doi: 10.56294/hl2024.178

ORIGINAL

Development of a chatbot for mental health support using ai-intelligent

Desarrollo de un chatbot para apoyo en salud mental utilizando inteligencia artificial

Iroda Sa’dulloyeva¹ *, Farkhod Raufov² *, Munisa Bakhadirova³ *, Nargiza Nasirova⁴ *, Ykhval Pekhanova⁵ *, Iroda Mamarasulova⁶ *, Barno Pulatova⁷ *, Makhruya Khakimova⁸ *

¹Bukhara State Medical Institute, Bukhara, Uzbekistan.

2Samarkand State Medical Medical University, Samarkand.

3Center for development of professional qualification of medical workers, Tashkent, Uzbekistan.

⁴Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Uzbekistan.

⁵Osh State University, Kyrgyzstan.

⁶Jizzakh state pedagogical university, Uzbekistan.

⁷Alfraganus University, Uzbekistan.

⁸“Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Tashkent, Uzbekistan.

Cite as: Sa’dulloyeva S, Raufov F, Bakhadirova M, Nasirova N, Pekhanova Y, Mamarasulova I, et al. Development of a chatbot for mental health support using ai-intelligent. Health Leadership and Quality of Life. 2024;3:.178. https://doi.org/10.56294/hl2024.178

Submitted: 26-02-2024                   Revised: 21-06-2024                   Accepted: 19-11-2024                 Published: 20-11-2024

Editor: PhD. Prof. Neela Satheesh

Corresponding author: Iroda Sa’dulloyeva *

ABSTRACT

People have been impacted by COVID-19 not just physically but also psychologically, and the epidemic has had a significant societal impact, particularly in underdeveloped nations. During such perplexing circumstances, there is undoubtedly a significant increase in psychosocial discomfort. On the other hand, more people are now seeking mental health assistance. The researcher identified a tool to help promote mental wellness and bring about a behavioural change in people’s minds using the broaden and build theory of psychological wellness (Fredrickson 1998), with the goal of promoting positivity and mental well-being. This was done by utilising design research methodology and human centred design principles. Through the use of human-centered design, the study illustrated how issues can be found, verified, and their impact mitigated through the use of an intervention. In order to delve deeply into the problems that emerged during the COVID19 pandemic and ultimately lessen the psychological effects of a pandemic, the research will help the public in times of hardship and policy makers. By offering suitable, sympathetic insights and solutions in relation to human-centered design, and particularly in terms of design for the healthcare and wellness space, the study results also demonstrate further steps towards developing advanced design research during a psychosocial distress situation on people’s mental wellness.

Keywords: COVID Pandemic; AI Intelligent; Chatbot; Deep Learning.

RESUMEN
 
La COVID-19 ha afectado a las personas no solo a nivel físico sino también psicológico, y la epidemia ha tenido un impacto social significativo, en particular en las naciones subdesarrolladas. En circunstancias tan desconcertantes, sin duda se produce un aumento significativo del malestar psicosocial. Por otro lado, ahora más personas buscan asistencia en materia de salud mental. El investigador identificó una herramienta para ayudar a promover el bienestar mental y generar un cambio de comportamiento en la mente de las personas utilizando la teoría de ampliar y construir el bienestar psicológico (Fredrickson 1998), con el objetivo de promover la positividad y el bienestar mental. Esto se hizo utilizando la metodología de investigación de diseño y los principios de diseño centrado en el ser humano. Mediante el uso del diseño centrado en el ser
humano, el estudio ilustró cómo se pueden encontrar problemas, verificar y mitigar su impacto mediante el uso de una intervención. Con el fin de profundizar en los problemas que surgieron durante la pandemia de COVID-19 y, en última instancia, reducir los efectos psicológicos de una pandemia, la investigación ayudará al público en tiempos difíciles y a los responsables políticos. Al ofrecer perspectivas y soluciones adecuadas y comprensivas en relación con el diseño centrado en el ser humano, y en particular en términos de diseño para el espacio de la atención médica y el bienestar, los resultados del estudio también demuestran nuevos pasos hacia el desarrollo de una investigación de diseño avanzada durante una situación de angustia psicosocial en el bienestar mental de las personas.
 
Palabras clave: Pandemia de COVID; Inteligencia Artificial; Chatbot; Aprendizaje Profundo.

INTRODUCTION

The COVID pandemic has led to an increase in demand for health services, which is putting more pressure on society to reconsider and change the way that healthcare is now provided and how we as a society see fit.⁽¹⁾ Though there might be a new creative space for design to aid in the cultural and economic recovery, particularly in the context of design for health, there is currently debate about whether or not design research practices need to be altered or transformed.⁽²⁾ As previously mentioned, a number of nations, including China, established online research portals and telemental health services to examine the effects of the epidemic and governmental protocols such as lockdown and quarantine.⁽³⁾ Medical facilities and academic institutions in China launched online resources to provide psychological counselling services to patients, their relatives, and other individuals impacted by the pandemic (National Health Commission of China, 2020). In order to address public health emergencies, a number of nations, including the United States and the United Kingdom, have devised protocols for psychological crisis interventions.⁽⁴⁾ Online counselling programs and chatbots and other automated mental health conversational agents are available for mental health support. The requirement for comprehensive healthcare during the pandemic will be aided by the expansion of mental health services via electronic and digital media.⁽⁵⁾ E-mental health services, can be utilised for communicating symptoms like burnouts, toxic productivity, sadness, anxiety and PTSD and for getting cognitive coping mechanisms, self-care and self-help programs as well as relaxing techniques during the pandemic imposed lockdown. The phrase “design maturity” refers to the degree to which design approach is applied in routine business operations.⁽⁶⁾ We must work to improve service delivery design across the board for internal, external, and mental healthcare as the design maturity in the industry grows. There is no denying that technology has a huge impact on the healthcare industry, and design has a critical role to play. All stakeholders benefit from design when it involves them, for them, and ultimately for everyone. The pandemic has presented a challenge to decision-makers, managers, and all departments on the limitations of the current healthcare systems as well as the need for quick innovation to address the issues that have arisen. It has inspired leaders to re-think and innovate further in e-healthcare services, and innovation doesn’t happen without the cradle of design thinking.⁽⁷⁾

The paper is organized in five parts. The introduction forms the base of the motivation behind the research. Followed by the research questions that identify the problem, the context and scope of the research, the contribution and significance of this research to the academia and policy level decision-making is shown in section 2. Followed by the proposed approach in section 3 and section 4 discusses the work, finally section 5 concludes the work.

Related Works

It is possible to research the benefits of automated mental health conversational agents, such as chatbots and apps, and online therapy choices for mental health support. According to a comment from,⁽⁸⁾ telepsychiatry is a good fit for outpatient consultations, but in certain situations, such as high-risk mental illness requiring extra treatment, an in-person visit may be necessary. This is permissible despite the danger of exposure. The necessity for comprehensive healthcare during the pandemic will be aided by the expansion of mental health services via electronic and digital media. According to,⁽⁹⁾ e-mental health services can be used to discuss symptoms such as burnout, toxic productivity, sadness, anxiety, and PTSD. They can also be utilised to receive cognitive coping mechanisms, self-care and self-help programs, and relaxation techniques while under lockdown due to a pandemic. Working with social workers and psychologists in an interdisciplinary distant setting can help people experience fewer negative effects on their mental health in.⁽¹⁰⁾ During an outbreak, healthcare professionals and policymakers need to collaborate with healthcare systems to establish programs and remote initiatives to provide a comprehensive healthcare and mental healthcare model.

According to their study,⁽¹¹⁾ it is now difficult for people to seek mental health care through conventional ways like in-person meetings; as a result, it was necessary to implement alternate alternatives like online services. Providing mental health services via telemedicine and online platforms will contribute to the development of a support network and offer the chance to establish a national psychological first mental AI program that is prevention-focused.⁽¹²⁾ With the aid of existing resources, the pandemic threat’s effects on mental health needed to be promptly reduced. Applications for mental health care could be swiftly modified to maintain current treatments and care for vulnerable populations that may emerge in due course. Getting mental health care online using videoconferencing and other digital technology has several benefits.⁽¹³⁾ urge the strengthening and improvement of the mental health system’s accessibility, particularly after evaluating the first intervention and considering national strategic planning and coordination for psychological first aid in times of crisis. According to,⁽¹⁴⁾ the progression of psychosocial distress can be stopped with the aid of an all-encompassing intervention system that includes epidemiological surveillance, screening, referral, and focused intervention. On a microscopic level,⁽¹⁵⁾ reports that the virus is spreading more quickly, particularly in a clinical setting. Eventually, clinics and hospitals will need to modify their procedures to lower the risk of exposure, such as by limiting the number of outpatients they can accept or by having consent given verbally rather than in writing and sharing it. It is possible to shield patients who don’t need much care from uninvited exposure.⁽¹⁶⁾ Medication may now be ordered online thanks to the increase in home delivery alternatives, which affects both the spread’s reduction and the gaps in medical care.⁽¹⁷⁾ demonstrate that tele-psychiatric therapies are necessary during the pandemic as there is an increased danger of contracting the virus, requiring safer and more effective methods. 

METHOD

Continuous enhancement and refining of the mental health tool can be achieved through the use of iterative prototyping and participant evaluation. After every iteration, researchers can collect participant input and ideas to make sure the tool adapts to their changing needs. Involving people in data analysis beyond the iterative prototype stage can also result in new insights and interpretations of the results. Scholars have the option to arrange workshops on data analysis or ask participants to go over and consider the themes and patterns that emerged from the thematic analysis. Users can always use our system to text-chat with a computer program. To comprehend and reply to customer enquiries, it makes use of Natural Language Processing (NLP) and Artificial Intelligence (AI).⁽¹⁷⁾ The bot can assist users with scheduling appointments and offer standard treatments for ailments including headaches, fevers, and colds. Reminders for booked appointments are also sent via it. The bot allows multiple users to talk at once, and it has the ability to view and download chat histories. We used the computer language Python 3.11 to create the system in order to fully utilise NLP and AI. The goal of natural language processing in artificial intelligence is to enable computers to understand, interpret, and produce human language using a variety of methods to facilitate effective communication.

Chatbot Design

This study was exploratory and interpretivist in nature. It is predicated on the interpretivism theory, which holds that knowledge and understanding can only be attained by interpretation and meaning-making and that human behaviour and meaning are socially constructed and subjective. Using this method, the researcher looks for the meanings and interpretations of the observable events by trying to comprehend the subjective experiences and viewpoints of the phenomenon. With an emphasis on how society constructs reality, the researcher seeks to make sense of the world by analysing observed events.⁽¹⁹⁾

The study depended on qualitative data since it needed detailed, subjective, and in-depth information to meet its goals. A thematic analytical framework was employed to analyse the gathered secondary and qualitative data in order to develop themes that corresponded with the objectives and enquiries of the study.⁽²⁰⁾ The paper has attempted to go into great detail about the moral conundrums that are arising in the field of education as a result of the continuous advancements in chatbots and artificial intelligence. Thus, it primarily employs an exploratory research methodology with the goal of investigating the relatively new phenomena of chatbot use in research and teaching. Gaining a deeper comprehension of the subject and producing fresh concepts and theories are the objectives. The study also attempts to thoroughly examine the phenomenon and pinpoint any pertinent elements that might require additional research.⁽²¹⁾

In this case, an exploratory study strategy would be helpful because it would enable researchers to obtain preliminary data and insights into the possible applications of artificial intelligence (AI) systems and chatbots in the academic domain, as well as the ethical issues surrounding their use. Creswell states that the purpose of exploratory research is to become more familiar with a phenomenon or to generate fresh ideas and theories about it.^(22,23) conducted a qualitative study in their earlier work to examine the application of chatbots in customer support. This study was based on an exploratory research technique and methodology. Comparably, the actual research offers insightful information about the possible advantages and disadvantages of AI systems and chatbots in research and education, as well as the moral ramifications of their application.⁽²⁴⁾

A Multidimensional Approach to Research Methodologies

Subscribers will see a welcome message with three call-to-action (CTA) buttons upon activating the chatbot following completion of the pre-test questionnaire: simple exercises, meditation, and positive affirmations.⁽²⁵⁾ The user will be directed to the exercise cue—a series of encouraging messages for positive self-affirmation, a guided meditation audio note, and basic exercise illustration-based graphics to assist the user in doing the same—by tapping any activity on the app.⁽²⁶⁾ Following their initial introduction to the fundamentals, the Chatbot encouraged the members to complete one task each day by sending them reengagement messages. Included were messages such as a trigger for gardening, strolling on the terrace, contacting a buddy, and viewing the sunset. Participant involvement steadily increased as they grew accustomed to utilising the chatbot. Over time, more and more contributions from the participants were received. (figure 1).

Figure 1. The user engagement of the chatbot increased with time

Instead of being a Facebook-supported chatbot, participants proposed that the chatbot may have been developed into a smartphone application. A participant suggested that by offering COVID-19 updates, the chatbot may have served as an all-arounder.^(26,27)  The app might have included information about the epidemic and physical health metrics in addition to uplifting news. A session lasted seven seconds on average. Sessions for the majority of users lasted between 1 and 9 seconds (87,2 %), then between 10 and 29 seconds (4,26 %) and 30-59 seconds (2,1 %). 6,3 % of participants utilised it for more than four to nineteen minutes in figure 2.

Figure 2. Most popular buttons chosen by users were meditate, positive affirmations and exit

Two of the 31 recruited participants dropped out of the research between March 16, 2020, and April 19, 2020. On March 23, 2020, one of the participants “blocked” the chatbot, discontinuing their subscription, and on April 16, 2020, another person did the same. Thirteen users, including the researcher,^(29,30) were active at the end of March 2020 and April 2020, respectively. Nonetheless, the individuals who disabled the Chatbot’s ability to send them messages did complete the post-test survey and offer their opinions about the Chatbot in below figure 3.

Figure 3. The interface of the Chatbot and addition of graphics to promote instant gratification

Following the intervention period, the individual was asked to complete four sections of a questionnaire. The first set of questions concerned basic chatbots; these were followed by modified WHOQOL, usability, and the modified Kessler fear of psychological distress questionnaire.^(31,32,33) Following receipt of the responses, the researcher spoke with the user over the phone to learn more about their experiences and gauge how satisfied they were with the Chatbot.

RESULTS AND DISCUSSION

Other users expressed the opinion in a few comments that the Chatbot’s re-engagement messages could have been more specifically tailored to each participant’s needs rather than offering general advice. According to the opinions of three other participants, the chatbot ought to have enquired about their present mental state and suggested tasks and cues based on it. Instead of giving out cues every day, two of the participants suggested that the Chatbot should be more conversational and integrate more two-way communication.

Table 1. Step length comparison
Types	F1-score	Precision	Recall
Anxiety Disorders	0,984	98,1	92
Bipolar Disorder	0,98	97	91,7
Post-Traumatic Stress Disorder	0,97	90	98,4
Neurodevelopmental disorders	0,98	92,2	98
Depression	0,91	93,8	97
Accuracy	98,75
Macro avg.	91	98	92
Weighted avg.	91	91	93

The step length serves as the basis for the performance comparison. Step length is the maximum length of unlabelled data that is considered for each iteration from test data in table 1. The following curve illustrates how the method performs better when the step length varies at each iteration. For improved classification accuracy, several PoS tagged features are considered as the training data size increases.

Figure 4. Screenshots from the Chatbot

Participants argue that instead of being a Facebook-supported chatbot, the chatbot may have been developed into a smartphone application in above Figure 4. By giving COVID-19 updates, one of the participants proved that the chatbot may have been a versatile tool. The app might have offered national or worldwide statistics about the pandemic in addition to physical health measures that could be utilised to address symptoms of the coronavirus, instead of just offering good news. A participant even mentioned that the Chatbot improved their quality of sleep by providing them with a short audio clip every night for meditation. Due to their lack of physical activity, exercises were deemed stressful by around 32,2 % of the participants. But they were more interested in positive affirmation and meditation than in working out. Of those who responded, 48,3 % indicated they would keep meditating, and 22,5 % said they would keep using positive affirmations in their daily lives.

CONCLUSIONS

Through expert interviews and community-based questionnaires, in addition to human-centered examination of available tools and therapies, the researcher determined that a chatbot would be a useful tool in supporting them. Therefore, the Chatbot was designed using the broaden and build principle of pleasant feelings. The participants receive one or more re-engagement messages from the Chatbot helping with fundamental coping strategies such journaling, positive affirmation exercises, meditation, doodling, and positive affirmations. The widen and develop approach aims to cultivate positive emotions over negative ones, therefore the Chatbot’s techniques may help users experience fewer feelings of anxiety, melancholy, and loneliness.

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FINANCING

The authors did not receive financing for the development of this research.

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest.

AUTHORSHIP CONTRIBUTION

Conceptualization: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Data curation: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Formal analysis: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Research: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Methodology: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Project management: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Resources: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Software: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Supervision: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Validation: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Display: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.

Drafting - original draft: Iroda Sa’dulloyeva, Farkhod Raufov, Munisa Bakhadirova, Nargiza Nasirova, Ykhval Pekhanova, Iroda Mamarasulova, Barno Pulatova, Makhruya Khakimova.