International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa SOCIAL AND BEHAVIORAL SCIENCES. Health Care Sciences ORIGINAL RESEARCH A Persuasive Technology mHealth Self- Monitoring System for Intervention in Diabetic Patients Medical Adherence Authors’ Contribution: A – Study design; Kgasi M. R.1 ABCDEF , Chimbo B.1 AEF , B – Data collection; Motsi L.1 ACEF C – Statistical analysis; D – Data interpretation; 1 University of South Africa, South Africa E – Manuscript preparation; F – Literature search; Received: 14.06.2024; Accepted: 23.07.2024; Published: 25.12.2024 G – Funds collection Abstract Background and The prevalence of chronic diseases like diabetes has caused unmeasurable strain on Aim of Study: many health systems especially in developing countries. Chronically ill patients are traumatised by their incurable illnesses, which adversely affects their adherence to their medical treatment, resulting in serious complications and even death. The aim of the study: to implement an intervention mobile health (mHealth) system by integrating persuasive technologies into mobile applications to empower diabetic patients to adhere to medical prescriptions. Material and Methods: Fogg Behaviour Model (FBM) was leveraged for the integration of mHealth and behaviour aspects. The system was developed with Kotlin programming using the Android Studio working integrated development environment (IDE). Tools including Firebase Real Time Database, Android Studio and Android Mobile Phone were used to afford a fully fledged mHealth self-monitoring system. The system was evaluated using descriptive statistics by medical personnel and social workers to determine the completeness, clarity, logical arrangement, correctness, reliability, usability, as well as content validity. Results: Findings indicated that the mHealth system meets a good degree of the measures that inform patients’ self-monitoring for medicine adherence. The evaluation results also suggested that some functionality of the mHealth self-monitoring system requires an incremental improvement, to provide a seamless healthcare support. The artefact was descriptively evaluated on seven parameters: completeness that showed a mean of 3.75 with a standard deviation of 1.070; functionality with a mean of 4.05 and standard deviation of 0.945; accuracy with a mean of 3.70 and standard deviation of 1.031; reliability a mean of 3.90 and standard deviation of 0.945; consistence a mean of 4.00 and standard deviation of 0.968; performance a mean of 3.75 and standard deviation of 1.250, and usability with a mean of 3.55 and standard deviation of 0.999. Conclusions: The developed system is as effective as face-to-face consultations and personal visits to healthcare facilities. Diabetic patients need to adhere to medicine to avoid further complications that could lead to death. Keywords: diabetes, mHealth, self-monitoring, medical adherence, persuasive technology, chronic diseases, remote healthcare provision. Copyright: © 2024 Kgasi M. R., Chimbo B., Motsi L. Published by Archives of International Journal of Science Annals DOI: https://doi.org/10.26697/ijsa.2024.2.2 Conflict of interests: The authors declare that there is no conflict of interests Peer review: Double-blind review Source of support: This research did not receive any outside funding or support Information about Kgasi Mmamolefe Rosina (Corresponding Author) – https://orcid.org/0009-0006- the authors: 7366-9196; 10151133@mylife.unisa.ac.za; Doctor of Philosophy in Information Systems, University of South Africa, Johannesburg, South Africa. Chimbo Bester – https://orcid.org/0000-0003-1916-0090; Doctor of Philosophy in Information Systems, Professor, University of South Africa, Johannesburg, South Africa. Motsi Lovemore – https://orcid.org/0000-0002-2149-7429; Doctor of Philosophy in Information Systems, Professor, University of South Africa, Johannesburg, South Africa. 76 International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa Introduction Adherence to medicines is the extent to which the distress, making drug regimen adherence a challenge patient’s action matches the agreed recommendations by (Kalema & Mosoma, 2019; Köhler et al., 2017). the healthcare provider. According to Franklin et al. Diabetic patients need reminders to take care of their (2020), non-adherence to medications can lead to health by adhering to the prescribed medicine. This call hospitalizations and readmissions, increase mortality has led to the development of various self-management rates and adversely affect patients’ quality of life. Non- reminder systems in which many have leveraged mobile adherence, both intentional and unintentional, limits health (mHealth) applications (Reidy et al., 2020). medication benefits, resulting in health decline and high Debon et al. (2019) note that many of the mHealth economic costs attributed not only to wasted medicine systems that have been developed to assist in healthcare but also to knock-on costs arising from increased monitoring of patients, lack the aspects that could trigger healthcare demands should health deteriorate (Lin et al., self-monitoring. These researchers indicate that the use 2022). There are various reasons for patients having of mHealth in the self-monitoring of diabetic patients difficulty taking their medication. These include should be coupled with persuasive technology that constant refills, the perception that medical treatments embraces both technology and behaviour change; as are improving, forgetfulness, or disinterest in taking well as taking into consideration any aspects of cultural medications, and non-availability of medication context. This paper reports on the development of a (Istepanian & Al-Anzi, 2018). Psychologically, patients persuasive technology mHealth self-monitoring system experiencing comorbid illnesses who take regular to enhance adherence to medication among patients with medicine are more likely to neglect their medication due diabetic conditions. either to fatigue or stigmatization or both. It is essential The prevalence of diabetes around the world poses a that effort be made to improve patients’ adherence to considerable burden on healthcare systems and patients their medications. Such efforts should include support suffering from this chronic condition. The rise in from both healthcare providers and relatives, social diabetes and other chronic diseases poses a particular support from peers, leveraging of technological challenge to low-income countries, many citizens innovations, and digital products (Pypenko, 2019) lacking adequate medical equipment and clinics (Chang where possible. et al., 2022). As a result, nations, as well as healthcare Globally, diabetes has been listed among the leading providers, must ensure that four basic functions are causes of death, with 1.5 million people in 2019 alone provided to the citizens in order to ensure diversity and dying from this condition (Lin et al., 2022). According equality. Among these functions are financial to the WHO (2023), in sub-Saharan Africa, South Africa management, provision of stewardship and development has the second-largest population in this region of of resources, such as human resources, physical people with diabetes (12.7% of adults); and South Africa infrastructure, and knowledge dissemination (Bacelar- had 16.0% of the total deaths in 2016 attributed to Silva et al., 2022). Additionally, Kendzerska et al. diabetes and other non-communicable diseases (NCDs). (2021) argue that enabling the effectiveness of these The WHO (2023) emphasizes that diabetes functions will improve the accessibility and pervasiveness is mainly attributed to lack of awareness responsiveness of the healthcare system. Regardless of of the disease, poor accessibility to proper healthcare, as the economic standing of a country, healthcare well as poor adherence to medical prescriptions. Debon responsiveness is of paramount importance. Some et al. (2019) allude to medical-taking inconsistencies researchers (Pypenko & Melnyk, 2021) argue that have been the major cause of high mortality rates for building the state economy on the principles of people with chronic diseases. The above researchers digitalisation will help solve these problems. According note that routine and timeous taking of medication to Rensburg (2021), countries should find better ways of suppresses the symptoms and other ailments that could ensuring that health systems are equally accessible and complicate diabetic conditions. Hence, failure to take available to all citizens, regardless of their geographical medication regularly allows ailments and symptoms the location. As part of this process, it is also necessary to opportunity to worsen the patient’s condition, resulting bring healthcare closer to communities, especially in from low levels of immunity. areas that are difficult for health workers to reach. Chronic diseases, which are persistent human health According to Achoki et al. (2022), improving conditions, or diseases with long-lasting effects, accessibility to healthcare systems is one way of closing contribute to various causes of death and disability the gap between urban and rural settings with limited worldwide (Debon et al., 2019). In both developing and resources. A number of initiatives have been motivated developed countries, chronic diseases have a high by attempts to improve the accessibility and availability prevalence; and are pervasive across all socio-economic of healthcare systems. Utilization of technological classes (Lin et al., 2022; WHO, 2023). Chronic innovations such as electronic health (e-health) and conditions require regular medication administration. mobile health (mHealth) has been at the forefront The strain of living with conditions that cannot be cured (Arsenijevic et al., 2020; Shaw et al., 2020). normally leads to distress and depression among The proliferation of ICTs and the increasing use of patients as a result of taking routine medicines. Such mobile telephony continue to be leveraged as mediums anxiety and depression in patients being aware of living of communication between healthcare providers and with an incurable malignancy leads to psychological patients. Consequently, mobile devices such as 77 International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa cellphones, PDAs, and other wireless devices have mainly because social responses to certain computing evolved into patient-monitoring devices. The rapid systems are automatic and natural. The researcher notes evolution of mobile technology platforms makes that individuals are hardwired to respond to signals in mHealth the fastest-growing segment of eHealth (Shaw the environment that seem alive in some way; and such et al., 2020). mHealth has played a major role in responses are instinctive rather than rational. empowering patients with information, increasing Additionally, computers can serve as persuasive social access to health services, and improving real-time data actors capable of rewarding individuals with positive management (Debon et al., 2019). Diabetic patients feedback, modelling, and providing social support (Nass require continuous monitoring; yet specialists in this et al., 1996). When human beings perceive a social domain are few, and those available are overwhelmed presence, they naturally respond in social ways that may by work. Hence remote health-monitoring emerges as a include feeling empathy, being angry, or performing a better alternative, preventing unnecessary complications social task (Fogg, 2020). This implies that social cues (Istepanian & Al-Anzi, 2018). As a result, mHealth has from computing products are essential. Such social cues become a popular tool for monitoring of patients with trigger automatic responses in individuals whereby a chronic conditions. Consequently, Chatterjee (2019) has given behaviour happens when motivation, ability, and emphasized that, for effective empowerment of patients a prompt come together simultaneously. with chronic conditions, it is essential to leverage Chatterjee (2019) avers that, since human beings persuasive technology that combines the use of respond socially to computer products, the use of technology with the patient’s behaviour in responding to persuasive technology is of paramount importance for drug adherence. mHealth self-monitoring of patients with chronic With the advent of digital health technologies, diseases. In mHealth self-monitoring, the mobile device healthcare has undergone a revolution, from the plays the role of persuasion dynamics described as widespread use of computers to algorithms for the social influence arising from social situations. detection, treatment, and monitoring of diseases. The Researchers such as (Fogg, 2002; Nass et al., 1996) use of technology has been extended from robotic observe that affiliation and social identity effects in surgery to artificial intelligence, machine learning, human-computer interactions make human beings computer-aided decision models, to mobile applications teaming up with computers behave similarly as they that help patients to manage their lives (Kgasi et al., would on teams with other humans in terms of the 2023). From diseases to electronic medical records, physical, psychological, social dynamics, social roles, digital health has experienced a revolution. As and language. In self-monitoring of diabetes patients, healthcare systems become more people-centred, the the changes in lifestyle with the use of mHealth is contribution of digital health technologies to preventive noteworthy in that the mobile apps facilitate the sending and diagnostic treatment, and self-monitoring of simple messages and alerts aiding in adherence to capabilities becomes enormous. However, many treatment (Debon et al., 2019). More so, the possibility technological interventions in healthcare have been of providing direct communication by a multimodal more intended to facilitate the work of healthcare content mHealth tool is crucial for higher adherence personnel than to facilitate patients managing their lives among patients to routine medicine taking (Arsenijevic (Chatterjee, 2019). Researchers such as (Chatterjee, et al., 2020). 2019; Debon et al., 2019; Kalema & Mosoma, 2019) A literature search was conducted using Litmaps by argue that, in order to empower patients to self-monitor combining phrases and a combination of the words their health, technological interventions must be “mHealth”, “mHealth self-monitoring systems”, designed to incorporate motivational factors that are “mHealth self-monitoring systems for diabetic essential to trigger behaviour change. Earlier researchers patients”, and “mHealth self-management of chronic such as (Fogg, 2002; Nass et al., 1996) recommended diseases”. The search was filtered to include electronic that self-monitoring can be effectively achieved by databases for published articles and conference leveraging persuasive technology. proceedings, online databases for theses, as well as Fogg (2020) notes that persuasive technology involves reference lists of relevant reports and reviews for the the incorporation of psychological insights into the years ranging from 2016 to 2023. The search revealed design of products such as mobile apps and wearables, that Dobson et al.’s (2017) study on mHealth for self- to modify people’s habits and beliefs. Therefore, Fogg management support was the most relevant; and has a (2020) believes that the designing process of persuasive wide impact on mHealth self-management research, technology should consider factors such as ability and hence it was used as the seed article. The Dobson et al. motivation, where motivation arises from one’s (2017) study investigated the use of mHealth in yearning for social connection. This implies that such an delivering self-management support to young people individual must have the ability easily to do what the app with Type 1 diabetes. The Dobson et al. (2017) study wants conducted. Therefore, the use of persuasive analysed clinical trials of using the text-message-based technology approaches have been widely designed with diabetes self-management support system in which the prompting features, such as reminder systems role of age in diabetes self-management was (Arsenijevic et al., 2020; Huzooree et al., 2019). Fogg emphasized. Much as their study has been widely used, (2002) indicated that human beings may respond to referenced, and extended, the study only analysed the computers as though they were living beings. This is moderating factors descriptively; and such limited the 78 International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa prediction of patients’ continuing usage of the study supports a patient to carry out self-medication and intervening mHealth system. treatment as well as reminding them to take their In a systematic review and meta-analysis of mHealth medicine as prescribed by medical personnel. Other and online health interventions for diabetes published researchers such as (Mueller et al., 2019) stress that, before 2015, Larbi et al. (2019) identified and much as various self-management interventions have categorized several factors that influence the use of been developed, including individuals’ links to health mHealth for diabetes self-monitoring. These factors systems where patients share data with healthcare included usability and suitability of the developed professionals (HCP), many such systems may be mobile apps and other online interventions, effect on misleading due to poor development procedures. These clinical health measures, data protection, information studies recommended that developed interventions needs, other external factors, support and access to should be scientifically evaluated. The developed services, coping, patient engagement and empowerment intervention system should be feasible, acceptable, needs, and technological needs. Their study emphasized usable, efficient, effective, including cost-effective that in developing interventions for diabetes self- while promoting safety in its implementation. monitoring, the role that patients and their healthcare Lin et al. (2022), using a descriptive analysis approach professionals play is significant in the development of evaluated Type 1 diabetes patients’ accessibility and tools and applications for such chronic diseases self- openness to receiving mHealth support. Their study monitoring. To address this call, our current study observed that patients’ perceptions of using mHealth as developed its artefact based on the Kgasi et al. (2023) a tool for delivering information is dependent on the model that was quantitatively designed and validated for delivery style, nature of messages delivered, and the mHealth self-monitoring. content that is delivered. Hence, the above researchers Reidy et al. (2020) based their study on the behaviour- recommended the implementation of interactive voice change wheel and theoretical domains framework in response rather than SMS for the elderly chronic-disease investigating the effects of a facilitated web-based self- patients. Additionally, their study emphasized the management tool for Type 1 diabetic patients using an importance of leveraging a contextualized model in the insulin pump. The study by the above researchers development of mHealth interventions: an approach leveraged the combination of contextualization of the suitable for one population may not be appropriate for healthcare intervention model, use of theory-driven another. The current study leveraged the Kgasi et al. intervention for healthcare self-monitoring, and the use (2023) contextualized model in developing the of big sample size of participating patients in the persuasive technology intervention for mHealth self- application of the mHealth system. Findings of Reidy et monitoring. al. (2020) indicated that successful self-management The aim of the study. To implement an intervention systems are situational and contextual, with time and life mHealth system by integrating persuasive technologies circumstances being major moderating factors. Much as into mobile applications to empower diabetic patients to their study bridged the gaps that had been presented by adhere to medical prescriptions. earlier researchers such as (Dobson et al., 2017; Larbi et al., 2019), the study fell short of addressing the Materials and Methods psychosocial support factors, or their integration into the Researchers Lagan et al. (2021) argue that the development of the intervention self-management proliferation of mobile health apps has made selecting models and systems. the right one increasingly challenging for clinicians and The integration of psychosocial support into routine patients. Despite the myriad of mobile health apps diabetes care has been cited as important in reducing available, app evaluation frameworks can assist in challenges of distress, anxiety, depression, and sleep sorting through them; however, the growing number of disorders, which are major antecedents of medicine frameworks further complicates the process. With this adherence (Kgasi et al., 2023). understanding, this study set to develop a persuasive The World Health Organization (WHO) report on the mHealth system based on previously validated models uses of self-care interventions indicates that the (Fogg, 2002; 2009; Kgasi et al., 2023). In persuasive classification of self-care interventions depends on the technology, behavioural occurrence is seen as the goal purpose of the intervention being developed (World achieved after aggregating other parameters that include Health Organization, 2021). The report indicates that motivation, ability, and a prompt (Fogg, 2002). Hence, these classifications include individual agencies that are the general architecture consists of devices connecting advanced to promote awareness about self-care. Health the patients’ physiological information, implanted information-seeking is recognized, with agencies systems for signal processing, and wireless intended to provide education for informed health communication as demonstrated in Figure 1. decision-making, and social and community support. As illustrated in Figure 1, the patients’ physiological Such agencies are purposely developed for peer data and the mobile application components interact mentorship and counselling and personal health tracking directly and are supported by the ease-of-use design designed to keeping home-based records of health and principles. Similarly, the persuasive technology diagnostic data. Other purposes are self-diagnosis of characteristics such as assessment, self-monitoring, health conditions intended for self-testing as well as patients’ adherence, as well as evaluation form the self-management of health. One such developed by this components of the health-management system. 79 International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa Figure 1 MHealth Self-Monitoring System Architecture (Source: Modified from Jia et al., 2015) System Functionalities and Integration with dashboard, reports, as well as home screen. The design Persuasive Technology process considered these functionalities along with The mHealth self-monitoring system functionalities that Fogg’s (2009) five persuasive strategies, namely, describe how well it should operate were identified to investigation, assessment, patient’s health plan, self- include productivity, access to information, training, monitoring, and evaluation. These features were access to diabetes national programmes, security, trust, incorporated into the system to enhance patients’ and scalability (Lagan et al., 2021). On the other hand, execution ability and adherence. Based on these for self-monitoring of the system’s features, parameters, the design process then followed an iterative descriptions, dependencies, and functions needed to approach incorporating patients’ feedback and medical include registration, patient verification, and push personnel evaluation of how the patients have behaved notification, connection to social accounts, utility, news towards the system’s triggers as demonstrated in feed, product and services, contacts, messages, Figure 2. Figure 2 Integration of Persuasive Technology for Self-Monitoring (Modified from Fogg, 2009; Jia et al., 2015) Physical Design and Coding of the System development environment (IDE). Kotlin programming The designed mHealth self-monitoring system is an language ensures code safety and developer’s android application designed with Kotlin programming satisfaction for professional android developers. The using the Android Studio working integrated following tools were used: 80 International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa - Firebase real time database, a cloud (online) NoSQL Coding and Graphical Interfaces database, that stores and syncs data between users in The developed frontend and backend were deployed on realtime. This helped to store information about the the android phone to enable the displaying of the output registered patients on the mHealth system. on the graphical interface. A sample of coding of the - Android Studio an integrated working environment frontend is demonstrated in Figure 3. Each functionality (IDE) designed specifically for android development. was developed with both the frontend and backend. The This helped in the utilization of the android studio frontend illustrated the patient’s interface of interaction chipmunk that allows the inspection and debugging of with the system; while the backend illustrates the exact the animations features built in a composable preview. occurrence within the system when a function or - Android Mobile Phone was used to run the application. command is issued. Figure 3 MHealth Self-Monitoring System’s Frontend Since the objective of the mHealth self-monitoring exact time set for medicine-taking; then an alarm system is to remind a patient to adhere to the medical automatically goes on. Figures 4 illustrates the messages prescription at the time recommended by the medical and the reminding frontend and backend coding. The personnel or social worker, the system was designed in system also enables a patient to schedule and create such way that it takes two approaches to reminding the personal alarm notifications on the App by setting the patient. It first sends a message to alert the patient at the ring notification time. Figure 4 Messages and the Reminding System Settings Frontend and Backend 81 International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa While on the system, the patient may navigate to collected from medical experts by using a close-ended perform other tasks such as reading the latest news, questionnaire and was analysed descriptively. The setting appointments, browsing the nearest pharmacy, as artefact was evaluated on the attributes of completeness, well as viewing his or her individual report in functionality, accuracy, reliability, consistency, responding to the system. The “Exit App” button helps performance, and usability. Because data was to be the patients to exit the application and resets the system analysed descriptively, a small sample of about 20 to the “Get Started” page of the App. Additionally, the respondents was deemed sufficient. The judgment- system was designed in such a way that it allows medical sampling technique was used to select the respondents. personnel at the facility where the patient is registered to The experts sought were healthcare professionals, both view and produce a report of the patient’s performance. medical and social workers, with relevant experience of Based on these reports, an evaluation of the patient’s working with diabetic patients. The artefact was adherence to the system’s triggers, and responses to drug deployed on these experts’ cellphones and the experts adherence, are recorded including the frequency of the were asked to practise with it for a period of two weeks. patient’s interaction with the system. Adherence is then The questionnaire was distributed in person; and experts confirmed by observing the patient’s replenishing of the were allowed three days for its completion. required medicine on time. Evaluation of MHealth Self-monitoring System Results Several methods of testing an artefact may be used to Respondents were asked to evaluate the artefact based confirm its operability. These may include, inter alia on the seven attributes of completeness, functionality, functional and structural testing, testing using accuracy, reliability, consistency, performance, and experimental methods such as those conducted in the usability. Results presented in Table 1 demonstrate the field and laboratories, statistical testing including respondents’ evaluation of how best the mHealth self- descriptive and inferential methods, as well as analytical monitoring system design conforms to the expected and architectural analysis (Hevner, 2007). Data was criteria in terms of the seven tested attributes. Table 1 Descriptive Analysis of Artefact Evaluation Parameters Implications of Findings terms of the level of quality and precision, stability and Completeness: This aspect evaluated whether the security, and providing solutions without confusion. As artefact’s components were sufficiently complete to demonstrated in Table 1, the minimum and maximum enable patients and medical personnel to interact with the responses were 2 and 5, respectively, with a mean of 3.70 systems, as well as being in a position to receive and and a standard deviation of 1.031. The findings of the share information. Findings indicate that the minimum study imply that many respondents were skewed towards and maximum responses are 2 and 5; with a mean of 3.75, agreeing that the artefact accurately gives the expected and standard deviation of 1.07. This implies that most results. responses were skewed towards agreeing that the system Reliability: This aspect assessed the probability that the is complete and could be used for monitoring patients’ artefact performs correctly regardless of the time and adherence to medicine. location, and is performing adequately according to Functionality: This aspect tested the artefact’s predefined specifications and requirements. Results usefulness; and how best it reminds the patients to adhere demonstrated in Table 1 indicate that experts’ responses to the medical prescriptions. Functionality was tested in were more skewed towards agreeing that the system is terms of the system’s input, processing, storage, as well reliable, and performs according to stated functional and as the output, including the extracted reports by the non-functional requirements. Reliability is essential for medical personnel. Results demonstrated in Table 1 event-based reporting that occurs on a daily basis; hence indicate that responses had a minimum of 2 and a this confirms that the system will perform to maximum of 5, with a mean of 4.05 and a standard expectations. deviation of 0.945. The implication of these findings is Consistency: This aspect evaluated the system’s that experts considered the system to be performing capability of producing a solution as intended. In the case averagely, as expected. of this study, consistency refers to whether the mHealth Accuracy: This aspect evaluated the degree of closeness self-monitoring system could support patients in self- of the artefact to perform self-monitoring. This was in managing their health. Results demonstrated in Table 1 82 International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa indicate that experts’ evaluations were a minimum of 2 self-monitoring systems are regarded as effective tools and a maximum of 5 with a mean of 3.90 and standard for fostering physical well-being and quality of life for deviation of 0.968. This confirms that accuracy and patients (Chifu et al., 2022; Cruz-Ramos et al., 2022; consistency of mHealth self-monitoring are important in Prioleau, 2021). assessing and understanding predictive validity. Such Other technologies could also be used in the same includes the ability to detect events or pattern changes manner; and these include assistive technologies to and for the intervention of the application. monitor nutrition and physical activity, awareness Performance: The system was evaluated in terms of how campaigns to promote health, and digitally accessible well it does the reminding of the patients; and whether it community-based and integrated-care models to improve accurately sends the messages as and when needed. access to healthcare services. Results demonstrated in Table 1 indicate that the majority As the prevalence of diabetes increases worldwide, it of the respondents 70% (n=14) agreed that the system places a considerable burden on countries’ healthcare performs to expectations. The implication of this findings systems as well as on the economic conditions of patients is that self-monitoring strategies are essential in helping suffering from these chronic conditions. Therefore, patients maintain adherence to medical prescription for leveraging technological innovations such as the their own progress toward controlling complications that mHealth self-monitoring system could save diabetic could be caused by the diabetic conditions. patients from the challenges of resource constraints and Usability: As demonstrated in Figure 1, the mHealth self- give these patients an added advantage of enhanced self- monitoring system architecture emphasized that the care. system be developed with ease-of-use features. This The mHealth self-monitoring system architecture implies that both the patients and healthcare workers presented in Figure 1 indicated that the system should be should be able to navigate and use the system with ease. developed with ease-of-use features; and should be Results demonstrated in Table 1 indicate that responses beneficial to the intended users. These two technological were a minimum of 2 and a maximum of 5, with a mean aspects are essential in that, because diabetic conditions of 3.55 and standard deviation of 0.999, with a positive are prevalent in both youth and adults, the developed skewedness of 0.024. Therefore, most responses were system should be accessible to all age groups. The system towards “agree” and “strongly agree”. The implication of should be easy to use and at the same time patients should this finding is that usability plays a key role in appreciate its usefulness. As Jia et al. (2015) note, failure engagement and behaviour changes. to make the mHealth system easy to use will imply usage By interacting with the system, a high-usability mHealth limited to only younger age patients, leaving the elderly self-monitoring system should increase engagement and ones socially isolated. Enhancing positive social support result in positive behaviour change. network is generally crucial to a patient’s well-being, irrespective of chronic diseases complications, as this Discussion improves their positive motivation towards adherence, This paper presents a designed artefact that can be leading to better recovery. Additionally, social support implemented into a fully-fledged mHealth self- for patients increases resilience to stress, hence lessening monitoring system to assist diabetic patients to adhere to effects of trauma and depression (Fogg, 2020; World medical prescriptions. The designed artefact was Health Organization, 2023). evaluated by healthcare personnel in terms of its Due to the stigmatization of having incurable health completeness, functionality, accuracy, reliability, conditions, chronic-disease patients sometimes become consistency, performance, and usability. Results reserved when interacting with peers, leading to low self- indicated that the artefact meets a good measure of esteem (Kalema & Mosoma, 2019; Köhler et al., 2017). patients’ self-monitoring of their health. The evaluation Hence, healthcare intervention programmes should not results also suggested that some functionality of the be limited to building the capacity of individual patients mHealth self-monitoring system requires an incremental as well as their family members, in managing the chronic improvement, so as to provide a seamless healthcare disease effectively. Programmes should also emphasize support. Preventing NCDs is crucial to enabling better the use of technological innovations such as the mHealth healthcare so as reduce long-term care costs while self-monitoring system. Additionally, individuals with harnessing the potential of economic growth. chronic physical illness are at increased risk of negative It is vital that better disease-management strategies, psychological sequelae; hence self-monitoring systems systems, and innovative tools are implemented to support act as an intermediary innovative approach intended to the already overburdened healthcare systems, especially reduce these negative effects and increase quality of life in low-income countries (Yagiz & Goderis, 2022). In this in such individuals (de Leeuwerk et al., 2022). regard, new tools and integrated care models such as self- The fact that the persuasive mHealth self-monitoring monitoring systems are required to support primary, system embraces the integration of patients’ behaviour community, and home-based healthcare, as well as long- with technology is a good alternative to human medical term care. personnel when dealing with patients with chronic Due to experiences of COVID-19 that introduced travel illness. Delivering a smartphone intervention system is restrictions and social distancing, accessibility to medical feasible as it meets the desired criteria of availability, facilities was limited; and such emphasized the need for demand, acceptability, and limited-efficacy testing electronic medical care systems. As a result, mHealth (Huberty et al., 2019). 83 International Journal of Science Annals, Vol. 7, No. 2, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa Limitations and Recommendations mHealth systems that combine all these health conditions The use of persuasive technology involves the that should be monitored, into one integrated system. incorporation of technological aspects of mobile- Furthermore, due to increasing numbers of patients technology software and hardware, along with the users’ suffering from chronic conditions, data storage, as well individual characteristics and other triggering factors as network stability, may become an impediment for such as environment, institutional support, social, as well effective use of the mHealth self-monitoring system. This as cultural aspects, to cause behaviour change. The study therefore recommends that future mHealth system development of the artefact was based on the pre-tested and device integration be developed, supported by a more model (Kgasi et al., 2023) that had been developed with comprehensive, cloud-based system. Cloud-based consideration of patients’ demographics and situational solutions will provide various benefits, including variables to moderate behavioural change. However, the stability, availability, and security, in addition to evaluation of the artefact was based on the system’s healthcare personnel being in a position to analyse parameters, namely, completeness, functionality, patients’ data from a central platform. accuracy, reliability, consistency, performance, and usability, without considering the evaluators’ Conclusions demographic variables. Furthermore, the evaluation was The pervasiveness of the use of technological conducted at one time only, yet system usage behaviour innovations into the healthcare domain, and the increase may change over time (Chang et al., 2022; Fogg, 2009; of disease burdens, has made mHealth a much sought- Kalema & Mosoma, 2019). Therefore, this study after tool in the healthcare sectors of many countries. recommends that future research use longitudinal data mHealth has been widely applied to the various aspects collection in which data on the effectiveness of the of healthcare management, especially to chronic system is collected at different intervals after usage. This complications that require routine monitoring, making will help to identify those parameters that have ceased to adherence a challenge (Huberty et al., 2019; Leeuwerk et be significant, together with those that have become al., 2022). mHealth systems such as the one developed in salient. this study not only work as a reminder system for The increasing globalization and urbanization is seeing a patients, but also allow healthcare professionals to collect number of chronic diseases both communicable and non- quantitative information related to patients’ health and communicable becoming more prevalent (Huberty et al., behaviour towards medicine adherence; and such helps 2019; World Health Organization, 2023). As the number personnel to make meaningful decisions. of citizens with chronic disease increases, healthcare Through the data generated, stored, and disseminated by systems become overwhelmed with the many patients the mHealth systems, healthcare providers will be who require routine healthcare. Technological capable of gathering patients’ related data and making innovations such as mHealth self-monitoring become key decisions such as patients’ risk prediction, need for players in improving patients’ self-management of their physical monitoring, or admission to intensive care. On health. The mHealth self-monitoring system developed the other hand, the integration of patients’ electronic for this study goes beyond simply providing health health records, their behaviour and wearable information and SMSs, to include a reminder system and technologies through the use of mHealth self-monitoring printing of the patient’s reports on interaction with the is essential for patient self-monitoring of their chronic system. The reminder system was developed in such a conditions. Hence, an understanding of how to use the way that the time for the alarm to go on and the sending data generated from patients suffering from chronic of messages are set manually either by the patient or a conditions such as diabetes could lead to better treatment. healthcare worker. This implies that the system is not Such could also lead to effective monitoring and control intelligent enough to detect from the patient’s condition of other related complications that may arise from that the alarm or reminder should sound. This study worsened conditions of chronic diseases due to poor therefore recommends that future research should adherence to medicine (Shaw et al., 2020). This is develop the mHealth self-monitoring that is intelligent essential especially for diabetes where related enough to automatically detect patient’s triggers for complications leads to increased the risk heart problems reminders before the alarm goes on. Patients’ reports on such as heart attack, stroke and narrowing of arteries that the healthcare personnel’s site should be based on real- may lead to death. time responses to allow immediate actions by the medical personnel. Such real-time interventions will help to ease Acknowledgments the work of the healthcare personnel due to increasing The authors wish to thank all healthcare providers, social numbers of patients. workers and administrators who helped in one form or This study was concerned with the development of a self- another during the processes of setting up appointments monitoring system for medicine adherence only, with no for securing ethical clearance and collection of data, as intervention for influencing health outcomes. However, well as those who participated in the study. there are also various other ways by which diabetic patients may be monitored, such as rate of physical Ethical Approval activity, weight gain or loss, and blood-glucose levels. The study obtained ethical clearance from the Ethics These other health-monitoring facilities were out of the Committee of University of South Africa, UNISA (No. scope of this study. 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It can be found online in the IJSA Archive https://ijsa.culturehealth.org/en/arhiv This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/deed.en). 86