The title or topic of this research proposal is “The Effect of Online Health Services or Mobile applications on the Mental Health in the remote population.”
The study of online health services and mobile applications in remote areas has become important today among the research community. Online health service or m-Health is a term for the use of mobile phones and other wireless communication devices in health care in order to educate patients about preventive health care. The use of m-health is highly popular in the rural areas where healthcare amenities are far off or not available or inaccessible. Therefore, the research scope in this topic is expanding day by day, along with the diversification of the impact areas such as mental health (Mohr, Burns, Schueller, Clarke and Klinkman, 2013). In this context, this research proposal is designed to provide an insight into the effect of an online health service or mobile application on the mental health of people in the remote areas.
From the past few years, it has been observed that around 25 percent of the Australian population from the rural areas experience mental health issues however, only 10 to 15% of them receive proper care. The key reasons for this treatment gap are unavailability of health professionals, health services, and stigma that are worse especially in the remote areas of Australia. Thus, the use of mobile technology is helpful in delivering mental health care coupled with training of primary care health professionals for depression, stress, and suicidal cases in people (Price, Yuen, Goetter, Herbert, Forman, Acierno and Ruggiero, 2014). Despite the fact that the evidence supports the use of online health apps as a means for providing mental health treatment, there remains question around whether such online applications have brought high efficacy in remote areas.
The hypotheses for this research proposal are:
H1: There is a Positive Effect of Online Health Services or Mobile applications on the Mental Health in the remote population
H2: There is a Negative Effect of Online Health Services or Mobile applications on the Mental Health in the remote population.
Globally, the use of internet has risen considerably over the past decade, with a jump up to 52% of the population in the Australia. Although online health services and m-health information differ in quality and readability however it has helped people by improving disease coping strategies, self-efficacy, and empowerment for the remote population of Australia. In this context, this study establishes the doctor-patient relationship, and enhances the ability of remote area consumers to make decisions on health-related behaviors. This research also creates a foundation for the future researches on the impact of online health services on consumers at global level.
Since this research proposal is prepared using quantitative approach, cross-sectional study will be used in this research. The remote place chosen for the study is Kiwirrkurra, located in Western Australia, and the time duration taken is one month.
The cross-sectional study is helpful studying one or more variables within a given population at one point in time but the cohort study is not helpful for this type of researches as it is useful to investigate to a group of people within a population.
The sample technique used by the researcher in this study is random sample technique. The target population selected using this technique is 24 participants from Kiwirrkurra area. Random sampling technique has been selected as it gives equal chance to every unit of the population to participate, and thus helps the researcher in yielding unbiased results.
Stratified random technique has not been used because it takes participants from the selected/identifiable groups and populations. It ultimately results in hampering the research results.
Data collection part is an essential part of a research study in which the researcher selects an appropriate method to collect the relevant information about the research issue. In this research study the researcher will use primary data collection method appropriate information about the research issue.
Primary data collection method is an appropriate method of collecting information from the research participants and understands their behavior and attitude about the research issue. On the other hand, the secondary data collection method cannot be used to collect information regarding the behavioral aspect of the research participants. However, the secondary information is used to support the reliability and viability of the research outcomes in proper manner.
In this research study, descriptive statistical analysis method will be used to analyze the collected data in effective manner.
The descriptive statistical analysis is an effective method for the quantitative research studies and analyzes the collected data through survey strategy through a systematic questionnaire. In addition, it is an effective method for small sample size research studies. Therefore, descriptive analysis will be used in this research study. On the other hand, inferential statistical method is a good method to big sample size research studies so that it cannot be used in this research study.
In this research study, a consent form is signed from the research participants to get their acceptance in the research study.
Consent form is a standard method of eliminating ethical consideration from the research participants as it includes entire process and propose of the research study. As well as, this form provides a free environment where the research participants can leave the research study at any time.
The limitations of this research study are time, budget and limited sample size. These limitations restricts the scope of the research study.
In order to confirm the findings of the preliminary research, following research questions have been designed:
RQ1: What is the impact of using online health service or mobile application on mental health?
RQ2: What are the benefits of using online health service or mobile application in the remote population?
RO3: How can be the use of mobile health services can be improved in the remote areas to treat mental health issues?
RQ1: What is the impact of using online health service or mobile application on mental health?
In the view of Berrouiguet, Baca-Garcia, Brandt, Walter & Courtet (2016), in the recent years, online health services or mobile applications have targeted a wide range of mental disorders. These apps have different functionalities and designs. The mental health apps are helpful in cognition improvement, self management, social support, passive data collection, skill training, and symptom tracking. At all stages of medical care delivery, the mental health apps facilitate prevention, effective crisis intervention, supplement to personal therapy, primary treatment, diagnosis, and condition management after treatment. Kallander, Tibenderana, Akpogheneta, Strachan, Hill, Asbroek & Meek (2013) has found that online health services have brought a positive impact in combating mental health issues, in comparison with other platforms due to high hedonic motivation, low effort expectancy, and ease of habit for patients. Plaza, MartiN, Martin & Medrano (2011) has examined that some mental health apps exploit transdiagnostic tools of treatment to encourage patient involvement by minimizing the need of interaction with numerous apps. However, being a technological limitation, the online health services are filled with a number of challenges and threats. The malfunctioning of m-health can possess a threat that can adversely affect the patient care. Moreover, there are still no regulations to protect patients’ rights . Privacy and ethical factors have become even more critical in psychiatric patients at high risk who may not be able to protect their own rights.
RQ2: What are the benefits of using online health service or mobile application in the remote population?
According to Kumar, Nilsen, Abernethy, Atienza, Patrick, Pavel & Hedeker (2013), people in the remote areas face a number of challenges in receiving health care due to the availability of limited resources to service communities. Also, the remote population is already facing greater risk factors in mental health areas together with financial uncertainty and social isolation. Varshney (2014) has stated that due to lack of healthcare provision, geographical and financial barriers, attitudinal factors, and concerns for anonymity, the remote population is unable to get access to the health services. The use of online health applications has the ability to connect the consumers to health professionals by installing bio-monitoring device and comprehensive medical library in their pocket. m-health techniques such as 3G Doctor has been successful in improving and promoting the healthier and long life of remote population. Online health applications have enabled increased access to the health relevant information in remote areas, and improved ability of diagnosing and monitoring of diseases. Moreover, the people in remote areas can easily take appointments and the doctors text them to remind of their appointments, thus increasing the patient engagement. The use of m-health, remote population has been able to improve their wellness by sticking to a physician recommended diet, healthy exercise routines, and by taking prescriptions and regular medical check-ups.
RO3: How can be the use of mobile health services can be improved in the remote areas to treat mental health issues?
In the words of Brown, Yen, Rojas & Schnall (2013), while designing m-health apps for providing mental health care, the unique features of the service should be considered. Such features include privacy, safety, temperament, and evidence base, for improving the operation of the online health services. However, the priority of development aspects that signify the areas of continuing study can differ throughout different mobile applications or mental health status. In support of this Chan, Torous, Hinton & Yellowlees (2015) has suggested that online health services need to analyze the need of introducing a direct line connection between doctors and patients in the times of emergency throughout the remote areas. Since the emergent requirement can occur unpredictably in mental health patients, the facility of communicating instantly with each other who can provide help in real time could be significant in the remote areas. It can take in substance abuse consultant, a patient’s therapy, contracting service hotlines, local medical emergency care, and support from peers. In addition to this, the m-health developers should also ensue that patients are properly communicated and attentive of the risks, capabilities, as well as limitations of a specific m- health app. The exact expectations also need to be checked for what advantage can be obtained from a specific application or technology to enable consumers located at remote areas, to search for right doctors at right time in urgent circumstances. Nhavoto and Gronlund (2014) have also suggested that mental health care patients should be fully informed about the limitations of interventions controlled by the providers. Given the stigma towards mental health in remote population, the protection of consumers’ information and records should be taken into consideration.
Conclusion
From the above discussion it can be concluded that mobile health application is an effective development in the healthcare services in remote areas. The individuals in remote areas have got better way of communicating with the care professionals for quick care services.
References
Berrouiguet, S., Baca-Garcia, E., Brandt, S., Walter, M., & Courtet, P. (2016). Fundamentals for future mobile-health (mHealth): a systematic review of mobile phone and web-based text messaging in mental health. Journal of medical Internet research, 18(6).
Brown, W., Yen, P. Y., Rojas, M., & Schnall, R. (2013). Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology. Journal of biomedical informatics, 46(6), 1080-1087.
Chan, S., Torous, J., Hinton, L., & Yellowlees, P. (2015). Towards a framework for evaluating mobile mental health apps. Telemedicine and e-Health, 21(12), 1038-1041.
Kallander, K., Tibenderana, J. K., Akpogheneta, O. J., Strachan, D. L., Hill, Z., Asbroek, A. H., & Meek, S. R. (2013). Mobile health (mHealth) approaches and lessons for increased performance and retention of community health workers in low-and middle-income countries: a review. Journal of medical Internet research, 15(1).
Kumar, S., Nilsen, W. J., Abernethy, A., Atienza, A., Patrick, K., Pavel, M., & Hedeker, D. (2013). Mobile health technology evaluation: the mHealth evidence workshop. American journal of preventive medicine, 45(2), 228-236.
Mohr, D. C., Burns, M. N., Schueller, S. M., Clarke, G., & Klinkman, M. (2013). Behavioral intervention technologies: evidence review and recommendations for future research in mental health. General hospital psychiatry, 35(4), 332-338.
Nhavoto, J. A., & Gronlund, A. (2014). Mobile technologies and geographic information systems to improve health care systems: a literature review. JMIR mHealth and uHealth, 2(2).
Plaza, I., MartiN, L., Martin, S., & Medrano, C. (2011). Mobile applications in an aging society: Status and trends. Journal of Systems and Software, 84(11), 1977-1988.
Price, M., Yuen, E. K., Goetter, E. M., Herbert, J. D., Forman, E. M., Acierno, R., & Ruggiero, K. J. (2014). mHealth: a mechanism to deliver more accessible, more effective mental health care. Clinical psychology & psychotherapy, 21(5), 427-436.
Varshney, U. (2014). Mobile health: Four emerging themes of research. Decision Support Systems, 66, 20-35.
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