the Sentiment Analysis Web Application, one can create collections (Figure 1) by inserting exhibits (Figure 2). Appl. Sci. 2025, 15, x FOR PEER REVIEW 5 of 22 set of exhibits included in the collections. It allows curators to define collections and populate them with exhibits. Sentiment analysis is employed to identify the emotions conveyed by the exhibit texts, and the results are visualized at both the exhibit and collection/itinerary levels. The Sentiment Analysis Web Application analyzes content based on 6 primary emotions, namely anger, happiness, sadness, fear, surprise, and disgust, based on Ekman’s Basic Emotions Theory [49,50]. In addition, the Sentiment Analysis Web Application also estimates the level of arousal and the emotional intensity following the Circumplex Model of Affect, which categorizes emotions along two dimensions: valence (pleasant vs. unpleasant) and arousal (high vs. low) [51,52]. The Sentiment Analysis Web Application was used here to test the emotional aspects of the content that would be presented to the study participants for 3 main reasons: 1. To make sure a diverse spectrum of emotions is used. 2. To balance the intensity of the different emotions and have similar intensity of negative and positive emotions during the study phase. 3. To find the right order of presentation avoiding the concentration of negative or positive emotions together, allowing a sequence of positive and negative emotional experiences throughout the presentation. To use the Sentiment Analysis Web Application, one can create collections (Figure 1) by inserting exhibits (Figure 2). Figure 1. Sentiment Analysis Web Tool, collection creation function. Figure 1. Sentiment Analysis Web Tool, collection creation function. Once images are inserted and collections are made (Figure 3), the tool analyzes the images and their descriptions. The tool also provides visualizations of the emotions depicted in the images and analyses of the emotion pathways for the entire collection to create a balanced order of presentation regarding the emotional reactions the images will create. For example, the images presented in the current study followed a specific order. As presented in Figure 4, the polarity analysis of the order of presentation showed that by following this order, positive and negative emotions were spread out and participants would not experience all negative or positive emotions at the same time. Balancing the type of emotional reactions would allow people to recover from possibly strong emotional reactions between images. The presentation order of visual stimuli is crucial and should be considered, as past research has shown the impact of stimulus presentation order on working memory [ 49 , 50 ]. Appl. Sci. 2025,15, 1820 6 of 21 Therefore, the Sentiment Analysis Web Application allows the visualization of the emotion pathway in specific presentation orders (Figure 5), which helped researchers decide on the presentation order. Appl. Sci. 2025, 15, x FOR PEER REVIEW 6 of 22 Figure 2. Sentiment Analysis Web Tool, exhibiting adding function. Once images are inserted and collections are made (Figure 3), the tool analyzes the images and their descriptions. Figure 3. Examples of images and descriptions inserted into the Sentiment Analysis Web Tool. The tool also provides visualizations of the emotions depicted in the images and analyses of the emotion pathways for the entire collection to create a balanced order of presentation regarding the emotional reactions the images will create. For example, the images presented in the current study followed a specific order. As presented in Figure 4, the polarity analysis of the order of presentation showed that by following this order, positive and negative emotions were spread out and participants would not experience all negative or positive emotions at the same time. Balancing the type of emotional reactions would allow people to recover from possibly strong emotional reactions between images. The presentation order of visual stimuli is crucial and should be considered, as past research has shown the impact of stimulus presentation order on working memory [49,50]. Therefore, the Sentiment Analysis Web Application allows the visualization of the emotion pathway in specific presentation orders (Figure 5), which helped researchers decide on the presentation order. Figure 2. Sentiment Analysis Web Tool, exhibiting adding function. Appl. Sci. 2025, 15, x FOR PEER REVIEW 6 of 22 Figure 2. Sentiment Analysis Web Tool, exhibiting adding function. Once images are inserted and collections are made (Figure 3), the tool analyzes the images and their descriptions. Figure 3. Examples of images and descriptions inserted into the Sentiment Analysis Web Tool. The tool also provides visualizations of the emotions depicted in the images and analyses of the emotion pathways for the entire collection to create a balanced order of presentation regarding the emotional reactions the images will create. For example, the images presented in the current study followed a specific order. As presented in Figure 4, the polarity analysis of the order of presentation showed that by following this order, positive and negative emotions were spread out and participants would not experience all negative or positive emotions at the same time. Balancing the type of emotional reactions would allow people to recover from possibly strong emotional reactions between images. The presentation order of visual stimuli is crucial and should be considered, as past research has shown the impact of stimulus presentation order on working memory [49,50]. Therefore, the Sentiment Analysis Web Application allows the visualization of the emotion pathway in specific presentation orders (Figure 5), which helped researchers decide on the presentation order. Figure 3. Examples of images and descriptions inserted into the Sentiment Analysis Web Tool. Appl. Sci. 2025, 15, x FOR PEER REVIEW 7 of 22 Figure 4. Emotion polarity analysis. Figure 5. Ekam emotion pathways. 3.3. Choice of Images A set of images was chosen by a team of experts, including a psychologist and a museum specialist, using the Basic Emotions Theory [51,52], representing basic emotions like anger, happiness, sadness, fear, surprise, and disgust since these emotions seem to be globally recognized and expressed. In addition, these emotions are a combination of positive and negative ones as they are recognized as the primary emotion categories from the Circumplex Model of Affect [53,54]. Overall, 14 images were used. The descriptions of the images are shown in Table 1 in the order of presentation (the actual images are not presented due to copyright issues). Table 1 also describes the main emotion found after the sentiment analysis of the images and the main emotions expected by the psychologist of the study. Figure 4. Emotion polarity analysis. Appl. Sci. 2025,15, 1820 7 of 21 Appl. Sci. 2025, 15, x FOR PEER REVIEW 7 of 22 Figure 4. Emotion polarity analysis. Figure 5. Ekam emotion pathways. 3.3. Choice of Images A set of images was chosen by a team of experts, including a psychologist and a museum specialist, using the Basic Emotions Theory [51,52], representing basic emotions like anger, happiness, sadness, fear, surprise, and disgust since these emotions seem to be globally recognized and expressed. In addition, these emotions are a combination of positive and negative ones as they are recognized as the primary emotion categories from the Circumplex Model of Affect [53,54]. Overall, 14 images were used. The descriptions of the images are shown in Table 1 in the order of presentation (the actual images are not presented due to copyright issues). Table 1 also describes the main emotion found after the sentiment analysis of the images and the main emotions expected by the psychologist of the study. Figure 5. Ekam emotion pathways. 3.3. Choice of Images A set of images was chosen by a team of experts, including a psychologist and a museum specialist, using the Basic Emotions Theory [ 51 , 52 ], representing basic emotions like anger, happiness, sadness, fear, surprise, and disgust since these emotions seem to be globally recognized and expressed. In addition, these emotions are a combination of positive and negative ones as they are recognized as the primary emotion categories from the Circumplex Model of Affect [53,54]. Overall, 14 images were used. The descriptions of the images are shown in Table 1 in the order of presentation (the actual images are not presented due to copyright issues). Table 1also describes the main emotion found after the sentiment analysis of the images and the main emotions expected by the psychologist of the study. Table 1. Descriptions and presentations of images used. Presentation Order Image Name Description Sentiment Analysis Experts’ Expectation 1 Rich and Poor Two people are sitting at a table. The one on the left is obese and well-dressed and has a large amount of food in front of him. The one on the right is skinny and poorly dressed, having a small amount of food. The person on the left takes food away from the person on the right. Anger 26% Disgust 3% Fear 1% Joy 8% Sadness 57% Surprise 5% Anger 2 Forest fire A forest is on fire. A young person stands in front of the fire looking unable to take action or being responsible for starting the fire. Anger 2% Disgust 1% Fear 53% Joy 11% Sadness 3% Surprise 31% Anger Appl. Sci. 2025,15, 1820 8 of 21 Table 1. Cont. Presentation Order Image Name Description Sentiment Analysis Experts’ Expectation 3 Flower garden A beautiful flower garden with arches of red, fuchsia and pink flowers over a neat alley among two lanes of green bushes. Anger 0% Disgust 0% Fear 0% Joy 97% Sadness 1% Surprise 2% Joy 4 Happy baby A happy, smiling baby with blue eyes being playfully covered with a white towel. Anger 0% Disgust 0% Fear 0% Joy 100% Sadness 0% Surprise 0% Joy 5 Family selfie A family with children, parents and grandparents, getting close to each other for a selfie. All members are smiling and looking towards the camera. Anger 0% Disgust 0% Fear 0% Joy 90% Sadness 3% Surprise 6% Joy 6 Wildfire Burnt forest after a wildfire eliminating one million acres. Anger 5% Disgust 2% Fear 6% Joy 34% Sadness 29% Surprise 23% Sadness 7Children into severe famine African children into severe famine, obviously malnourished and underweight, with their bones being visible under their skin. They are stretching their hands, presumably asking for food. Anger 5% Disgust 12% Fear 8% Joy 8% Sadness 17% Surprise 51% Sadness 8 Spider A solifugae-species spider. Anger 2% Disgust 2% Fear 48% Joy 14% Sadness 13% Surprise 21% Fear 9 At the edge A person standing at the edge of a rooftop, high above the ground. High risk of falling. Anger 2% Disgust 1% Fear 83% Joy 3% Sadness 1% Surprise 10% Fear 10 Nazi parade Hitler moving upwards some stairs among Nazi soldiers lining up holding Nazi flags. Anger 6% Disgust 5% Fear 52% Joy 26% Sadness 4% Surprise 7% Fear 11 Jack in a box A Jack in a box happily jumping out of its box. Anger 0% Disgust 0% Fear 1% Joy 24% Sadness 1% Surprise 74% Surprise Appl. Sci. 2025,15, 1820 9 of 21 Table 1. Cont. Presentation Order Image Name Description Sentiment Analysis Experts’ Expectation 12 Floating nail polish bottle An art installation of a very large nail polish bottle floating in the air and spilling its contents on the pavement. Bypassers are staring, curious and entertained. Anger 2% Disgust 1% Fear 8% Joy 64% Sadness 6% Surprise 20% Surprise 13 Eating grasshoppers A person holding a grasshopper between his/her teeth, presumably before eating it. Anger 1% Disgust 7% Fear 84% Joy 2% Sadness 1% Surprise 3% Disgust 14 Highly questionable food serving On a plate there is candy and chocolate mix with barbeque sauce and some random animal’s intestines. Anger 8% Disgust 24% Fear 16% Joy 10% Sadness 4% Surprise 38% Disgust The images were used as input in the Sentiment Analysis Web Application to ensure the presentation of a diverse spectrum of emotions. The analysis showed that, indeed, the images chosen could provoke all 6 basic emotions, as shown in Figure 5. Testing the intensity of the emotions provoked, the Sentiment Analysis Web Application showed that there is adequate fluctuation of emotions. Figures 6and 7show examples of the intensity of emotions for the different images. Appl. Sci. 2025, 15, x FOR PEER REVIEW 10 of 22 Figure 6. Anger intensity for the images used. Figure 7. Sadness intensity for the images used. Testing the order of presentation, the Sentiment Analysis Web Application showed that the order of the presentation of the images maintains a balance between negative and positive images and spreads them throughout the presentation (Figure 4). 3.4. Choice of Film The short film “As a letter to memory” by Michalis Manoussakis was chosen for the reasons below: 1. The short duration of the film is ten (10) minutes. 2. The topic of the film presents the story of a woman (the grandmother of the film’s creator) forced to leave her home after the end of the Greco-Turkish war of 1922 and the refugee crisis that followed. This topic was chosen since many participants are of refugee origin or have lived next to Asia Minor refugees and they are therefore involved directly with the events presented in the short film. 3. The film, created for the exhibition Topoi Atopoi tis Anatolis (translation: Places Unplaces of the East) at the Municipal Art Gallery of Thessaloniki, Greece in 2022, 100 Figure 6. Anger intensity for the images used. Testing the order of presentation, the Sentiment Analysis Web Application showed that the order of the presentation of the images maintains a balance between negative and positive images and spreads them throughout the presentation (Figure 4). Appl. Sci. 2025,15, 1820 16 of 21 5. Threats to Validity The present work is an observational study wishing to inform the design of virtual cultural experiences for the elderly. There are a few limitations with the methodology followed that should be mentioned here, together with possible mitigation efforts. First, the present study cannot create generalizable results due to the limited sample size. In fact, elders from an Open Care Center were invited, implying that people in relatively good health were involved since elders in Open Care Centers go to the Center on their own daily. In addition, and due to the nature of the observational study, there was no control group in the present work. In a future study, an experiment could be set up where some people use new technologies to engage with historical and cultural content and others do not use technology. In an observational study, like the one described here, the Hawthorne effect is also present, implying that there might be biases when people know they are observed. To minimize the effect, during data collection in phase 2, participants were interviewed in a separate room by only one researcher, while the other researchers waited outside. However, the effect remains in such a research setup. In a future study, data could be collected by an application that would record the responses of the participants without the presence of a researcher (although interaction without human presence might feel strange for people in this age group). Another important issue is the selection of images to be presented, their presentation order, and the choice of film. Different images in different presentation orders and a different film might produce different results. Furthermore, the questions used to collect data were open-ended to produce rich qualitative data, but at the same time, they also introduce significant variability, making it difficult at times to quantify the responses. In a qualitative study like this one and analysis of qualitative data, there are also researcher interpretation biases since our preconceptions and expectations might influence the analysis, even though the involved researchers are highly experienced in qualitative research. To balance these biases, future works could use different types of films and images and possibly create/use a taxonomy of images and films with specific characteristics. Finally, during the group discussion phase, the group dynamics might also bias the results, although a group discussion is made for recording group results and does not treat responses as individuals. In addition, the results were not only collected from the group phase but also from phase 2 where participants viewed content on their own and provided responses individually. Overall, the present work presents a first attempt to engage elders with cultural content using cutting-edge technology and, as such, provides the first understanding of possible factors that affect such interactions. Hopefully, future work can build on the present findings and proceed with methodologies that provide more generalizable results. 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, the Appl. Sci. 2025,15, 1820 17 of 21 sample 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 – 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). In addition, heavy head-mounted equipment cannot be easily used with this age group due to its weight but also because it might affect the location and function of hearing aids, vision glasses, etc. It is better to have something to hold like VR cardboard than something to wear like headsets. The current study did not focus on the social potential of VR cultural experiences for the elderly. Considering the slower and serial processing time of older individuals, future works need to focus on studying the balance needed between providing opportunities for socialization through networked VR and keeping cognitive load to a manageable level for people of that age. Although previous works [ 42 ] found that, depending on the conditions, users can have low-end devices or high-end ones, the present study argues for the use of low-end devices like desktop applications and VR cardboards for people over 65 due to usability issues raised during data collection. Finally, regarding procedure requirements for future studies, when working with older people, one needs to allow more time for all processes, including the use of technology. All activities should have a duration of 2 to 3 h with sitting arrangements, and bathrooms should be also close by as most participants explained their importance. In this light, the possibility of having VR experiences from home seems very important if the experience is designed according to older adults’ needs for comfort. Appl. Sci. 2025,15, 1820 18 of 21 Therefore, regarding the design of VR experiences for the elderly, a few guidelines emerged, such as: 1. Involving older individuals in participatory design processes and following accessibility and usability guidelines for content and technology development. 2. Applying technology acceptance models since older individuals are particularly skeptical of the use of new technologies. 3. Using simple graphics and simple images and avoiding unnecessary details and purely decorative elements. 4. Avoiding dark colors. 5. Including positive messages and messages of hope in the VR experiences. 6. Avoiding the use of head-mounted displays and heavy headsets. VR cardboards and/or desktop applications are preferable. 7. Allowing plenty of time for the experiences and making sure there are sitting arrangements and frequent breaks. 8. Creating opportunities for social interactions in VR worlds. The research team will continue working with elders and VR cultural experiences. In particular, the next set of studies will focus on collecting physiological data from elders when exposed to VR cultural experiences, like brain waves. In addition, eye-tracking technology will be also used to study further the findings of the current study regarding the serial processing of image details. In addition, the sentiment analysis tool will be used to further extract participants’ affective profiles. The affective profiles will be used to create balanced group interactions since people with similar affective profiles seem to create better social interactions [56]. Author Contributions: Conceptualization, A.A. and S.S.; methodology, A.A.; software, C.V. and G.K. (Georgios Kantianis); validation, A.A. and C.V.; formal analysis, A.A.; investigation, A.A., C.V. and S.S.; resources, A.A., C.V., G.K. (George Kolokithas) and S.S.; data curation, A.A.; writing—original draft preparation, A.A.; writing—review and editing, A.A. and C.V.; visualization, A.A.; supervision, S.S.; project administration, S.S. and G.K. (George Kolokithas); funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript. Funding: The research project is implemented in the framework of H.F.R.I called “Basic research Financing (Horizontal support of all Sciences)” under the National Recovery and Resilience Plan “Greece 2.0” funded by the European Union—NextGenerationEU (FIREFLY-Fostering vIrtual heRitage Experience For eLderlY, H.F.R.I. Project Number: 15497). Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of International Hellenic University (protocol code 88/2024) for studies involving humans. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: Sentiment Analysis data can be found at http://hydra-6.dit.uop.gr: 3000/list (accessed on 1 February 2025). The datasets from the study participants are not readily available because of Ethics requirements. Requests to access the datasets should be directed to the corresponding author. Acknowledgments: We are grateful to the study participants for a unique and memorable data collection session and their accompanying nurse from the Municipality of Patras (Greece), Plota, for organizing the transportation of the elders and providing valuable knowledge for the management of the workshop. Conflicts of Interest: The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Appl. Sci. 2025,15, 1820 19 of 21 References 1. Bloom, D.E.; Boersch-Supan, A.; McGee, P.; Seike, A. Population aging: Facts, challenges, and responses. Benefits Compens. Int. 2011,41, 22. 2. Nelson, M.E.; Rejeski, W.J.; Blair, S.N.; Duncan, P.W.; Judge, J.O.; King, A.C.; Macera, C.A.; Castaneda-Sceppa, C. Physical activity and public health in older adults: Recommendation from the American College of Sports Medicine and the American Heart Association. Circulation 2007,116, 1094. [CrossRef] 3. Alvares Pereira, G.; Silva Nunes, M.V.; Alzola, P.; Contador, I. Cognitive reserve and brain maintenance in aging and dementia: An integrative review. Appl. Neuropsychol. Adult 2022,29, 1615–1625. [CrossRef] 4. Karst, K.L. Paths to belonging: The constitution and cultural identity. NCL Rev. 1985,64, 303. 5. Shackel, P.A. Pursuing heritage, engaging communities. Hist. Archaeol. 2011,45, 1–9. [CrossRef] 6. Delfa-Lobato, L.; Guàrdia-Olmos, J.; Feliu-Torruella, M. Benefits of cultural activities on people with cognitive impairment: A systematic review. Front. Psychol. 2021,12, 762392. [CrossRef] [PubMed] 7. Why Culture and Education? Available online: https://www.unesco.org/en/about-culture-education (accessed on 26 November 2024). 8. Cominelli, F.; Greffe, X. Intangible cultural heritage: Safeguarding for creativity. City Cult. Soc. 2012,3, 245–250. [CrossRef] 9. Knobloch, U.; Robertson, K.; Aitken, R. Experience, emotion, and eudaimonia: A consideration of tourist experiences and well-being. J. Travel Res. 2017,56, 651–662. [CrossRef] 10. Bekele, M.K.; Pierdicca, R.; Frontoni, E.; Malinverni, E.S.; Gain, J. A survey of augmented, virtual, and mixed reality for cultural heritage. J. Comput. Cult. Herit. 2018,11, 1–36. [CrossRef] 11. Chong, H.T.; Lim, C.K.; Rafi, A.; Tan, K.L.; Mokhtar, M. Comprehensive systematic review on virtual reality for cultural heritage practices: Coherent taxonomy and motivations. Multimed. Syst. 2022,28, 711–726. [CrossRef] 12. Škola, F.; Rizvi´c, S.; Cozza, M.; Barbieri, L.; Bruno, F.; Skarlatos, D.; Liarokapis, F. Virtual reality with 360-video storytelling in cultural heritage: Study of presence, engagement, and immersion. Sensors 2020,20, 5851. [CrossRef] [PubMed] 13. Montagud, M.; Orero, P.; Matamala, A. Culture 4 all: Accessibility-enabled cultural experiences through immersive VR360 content. Pers. Ubiquitous Comput. 2020,24, 887–905. [CrossRef] 14. Banfi, F.; Bolognesi, C.M. Virtual reality for cultural heritage: New levels of computer-generated simulation of a unesco world heritage site. In From Building Information Modelling to Mixed Reality; Bolognesi, C., Villa, D., Eds.; Springer International Publishing: Cham, Switzerland, 2021; pp. 47–64. 15. Antoniou, A. Mixed Cultural Visits or What COVID-19 Taught Us. Computers 2023,12, 133. [CrossRef] 16. Katifori, A.; Antoniou, A.; Damala, A.; Raftopoulou, P. Editorial for the special issue “advanced technologies in digitizing cultural heritage”. Appl. Sci. 2023,13, 5873. [CrossRef] 17. Ch’Ng, E.; Li, Y.; Cai, S.; Leow, F.T. The effects of VR environments on the acceptance, experience, and expectations of cultural heritage learning. J. Comput. Cult. Herit. 2020,13, 1–21. [CrossRef] 18. Trunfio, M.; Lucia, M.D.; Campana, S.; Magnelli, A. Innovating the cultural heritage museum service model through virtual reality and augmented reality: The effects on the overall visitor experience and satisfaction. J. Herit. Tour. 2022,17, 1–19. [CrossRef] 19. De Paolis, L.T.; Chiarello, S.; Gatto, C.; Liaci, S.; De Luca, V. Virtual reality for the enhancement of cultural tangible and intangible heritage: The case study of the Castle of Corsano. Digit. Appl. Archaeol. Cult. Herit. 2022,27, e00238. [CrossRef] 20. Selmanovi´c, E.; Rizvic, S.; Harvey, C.; Boskovic, D.; Hulusic, V.; Chahin, M.; Sljivo, S. Improving accessibility to intangible cultural heritage preservation using virtual reality. J. Comput. Cult. Herit. 2020,13, 1–19. [CrossRef] 21. Theodoropoulos, A.; Antoniou, A. VR games in cultural heritage: A systematic review of the emerging fields of virtual reality and culture games. Appl. Sci. 2022,12, 8476. [CrossRef] 22. Hulusic, V.; Gusia, L.; Luci, N.; Smith, M. Tangible user interfaces for enhancing user experience of virtual reality cultural heritage applications for utilization in educational environment. ACM J. Comput. Cult. Herit. 2023,16, 1–24. [CrossRef] 23. Zhong, H.; Wang, L.; Zhang, H. The application of virtual reality technology in the digital preservation of cultural heritage. Comput. Sci. Inf. Syst. 2021,18, 535–551. [CrossRef] 24. Chong, H.T.; Lim, C.K.; Ahmed, M.F.; Tan, K.L.; Mokhtar, M.B. Virtual reality usability and accessibility for cultural heritage practices: Challenges mapping and recommendations. Electronics 2021,10, 1430. [CrossRef] 25. Cherniack, E.P. Not just fun and games: Applications of virtual reality in the identification and rehabilitation of cognitive disorders of the elderly. Disabil. Rehabil. Assist. Technol. 2011,6, 283–289. [CrossRef] [PubMed] 26. Amorim, J.S.C.D.; Leite, R.C.; Brizola, R.; Yonamine, C.Y. Virtual reality therapy for rehabilitation of balance in the elderly: A systematic review and META-analysis. Adv. Rheumatol. 2019,58, 18. [CrossRef] [PubMed] 27. Bauer, A.C.M.; Andringa, G. The potential of immersive virtual reality for cognitive training in elderly. Gerontology 2020, 66, 614–623. [CrossRef] [PubMed] Appl. Sci. 2025,15, 1820 20 of 21 28. Garcia-Betances, R.I.; Jiménez-Mixco, V.; Arredondo, M.T.; Cabrera-Umpiérrez, M.F. Using virtual reality for cognitive training of the elderly. Am. J. Alzheimer’s Dis. Other Dement.®2015,30, 49–54. [CrossRef] 29. de Bruin, E.D.; Schoene, D.; Pichierri, G.; Smith, S.T. Use of virtual reality technique for the training of motor control in the elderly: Some theoretical considerations. Z. Gerontol. Geriatr. 2010,43, 229–234. [CrossRef] [PubMed] 30. Kami´nska, M.S.; Miller, A.; Rotter, I.; Szyli´nska, A.; Grochans, E. The effectiveness of virtual reality training in reducing the risk of falls among elderly people. Clin. Interv. Aging 2018,13, 2329–2338. [CrossRef] [PubMed] 31. Jeng, M.Y.; Pai, F.Y.; Yeh, T.M. The virtual reality leisure activities experience on elderly people. Appl. Res. Qual. Life 2017, 12, 49–65. [CrossRef] 32. Matsangidou, M.; Solomou, T.; Frangoudes, F.; Ioannou, K.; Theofanous, P.; Papayianni, E.; Pattichis, C.S. Affective out-world experience via virtual reality for older adults living with mild cognitive impairments or mild dementia. Int. J. Environ. Res. Public Health 2023,20, 2919. [CrossRef] 33. Lin, C.X.; Lee, C.; Lally, D.; Coughlin, J.F. Impact of virtual reality (VR) experience on older adults’ well-being. In Human Aspects of IT for the Aged Population. Applications in Health, Assistance, and Entertainment, Proceedings of the 4th International Conference, ITAP 2018, Held as Part of HCI International 2018, Las Vegas, NV, USA, 15–20 July 2018; Zhou, J., Salvendy, G., Eds.; Springer International Publishing: Cham, Switzerland, 2018; Part II 4, pp. 89–100. 34. Syed-Abdul, S.; Malwade, S.; Nursetyo, A.A.; Sood, M.; Bhatia, M.; Barsasella, D.; Liu, M.F.; Chang, C.C.; Srinivasan, K.; Li, Y.C.J. Virtual reality among the elderly: A usefulness and acceptance study from Taiwan. BMC Geriatr. 2019,19, 223. [CrossRef] 35. Chatterjee, H.; Vreeland, S.; Noble, G. Museopathy: Exploring the healing potential of handling museum objects. Mus. Soc. 2009, 7, 164–177. 36. Thomson, L.J.; Chatterjee, H.J. Well-being with objects: Evaluating a museum object-handling intervention for older adults in health care settings. J. Appl. Gerontol. 2016,35, 349–362. [CrossRef] 37. Veldmeijer, L.; Wartena, B.; Terlouw, G.; van’t Veer, J. Reframing loneliness through the design of a virtual reality reminiscence artefact for older adults. Des. Health 2020,4, 407–426. [CrossRef] 38. Rai, A.; Kannan, R.J.; Ramanathan, S. Multi-user networked framework for virtual reality platform. In Proceedings of the 2017 Proceedings of the 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, 8–11 January 2017. 39. Oriti, D.; Manuri, F.; Pace, F.D.; Sanna, A. Harmonize: A shared environment for extended immersive entertainment. Virtual Real. 2023,27, 3259–3272. [CrossRef] [PubMed] 40. Ruan, J.; Xie, D. Networked vr: State of the art, solutions, and challenges. Electronics 2021,10, 166. [CrossRef] 41. Torres Vega, M.; Liaskos, C.; Abadal, S.; Papapetrou, E.; Jain, A.; Mouhouche, B.; Kalem, G.; Ergüt, S.; Mach, M.; Sabol, T.; et al. Immersive interconnected virtual and augmented reality: A 5G and IoT perspective. J. Netw. Syst. Manag. 2020,28, 796–826. [CrossRef] 42. Parthasarathy, V.; Simiscuka, A.A.; O’Connor, N.; Muntean, G.M. Performance evaluation of a multi-user virtual reality platform. In Proceedings of the 2020 International Wireless Communications and Mobile Computing (IWCMC), Limassol, Cyprus, 15–19 June 2020. 43. Schroeder, R. Networked Worlds: Social Aspects of Multi-User Virtual Reality Technology. Sociol. Res. Online 1997,2, 89–99. [CrossRef] 44. Park, C.H.; Ko, H.; Kim, T. NAVER: Networked and Augmented Virtual Environment aRchitecture; design and implementation of VR framework for Gyeongju VR Theater. Comput. Graph. 2023,27, 223–230. [CrossRef] 45. Shao, D.; Lee, I.J. Acceptance and influencing factors of social virtual reality in the urban elderly. Sustainability 2020,12, 9345. [CrossRef] 46. Kantianis, G. Sentiment Analysis for Cultural Venue Interfaces. Bachelor Thesis, Department of Informatics and Telecommunications, University of Peloponnese, Tripoli, Greece, 2024. 47. Norman, D.A. The Design of Everyday Things; Doubleday: New York, NY, USA, 1988. 48. Norman, D.A. Emotional Design: Why We Love (or Hate) Everyday Things; Basic Books: New York, NY, USA, 2004. 49. Xu, X.; Jiang, M.; Yin, H.; Wang, G.; Colzato, L.; Zhang, W.; Hommel, B. The impact of stimulus format and presentation order on social working memory updating. Soc. Cogn. Affect. Neurosci. 2024,19, nsae067. [CrossRef] [PubMed] 50. Silvert, L.; Naveteur, J.; Honoré, J.; Sequeira, H.; Boucart, M. Emotional stimuli in rapid serial visual presentation. Vis. Cogn. 2004, 11, 433–460. [CrossRef] 51. Ekman, P. An Argument for Basic Emotions. Cogn. Emot. 1992,6, 169–200. [CrossRef] 52. Ekman, P. Emotions Revealed: Recognizing Faces and Feelings to Improve Communication and Emotional Life; Times Books: New York, NY, USA, 2003. 53. Russell, J.A. A Circumplex Model of Affect. J. Personal. Soc. Psychol. 1980,39, 1161–1178. [CrossRef] 54. Russell, J.A. Core Affect and the Psychological Construction of Emotion. Psychol. Rev. 1983,110, 145–172. [CrossRef] Appl. Sci. 2025,15, 1820 21 of 21 55. Soren, B.J. Museum experiences that change visitors. Mus. Manag. Curatorship 2009,24, 233–251. [CrossRef] 56. Cheong, J.H.; Molani, Z.; Sadhukha, S.; Chang, L.J. Synchronized affect in shared experiences strengthens social connection. Commun. Biol. 2023,6, 1099. [CrossRef] [PubMed] Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.