INTRODUCTION

The proportion of individuals aged 65 and above is increasing annually in Asia. Indonesia has the largest population of older adult citizens among Southeast Asian nations. According to the 2022 National Socioeconomic Survey, the proportion of older adults in Indonesia exceeded 11.75% (32.3 million) of the overall population. It is predicted to reach 74 million or approximately 25% of the total population by 2050 [1].

The older adult population commonly experiences a deterioration in overall health, which can result in various disabilities [2]. Multimorbidity in this specific group increases the possibility of polypharmacy [3,4], and polypharmacy adversely affects the physical and mental health of geriatric patients [5]. Polypharmacy is also associated with medication-related burdens in older adults, as increased use of medications substantially impacts the rise in medication-related issues [6]. A study by Chen et al. [7] showed that the medication-related burden is affected not only by polypharmacy but also by age, comorbidity, and treatment cost. Other studies in Malaysia also reported that, in addition to polypharmacy, challenges in the treatment of older adults included medication administration difficulties, limited awareness of adverse drug events, issues with adherence, and accessibility to healthcare services [8]. Another study in Kuwait also showed a correlation between the medication-related burden and adherence in older adults [9].

Previous studies in China have quantified the medication-related burden using the Living with Medicine Questionnaire (LMQ) for older adults with chronic conditions [6]. However, these studies focused primarily on quantitative approaches, limiting the scope of the investigation. A qualitative study in the United Kingdom explored medication-related problems in older adults with various levels of function, with a specific focus on the period following hospital discharge [10]. Another study in Malta recommended that healthcare professionals identify the factors contributing to medication-related burdens to improve patient outcomes [11]. However, research on the medication-related burdens of older adults in Indonesia has not yet been conducted. Most studies conducted in Indonesia on geriatric adults with chronic diseases have concentrated on adherence issues [12,13], polypharmacy [3,14,15] and quality of life [16–19]. To implement effective interventions, it is essential to thoroughly examine the burden experienced by older adults receiving treatment for chronic diseases. Therefore, this study aimed to explore the burden experienced by older adults with chronic disease and its contributing factors.

METHODS

An exploratory mixed methods study was conducted to determine the medication-related burden of geriatric patients taking chronic medications. A survey was conducted using the validated Indonesian version of the LMQ. When compared to more specific instruments, such as the Treatment Burden Questionnaire or the Multimorbidity Treatment Burden Questionnaire, the LMQ was preferred because it has been shown to be valid and reliable in assessing medication-related burdens across multidimensions [7]. After completing the quantitative study, the study team conducted semi-structured interviews with selected participants in a teaching hospital in Surakarta, Central Java, Indonesia, between August 2023 and September 2023. The participants, data collection, and analyses for both phases are summarized below.

The Quantitative Study

A purposive sampling method was used to recruit participants over 60 years old who attended routine monthly checkups at outpatient internal medicine clinics. Eligible patients were able to communicate well or were accompanied by a caregiver to provide consent. Incomplete questionnaires were excluded. The minimum sample size was calculated using the sample size formula to estimate the mean value, with a confidence level of 95%, a mean LMQ score of 97.9, and a standard deviation of 20 [7]. The dropout rate was estimated at 20%. Hence, a minimum sample size of 78 was obtained.

The medication-related burden was assessed using the Indonesian version of the LMQ, which consisted of 41 items in 8 domains. All items were valid and reliable (Cronbach’s alpha =0.864) [20]. The domains included interference with day-to-day life, relationships/communication with health professionals about medications, lack of medication effectiveness, general concerns about medications, side effects, practical difficulties, cost-related burden, and autonomy. These were scored on a 4-point scale from strongly agree to strongly disagree [21]. For patients with reading limitations, the researcher interviewed the patient and filled out the questionnaire for them. If any answers were unclear, the caregiver provided additional information. This was done before their physician consultation and routine checkup.

The total score for all 8 domains was termed the total burden, and increases in the score correlated with greater medication-related burdens. The total burden was classified into 3 categories, minimum (scores 41–87), moderate (scores 88–110), and high (scores ≥111) [7]. To determine the impact of patient characteristics, including age, gender, marital status, presence of a caregiver, education level, employment status, financial status, number of medications, treatment duration, drug dosage and form, and health condition on the LMQ score, a t-test or F-test was conducted. The Mann-Whitney U test and Kruskal-Wallis test were used as alternatives.

The Qualitative Study

Data collection was aimed at investigating the patients’ experience of burden with chronic medication use, and enhancing our understanding of the factors that contribute to the medication-related burden. Before conducting interviews with the enrolled participants, a pilot test was performed using the draught interview guide with 2 participants. This was done to confirm that the questions were interpreted as intended and to prove uniformity with face validity.

A single interviewer (YF), a woman PhD candidate trained in qualitative research, conducted all interviews after scheduling time with the patients. A purposive sampling method was used to select participants based on the homogeneity of their characteristics. Each interview lasted approximately 20–30 minutes, and the patients were given a gift as a token of appreciation. The interviews were recorded and transcribed verbatim, while data in Bahasa Indonesia was analyzed using an inductive thematic framework technique and translated into English. The familiarization process started during the interview phase by attentively listening to the participants’ comments. This process was extended to transcribing the audio recordings of the interviews by revisiting and cross-referencing with the written transcripts. This played a crucial role in the first data analysis and in identifying key themes. Instead of sending the transcripts to participants for feedback or to make any necessary revisions, they were initially coded by 2 authors (YF and AWW) who examined them for generated themes. Meaningful phrases in the textual transcripts were manually coded using Microsoft Word and Excel (Microsoft, Redmond, WA, USA). Another team member (P) confirmed the produced codes. After completion of the data coding, this study analyzed the codes for pertinent patterns and organized them into themes and subthemes. This analysis was conducted using Microsoft Excel, and discrepancies were resolved by consensus among the study team (YF, AWW, TMA, and P). In the end, quotations that exemplified the themes were selected with the consensus of the entire study team.

Ethics Statement

This study received ethics approval (reference No. 1.222/VII/HREC/2023) from the Health Research Ethics Committee at Dr. Moewardi General Hospital and was conducted in accordance with the Declaration of Helsinki. All participants provided informed consent prior to the study.

RESULTS

Quantitative Study

Characteristics of participants

This quantitative study included 129 participants who completed the Indonesian version of the LMQ and excluded 5 incomplete questionnaires. The characteristics of the participants are shown in Table 1. Most patients were aged <75 years, with an average age of 69.2 years. The cut-off age was set at 75 years, in line with recent definitions of elderly adults as ≥75 years because of positive changes seen in the physical and mental health of those <75 years [22]. The gender distribution was nearly equivalent (50.4% men and 49.6% women), and most still had spouses (65.1%), as well as caregivers (either the spouse or their children). The provided data pertains to the state of older adults in Indonesia, as shown by statistics from the year 2022 [23]. Most of this demographic consisted of individuals <70 years old, who possessed an elementary school education or less, and were married.

Cardiovascular disease (CVD) was the most prevalent diagnosis (58.9%) among the participants, and 67.4% used 5–10 medications every day. A minority (24.0%) received medications administered by specialized devices, such as an injection (e.g., insulin) or an inhaler.

Participant characteristics associated with medication-related burden

The overall LMQ mean score was 90.4, classified as a moderate burden, and higher LMQ scores were related to greater medication-related burdens [21]. Overall, the LMQ score was not associated with differences in age, gender, education level, caregiver status, marriage status, employment status, finances, or drug dosage and form. A comparison of average LMQ scores by group according to participant characteristics showed no statistically significant distinctions, except for the number of medications, treatment duration, and diagnoses of CVD, diabetes mellitus (DM), or stroke (p<0.05) (Table 1). According to a post hoc analysis, there were substantial differences in LMQ scores when the number of prescribed medications exceeded 10, as compared to 1–4 (95% confidence interval [CI], 3.25 to 17.67; p=0.002) and 5–10 (95% CI, 2.46 to 12.03; p=0.001). Participants did not experience a significant burden when the number of medications was below 10.

Medication-related burden in each domain of the LMQ

The patient characteristics that influenced the LMQ score in each domain are detailed in Table 2. No characteristics influenced the ‘relationships with health professionals’ domain. The number of medications influenced the ‘interference in day-to-day life’ (p=0.005), ‘lack of medication effectiveness’ (p=0.031), and ‘side effects’ (p=0.032) domains. Post hoc analysis showed that patients with hyper-polypharmacy (>10 medications) experienced a significantly higher burden in the ‘interference in day-to-day life’ (1–4 vs. >10, p=0.012; 5–10 vs. >10, p=0.002), ‘lack of medication effectiveness’ (1–4 vs. >10, p=0.019), and ‘side effects’ (5–10 vs. >10, p=0.009) domains. The ‘general concerns about medication’ domain was influenced by employment status (p=0.001), drug dosage and form (p=0.002), and the occurrence of CVD (p=0.046). CVD also influenced the cost domain (p=0.015), while stroke influenced the practical difficulties domain (p=0.011), and education level influenced autonomy.

Previous studies have reported that older adults are at risk of polypharmacy related to multimorbidity [3,8,24–26]. Comparing patients without CVD, DM, and stroke to those with these conditions, the average LMQ score varied significantly (p<0.05). The scope of this study was restricted to data analysis of the 6 most prevalent ailments experienced by the participants. Previous studies have indicated that older adults with cardiovascular conditions may be at a heightened risk of polypharmacy. The likelihood of polypharmacy in patients with CVD is approximately twice that of other patient populations [27]. Another study in Indonesia also reported that CVD (odds ratio [OR], 2.33; 95% CI, 1.43 to 3.81), DM (OR, 2.39; 95% CI, 1.51 to 3.79; p<0.001), and hypertension (OR, 1.95; 95% CI, 1.17 to 3.24; p=0.01) significantly influence polypharmacy [3].

Qualitative Study

Because of time constraints and data saturation, the interviews were conducted with only a few select patients. A total of 12 patients were approached to participate, but only 8 were interviewed. Four patients did not participate because they failed to respond when contacted or did not come in for scheduled appointments. The selected participants were aged 65–76 years with a primary school to college education. Of these participants, 5 had undergone treatment for >5 years. Three consumed >10 medications daily, and 6 had DM. Based on the LMQ classification of burden, 2 participants scored mild, 4 moderate, and 2 high. Three primary themes regarding medication-related burden, as well as corresponding subthemes, were identified from the data. An explanation and support for the quantitative data analysis are provided in Table 3.

Experiences With Medication Use

Medication adherence

The interviews showed high medication adherence among geriatric patients. The pharmaceuticals were likely perceived as a necessity rather than a burden, a belief that influenced medication adherence.

Medication management

Although not all patients understood the indication or name of each drug they took, they relied on the physical packaging to identify the medication and recall the instructions for its usage. Patients self-administered their medications, primarily based on directions given by their provider or pharmacist.

Lack of concern about drug interactions

Most of the interviewed participants were unaware of drug interactions. Convenience, rather than concerns about drug interactions, influenced how they took their medications, whether it was several types of medication simultaneously, with or without meals, or with breaks between medications. The participants showed a low level of concern about interactions when taking multiple medications concurrently. These findings supported the quantitative study, which found that ‘general concern about medications’ was unaffected by the number of medications.

Side effects

Some participants who experienced the adverse effects of a medication were not anxious or disturbed by them. This was because the adverse effect could be alleviated with an additional physician-prescribed medication, even though the side effects burden increased with each additional medication (p=0.032).

Cost

Although patients did not object to paying insurance premiums in the absence of government aid, not all medications were covered by insurance, and patients had to pay for them independently. In this study, quantitative analysis supported the finding that treatment for CVD affected the cost burden (p=0.015).

Challenges of Medication Use in Older Adults

Practical difficulties

The challenges of treating older adults are directly related to the practical implications of their declining physical state. Diminished vision hampers the ability to read labels, leading to frequent requests to rewrite the appropriate medication times, particularly for new medications. The quantitative analysis in this study proved that the occurrence of a stroke influenced practical difficulties in the medication-related burden (p=0.011). In this context, the role of family members or caregivers was crucial in supporting treatment. This result also corroborates an earlier study reporting that geriatric people can find it difficult to comprehend and follow the directions for medication usage [28].

Perceived ineffectiveness

Despite continuing to use the medications, some patients expressed dissatisfaction with their efficacy, underscoring the need to seek alternative treatments. This also confirmed the quantitative analysis finding that a high number of medications was related to a greater likelihood of experiencing ineffectiveness (p<0.001).

Medication/treatment fatigue

Aside from dissatisfaction with the effectiveness of therapy, patients may also feel a sense of overwhelm or fatigue from the long-term effort required to manage the medication.

Motivations for Chronic Medication Use in Older Adults

Internal motivation

Even with feelings of medication fatigue, the internal motivation to be healthier can help the patient adhere to the treatment.

Family support

The presence of family or environmental supports also motivated the patients to overcome their treatment fatigue. Although the patients with several comorbidities took a significant number of medications, the average medication-related burden was moderate based on the LMQ scores. Support from family members included providing medication reminders, buying and preparing the medications, and going with patients to doctor appointments.

The triangulation of both quantitative and qualitative results is presented in Figure 1. The triangulation framework offers a complete picture of the medication-related burdens older adults encounter during chronic treatment. The patients showed robust determination in the face of medication-related burdens, likely due to their motivation to be healthier and significant support from family. Correlations were found between the quantitative and qualitative study results.

DISCUSSION

The present study found that patients experienced higher medication-related burdens when using >10 medications and had a treatment duration of >5 years. According to an earlier study, the medication-related burden increased in older adults receiving >10 prescription medications during their last month of life [29]. In addition, health issues such as CVD, DM, and stroke affected the overall medication-related burden. Specifically, CVD influenced general concerns about medication. Generally, non-communicable diseases, including hypertension, DM, and heart disease, which rank at the top in Indonesia [30], influence polypharmacy in older adults [3,27]. Increased use of medications substantially impacts the rise in medication-related issues [6].

Although the quantitative study showed that an increase in the number of medications raised the side effect burden, the qualitative study indicated that patients did not feel overwhelmed by adverse events. A primary reason for this was that the adverse drug reactions were predictable and could be anticipated. Another reason was the patients’ lack of comprehension regarding adverse drug events. Patients may have difficulty distinguishing disease complaints from adverse events. One study reported that approximately 33.6% (n=132) of older adults lacked knowledge of their medication’s side effects [8].

Education level was the only characteristic that affected autonomy. Patient autonomy means the right of patients to make decisions about their medications [31]. The ability to make decisions is related to the patient’s knowledge base and level of education, critical determinants of understanding [32]. Furthermore, limited formal education has been associated with lower cognitive status [33].

Patients and health professionals often hold divergent viewpoints about the effectiveness of treatment. Patients tend to evaluate the efficacy of a medication based solely on the relief of symptoms and the drug’s ability to prevent the recurrence of symptoms. However, beyond this subjective understanding, established parameters can be used to assess treatment efficacy. This observation underscores the need for more effective communication between patients and healthcare practitioners to determine the true effectiveness of treatment. Effective communication is not just a tool but a necessity in addressing patients’ needs, concerns, and preferences [34].

Our study showed that many participants had a high level of adherence. The patients could identify medications by their packaging or physical characteristics despite limited understanding of the treatment. Although certain patients were found to be capable of handling their medications independently, others required complete aid from their families. Patients with stroke had a significantly higher burden related to practical difficulties than patients without stroke (p=0.011). In addition, non-oral dosage forms affected general concerns about medication among older adult patients. Using several different medications with complex instructions can be challenging and time-consuming for patients [9].

Long-term daily medication use often induced feelings of treatment fatigue, but perseverance in treatment was sustained by an internal motivation to be healthier and by familial support. This study underscores the vital role of familial support in minimizing the burden experienced by older adults. Family support from cohabiting spouses, offspring, and siblings strongly correlated with medication adherence, whereas feelings of loneliness tended to lower the level of compliance [12]. This highlights the significant impact that family members can have on the health and well-being of older adults and emphasizes the importance of their role in the care process. As caregivers, family members play a crucial role in aiding older adults with daily activities, communicating with healthcare professionals, and facilitating medical aid [35]. Another study found that older adults who lived with family members had a greater adherence to their medications. Social support protects against the detrimental effects of loneliness, which can negatively affect overall health [8].

In general, our results showed that medication adherence, management, side effects, drug interactions, and cost posed significant challenges to older adults with chronic diseases, affecting their medication-related burdens. Older adults face several challenges in treatment, including practical difficulties, medication fatigue, and the perceived effectiveness of their medications. This holistic understanding underscores the importance of a comprehensive approach when caring for older adults with chronic diseases. Furthermore, the study showed that internal motivation and family support play a role in mitigating medication-related burdens and overcoming medication fatigue during treatment. Managing chronic diseases in older adults demands the active participation of patients, families, and healthcare professionals.

The strength of this study was the use of mixed methods, including the integration of a quantitatively analyzed survey with a qualitative examination using semi-structured interviews and thematic analysis. This allowed for a comprehensive analysis of the factors influencing the medication-related burden of older adults. Due to the small sample size and single-center design, the results may not be generalizable to the entire older adult population in Indonesia. Furthermore, the LMQ was not tailored exclusively to older adults, resulting in some irrelevant questions, such as those about the impact of medications on sexual functioning and driving abilities.

In conclusion, this study showed that older adults with chronic diseases face medication-related burdens associated with the presence of CVD, DM, or stroke; treatment duration of >5 years; and use of >10 medications. Furthermore, motivation to be healthier and familial support effectively counteracted dissatisfaction due to medication fatigue. Effective communication between healthcare professionals and patients is crucial to understanding the patient’s needs and concerns, thereby helping manage the challenges of medication-related burdens.

Notes

Conflict of Interest

The authors have no conflicts of interest associated with the material presented in this paper.

Funding

This study was supported by the Scholarship of Education Fund Management Institute (Lembaga Pengelola Dana Pendidikan/LPDP).

Acknowledgements

The authors are grateful to the participants and pharmacy staff at Universitas Sebelas Maret Hospital.

Author Contributions

Conceptualization: Widayanti AW, Andayani TM. Data curation: Farida Y, Widayanti AW. Formal analysis: Farida Y, Widayanti AW. Funding acquisition: Farida Y. Methodology: Widayanti AW, Andayani TM. Project administration: Widayanti AW, Andayani TM, Probosuseno. Visualization: Farida Y. Writing – original draft: Farida Y, Widayanti AW. Writing – review & editing: Farida Y, Widayanti AW, Andayani TM, Probosuseno.

Figure 1

Triangulation of quantitative and qualitative findings.

REFERENCES

• 1. Sari NR, Yulianto KT, Agustina R, Wilson H, Nugroho SW, Anggraeni G. Statistics of senior citizens; 2023 [cited 2025 Mar 9]. Available from: https://www.bps.go.id/id/publication/2023/12/29/5d308763ac29278dd5860fad/statistik-penduduk-lanjut-usia-2023.html (Indonesian)
• 2. Khan ZA, Singh C, Khan T. Correlates of physical disability in the elderly population of rural North India (Haryana). J Fam Community Med 2018;25(3):199-204. https://doi.org/10.4103/jfcm.JFCM_160_17Article
• 3. Faisal S, Zairina E, Nathishuwan S, Khotib J, Kristina SA, Nugraheni G. Prevalence and predictors of excessive polypharmacy in geriatric inpatients: a retrospective cross-sectional study in Indonesia. J Prim Care Community Health 2023;14: 21501319231178595. https://doi.org/10.1177/21501319231178595ArticlePubMedPMC
• 4. Jennings EL, O’Mahony D, Gallagher PF. Medication-related quality of life (MRQoL) in ambulatory older adults with multi-morbidity and polypharmacy. Eur Geriatr Med 2022;13(3):579-583. https://doi.org/10.1007/s41999-021-00573-6ArticlePubMed
• 5. Tegegn HG, Erku DA, Sebsibe G, Gizaw B, Seifu D, Tigabe M, et al. Medication-related quality of life among Ethiopian elderly patients with polypharmacy: a cross-sectional study in an Ethiopia university hospital. PLoS One 2019;14(3):e0214191. https://doi.org/10.1371/journal.pone.0214191ArticlePubMedPMC
• 6. Wang Y, Li X, Jia D, Lin B, Fu B, Qi B, et al. Exploring polypharmacy burden among elderly patients with chronic diseases in Chinese community: a cross-sectional study. BMC Geriatr 2021;21(1):308. https://doi.org/10.1186/s12877-021-02247-1ArticlePubMedPMC
• 7. Chen WS, Islam MR, Ambepitiya S, Sim W, Yiu W, Carey J, et al. Factors associated with patient experiences of the burden of using medicines and health-related quality of life: a cross-sectional study. PLoS One 2022;17(4):e0267593. https://doi.org/10.1371/journal.pone.0267593ArticlePubMedPMC
• 8. Christopher CM, Blebil AQ, Bhuvan KC, Alex D, Mohamed Ibrahim MI, Ismail N, et al. Medication use problems and factors affecting older adults in primary healthcare. Res Social Adm Pharm 2023;19(12):1520-1530. https://doi.org/10.1016/j.sapharm.2023.08.001ArticlePubMed
• 9. Awad A, Alhadab A, Albassam A. Medication-related burden and medication adherence among geriatric patients in Kuwait: a cross-sectional study. Front Pharmacol 2020;11: 1296. https://doi.org/10.3389/fphar.2020.01296ArticlePubMedPMC
• 10. Nicosia FM, Spar MJ, Stebbins M, Sudore RL, Ritchie CS, Lee KP, et al. What Is a medication-related problem? A qualitative study of older adults and primary care clinicians. J Gen Intern Med 2020;35(3):724-731. https://doi.org/10.1007/s11606-019-05463-zArticlePubMed
• 11. Sacco K, West LM, Grech LM, Krska J, Cordina M. Assessing medication-related burden of community-dwelling individuals with chronic conditions in a small island state. Chronic Illn; 2023 17423953231205918 https://doi.org/10.1177/17423953231205918Article
• 12. Sari DN, Utami W, Zairina E. The influence of feeling lonely and received social support on medication adherence in elderly with hypertension. Pharm Pharm Sci J 2022;9(3):252-261. http://doi.org/10.20473/jfiki.v9i32022.252-261Article
• 13. Widyakusuma NN, Suryawati S, Wiedyaningsih C, Probosuseno . What do seniors believe about medication adherence? A qualitative study among seniors with chronic conditions in Yogyakarta, Indonesia. Patient Prefer Adherence 2023;17: 1381-1392. https://doi.org/10.2147/PPA.S412981ArticlePubMedPMC
• 14. Soejono CH, Rizka A. Polypharmacy and drug use pattern among Indonesian elderly patients visiting emergency unit. Acta Med Indones 2021;53(1):60-76PubMed
• 15. Fauziyah S, Radji M, Andrajati R. Polypharmacy in elderly patients and their problems. Asian J Pharm Clin Res 2017;10(7):44-49. https://doi.org/10.22159/ajpcr.2017.v10i7.18548Article
• 16. Lionthina M, Wiwaha G, Gondodiputro S, Sukandar H, Arya IF, Sunjaya DK. Elderly quality of life and its predictors in chronic disease management program: Indonesian version of WHOQOL-BREF and WHOQOL-OLD. Majalah Kedokteran Bandung 2020;52(1):28-34. https://doi.org/10.15395/mkb.v52n1.1729Article
• 17. Hidayati AR, Gondodiputro S, Rahmiati L. Elderly profile of quality of life using WHOQOL-BREF Indonesian version: a community-dwelling. Althea Med J 2018;5(2):105-110. https://doi.org/10.15850/amj.v5n2.1417Article
• 18. Gunawan I, Lin MH, Hsu HC. Exploring the quality of life and its related factors among the elderly in Indonesia. South East Asia Nurs Res 2020;2(1):1-10. https://doi.org/10.26714/seanr.2.1.2020.1-10Article
• 19. Juanita J, Nurhasanah N, Jufrizal J, Febriana D. Health related quality of life of Indonesian older adults living in community. Enferm Clin 2022;32(Suppl 2):S71-S75. https://doi.org/10.1016/j.enfcli.2022.03.022Article
• 20. Putra JA, Widayanti AW, Wiedyaningsih C, Kes M, Sc MA. Psychometric analysis of validity and reliability of the Indonesian version of the living with medicine questionnaire (LMQ) instrument for hypertension patients in the special region of Yogyakarta (DIY); 2023 [cited 2025 Mar 9]. Available from: https://etd.repository.ugm.ac.id/penelitian/detail/227984 (Indonesian)
• 21. Alqallaf SM, Matar L, Ghuloom K, Alabbad K, Alshaikh F, Alhaddad M. Medication-related burden from the perspective of the elderly. Med Pharm Rep 2022;95(3):320-331. https://doi.org/10.15386/mpr-2133ArticlePubMedPMC
• 22. Ouchi Y, Rakugi H, Arai H, Akishita M, Ito H, Toba K, et al. Redefining the elderly as aged 75 years and older: proposal from the Joint Committee of Japan Gerontological Society and the Japan Geriatrics Society. Geriatr Gerontol Int 2017;17(7):1045-1047. https://doi.org/10.1111/ggi.13118ArticlePubMed
• 23. Girsang AP, Sulistyowatu R, Dewi FW, Nugroho SW, Ramadani KD, Wilson H. The statistics of senior citizens; 2022 [cited 2025 Mar 9]. Available from: https://www.bps.go.id/id/publication/2022/12/27/3752f1d1d9b41aa69be4c65c/statistik-penduduk-lanjut-usia-2022.html (Indonesian)
• 24. Dills H, Shah K, Messinger-Rapport B, Bradford K, Syed Q. Deprescribing medications for chronic diseases management in primary care settings: a systematic review of randomized controlled trials. J Am Med Dir Assoc 2018;19(11):923-935. https://doi.org/10.1016/j.jamda.2018.06.021ArticlePubMed
• 25. Gharekhani A, Kanani N, Khalili H, Dashti-Khavidaki S. Frequency, types, and direct related costs of medication errors in an academic nephrology ward in Iran. Ren Fail 2014;36(8):1268-1272. https://doi.org/10.3109/0886022X.2014.934650ArticlePubMed
• 26. Niveditha TV, Pradhan A, Shabaraya AR, Ambika V, Jose C, Shwetha N. Drug related problems in geriatric patients with inappropriate medication use. Int J Res Rev 2021;8(5):487-496. https://doi.org/10.52403/ijrr.20210559Article
• 27. Tefera YG, Alemayehu M, Mekonnen GB. Prevalence and determinants of polypharmacy in cardiovascular patients attending outpatient clinic in Ethiopia University Hospital. PLoS One 2020;15(6):e0234000. https://doi.org/10.1371/journal.pone.0234000ArticlePubMedPMC
• 28. Notenboom K, Beers E, van Riet-Nales DA, Egberts TC, Leufkens HG, Jansen PA, et al. Practical problems with medication use that older people experience: a qualitative study. J Am Geriatr Soc 2014;62(12):2339-2344. https://doi.org/10.1111/jgs.13126ArticlePubMedPMC
• 29. Morin L, Vetrano DL, Rizzuto D, Calderón-Larrañaga A, Fastbom J, Johnell K. Choosing wisely? Measuring the burden of medications in older adults near the end of life: nationwide, longitudinal cohort study. Am J Med 2017;130(8):927-936. https://doi.org/10.1016/j.amjmed.2017.02.028ArticlePubMed
• 30. Basrowi RW, Rahayu EM, Khoe LC, Wasito E, Sundjaya T. The road to healthy ageing: what has Indonesia achieved so far? Nutrients 2021;13(10):3441. https://doi.org/10.3390/nu13103441ArticlePubMedPMC
• 31. Albugami M, Alem UE. Patient autonomy. Int J Med 2021;9(1):58-59. https://doi.org/10.14419/ijm.v9i1.31526Article
• 32. Yeom HE, Lee J. The association of education level with autonomy support, self-efficacy and health behaviour in patients with cardiovascular risk factors. J Clin Nurs 2022;31(11–12):1547-1556. https://doi.org/10.1111/jocn.16008ArticlePubMed
• 33. Brigola AG, Alexandre TD, Inouye K, Yassuda MS, Pavarini SC, Mioshi E. Limited formal education is strongly associated with lower cognitive status, functional disability and frailty status in older adults. Dement Neuropsychol 2019;13(2):216-224. https://doi.org/10.1590/1980-57642018dn13-020011ArticlePubMedPMC
• 34. Kwame A, Petrucka PM. A literature-based study of patient-centered care and communication in nurse-patient interactions: barriers, facilitators, and the way forward. BMC Nurs 2021;20(1):158. https://doi.org/10.1186/s12912-021-00684-2ArticlePubMedPMC
• 35. Lei L, Gerlach LB, Powell VD, Maust DT. Caregiver support and place of death among older adults. J Am Geriatr Soc 2021;69(5):1221-1230. https://doi.org/10.1111/jgs.17055ArticlePubMedPMC

Figure & Data

References

Citations

Citations to this article as recorded by