Mental health problems are a significant issue in Bangladesh, where a large number of individuals of different ages suffer from mental illness due to a shortage of mental health services. The causes of mental health problems in BD are due to a combination of various reasons, including inadequate mental health facilities, insufficient mental health care, stigma, panic, and insecurity.

Mental health care facilities in the country are limited. In recent years, mobile health (m-Health) technology has been introduced, significantly improving access to mental health support and solutions. This technology enhances the quality, accessibility, and affordability of mental healthcare. Unfortunately, societal stigma often leads individuals and families t avoid seeking help, but m-Health technology allows them to receive treatment discreetly.

The m-Health technology employs mobile devices to support healthcare services, including smartphones, tablets, wearables, and other devices. Well-known m-Health services in BD include Relaxy, Moner Bondhu, and the like. Relaxy is a locally developed app that connects users with mental health professionals, while Moner Bondhu offers online and in-person counseling, as well as a 24/7 crisis and emergency response helpline. These services aim to make mental health support more accessible and affordable for everyone in Bangladesh. Currently, BD has numerous mobile apps, online counseling platforms, and other services that play a significant role in addressing mental health issues.

m-Health is one of the digital solutions tackling health problems, and in recent years, people of BD have increasingly turned to this technology for medical support. However, the quality, accessibility, and affordability of m-Health technology for mental health solutions remain insufficient.

This research adopts the technology acceptance model (TAM) to evaluate the perceived benefits (PBs) and usefulness of m-Health technology for mental support. It also focuses on the attitudes of the people of the Bangladeshi population toward m-Health technology. In this research, the TAM framework helps to efficiently identify the relationships between various factors such as perceived usefulness (PU) and users’ attitude toward m-Health technology, as well as the correlation between usefulness and the intention to use this technology.

Additionally, the research also discusses the role of m-Health technology in preventing mental health problems in BD and examines various factors associated with these issues.

This research was conducted from January 2023 to June 2024, adhering to ethical considerations to ensure the confidentiality and anonymity of all respondents.

In Bangladesh, over 6 million people suffer from depressive disorders, while 7 million experience anxiety disorders. It is estimated that more than 10,000 individuals die by suicide each year in the country. Among students aged 13–17 in Bangladesh, around 4% of boys and 6% of girls contemplate suicide.

This guideline addresses common mental health disorders in adults (18 years and older), including depression (including sub-threshold disorders) and various anxiety disorders [such as generalized anxiety disorder, panic disorders, phobias, social anxiety disorder, obsessive–compulsive disorder, and post-traumatic stress disorder (PTSD)] (1).

Mental health issues are a significant concern in Bangladesh. Unfortunately, those with mental health conditions often do not receive adequate treatment, and mental health is not recognized as a serious public health issue. The prevalence of mental disorders is high across different population groups, which is compounded by negative societal perceptions. People with mental illnesses are often stigmatized and labeled as “mad,” leading to a poor reputation within society. m-Health technology provides discreet support to individuals experiencing mental health challenges (2).

The increasing number of mental health patients in BD can be attributed to several factors, including a lack of well-trained mental health professionals, shortage of public mental health facilities, limited financial resources, inadequately stewarded mental health policies, and social stigma.

Various forms of stigma against mental illness exist in BD such as self-stigma, public stigma, professional stigma, and institutional stigma. Self-stigma is a negative attitude of patients against themselves due to having mental issues. Public stigma toward mental patients is very common in Bangladesh; this denotes the general people’s negative and discriminatory behaviors toward mental health patients, hindering their access to medical support. In this regard, m-Health technology is able to conceal the records of patients with mental illness and support them secretly (3).

Professional stigma indicates the negative and prejudiced attitude of patients, general people, or other healthcare professionals toward mental healthcare professionals due to their association with stigmatized patients, affecting their practice. So, through m-Health technology, mental healthcare doctors secretly prescribed to their patients. Lastly, institutional stigma is defined as the intentional or unintentional policies of an organization and negative attitudes toward mental patients that restrict the opportunities for them. m-Health technology can help conceal the identities of mental health patients and provide them with support in a confidential manner (3).

In Bangladesh, community care facilities for psychiatric patients are limited, and the BD government’s budget for mental health care is minimal. Only a small percent of mental patients receive free essential psychotropic medications.

Recently, the Bangladeshi government has prescribed some mental health policies, such as

There are several online counseling platforms available in Bangladesh such as.

m-Health technology uses mobile phones and other wireless technology to help with healthcare, such as tracking health, managing chronic diseases, and providing medical advice. The most common application of m-Health is the use of mobile devices to educate consumers about preventive healthcare services.

m-Health technology significantly influences mental health development by delivering accessible, convenient, and often discreet tools for self-management, symptom monitoring, and therapeutic interventions, allowing individuals to engage with mental health support more readily and consistently, particularly in situations where traditional access might be limited (4).

Childhood trauma: Childhood abuse, neglect, or trauma can lead to mental health issues.

Traumatic life events: Stressful life events, such as financial problems, the death of a loved one, or divorce, can lead to mental health issues.

Substance misuse: Substance misuse is a growing concern in Bangladesh, especially among young people.

Implementing stress management programs, flexible work arrangements, supportive work environments, and access to employee assistance programs.

Maintaining a healthy lifestyle, practicing relaxation techniques, setting boundaries, and seeking professional help when needed.

Most people who die by suicide have a mental health issue. It may be a depressive or substance abuse disorder. They may feel lonely, depressed, or isolated. They may have had a traumatic life experience.

m-Health refers to the use of mobile devices such as smartphones and tablets to support healthcare services, facilitating health data tracking, medical consultations, and health management. The features of m-Health technologies are healthcare practices; technological modality of the mobile device; intended user group; the stakeholders.

Data tracking: m-Health apps and wearable devices can monitor vital signs, activity levels, and other health data.

Medical consultations: Tele medicine platforms allow for remote consultations with doctors and other healthcare professionals.

Health management: m-Health tools can help individuals manage chronic conditions, track medications, and receive reminders for appointments.

Convenience: m-Health provides accessible and convenient healthcare services, especially in remote areas or for individuals with limited mobility.

Improved health outcomes: By enabling continuous monitoring and real-time data collection, m-Health can help healthcare providers and patients make informed decisions about treatment and care.

Empowerment: m-Health empowers individuals to take an active role in their health management and decision-making.

Classifies m-Health apps into six categories: health record apps, lifestyle apps, remote counseling and monitoring apps, health education apps, apps for contacting healthcare providers, and diagnostic and treatment apps. Mobile fitness applications fall within the realm of lifestyle and health applications.

The healthcare sector of BD tries to establish online and instant medical facilities for the patients. As a result healthcare sectors are implementing new digital solutions for medical support. Now, m-Health technology is used in administering clinical, administrative, and financial operations of medical organizations.

The health care information system provides healthcare data, information technology, instant medical support, mental support, gives instant solutions to various mental and physical problems, and the like. Technology implementation plays a significant role in boosting m-Health sector (6).

Health Information System (HIS), generally acknowledged as HIS, is one of the most influential technological boons for the medical sector. HIS performs a significant role in developing mental health management with utter efficiency.

The TAM and the unified theory of acceptance and use of technology (UTAUT) are used to better understand why users accept or reject a given technology, as well as how user acceptance can be improved through better and modified technological strategies.

In this research, the author used TAM and UTAUT theory to predict the importance of m-Health technology on the mental health development in Bangladesh. The author successfully used the theory of TAM to predict technology adoption in the healthcare service of Bangladesh. Both TAM and UTAUT models are effectively applied in the mental health care sector of Bangladesh. In this paper, the author showed that TAM and UTAUT models are able to explain stable predictive capabilities for acceptance and use of technologies in the mental healthcare sector of Bangladesh. Mental health issues may be a specific context of health care, where not only the technology, but also socio-organizational and cultural factors influence technology acceptance (4).

By the principle of TAM and UTAUT, we know that the actual use of a specific technology is affected by one’s behavioral intention to use it.

The theory of TAM explains that the intended use is determined by attitude toward using the technology, which in turn is determined by two perceptions of the system: PU and perceived ease of use (PEU).

There are various external factors that influence the perceptions of TAM and UTAUT. The perceptions of UTAUT are the extension of TAM as well as seven other theoretical frameworks. It proposes four constructs that affect usage intention—performance expectancy, effort expectancy, social influence, and facilitating conditions. Age, gender, experience, and voluntariness of use mediate the impact of these expediencies and facilitating conditions on intention (6).

The population for this study consisted of 435 respondents from various locations across Bangladesh. Participants were selected using intentional random sampling and completed a questionnaire based on a 1–5 Likert scale. The research data analysis utilized several statistical tests including Pearson correlation R test, independent t-test, validity test, goodness-of-fit test, and chi-square test. Participants were then directed to the questionnaire, where they shared their experiences with M & E health technology that enhances mental health development in Bangladesh.

All questionnaires were self-administered. The testing process was completed once participants finished answering the questions.

The research method employed was a quantitative descriptive method.

Table 1 shows that young age people are highest number of respondents in this area. SD is a widely used measurement of variability in statistics. It shows how much variation there is from the average (mean). A low SD indicates that the data points tend to be close to the mean, whereas a high SD indicates that the data are spread out over a large range of values. The mean value is 35.03, indicating that most of the respondents agreed to that variable. The SD value is 6.78, indicating that there is a moderate stability of ideas on the specific variable.

Table 2 shows that Under-graduate and graduate people are the highest number of respondents in this area; higher education level people are very lower percentage.

The mean value is 1.76, indicating that most of the respondents did not agree on that variable. The SD value is 12.74, indicating that there is a low stability of ideas on the specific variable.

Table 3 shows that students are the highest number of respondents in this research. The highest mean indicates that most of the respondents agreed on that variable. The lowest SD indicates that there is a stability of ideas on the specific variable.

The mean value is 3.26, indicating that most of the respondents agreed on that variable. The SD value is 9.41, indicating that there is a low stability of ideas on the specific variable.

The range of interpreting the Likert scale mean score is as follows: 1.0–2.4 (Negative attitude), 2.5–3.4 (Neutral attitude), and 3.5–5.0 (Positive attitude).

A low SD means there was a lot of agreement about the answers. High SD means there was a wide range of answers, indicating disagreement. Here, the author gets high SD, indicating high disagreement among the answers.

The range of interpreting the Likert scale mean score is as follows: 1.0–2.4 (Negative attitude), 2.5–3.4 (Neutral attitude), and 3.5–5.0 (Positive attitude). Here, the author gets high SD, indicating high disagreement among the answers.

The mean of all statements is greater than 3.5, respectively, which indicates positive attitude of PEU of ride sharing app. SD of all the statements are greater than 10, which indicates high disagreement among the answers.

The mean of all five statements is greater than 3.5, which indicates positive attitude of PU of ride sharing app. SD of all the statements are greater than 10, which indicates high disagreement among the answers.

The mean of all the statements is greater than 3.5, which indicates positive attitude of PB of ride sharing app. SD of all the five statements are greater than 10, which indicates high disagreement among the answers.

The mean of all the statements is greater than 3.5, which indicates positive attitude toward ride sharing app. SD of all the statements are greater than 10, which indicates high disagreement among the answers.

The mean of all the statements is greater than 3.5, which indicates positive attitude of intention toward ride sharing app. SD of all the statements are greater than 10, which indicates high disagreement among the answers.

Here, the mean of all the statements is greater than 3.5, which indicates positive attitude of social impact of ride sharing app. The author gets high SD, which indicates that there was a wide range of answers, indicating disagreement.

The range of interpreting the Likert scale mean score is as follows: 1.0–2.4 (Negative attitude), 2.5–3.4 (Neutral attitude), and 3.5–5.0 (Positive attitude). Here, the author gets high SD, indicating disagreement among the answers.

The range of interpreting the Likert scale mean score is as follows: 1.0–2.4 (Negative attitude), 2.5–3.4 (Neutral attitude), and 3.5–5.0 (Positive attitude).

A low SD means there was a lot of agreement about the answers. High SD means there was a wide range of answers, indicating disagreement. Here, the author gets high SD, indicating high disagreement among the answers.

H01: m-Health technology has no impact on prevention of mental health problem in BD.

Here the author used independent t-test;

Calculated t-value = 0.06436206

Table value t = 0.00000

If the absolute value of the t-value is greater than the critical value, we reject the null hypothesis. So, the null hypothesis m-Health technology has no impact on prevention of mental problem in BD is rejected or not true. There is a significant impact of m-Health technology on prevention of mental health problem of Bangladesh.

H02: There is no association between gender and type of mental health problem in BD.

Here the author used chi-square test.

The calculated chi-square value = 13.31.

Degrees of freedom = (2–1)*(7–1) = 6

At 0.05 level of significance and 6 degrees of freedom the table value of chi-square value = 12.592.

So, chi-square cal > chi-square table.

If our chi-square calculated value is greater than the chi-square critical value, then we reject our null hypothesis. So, in the null hypothesis, there is no significant association observed between gender and type of mental problem in BD, which is rejected or not true. So, there exists a significant association between gender and type of mental health problem in BD.

H03: There is no association between employment status and type of mental health problems in BD.

Here, the author used chi-square test.

The calculated chi-square value = 42.7316.

Degrees of freedom = (2–1)*(7–1) = 6.

At 0.05 level of significance and 6 degrees of freedom, the table value of chi-square value = 12.592.

So, chi-square cal > chi-square table.

If our chi-square, calculated value is greater than the chi-square critical value, then we reject our null hypothesis. So, in the null hypothesis, there is no significant association observed between employment status and type of mental health problem in BD, which is rejected or not true. So there exists a significant association between employment status and type of mental health problem in BD.

H04: Activities of m-Health technology has no association with the protection of mental health problem in BD.

Here, the author used chi-square test.

The calculated chi-square value = 43.12.

Degrees of freedom = (3–1)*(6–1) = 2*5 = 10.

At 0.05 level of significance and 10 degrees of freedom, the table value of chi-square value is = 18.307.

So, chi-square cal > chi-square table.

So, in the null hypothesis, activities of m-Health technology have no association with the protection of mental health problem in BD, which is rejected or not true. So, activities of m-Health technology have a direct association with the protection of mental health problems in BD.

H05: Purpose of m-Health technology is not associated with raising awareness toward mental health development.

Here, the author used chi-square test.

The calculated chi-square value = 38.659.

Degrees of freedom = (3–1)*(3–1) = 2*2 = 4.

At 0.05 level of significance and 4 degrees of freedom, the table value of chi-square value = 9.488.

So, chi-square cal > chi-square table.

So, in the null hypothesis, the purpose of m-Health technology is not associated with raising awareness toward mental health development, which is rejected or not true So, the purpose of m-Health technology is directly associated with raising awareness toward mental health development in Bangladesh.

H05: There exist no remarkable association between PEU and attitude of customers toward using m-Health technology.

The consequence in Tables 22 and 23 shows that there is a remarkable association between PEU and attitude of customers toward m-Health technology, because the P-value of 0.000 in this association is less than the pre-set level of significance in this study, which is 0.05 (P = 0.00 < 0.05). The beta value (r = 0.9998) discloses that there is a strong positive correlation between attitude and PEU. The R square proved that 0.9996 of the total variation of attitude is being explained by PEU. On that basis, therefore, the null hypothesis is accepted, and the alternative rejected.

H06: There exist no remarkable association between PU and attitude of customers toward using m-Health technology.

The consequence of Table 24 expressed a strong evidence against the null hypothesis based on “t” value results.

The outcomes in Table 24 disclosed that there exist a remarkable association between PU and attitude of respondents toward the use of m-Health technology, that is, the P-value of 0.00 in this association is less than the pre-set level of significance in this study, which is 0.05 (P = 0.00 < 0.05). The beta value (r = 0.999) also disclosed that there is a strong association between attitude and PU. The R square value proved that 99.99% of the total variation of attitude is being explained by PEU. Consequently, it can be concluded that there is a positive association exists between attitude of customers and their PU of m-Health technology. On that ground, the null hypothesis is accepted and the alternative rejected.

H07: There exist no remarkable association between PB and attitude of customers toward using m-Health technology.

The consequence of Table 26 expressed a strong evidence against the null hypothesis based on “t” value results.

The outcomes in Table 27 disclose that there exist a remarkable association between PU and attitude of customers toward the use of m-Health technology, that is, the P-value of 0.00 in this relationship is less than the pre-set level of significance in this study, which is 0.05 (P = 0.00<0.05). The beta value (r = 0.999940717) also proves that there exist a strong association between attitude and PBs. The R square disclosed that 99.99% of the total variation of attitude is being explained by PEU. Hence, it can be established that there exist a positive correlation between attitude of respondents and their PB of m-Health technology. On that basis, the null hypothesis is accepted and the alternative rejected.

H08: There is no significant relationship between social influence and benefits toward using m-Health technology.

Here, the author used Pearson r test., r = 0.7067

So, there exists a strong positive relationship between social influence and benefits toward using m-Health technology.

H09: There is no significant relationship between usefulness and attitude of customers toward using m-Health technology.

The consequence of Table 28 expressed a strong evidence against the null hypothesis based on “t” value results.

The outcomes in Table 29 disclose that there exist a remarkable association between PU and attitude of customers toward the use of m-Health technology, that is, the P-value of 0.00 in this relationship is less than the pre-set level of significance in this study, which is 0.05 (P = 0.00 < 0.05). The beta value (r = 0.99994) also disclosed that there is a strong relationship between attitude and PU. The R square proves that 99.99% of the total variation of attitude is being explained by PEU. Hence, it can be established that there exist a positive correlation between attitude of respondents and their PU of m-Health technology. On that ground, the null hypothesis is accepted and the alternative rejected.

From the consequence of the above test, it can be found that there exists a strong relationship between PEU and attitude. Of patients towards m-Health technology. Maximum of the respondents agree that they found m-Health technology service easy to use. The respondents also admit that the medical support they get in terms of mental health issues from m-Health technology in BD is very useful for them.

The research showed that young age people are highest number of mental patients in Bangladesh (Table 1).

Table 2 showed that no education or graduate people are the highest number of mental patients in Bangladesh. Higher education level people have very lower percentage of mental issues in Bangladesh.

The data of Table 3 showed that students are the highest number of respondents in this research.

The research found that male participated more in the interview. This paper also showed that unemployed people are more susceptible to mental health issues than employed people in Bangladesh. The research also showed that people whose education level is in undergraduate level are highly susceptible to mental health problems in Bangladesh. This paper also showed that urban people presented more mental health problems than rural people of Bangladesh. The paper found that married people are more susceptible to mental health crises in Bangladesh (Table 4).

The research disclosed that maximum of the respondents agreed that the role of m-Health technology is smoothly performed as a mental health development tool (Table 5).

The research found that activities of m-Health technology had a positive impact on the mental development in Bangladesh (Table 6).

The research showed that maximum of the respondents accorded that it would be easy to use these m-Health tools to find information regarding mental health issues, which indicated that PEU has an optimistic effect on attitude toward m-Health technology in BD (Table 7).

The research found that most of the respondents agreed that PU of m-Health technology is very effective (Table 8).

The research showed that PB of m-Health technology on mental health development is recognized by maximum of respondents (Table 9).

The research found that maximum of the respondents showed positive attitude toward m-Health technology (Table 10).

The research disclosed that most of the respondents have strong intention toward m-Health technology in Bangladesh (Table 11).

The research found that m-Health technology has a positive social influence in Bangladesh (Table 12).

Most of the respondents in this research expressed moderate satisfaction toward m-Health technology (Table 13).

In this research, the author disclosed the percentage of suicidal tendency according to age (Table 14). The research found that 16–25 age people have more suicidal tendency in this country.

Here, the author also mentioned the type of mental problem and percentage of mental patient of each type of mental problem in BD (Table 15). This research showed that depression is the most common mental problem in Bangladesh. Then most of the respondents are victim of insomnia, addictive behavior, anxiety disorders, stress, and schizophrenia.

In this research, the author also explained the mental disorder rate according to their profession (Table 16). The research found that students in BD are most susceptible to stress, depression, insomnia, and addictive behavior. Bankers and businessmen are most suffered by stress. Teachers experienced depression the most. Housewives are also victims of depression and stress. Most of the corporate jobholders also were susceptible to depression.

The research found that schizophrenia patients had more tendency to commit suicide than any other mental patient in Bangladesh. Then, depression, PTSD, and stress caused most suicidal tendency in Bangladesh (Table 17).

In this research the author found an association between gender and type of mental health problems (Table 18). This research found that males are the most susceptible to depression, stress, insomnia, and additive behavior. And females are the most affected by depression and stress.

Here, the author found a relationship between employment and types of mental problems (Table 19). The research proved that unemployed are the most victim of depression than employed people in Bangladesh. Unemployed people have more additive behavior than employed people. Again, employed people are the victim of stress than unemployed people in Bangladesh.

The research found that activities of m-Health technology has a direct association with the protection of mental health problem in BD (Table 20).

The research showed that the purpose of m-Health technology is directly associated with raising awareness toward mental health development in BD (Table 21).

This research defends Davies TAM that the PEU affects the attitude and the intention to use m-Health technology in Bangladesh.

The research showed that the degree of PU of m-Health technology positively influences the attitude of respondents toward m-Health technology (Tables 24 and 25). The PU of m-Health care service upgrades the job performance of mental health care industry in Bangladesh, which indicates that m-Health technology with a high level of PU is one for which a user believes that there is a positive user performance relationship. The results of this research found that there is a strong positive relationship between PU and attitude of respondents toward using m-Health technology (Tables 28 and 29).

In this research the author also revealed that there is a significant impact of m-Health technology on prevention of mental health problem of Bangladesh. The author also found that there exists a significant association between gender and type of mental problem in BD. Male and female responded differently to mental health crises (Table 18)

The author also showed that there exists a significant association between employment status and type of mental health problem in BD. Employed people are mostly affected by depression, insomnia, and stress because of workload and career pressure. While unemployed people are mostly affected by depression and additive behavior, because of disappointment, family and social stress, and the like.

The research found that more than 70% respondents have positive attitude toward m-Health technology. The research showed that the most significant barriers of m-Health technology are the unwillingness and low literacy rate of respondents toward m-Health technology.

However, this research is not beyond its limitations. This is a perception-based research where a limited number of convenience samples are considered to determine the benefit of m-Health and E-health technology and factors that affect mental health problems in Bangladesh.

There also exist some other limitations in this research, such as all respondents are not so qualified to replied and respond accurately. Time limitation is also a constraint here.

The research showed that m-Health technology plays an important role in preventing mental illness in Bangladesh. m-Health service application is rising gradually in Bangladesh. At present, the number of mental health patients in BD increased rapidly as a result of rate of suicide, crimes, and rape reported. As a consequence, family life, social life, and productivity are hampered seriously. m-Health technology performs a crucial part in protecting mental illness and provide mental support to the patient immediately, promptly, secretly, and remotely.

This research showed that m-Health service performed its activity smoothly because of modern technology. The use of technology eases the use of m-Health service. As a result, more people are interested in m-Health technology.

The research found that Information & Communication Technology (ICT) application of the m-Health technology is in both rural and urban areas of Bangladesh. This research frequently used the perception of TAM and UTAUT implying that acceptance of m-Health applications of all class of people of this country. Now BD mostly exploits ICT to develop m-Health service organizations.

This research explained the role of m-Health technology on the development of mental soundness in Bangladesh. This paper discussed how m-Health tools can be implemented and sustained over time for diverse types of people in this country.

This paper is an implementation science research that emphasized the mental soundness of all class of people through technology-based support system such as m-Health care implementation. This m-Health technology works actively against the societal stigma toward mental patient in Bangladesh.

Besides the crucial part of this paper, the outcomes may identify the correlation among various demographic factors, set up a mental health care development strategy to capture outcomes in a systematic way that prioritizes usefulness of m-Health technology, factors cause mental problem in Bangladesh, inclusion, and robust measurement science.

Conclusively this paper recommended that m-Health technology is a very efficient tool to ensure innovative healthcare service. This technology is meeting the emerging needs of people all over the country. On account of technological innovation m-Health service is very easy to access and implement.

The application of m-Health service is contiguously accelerating. The m-Health technologies provide a solution to support a lonely person live in a remote place, who may not be able to access in-person medical care services.

The impact of m-Health technology on the development of mental health issues has been increased rapidly.

Future researcher, policymakers, and service providers can study the core research done in this paper in order to conduct more research, issue advance policy, and offer more flexible service.

The result of this research demonstrated a range of studies to capture the exponential growth of m-Health interventions for people. This research showed that m-Health technology had a significant potential to solve various mental health problems of different classes of people and for the youth generation of BD who are facing mental health challenges and seeking support to overcome these challenges.

However, the research found out that the factors that affect mental health problem of people in Bangladesh. The research focused on the reasons for mental health problem in Bangladesh. Again, the paper discussed how m-Health technology lessens the mental health crisis issues of the people of Bangladesh.

However, the review also highlighted notable attention in research that include benefits of m-Health technology, social influence of m-Health technology, satisfaction toward m-Health service, and the like.

Future research may be conducted on adoption of equity, diversity, and inclusion lens of m-Health services. The upcoming research prioritizes understanding how current m-Health technologies can be adopted into existing models of care and develop guidelines, standards, and evaluation frameworks to support future m-Health development and implementation.

The technological advancement expand rapidly in all sectors of modern life including healthcare. Now more global resources are needed to monitor technological advancements to provide quality mental health support through m-Health technology to all people of BD where and when they need them.