Etapa 7 Control experimental

should be held save, making the elderly willing to use this product and making them eager to talk.

Solution:​ Information about preferences and location needs to be gathered in order for this system to work. The personal data of the user has to be stored in order with the Dutch law, meaning that it cannot be shared with others and only used if it is needed by the system. The personal data will be protected from danger in this way.

7.5 Discussion

The goal of this project was to reduce social loneliness in daily life of older adults living at home using the Google Home system. This has been conducted in a step-by-step approach, which led to a final design. The project had some implications which need to be discussed.

A State of the Art research and literature review led to the choice of the Google Home system as main technology to use. Research was needed, expert guidance gave a better understanding of loneliness within the elderly community and the usage of the Google Home system. The online survey was answered by 151 respondents, these respondents were divided within 3 different groups. Group 1 (Community nurses) had 122 respondents, group 2 (caregivers) had 8 respondents and group 3

(respondents with elderly in their social circle) had 21 respondents. The reason for this big difference is the fact that BuurtzorgWeb helped in getting the most responses, making this group count the heaviest within the results. A follow-up research could be conducted, which also gets more input from the other two groups via different channels with more into-depth questions.

All of the groups thought that social conversations are needed in order to reduce loneliness, but group 3 was more positive about this thought. It could be that group 1 and 2 are more critical when talking about loneliness, since they actually work with elderly themselves whereas group 3 spends less time with the elderly. Having a social conversation with the Google Assistant was perceived rather neutral, respondents were not sure if this was the best solution, group 3 was however more on the agreeing side than the other two groups. This can again be the cause of group 3 not really working together with the elderly, making them a bit less critical when giving an answer. When asked whether a user would feel less lonely by calling through a social assistant, the average response was absolute, human to human contact is preferred over human to computer contact. In this case however, group 2 was more critical with also a few respondents disagreeing. A possible explanation for this result is that group 2, the caregivers, spend more time one on one with a client. Meaning that their answer is based upon one client's personality.

The results of the online survey and interviews were used as a base for the Ideation and Realisation phase. By connecting the two ideas of social conversations and activation the concept of the Social Activity Agent was created. The decreasing mobility and type of neighbourhood needed to be taken into account. This has been done by asking the user in which part of Enschede they want to conduct the activity: North, East, West or South. For a small town like Enschede it works, however for a big city e.g Amsterdam or Rotterdam this would not work. There the town would have to be split in more areas. Suggestions based upon location (GPS) would be a great solution for this.

Scenario writing and iteration lead to the final conversational scenario. The construction of the Database was conducted with the conversational scenario in mind. Activities were chosen upon popularity and availability in Enschede. This could mean that some activities were not taken into account because they were only given in certain parts of Enschede . In a second version of the prototype, a bigger variety of

activities should be present.

The elderly assessment and functional user testing gave a good understanding of the current status of the prototype. Whether someone would use the Social Activity Agent really depends on the kind of person, some elderly are more interested in technology and gadgets than others. Next to this, going to an activity can be quite tough for some elderly. Possibly the Agent can suggest the user to take a close relative or friend with them.

Overall the results from the user tests were positive, meaning that almost all of the requirements were met except for the Dutch version of the Agent. A bias within the user testing was the fact that some participants pronounced their answers in English not accurately enough. This resulted in the Agent repeating the questions. Next to this, a few correct formulations were not immediately recognized by the Agent. The more the Agent is used within the future, the less these errors will occur. All of the logs and errors can be reviewed, making it possible to keep improving the system. Definitely an option for repeating an answer should be implemented, so that users are able to listen to something over again. Lastly, within the Google Calendar appointment the information present within the database has to be added, making it possible for the users to read the activity information again if needed.

7.5.1 Limitations within the studies

There have been a few constraints within the research, target group and prototype. As mentioned earlier, the amount of respondents within the research was unevenly distributed. This made the average opinion very heavily depend on group 1, the community nurses. For the interviews, only 7 employees were questioned. A general result could be generated, but their personal opinion can be heavily dependent upon personal opinions. The same thing can be said about the elderly assessment, only 6 persons were interviewed in this case. A bigger sample size could have given a better overview of the current situation, this was however not possible due to time constraints.

The research was based upon the most used features of the Google Home system. Other not so well known features could also have led to a final concept for the prototype, but in a completely different way. Other less well-known features can be explored and possibly be implemented, leading to a better Agent. During the realisation of the realtime database, it became clear that there is not one general overview present of the different activities that can be done within Enschede. The researcher therefore created the database herself based upon the conversational scenario, availability of activities within the different neighbourhoods and their overall popularity. This can also be a real big problem for elderly trying to find activities which they can attend in Enschede.

As discussed within the Prototype Realisation, another great possibility is to use the Social Activity Agent on a smartphone or tablet. Users can read what the Agent will be saying, this might be easier in usage than the Google Home. Thereby, there are also suggesting cards available for the users. It was not possible to user test this possibility within the functional user testing due to time constraints, a bigger sample is needed.