BioMed Research International

BioMed Research International / 2020 / Article

Research Article | Open Access

Volume 2020 |Article ID 8730212 | https://doi.org/10.1155/2020/8730212

Yan-Qing Song, Wen-Rui Zhang, Si-Xi Zhang, Ting-Hong Wang, Zhe Jiang, Chun-Feng Meng, Tian-Zhen Zhang, Qi-Zhong Xin, Ke-Jun Cao, Yue Zhang, Ying Sun, "Factors Influencing Administration, Recognition, and Compliance of Medicine among Community Residents from Jilin Province, China: A Questionnaire Study", BioMed Research International, vol. 2020, Article ID 8730212, 13 pages, 2020. https://doi.org/10.1155/2020/8730212

Factors Influencing Administration, Recognition, and Compliance of Medicine among Community Residents from Jilin Province, China: A Questionnaire Study

Academic Editor: Janet Sultana
Received31 May 2019
Revised07 Aug 2019
Accepted05 Jun 2020
Published18 Jul 2020

Abstract

Introduction. To identify and analyze factors that influence administration, recognition, and compliance of medicine among community residents in Jilin Province, China. Methods. A survey was carried out among 2417 community residents in Jilin Province, China, to study their administration (CRA), recognition (CRR), and compliance (CRC) of medicine. Multivariate logistic regression analyses and chi-squared tests were performed to assess factors influencing CRA, CRR, and CRC. Results. Logistic analyses showed that gender, educational level, and occupation were influencing factors on CRA; age, educational level, smoking status, and health condition were influencing factors on CRR; and gender, age, occupation, and health condition were influencing factors on CRC. Conclusions. CRA, CRR, and CRC are associated with specific lifestyles and social economic statuses of community residents. Attention should be paid to influencing factors in order to facilitate community pharmaceutical care, promote the rational use of drugs, and ensure the safe use of medications. This study explores the type and extent of professional services provided through community pharmacies in Jilin Province, China, and provides evidence for optimizing the quality of community pharmacy services.

1. Introduction

The World Health Organization (WHO) defines adverse drug reactions (ADRs) as “any response to a drug that is noxious and unintended and occurs at doses normally used in man for prophylaxis, diagnosis, or therapy of diseases” [1]. ADRs are a major global clinical problem and can lead to substantial mortality and morbidity [2]. ADRs are caused by a combination of patient-related, medication-related, and social-related factors [3]. Potentially inappropriate medications (PIMs) refer to the use of a medication whose adverse outcome outweighs the potential benefit [4].

Risk factors of medication-related represented patient-, environment-, and treatment-related domains, which can be identified at home visits, include poor adherence with medication regimens, inappropriate storage of medication, use of expired medication, application/usage of inappropriate medications, and possible underdosing or possible overdosing. As medication use is an effective way of providing basic medical and health services, rational administration of pharmacy services has become a critical factor influencing the quality of community health services.

Pharmacies are an important part of health care in China. In the 1990s, pharmaceutical care was first introduced in China, and the responsibility of the pharmacist was defined as improving the patient’s quality of life by providing health care services and achieving specific results. According to the European Society of Clinical Pharmacy, one of a clinical pharmacist’s responsibilities is the detection and prevention of harmful medication errors [59] and drug-related problems, including ADRs [1012]. Before taking a prescription drug, patients are counseled by their physician or clinical pharmacist with drug-related questions. For community residents, the use of medications is becoming more complex as more medicines are being introduced to the market, so the demand for community-based pharmaceutical care is increasing.

However, current knowledge on the scope and quality of pharmacy services in developing countries is limited. Therefore, it is worthwhile to further investigate the current status of community residents’ administration (CRA), recognition (CRR), and compliance (CRC) of medicine in China. We studied this topic in randomly selected communities in Jilin Province of China with the aim of providing a more effective service for residents and improving the public’s knowledge of self-medication safety.

2. Methods

2.1. Population

A questionnaire survey was conducted between June 2016 and January 2017 in Jilin Province, China. A total of 2800 community residents (aged 18 years or older) completed the questionnaires. “Community residents” were defined as people living in homes or apartments of a community and not in institutions such as hospitals. Inclusion criteria included community residents having a clear understanding of the study, having no problems in communicating with investigators, being willing to cooperate with the researcher, and filling at least three or more prescriptions at a pharmacy in the past 12 months. Exclusion criteria were the submission of incomplete questionnaires and/or duplicated answers to each question on each page.

Authors summarized the problems pertaining to the rational use of drugs regarding CRA, CRR, and CRC when designing the questionnaire. The survey was anonymous. According to the results of the investigation and feedback, further argumentation, modifications, and finalization were undertaken by pharmaceutical experts. The survey providers randomly distributed the questionnaire to community residents who were asked to fill in the required information and submit the questionnaires on the spot. The Ethics Committee of the First Hospital of Jilin University approved the study protocol on May 2016 (2016-028), and written informed consent was obtained from all community residents to allow the use and publication of their data in the study.

2.2. Questionnaire Setting

The questionnaire included the following information: sociodemographic characteristics of the residents (including gender, age, educational level, occupation, monthly income, marital status, hospitalizations per year, medical insurance, types of medicines per day, number of medications received each time, adverse reactions, smoking status, alcohol consumption status, and self-rated health status); CRA (category of drug storage, storage method, whether it is classified, whether the medicine cabinet was cleaned regularly, and whether the individual has the knowledge of drug administration); CRR (understanding basic drug information including drug name, labelled indications, dosage, drug-drug interactions, drug-food interactions, and adverse effects); and CRC (drug intake behavior and strict adherence to the prescribed medicine and required dosage). The data were double entry and were independently checked by two investigators.

An analysis of questionnaire reliability was undertaken using Cronbach’s alpha, which gave results for CRA, CRR, and CRC of 0.834, 0.782, and 0.825, respectively. Questionnaire scores were grouped in the following categories. CRA: poor (≤24 points) and good (25–31 points); and CRR: poor (≤28 points) and good (29–38 points). CRC scores could range from 0 to 8 with low adherence defined as a .

2.3. Statistical Analyses

SPSS v17.0 (SPSS Inc., Chicago, IL, USA) software package was used for statistical analyses. To examine bivariate associations between independent variables with poor and better CRA, CRR, and CRC, we performed chi-squared () analyses or Fisher’s exact tests for categorical independent variables ( for statistical significance) and Mann-Whitney test or -test for continuous independent variables ( for statistical significance). Significant independent variables from bivariate analyses were further examined in multivariate logistic regression analysis to determine factors associated with poor and better categories of CRA, CRR, and CRC. A two-sided value less than 0.05 was considered statistically significant.

3. Results

3.1. Sociodemographic Characteristics

A total of 2800 questionnaires were distributed to the community residents, and 2417 usable questionnaires were returned (from 972 males and 1445 females) thus giving a valid response rate of 86.3%. Figure 1 shows the details of the selection process. The average age of the community residents was years; 31.6% graduated from senior high school or polytechnic and 84.6% had a monthly income of less than $600, 73.7% were never smokers, and 66.6% were abstainers (Table 1). Community residents had some general knowledge of medication safety. Only about 10% of the residents had private medical insurance or other means to buy medications.


VariablesCommunity residents ()Weighted percentages

Gender
Male97240.2
Female144559.8
Age (years)
<1810.1
18–4079733.0
41–60101141.8
61–8059324.5
>80150.6
Ethnicity
Han Chinese220691.3
Other2118.7
Highest educational level
Primary school1777.3
Middle school62125.7
Senior high school or polytechnic76331.6
Junior college53722.2
Undergraduate31913.2
Occupation
Agricultural worker2299.5
Industrial (or skilled) worker81733.8
Professional38515.9
Service provider54622.6
Other44018.2
Monthly income
≤1000 RMB1827.5
1001–2000 RMB66127.3
2001–3000 RMB67227.8
3001–4000 RMB53021.9
4001–5000 RMB24110.0
>5000 RMB1315.4
Marital status
Unmarried28011.6
Married206385.4
Divorced743.1
Hospitalizations per year
0146660.7
159924.8
2–330012.4
4–6381.6
>6140.6
Medical insurance
Medical insurance in urban area74630.9
Urban employees’ medical insurance102542.4
“New-style” rural cooperative medical care40416.7
Commercial medical insurance381.6
Private expenses1676.9
Others371.5
Types of medicines per day
≤2181174.9
2–557023.6
6–10321.3
>1040.2
Number of medications received each time
≤5198682.2
6–1037215.4
11–15451.9
>15140.6
Adverse reactions
Yes52721.8
No141758.6
Uncertain47319.6
Smoking status
No smoking178173.7
Light smoking ()34614.3
Middle-heavy smoking (PI 200–400)1998.2
Heavy smoking ()301.2
Smoking cessation381.6
Smoking cessation (≥2 years)231.0
Alcohol consumption status
No drinking160966.6
Heavy drinking522.2
Middle–heavy drinking2329.6
Light drinking51221.2
Temperance90.4
Temperance (≥2 years)30.1
Self-rated health status
Very good33613.9
Good94439.1
Fair92438.2
Poor1988.2
Very poor150.6

3.2. Influencing Factors on CRA, CRR, and CRC

The appropriateness of CRA, CRR, and CRC was 53.6%, 47.7%, and 54.0%, respectively; only 25.2% of the residents met the three criteria of CRA, CRR, and CRC. In the univariate analyses (Tables 2 and 3), we found that gender, age, educational level, and occupation of residents were significantly associated with appropriate CRA (). Gender, age, educational level, occupation, smoking status, and drinking levels were statistically significant () when associated with appropriate CRR while gender, age, occupation, medical insurance, number of medications taken on each occasion, types of medicines per day, smoking status, health condition, and drinking levels of community residents were statistically significant () when associated with appropriate CRC.


VariablesCommunity residents
(%)
CRACRRCRC
Appropriately
(%)
Inappropriately
(%)
StatisticsAppropriately
(%)
Inappropriately
(%)
StatisticsAppropriately
(%)
Inappropriately
(%)
Statistics

Gender
 Male972 (40.2)520 (53.5)452 (46.5): 25.816<0.001564 (58.0)408 (42.0): 21.386<0.001466 (47.9)506 (52.1): 2.4500.117
 Female1445 (59.8)621 (43.0)824 (57.0)700 (48.4)745 (51.6)646 (44.7)799 (55.3)
Ethnicity
 Han Chinese2206 (91.3)1165 (52.8)1041 (47.2): 0.0030.9551060 (48.1)1146 (51.9): 3.5910.0581193 (54.1)1013 (45.9): 0.0770.781
 Others211 (8.7)111 (52.6)100 (47.4)87 (41.2)124 (58.8)112 (53.1)99 (46.9)
Highest educational level
 Primary school177 (7.3)105 (59.3)72 (40.7): 80.087<0.001106 (59.9)71 (40.1): 80.725<0.00190 (50.8)87 (49.2): 7.2260.124
 Middle school621 (25.7)356 (57.3)265 (42.7)395 (63.6)226 (36.4)267 (43.0)354 (57.0)
 Senior high school or polytechnic763 (31.6)358 (46.9)405 (53.1)412 (54.0)351 (46.0)349 (45.7)414 (54.3)
 Junior college537 (22.2)227 (42.3)310 (57.7)223 (41.5)314 (58.5)266 (49.5)271 (50.5)
 Undergraduate319 (13.2)95 (29.8)224 (70.2)128 (40.1)191 (59.9)140 (43.9)179 (56.1)
Occupation
 Agricultural worker229 (9.5)142 (62.0)87 (38.0): 55.406<0.001141 (61.6)88 (38.4): 38.197<0.001125 (54.6)104 (45.4): 36.657<0.001
 Industrial (or skilled) worker817 (33.8)437 (53.5)380 (46.5)480 (58.8)337 (41.2)352 (43.1)465 (56.9)
 Professional385 (15.9)152 (39.5)233 (60.5)176 (45.7)209 (54.3)136 (35.3)249 (64.7)
 Service provider546 (22.6)221 (40.5)325 (59.5)254 (46.5)292 (53.5)284 (52.0)262 (48.0)
 Other440 (18.2)189 (43.0)251 (57.0)213 (48.4)227 (51.6)215 (48.9)225 (51.1)
Monthly income
 ≤1000 RMB182 (7.5)85 (46.7)97 (53.3): 9.1470.10381 (44.5)101 (55.5): 11.0210.05191 (50.0)91 (50.0): 5.5340.354
 1001–2000 RMB661 (27.3)352 (53.3)309 (46.7)309 (46.7)352 (53.3)355 (53.7)306 (46.3)
 2001–3000 RMB672 (27.8)354 (52.7)318 (47.3)318 (47.3)354 (52.7)373 (55.5)299 (44.5)
 3001–4000 RMB530 (21.9)259 (48.9)271 (51.1)262 (49.4)268 (50.6)272 (51.3)258 (48.7)
 4001–5000 RMB241 (10.0)139 (57.7)102 (42.3)132 (54.8)109 (45.2)136 (56.4)105 (43.6)
 >5000 RMB131 (5.4)75 (57.3)56 (42.7)76 (58.0)55 (42.0)78 (59.5)53 (40.5)
Marital status
 Unmarried280 (11.6)151 (53.9)129 (46.1): 2.0430.360161 (57.5)119 (42.5): 5.7670.056111 (39.6)169 (60.4): 4.7550.093
 Married2063 (85.4)1072 (52.0)991 (48.0)1040 (50.4)1023 (49.6)800 (38.8)1263 (61.2)
 Divorced74 (3.0)33 (44.6)41 (55.4)34 (45.9)40 (54.1)38 (51.4)36 (48.6)
Hospitalizations per year
 01466 (60.7)743 (50.7)723 (49.3): 6.2940.178700 (47.7)766 (52.3): 4.1590.385839 (57.2)627 (42.8): 8170.146
 1599 (24.8)271 (45.2)328 (54.8)265 (44.2)334 (55.8)344 (57.4)255 (42.6)
 2–3300 (12.4)138 (46.0)162 (54.0)133 (44.3)167 (55.7)190 (63.3)110 (36.7)
 4–638 (1.6)17 (44.7)21 (55.3)14 (36.8)24 (63.2)20 (52.6)18 (47.4)
 >614 (0.6)7 (50.0)7 (50.0)6 (42.9)8 (57.1)11 (78.6)3 (21.4)
Medical insurance
 Medical insurance in urban area746 (30.9)404 (54.2)342 (45.8): 9.9630.076366 (49.1)380 (50.9): 9.8050.081332 (44.5)414 (55.5): 6.7950.236
 Urban employees’ medical insurance1025 (42.4)563 (54.9)462 (45.1)485 (47.3)540 (52.7)498 (48.6)527 (51.4)
 New-style rural cooperative medical care404 (16.7)224 (55.4)180 (44.6)204 (50.5)200 (49.5)197 (48.8)207 (51.2)
 Commercial medical insurance38 (1.6)17 (44.7)21 (55.3)22 (57.9)16 (42.1)23 (60.5)15 (39.5)
 Private expenses167 (6.9)110 (65.9)57 (34.1)86 (51.5)81 (48.5)85 (50.9)82 (49.1)
 Others37 (1.5)22 (59.5)15 (40.5)26 (70.3)11 (29.7)17 (45.9)20 (54.1)
Adverse reactions
 Yes527 (21.8)276 (52.4)251 (47.6): 4.2470.120259 (49.1)268 (50.9): 4.1180.128294 (55.8)233 (44.2): 1.1600.560
 No1417 (58.6)769 (54.3)648 (45.7)688 (48.6)729 (51.4)763 (53.8)654 (46.2)
 Uncertain473 (19.6)231 (48.8)242 (51.2)206 (43.6)267 (56.4)248 (52.4)225 (47.6)
Smoking status
 No smoking1781 (73.7)887 (49.8)894 (50.2): 6.0340.303847 (47.6)934 (52.4): 69.326<0.001901 (50.6)880 (49.4): 5.7400.332
 Light smoking ()346 (14.3)154 (44.5)192 (55.5)210 (60.7)136 (39.3)169 (48.8)177 (51.2)
 Medium-heavy smoking (PI 200–400)199 (8.2)96 (48.2)103 (51.8)138 (69.3)61 (30.7)91 (45.7)108 (54.3)
 Heavy smoking ()30 (1.2)12 (40.0)18 (60.0)22 (73.3)8 (26.7)18 (60.0)12 (40.0)
 Smoking cessation38 (1.6)19 (50.0)19 (50.0)29 (76.3)9 (23.7)14 (36.8)24 (63.2)
 Smoking cessation (≥2 years)23 (1.0)8 (34.8)15 (65.2)18 (78.3)5 (21.7)12 (52.2)11 (47.8)
Alcohol consumption status
 No drinking1609 (66.6)872 (54.2)737 (45.8)a5.3530.370791 (49.2)818 (50.8)aFisher: 27.181<0.001898 (55.8)711 (44.2)aFisher: 6.3210.264
 Heavy drinking52 (2.2)24 (46.2)28 (53.8)36 (69.2)16 (30.8)23 (44.2)29 (55.8)
 Medium-heavy drinking232 (9.6)132 (56.9)100 (43.1)148 (63.8)84 (36.2)120 (51.7)112 (48.3)
 Light drinking512 (21.2)282 (55.1)230 (44.9)281 (54.9)231 (45.1)263 (51.4)249 (48.6)
 Temperance9 (0.4)5 (55.6)4 (44.4)6 (66.7)3 (33.3)5 (55.6)4 (44.4)
 Temperance (≥2 years)3 (0.1)0 (0.0)3 (100.0)2 (66.7)1 (33.3)2 (66.7)1 (33.3)
Types of medicines per day
 ≤21811 (74.9)981 (54.2)830 (45.8): 6.4140.093890 (49.1)921 (50.9): 6.1780.103864 (47.7)947 (52.3)aFisher: 9.2660.026
 2–5570 (23.6)278 (48.8)292 (51.2)248 (43.5)322 (56.5)232 (40.7)338 (59.3)
 6–1032 (1.3)16 (50.0)16 (50.0)13 (40.6)19 (59.4)15 (46.9)17 (53.1)
 >104 (0.2)1 (25.0)3 (75.0)2 (50.0)2 (50.0)1 (25.0)3 (75.0)
Number of medications received each time
 ≤51986 (82.2)1066 (53.7)920 (46.3): 5.4580.142971 (48.9)1015 (51.1): 1.3430.719938 (47.2)1048 (52.8): 13.3170.004
 6–10372 (15.4)176 (47.3)196 (52.7)172 (46.2)200 (53.8)153 (41.1)219 (58.9)
 11–1545 (1.9)22 (48.9)23 (51.1)20 (44.4)25 (55.6)20 (44.4)25 (55.6)
 >1514 (0.6)8 (57.1)6 (42.9)6 (42.9)8 (57.1)1 (7.1)13 (92.9)
Self-rated health status
 Very good336181 (53.9)155 (46.1): 7.9360.094164 (48.8)172 (51.2): 5.6370.228195 (58.0)141 (42.0): 37.000<0.001
 Good944519 (55.0)425 (45.0)495 (52.4)449 (47.6)449 (47.6)495 (52.4)
 Fair924475 (51.4)449 (48.6)496 (53.7)428 (46.3)394 (42.6)530 (57.4)
 Poor19897 (49.0)101 (51.0)98 (49.5)100 (50.5)71 (35.9)127 (64.1)
 Very poor154 (26.7)11 (73.3)11 (73.3)4 (26.7)3 (20.0)12 (80.0)

Abbreviations: CRA: community residents’ administration of medicine; CRR: community residents’ recognition of medicines; CRC: community residents’ medication compliance; : chi-squared; aFisher’s exact text was conducted.

VariablesCRACRRCRC
Appropriately
(%)
Inappropriately
(%)
StatisticsAppropriately
(%)
Inappropriately
(%)
StatisticsAppropriately
(%)
Inappropriately
(%)
Statistics

Age (years)1141 (47.2)1276 (52.8)<0.0011264 (52.3)1153 (47.7)<0.0011112 (46.0)1305 (54.0)<0.001

Abbreviations: CRA: community residents’ administration of medicine; CRR: community residents’ recognition of medicines; CRC: community residents’ medication compliance; : chi-squared.

After controlling for potential covariates in the multivariable regression models (Table 4), we found that female gender, higher educational level (junior college and above), and professional and service provider occupations were significantly associated with a higher occurrence of appropriate CRA. Educational level (junior college, undergraduate, and above) and poor health condition (poor) were significantly associated with the raised occurrence of appropriate CRR. We also found that age and smoking status were negatively associated with the occurrence of appropriate CRR; these community residents did not generally understand the problems associated with drug use. Female gender, age, occupation, and health condition were positively associated with the occurrence of appropriate CRC, and these patients had better medication adherence.


VariablesLogistic regression analysis
CRACRRCRC
Odds ratio95% CIOdds ratio95% CIOdds ratio95% CI

Gender
 Male111
 Female1.4691.231–1.753<0.0011.1000.897–1.3480.3611.2581.059–1.4950.009
Age (years)
0.9970.990–1.0040.3940.9870.981–0.994<0.0011.0131.005–1.0200.001
Highest educational level
 Primary school11aNA
 Middle school0.9970.694–1.4320.9850.7630.528–1.1020.149
 Senior high school or polytechnic1.4370.979–2.1100.0641.0670.728–1.5640.740
 Junior college1.5981.045–2.4440.0311.5271.006–2.3170.047
 Undergraduate2.6271.619–4.263<0.0011.5050.948–2.3890.043
Occupation
 Agricultural worker111
 Industrial (or skilled) worker1.2490.862–1.8090.2400.9830.702–1.3760.9211.4321.003–2.0440.048
 Professional1.6881.089–2.6170.0191.2670.847–1.8970.2501.8141.189–2.7690.006
 Service provider1.5061.017–2.2290.0411.0370.717–1.5010.8461.2310.843–1.7980.283
 Other1.3980.947–2.0650.0921.0750.740–1.5610.7051.3120.895–1.9220.164
Medical insurance
 Medical insurance in urban areaaNAaNA1
 Urban employees’ medical insurance1.1210.918–1.3690.264
 New-style rural cooperative medical care0.8650.654–1.1440.310
 Commercial medical insurance0.5910.299–1.1660.129
 Private expenses1.0460.735–1.4890.803
 Others1.1630.590–2.2920.604
Smoking status
 No smokingaNA1aNA
 Light smoking ()0.6840.518–0.9040.008
 Middle-heavy smoking (PI 200–400)0.4630.317–0.676<0.001
 Heavy smoking ()0.3780.162–0.8850.025
 Smoking cessation0.3130.141–0.6940.004
 Smoking cessation (≥2 years)0.3300.115–0.9450.039
Alcohol consumption status
 No drinkingaNA1aNA
 Heavy drinking0.6640.352–1.2520.206
 Medium-heavy drinking0.8540.598–1.2190.384
 Light drinking0.9260.735–1.1670.515
 Temperance1.2210.270–5.5180.796
 Temperance (≥2 years)0.7750.054–11.0910.851
Types of medicines per day
 ≤2aNAaNA1
 2–50.9610.742–1.2440.761
 6–100.7020.320–1.5380.376
 >101.9340.171–21.8470.594
Number of medications received each time
 ≤5aNAaNA1
 6–101.0350.776–1.3820.813
 11–150.8140.422–1.5700.538
 157.4360.940–58.8440.057
Self-rated health status
 Very goodaNA11
 Good1.0810.831–1.4050.5631.4581.126–1.8880.004
 Fair1.2190.928–1.6020.1541.6931.293–2.217<0.001
 Poor1.8211.239–2.6780.0022.0641.377–3.094<0.001
 Very poor0.7790.225–2.7000.6945.3881.408–20.6120.014

Abbreviations: CRA: community residents’ administration of medicine; CRR: community residents’ recognition of medicines; CRC: community residents’ medication compliance; : chi-squared; NA: not applicable.aNo relationship in independent variables from chi-squared () analyses or Fisher’s exact test and Mann-Whitney test.

4. Discussion

In this study, we measured the prevalence of potential medication-related risk factors among community residents. We found that the appropriateness of CRA, CRR, and CRC was 53.6%, 47.7%, and 54.0%, respectively. CRA, CRR, and CRC are associated with specific lifestyles and social economic statuses of community residents. Attention should be paid to factors that affect foster community pharmaceutical care, promote the rational use of drugs, and ensure the safety of medications.

According to the results of the multivariate logistic regression analysis, female community residents exhibited appropriate CRA and CRC. The compliance rate was significantly lower among males and those who were illiterate. Okumura et al.’s study showed that women were mainly responsible for the management of medications in the family household [13]. This underlines the important role of women in all aspects of health care, including as the main decision-maker for the management of stored medications. Indeed, females in China are generally obliged to be responsible for the health of their families. We also found that older age was associated with a lack of CRR. Access to CRR is not limited to doctors or pharmacists; some may come from the Internet or written instructions. Older individuals are more likely to suffer from visual or cognitive impairment and thus may find it more difficult to view product labels than their younger counterparts [14]. Age may limit the information acquisition. Regarding CRC, older age corresponded to increased compliance with drug therapy, although this is contrary to the results of another study [15] and may be due to geographical variation in participants’ education as well as other social factors. Ageing is arguably associated with a higher awareness of health and drug relationships and stronger perceived drug effectiveness. Yet, the ability to read medication-related information via the Internet or written instructions can be reduced by factors such as visual impairment. Thus, age-related functional decline may curb access to medication-related information. This finding highlights the importance of providing easily accessible medication information to elderly people. Additionally, aged community residents with poorer health have a higher motivation to receive medications and had better compliance and paid more attention to their health problems since they had a stronger desire to improve their own health. However, community residents with very poor health status have less cognitive ability and are often over the age of 75 years, so age has an effect on CRR.

Moreover, a higher level of education also exerts a significant influence on CRA and CRR. A national study in China indicated that diabetes patients with higher education have a more positive attitude towards their diabetes and tend to achieve better blood glucose control [16]. Indeed, highly educated people are generally more capable of receiving and handling knowledge [16]. Conversely, according to the investigation, patients with a lower educational background were more likely to have the misconception that hypoglycemia was not a concern for diabetic patients, which hinders the adoption and implementation of ADR prevention and drug management.

Furthermore, community residents with better educational qualifications have a better knowledge of medication use. Indeed, education plays an important role in improving appropriate CRR knowledge. In line with education, we found that professional and service provider occupations were positively correlated with appropriate CRA and CRR, and such patients were better able to manage their drugs. This might be explained by their history of communicating with medical professionals during their working lives.

Recently, there has been a steady increase in the consumption of both over-the-counter (OTC) and prescription drugs. Drugs are often stored for long periods at the community resident’s home, and leftover medication may later be used for self-medication. Moreover, the use of multiple drugs increases the risk of several drug-related problems. A recent study showed that only 7% of patients stored these drugs continuously at temperatures specified in the product label [17].

Proper storage temperatures are important because improper storage temperatures can lead to chemical instability resulting in a reduction in the effectiveness and a potential increase in adverse effects [18]. Patients are expected to store their drugs at home according to the storage conditions stated on the labels—such as in the case of drugs requiring refrigeration or storage in the original (outer) packaging to protect from moisture or light—which are provided by the drug companies in the package insert and on the drugs’ packaging. In addition to adequate storage conditions, patients should use the drug before the expiry date and keep the drug in its undamaged primary package to ensure drug quality. Furthermore, adequate storage practices also require patients to have access to drug information, by having drugs stored that are identifiable (e.g., for caregivers) and having package inserts available [1921].

Pharmacists deal with a broad variety of customers, some of whom lack awareness of potential drug interactions [22, 23] or potential side effects [24]. In addition, users of OTC drugs may confuse concepts such as “contraindications” with “side effects,” be unable to calculate simple dosages [25], or significantly overestimate the risk of side effects [26]. These errors result in PIMs or dosing of OTC drugs during hospitalizations, many of which are preventable [27]. Since OTC drugs have become commonly available, the primary way for community residents to obtain information about drugs is from the medication label, and patient compliance reportedly varies in the management of chronic diseases such as diabetes mellitus [15, 28]. Patient noncompliance with prescribed hypoglycemic medications may decrease treatment effectiveness [29, 30].

An attempt was made in this present study to measure the association of various sociodemographic factors and other patient characteristics against the compliance to medications and the reasons behind the nonadherence, as reported by the community residents. In our study, the compliance rate with drugs was found to be 54.0%. Two studies reported that compliance among diabetes patients (in all settings) in taking hypoglycemic drugs was 32.1% and 57.7%, respectively [15, 31]. However, among community residents, medication compliance rates were likely to be worse due to less advice being available from clinical pharmacists and doctors.

Some study limitations should be acknowledged. A potential source of bias is that those with less education and literacy may be less likely to participate in online surveys. However, for this hard copy questionnaire, the overall participation rate was high (). Furthermore, the study focused on adherence in general, rather than specific conditions or medications. Further larger-scale studies using a longitudinal design are warranted to provide a more accurate demonstration of the factors influencing different diseases or different kinds of drugs. Finally, the study was restricted by the survey length, which limited the researchers’ ability to explore specific disorders and identify each resident’s health status in more detail. Although the results are representative only of Jilin Province in China, the study was highly consistent with other studies and thus may indirectly contribute to our general understanding of CRA, CRR, and CRC.

5. Conclusions

In conclusion, this study identified many inappropriate practices among community residents that could contribute to the improper use of medications. As community pharmaceutical care is a critical part of the community health service that can provide medicine in a safe, reasonable, and effective way, it should be customized to specific groups such as males, elderly people, and individuals with low education levels and less professional training. Large multicenter studies are required to explore the cost-effectiveness of community pharmacy services and the impact of these services on CRA, CRR, and CRC of medications.

Abbreviations

CRA:Community residents’ administration of medicine
CRR:Community residents’ recognition of medicines
CRC:Community residents’ medication compliance
:Chi-squared.

Data Availability

The datasets generated and analyzed during the present study are available from the corresponding author on reasonable request.

Ethical Approval

This study was approved by the Ethics Committee of Jilin University.

Conflicts of Interest

The authors declare that they have no competing interests.

Acknowledgments

The authors are grateful to the study participants.

References

  1. World Health Organization, “Essential medicines and health products. Pharmacovigilance,” 2016, March 2016, http://www.who.int/medicines/areas/quality_safety/safety_efficacy/pharmvigi/en/. View at: Google Scholar
  2. J. C. Bouvy, M. L. De Bruin, and M. A. Koopmanschap, “Epidemiology of adverse drug reactions in Europe: a review of recent observational studies,” Drug safety, vol. 38, no. 5, pp. 437–453, 2015. View at: Publisher Site | Google Scholar
  3. M. J. Alomar, “Factors affecting the development of adverse drug reactions (review article),” Saudi Pharmaceutical Journal, vol. 22, no. 2, pp. 83–94, 2014. View at: Publisher Site | Google Scholar
  4. M. H. Beers, J. G. Ouslander, I. Rollingher, D. B. Reuben, J. Brooks, and J. C. Beck, “Explicit criteria for determining inappropriate medication use in nursing home residents. UCLA Division of Geriatric Medicine,” Archives of Internal Medicine, vol. 151, no. 9, pp. 1825–1832, 1991. View at: Publisher Site | Google Scholar
  5. J. M. Rothschild, W. Churchill, A. Erickson et al., “Medication errors recovered by emergency department pharmacists,” Annals of Emergency Medicine, vol. 55, no. 6, pp. 513–521, 2010. View at: Publisher Site | Google Scholar
  6. J. K. Wang, N. S. Herzog, R. Kaushal, C. Park, C. Mochizuki, and S. R. Weingarten, “Prevention of pediatric medication errors by hospital pharmacists and the potential benefit of computerized physician order entry,” Pediatrics, vol. 119, no. 1, pp. e77–e85, 2007. View at: Publisher Site | Google Scholar
  7. H. M. Vasileff, L. E. Whitten, J. A. Pink, S. J. Goldsworthy, and M. T. Angley, “The effect on medication errors of pharmacists charting medication in an emergency department,” Pharmacy world & science : PWS, vol. 31, no. 3, pp. 373–379, 2009. View at: Publisher Site | Google Scholar
  8. P. A. Gheewala, G. M. Peterson, C. M. Curtain, P. S. Nishtala, P. J. Hannan, and R. L. Castelino, “Impact of the pharmacist medication review services on drug-related problems and potentially inappropriate prescribing of renally cleared medications in residents of aged care facilities,” Drugs & Aging, vol. 31, no. 11, pp. 825–835, 2014. View at: Publisher Site | Google Scholar
  9. S. D. Williams, D. L. Phipps, and D. M. Ashcroft, “Understanding the attitudes of hospital pharmacists to reporting medication incidents: a qualitative study,” Research in social & administrative pharmacy : RSAP, vol. 9, no. 1, pp. 80–89, 2013. View at: Publisher Site | Google Scholar
  10. A. B. Pai, A. Boyd, J. Depczynski, I. M. Chavez, N. Khan, and H. Manley, “Reduced drug use and hospitalization rates in patients undergoing hemodialysis who received pharmaceutical care: a 2-year, randomized, controlled study,” Pharmacotherapy, vol. 29, no. 12, pp. 1433–1440, 2009. View at: Publisher Site | Google Scholar
  11. S. Phansalkar, J. M. Hoffman, J. F. Hurdle, and V. L. Patel, “Understanding pharmacist decision making for adverse drug event (ADE) detection,” Journal of Evaluation in Clinical Practice, vol. 15, no. 2, pp. 266–275, 2009. View at: Publisher Site | Google Scholar
  12. C. F. Green, D. R. Mottram, P. H. Rowe, and M. Pirmohamed, “Attitudes and knowledge of hospital pharmacists to adverse drug reaction reporting,” British Journal of Clinical Pharmacology, vol. 51, no. 1, pp. 81–86, 2001. View at: Publisher Site | Google Scholar
  13. J. Okumura, S. Wakai, and T. Umenai, “Drug utilisation and self-medication in rural communities in Vietnam,” Social Science & Medicine, vol. 54, no. 12, pp. 1875–1886, 2002. View at: Publisher Site | Google Scholar
  14. D. A. Petrovici and C. Ritson, “Factors influencing consumer dietary health preventative behaviours,” BMC Public Health, vol. 6, no. 1, p. 222, 2006. View at: Publisher Site | Google Scholar
  15. S. Mukherjee, B. Sharmasarkar, K. K. Das, A. Bhattacharyya, and A. Deb, “Compliance to anti-diabetic drugs: observations from the diabetic clinic of a medical college in Kolkata, India,” Journal of clinical and diagnostic research : JCDR, vol. 7, no. 4, pp. 661–665, 2013. View at: Publisher Site | Google Scholar
  16. WHO, “Definition, diagnosis and classifications of diabetes mellitus and its complications,” Report of a WHO consultation, Part 1: Diagnosis and classification of diabetes mellitus, World Health Organization, Geneva, 1999. View at: Google Scholar
  17. N. D. Vlieland, H. Gardarsdottir, M. L. Bouvy, T. C. Egberts, and B. J. van den Bemt, “The majority of patients do not store their biologic disease-modifying antirheumatic drugs within the recommended temperature range,” Rheumatology, vol. 55, no. 4, pp. 704–709, 2016. View at: Publisher Site | Google Scholar
  18. M. E. Deutsch, “Keeping drugs at the proper temperature,” Science, vol. 305, no. 5683, p. 478, 2004. View at: Publisher Site | Google Scholar
  19. S. L. Maddigan, K. B. Farris, N. Keating, C. A. Wiens, and J. A. Johnson, “Predictors of older adults’ capacity for medication management in a self-medication Program,” Journal of Aging and Health, vol. 15, no. 2, pp. 332–352, 2016. View at: Publisher Site | Google Scholar
  20. C. G. M. Sino, M. Sietzema, T. C. G. Egberts, and M. J. Schuurmans, “Medication management capacity in relation to cognition and self-management skills in older people on polypharmacy,” The journal of Nutrition, Health & Aging, vol. 18, no. 1, pp. 44–49, 2014. View at: Publisher Site | Google Scholar
  21. K. Notenboom, E. Beers, D. A. van Riet-Nales et al., “Practical problems with medication use that older people experience: a qualitative study,” Journal of the American Geriatrics Society, vol. 62, no. 12, pp. 2339–2344, 2014. View at: Publisher Site | Google Scholar
  22. J. Indermitte, D. Reber, M. Beutler, R. Bruppacher, and K. E. Hersberger, “Prevalence and patient awareness of selected potential drug interactions with self-medication,” Journal of Clinical Pharmacy and Therapeutics, vol. 32, no. 2, pp. 149–159, 2007. View at: Publisher Site | Google Scholar
  23. S. N. T. Ngo, I. Stupans, W. S. Leong, and M. Osman, “Appropriate use of non-prescription ibuprofen: a survey of patients’ perceptions and understanding,” The International Journal of Pharmacy Practice, vol. 18, no. 1, pp. 63–65, 2010. View at: Publisher Site | Google Scholar
  24. C. M. Wilcox, B. Cryer, and G. Triadafilopoulos, “Patterns of use and public perception of over-the-counter pain relievers: focus on nonsteroidal antiinflammatory drugs,” The Journal of Rheumatology, vol. 32, no. 11, pp. 2218–2224, 2005. View at: Google Scholar
  25. A. Calamusa, A. Di Marzio, R. Cristofani et al., “Factors that influence Italian consumers' understanding of over-the-counter medicines and risk perception,” Patient Education and Counseling, vol. 87, no. 3, pp. 395–401, 2012. View at: Publisher Site | Google Scholar
  26. D. Berry, T. Raynor, P. Knapp, and E. Bersellini, “Over the counter medicines and the need for immediate action: a further evaluation of European Commission recommended wordings for communicating risk,” Patient Education and Counseling, vol. 53, no. 2, pp. 129–134, 2004. View at: Publisher Site | Google Scholar
  27. C. S. van der Hooft, J. P. Dieleman, C. Siemes et al., “Adverse drug reaction-related hospitalisations: a population-based cohort study,” Pharmacoepidemiology and Drug Safety, vol. 17, no. 4, pp. 365–371, 2008. View at: Publisher Site | Google Scholar
  28. J. A. Cramer, “A systematic review of adherence with medications for diabetes,” Diabetes Care, vol. 27, no. 5, pp. 1218–1224, 2004. View at: Publisher Site | Google Scholar
  29. J. M. Schectman, M. M. Nadkarni, and J. D. Voss, “The association between diabetes metabolic control and drug adherence in an indigent population,” Diabetes Care, vol. 25, no. 6, pp. 1015–1021, 2002. View at: Publisher Site | Google Scholar
  30. K. Krapek, K. King, S. S. Warren et al., “Medication adherence and associated hemoglobin A1c in type 2 diabetes,” The Annals of Pharmacotherapy, vol. 38, no. 9, pp. 1357–1362, 2004. View at: Publisher Site | Google Scholar
  31. A. R. Khan, Z. N. Al-Abdul Lateef, M. A. Al Aithan, M. A. Bu-Khamseen, I. Al Ibrahim, and S. A. Khan, “Factors contributing to non-compliance among diabetics attending primary health centers in the Al Hasa district of Saudi Arabia,” Journal of Family & Community Medicine, vol. 19, no. 1, pp. 26–32, 2012. View at: Publisher Site | Google Scholar

Copyright © 2020 Yan-Qing Song et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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