Startseite Impact of COVID-19 infection on medication adherence and medication taking behavior among rural-dwelling older adults with chronic diseases: a cross-sectional study
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Impact of COVID-19 infection on medication adherence and medication taking behavior among rural-dwelling older adults with chronic diseases: a cross-sectional study

  • Baoyi Zhang , Xinxin Li , Jingyue Xie , Ni Gong , Yu Cheng und Meifen Zhang EMAIL logo
Veröffentlicht/Copyright: 20. August 2024
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Asian Journal of Medical Humanities
Aus der Zeitschrift Asian Journal of Medical Humanities Band 3 Heft 1

Abstract

Objectives

To explore the impact of COVID-19 infection on medication adherence among rural-dwelling older adults with chronic diseases, and identify the medication taking behavior and its influencing factors among rural-dwelling older adults with COVID-19 infection.

Methods

A cross-sectional study of 111 rural-dwelling older adults was conducted from February to March 2023 in rural villages in China. Demographic and clinical characteristics, medication adherence, medication taking behavior, COVID-19 related illness perception, COVID-19 related stigma, and social network were evaluated by questionnaires. Independent-sample t test, Chi-square test, and multivariable logistic regression were performed to analyze the data.

Results

There was no significant difference in the medication adherence between COVID-19 infected group and non-COVID-19 infected group. For COVID-19 infected older adults, 63.93 % maintained taking medication for chronic diseases, but 32.79 % stopped taking medication during COVID-19 infection. COVID-19 related illness perception (OR=1.111, p=0.004) and social network (OR=1.156, p=0.010) correlated with the behaviors such as reducing the dose of medication or stopping taking medication during COVID-19 infection.

Conclusions

The COVID-19 infection has no effect on medication adherence among rural-dwelling older adults. Older adults with negative illness perception of COVID-19 and better social network were more likely to reduce or stop taking medication when they were infected with COVID-19. Thus, specific strategies to reduce negative perception about COVID-19 and strengthen social connection are warranted for rural-dwelling older adults.

Keywords: medication adherence; medication taking behavior; older adults; chronic diseases; rural areas; COVID-19

Introduction

With the acceleration of population aging, chronic diseases have become one of the most prominent health issues among older adults, which contribute to the highest disease burden globally [1]. In China, the number of older adults with at least one chronic disease exceeded 180 million in 2019 [2]. The prevalence of chronic diseases among older adults in rural China reached 82.6 %, which was higher than that in urban areas [3]. Around the world, 41 million people died of chronic diseases, accounting for 74 % of all deaths [1]. Given the high morbidity and mortality, the health management of older adults with chronic diseases is of great significance.

Medication is the primary method for chronic disease treatment in older adults [2], but its effect on maintaining health depends on the medication adherence. Medication adherence refers to ‘the extent to which an individual’s medication behavior is consistent with treatment recommendations agreed upon by the health care provider’ [4]. Medication adherence is widely advocated as the key to controlling disease stability, which has been demonstrated to improve clinical outcomes and reduce mortality significantly [5, 6]. In addition, medication non-adherence causes extraordinarily high healthcare costs for each patient ranging from $949 to $44,190 per year, resulting in $100 to $290 billion in annual health care expenditures, in the United States alone [7]. Thus, higher medication adherence is beneficial for both patients and the healthcare system. However, non-adherence to medication is a widespread issue [8]. Notably in rural areas, older adults’ adherence to medication was lower than in urban areas [9, 10], and medication non-adherence could result in worsening health status and higher readmission rate [11]. Therefore, more attention should be paid to the medication adherence of rural older adults.

However, the outbreak and spread of the coronavirus disease 2019 (COVID-19) has placed drastic disruption on health care services [12], and increased concerns about the medication adherence [13]. The concerns of COVID-19 infection, medication shortage, travel and financial restrictions are obstacles to long-term medication adherence for older adults [12], and their medication adherence may be negatively affected [14]. Especially in rural areas, where socioeconomic level is lower and health care services are relatively scarce, the medication adherence of older adults may be more vulnerable to the adverse effects of COVID-19 [9]. Thus, with the COVID-19 pandemic entering the stage of regular control, the impact of COVID-19 infection on medication adherence of rural-dwelling older adults with chronic diseases requires more attention and in-depth exploration. Existing studies have compared changes in medication adherence before and during COVID-19, regardless of whether participants were infected with COVID-19 [14–16]. But little is known regarding the impact of COVID-19 infection on the medication adherence among older adults with chronic diseases. Furthermore, it is unclear whether there are changes in the medication taking behavior and what factors influencing the medication taking behavior among those with COVID-19 infection in rural areas.

Previous studies have indicated that medication adherence among chronic diseases patients during COVID-19 is multifactorial, which was related to medication beliefs, social support, demographic characteristics (age, education level) and clinical characteristics (comorbidities) [9, 17]. According to the Capacity, Opportunity, Motivation-Behavior (COM-B) model proposed by Michie in 2011, the interaction of capacity (the physical and psychological ability to participate in the behavior), motivation (all processes of brain activity that motivate and direct behavior) and opportunity (all external factors that facilitate the behavior) will affect the health behavior [18, 19]. For older adults with chronic diseases infected with COVID-19, their medication taking behavior may be associated or affected by psychological variables, such as COVID-19 related illness perception and stigma. COVID-19 related illness perception and stigma are brain activities that motivate or discourage medication adherence, which could correspond to the concept of motivation in the COM-B model. Besides, older adults with COVID-19 infection were required to avoid social contact, and their social network may be impaired [13]. Social network, as an external factor, is consistent with the connotation of opportunity, but the correlation between medication adherence and social network has rarely been discussed during COVID-19. Thus, this study explored the effects of COVID-19 related psychological variables (COVID-19 related illness perception and stigma), social networks, demographic and clinical characteristics on the medication taking behavior during COVID-19. As shown in Figure 1, this study hypothesized that COVID-19 related illness perception, stigma and social network were influencing factors of medication taking behavior.

Figure 1: The theoretical framework of this study.
Figure 1:

The theoretical framework of this study.

Therefore, this study aims to: (1) examine the impact of COVID-19 infection on medication adherence among rural-dwelling older adults with chronic diseases by comparing the scores of medication adherence between COVID-19 infected group and non-COVID-19 infected group; (2) describe the medication taking behavior and identify its influencing factors among rural-dwelling older adults with chronic diseases during COVID-19 infection, so as to guide targeted interventions to improve their medication adherence.

Methods

Study design and participants

This was a cross-sectional study, strictly following the STROBE statement [20]. This study was conducted between February and March, 2023, when optimized epidemic control policy has been implemented for 2 months and a large number of older adults had been infected with COVID-19 in China [21]. A convenience sample was collected and 111 older adults were recruited from 10 villages in Shanwei city, Guangdong province, China. The inclusion criteria were (1) aged 60 or above; (2) rural-dwelling; (3) diagnosed with at least 1 chronic disease, required long-term oral medication; (4) informed consent and voluntary to participate in the study. Participants were excluded if they were with hearing or speech disabilities. After training researchers to unify the interpretation of the study purpose and questionnaire, three researchers asked participants to complete questionnaires at their homes.

Participants were divided into the COVID-19 infected group and non-COVID-19 infected group based on whether they had been infected with COVID-19 and how they were diagnosed with COVID-19 infection (SARS-CoV-2 nucleic acid test, SARS-CoV-2 antigen test, specific symptoms of COVID-19 infection, et al.) [22]. Older adults with chronic respiratory disease can also identify COVID-19 infection by COVID-19 specific symptoms (acute fever, muscle pain, headache, and loss of taste or smell), recent contact history with COVID-19 infected patients, and COVID-19 detection methods [22].

According to the sample size calculation in logistic regression analysis, the sample size could be 10 times of number of independent variables [23]. There were 10 independent variables in this study. Considering 15 % of invalid questionnaires, the sample size was calculated to be at least 118. In the current study, 127 questionnaires were collected, and 111 questionnaires were valid for statistical analysis.

Measures

For all participants in this study, demographic and clinical characteristics, and medication adherence are assessed. Medication taking behavior, COVID-19 related illness perception, COVID-19 related stigma and social network are evaluated only for the COVID-19 infected group.

Demographic and clinical characteristics

A self-designed questionnaire is delivered to collect the data of demographic and clinical characteristics, including age, gender, marital status, whether living alone, duration of chronic disease (if participants have more than 1 chronic disease, the longest duration of disease was selected), number of types of long-term medication taken daily, and blood pressure.

Medication adherence

The 8-item Morisky Medication Adherence Scale (MMAS-8) is developed by Morisky [24]. For item 1 to 7, participants answer “Yes” or “No”. For item 8, participants choose one option from “Never”, “Once in a while”, “Sometimes”, “Usually” and “All the time”. The total scores of MMAS-8 are classified into 3 levels: low adherence (score<6), medium adherence (6 to 7), and high adherence (a score of 8). Higher MMAS-8 score indicates greater adherence to long-term medication. In the study of Morisky, the Cronbach’s α of MMAS-8 is 0.830. In this study, the Cronbach’s α of MMAS-8 is calculated to be 0.833.

Medication taking behavior

A self-designed item, “When you were infected with COVID-19, did your long-term medication intake change”, is used to evaluate the medication taking behavior. Participants choose an option from “No change”, “Reduce the dose of medication”, and “Stop taking medication”.

COVID-19 related illness perception

The Brief Illness Perception Questionnaire (BIPQ) is used to measure the level of illness perception about COVID-19, which is developed by Broadbent et al. [25] and translated into Chinese by Sun et al. [26]. There are 8 items in the BIPQ, each of which is rated on a scale of 0 to 10. A high score of BIPQ indicates a negative level of illness perception. According to Sun et al., BIPQ has a good test-retest reliability of 0.931 and has the criterion validity of 0.640 [26]. In this study, the Cronbach’s α is calculated as 0.684.

COVID-19 related stigma

The Self-Stigma Scale-Short Form (SSS-S) is compiled by Mak and Cheung [27], which is used to evaluate the level of COVID-19 related self-stigma. SSS-S is a 4-point Likert scale, with 9 items rating from “1=strongly disagree” to “4=strongly agree”. The total score is the mean of all items. A higher score in the SSS-S reflects higher level of stigma. SSS-S has been adopted to measure COVID-19 related stigma, which has good psychometric properties [28]. According to Mak and Cheung, the SSS-S has an excellent Cronbach’s α of 0.91 and good criterion validity [27]. In the present study, the Cronbach’s α of SSS-S is 0.896.

Social network

The 6-item Lubben Social Network Scale (LSNS-6) was developed by Lubben et al. to evaluate social networks in older adults [29]. LSNS-6 consists of 6 items, including 3 items in family subscale and 3 items in friends subscale. LSNS-6 was rated on a scale of 0 to 5, with “0=none”, “1=one”, “2=two”, “3=three or four”, “4=five thru eight” and “5=nine or more”. The total score of LSNS ranges from 0–30, with higher scores representing greater social network. The Chinese version of LSNS-6 has good structural validity and the Cronbach’s α of 0.83 [29, 30]. And the Cronbach’s α in this study is 0.898.

Data analysis

Descriptive statistics, including mean and standard deviation (SD)/median with interquartile range and frequency with percentage, were applied to describe participants’ continuous variables and categorical variables. Independent-sample t test, Mann-Whitney U test and Chi-square test were employed to compare demographic characteristics, clinical characteristics and medication adherence between COVID-19 infected group and non-COVID-19 infected group. Chi-square test and Point-biserial correlation were conducted to analyze influencing factors of medication taking behavior among COVID-19 infected participants. Those factors significant in Chi-square test and Point-biserial correlation analysis were included in the multivariable logistic regression. Statistics analyses were conducted by IBM SPSS 25.0. The results were considered statistically significant if p value less than 0.05.

Ethical consideration

This study was approved by the Medical Ethic Committee (No. KY-2022-111). Before data collection, each participant was informed of the purpose of the study and their rights to terminate the investigation and withdraw from the study. Oral informed consent was obtained from all participants in this study.

Results

A total of 127 eligible older adults participated in the survey. Of 127 questionnaires, 16 were excluded due to incomplete information, with 111 (87.4 %) questionnaires remaining valid. In rural areas, a number of older adults have a low level of education or have never received any education. Older adults with low educational level refused to participate in the study because they could not understand the significance of the research or the academic questions of the questionnaire. In addition, dialects were spoken in the surveyed rural areas, and some older adults were unable to communicate with the researchers in Mandarin. Although there were difficulties in recruiting rural-dwelling older adults, the number of participants still meets the standard for the required sample size.

Participants characteristics

The mean age of participants was 73.61±6.47 years, ranging from 60 to 90 years. Most participants were married (72.07 %) and living with families (81.08 %). The duration of chronic diseases ranged from 1 to 50 years, and its median and interquartile range were both 7.00 years. 84.68 % of participants had abnormal blood pressure (systolic pressure higher than 140 mmHg or diastolic pressure higher than 90 mmHg), and the mean systolic pressure and diastolic pressure were 162.36±24.32 mmHg and 91.16±13.50 mmHg respectively. Approximately 70 % of participants took 1 to 3 types of medication for chronic diseases. There was no significant difference in demographic and clinical characteristics between COVID-19 infected group and non-COVID-19 infected group. Characteristics of participants were shown in Table 1.

Table 1:

Descriptive characteristics of the participants and comparisons between COVID-19 infected group and non-COVID-19 infected group (n=111).

Variable All (n=111) CGa (n=61) NCGb (n=50) t/Z/χ 2 p-Valuec
Mean±SD/median(interquartile range)/n (%) Mean±SD/median(interquartile range)/n (%) Mean±SD/median(interquartile range)/n (%)
Age, years 73.61±6.47 72.64±6.07 74.80±6.80 −1.768 0.080
Gender
 Male 47(42.34) 21(34.43) 26(52.00) 3.476 0.062
 Female 64(57.66) 40(65.57) 24(48.00)
Marital status
 Married 80(72.07) 41(67.21) 39(78.00) 1.588 0.208
 Unmarriedd 31(27.93) 20(32.79) 11(22.00)
Living alone
 Yes 21(18.92) 12(19.67) 9(18.00) 0.050 0.823
 No 90(81.08) 49(80.33) 41(82.00)
The number of long-term medication taken daily
 1–3 77(69.37) 46(75.41) 31(62.00) 2.325 0.127
 4–6 34(30.63) 15(24.59) 19(38.00)
Duration of chronic disease, years 7.00(7.00) 7.00(6.50) 5.00(7.00) −0.428 0.669
Blood pressure, mmHg 162.36±24.32/91.16±13.50 162.10±26.33/90.17±13.96 162.67±21.88/92.36±12.95 −0.121/−0.852 0.904/0.396

  1. aCG refers to COVID-19 infected group. bNCG refers to non-COVID-19 infected group. cp value was obtained by comparing the differences in demographic characteristics, clinical characteristics and scores of adherence to medication between two groups. dUnmarried status includes single, divorced and widowed status.

Comparisons of medication adherence for chronic diseases between COVID-19 infected group and non-COVID-19 infected group

As shown in Table 2, the scores of medication adherence for “COVID-19 infected group” and “non-COVID-19 infected group” were 4.92±2.39 and 5.20±2.34 respectively, which were both at low levels. Although the medication adherence score of COVID-19 infection group was lower than that of non-COVID-19 infected group, there was no significant difference in medication adherence scores between two groups (t=−0.614, p=0.541).

Table 2:

Comparison of medication adherence between COVID-19 infected group and non-COVID-19 infected group.

Variable All (n=111) CGa (n=61) NCGb (n=50) t p-Value
Mean±SD Mean±SD Mean±SD
Scores of medication adherencec 5.04±2.36 4.92±2.39 5.20±2.34 −0.614 0.541

  1. aCG refers to COVID-19 infected group. bNCG refers to non-COVID-19 infected group. cThe MMAS-8 Scale, content, name, and trademarks are protected by US copyright and trademark laws. Permission for use of the scale and its coding is required. A license agreement is available from MMAR, LLC., www.moriskyscale.com

Three levels of medication adherence were presented in Figure 2. There was no significant difference in the levels of medication adherence between COVID-19 infected group and non-COVID-19 infected group (χ 2=1.261, p=0.532).

Figure 2: Medication adherence for chronic diseases between COVID-19 infected adults and non-COVID-19 infected adults.
Figure 2:

Medication adherence for chronic diseases between COVID-19 infected adults and non-COVID-19 infected adults.

The medication taking behavior among participants with COVID-19 infection

For participants infected with COVID-19, 63.93 % maintained taking medication for chronic diseases when they were infected with COVID-19. 3.28 % of the participants reduced the dose of medication for chronic diseases, and 32.79 % of them stopped taking the medication for chronic diseases. The results were described as Table 3.

Table 3:

Descriptive characteristics of participants with COVID-19 infection (n=61).

Variable Mean±SD/n (%)
COVID-19 related illness perception 33.89±10.26
COVID-19 related stigma 2.35±0.48
Social network 14.20±6.04
Medication taking behavior
 No change 39(63.93)
 Reduce the dose of medication 2(3.28)
 Stop taking medication 20(32.79)

Influencing factors of medication taking behavior among COVID-19 infected participants

In the statistical analysis of the associated factors of medication taking behavior, medication taking behavior was divided into a binary variable, with values of “0=No change” and “1=Reduce the dose of medication or stop taking medication” respectively.

According to the results of Point-biserial correlation shown in Table 4, the scores of COVID-19 related illness perception (r=0.408, p=0.001), COVID-19 related stigma (r=0.333, p=0.009), and social network (r=0.351, p=0.005) were positively correlated with the change of medication taking behavior. And the results of multivariable logistic regression, shown in Table 5, indicated that COVID-19 related illness perception (OR=1.111, p=0.004) and social network (OR=1.156, p=0.010) were influencing factors of reducing the dose of medication or stopping taking medication among COVID-19 infected participants.

Table 4:

Univariate analysis of factors associated with medication taking behavior among COVID-19 infected participants (n=61).

Variable χ 2/r p-Value
Age −0.063 0.631
Gender 0.057 0.811
Marital status 0.015 0.904
Living alone 0.308 0.579
Duration of chronic disease 0.105 0.419
The number of long-term medication taken daily 1.398 0.237
COVID-19 related illness perception 0.408 0.001a
COVID-19 related stigma 0.333 0.009a
Social network 0.351 0.005a

  1. ap<0.05.

Table 5:

Multivariable logistic regression analysis of factors associated with medication taking behavior among COVID-19 infected participants (n=61).

Variable B SEa Wald χ 2 p-Value ORb 95 % CIc
Constant −6.418 1.725 13.834 <0.001 0.002 –
COVID-19 related illness perception 0.105 0.036 8.409 0.004 1.111 (1.035, 1.193)
Social network 0.145 0.057 6.574 0.010 1.156 (1.035, 1.291)

  1. aSE, Standard error. bOR, Odd ratio. cCI, Confidence Interval.

Discussions

This study found out what changes the COVID-19 infection can cause on medication adherence among older adults with chronic diseases, and focused on the medication taking behavior and its influencing factors among older adults with chronic diseases during COVID-19 infection. The present study identified three major findings. Firstly, there was no statistically significant difference in medication adherence between COVID-19 infected group and non-COVID-19 infected group. Secondly, most participants did not change the intake of chronic diseases medication during COVID-19 infection, but still more than one-third of participants reduced the dose of medication or stopped taking medication. Thirdly, COVID-19 related illness perception and social network were influencing factors of reducing the dose of medication or quitting medication among rural-dwelling older adults with chronic diseases.

Impact of COVID-19 infection on medication adherence among rural-dwelling older adults with chronic diseases

This study showed that there was no significant effect of COVID-19 infection on medication adherence for chronic diseases among rural-dwelling older adults. This was consistent with studies of Zhang et al. and Yoon et al., which compare medication adherence before and during the COVID-19 pandemic [31, 32]. With the optimization of COVID-19 controlling strategies, the risk perception related to COVID-19 was lower than before [33, 34]. At this stage, the impact of COVID-19 on chronic diseases management was no longer as serious as it was at the beginning of the COVID-19 outbreak. In addition, measures coping with the COVID-19 outbreak have increased health knowledge, improved health literacy and promoted health management among older adults to some extent [35, 36]. Older adults paid more attention to daily health practices (hand washing, mask-wearing, et al.) and utilize health information to support healthier lifestyle [35, 36]. Therefore, this study does not anticipate any negative effect of COVID-19 infection on medication adherence. However, the medication adherence of rural-dwelling older adults was not at the desired level regardless of whether they were infected with COVID-19. This indicates that medication adherence among older adults with chronic diseases in rural areas still warrant more in-depth understanding.

Additionally, although there was no significant difference in medication adherence during COVID-19 infection, the impact of the long-term sequalae of COVID-19 infection on medication adherence still requires attention. The cumulative incidence of long-term sequalae of COVID-19 was reported to range from 9 to 63 %, which includes fatigue, cognitive impairment and memory issues [37]. Cognition impairment was a significant risk factor of medication non-adherence among older adults with chronic diseases [38]. But the evidence regarding the association between the sequalae of COVID-19 infection and medication adherence is limited, which needs to be further discussed in future research.

The medication taking behavior among rural-dwelling older adults with chronic diseases when they were infected with COVID-19

In the present study, more than 30 % of older adults reduced the dose of medication or even stopped taking medication when they were infected with COVID-19, which was in line with the rate of non-adherence to chronic medication during COVID-19 reported by Zakaria et al. [39]. Nevertheless, compared with the rate of non-adherence in Barnes et al.’s study [40], the rate of reducing the medication dose in our study was higher. The reasonable explanation might be that our participants were older adults dwelling in rural areas, who were high-risk population with suboptimal medication adherence [41]. From the perspective of environmental factors, the unequal distribution of healthcare facilities and transport constraints contribute to the poor accessibility of healthcare service in rural areas [42]. In terms of personal factors, relatively limited knowledge, low income, and poor awareness of receiving medical services may hinder older adults from taking medication regularly [9]. And low socioeconomic status combined with medication non-adherence significantly increase risks of complications and mortality [41]. Thus, factors associated with reducing the dose of medication or stopping taking medication among rural-dwelling older adults are necessary to be identified to provide targeted guidance.

Influencing factors of medication taking behavior among rural-dwelling older adults with chronic diseases

Negative illness perception of COVID-19 was a risk for older adults to reduce the dose of medication or stop taking medication. If older adults have more negative perception and worries about COVID-19, they are more likely to reduce the dose of medication or even quitting medication. It was consistent with the perspectives of Kaye et al. that medication non-adherence may be related to the concerns that chronic diseases may be affected by COVID-19 [15]. Besides, patients were concerned that medication used to treat their discomfort may lead to worse clinical outcomes of COVID-19 infection [43]. And the concerns about medication could disrupt their adherence to chronic diseases medication [40]. Thus, negative illness perception of COVID-19 could contribute to reducing the dose of medication or stopping taking medication during COVID-19 infection. Therefore, further evidence guiding the intake of chronic diseases medication during the COVID-19 infection is required. Specific and appropriate education program about COVID-19 should be continuously strengthened to increase knowledge about COVID-19 and reduce the negative illness perception of COVID-19 infection [44].

Social network are also correlated with the reduction or withdrawal of medication intake during COVID-19 infection. Several studies indicate that social support could effectively improve patients’ adherence to chronic diseases medication during COVID-19 [9, 45]. Our findings seem to come in contrast to previous studies. However, it highlights the importance of social support and social connection for medication adherence behavior. To our knowledge, due to traffic restrictions in rural areas, weak mobility of older adults and the Chinese traditional view that “a near neighbor is better than a distant cousin”, the primary social contacts of older adults were their families and neighbors. Older adults are less knowledgeable about digital technology and prefer communicating and interacting with their families and neighbors face to face [46], especially for those in rural areas. During the period of COVID-19 infection, older adults are required to stay at their homes to avoid spreading the virus to others. As a result, social contact and social connection is reduced and restricted [9]. And those who are with better social network before the COVID-19 pandemic may be more vulnerable to the negative effects of social isolation due to home quarantine. Therefore, adequate social support should be provided to rural-dwelling older adults by various forms, including telephone, video call, and other real-time interactive communication, especially for those with better social network in daily life.

Limitations

There are several limitations in the present study. Firstly, the sample only included older adults in Guangdong province by convenience sampling, and the findings could not be generalized. Secondly, medication adherence behavior is a complex issue, which requires an in-depth qualitative interview to understand its intrinsic logicality. Thus, it is necessary to conduct studies with representative and large sample and consider mix-method design in the future. Despite the limitations, our study provides additional knowledge about the impact of COVID-19 infection on medication taking behavior among older adults in rural areas, and the significance of improving COVID-19 related illness perception and enhancing social support for older adults in rural areas.

Conclusions

In summary, although this study did not find out any negative effects of COVID-19 infection on medication adherence in rural-dwelling older adults with chronic diseases, the medication adherence of older adults with COVID-19 infection was suboptimal, and still more than one-third of participants reduced the dose of medication or stopped taking medication. Older adults with negative illness perception of COVID-19 and better social network were more likely to reduce or stop taking medication for chronic diseases when they were infected with COVID-19. Therefore, during the ongoing COVID-19 pandemic, older adults with chronic diseases are recommended to increase knowledge about COVID-19 infection and polypharmacy. And healthcare providers should provide targeted health education to mitigate the negative perception of COVID-19 and guide older adults to connect with their families and friends through modern technology in the future.

Corresponding author: Meifen Zhang and Yu Cheng, School of Nursing, Sun Yat-sen University, No. 74, Zhongshan Road II, Yuexiu District, Guangzhou 510000, China, School of Medicine, Sun Yat-sen University, Gongchang Road, Guangming District, Shenzhen 518000, China; The Seventh Affiliated Hospital, Sun Yat-sen University, No.628, Zhenyuan Road, Xinhu Street, Guangming New District, Shenzhen 518000, China; School of Sociology & Anthropology, Sun Yat-sen University, No.135, West Xingang Road, Haizhu District, Guangzhou 510000, China, E-mail: (M. Zhang), (Y. Cheng)

Meifen Zhang and Yu Cheng share equal corresponding authorship.

Funding source: National Social Science Fund of China

Award Identifier / Grant number: 20&ZD122

Acknowledgments

The MMAS-8 Scale, content, name, and trademarks are protected by US copyright and trademark laws. Permission for use of the scale and its coding is required. A license agreement is available from MMAR, LLC., www.moriskyscale.com.

  1. Research ethics: The study was approved by the Medical Ethic Committee of the First Affiliated Hospital of Jinan University (No. KY-2022-111).

  2. Informed consent: The study has obtained oral informed consent from all participants.

  3. Author contributions: Baoyi Zhang: investigation, data analysis, first-draft writing; Xinxin Li: investigation, writing – including review and copyediting; Jingyue Xie: investigation, writing – including review and copyediting; Ni Gong: conceptualization, supervision; Yu Cheng: conceptualization, writing – reviewing and copyediting; Meifen Zhang: conceptualization, methodology, writing – reviewing and copyediting.

  4. Competing interests: The authors state no conflict of interest.

  5. Research funding: This work was supported by the National Social Science Foundation of China (grant number: 20&ZD122).

  6. Data availability: The data used in this study is available from the corresponding authors upon reasonable request.

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Received: 2024-04-27
Accepted: 2024-07-11
Published Online: 2024-08-20

© 2024 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Artikel in diesem Heft

  1. Frontmatter
  2. Editorials
  3. Expert consensus on narrative medicine in China (2023)
  4. The living will in China: progress and challenges following Shenzhen’s legislation
  5. Review Article
  6. Re-exploration of Oslerian legacy of Osler’s address “Old Humanities and New Science”
  7. Research Articles
  8. Teaching close reading: an instructor’s reflective case study of a Contemporary English Literature course for EFL medical students
  9. Subjective well-being of women undergoing in vitro fertilization and embryo transfer and influencing factors
  10. Reverse care at the end of life
  11. Impact of COVID-19 infection on medication adherence and medication taking behavior among rural-dwelling older adults with chronic diseases: a cross-sectional study
  12. A qualitative study on illness perceptions and self-mastery among Chinese elderly with hypertension
  13. Letter to the Editor
  14. Rural doctor in early 13th-century China
  15. Case Reports
  16. Denial as an ethical problem: the example of ICU triage in the context of the COVID-19 pandemic
  17. A case study of palliative care consultation: narrative practice for addressing clinical bottleneck problems
  18. Miscellaneous
  19. To solve the dilemma of modern medical ethics review with the wisdom of traditional Chinese philosophy
https://doi.org/10.1515/ajmedh-2024-0013
Schlagwörter für diesen Artikel
medication adherence; medication taking behavior; older adults; chronic diseases; rural areas; COVID-19
Creative Commons
BY 4.0

Artikel in diesem Heft

  1. Frontmatter
  2. Editorials
  3. Expert consensus on narrative medicine in China (2023)
  4. The living will in China: progress and challenges following Shenzhen’s legislation
  5. Review Article
  6. Re-exploration of Oslerian legacy of Osler’s address “Old Humanities and New Science”
  7. Research Articles
  8. Teaching close reading: an instructor’s reflective case study of a Contemporary English Literature course for EFL medical students
  9. Subjective well-being of women undergoing in vitro fertilization and embryo transfer and influencing factors
  10. Reverse care at the end of life
  11. Impact of COVID-19 infection on medication adherence and medication taking behavior among rural-dwelling older adults with chronic diseases: a cross-sectional study
  12. A qualitative study on illness perceptions and self-mastery among Chinese elderly with hypertension
  13. Letter to the Editor
  14. Rural doctor in early 13th-century China
  15. Case Reports
  16. Denial as an ethical problem: the example of ICU triage in the context of the COVID-19 pandemic
  17. A case study of palliative care consultation: narrative practice for addressing clinical bottleneck problems
  18. Miscellaneous
  19. To solve the dilemma of modern medical ethics review with the wisdom of traditional Chinese philosophy
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