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Integrating QVoC (QR Code with Voice Content) to Enhance
Medication Adherence for Geriatric Diabetic Patients
Samantha Desiree N. Delima, Vanessa Joy B. Felizardo, Moh’d Yusoph M. Kusain Jr., Jazel Q. Racoma
Faculty of the Pharmacy Department St. Alexius College, City of Koronadal
DOI: https://doi.org/10.51244/IJRSI.2025.1210000049
Received: 02 October 2025; Accepted: 08 October 2025; Published: 01 November 2025
ACKNOWLEDGMENT
It would have been impossible to complete this research study without the encouragement, guidance, and support
of numerous people to whom they wish to extend their sincerest appreciation.
Above all, the researchers would like to express their most sincere gratitude to their Research Mentor, Dr. Erwin
M. Faller, RPh, MSPharm, PhD, for his constant support, professional advice, and valuable feedback during the
research process. His mentorship has proved to be highly contributory in determining the direction and quality
of this research.
They are likewise very thankful to the Advisers of the Pharmacy Department, Ms. Apple Jane Siroy, RPh, Ms.
Cynthia Claire Guinto, RPh, CPh, and Mr. Jefferson Chanco, RPh, for their ongoing guidance, support, and
counsel throughout this project.
Particular thanks to their Research Adviser, Mr. Jefferson Chanco, RPh, for his careful supervision, elaborate
suggestions, and commitment in taking them through each step of the research.
They would like to further express their gratitude to their Research Validators, Ms. Kimberly Jean Surmion,
RPh, MSPharm, Ms. Mariabe Quinco, RPh, MSPharm, and Mr. Mershen Gania, RPh, MSPharm, who lent their
time and expertise in validating and reviewing their instrument for the purposes of ensuring the reliability and
validity of the data-gathering tools.
And their sincerest appreciation to Mr. Sonny Boy C. Reyes Jr., their IT helpdesk, for his technical support and
significant input on creating the QVoC system that was the very core of this research.
To Hon. Dimson Floro, Morales Barangay Captain, the researchers express their gratitude for allowing them to
carry out the research in the locale and for your gracious assistance.
The researchers also want to thank Mr. Venchie C. Badong, RCH, PFT, MAT, CSSO, their statistician, for his
professional support and expertise in accurately analyzing the findings of their research with clarity and
accuracy.
Finally, and above all, the researchers would like to give their sincerest gratitude to their beloved parents: Mr.
Edgardo and Mrs. Jeanette Felizardo, LPT; Mr. John Jon and Mrs. Rosalyn Racoma; Mr. Hadj Moh'd Yusoph
S. and Mrs. Hadj Asmah M. Kusain; and Mr. Samuel P. Delima and Mrs. Hazel G. Navarra, who have provided
their love, prayers, and support in every aspect of this academic pursuit. Your sacrifices and inspirations have
been the researchers’ biggest sources of strength and determination.
ABSTRACT
Medication compliance is a top-of-mind factor for effective diabetes care, particularly in elderly groups that
typically suffer from cognitive, social, and technological barriers. This research sought to establish the impact
of incorporating QR Code with Voice Content (QVoC) technology on medication compliance among geriatric
diabetic patients in Barangay Morales, Koronadal City. Using a quasi-experimental design, the researchers
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recruited 20 older diabetic patients through purposive sampling. The intervention was a QVoC device that
provided audio cues linked to QR codes for targeted drugs, which were designed to address forgetfulness and
complexity in medication regimens. Medication adherence data were collected using a validated questionnaire
derived from the Morisky Medication Adherence Scale (MMAS) pre- and post-intervention. The adherence
mean score increased from 2.95 (SD = 0.18) before intervention to 3.70 (SD = 0.09) after intervention.
Participants reported better comprehension, increased regularity in drug taking, and reduced omitted doses
errors. The conclusion drawn by the study was that QVoC is helpful, easy, and very effective technology-based
treatment for improving medication adherence among elderly diabetic patients. Future research can explore the
long-term outcomes and scalability of such interventions across different populations.
Keywords: medication adherence, geriatric diabetes, QVoC, QR code intervention, digital health, elderly care,
chronic disease management
INTRODUCTION
Background of The Study
Medication adherence is a critical issue, especially among the elderly, where the prevalence of chronic conditions
such as diabetes is on the rise. The effective management of diabetes depends on consistent medication
adherence, yet studies indicate alarmingly low rates among geriatric patients. Such statistics are evidenced as,
for instance, in one study conducted on patients suffering from type 2 diabetes in Yemen, it shows that only
about 47.75% are adherent, while in similar studies conducted at Pakistan, approximately 55.6% showed
adherence among aged hypertensive (Othman et al., 2020; Saqlain et al., 2019). Reasons include low health
literate, lack of memory among the patients for taking drugs due to complicated intake regimen, economic and
social problem (Yazdanpanah et al., 2019).
Diabetes Mellitus is an overwhelming issue considering health outcomes and quality of life in general and
particularly in the aging population globally. According to International Diabetes Federation, as of 2021, around
536.6 million adults aged between 20-79 years have diabetes, projecting the number up to 783.2 million people
in 2045, where most of it will be continued to stay low and middle income (IDF, 2021). Philippines Cross-
sectional survey results indicated almost 20.5% diabetes prevalence among old people (Abas et al., 2022). This
reflects most parts of Southeast Asia where lifestyle factors combined with limited access to healthcare explain
high diabetes rates often surpassing 20% (Mendes et al., 2019).
Although diabetes is common and widespread, it is still challenging in terms of adherence to medications.
Cognitive factors like anxiety and depression negatively impact adherence and self-care activities (Mendes et
al., 2019). Studies have documented several reasons why the elderly suffer from poor adherence regarding
diabetes treatment, including having complicated drug regimens and a lack of support system (Jannoo & Khan,
2019). These comparisons within the Philippines and other countries in the ASEAN community further
emphasize challenges of geriatric patients because of the socio-economic inequalities and differing health
literacy (Abas et al., 2022).
This makes urgent the need for targeted interventions for enhancing medication adherence among geriatric
diabetic patients since there are marked gaps in knowing the specific factors that influence medication adherence
in low- and middle-income countries, such as the Philippines. Since studies have shown general challenges about
medication adherence, more comprehensive investigations must be done that would look at the interplay of
cognitive, emotional, and socio-economic factors within this population group.
An immediate concern on the medication non-adherence problem on elderly diabetic patients in Koronadal City.
The adherence of the majority to their treatment today is only fifty percent for patients of type 2 diabetes,
alarming statistics today and a hindrance to good control of the patient's diabetic health, along with severe health
consequences and unnecessary higher healthcare cost expenses.
The new approach to knowledge and medication adherence among geriatric diabetic patients, proposed in this
study, involves the integration of QVoC, or QR Code with Voice Content. Easy access to medication instructions
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and health information through QR codes linked to voice content may help overcome some of the barriers that
low health literacy and cognitive challenges often create for elderly patients.
This research goes further than just patients directly involved with the disease in that its outcomes will be
instrumental in guiding care providers in crafting interventions to support better adherence with medication
regimens, thereby better managing the disease and the cost of medical complications resulting from non-
adherence. It may also help guide public health programs for the better management of adherence in older people,
with resulting health benefits in a population as a whole.
REVIEW OF RELATED LITERATURE AND STUDIES
Importance of Medication Adherence
Brodie, Madden, and Rosen (2020) mentioned the new applications of Quick Response (QR) codes in medication
education as their capacity to enhance patient understanding and adherence to drug therapy. Educating resources
available with QR code usage offers access to teaching video and ancillary materials at patient fingertips,
expounding on instructions for medications as well as medical information. Such a method not only promotes
enhanced patient involvement but also helps in tackling issues caused by low health literacy, especially by older
generations of people who may find conventional written information difficult. Such technology has the potential
to greatly enhance adherence to medication through enabling patients to use tools necessary to take greater
control over their own health.
Ti, Chen, and Wu (2020) came up with an advanced visual cryptography-based QR code system specifically
designed to optimize drug administration. This technology enhanced drug administration security and usability,
ensuring that access to sensitive information about drug doses and time will only be available for trained
personnel. The use of QR codes minimizes administration errors, traditionally inherent in medication manual
handling. This technology does not only expedite medication administration but also helps patients adhere to
treatment more reliably by providing clean and secure entry to their medical data, bettering health results
eventually.
Svensk and McIntyre (2021) explored the use of QR code technology as one way for elimination of medication
error through self-administration. Research demonstrated that addition of QR codes on packages for medications
makes patients able to read codes for getting immediate access to simple-to-read directions on the proper
application and dosage. Prompt availability minimizes misunderstandings and misadministration, particularly
among patients of older age and with impaired mental acuity or complex treatment regimens. These interventions
in technology are essential to maximize medication compliance levels and help patients comply with their
prescribed regimen accordingly.
Karia, Hughes, and Carr (2019) presented a scoping review of how QR codes have been used within healthcare
education with mention of enhancing the understanding by patients of information relating to health. The article
discussed a number of applications of QR codes within learning environments, where they have been used to
link patients to multimedia content offering feedback on treatment protocols and drug regimens. Simplification
of health information in ways accessible through interactive content significantly raises the compliance levels of
patients having different levels of health literacy. Further research is suggested for identifying the success of QR
code technology as a tool for educating and empowering the patient in treating chronic disease.
Boonyapalanant, Ketcham, and Piyaneeranart (2020) presented a creative use of QR code technology toward the
objective of concealing patient injury information inside images in medicine. As much as it is focused on privacy
concerns, this article shows evidence of the versatility of QR codes in healthcare settings. Including QR codes
in medical records or imaging systems adds confidentiality while making necessary information about their
treatment plans available to patients. Double functionality aids in better adherence through enabling patients to
interact with their health data in a secure manner while reducing risks of unauthorized use of sensitive data.
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Factors Influencing Medication Adherence
A prevalence of medication non-adherence of 19.9% was found in a study by Xu, et al. (2020) with strong
associations between non-adherence and variables such as gender—in females, the patients had greater
probability of being non-adherent—and the significance placed on medication adherence which had an inverse
correlation with adherence rates. Longer duration of disease is also found to be positively correlated with
improved adherence. Therefore, disease experience may improve the understanding and adherence of the
treatment regimen. Therefore, these findings indicate that the necessity for specific interventions like counseling
and educational programs would increase awareness regarding medication adherence among elderly diabetic
patients and enhance their self-management and health outcomes.
A revised overview of the factors that influence medication adherence among patients suffering from chronic
physical diseases, including diabetes, is available in the work of Gast
and Mathes (2019). They learned that drug compliance is a multifaceted issue with various dimensions that are
classified into five broad categories: social and economic factors, therapy factors, disease factors, patient factors,
and items related to the healthcare system. The authors emphasized that the identification of patients at high risk
for non-adherence and the development of specialized therapies to enhance adherence relies on an understanding
of these contributing factors. For instance, they note that unintentional non-adherence often results from
forgetfulness or cognitive impairment, but intentional non-adherence can be the result of conscious decisions
based on costly prescription medications or complex treatment regimens.
Wilhelmsen and Eriksson (2019) reported a thorough assessment of medication compliance programs and how
effective they are, particularly when dealing with diseases such as diabetes. They learned that successful efforts
to enhance diabetic patients' compliance with their medication often involve employing a variety of strategies,
including the use of technology, changes in behavior, and education campaigns. The authors emphasized that
educational interventions are particularly critical as they enable patients to better understand their prescription
regimens and highlight just how crucial adherence is to effectively be managing diabetes. Additionally identify
a series of significant factors that influence drug adherence. These are the complexity of treatment regimens,
which can discourage patients from adhering to their medications, and the efficacy of social support from loved
ones and physicians.
Stewart, Moon, and Horne's (2023) essay provided a comprehensive review of pharmaceutical nonadherence,
with a focus on its health impacts, prevalence, associations, and potential solutions. In the view of the authors,
drug nonadherence is a significant public health issue whose implications fall on treatment outcomes and
increase morbidity and medical costs. They highlighted that approximately 800 unique factors contribute to
adherence behavior, from the systemic level such as access to care and prescription expenses to patient- related
factors such as psychological and health literacy.
Anderson et al. (2020) emphasized the need for adherence in the proper management of diabetes by
systematically reviewing medication adherence programs and their impact on diabetic patients. The researchers
found that strengthening medication adherence is important to improving glycemic control and reducing
diabetes-related complications such as renal failure and cardiovascular illness. They emphasized that not
following the instructions when taking prescription medicines can have unfavorable health consequences such
as increased hospitalization and health costs. Several effective interventions that have been proven to enhance
medication adherence among diabetes patients are enumerated by Anderson, et al. (2020). They include
strategies such as patient education programs that offer patients information on their condition and the treatments
that can be offered, and simplification of dosing, which simplifies pharmaceutical regimens.
To illuminate the significant effects of medication adherence on patient health outcomes, Kvarnström, et al.
(2021) analyzed the determinants of medication adherence among patients with chronic diseases. The authors
emphasized that regular use of medication can lead to improved glycemic control, fewer issues, and a better
quality of life, particularly in chronic diseases such as diabetes, where medication adherence is crucial for
effective disease management. They learned that noncompliance could produce adverse health results, including
disease progression, longer hospitalizations, and higher costs of medical care. The authors note that whether a
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patient takes drugs depends largely on the patient's perception of drugs; for example, patients tend to miss doses
or discontinue treatment altogether when they believe that their drugs will not work or have undesirable side
effects.
Levels of adherence were significantly affected by monthly income per Sendekie et al. (2022). Patients from
lower incomes had trouble in meeting the cost of their prescription medicines, which was an immediate
determining factor for adherence. The author asserts that increased education level for a patient had a correlation
with improved medication regimen and understanding leading to improved adherence. Knowledge regarding
diabetes and managing it was fundamental. In addition, elderly individuals often have cognitive impairment that
can greatly interfere with their remembering prescription regimens and understanding treatment plans. As a
result, individuals with greater cognitive ability are more likely to adhere to taking their medications as directed,
studies indicate.
Several factors affect medication adherence among older diabetes patients with follow- up treatment, according
to Demoz et al. (2019). The level of understanding regarding diabetes treatment and medication is crucial.
Patients who are more aware of their condition and the importance of adhering to their medication are more
likely to continue with adherence. This category can be helped through educational interventions that enhance
their understanding and self-management skills. Financial issues have a strong influence on medication
adherence. Poorer patients often struggle with paying for prescription medications, resulting in them dropping
doses or withdrawing from therapy entirely. Adherence can be strengthened by overcoming such financial
barriers.
Patient Experiences with Medication Adherence
Religious individuals who are strong are more likely to adapt with ease managing their diabetes, and this is
attributed to greater compliance with prescription regimes, as stated in the Saffari et al. (2019) article. This
association suggests that a patient’s compliance with prescribed treatments may be aided by religious coping
styles such as volunteering and prayer. In addition, the researchers found that social support is a significant
mediating variable, implying that having supportive others can further enhance drug compliance. The authors
suggest an integrated approach to diabetic patients' medication compliance, incorporating social support and
religious coping strategies into diabetes treatment plans.
Religious beliefs can be a powerful motivator for diabetic patients to adhere to their medication, as stated by the
Onyishi et al. (2022) journal. Individuals are more likely to prioritize their treatment when they feel that it is
their religious duty to maintain their health. Improved glucose control and overall health outcomes may be
achieved through consistent medication intake triggered by this feeling of responsibility. Religion positively
influences mental health, which is important in terms of controlling diabetes, according to the authors. Religious
patients are often reported to experience less depression and anxiety, two conditions that could make medication
difficult to manage as directed.
The article by Onyishi et al. (2022) reveals that religious beliefs have a significant impact on medication
adherence among diabetic patients. The authors point out that people who are more religious tend to have better
health outcomes because they are intrinsically motivated to manage their health as part of their spiritual beliefs,
which encourages patients to follow their prescribed medication regimens more closely. They also stress that
faith can instill a sense of duty in patients to care for their health, which leads to improved adherence to
medication. When people see their health management as a spiritual obligation, they are more likely to prioritize
taking their medications as directed.
Although the majority of participants claimed adherence to their prescription anti- diabetes medication, non-
adherence is a critical issue, particularly in younger patients and less educated ones, as revealed by Afaya et al.'s
(2020) article. This raises an issue with a demographic shortfall where younger patients are likely to find it harder
to adhere to their prescription timetables compared to older patients. The study highlights the strong correlation
of self-care measures like blood sugar control and management of diet and medication compliance. Effective
self-care skills increase the likelihood of a patient following the medication regimen. The study further quotes
that improper self-care behaviors are followed by most patients, which can have a negative effect on medication
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adherence.
As per Sahoo et al. (2022), various risk factors and lifestyle choices play a significant role in a diabetic patient's
drug adherence. Only 34.14% of the subjects demonstrated good compliance with their prescribed anti-diabetic
medication, revealing that drug adherence in diabetic patients is appalling. This poor compliance rate is alarming
because it could lead to poor glycemic control and increase the risk of diabetes-related complications. The
authors found that a 2.35-fold higher risk of non-adherence was associated with ongoing alcohol use. Alcohol
may complicate the control of diabetes and make individuals more likely to forget taking their medications.
In line with the Mannan et al. (2021) article, a significant proportion of type 2 diabetes patients had not been in
good medication adherence, showing a widespread public health concern. Approximately 46.3% of the patients
did not adhere to their anti-diabetic medication as recommended, the researchers found. Increasing adherence
rates is needed through individually tailored interventions, as this prevalence indicates. Mannan and co-workers
found various sociodemographic factors associated with poor adherence. It was found that men were more likely
than women to fail to follow through on their treatment regimens, which could mean that gender affects how
patients engage with them.In addition, there were higher chances of non-adherence among poorer families, hence
financial limitations may make it more difficult to obtain prescription drugs and healthcare.
The focus on medication compliance among diabetic patients is critical towards enhanced health outcomes and
successful diabetes management, as stipulated by the Zhang et al. (2021) journal article. Zhang et al. (2021)
suggest that to enhance glycemic control and reduce the risk of diabetes complications, diabetic patients need to
prioritize medication adherence very highly. About 59.8% of patients, by the research findings, suffered from
medication non-adherence, with direct implications to their health conditions. The medication adherence was,
by the study, significantly determined by variables like self-efficacy and support; more especially, increased
support led to high levels of social support that enabled increased self-efficacy resulting in better medication
adherence.
According to the journal article published by LeRoith et al. (2019), diabetes, especially type 2 diabetes, is more
common among people aged 65 years and above, which requires individualized management practices
considering the intricacies of aging. They emphasize the need for personalized treatment targets that take into
account patients' individual values and overall health, in addition to glycemic control. In a quest to ensure highest
treatment results, the guidelines are supportive of involving a multidisciplinary team that includes
endocrinologists and providers of diabetes care. The writers assert that special attention needs to be paid when
evaluating the global health of individual patients as well as comorbidities before deciding the therapy extent in
order to prevent medicine abuse in diabetics. They promote taking reasonable targets in glycemic as well as
adopting individual patients' needs into account.
Interventions to Improve Medication Adherence
Extensive patient education was revealed to be the most effective therapy. This involves teaching individuals
how to live with their diabetes, the importance of adhering to their medication schedules, and the science behind
their actions. Educational sessions were often tailored to fit the needs of patients so that they could grasp their
treatment programs (Presley et al., 2019). It has been shown that direct advice from a pharmacy significantly
enhances drug adherence. Pharmacists explained patients' prescriptions to them, replied to questions, and
provided advice on overcoming barriers to adherence. Patients were encouraged to follow their prescribed
regimens, and confidence was increased through this tailored technique.
As Pouls et al. (2021) posit, tele-feedback through SMS or telephone calls was shown to be an efficient means
of supporting habits of adherence. Through this strategy, healthcare professionals can monitor the progress of
patients and offer help in real-time, helping in the solution of any arising issues. They suggest that another
effective strategy discovered in the review is the integration of medication adherence care among medical
practitioners. In order to prevent miscommunication and enhance compliance, one should ensure that all
members of the healthcare team are communicating and caring for the patient in a similar manner. It is critical
to enhance patient-to-health professional communication. Higher patient satisfaction and compliance can arise
from interactive eHealth programs that provide forums where patients can speak up about concerns and ask
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questions about their medication.
Wiecek et al. (2019), interventions that used a lot of techniques were most often more effective than those which
employed a single technique. This validates the argument that an integrated strategy would be necessary to
address the complex nature of pharmaceutical non- adherence. Enhanced outcomes, for example, can be garnered
by combining behavioral strategies, technology, and patient education. Governments can appropriate funds to
develop and provide funding for multicomponent interventions that utilize behavioral strategies, technology, and
patient education. These interventions can be tailored to suit patients' diverse needs, particularly those of elderly
persons who may have severe challenges with drug management.
Medication adherence interventions and outcomes are critical components of effective healthcare provision,
assert by Eriksson (2019). It has also been proven that nurse and pharmacist interventions are more effective
than those made by general practitioners in promoting adherence and health outcomes. For this reason,
pharmacists and nurses can increase patient comprehension and medication adherence by focused interaction
and targeted training. It has also been proven that nurse and pharmacist interventions are more effective than
general practitioner interventions in improving adherence and health outcomes. This means that nurses and
pharmacists can enhance medication compliance and patient understanding by targeted interaction and targeted
education.
To evaluate treatments for increasing medication adherence in older patients on multiple medications, Cross et
al. (2020) conducted a systematic review. The research points to the importance of some of the therapies that
address issues specific to individualized concerns of older patients such as cognitive problems, complex
medication regimens, and the importance of effective communication with health professionals. Utilization of
reminder systems to aid compliance, behavior and education interventions to enhance patient knowledge about
medication and pharmacist-performed thorough medication reviews for regimen simplification and regimen
complexity reduction are some of the important steps laid out. Multidisciplinary intervention, whose
effectiveness lies in the establishment of a collaborative working of medical professionals to ensure patient-
centered and customized interventions, is also highlighted as a component of the review.
Murali et al. (2019) have identified several effective strategies, such as cognitive- behavioral therapies that allow
patients to effectively manage their treatment regimen and education programs that enhance patients' knowledge
regarding their medication, as well as the importance of adherence. Technology-based interventions such as
reminder systems and mobile applications were also noted for monitoring medication taking and providing
reminders at appropriate times. Further, it was established that multidisciplinary teams of dietitians and
pharmacists and collaborative care models are helpful in providing extensive support. To conclude, the review
emphasizes that older patients with ESKD can improve medication adherence to a considerable extent by
adopting a combination of behavioral, educational, and technological interventions, which will enhance their
health outcomes.
Allemann et al. (2017) described that the overarching goal of efforts to reduce medication non-adherence in
older patients is to make the interventions used and the profile of the patient match. Effective practices involve
individualized education directed towards habituation with prescription regimens, simplification of dosing
regimens to reduce complexity, and the use of reminder devices to remind patients about taking their
medications. Use of multidisciplinary teams with doctors, nurses, and pharmacists can also improve
communication regarding the treatment regimen and deliver comprehensive care.
Filipino Geriatric Diabetic Patients
Dimaporo et al. (2024) pointed out that among diabetic Filipino patients, particularly those who have had the
disease for more than five years, exocrine pancreatic insufficiency (EPI) prevalence can be underappreciated.
Especially in elderly individuals, who are at greater risk for both diabetes and pancreatic impairment, this
underestimation can lead to severe medical conditions, like malnutrition and a compromised quality of life. To
facilitate early detection and treatment, the authors recommend routine EPI screening of elderly diabetic patients.
For Filipino patients, screening programs carried out in the community may be required because health
awareness and access may differ. These programs should focus on educating patients and healthcare providers
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about the presentation and symptoms of EPI, including unexplained weight loss and gastrointestinal symptoms.
Exploring active ageing health determinants of working and retired Filipino elderly, de la Vega et al. (2021)
informed the variables shaping their general wellness and health. This is relevant for elderly adults with diabetes
given that, according to the findings revealed by the study, diabetes and other non-communicable diseases are
very common among them. To promote active aging, the authors emphasize the importance of social support,
lifestyle habits such as diet and exercise, and availability of healthcare services. All these are critical to effective
diabetes management in older Filipino adults. The report indicates that community-based health programs
focusing on diabetes education, regular screening, and the promotion of healthy lifestyles should be
implemented.
According to Tolentino and Brynes's (2024) journal, elderly diabetic patients in the Philippines need to be
integrated fully into culturally appropriate diabetes treatment programs that merge the Filipino traditional values
of community and family care. Through a sense of belonging and shared responsibility among members of
families, such programs are likely to improve treatment program adherence. To fulfill the emotional and social
role of food in Filipino culture, authors also propose the inclusion of dietary education that honors traditional
eating practices but promotes healthier eating. Healthcare workers can create supportive settings that allow older
adults to manage their diabetes care through the use of family networks and community resources. This will
ultimately enhance the health and well-being of this group.
A significant prevalence of diabetes is reported among community-living older Filipinos, especially with a self-
reported diabetes rate of 20.5%, according to Giron and de la Vega (2022). This study included a cross-sectional
analysis of older adults aged 60 years and above, showing that no demographic differences were observed
between the diabetic and non- diabetic populations in age, sex, education, or BMI. However, it found that the
elderly with diabetes were generally associated with multiple comorbidities including visual impairment,
hypertension, and hyperlipidemia. This therefore calls for targeted public health interventions in prevention and
management of the disease among such a vulnerable population who are at a higher risk of morbidity and
mortality in the face of the disease and its complications.
Under Garcia et al.'s (2022) writing, this study concentrates on diabetes' implications to sensory impairments in
working and retired academicians in the Philippines. Detection is found with a high frequency of visual as well
as hearing impairments between individuals with type 2 diabetes mellitus and may significantly alter their quality
of life and also functional independence. The study pointed out that such sensory input deficiencies interfere
with diabetes control and enhance the risk of falling or injuring elderly populations. The holistic approaches to
healthcare suggest incorporating diabetes care with health to enhance well-being in geriatric populations in the
Philippines.
Pivotal to understanding how knowledge might unfold with health outcomes is Ydirin's (2021) research, in a
rural Filipino community on the relationship between health literacy and adults' health-promoting behaviors who
are at risk for diabetes. Poor health literacy is viewed as being responsible for worse health-promoting behaviors,
further exacerbating risks of contracting diabetes in old age. This finding is particularly relevant to Filipino
geriatrics because a boost in health literacy is likely to empower them to use self-management practices more
effectively. The conclusion drawn from the study could be that tailored educational programs at improving health
literacy may be necessary for preventing diabetes and healthier living among this population.
Related Studies
Enhanced knowledge of their condition and treatment can greatly increase adherence rates, as Lohrasbi et al.
(2021) also highlighted the critical role played by health literacy in medication adherence among older diabetic
patients. In the authors' view, various comorbidities and cognitive impairment are common issues that older
people have difficulties with, which can make the management of their medication for them more challenging.
They suggested introducing patient teaching programs that seek to meet the special needs of older diabetic
patients through simplifying complicated drug regimens and dealing with the significance of compliance.
Furthermore, by providing psychosocial and instrumental support, creating a supportive environment with
family member involvement could further improve compliance.
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Improved understanding of their condition and management is able to significantly boost levels of medication
adherence, report Lohrasbi et al. (2021), again stressing the underlining critical contribution health literacy will
have to boosting medicine adherence in older individuals with diabetes. In line with the authors' view, numerous
comorbidities as well as the decay of intellects are universal matters that affect old individuals and hence may
enhance chances of poor administration of medicine among them. They recommend installing instructional
programs suited to the particular needs of older diabetic patients and focused on rendering complex drug regime
simpler to follow and enhancing appreciation for the need to adhere. In addition, establishing an enabling
environment through involving families will further ensure adherence by practical as well as psychologic
mechanisms.
Musavi Ghahfarokhi et al. (2024) outlined the relationship among food compliance, health literacy, and dialysis
adequacy and highlight the key role that health literacy has to play in accommodating dialysis patients with
chronic disease. Greater health literacy, argue the authors, is associated with higher medication and food
compliance and is particularly useful for older patients with diabetes who may also be undergoing dialysis. To
improve medication and diet compliance, they suggest the use of patient-specific education programs that will
make it easier for patients to learn more about their disease states and therapeutic regimens. To make sure that
older patients clearly comprehend their regimens, authors also stress the need for healthcare providers to
continuously measure levels of health literacy and accordingly modify communication strategies.
Among type 2 diabetic patients, there is a high correlation between medication compliance and health literacy,
and it has been suggested that higher adherence to treatment regimens is a result of higher health literacy skills
(Hasanpour et al., 2024). One of the key strategies to enhance medication adherence among older diabetic
patients is for healthcare providers to focus on enhancing health literacy. The authors advocate for the
implementation of targeted educational programs that break down complex medical facts regarding diabetes
therapy and cater to the specific needs of elderly citizens. In order to make sure that older citizens are aware of
their medication rules and the necessity of adherence, they also focus on the necessity of constant assistance and
communication between patients and healthcare professionals.
The Mendes, Martins, and Fernandes (2019) research centers on medication compliance, exercise, and dietary
control in older adults with diabetes, with an emphasis on the strong relationships with cognitive functioning,
anxiety, and depression. The study indicates that medication non-compliance is highly related to heightened
levels of anxiety and depression, suggesting that psychological factors are paramount to therapeutic compliance.
Additionally, cognitive impairment was found to predict non-adherence to physical activity, implying that
cognitive function is essential to maintaining an active lifestyle in this population. The authors recommend that
holistic management strategies be implemented that not only address the medical concerns of elderly people
with diabetes but also their mental health and cognitive function.
The Świątoniowska-Lonc et al. (2021) systematic review demonstrated the complex psychosocial behavior-
adherence relationship as it discusses the psychosocial determinants of type 2 diabetes patients who are adherent
to medication. Authors highlight several important psychosocial determinants, such as depression, anxiety,
social support, and physician-patient communication, which have a dominant influence on adherence. They
observe that although effective social support networks can enhance compliance by reminding the patient and
encouraging them, negative feelings such as anxiety and hopelessness can interfere with patients complying with
their treatment. The study also stresses that there must be good communication between health care professionals
and patients so that there is understanding and trust, both of which are prerequisites for compliance.
Perception of type 2 diabetes by type 2 diabetes patients also influences their behavior in adhering, as explained
by a study conducted by Hashimoto et al. in 2019 proposed in its investigation of the correlation between illness
perception of patients and medication adherence. The findings of the study indicate that increased rates of
medication adherence correlate with a positive perception of diabetes, characterized by a set of attitudes towards
disease control and treatment effectiveness. Through education and conversation, the authors suggest that
physicians attempt to better educate and improve patients' attitudes and knowledge about their diabetes. Patients
will be more likely to adhere to prescription habits as long as they understand their disease better, which they
may learn to accept positively. The study also emphasizes how much treating diabetic care is needed.
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The "Adherence to Treatment in Medical Conditions" chapter by McElnay and McCallion (2020) discussed the
challenges of medication adherence in older patients, particularly with regard to the special challenges that this
group of patients are prone to because of such factors as polypharmacy, deteriorating mental capabilities, and
varying health literacy. The writers observe that the co-morbid presence of a range of chronic diseases may
confuse and complicate the ability of elderly citizens to follow prescribed regimens. They suggested that health
workers apply comprehensive approaches that are tailored to meet the specific needs of elderly citizens, for
instance, simplifying prescription regimens, enhancing patient education, and promoting effective patient-to-
worker communication.
AlQarni et al.'s (2019) research assesses medication adherence in Saudi patients residing in Khobar City with
type 2 diabetes mellitus. It offers critical information regarding adherence patterns and determining factors.
35.8% of the 212 study participants only exhibited high compliance with their anti-diabetic medications,
reflecting a significant compliance deficit among this group. HbA1c level and adherence score were correlated
strongly, implying worsening glycemic control as in lower adherence. The research further showed that patients
in bulk change prescription times during Eid and Ramadan, an evidence of how cultural practices affect drug
compliance. The authors assert that pharmacists are key educators and encourage improved patient counselling
to the aim of changing attitudes toward medication and adherence importance. Sanati, Vaezi, and Jambarsang
(2020) conducted research in Iran among adults aged 60 and older examining medication adherence and
associated characteristics, and it has important new findings about how hard this group of people is doing. The
study, sampling from 196 people aged 60 and older using the Morisky Medication Adherence Scale for
measurement of medication adherence, showed that more than half of those in the sample had low rates of
adherence with their prescribed drugs. Difficulty with medication regimens, side effects, cognitive impairment,
and cost issues are some of the problems the authors list as responsible for low levels of adherence. They note
that sensory and cognitive changes in old age may contribute to confusion about how to take medications, thus
exacerbating adherence issues.
Theoretical Framework
Rosenstock in 1974 came up with the Health Belief Model (HBM) that provides a general framework of
explaining health behavior, especially with regard to chronic conditions like diabetes. According to the model,
a person's beliefs about whether they are at risk of suffering from a health problem, the seriousness of the
problem, the advantages of making a change, and the drawbacks of making the change all impact their likelihood
of adopting health- improving actions. The concept of self-efficacy, referring to an individual's perception of his
or her ability to perform an action successfully, is also part of the model. With the utilization of the HBM, the
present study can gain more insight into how the intervention could impact patients' perceptions of their
prescription regimen and diabetes control and potentially improve adherence and health outcomes.
The Health Belief Model (HBM) is a foundation model for explaining the process of medication compliance in
elderly diabetic patients for this research. By integrating QVoC technology, the research aims to enhance
patients' belief in the severity of the illness and in their vulnerability to complications of diabetes, which are key
constructs under the HBM. This approach aligns with the model's emphasis on medication adherence perceived
benefits, as patients will be getting tailored information that highlights the importance of compliance with their
prescribed regimens.
Conceptual Framework
Figure 1: Conceptual Framework
INDEPENDENT VARIABLE
Medication Adherence QVoC Intervention
DEPENDENT VARIABLE
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The conceptual framework of the study illustrated how the QVoC intervention, the independent variable, and
the dependent variables—medication adherence, knowledge, and blood sugar levels (HbA1c) among older
diabetic patients—interrelate. Through the use of voice-activated QR codes, the QVoC intervention seeks to
enhance patients' understanding of their prescription schedules and promote adherence by making information
readily accessible. This paradigm identifies how revolutionary technology can help older adults who struggle to
manage their health in the right way.
Statement of the Problem
This study aimed to investigate the Effectiveness of QVoC (QR Code with Voice Content) in Enhancing
Medication Adherence for Geriatric Diabetic Patients in Koronadal City.
This study specifically seeks to answer the following questions:
1. What is the demographic profile of the respondents in terms of:
a. Age
b. Sex
c. Educational attaintment
1. What is the level of medication adherence among geriatric diabetic patients before using QVoC
QR Code?
2. What is the level of medication adherence among geriatric diabetic patients after using QVoC
QR Code?
3. Is there a significant difference in the level of medication adherence among geriatric diabetic
patients before using QVoC QR Code?
Hypotheses
Null Hypothesis
H₀: There is no significant difference in medication adherence among Geriatric Diabetic patients before and
after using QVoC.
Alternative Hypothesis
H1: There is a significant difference in medication adherence among Geriatric Diabetic patients before and
after using QVoC.
Significance of Study
The following will benefit from this study:
Geriatric Diabetic Patients: Since enhanced compliance with drugs and greater awareness can result in better
health results, quality of life, and fewer complications with diabetes care, the geriatric patients themselves benefit
the most from this study.
Health Care Practitioners: Doctors, nurses, and pharmacists will learn about how the use of QVoC and other
technology can help them educate the patient and control medication, which will ultimately result in better
treatment programs tailored to the needs of older adults.
Health System: By addressing the imperative of bringing cutting-edge digital health solutions to bear on
addressing medication compliance challenges—a key driver of being able to keep chronic diseases like diabetes
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under control in older segments—the findings might be able to guide health policies and strategies.
Family Relatives and Caretakers: QVoC will enable family members and caregivers to take care of their
diabetic relatives in less stressful terms through increased adherence to medications as well as experience. This
will lead to a more supportive environment for elderly patients.
Future Researchers: The findings of the study could be used as a basis for future research in investigating the
utilization of technology to improve medication adherence among various populations and conditions of illness.
Researchers: The researchers benefited from this study by gaining valuable knowledge on how technology,
specifically QR codes with voice content (QVoC), can be used to improve medication adherence among elderly
diabetic patients. They also developed skills in designing and evaluating digital health interventions, as well as
in collaborating with healthcare providers and local communities to address public health challenges
Scope and Delimitation
This research focuses on incorporating QR Code with Voice Content, or QVoC, into a digital tool to help the
geriatric diabetic patients in Koronadal City, South Cotabato improve their knowledge and medication
adherence. The system would be tested by healthcare professionals, caregivers, and patients, all of whom are
involved in improving the practicality and suitability for the culture of the QVoC system. However, the study is
specific only to geriatric diabetic patients of Koronadal City and may not be generalized to other areas or
populations. Population access may be limited due to accessing a smartphone. The focus on diabetes excludes
other chronic diseases. Finally, the use of voice content would be restricted to local language or dialect and
makes it limited. Given that time constraints will reduce the study period to only six months, it may not be long
enough to capture the long-term effects that may arise from an extended period of exposure to the QVoC
intervention. Resource constraints, also in terms of finance and technical support, limit the generalizability of
results.
Definition of Terms
For further understanding, the following terms are operationally and conceptually defined:
QVoC: It refers to established technology innovation presented by the researcher using QR codes with bundled
voice content as a method for presenting patients with concise information relating to their drugs in the form of
dosing guidance and potential side effects.
Medication adherence: It refers to the degree with which the action of a patient matches the common
understanding recommendations between the patient and the health worker regarding timing, dosing, and
medication intake frequency.
Geriatrics: Is the branch of medicine concerned with the health care of older adults, dealing with the prevention,
diagnosis, treatment, and management of diseases and conditions common in old age
Diabetes mellitus: (Often shortened to diabetes) is a chronic metabolic disease characterized by elevated levels
of blood glucose (hyperglycemia) resulting from defects in insulin secretion, insulin action, or both.
Respondents: It refers to the individuals who provide data for analysis by completing surveys, questionnaires,
or interviews
METHODOLOGY
This chapter presented the research method, the respondents of the study, sampling technique, the research
instrument, scaling and quantification of data, data gathering procedure and statistical treatment of data.
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Research Design
The study design applied a quasi-experimental methodology according to Maciejewski (2020), which is
especially suitable for assessing the effectiveness of the QVoC (QR Code with Voice Content) intervention in
improving medication compliance among geriatric diabetic patients. Quasi-experimental design refers to a
method used to examine the impact of independent variables on dependent variables without random assignment
(Appinio, 2023).
This is a suitable design for this study because it allowed for the assessment of real- world interventions in
settings where randomization may be difficult or unethical, particularly when working with vulnerable
populations such as the elderly. Quasi-experimental design offers the researcher the possibility of assessing
differences in medication compliance before and after the introduction of the QVoC intervention and taking into
consideration practical constraints. Besides, this approach provides valuable information on causal effects
between adherence and intervention outcomes, which facilitates the comprehension of the effect of technology
on diabetes care among geriatric patients in a less apparent manner.
Research Locale
This research was carried out in Barangay Morales, City of Koronadal. It provided distinct demographic and
socio-economic features necessary for determining medication compliance among geriatric diabetic patients.
Based on the Philippine Statistics Authority, the population of Koronadal City was around 195,398 as of 2020,
and Barangay Morales contributes significantly to this number. A barangay usually has a combination of ages
and has a proper number of elderly people, which is important for this study on geriatric patients.
Barangay Morales has a population of approximately 9,133, which represents 4.67% of the total population of
Koronadal City. The barangay has shown an upward trend for diabetes and is also a research priority for diabetes
care and compliance to medication. Elderly living in Barangay Morales are facing health literacy issues and
limited resources available for healthcare services that contribute largely towards their ability to follow
recommended regimens of prescribed medication.
The socio-economic profile of Barangay Morales also warrants its choice as the study area. The majority of its
residents are from lower-income groups, whose access to health care services and diabetes education could be
restricted. Furthermore, the health care facilities within the barangay could be poorly equipped, affecting the
quality of health care extended to diabetic patients. All these conditions highlight the necessity for creative
interventions, like the QVoC system, to promote knowledge and medication adherence in this population at risk.
Figure 2: Map of Koronadal city, South Cotabato, Philippines
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Respondents of the study
Respondents of this study were elderly diabetic patients from Barangay Morales, Koronadal City. The
participants for inclusion were those who are 60 years and above who have type 2 diabetes and are currently
from Barangay Morales. Participants will also need to be able to give informed consent and participate in the
interview. Exclusionary criteria would be those who have significant cognitive impairments that will render it
impossible for them to understand the aim of the study or offer informed consent, and those who have significant
comorbidities that can compromise their ability to adhere to medication regimens, such as untreated depression
or other incapacitating illness. This focused design ensures that the study captures the experiences and
viewpoints of those most impacted by diabetes management challenges, thus offering insightful information that
can guide future interventions aimed at enhancing health outcomes among geriatric populations in comparable
contexts.
Sampling Technique
To determine the number of respondents needed for the study, the purposive sampling approach was employed
as per Robinson (2024), whereby the participants are chosen based on certain characteristics that pertain to the
research question. The method is best suited to allow us to ensure that the respondents chosen fall under our
inclusion criteria necessary for the research, such as elderly persons who are diabetic and taking antidiabetic
medication. Purposive sampling, or judgmental or selective sampling, is a non-probability method of sampling
in which participants are selected on purpose according to predetermined criteria that relate to the aim of the
study.
The strategy suits research that requires extensive comprehension of phenomena as it allows researchers to focus
on individuals likely to provide rich and relevant information.
Research Instrument
The questionnaire was specifically designed to assess various dimensions related to medication compliance of
old diabetic patients before and after the QVoC intervention. Each questionnaire contained 10 questions for pre-
intervention about medication adherence and for post intervention. The questionnaire contains demographic
items to put the respondents' backgrounds into perspective, followed by pre-test and post-test items assessing
adherence behavior on a 4-point frequency scale. The scale allows accurate measurement of frequency of
compliance, medication taking habits, and problems experienced by the participants. Parallel pre- and post-
intervention items allow changes introduced by the QVoC tool to be compared.
Furthermore, a subsection evaluating the usability and effectiveness of the QR Code intervention was
incorporated on a Likert-type scale to quantify patients' self-reporting of the effect of the technology on
medication management. The dual interest—both in compliance of behavior and technology acceptability—
serves to ensure that the instrument is not only measuring the outcome but also the user experience of the QVoC
system. The formal format is amenable to quantitative analysis for trend detection and effectiveness, while verbal
analogies and simple instructions allow for respondent clarity and valid self-reporting. The questionnaire is thus
a valid tool to systematically determine how combining QR codes with voice content can enhance medication
adherence in an older diabetic population.
Also, three master's degree registered pharmacists were requested to validated the contents of the research
questionnaire. Prior to the printing of the final questionnaire version, recommendations from the validators were
considered as per revising and finalizing the questionnaires.
Research Procedure
To successfully conduct our study, we began by securing the necessary demographic data from the City Health
Office, specifically the census of geriatric diabetic patients in our target area. This information served as the
basis for identifying potential participants. After obtaining the census, the researchers prepared a formal letter
of intent to conduct the research, which was duly signed and approved by the research adviser. Following this,
we secured the approval of the Barangay Captain to carry out the study within the community. Once permission
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was granted, the researchers proceed to prepare the necessary materials, including the QR codes integrated with
voice content. These QR codes were developed with the assistance of the IT personnel and were designed to
enhance medication adherence through audio-based instructions. The researchers then gathered the identified
participants and conducted an orientation and training session lasting for 45 minutes to ensure the respondents
understood how to use the QR code system effectively. After that, the researchers allow them use the app for at
least 5-10 minutes to assess if they understand the process. After the orientation, the researchers administered a
pre-test to assess their baseline knowledge and behavior related to medication adherence. Two weeks after the
initial intervention, the researchers conducted a post-test to measure any improvements or changes resulting
from the use of the QR code with voice content system. This approach allowed the researchers to evaluate the
effectiveness of our intervention in supporting medication adherence among geriatric diabetic patients.
Statistical Treatment
Descriptive statistics (Ramachandran & Tsokos, 2020), i.e., percentage and frequency, were used by the
researcher to display respondents' demographic information in terms of gender, age, and educational level.
Descriptive statistical values provided a description of the population structure of the sample for enhanced
understanding of how demographic variables would influence medication adherence.
In order to determine the level of medication adherence among geriatric diabetic patients prior to the application
of QVoC QR Code, the researcher shall employ mean scores obtained from a validated tool on medication
adherence like the Morisky Medication Adherence Scale (MMAS). It was employed in assessing the levels of
medication adherence by examining self-reported medication-taking behaviors thereby enabling the researcher
to employ such a benchmark.
The same validated medication adherence scale (MMAS) will be used by the researcher to maintain consistency
in the measurement of the level of medication adherence among geriatric diabetic patients following the use of
QVoC QR Code. A comparison of post- intervention and pre-intervention scores was enabling the researcher to
identify whether there are differences in the levels of adherence that are due to the QVoC intervention.
To determine the difference in the level of medication adherence between the pre- existing geriatric diabetic
patients and those which emerged after applying QVoC QR Code, inferential statistical tests like paired t-tests
were utilized by the researcher depending on whether the data fulfilled parametric assumptions. These were
tested if there are statistically significant differences in levels of adherence, pre-intervention and post-
intervention, thus determining if the QVoC strategy has an effect on drug compliance among this group.
Ethical Considerations
Key ethical issues arise when appreciating QVoC with voice content being implemented to enhance knowledge
for enhancing medication compliance among elderly diabetic patients. Such considerations are based on the
Respect for Persons, Beneficence, and Justice principles. These three principles, which constitute the skeleton
of the Belmont Report, are essential in informing the use of this research in theoretical and practical scenarios.
This principle focuses on the acquisition of informed consent from all participants. The participants were
thoroughly informed regarding the objectives, procedures, possible risks, and benefits of the study. They were
also clearly informed of their right to withdraw from the study at any time. This guarantees that participants are
treated as autonomous agents who can make informed choices regarding their participation. Care will be taken
with older people who might suffer a loss of autonomy as a result of mental impairment or decline in health.
Proper support and information will be given to such people, enabling them to comprehend their rights and make
informed decisions regarding their involvement.
This principle demands that research be conducted to maximize benefits while minimizing risks to participants.
The research’s participants were informed and have considered the potential risks involved by being part of the
QVoC intervention carefully and address them. Clear and detailed instructions shall be given during the
intervention stages to promote the well-being of the participants. The possible advantages, such as better
medication compliance and increased understanding of how to manage diabetes, will be highlighted. These
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advantages were illustrate how being part of the intervention can result in improved overall health among older
patients.
The doctrine of justice focuses on the fair choice of participants such that no group is disproportionately burdened
or disproportionately excluded from sharing in the rewards of the study. This research was making every effort
to sample a representative number of geriatric diabetic patients in Barangay Morales. Every attempt will be made
to sample by age groups, gender, and educational level such that the results are applicable to a wide range of this
at-risk population.
To ensure personal data of the participants is secure, confidentiality and privacy will be ensured during and after
the study. Participant information was anonymized, and only authorized members of the study team will access
this information. Storage of information will be under guidelines to exclude unauthorized access. Participants
will be informed that they can guarantee confidentiality of response and use for research purposes.
Transparency is key to establishing trust between participants and researchers. Researchers explicitly state the
aim of the study, the research methods employed, and any alterations that occur during the research process.
Participants will be made aware of how their data will be utilized and represented in the findings. Transparency
was helping participants realize their role in generating knowledge regarding medication adherence.
RESULTS AND DISCUSSIONS
This chapter presented the findings and analysis of the study entitled "Integrating QVoC (QR Code with Voice
Content) to Enhance Medication Adherence for Geriatric Diabetic Patients." The results are discussed in
accordance with the specific objectives outlined in the Statement of the Problem.
Demographic Profile
Table 1 presented the demographic profile of the geriatric diabetic patients who participated in the study. The
data cover three key variables: age, sex, and educational attainment. Understanding these demographic
characteristics is essential in contextualizing the respondents’ baseline familiarity with technology and potential
responsiveness to the QVoC (QR Code with Voice Content) intervention. These factors may influence
medication adherence behaviors and provide insight into how personalized health technologies can be optimized
for elderly patients in similar settings.
Table 1
Demographic Profile of Respondents
Profile Segmentation Frequency (f)
n=20
%
Distribution
Age 60-65 years old 8 40.0
66-70 years old 6 30.0
>70 years old 6 30.0
Sex Female 13 65.0
Male 7 35.0
Educational Attainment Elementary Level 1 5.0
Elementary Graduate 0 0.0
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High School Level 1 5.0
High School Graduate 16 80.0
College Level 0 0.0
College Graduate 1 5.0
Post Graduate 1 5.0
The demographic profile of the geriatric diabetic patients participating in this study is summarized in Table 1. A
total of 20 respondents were included, with their ages ranging from 60 years and above. The largest age group
was between 60 to 65 years old, comprising 40.0% (n=8) of the total respondents. This was followed by those
aged 66 to 70 years old (30.0%, n=6) and those above 70 years old (30.0%, n=6), indicating that a considerable
portion of the participants belonged to the early and mid-stage geriatric age range.
In terms of sex, the majority of the respondents were female, accounting for 65.0% (n=13), while the remaining
35.0% (n=7) were male. This distribution suggested a higher prevalence of participation among elderly women,
which may reflect broader demographic trends in health service utilization among geriatric populations.
With regard to educational attainment, a significant number of respondents were high school graduates (80.0%,
n=16), indicating that most participants had attained basic formal education. A small proportion had either lower
(elementary level – 5.0%,
high school level – 5.0%) or higher educational qualifications (college graduate – 5.0%, post-graduate – 5.0%).
This educational profile suggests a moderate literacy level among respondents, which is an important
consideration in the implementation of technological interventions like QVoC, as it may influence their ability
to understand and adhere to digital health tools.
These findings suggested that the participants had the cognitive and literacy ability to be able to use and benefit
from the QVoC tool. Their age, gender, and education levels indicate that with good design and support,
electronic health interventions such as QVoC can be acceptable and effective among corresponding elderly
populations. The demographic characteristics also show the need to adjust such tools to the special needs and
capabilities of elderly people to ensure maximum use and health benefits.
The results of this research are confirmed by Ahmad et al. (2020) highlighted that older diabetic patients'
willingness to maintain the use of digital health technologies is strongly related to perceived usefulness, ease of
use, and personal traits including education level and cognitive ability which are in accordance with the moderate
literacy and educational level seen among the present respondents.
Likewise, Yan et al. (2022) recognized demographic variables such as age and education, as key predictors of
diabetes awareness, control, and utilization of digital technologies among older Chinese patients, underscoring
the need for interventions such as QVoC to be specifically designed according to the capabilities of this older
population.
Besides, Al Mansour (2020) supported that age and gender were important predictors of type 2 diabetes risk and
management behavior in semi-urban older populations. This lends validity to the finding of the current study of
a higher percentage of female respondents, which may testify to the prevalence of gendered health-seeking
behavior and utilization of services among the elderly.
Table 2 presented the mean responses to ten items assessing medication adherence among geriatric diabetic
patients before the introduction of the QVoC (QR Code with Voice Content) intervention. The items included
both negatively and positively worded questions, allowing a more nuanced understanding of the respondents’
behaviors and challenges in adhering to their prescribed diabetes medications.
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Table 2
Level of Medication Adherence Among Geriatric Diabetic Patients Before Using Qvoc Qr Code
Items Mean SD Remarks*
1. Do you have difficulty in remembering to take your
diabetes medication as prescribed?
3.20 0.77 High extent
2. Over the past two weeks, have you missed or skipped
taking your diabetes medication?
2.85 0.93 High extent
3. Have you ever skipped or reduced your diabetes
medication due to side effects without consulting your
doctor?
2.70 1.13 High extent
4. Do you leave home or travel without bringing your diabetes
medication?
3.15 0.67 High extent
5. Did you remember diabetes medication yesterday as
prescribed?
2.95 0.89 High extent
6. Do you continue taking your diabetes medication as
prescribed even when your blood sugar feel under control?
2.90 0.85 High extent
7. Do you ever feel burdened or hassled by sticking to your
diabetes treatment plan?
3.05 1.10 High extent
8. Do you struggle to remember to take all your prescribed
diabetes medications?
3.05 1.10 High extent
9. How consistent are you in taking your diabetes medication
at the correct time each day? 2.65 0.75 High extent
10. Do you follow the specific instructions for taking your
diabetes medication (e.g., before/after meals, with food,etc.)? 2.95 0.83 High extent
Overall Mean 2.95 0.179 High Extent
Prior to using QVoC, respondents reported experiencing difficulties in several aspects of medication adherence.
For instance, the item “Do you have difficulty in remembering to take your diabetes medication as prescribed?”
yielded a mean score of 3.20 (SD = 0.77), indicating a high extent of forgetfulness. Similarly, frequent challenges
such as skipping doses without consulting a physician (M = 2.70), forgetting medication when traveling (M =
3.15), and struggling to remember all prescribed medications (M = 3.05) were reported to a high extent. These
behaviors reflect poor adherence and highlight the need for targeted interventions to support geriatric patients in
managing their medication routines.
However, it is important to note that even positively framed questions, such as “Did you remember diabetes
medication yesterday as prescribed?” and “Do you follow the specific instructions for taking your diabetes
medication?” also showed only moderate to high extent responses (means ranging from 2.90 to 2.95). This
suggested that while patients may sometimes comply with their medication schedule, the overall consistency
and precision in adherence remained limited.
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The overall mean score of 2.95 indicates a high extent of adherence-related issues, particularly when examining
items that reflect forgetfulness, inconsistency, and perceived burden. These findings underscore the baseline
challenges faced by elderly diabetic patients and establish a clear rationale for implementing a voice-assisted
QR code intervention like QVoC to potentially reduce these barriers and enhance medication adherence.
The improvement in adherence can be attributed to the QVoC's voice cues and convenient access to drug guides,
which supplemented memory loss and cognitive impairments characteristic of the elderly. The interactive and
user-friendly features of QVoC also optimized patient interaction and reduced confusion, enabling the patients
to adhere more precisely to their treatment regimen.
Comparable enhancements in medication compliance have been seen in other studies investigating the efficacy
of targeted interventions for chronic disease management in older populations. For example, Punnapurath et al.
(2021) found that the use of personalized digital platforms and reminder systems tailored to geriatric patients
with chronic conditions led to a remarkable improvement in rates of compliance. These interventions, typically
defined by easy-to-use interfaces and step-by-step simplifications, helped patients to better navigate complicated
medication regimens and decrease rates of missed doses.
Similarly, Ngamdee et al. (2024) highlighted the need to transcend behavioral and cognitive barriers that are
mostly responsible for medication adherence in older diabetic patients. The study validated that intervention
strategies fighting forgetfulness, limiting drug procedure explanations, and simplifying administrative tasks
brought substantial value to higher levels of adherence. By tailoring the intervention design to meet the particular
cognitive and lifestyle demands of elderly patients, the study found the potential of behaviorally based
interventions to bring measurable improvement in medication adherence.
But importantly, the relative efficacy of internet interventions is heterogeneous among patient groups.
Świątoniowska-Lonc et al. (2021) declare that psychosocial determinants are at the center of controlling the
behavior of compliance. Variables such as the emotional state of the patient, self-efficacy, motivational status,
and support networks play an important role in moderating the effectiveness of technological devices to a great
extent. Even when adherence is quantitatively improved, certain patients might continue to have difficulty with
compliance over time due to anxiety, depression, or disbelief in the effectiveness of the treatment. The present
findings indicate that although digital innovation such as QVoC is promising, such innovations need to be
supplemented with comprehensive patient care approaches that aim at the patient's overall psychosocial reality.
Table 3 presented the mean level of medication adherence among geriatric diabetic patients after the
implementation of the QVoC (QR Code with Voice Content) intervention, with reverse scoring applied to
selected negatively worded items. This scoring approach ensures that higher mean values consistently indicate
a greater extent of adherence across all items, regardless of their original wording. The results demonstrate a
substantial improvement in the respondents’ medication-taking behaviors following the use of the QVoC
technology.
Table 3
Level of Medication Adherence Among Geriatric Diabetic Patients After Using Qvoc Qr Code
Items Mean SD Remarks*
1. Since using the intervention, do you still have difficulty in
remembering to take your diabetes medication as prescribed?
**
3.60 0.60 Very High Extent
2. Over the past two weeks, have you missed or skipped
taking your diabetes medication? **
3.65 0.67 Very High Extent
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3. Since using the intervention, have you skipped or reduced
your diabetes medication due to side effects without
consulting your doctor?**
3.70 0.80 Very High Extent
4. When traveling or leaving home, do you still forget to bring
your diabetes medication?**
3.65 0.67 Very High Extent
5. Did you remember and take your diabetes medication
yesterday as prescribed?
3.75 0.55 Very High Extent
6. Since the intervention, do you continue taking your
diabetes medication as prescribed even when your blood
sugar feels under control?
3.75 0.55 Very High Extent
7. Since the intervention, do you still feel burdened or hassled
by sticking to your diabetes treatment plan?** 3.60 0.68 Very High Extent
8. Since the intervention, do you still struggle to remember to
take all your prescribed diabetes medications?** 3.60 0.68 Very High Extent
9. Since the intervention, are you now consistent in taking
your diabetes medication at the correct time each day? 3.80 0.41 Very High Extent
10. Since the intervention, do you now follow the specific
instructions for taking your diabetes medication (e.g.,
before/after meals, with food,etc.)?
3.85 0.37 Very High Extent
Overall Mean 3.70 0.09 Very High Extent
The overall mean adherence score increased to 3.70 (SD = 0.09), categorized as a very high extent, suggesting
that the majority of respondents significantly enhanced their consistency and compliance with their diabetes
treatment regimen. Notably, even items that previously reflected poor adherence showed marked improvement.
For example, the item “Since using the intervention, do you still have difficulty in remembering to take your
diabetes medication as prescribed?” recorded a mean of 3.60, indicating that patients were now remembering
to take their medications more reliably. Similar improvements were seen in questions related to skipping doses
due to side effects (M = 3.70) and forgetting medication when traveling (M = 3.65).
Positively worded items further reinforced this upward trend. Participants reported high consistency in taking
medications at the correct time (M = 3.80) and strict adherence to specific intake instructions (M = 3.85), the
highest among all items. Moreover, behaviors indicating long-term commitment, such as continuing medication
even when blood sugar appears controlled (M = 3.75), were also positively rated.
These findings underscore the effectiveness of the QVoC intervention in promoting medication adherence. The
consistently high post-intervention scores across both formerly negative and positive behaviors reflect a
comprehensive improvement in the medication routines of the elderly diabetic population. This suggests that
voice-assisted QR code technology may serve as a valuable and accessible tool in supporting chronic disease
management among older adults.
The nature of the large medication adherence observed in this setting is primarily a result of the interactive nature
and self-explanatory nature of the QVoC intervention. By combining visual and auditory aspects, QVoC gave
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an accessible and clear-cut platform potentially decreasing the cognitive load usually implied with intricate
medication regimens. This usability might have been advantageous to elderly patients, who are more prone to
memory impairment and confusion, to easily understand and remember the prescribed regimens. The
customized, persistent voice prompts in the QR codes served as continuous reminders that reinforced daily
compliance and mitigated the possibility of skipped or improperly taken medication.
Moreover, the real-time availability and mobility of the QVoC system allowed patients to engage with their
medication instructions anywhere they were, i.e., on the go and while traveling the very circumstance in which
nonadherence is habitually encountered. Being readily available all the time served not only to compensate for
forgetfulness but also gave patients greater control over their health, raising the likelihood that their motivation
and confidence to continue prescribed treatments could be boosted.
These results are consistent with Babel et al. (2021), who highlighted the increasing potential of artificial
intelligence and digital innovations to enhance health behavior in patients with chronic diseases. In their
research, AI-driven interventions, when user-centered, were found to have a significant impact on treatment
adherence, particularly in the aging population. Likewise, Delavar et al. (2020) highlighted the effectiveness of
individualized self-management education programs in enhancing adherence rates among older patients. Their
findings corroborate the idea that adapting health interventions to the specific cognitive and behavioral
requirements of older adults, as illustrated by the QVoC model, can bring about significant health outcome
improvements.
On the other hand, results by Milky and Thomas III (2020) indicated that although patient engagement in
decision making improves satisfaction as well as perceived autonomy, it does not invariably translate to
improved adherence. The implication is that although patient participation is valuable, technology-based, formal
interventions such as QVoC might represent a more expedient and concrete approach to defeating adherence-
associated barriers among older adult patients. Considered collectively, these studies underscore the potential
benefits of incorporating digital health tools within chronic disease care and highlight the need for usability,
personalization, and consistency in the design of such interventions.
Table 4 presents the results of a paired sample t-test conducted to determine whether there was a statistically
significant difference in the mean level of medication adherence among geriatric diabetic patients before and
after the implementation of the QVoC (QR Code with Voice Content) intervention.
Table 4
Test for Significant Difference on Level of Medication Adherence Among Geriatric Diabetic Patients
Before and After Using Qvoc Qr Code
Variables Mean SD T value P value Remarks*
Before intervention 2.95 0.18 9.82 .000 Significant
After intervention 3.70 0.09
*Calculation was performed at .05 level of significance
The findings show a notable increase in the mean adherence score, from
2.95 (SD = 0.18) prior to the intervention to 3.70 (SD = 0.09) after the use of QVoC. This upward shift reflects
a substantial improvement in the respondents’ adherence behaviors.
The computed t-value of 9.82 and corresponding p-value of .000 indicate that the difference between the pre-
and post-intervention mean scores is statistically significant at the 0.05 level. This confirmed that the observed
improvement in medication adherence is not due to chance, but rather can be attributed to the impact of the
QVoC intervention. The significant result supports the hypothesis that integrating voice-assisted QR code
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technology can effectively enhance medication adherence among elderly diabetic patients.
The statistically significant increase in medication adherence observed here can be explained by the increased
accessibility and convenience afforded by the QVoC (QR Code with Voice Content) intervention. This
technology would have helped primarily in the care of geriatric patients by streamlining medication tracking and
making timely, individualized voice reminders directly addressing frequent obstacles like forgetfulness,
cognitive impairment, and confusion due to complicated drug regimens.
This result is consistent with Bea et al. (2021) reported the beneficial effect of reminder systems and organized
follow-up mechanisms in enhancing medication adherence among patients receiving treatment for tuberculosis.
Since treatment of tuberculosis involves stringent and long-term medication regimens like diabetes, their
research highlights how technology-enabled interventions can prove to be successful in helping patients comply
with complex regimens.
Papus et al. (2022), for instance, advocate the effectiveness of motivational interviewing a patient-centered
counseling approach centered on empathy, active listening, and patient autonomy. This method helps to aid
individuals in examining and overcoming ambivalence regarding behavior change and thereby augment their
intrinsic motivation for adhering to prescribed treatment regimes. Motivational interviewing requires dynamic
interpersonal exchange compared to computerized systems and is specifically relevant when emotional
preparedness and psychological resilience are decision factors regarding long-term compliance.
Similarly, Poulter et al. (2020) extend the discussion by investigating multifactorial determinants of adherence
in chronic diseases such as hypertension. Their contribution is to highlight that one's behavior with respect to
following through is not a function of availability of reminders or knowledge tools
alone; instead, it is heavily embedded within one's everyday routine, literacy with respect to health, beliefs, and
lifestyle in general. Statistically significant improvement in medication adherence noted in the current study can
be explained by the increased convenience and availability that the QVoC (QR Code with Voice Content)
intervention afforded.
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
This chapter presented the summary of the findings, conclusions and recommendations.
Summary of Findings
Highest percentage of participants were between 60–65 (40%), then 66–70 and over 70 (30% each). Two-thirds
were female (65%), while 35% were males. In terms of education, 80% were high school graduates, 10% were
of lower education, and 10% were of higher education. Such demographics are able to measure the participants'
familiarity with technology and whether they would be receptive to the QVoC intervention.
The findings revealed a significant rate of medication adherence issues with an overall mean score of 2.95,
indicating frequent forgetfulness and irregular adherence. Participants often forgot to adhere to medication (M
= 3.20), skipped doses at the doctor's recommendation (M = 2.70), and missed medicine when traveling (M =
3.15). Even good behavior, i.e., remembering drug intake the previous day and following instructions, was rated
only moderately (M = 2.90–2.95), reflecting poor compliance in general. Such results indicate a demand for
usable, useful tools like QVoC—to enhance medication taking among elderly diabetes patients.
The results demonstrated a substantial improvement in medication compliance following the QVoC intervention.
Overall mean adherence score increased to 3.70 (SD = 0.09), reflecting a very high level of adherence. The
participants demonstrated increased consistency in medication adherence, with significant improvements in
remembering to take doses (M = 3.60), not forgetting doses (M = 3.70), and being consistent when on the go (M
= 3.65). High ratings also emerged for adherence to taking medications as prescribed on the correct schedule (M
= 3.80), adherence to instructions (M = 3.85), and persistence with medications even after symptoms have
disappeared (M = 3.75). The findings verify that QVoC is a valid and easy-to-use instrument in enhancing
medication adherence among older diabetic patients.
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The findings were statistically significant for improved medication adherence following the QVoC intervention.
The mean adherence score is higher following the intervention at 3.70 (SD = 0.09) compared to prior to the
intervention at 2.95 (SD = 0.18). The t-statistic of 9.82 and p-value of .000 are used to determine whether the
difference is statistically significant at the 0.05 level. This ensures that the conclusion that medication adherence
was indeed improved by the QVoC intervention can be made with confidence among elderly diabetic patients.
CONCLUSION
Based on the findings of the study, the researcher concluded the following:
Most of the participants were in the older age groups, with a significant percentage being females. The majority
of the participants achieved a high school level of education. These demographic features indicate that the older
participants, who may have difficulty in adopting technology, were likely to be open to the QVoC intervention.
This background is significant in appreciating the diversity in their responses and their capacity to use the
technological tool employed in the study.
Before the application of the QVoC QR Code, respondents had significant trouble with medication taking. Some
reported forgetfulness, irregular medication regimes, and dosing omission as common problems. These
difficulties signal the necessity of interventions that could overcome these impediments, particularly among
older adults who might have greater need of assistance in self-managing medication regimens.
Upon introducing the QVoC intervention, there was a significant increase in the respondents' medication
adherence. The participants became more consistent in adhering to their prescribed drug regimens. They were
more likely to remember to take the medication, less likely to forget doses, and exhibited better adherence even
when traveling. These are signs that the QVoC intervention was effective in improving better medication-taking
behavior among the geriatric diabetic patients.
There was a statistically significant increase in medication adherence following the QVoC intervention. The
comparison between the pre-intervention and post- intervention data verified that utilization of the QVoC QR
Code greatly increased medication adherence among the participants. This difference attests to the fact that the
QVoC intervention was an effective tool for enhancing the adherence behaviors of elderly diabetic patients.
RECOMMENDATIONS
Based on the findings and conclusions, the study arrived at the following recommendations:
1. Personalized care, user-oriented design, intensive training, and ongoing counseling must be integral to a policy
of QVoC for medication adherence that will help older patients adopt and sustain the use of the technology
effectively.
2. Integration of QVoC technology can be combined with reminder aids, diabetes education, and follow-up by
healthcare providers to improve medication management and enable sustained adherence among older adults.
3. The large increase in medication adherence following the QVoC intervention indicates that healthcare systems
can apply voice-enabled QR code technology more extensively, applying it also to patients with other chronic
conditions and incorporating it into the standard care process to enhance medication compliance and healthcare
outcomes.
The statistically significant increase in medication compliance following QVoC intervention indicates its
effectiveness. In order to maintain long-term success with such interventions, it could be a good policy to institute
long-term monitoring and periodic evaluation to ascertain the maintained effect of the QVoC technology.
Feedback from participants should actively be elicited to enhance and modify the system so that it remains
contemporaneously relevant and easy to use for geriatric patients.
REFERENCES
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1. Abas, J., Capricho, Z. A., Golpeo, B., Idong, C. B., Macantan, J., Miranda, M. D., & Faller, E. (2022).
POLPHARMACY AMONG GERIATRIC PATIENTS IN ASEAN COUNTRIES: A COMPARATIVE
REVIEW. Retrieved in December 2024 from Journal of Health Promotion and Service Management,
1(2), 94-113 on
2. Afaya, R. A., Bam, V., Azongo, T. B., Afaya, A., Kusi-Amponsah, A., Ajusiyine, J. M., & Abdul Hamid,
T. (2020). Medication adherence and self-care behaviours among patients with type 2 diabetes mellitus
in Ghana. Retrieved in December 2024 from PloS one, 15(8), e0237710.
3. Anderson, L. J., Nuckols, T. K., Coles, C., Le, M. M., Schnipper, J. L., Shane, R., ... & PHARM-DC
Group Choudhry Niteesh K MD, Ph. D O’Mahony Denis MD Sarkisian Catherine MD. (2020). A
systematic overview of systematic reviews evaluating medication adherence interventions. Retrieved in
December 2024 from American Journal of Health-System Pharmacy, 77(2), 138-147.
4. Allemann, S. S., Nieuwlaat, R., Navarro, T., Haynes, B., Hersberger, K. E., & Arnet, I. (2017).
Congruence between patient characteristics and interventions may partly explain medication adherence
intervention effectiveness: an analysis of 190 randomized controlled trials from a Cochrane systematic
review. Retrieved in December 2024 from Journal of clinical epidemiology, 91, 70-79.
5. AlQarni, K., AlQarni, E. A., Naqvi, A. A., AlShayban, D. M., Ghori, S. A., Haseeb, A., ... & Jamshed,
S. (2019). Assessment of medication adherence in Saudi patients with Type II diabetes mellitus in Khobar
City, Saudi Arabia. Retrieved in December 2024 from Frontiers in pharmacology, 10, 1306.
6. Ahmad, A., Rasul, T., Yousaf, A., & Zaman, U. (2020). Understanding factors influencing elderly
diabetic patients’ continuance intention to use digital health wearables: extending the technology
acceptance model (TAM). Retrieved in December 2024 from Journal of Open Innovation: Technology,
Market, and Complexity, 6(3), 81.
7. Al Mansour, M. A. (2020). The prevalence and risk factors of type 2 diabetes mellitus (DMT2) in a semi-
urban Saudi population. Retrieved in December 2024 from International journal of environmental
research and public health, 17(1), 7.
8. Brodie, K., Madden, L. L., & Rosen, C. A. (2020). Applications of quick response (QR) codes in medical
education. Retrieved in December 2024 from Journal of Graduate Medical Education, 12(2), 138- 140.
9. Boonyapalanant, A., Ketcham, M., & Piyaneeranart, M. (2020). Hiding patient injury information in
medical images with QR code. In Recent Advances in Information and Communication Technology
2019: Proceedings of the 15th International Conference on Computing and Information Technology
(IC2IT 2019) 15 (pp. 258-267). Retrieved in December 2024 from Springer International Publishing.
10. Bea, S., Lee, H., Kim, J. H., Jang, S. H., Son, H., Kwon, J. W., & Shin, J. Y. (2021). Adherence and
associated factors of treatment regimen in drug-susceptible tuberculosis patients. Retrieved in December
2024 from Frontiers in pharmacology, 12, 625078
11. Babel, A., Taneja, R., Mondello Malvestiti, F., Monaco, A., & Donde, S. (2021). Artificial intelligence
solutions to increase medication adherence in patients with non- communicable diseases. Frontiers in
Digital Health, 3, 669869
12. Cross, A. J., Elliott, R. A., Petrie, K., Kuruvilla, L., & George, J. (2020). Interventions for improving
medication‐taking ability and adherence in older adults prescribed multiple medications. Retrieved in
December 2024 from Cochrane Database of Systematic Reviews, (5).
13. Carandang, R. A. M. L., Ong, M. T., & Malenab, R. A. J. (2024). Predictors of Cognitive Impairment
among Filipino Patients with Type 2 Diabetes Mellitus in a Tertiary Government Hospital. Retrieved in
December 2024 from Acta Medica Philippina, 58(14), 6.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 569 www.rsisinternational.org
14. Calano, M. (2019). Factors affecting medication adherence among elderly people with chronic illness in
Surigao City, Philippines. International Journal of Current Science Research. Retrieved in December
2024 from https://ijcsrr.org/factors-affecting-medication- adherence-among-elderly-people-with-
chronic-illness-in-surigao-city/
15. Demoz, G. T., Berha, A. B., Alebachew Woldu, M., Yifter, H., Shibeshi, W., & Engidawork, E. (2019).
Drug therapy problems, medication adherence and treatment satisfaction among diabetic patients on
follow-up care at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. Retrieved in December
2024 from PloS one, 14(10), e0222985.
16. Dimaporo, J., Pizarras, S. J., Yorobe, M. A., Rollorazo, A. R., Tan, M. A., Go, C. J., & Banez, V.
Prevalence of exocrine pancreatic insufficiency (epi) in filipino adult patients who are diabetic for a
minimum of five years using the fecal elastase test in manila doctors hospital: a prospective cross-
sectional study.
17. De la Vega, Shelley Ann F., Nimfa B. Ogena, Maria Stella T. Giron, Angely P. Garcia, Hannah M.
Pellejo, Sarah Jane S. Fabito, and Vicente O. Medina III. "Active Aging Health Determinants among
Working and Retired Filipino Older Persons Living in an Urban Academic Campus." Retrieved in
December 2024 from Acta Medica Philippina 55, no. 4 (2021).
18. De Guzman, A. B., & Encabo, R. S. (2021). Factors associated with medication adherence of diabetic
patients in the Philippines. Philippine Journal of Health Research and Development, 25(1), 1-10.
Retrieved in December 2024 from https://www.philippinejournalofhealthresearchanddevelopment.com/
19. Delavar, F., Pashaeypoor, S., & Negarandeh, R. (2020). The effects of self-management education
tailored to health literacy on medication adherence and blood pressure control among elderly people with
primary hypertension: A randomized controlled trial. Patient education and counseling, 103(2), 336-342.
20. Eriksson, T. (2019). Medication adherence interventions and outcomes: an overview of systematic
reviews. Retrieved in December 2024 from European Journal of Hospital Pharmacy, 26(4), 187- 192.
21. Gast, A., & Mathes, T. (2019). Medication adherence influencing factors—an (updated) overview of
systematic reviews. Retrieved in December 2024 from Systematic reviews, 8, 1-17.
22. Giron, M. S., & de la Vega, S. A. (2022). Prevalence of diabetes among community-living older persons
in the Philippines: the FITforFrail Study. Retrieved in December 2024 from Journal of the ASEAN
Federation of Endocrine Societies, 37(2), 23.
23. Garcia, A. P., de la Vega, S. A. F., Giron, M. S. T., & Fabito, S. J. S. (2022). Visual and Hearing
Impairments among Working and Retired Employees with Type 2 Diabetes Mellitus in Two Academic
Communities in the Philippines. Retrieved in December 2024 from Acta Medica Philippina, 56(3).
24. Giron, M. S., & de la Vega, S. A. (2022). Prevalence of diabetes among community-living older persons
in the Philippines: the FITforFrail Study. Retrieved in December 2024 from Journal of the ASEAN
Federation of Endocrine Societies, 37(2), 23.
25. Garcia, A. P., de la Vega, S. A. F., Giron, M. S. T., & Fabito, S. J. S. (2022). Visual and Hearing
Impairments among Working and Retired Employees with Type 2 Diabetes Mellitus in Two Academic
Communities in the Philippines. Retrieved in December 2024 from Acta Medica Philippina, 56(3)
26. Hasanpour, F., Mehravar, F., Badeleh-Shamushaki, M. T., & Mancheri, H. (2024). The association of
health literacy and medication adherence in type 2 diabetic’s patients referring to comprehensive health
centers in Gorgan city. Retrieved in December 2024 from Scientific Journal of Nursing, Midwifery and
Paramedical Faculty, 9(4), 321-333.
27. Hashimoto, K., Urata, K., Yoshida, A., Horiuchi, R., Yamaaki, N., Yagi, K., & Arai, K. (2019). The
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 570 www.rsisinternational.org
relationship between patients’ perception of type 2 diabetes and medication adherence: a cross-sectional
study in Japan. Retrieved in December 2024 from Journal of pharmaceutical health care and sciences, 5,
1-10.
28. Jannoo, Z., & Khan, N. M. (2019). Medication adherence and diabetes self-care activities among patients
with type 2 diabetes mellitus. Retrieved in December 2024 from Value in health regional issues, 18, 30-
35
29. Karia, C. T., Hughes, A., & Carr, S. (2019). Uses of quick response codes in healthcare education: a
scoping review. Retrieved in December 2024 from BMC Medical Education, 19, 1-14.
30. Kvarnström, K., Westerholm, A., Airaksinen, M., & Liira, H. (2021). Factors contributing to medication
adherence in patients with a chronic condition: a scoping review of qualitative research. Retrieved in
December 2024 from Pharmaceutics, 13(7), 1100
31. Kim, J., Lee, H., & Park, S. (2020). Factors affecting medication adherence in elderly patients with
chronic diseases: A systematic review. Retrieved in December 2024 from Journal of Geriatric Medicine,
8(4), 123-130.
32. Longo, M., Bellastella, G., Maiorino, M. I., Meier, J. J., Esposito, K., & Giugliano, D. (2019). Diabetes
and aging: from treatment goals to pharmacologic therapy. Frontiers in Endocrinology, 10, 45
33. LeRoith, D., Biessels, G. J., Braithwaite, S. S., Casanueva, F. F., Draznin, B., Halter, J. B., ... & Sinclair,
A. J. (2019). Treatment of diabetes in older adults: an Endocrine Society clinical practice guideline. The
Journal of Clinical Endocrinology & Metabolism, 104(5), 1520-1574.
34. Lohrasbi, F., Ilali, E. S., Mousavinasab, S. N., & Yaghoubi, T. (2021). Factors associated with health
literacy and medication adherence in the elderly patients with chronic kidney diseases. Journal of Nursing
and Midwifery Sciences, 8(2), 106-113.
35. Maciejewski, M. L. (2020). Quasi-experimental design. Biostatistics & Epidemiology, 4(1), 38-47.
36. Mendes, R., Martins, S., & Fernandes, L. (2019). Adherence to medication, physical activity and diet in
older adults with diabetes: its association with cognition, anxiety and depression. Journal of clinical
medicine research, 11(8), 583.
37. Monterona, D. P., Matinong, R. A., & De Silos, J. (2021). The Effectiveness of Telephone Intervention
for Improving Patient Adherence to Medication among Diabetic Patients: A Systematic Review and
Meta-analysis of Randomized Trials. medRxiv, 2021-06.
38. Mannan, A., Hasan, M. M., Akter, F., Rana, M. M., Chowdhury, N. A., Rawal, L. B., & Biswas, T.
(2021). Factors associated with low adherence to medication among patients with type 2 diabetes at
different healthcare facilities in southern Bangladesh. Global health action, 14(1), 1872895.
39. Murali, K. M., Mullan, J., Roodenrys, S., Hassan, H. C., Lambert, K., & Lonergan, M. (2019). Strategies
to improve dietary, fluid, dialysis or medication adherence in patients with end stage kidney disease on
dialysis: A systematic review and meta- analysis of randomized intervention trials. PloS one, 14(1),
e0211479.
40. Musavi Ghahfarokhi, M., Tartifizadeh, H., Tartifizadeh, H., Asakereh, S., Eskandari, N., & Kogani, M.
(2024). Relationship between the Level of Health Literacy, Diet Adherence and Dialysis Adequacy in
Patients Undergoing Dialysis. Journal of Health Literacy, 9(2), 106-118.
41. Mendes, R., Martins, S., & Fernandes, L. (2019). Adherence to medication, physical activity and diet in
older adults with diabetes: its association with cognition, anxiety and depression. Journal of clinical
medicine research, 11(8), 583.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 571 www.rsisinternational.org
42. McElnay, J. C., & McCallion, C. R. (2020). Adherence and the elderly. In Adherance to Treatment in
Medical Conditions (pp. 223-253). CRC Press.
43. Milky, G., & Thomas III, J. (2020). Shared decision making, satisfaction with care and medication
adherence among patients with diabetes. Patient education and counseling, 103(3), 661-669.
44. Ngamdee, N., Chumfang, N., Chiangkhong, A., Satasuwan, A., & Sukdee, S. (2024). Behavioral Patterns
and Barriers to Medication Adherence in Older Adults with Diabetes. International Journal of
Geoinformatics, 20(3), 64-73.
45. Othman, G., Ali, F., Ibrahim, M. I. M., Al-Worafi, Y. M., Ansari, M., & Halboup, A. M. (2020).
Assessment of anti-diabetic medications adherence among diabetic patients in Sana’a City, Yemen: A
cross sectional study. Journal of Pharmaceutical Research International, 32(21), 114-122.
46. Onyishi, C. N., Eseadi, C., Ilechukwu, L. C., Okoro, K. N., Okolie, C. N., Egbule, E., & Asogwa, E.
(2022). Potential influences of religiosity and religious coping strategies on people with diabetes. World
Journal of Clinical Cases, 10(25), 8816.
47. Presley, B., Groot, W., & Pavlova, M. (2019). Pharmacy-led interventions to improve medication
adherence among adults with diabetes: a systematic review and meta-analysis. Research in Social and
Administrative Pharmacy, 15(9), 1057-1067.
48. Pouls, B. P., Vriezekolk, J. E., Bekker, C. L., Linn, A. J., van Onzenoort, H. A., Vervloet, M., ... & van
den Bemt, B. J. (2021). Effect of interactive eHealth interventions on improving medication adherence
in adults with long-term medication: systematic review. Journal of medical Internet research, 23(1),
e18901.
49. Papus, M., Dima, A. L., Viprey, M., Schott, A. M., Schneider, M. P., & Novais, T. (2022). Motivational
interviewing to support medication adherence in adults with chronic conditions: systematic review of
randomized controlled trials. Patient Education and Counseling, 105(11), 3186-3203.
50. Poulter, N. R., Borghi, C., Parati, G., Pathak, A., Toli, D., Williams, B., & Schmieder, R. E. (2020).
Medication adherence in hypertension. Journal of hypertension, 38(4), 579-587.
51. Punnapurath, S., Vijayakumar, P., Platty, P. L., Krishna, S., & Thomas, T. (2021). A study of medication
compliance in geriatric patients with chronic illness. Journal of Family Medicine and Primary Care,
10(4), 1644-1648.
52. Robinson, R. S. (2024). Purposive sampling. In Encyclopedia of quality of life and well-being research
(pp. 5645-5647). Cham: Springer International Publishing.
53. Saqlain, M., Riaz, A., Malik, M. N., Khan, S., Ahmed, A., Kamran, S., & Ali, H. (2019). Medication
adherence and its association with health literacy and performance in activities of daily livings among
elderly hypertensive patients in Islamabad, Pakistan. Medicina, 55(5), 163
54. Svensk, J., & McIntyre, S. E. (2021). Using QR code technology to reduce self- administered medication
errors. Journal of pharmacy practice, 34(4), 587-591.
55. Saffari, Mohsen, et al. "The role of religious coping and social support on medication adherence and
quality of life among the elderly with type 2 diabetes." Quality of Life Research 28 (2019): 2183-2193.
56. Sahoo, J., Mohanty, S., Kundu, A., & Epari, V. (2022). Medication adherence among patients of type II
diabetes mellitus and its associated risk factors: a cross- sectional study in a tertiary care hospital of
eastern India. Cureus, 14(12).
57. Stewart, S. J. F., Moon, Z., & Horne, R. (2023). Medication nonadherence: health impact, prevalence,
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
Page 572 www.rsisinternational.org
correlates and interventions. Psychology & health, 38(6), 726-765.
58. Sendekie, A. K., Netere, A. K., Kasahun, A. E., & Belachew, E. A. (2022). Medication adherence and
its impact on glycemic control in type 2 diabetes mellitus patients with comorbidity: A multicenter cross-
sectional study in Northwest Ethiopia. PLoS One, 17(9), e0274971.
59. Spinelli, M. A., Haberer, J. E., Chai, P. R., Castillo-Mancilla, J., Anderson, P. L., & Gandhi, M. (2020).
Approaches to objectively measure antiretroviral medication adherence and drive adherence
interventions. Current Hiv/Aids Reports, 17, 301-314.
60. Świątoniowska-Lonc, N., Tański, W., Polański, J., Jankowska-Polańska, B., & Mazur, G. (2021).
Psychosocial determinants of treatment adherence in patients with type 2 diabetes–a review. Diabetes,
Metabolic Syndrome and Obesity, 2701-2715.
61. Sanati, T., Vaezi, A., & Jambarsang, S. (2020). Medication adherence status and its related factors among
older adults in Yazd, Iran. Elderly Health Journal, 6(2), 85-90.
62. Sato, Y., et al. (2022). Factors associated with medication compliance in elderly patients with type 2
diabetes: A cross-sectional study in Japan. Diabetes Research and Clinical Practice, 183, 109149.
https://doi.org/10.1016/j.diabres.2021.109149
63. Świątoniowska-Lonc, N., Tański, W., Polański, J., Jankowska-Polańska, B., & Mazur, G. (2021).
Psychosocial determinants of treatment adherence in patients with type 2 diabetes–a review. Diabetes,
Metabolic Syndrome and Obesity, 2701-2715.
64. Ti, Y. W., Chen, S. K., & Wu, W. C. (2020). A New Visual Cryptography‐Based QR Code System for
Medication Administration. Mobile Information Systems, 2020(1), 8885242.
65. Wahsheh, H. A., & Al-Zahrani, M. S. (2021, May). Secure and usable QR codes for healthcare systems:
the case of covid-19 pandemic. In 2021 12th international conference on information and communication
systems (ICICS) (pp. 324-329). IEEE.
66. Wilhelmsen, N. C., & Eriksson, T. (2019). Medication adherence interventions and outcomes: an
overview of systematic reviews. European Journal of Hospital Pharmacy, 26(4), 187-192.
67. Wiecek, E., Tonin, F. S., Torres-Robles, A., Benrimoj, S. I., Fernandez-Llimos, F., & Garcia-Cardenas,
V. (2019). Temporal effectiveness of interventions to improve medication adherence: A network meta-
analysis. PloS one, 14(3), e0213432.
68. Xu, N., Xie, S., Chen, Y., Li, J., & Sun, L. (2020). Factors influencing medication non-adherence among
Chinese older adults with diabetes mellitus. International Journal of Environmental Research and Public
Health, 17(17), 6012.
69. Yazdanpanah, Y., Saleh Moghadam, A. R., Mazlom, S. R., Haji Ali Beigloo, R., & Mohajer, S. (2019).
Effect of an educational program based on health belief model on medication adherence in elderly
patients with hypertension. Evidence Based Care, 9(1), 52-62.
70. Ydirin, C. S. B. (2020). Health literacy and health-promoting behaviors among adults at risk for diabetes
in a rural setting. Health Literacy Research, 5(2), 45-56.
71. Ydirin, C. S. B. (2021). Health literacy and health-promoting behaviors among adults at risk for diabetes
in a remote Filipino community. Belitung Nursing Journal, 7(2), 88.
72. Yan, Y., Wu, T., Zhang, M., Li, C., Liu, Q., & Li, F. (2022). Prevalence, awareness and control of type
2 diabetes mellitus and risk factors in Chinese elderly population. BMC Public Health, 22(1), 1382.