## 4 Discussion
### Synoptic Diagrams
#### 4.1.2 Second Diagram (Figure 4): Connecting Discussion to Findings  
The second diagram (Figure 4) is logically connected to the first and illustrates how the study transitions from the findings of the literature review to the discussion. The sequential organization follows a structured approach:  
* Block 5 identifies the emerging recommendations from the overviewed studies as reported in Table 6 (Section 4.3). * Connected to Block 5, Block 6 links to a comparison with the findings of recent Cutting Edge Research moving in the direction of the recommendations as reported in Table 7 (Section 4.4). \begin{table}
\begin{tabular}{c c c} \hline \hline
**Source** & **Recommendation** & **Description** & **Importance** \\ \hline \multirow{8}{*}{\begin{tabular}{c} [PERSON] et al. [11], \\ [PERSON] and \\ [PERSON] [13] \\ \end{tabular} } & \multirow{8}{*}{\
\begin{tabular}{c} Empathy-driven \\ Design \\ \end{tabular} } & \multirow{8}{*}{
\begin{tabular}{c} SASRs (SRs) should not only be functional \\ but also designed to understand and \\ engage with patients emotionally. This \\ means incorporating advanced sensors, \\ algorithms, and AI that can interpret \\ human emotions through facial \\ expressions, voice tone, body language, \\ and even physiological cues. This \\ empathetic capability is essential for \\ creating meaningful interactions, especially \\ for patients with cognitive impairments, \\ dementia, or mental health concerns. By \\ offering emotionally intelligent responses, \\ SASRs can help mitigate feelings of \\ loneliness, provide comfort, and strengthen \\ the emotional bond between robot and \\ patient, improving overall well-being. \\ \hline \hline \end{tabular} } \end{table} 
Table 6: Emerging general recommendations. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Source** & **Recommendation** & **Description** & **Importance** \\ \hline  & & SRs should be tailored to meet the diverse needs of various patient populations. This includes considering the cognitive, emotional, and physical abilities of users, such as children with autism, elderly individuals with dementia, and people undergoing medical treatments that affect their mental or physical states. The design should allow for easy customization, ensuring that SASRs are adaptable to different users’ needs, preferences, and specific medical conditions. & Tailoring SASRs to specific patient populations ensures that the robots can provide relevant support that addresses individual needs, thus enhancing their effectiveness in clinical settings. A user-centered design approach makes ASRs more accessible, reducing the likelihood of frustration or disengagement and improving their therapeutic outcomes. \\  & & \\ \hline  & & SRs are increasingly used in clinical settings, meaning they handle sensitive patient data such as personal information, health records, and behavioral data. To ensure the trust of both patients and healthcare providers, SASRs must be equipped with robust cybersecurity features. This involves adopting encryption techniques, secure data storage, and secure communication protocols to protect patient data from unauthorized access or cyber-attacks. In addition to protecting patient privacy, SASRs should be designed to comply with healthcare regulations such as GDPR or HIPAA. Ensuring cybersecurity also involves providing regular updates and monitoring the robots for potential vulnerabilities to safegu against emerging threats. \\  & & As SASRs are powered by AI, their development must be guided by ethical principles to ensure they act in ways that are beneficial to patients. These robots need to make decisions or interact with patients in ways that promote fairness, transparency, and accountability. \\  & & Algorethics involves ensuring that algorithms powering SASRs are free from biases and are designed with mechanisms for accountability so that the robots’ actions are understandable and can be questioned if necessary.