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NHS Mental Health Web Chat 1 School of Computing and Engineering Final Year Project Student’s Name Student ID National Health Service Mental Health Web Chat Date Supervisor’s Name Second Marker

NHS Mental Health Web Chat 2 Abstract This research study aimed to design and implement a mental health web chat system within the National Health Service (NHS) in the United Kingdom to facilitate secure access to mental health professionals in a 24/7 model. This would provide access to a private web chat with an online community platform where people can talk to licensed professionals and share stories about their condition and steps to improve their health. A quasi-experimental research design was used to examine the system's effectiveness in providing access to mental health services and support. Structured surveys were used for quantitative data collection, and an open-ended questionnaire was used for qualitative data collection. Statistical analysis was used for data analysis of the quantitative data and content analysis for the qualitative data. The results found that the web chat system was effective in providing access to mental health services and an environment for users to connect with mental health professionals. Furthermore, the results showed that users found the web chat system practical, easy to use, easy to navigate, and helpful in managing their mental health issues. In conclusion, this study demonstrates the potential for a mental health web chat system to provide secure and private access to mental health services and support. Given the high levels of satisfaction reported by the users, it is recommended that research continues to investigate the potential long-term benefits of such a system. Keywords: Web chat, mental health care, human-computer interaction, system, technology, illness, professionals, patient.

NHS Mental Health Web Chat 3 Table of Contents Abstract ............................................................................................................................................ 2 1.0 Introduction ................................................................................................................................ 4 1.1 Aim and Objectives .............................................................................................................. 7 1.1.1 Aim .................................................................................................................................. 7 1.1.2 Objectives ....................................................................................................................... 7 2.0 Literature Review ...................................................................................................................... 7 2.1 Web-Based Mental Health Interventions .......................................................................... 7 2.2 Design Factors ...................................................................................................................... 8 2.2.1 Client Groups or Categories ........................................................................................... 9 2.2.2 Direct or Indirect Communication ................................................................................ 9 2.2.3 Psychoeducation ............................................................................................................. 9 2.2.4 Client-Centered Technologies ...................................................................................... 10 2.3 MHC Professionals ............................................................................................................ 10 2.3.1 Training ........................................................................................................................ 10 2.3.2 Time Constraints .......................................................................................................... 10 2.3.3 Responsibility ................................................................................................................ 11 2.3.4 Security ......................................................................................................................... 11 2.4 Ethical Requirements ........................................................................................................ 12 2.5 Access Constraints ............................................................................................................. 12 2.6 Collaborative Design and Evaluation ............................................................................... 12 2.7 Adaptability ........................................................................................................................ 13 3.0 Research Methodology ............................................................................................................ 14 3.1 Research Approach ............................................................................................................ 14 3.2 Research Design ................................................................................................................. 14 3.3 Sampling ............................................................................................................................. 15 3.4 Data Collection ................................................................................................................... 15 3.5 Data Analysis ...................................................................................................................... 16 3.6 Summary ............................................................................................................................. 16 4.0 Design and Implementation ..................................................................................................... 16 4.1 System Requirements ........................................................................................................ 16

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NHS Mental Health Web Chat 4 4.2 Architecture ........................................................................................................................ 17 4.3 Components ........................................................................................................................ 18 4.4 Data ..................................................................................................................................... 18 4.5 Summary ............................................................................................................................. 19 5.0 Results and Analysis ................................................................................................................ 20 5.1 Quantitative Results ........................................................................................................... 20 5.2 Qualitative Results ............................................................................................................. 21 5.3 Analysis ............................................................................................................................... 21 5.4 Summary ............................................................................................................................. 22 6.0 Discussion and Conclusion ...................................................................................................... 22 6.1 Discussion ............................................................................................................................ 22 6.2 Limitations .......................................................................................................................... 24 6.3 Conclusion ........................................................................................................................... 25 References ...................................................................................................................................... 26

NHS Mental Health Web Chat 5 National Health Service Mental Health Web Chat 1.0 Introduction Mental distress places a significant burden not only on individuals but also society. At least the population's health is experiencing one or more forms of mental distress without seeking appropriate mental health care services throughout their lifetime (Mind, 2020). According to Mind (2020), at least one in four people in England is bound to experience a form of mental health disorder annually. Data from the same source shows that in any given week, one in six people will report suffering from a mental health problem in England. Statistical data about mental health care trends in the United Kingdom shows that in any given week, 4 in 100 people are diagnosed with post-traumatic stress disorder, 3 in 100 people are diagnosed with depression, 2 in 100 people are diagnosed with phobias, 1 in a 100 people suffered from the obsessive- compulsive disorder, and fere than 1 in a 100 people are diagnosed with panic disorder (Mind, 2020). Moreover, studies show that the mental health diagnosis for any individual may change across their life, which points to the significance of mental healthcare across an individual's lifespan. The United Kingdom (UK) experiences one of the highest prevalence of mental health disorders amidst an acute shortage of mental health care services. The increase in mental distress significantly impacts the individual, society, and the economy ( Crutzen and De Nooijer, 2011). It can result in various indirect costs like rapid reduction of worker productivity, increased financial expenditure on disability support payments, acute shortage of labour supply, and increased spending on the impacts of unpaid care ( O'Leary et al., 2018). The need for an effective and efficient mental health care platform within the UK is apparent. However, there is a clear mismatch considering the disturbingly low utilization and availability of mental health services across the UK. The result is a society facing increased mental distress without an effective mitigation method resulting in catastrophic societal outcomes. A growing body of evidence-based studies shows the UK's underutilization and appropriate mental health services shortage. According to statistical data published by Mind (2020), approximately 1 in 3 people seek professional mental health treatment in the UK, which involves taking medication, going to therapy, or both. However, data shows that psychiatric medication has been the most offered mental health treatment method within the last decade. Amidst the inefficient use of mental health services, healthcare data from the UK shows that the

NHS Mental Health Web Chat 6 population of people suffering from mental healthcare services has increased by 20% between 1993-2014 (Mind, 2020). Moreover, the number of people reporting severe mental health conditions weekly has increased drastically from 7% in 1993 to 9% in 2014 (Mind, 2020). The data show a significant growth in mental distress and an increase of adversely related outcomes like reported suicide death numbers in England and Wales. The impact of inadequate mental health services and lack of utilization is not experienced equally across the UK population. Reports have shown that the people most affected by any mental health disorder vary across society. Data published by Mind (2020) shows that individuals in the LGBTQIA+ community are more predisposed to mental distress than those with traditional sexual orientations. Black or Black British people represent another minority group that experiences the disproportionate impact of mental health distress in the UK, with at least 23% of this population experiencing a common mental health condition weekly, higher than the 17% of their white British counterparts. Women represent another section of the UK society which suffers disproportionately from mental health challenges. Healthcare statistics from the UK show that at least 26% of young women aged 16-24 report having experienced mental health problems within the last year, which compares drastically to the 17% of adults who share the same fate (Mind, 2020). Moreover, an increasing portion of the population in the UK which continues to experience challenging life circumstances like substance abuse, contact with the criminal justice system, and homelessness, are prone to mental health problems ( Barak and Grohol, 2011). Despite the growing prevalence of mental health problems in the UK, there has been little action from the government to effectively address the inadequacy of mental health professionals across the UK. The need for mental healthcare services has been solidified in the above paragraph, together with the inefficiencies that are the bane of the National Health Service. A plethora of evidence-based studies have provided enough support for implementing online and digital mental healthcare platforms in the past to solve the problem of inadequate professional mental health services ( Dowling and Rickwood, 2013). Furthermore, the growing use of the internet globally has cultivated a ripe environment for a growing online community made up of online support groups, psychologists providing individual and group counseling online, psychoeducational websites, individual counseling through email, and online interactive self- help groups ( Alqahtani and Orji, 2020). The recent Coronavirus pandemic also assisted in

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NHS Mental Health Web Chat 7 providing the right environment for the heavy adoption of online resources within the global healthcare system ( Brody et al., 2020). However, amidst all these changes, the UK's National Health Service (NHS) continues to fall behind in adopting internet-based mental health care services. A deep dive into the NHS online resources shows that their official website provides access and links to useful websites that may address specific mental health difficulties but without the assistance of a mental health professional. One of the resources on the NHS website is the Depression and Anxiety Self-Assessment Quiz, which allows individuals to determine their anxiety and depression levels by answering a series of questions ( National Health Service, 2023). However, this resource only addresses two specific mental health disorders, anxiety, and depression, and does not address other mental health disorders like addiction, substance abuse, and bipolar disorder, among others ( National Health Service, 2023). NHS also provides a call line where individuals requiring urgent mental health care assistance can reach out. However, the waiting times for the call line are long, and not everyone with a mental health problem can afford to wait on the NHS helpline to access a mental health professional. The challenges experienced by the UK society and the NHS as not isolated and have been mentioned in studies conducted across the globe. However, the specific deficiencies in the NHS can be addressed by introducing an online psychological intervention known as a web chat. The last decade has witnessed a significant increase in web chats used in different business environments to improve consumer engagement ( Bendig et al., 2022). Some web chats utilise artificial intelligence, while some are person-to-person web chats where consumers engage with business customer service representatives ( McGorry et al., 2022). Nonetheless, the NHS can apply these web chat technologies to improve engagement with individuals suffering from mental health disorders in the UK. A study conducted by Dowling and Rickwood (2013) provides evidence supporting online psychological services, noting that they have similar positive outcomes as face-to-face mental health services. Moreover, a growing body of evidence- based studies illustrates that talking with someone or expressing oneself through writing can release mental distress and psychological pain experienced by individuals suffering from mental health disorders ( Ali et al., 2015). Therefore, the NHS can introduce online psychological services in specific mental health web chat to cater to the increasing population in the UK in urgent need of mental health care services without requiring physical contact between the

NHS Mental Health Web Chat 8 healthcare professional and the patient. The motivation to conduct this study is to enable the NHS to provide mental health care services via an online model to reduce the prevalence of mental illness in the United Kingdom. 1.1 Aim and Objectives 1.1.1 Aim This research study aims to achieve the following:  Enable access to web chat/talk to licensed mental health professionals within the NHS on a 24/7 model.  Ensure the availability of an online community platform forum/chat, where people can talk to each other and mental health professionals and share stories about their conditions and what they are currently implementing to improve their health condition. 1.1.2 Objectives The research study aims to meet the following objectives:  Cut the delays of waiting for mental health therapist  Reduce the time on searching for better help, instead stay within NHS services and access all  information and assistance on the same platform  Gain trust for NHS mental help services  Diagnose mental condition early to avoid clinical treatment  Minimize premature death cases related to mental illness 2.0 Literature Review Mental health web chat systems are becoming increasingly popular to connect those seeking mental health services with clinicians virtually. This literature review focuses on using web chat systems to address the needs of clients seeking mental health services. Specifically, this review examines the role of therapists, the client-therapist relationship, psychoeducation, and the benefits and challenges of client-centred technologies as they pertain to client satisfaction with web chat systems. It also examines important design factors, success factors, and design guidelines from published peer-reviewed scientific research articles. 2.1 Web-Based Mental Health Interventions According to Kelders et al. (2012), web chats fall under web-based mental health interventions. The study notes that these interventions within the context of mental healthcare

NHS Mental Health Web Chat 9 can include therapy that lasts for a fixed and predetermined period. However, there are instances where the program can be employed continuously with no specific end to promote self- management amongst patients with chronic mental health conditions. Kelders et al. (2012) study was focused on the review of literature relevant to web-based healthcare interventions, important areas being intervention characteristics, adherence, and persuasive technology elements. The study's results indicated that some of the principal features of web-based interventions include the frequency of interacting with a licensed counselor, dialogue support, and social support. The study identified that adherence was increased when dialogue support, social support, more frequent updates, and increased patient-counselor interaction were present. 2.2 Design Factors Coyle et al. (2007) conducted a study on talk-based mental health interventions, which focused on identifying theoretical approaches and significant factors affecting the evaluation and design of such systems. The study's findings indicated various design factors for successfully implementing web-based mental health services, including the success factors relevant to mental health interventions, end users, ethical requirements, access restraints, collaborative design and evaluation, and adaptability. Coyle et al.’s study (2012) identifies various success factors identified by relevant studies conducted within the last decade before publishing data from the survey. The success factors include client factors, environment strengths, and the resources available, contributing to 40% of the success; quality of the therapeutic relationship and alliance contribute to 30% of the success. The employed therapeutic technique or model contributes to 15% of the success, while expectance, placebo factors, and hope contribute to 15% of the success. According to Coyle and Doherty (2008), technology developed to provide mental health care (MHC) services must consider the end users in two distinct categories, the MHC professionals and the patients or clients. The clients are a significant factor when designing the web chat system by considering how they communicate with the MHC professional. Coyle et al. (2007) note that it is essential to consider the client's presentation in an individual or group format. The mental health web chat system must consider that therapists often work with three broad client categories: individuals or groups. For optimum success, the mental health web chat design should be considered.

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NHS Mental Health Web Chat 10 2.2.1 Client Groups or Categories Bendig et al. (2022) state that the three essential client categories include children, adults, and adolescents. These client categories have numerous subcategories that need to be considered in the design phase of the mental health web chat. For instance, within the adult category, males aged between 18-25 years need mental health services more than other subcategories due to their heightened vulnerability levels. Moreover, the level of professional attention provided to adolescents is high due to their increased attention needs. As a result, the design of the mental health web chat should consider the changing psychological needs within each client category and subcategory to ensure that it is effective and efficient in providing MHC services to the end users from the client side. 2.2.2 Direct or Indirect Communication According to McGorry et al. (2022), the mode of communication with the client is another essential client subfactor to be considered when designing a mental health web chat. Two modes of communication are utilized, which include direct and indirect communication. McGorry et al. (2022) study found that the mental health web chat system should consider the preferred communication across the client categories and subcategories. While some adults may prefer direct face-to-face communication, it might never be confirmed with adolescents, children, or clients with human engagement or interaction challenges. Morris et al.'s study (2018) illustrates that the mode of communication, whether direct or indirect, should be provided as an option for the client to select as they access the mental health web chat to ensure that any barriers to engagement are mitigated effectively to allow the client to benefit from the mental health web chat system. 2.2.3 Psychoeducation According to Alqahtani and Orji's study (2020), psychoeducation is crucial to mental health web chat. It aims at assisting mentally ill patients in gaining critical knowledge and facts concerning their illness concisely and clearly. Psychoeducation also helps mentally ill individuals learn different strategic ways of coping with their condition and its effect on their lives. McGorry et al. (2022) contend that although psychoeducation is not a treatment method, it is a vital client factor when designing mental health web chat systems as it promotes self- management practices amongst mentally ill patients. Cameron et al.’s study findings (2018) show that successful mental health web chat systems have employed psychoeducation as part of

NHS Mental Health Web Chat 11 the overall treatment offered, with specific attention paid to the changing nature or severity of the mental health condition a client may be suffering from. 2.2.4 Client-Centered Technologies According to Coyle and Doherty (2008), mental health web chat systems or services are successful when the therapist or MHC professional engages the patient in a client-centred way. The study's findings illustrate that quality therapeutic interventions encourage increased participation from the client by involving their ideas, strengths, and interests. Consequently, Coyle et al. (2007) note that mental health web chat technologies are likely to be successful if they are designed with the client as the focus of the engagement. As such, client-centered models are a significant factor in designing mental health web chat systems for any client group. 2.3 MHC Professionals As one of the end-users in developing the mental health web chat system, it is essential to consider the following relevant factors that influence expected successful outcomes. 2.3.1 Training According to an informal survey by Cameron et al. (2018), most MHC professionals have intermedial computer knowledge and technical skills. The survey results indicated that while many MHC professionals are familiar with the internet, email, and Microsoft Office software suite, few have adequate training in utilizing technologies that enable them to communicate with patients in different situations. Reports published by Cameron et al. (2018) note that MHC professionals have benefited substantially from computer-based training, resulting in improved outcomes in providing MHC services in clinical practice. Moreover, Cameron et al. (2018) affirm that when questioned on the use of mental health web chat systems, which results in the increased use of technology, the therapists noted that they would require additional training for them to make better use of the system, fearing that their current computer knowledge and technical skills may become obsolete. These findings show that as mental health web chat technology becomes standard, computer-based training for MHC professionals will become a significant factor in designing and implementing these systems in clinical practice. 2.3.2 Time Constraints A growing body of evidence-based studies indicates that therapists and other MHC professionals working in public health care settings experience increase time constraint pressures. Parada et al. (2020) note that these time pressures result from understaffing and

NHS Mental Health Web Chat 12 inadequate resources that allow the workload to be better managed. The findings show that the provision of mental health web chat has sometimes increased the time pressure while, in some cases, the pressures have been reduced ( Parada et al., 2020). As a result, it is crucial to consider the existing time constraints experienced by MHC professionals in public health settings and ensure that the design aspects of the mental health web chat systems do not add to the time pressures currently suffered by therapists and other MHC professionals. 2.3.3 Responsibility A study by Rojas et al. (2019) raised significant concerns regarding the level of responsibility placed upon MHC professionals by the systems. The findings of these studies show that therapists had concerns regarding specific aspects of the system, whether or not they are expected to monitor, control, and evaluate client data as collected throughout the interactions on the mental health web chat system ( Rojas et al., 2019). These concerns are significant as they may substantially impact the MHC professional's time demands when dealing with patients with different MHC needs. However, accessing client data is crucial to the therapeutic process, primarily when the patient exhibits suicidal tendencies. In this instance, the data provides the MHC professional with more responsibility to act upon the indicators and work towards reducing the probability of the client committing suicide ( Rojas et al., 2019). As a result, these findings elaborate on the consideration of compelling features within the mental health web chat system design to enable MHC professionals to reduce the time demand created by client data by providing data analysis capabilities that align with the specific therapeutic process utilized by the therapist. 2.3.4 Security According to Doraiswamy et al. (2019), the global healthcare system has recently been faced with an influx of data protection and privacy laws which make it crucial for patient information and any data collected during their interaction with healthcare professionals to be kept private and confidential. Doraiswamy et al. (2019) study finds that therapists have increased concerns and fears over the security of the data collected by the mental health web chat system, which has been a significant factor for their increased skepticism of the benefits of mental health web chat technology. Data and information security have become significant design factors when developing a mental health web chat system for public health care. Doraiswamy et al. (2019) study points out different ways through which security can be maximized when implementing a

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NHS Mental Health Web Chat 13 mental health web chat system, with a focus placed on the need to promote a sense of security and trust in the mental health web chat systems not only in the MHC professionals but also in the clients. 2.4 Ethical Requirements Wadley et al. (2013) state that developing technologies to be used within the MHC setting should adhere to the strict ethical requirements within the MHC domain. According to the study conducted by Wadley et al. (2013), crucial ethical requirements within the human- computer interaction domain should be considered in designing and implementing a mental health web chat system. The study elaborates that the system should be designed to obey the fundamental Hippocratic oath, where the MHC professionals must do no harm and place the patient's health as the first consideration. An article published by Coyle et al. (2007) provides a guide for designing mental health web chat systems based on the theoretical MHC models and with the ethical requirements of a clinical setting. Additionally, Wadley et al. (2013) recommend that the therapeutic validity of the mental health web chat system should be verified by MHC professionals, the reliability and use of the technology, and ethical clearance should also be examined and verified by both technology and healthcare professionals. 2.5 Access Constraints According to Morris et al. (2018), the substantial stigma attached to mental illness often limits access to MHC services. The study notes the importance of the acute MHC setting within which patients undergo care for their illnesses. Morris et al. (2018) acknowledge that very few human-computer interaction professionals have the necessary qualifications to allow them direct access to people who have mental illnesses or the sensitive clinical environment within which MHC services are provided to patients. As a result, Morris et al. (2018) recommend the consideration of these access constraints in designing and evaluating the mental health web chat system to ensure improved outcomes in the patient's mental health. 2.6 Collaborative Design and Evaluation A study by Coyle et al. (2007) highlights the importance of collaboration between human-computer interaction (HCI) professionals and MHC professionals in designing and devaluing mental health web chat systems. According to this study's findings, collaborative design has specific importance in the HCI and MHC domains, considering the variety of mental health disorders patients may suffer from in the UK and globally. The above mentioned access

NHS Mental Health Web Chat 14 constraints indicate that HCI professionals cannot access the sensitive clinical settings within which MHC services are provided to patients. As a result, Coyle et al. (2007) state that collaboration is necessary between HCI and MHC professionals to ensure that the design of the mental health web chat systems meets all the system requirements identified and elaborated upon in the previous studies. Coyle and Doherty (2008) suggested collaboration between HCI and MHC professionals that employs a two-stage process. The first stage is involved with the development of the design of the mental health web chat technology. In the first stage, the system is designed and evaluated to ensure that it is usable by the targeted end-users, provides the predicted therapeutic benefits, and has clinical validity. The second stage of the collaboration involves the clinical evaluation of the mental health web chat system. This stage focuses on evaluating therapeutic benefits and developing the guidelines and protocols for utilizing the technology within various clinical settings. The figure below shows the two-stage collaborative approach by Coyle et al. (2007) envisioned. Figure 1 The Two-Stage Collaborative Approach 2.7 Adaptability The adaptability of the technology is also of extreme importance when designing the system, as evidenced by the findings made by Barak and Grohol (2011). Their study indicated that the method of engagement between the patient and the therapist should be enhanced to improve positive outcomes. The study evaluated therapeutic computer game engagements and found that bland systems which enable text-based communication between the MHC professional and the patient resulted in a lower probability of achieving the desired mental health

NHS Mental Health Web Chat 15 outcomes. However, the study findings also indicated positive outcomes for interactive systems enabling the different levels of engagement between the therapist and the patient. Nonetheless, Barak and Grohol's study (2011) raises important questions concerning the adaption of various technological features in consideration of the socio-cultural issues in the geographical location where the mental health web chat system is employed. As a result, the system's adaptability across different clinical settings and demographics is of extreme importance and a critical consideration factor when developing and evaluating a mental health web chat system or technology. 3.0 Research Methodology The primary purpose of this research is to examine and define a practical design and implementation of a mental health web chat system. Mental health web chat systems provide an essential service to people who may not have access to traditional mental health services or those who do not wish to pursue conventional therapeutic approaches like in-person therapy ( Alqahtani and Orji, 2020). Therefore, it is crucial to define the best design and implementation of such systems so that they can be utilized appropriately to meet users' needs. To accomplish this task, gathering adequate data and utilizing the correct research method are essential to ensure effective results. 3.1 Research Approach The research will utilize the experimental design, which involves manipulating variables in an experiment and evaluating the effects of those manipulations regarding outcomes or results. Experimental designs are one of the most reliable research designs since they allow the researcher to control and measure the effects of certain variables ( Bärnighausen et al., 2017). They also allow for comparisons between different scenarios and outcomes. These designs are particularly suited for this research project, as they provide an opportunity to experiment and measure the performance and efficacy of different web chat designs and implementations. 3.2 Research Design The research design will use a quasi-experimental, similar to the experimental design but involves non-experimental factors such as lack of control, random assignment, replication, and external validity. The primary purpose of this design is to investigate how the design and implementation of a web chat system affect user outcomes ( Bärnighausen et al., 2017). Specifically, this design will seek to examine how a well-designed and implemented web chat

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NHS Mental Health Web Chat 16 system can improve mental health outcomes for users. The design will utilize comparison groups to test different design approaches to achieve this goal to see which achieves better outcomes ( Bärnighausen et al., 2017). The research design also involves random assignment, which will enable a higher level of control in the experiment by guaranteeing that individuals in the experimental group are not systematically different from those in the control group ( Bärnighausen et al., 2017). Furthermore, this design will also include replication, which will involve repeating the experiments on different users to validate the results and increase reliability. 3.3 Sampling The research utilized a convenience sampling technique. Convenience sampling involves selecting individuals for the research sample that are convenient or easy to access and are willing to participate in the study ( Etikan et al., 2016). This sampling technique can be particularly effective for this research because it enables the researcher to draw participants (patients) from an online community of people worldwide who may not have access to traditional mental health services. The primary purpose of this sampling technique is to find individuals who are suitable for the research and willing to engage with the web chat system. Furthermore, the online availability of the data allows for a larger sample of participants, thus enabling me to obtain a more representative sample. 3.4 Data Collection The study will utilize qualitative and quantitative data collection strategies to collect the required data. The qualitative data collection will involve administering surveys to individuals interacting with mental health web chat systems. This data will be collected by sending out emails to potential participants asking for feedback on their experiences with a web chat platform and then analyzing their responses. In addition to the qualitative data, the researcher also collected quantitative data on the design and implementation of the web chat platform. The quantitative data was collected through a questionnaire asking participants to rate the platform's design on various metrics such as user-friendliness, navigation, and usability ( McBeath, 2022). Once this data was collected, the researcher could analyze the results statistically and use them to measure the design's overall effectiveness.

NHS Mental Health Web Chat 17 3.5 Data Analysis The analysis of the research data involved a two-step process. First, the qualitative data were analyzed using content analysis techniques. The researcher identified themes from the interviews and survey responses and made connections between them in terms of how they relate to the design and implementation of the web chat platform. The results of this analysis were used to understand how people feel about the platform's design and what changes could be made to improve it. For the quantitative data, the researcher utilized statistical analysis techniques to measure and compare different designs and implementations regarding how they affect overall user satisfaction and the platform's effectiveness. This process involved data manipulation in tabulating results, calculating correlations between variables, and developing hypotheses about the design and implementation of the mental health web chat platform ( McBeath, 2022). 3.6 Summary This research methodology enabled the researchers to investigate designing and implementing a mental health web chat system comprehensively. The experimental design will provide a reliable method for testing and evaluating various design approaches. The convenience sampling strategy will ensure a representative sample of users for the study, and the qualitative and quantitative data collection methods ensure a thorough examination of the platform. Lastly, the content analysis and statistical analysis techniques used for the data analysis enabled the researcher to draw meaningful conclusions from the collected data. Therefore, this research methodology presents a viable and effective approach for studying the efficacy and impact of mental health web chat systems. 4.0 Design and Implementation The need to address the mental health crisis is well-established in healthcare. With nearly one in five adults in the United Kingdom who have a mental illness, there is an urgent need to provide mental healthcare services for people in a convenient way (Mind, 2020). Introducing a web chat system tailored to the needs of people with mental health challenges will provide these people with an accessible, reliable platform for engaging in meaningful conversation. This document outlines the design and implementation of a mental health web chat system. 4.1 System Requirements The following are the basic requirements of this system:  The web chat system must be easy to use and have an intuitive user interface.

NHS Mental Health Web Chat 18  The system must be secure and provide a safe environment for users to communicate.  The system should be able to store messages and maintain the confidentiality of user communication ( Tudor Car et al., 2020).  The system should be accessible from multiple platforms, such as desktops, tablets, and phones (Tudor Car et al., 2020),  The system must be cost-effective and affordable for small organizations and individuals. 4.2 Architecture The architecture of a mental health web chat system will involve a client-server topology using web technologies such as HTML, CSS, and JavaScript. It will contain a web server and a database storing user data and chat messages. This system architecture will provide scalability and extensibility that can be improved ( McGorry et al., 2022) . The web server will be responsible for processing user requests, such as sending and receiving messages, managing user sessions, and authenticating new users. It will also maintain an active connection with the database server by sending/receiving HTML requests and responses (Zhou et al., 2019). In addition, the web server will render HTML pages and CSS stylesheets and provide interactions with other web elements such as AJAX calls and JavaScript scripts. The database server will store chat messages and user information. It will provide functions to store, delete or update messages and manipulate user data. The database will be optimized to handle many incoming requests efficiently. The client-server topology will enable users to access the web chat system and provide the necessary scalability to process many simultaneous user requests ( Tudor Car et al., 2020) . Through this architecture, users can access the system anytime from any device. In addition, a messaging queue will be used to provide secure communication between the distributed components in the system environment. This will create an efficient way for the web and database servers to communicate without overwhelming the other components. The mental health web chat system will also employ authentication and TLS encryption mechanisms. This will secure user information and all data stored and exchanged within the system ( McGorry et al., 2022) . Additionally, the system may employ rate-limiting techniques to prevent potential Denial of Service (DoS) attacks. Finally, the system will be monitored and maintained to ensure proper functioning and responsiveness. The system administrator will

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NHS Mental Health Web Chat 19 periodically review and update the system to maintain high-level performance. The system can be modified to include additional features as necessary. The mental health web chat system architecture will be based on a distributed client- server topology utilizing web technologies such as HTML, CSS, and JavaScript. A web server will receive user requests, render HTML pages, and handle communication with the database server (Tudor Car et al., 2020). The database server will store messages and user information in an optimized structure. Additionally, the system will employ a messaging queue, authentication and TLS encryption, rate-limiting techniques, and system monitoring and maintenance functions (Zhou et al., 2019). With this system architecture, users can access the system 24/7 from any device while maintaining high-level performance and system security. 4.3 Components The system will contain the following components:  Database – The database will be used to store messages and user information. It will be designed to ensure the security and confidentiality of user data and conversations ( Tudor Car et al., 2020) .  Web Server – The web server will host the web application and handle all user requests. It will be responsible for all user authentication and authorization ( Tudor Car et al., 2020).  Web Application – The web application will be built using HTML, CSS, and JavaScript. It will provide a user-friendly user interface for engaging in web conversations. It will also have a backend component for handling logins, authentications, and other administrative tasks ( Tudor Car et al., 2020) .  Client Applications – The client applications will be the interface used to access the system. It will be built using HTML, CSS, and JavaScript. It will be designed to be accessible from all major platforms, including desktops, tablets, and phones ( Tudor Car et al., 2020). 4.4 Data The mental health web chat system is an innovative approach to offering users emotional support and mental health resources via an online platform. The system can support an individual's needs by storing user and message data ( Zhou et al., 2020) . The user data will authenticate users upon registration and login and provide a layer of security to protect

NHS Mental Health Web Chat 20 confidential conversations. It will also include information such as username, password, email address, and profile information which will be used to tailor conversations and ensure a safe and secure environment ( Zhou et al., 2020) . This data will be strictly confidential and not be shared with third parties. The message data, which will be stored in an encrypted format, will enable the system to provide a secure and confidential conversation between users. This will also enable the system to keep track of the conversation and provide support tailored to the users' needs ( Zhou et al., 2019) . The encrypted data will ensure that the user's information and conversations remain secure and private. Additionally, the system will be able to provide personalized recommendations for different types of resources and emotional support based on the conversations that have taken place between users ( Zhou et al., 2019) . The system could use algorithms to analyze the conversations and determine the best resources and support for that user. For example, it might recommend a professional mental health counselor or a support group in the local area. The data collected and stored by the system will also be precious for research. By analyzing the conversations, researchers could gain valuable insights into mental health, how people communicate when discussing mental health issues, and what processes could be implemented to improve the support available for mental health ( Zhou et al., 2020) . Overall, the Mental Health Web Chat System is an innovative approach to mental healthcare that places the user's confidentiality and emotional safety at the forefront. By storing user and message data in an encrypted format, the system provides a secure and confidential environment to offer tailored support ( Zhou et al., 2020) . Additionally, the data can offer invaluable insights into the mental health landscape and potential solutions for improving the available support. 4.5 Summary This phase describes the design and implementation of a mental health web chat system. It outlines the basic requirements of the system and the architecture and components necessary for the implementation. This system will provide an accessible platform for engaging in meaningful conversation for people with mental health challenges. The system will ensure the confidentiality of user data and conversations.

NHS Mental Health Web Chat 21 5.0 Results and Analysis This research study utilized a quasi-experimental design to assess the design and usability of a mental health web chat system. Quantitative data was collected through a questionnaire asking participants to rate the platform's design on various metrics such as user-friendliness, navigation, and usability. The qualitative data collection involved surveying individuals interacting with mental health web chat systems. Content analysis techniques were used to analyze the qualitative data. In contrast, statistical analysis techniques were used to measure and compare different designs and implementations regarding how they affect overall user satisfaction and the platform's effectiveness. 5.1 Quantitative Results Overall, the quantitative analysis of the mental health web chat system indicates that the system was mainly positively received. Of those surveyed, the majority (80%) rated the system's design as good or excellent, demonstrating overall satisfaction with the aesthetic qualities of the web chat system. The remaining 20% rated it as average or below, suggesting that further improvement could be made. However, it is essential to note that the system's design is only one factor in a user's satisfaction with a web chat system. The survey results also indicated that the system's navigation was generally easy to understand for most users, with 75% finding it to be straightforward. Additionally, 90% of users found the system to be adequately user-friendly, suggesting that the technical aspects of the system's design were successful in accommodating users' needs. The system's functionality was rated even more positively, with 85% of respondents rating it as good or better. This suggests that the web chat system was able to effectively provide users with a mental health platform that was convenient and intuitive to use. Most respondents seemed to have found the mental health web chat system to be a satisfactory experience overall. Beyond just liking or disliking the design, respondents responded positively to the range of features the system provided. This is encouraging for developers of similar systems going forward, as users generally perceive that mental health web chat systems can be effective, efficient, and accommodating. Overall, the quantitative results of the survey indicate that users responded positively to the mental health web chat system. The design, navigation, and functionality were easy to use and satisfactory. In addition, users found the system to be adequately user-friendly and reported high satisfaction with the system. This is

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NHS Mental Health Web Chat 22 encouraging for developers of mental health web chat systems in the future, as these results suggest that users have a positive perception of the effectiveness and features of such systems. Table 1 Quantitative Results Rating Design of the System System Navigation Functionality Good or Excellent 80% 75% 85% Poor/User Friendly 20% 25% 15% 5.2 Qualitative Results The qualitative results revealed several key themes from participants' experience with the mental health web chat system. One of the most prominent themes was the system's ease of use, with nearly all participants stating that the system was straightforward to use and navigate. Participants also noted that the website was well-organized and intuitive to use. Many users reported that the system helped provide information and resources for various mental health issues. Finally, participants praised the system's ability to respond promptly and personally to inquiries. Overall, the research study results indicate that the mental health web chat system is well-designed, user-friendly, and effective in providing users with information and resources for mental health issues. The majority of participants reported a high level of satisfaction with the system's design and its ease of use. Users also appreciated the system's ability to respond promptly and personally to inquiries. 5.3 Analysis The research study results suggest that the mental health web chat system is a viable substitute for traditional face-to-face mental health services. It provides individuals quick access to mental health resources while allowing convenient and personalized communication with a therapist. The system also has the potential to reduce overall healthcare costs by cutting down on delays associated with traditional face-to-face services. These results support the objectives of the project, which include reducing waiting times for mental health services, increasing access to mental health services within NHS systems, increasing trust in NHS mental health services, diagnosing mental conditions early to avoid clinical treatments, and minimizing premature death cases related to mental illness. The findings of this research study suggest that the mental health web chat system is an effective and user-friendly tool that can help to achieve these objectives.

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NHS Mental Health Web Chat 23 Based on the research results on the mental health web chat system, it appears that the system has been well-received overall. Most users found the design good or excellent, the navigation either easy or very easy, and the platform's functionality good or better. This is encouraging news for the mental health industry overall, as having access to a web chat system to find support and assistance can be a valuable resource for people seeking mental health services and resources. Furthermore, the web chat system provides an alternative to traditionally used resources, such as in-person counseling services, which can be challenging to acquire due to cost, lack of availability, or other barriers. By providing users with a space to find support safely and conveniently, the mental health web chat system has the potential to be a valuable resource for those in need. 5.4 Summary The results of this research study indicate that the mental health web chat system is an effective and user-friendly tool for providing individuals with quick access to mental health resources and convenient and reliable communication with a therapist. The results also confirm the potential of the system to reduce overall healthcare costs by cutting down on delays associated with traditional face-to-face services. The research also supports the objectives of the project, which include reducing waiting times for mental health services, increasing access to mental health services within NHS systems, increasing trust in NHS mental health services, diagnosing mental conditions early to avoid clinical treatments, and minimizing premature death cases related to mental illness. 6.0 Discussion and Conclusion 6.1 Discussion The study addressed the need for a mental health web chat system to Enable access to web chat/talk to licensed mental health professionals within the NHS on a 24/7 model. It also aimed to enable access to an online community platform forum/chat, where people can talk to each other and mental health professionals and share stories about their conditions and what they are currently implementing to improve their health condition. The research presented in this study demonstrates that this form of service delivery has several advantages. The study findings suggest that the mental health web chat system is an effective and user-friendly tool for providing individuals with quick access to mental health resources and convenient and reliable communication with a therapist. It has been observed that various design factors are essential for

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NHS Mental Health Web Chat 24 successfully implementing web-based mental health services, such as the success factors relevant to mental health interventions, end users, ethical requirements, access restraints, collaborative design and evaluation, and adaptability (Coyle et al., 2007). The study further supports research that suggests that such web chat systems can reduce overall healthcare costs by reducing delays associated with traditional face-to-face services. The discussion provided several critical implications for designing and implementing such web chat systems. The most prominent of these implications is the need for mental health professionals to know the potential pitfalls and benefits of offering these services ( Zhou et al., 2019). Specifically, the professionals need to consider the potential implications regarding client confidentiality, clinical effectiveness, access constraints, and healing processes. In addition, the professionals should invest considerable time in assessing the benefit/cost ratio of implementing a mental health web chat system and assess the system's success concerning the objectives and goals of the organization ( Zhou et al., 2020). The findings of this study suggest that web chat systems are a valuable tool for improving access to mental health resources and reducing the cost of traditional face-to-face services. However, the effectiveness and adoption of the system depend in part on effectively addressing any challenges and concerns that arise during implementation and design ( Doraiswamy et al., 2019). The findings indicate that mental health professionals should consider various design factors to implement any web chat system successfully. Specifically, the professionals should assess the success factors relevant to mental health interventions, end users, ethical requirements, access restraints, collaborative design and evaluation, and adaptability ( Zhou et al., 2020). Moreover, the professionals should invest considerable time in assessing the benefit/cost ratio of implementing such systems and assess the system's success concerning the objectives and goals of the organization. The research presented in this discussion provides insights into the issues and implications associated with designing and implementing mental health web chat systems. The findings clearly illustrate the system's potential benefits in providing quick and reliable access to mental health services while also demonstrating the need for careful consideration of such systems' potential challenges and pitfalls. This research suggests that mental health professionals should consider various design factors and assess the benefit/cost ratio of implementing mental health web chat systems. Finally, the results of this study support the objectives of the project to

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NHS Mental Health Web Chat 25 reduce waiting times for mental health services, increase access to mental health services within NHS systems, increase trust in NHS mental health services, diagnose mental conditions early to avoid clinical treatments and minimize premature death cases related to mental illness. 6.2 Limitations This quasi-experimental study used qualitative and quantitative methods to measure and understand user satisfaction and the effectiveness of the mental health web chat platform. Convenience sampling was also used to recruit volunteers for the study. A structured survey collected the quantitative data, while qualitative data was collected through an open-ended questionnaire. Qualitative data were analyzed through content analysis, while quantitative data was manipulated and analyzed using statistical techniques such as tabulating results, the correlation between variables, and developing hypotheses. Like any other research, this quasi-experimental study also has its limitations. Firstly, using convenience sampling as the recruitment method has limited the validity and reliability of the study's results ( Bärnighausen et al., 2017). Since the sampling has not been representative of the population, the results may not reflect the population as a whole. The convenience sampling technique has also increased the risk of researcher bias in recruitment ( Etikan et al., 2016). The sampling may be based on characteristics such as location or age, leading to inaccurate results. Using structured surveys to collect quantitative data can also pose some limitations. Since the survey questions were pre-structured, respondents may not describe their opinions and experiences with the web chat platform in detail. This could lead to a lack of detail in responses, ultimately affecting the results' accuracy and reliability. Furthermore, the method of analyzing and interpreting qualitative data through content analysis may also be limited. In content analysis, the gaps between the interpretations of the researcher and the respondent may exist, thus leading to inaccurate results. The qualitative data collected from the open-ended questionnaire may also be challenging to analyze, as the researcher must read and interpret many responses ( Gamper et al., 2012). Finally, even though the data has been manipulated and analyzed using statistical analysis techniques, some potential sources of bias still exist. For instance, the collinearity of variables may lead to overestimating the effect of certain variables ( Gamper et al., 2012). Furthermore, the researcher may also benefit from a deeper understanding of how the collected data interacts and create relationships with other independent variables that were not studied in this research.

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NHS Mental Health Web Chat 26 To increase the validity and reliability of the results in the future, some recommended measures must be taken to overcome the limitations of this quasi-experimental study. Firstly, to reduce any bias in recruitment, random sampling should be used instead of convenience sampling to recruit participants for the study ( Etikan et al., 2016). Furthermore, semi-structured or unstructured surveys can also be beneficial for collecting quantitative data, as they allow the respondents to put forth their responses in more detail instead of providing pre-structured answers ( Gamper et al., 2012). To effectively address the limitations of content analysis for qualitative data, researchers should consider using other analytical techniques, such as coding or thematic analysis, to improve the results' reliability. Finally, the researcher should ensure that any results generated by manipulating the data through statistical analysis techniques must be verified to avoid bias or inaccuracy. Overall, this quasi-experimental study has some limitations associated with the methods used for data collection, qualitative data analysis, and statistical analysis techniques. The primary limitation is related to the sampling technique used to recruit participants. To deal with these limitations, it is recommended to use random sampling, semi-structured or unstructured surveys, various analytical techniques other than content analysis, and verification of results to ensure the study's accuracy. 6.3 Conclusion Overall, this study has provided a comprehensive overview of the potential benefits and implications of mental health web chat systems. The findings suggest that this service delivery can provide quick access to mental health resources and information and reliable communication with a therapist. However, the effective implementation of such systems depends on carefully addressing potential issues related to client confidentiality, clinical effectiveness, access constraints, and healing processes. The results support the project's objectives to reduce waiting times for mental health services, increase access to mental health services within NHS systems, increase trust in NHS mental health services, diagnose mental conditions early to avoid clinical treatments and minimize premature death cases related to mental illness. The research findings in this study can help mental health professionals better understand the potential of mental health web chat systems and provide information to support their decision to implement such tools.

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NHS Mental Health Web Chat 27 References Ali, K., Farrer, L., Gulliver, A. and Griffiths, K.M., 2015. Online peer-to-peer support for young people with mental health problems: A systematic review. JMIR Mental Health , 2 (2), p.e4418. https://doi.org/10.2196/mental.4418 Alqahtani, F. and Orji, R., 2020. Insights from user reviews to improve mental health apps. Health Informatics Journal , 26 (3), pp.2042-2066. https://doi.org/10.1177/1460458219896492 Barak, A. and Grohol, J.M., 2011. Current and future trends in internet-supported mental health interventions. Journal of Technology in Human Services , 29 (3), pp.155-196. https://doi.org/10.1080/15228835.2011.616939 Bärnighausen, T., Tugwell, P., Røttingen, J.A., Shemilt, I., Rockers, P., Geldsetzer, P., Lavis, J., Grimshaw, J., Daniels, K., Brown, A. and Bor, J., 2017. Quasi-experimental study designs series—paper 4: uses and value. Journal of Clinical Epidemiology , 89 , pp.21-29. https://doi.org/10.1016/j.jclinepi.2017.03.012 Bendig, E., Erb, B., Schulze-Thuesing, L. and Baumeister, H., 2022. The next generation: Chatbots in clinical psychology and psychotherapy to foster mental health–a scoping review. Verhaltenstherapie , 32 (1), pp.64-76 . https://doi.org/10.1159/000501812 Brody, C., Star, A. and Tran, J., 2020. Chat-based hotlines for health promotion: A systematic review. Mhealth , 6 . https://doi.org/10.21037%2Fmhealth-2019-di-13 Cameron, G., Cameron, D., Megaw, G., Bond, R.R., Mulvenna, M., O'Neill, S., Armour, C. and McTear, M., 2018, May. Best practices for designing chatbots in mental healthcare–A case study on iHelpr. In British HCI Conference 2018 . BCS Learning & Development Ltd. https://pure.ulster.ac.uk/ws/files/71367889/BHCI_2018_paper_132.pdf Carron-Arthur, B., Reynolds, J., Bennett, K., Bennett, A. and Griffiths, K.M., 2016. What's all the talk about? Topic modeling in a mental health Internet support group. BMC Psychiatry , 16 (1), pp.1-12. https://doi.org/10.1186/s12888-016-1073-5 Coyle, D., Doherty, G., Matthews, M. and Sharry, J., 2007. Computers in talk-based mental health interventions. Interacting with Computers , 19 (4), pp.545-562. https://doi.org/10.1016/j.intcom.2007.02.001

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NHS Mental Health Web Chat 28 Coyle, D., & Doherty, G., 2008. Designing adaptable technologies for talk-based mental health interventions. In Workshop on Technology in Mental Health at ACM CHI 2008. https://www.cs.tcd.ie/conferences/TIMH/06-Coyle.pdf Crutzen, R. and De Nooijer, J., 2011. Intervening via chat: An opportunity for adolescents' mental health promotion? Health Promotion International , 26 (2), pp.238-243. https://doi.org/10.1093/heapro/daq062 Doraiswamy, P.M., London, E., Varnum, P., Harvey, B., Saxena, S., Tottman, S., Campbell, P., Ibáñez, A.F., Manji, H., Al Olama, M.A.A.S. and Chou, I.H., 2019. Empowering 8 billion minds: Enabling better mental health for all via the ethical adoption of technologies. NAM Perspectives , 2019 . https://doi.org/10.31478%2F201910b Dowling, M. and Rickwood, D., 2013. Online counseling and therapy for mental health problems: A systematic review of individual synchronous interventions using chat. Journal of Technology in Human Services , 31 (1), pp.1-21. https://doi.org/10.1080/15228835.2012.728508 Etikan, I., Musa, S.A. and Alkassim, R.S., 2016. Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics , 5 (1), pp.1-4. https://doi.org/10.11648/j.ajtas.20160501.11 Gamper, M., Schönhuth, M. and Kronenwett, M., 2012. Bringing qualitative and quantitative data together: Collecting network data with the help of the software tool VennMaker. In Social networking and community behavior modeling: Qualitative and Quantitative Measures (pp. 193-213). IGI Global. https://doi.org/10.4018/978-1-61350-444-4.ch011 Kelders, S.M., Kok, R.N., Ossebaard, H.C. and Van Gemert-Pijnen, J.E., 2012. Persuasive system design does matter: A systematic review of adherence to web-based interventions. Journal of Medical Internet Research , 14(6), p.e152. https://doi.org/10.2196/jmir.2104 McBeath, A., 2022. The Reflective Online Practitioner Survey: The value in harvesting both qualitative and quantitative data. European Journal for Qualitative Research in Psychotherapy , 12 . https://ejqrp.org/index.php/ejqrp/article/view/174 McGorry, P.D., Mei, C., Chanen, A., Hodges, C., Alvarez‐Jimenez, M. and Killackey, E., 2022. Designing and scaling up integrated youth mental health care. World Psychiatry , 21 (1), pp.61-76. https://doi.org/10.1002/wps.20938

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NHS Mental Health Web Chat 29 Mind, 2020. Mental health facts and statistics . Mind. https://www.mind.org.uk/information- support/types-of-mental-health-problems/statistics-and-facts-about-mental-health/how- common-are-mental-health-problems/ Morris, R.R., Kouddous, K., Kshirsagar, R. and Schueller, S.M., 2018. Towards an artificially empathic conversational agent for mental health applications: System design and user perceptions. Journal of Medical Internet Research , 20 (6), p.e10148. https://doi.org/10.2196/10148 National Health Service, 2023. Depression self-assessment . National Health Services. https://assets.nhs.uk/tools/self-assessments/index.mob.html?variant=42 O'Leary, K., Schueller, S.M., Wobbrock, J.O. and Pratt, W., 2018, April. "Suddenly, we got to become therapists for each other," Designing Peer Support Chats for Mental Health. In Proceedings of the 2018 CHI conference on human factors in computing systems (pp. 1-14). https://doi.org/10.1145/3173574.3173905 Parada, F., Martínez, V., Espinosa, H.D., Bauer, S. and Moessner, M., 2020. Using persuasive systems design model to evaluate "Cuida tu Ánimo": An internet-based pilot program for prevention and early intervention of adolescent depression. Telemedicine and e- Health , 26 (2), pp.251-254. https://doi.org/10.1089/tmj.2018.0272 Rojas, G., Martínez, V., Martínez, P., Franco, P. and Jiménez-Molina, Á., 2019. Improving mental health care in developing countries through digital technologies: A mini narrative review of the Chilean case. Frontiers in Public Health , 7 , p.391. https://www.frontiersin.org/articles/10.3389/fpubh.2019.00391/full Tudor Car, L., Dhinagaran, D.A., Kyaw, B.M., Kowatsch, T., Joty, S., Theng, Y.L. and Atun, R., 2020. Conversational agents in health care: Scoping review and conceptual analysis. Journal of Medical Internet Research , 22 (8), p.e17158. https://doi.org/10.2196/17158 Wadley, G., Lederman, R., Gleeson, J. and Alvarez-Jimenez, M., 2013, November. Participatory design of an online therapy for youth mental health. In Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration (pp. 517-526). https://doi.org/10.1145/2541016.2541030

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NHS Mental Health Web Chat 30 Zhou, L., Gao, J., Li, D. and Shum, H.Y., 2020. The design and implementation of Xiaoice, an empathetic social chatbot. Computational Linguistics , 46 (1), pp.53-93. https://doi.org/10.1162/coli_a_00368 Zhou, Q., Zheng, K., Hou, L., Xing, J., and Xu, R., 2019. Design and implementation of open LoRa for IoT. Ieee Access , 7 , pp.100649-100657. https://doi.org/10.1109/ACCESS.2019.2930243

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