Research Article

Prevalence of and Factors Associated with Self-Medication among Health Professionals at Cape Coast Teaching Hospital, Ghana

by Shadrack Frimpong Adu1, Wook Jang2, Jaeyong Shin3*, Junghyun Kim4*

1Department of Human Resource, Cape Coast Teaching Hospital, Cape Coast, Republic of Ghana

2Department of Health Law and Ethics, Graduate School of Public Health, Yonsei University, Seoul, 03722, Republic of Korea

3Department of Preventive Medicine, Yonsei University, Seoul, 03722, Republic of Korea, Korea

4Department of Preventive Medicine, College of Medicine, Yonsei University, Seoul 03722, Republic of Korea, Korea

*Corresponding author: Jaeyong Shin, Department of Preventive Medicine, Yonsei University, Seoul, 03722, Republic of Korea, Korea and Junghyun Kim, Department of Preventive Medicine, College of Medicine, Yonsei University, Seoul 03722, Republic of Korea, Korea

Received Date: 23 May 2023

Accepted Date: 27 May 2023

Published Date: 30 May 2023

Citation: Adu SF, Jang W, Shin J, Kim J (2023) Prevalence of and Factors Associated with Self-Medication among Health Professionals at Cape Coast Teaching Hospital, Ghana. Ann Case Report. 8: 1325. https://doi.org/10.29011/2574-7754.101325

Abstract

Background: Irrational use of medication can put the lives of the people who engage in self-medication and those around them in danger. Among health professionals, it can also put their patients and the community in danger. Self-medication is a health concern in many developing countries including Ghana.

Study objective: This study examined the prevalence of and factors associated with self-medication among health professionals at Cape Coast Teaching Hospital, Ghana.

Methods: A cross-sectional study design was used to collect quantitative data at Cape Coast Teaching Hospital. Using proportionate sampling, 346 respondents were selected to take an online survey using a structured questionnaire. The data collected were analysed using frequencies, chi-squared tests, and multiple logistic regression with Jamovi version 2.2.5.

Results: The prevalence of self-medication was 81% among participants. The odds of self-medicating were higher for participants with mild, moderate, or severe perceived health needs compared to their colleagues with good health (OR = 12.07, 95% CI, 4.789 – 30.42; OR = 5.38, 95% CI, 2.372 – 12.22; OR = 2.86, 95% CI, 1.062 – 7.71, respectively). Educational level, job categorization, income, and health insurance status were not significantly associated with self-medication among participants.

Conclusion: Self-medication is commonly practiced among hospital staff. Drugs sold over the counter in pharmacies and other retail drug outlets must be regulated to reduce access to medication without a prescription. Further studies should be conducted to identify system gaps, such as policies that enable self-medication in Ghana.

Keywords: Self-Medication; Health Professionals; Hospital

Introduction

Self-medication, if practiced rationally, allows people to manage minor ailments on their own and access drugs without obtaining a prescription from or visiting a health professional. This saves time used in visiting health facilities when people experience minor ailments and enables health professionals to focus on more severe issues [1]. Self-medication is the act of treating oneself with medication or other remedies without the guidance or prescription of a healthcare professional. This can involve using over-thecounter drugs, herbal supplements, or prescription medications obtained without a doctor’s approval or supervision [2]. This can involve purchasing over-the-counter drugs, herbal supplements, or other treatments, or using prescription medications obtained from sources other than a doctor or pharmacist. Self-medication is part of the concept of self-care, along with non-drug selftreatment, social support in illness, and first aid in everyday life. Self-medication allows individuals to play an active role in the management of their own health [2]. Although the practice enables people to be involved in their own healthcare and provides relief from minor symptoms or conditions, for it to be practiced safely, people must be able to accurately recognize symptoms, choose the most appropriate medications, and determine the appropriate dosage and dosage schedule, all while considering their medical history, contraindications, and possible side effects of the drugs [2,3]. If appropriately practiced, self-medication has the potential to reduce national healthcare expenditure and help reduce the costs of community-funded healthcare programs. Individuals are afforded convenience to attend to their own health concerns and have the opportunity to be educated on certain health issues. However, this may create the misconception that there is a drug treatment available for every health condition [4]. Additionally, relying solely on self-medication may lead individuals to delay seeking care from healthcare professionals, as they might falsely believe they have enough knowledge to treat their condition on their own. It is important to recognize the limitations of self-medication and to seek appropriate medical guidance when necessary. Globally, the prevalence of self-medication ranges between 11.2–93.7%, depending on the target population and country [5]. In developing countries, most people treat themselves by self-medicating. The prevalence of self-medication in developing countries ranges between 12.7–95%, which raises concerns regarding irrational use of medicines. Most medicines are dispensed in these countries without medical prescription or proper monitoring (up to 80% of all drugs purchased), and this is attributed to shortages of available healthcare services or healthcare services with trained healthcare workers being somewhat expensive [6,7]. Ghana faces several challenges with its healthcare system that affect the access to and quality of the healthcare services delivered. The country’s National Health Insurance Scheme (NHIS) only financially protects 35% of the country’s population. Thus, healthcare costs remain high and are considered to be out of the financial reach of most Ghanaians. Out-of-pocket expenditure also remains high (53% in 2018) and can force people into poverty [8]. According to Agblevor, Missodey [9], consumers directly demand 82.5% of the drugs bought in urban chemical shops in Ghana. In rural areas, 78% of the drugs bought are directly demanded while only 1.5% are purchased using a prescription. The potential risks of self-medication include incorrect self-diagnosis, delays in seeking medical advice when needed, infrequent but severe adverse reactions, dangerous drug interactions, incorrect manner of administration, incorrect dosage, incorrect choice of therapy, masking of a severe disease, and risk of dependence and abuse [10]. Among health professionals, inappropriate self-medication can have effect on efficiency and productivity. It may risk the lives of not only those practicing but also those around them [11]. For health professionals, this will also put the lives of the patients they manage at risk. Limited literature on the prevalence and practice of self-medication among health professionals makes it difficult to determine what factors are associated with the practice of self-medication among health professionals. Therefore, this study aimed to determine the prevalence of and factors associated with self-medication among health professionals at Cape Coast Teaching Hospital, Ghana, and help policymakers control self-medication in Ghanaian hospitals by facilitating informed decision-making.

Methods and Materials

The cross-sectional study was conducted among the staff of Cape Coast Teaching Hospital, Ghana from September 2022 to October 2022. The data was collected through an online survey. Proportionate sampling was used, and the sample size of 346 staff was determined using Cochran’s formula (n = (Z2 P(1-P))/d2). Participation in the study was voluntary and anonymous, and the data obtained is kept confidential. The study was reviewed and approved by the Ethical Review Committee of the Cape Coast Teaching Hospital, Ghana. The questionnaire used in this study was adapted from previous studies on the prevalence and determinants of self-medication practice among selected households in Addis Ababa [7]. The questions were further reviewed and refined by experts in the medical and pharmacy professions to ensure accuracy and appropriateness for this study. The questionnaire encompassed information regarding the respondent’s educational level, job category, monthly income, health insurance status, and perceived severity of the condition for which they self-medicated. Covariates such as age, gender, religion, place of residence, and marital status, which are known risk factors for self-medication, were also included. The collected data was analysed using Jamovi version 2.2.5. The collected data was analysed and summarized using descriptive and inferential statistics. The results were presented in tables, and graphs. Multivariable logistic regression analyses were used to determine factors that influence self-medication. Associations were considered significant when the p-value was less than 0.05. In this study, self-medication was defined as the act of choosing and using medications or drugs alleged to treat, manage, and/or prevent a disease or health condition without a doctor’s prescription. The recall period used in the study was one year prior to the study. 

Results

Sociodemographic characteristics of the participants

Out of the initial 346 participants, 277 responded to the study. After data cleaning, 271 participants remained for analysis. Table 1 provides an overview of the sociodemographic characteristics of the study’s participants. Among the 271 participants, 53.9% were between the ages of 30 and 39, 37.3% were below 30 years old, and 8.8% were 40 years old and above. In terms of gender, 61.6% of the participants were female and 38.4% were male. In terms of educational level, 46.5% of the participants had a Bachelor’s degree, 38% had a diploma-level tertiary education, and 1.5% had a basic-level education (primary to secondary/high school). With regard to marital status, 56.5% of the participants were single, 42.8% were married, and 0.70% were in other forms of relationships. The majority of participants (91.1%) were Christians, while 6.3% identified as Muslims, and 2.6% belonged to other religions. In relation to residence, 75.6% of the participants lived within a 10-minute drive away from the hospital, while 12.9% lived further away. Among the participants, nurses and midwives accounted for 49.8% of the sample, administrative staff comprised 24%, and medical doctors made up 11.1%. In terms of work experience, 59% of the participants had 5 years or less of experience, while 10.3% had more than 10 years of experience. Concerning monthly income, 67.5% earned between 2000–3999 cedis ($169.84-$339.59), 18.8% earned below 2000 cedis ($169.84), and 13.7% earned 4000 cedis or above (>$339.67). Over half of the participants (56.8%) had 1 to 3 dependents, while 16.2% had no dependents. In terms of annual healthcare expenditure, 33.6% spent between 100–499 cedis, while 17.3% spent 2000 cedis or above (≥ $169.84). The majority of participants (91.9%) had an active NHIS subscription, and 22.5% had additional medical coverage in addition to the NHIS.

Variable

N

% of Total

Age group

   

< 30 years

101

37.3 %

30–39 years

146

53.9 %

40–49 years

19

7.0 %

≥ 50 years

5

1.8 %

Gender

   

Male

104

38.4 %

Female

167

61.6 %

Educational Level

   

Basic education

4

1.5 %

Certificate

13

4.8 %

Diploma

103

38.0 %

Degree

126

46.5 %

Master’s, equivalent and/or above

25

9.2 %

Marital Status

   

Single

153

56.5 %

Married

116

42.8 %

Other

2

0.70%

Religion

   

Islam

17

6.3 %

Christianity

247

91.1 %

Other

7

2.6 %

Location (proximity from the hospital)

   

≤10 minutes away from hospital

205

75.6 %

>10 minutes away from the hospital

35

12.9 %

Unknown

31

11.4 %

Occupation

   

Administrative staff

65

24.0 %

Medical doctors

30

11.1 %

Nurses/midwives

135

49.8 %

Other clinical staff

41

15.1 %

Years of Work Experience

   

≤ 5 years

160

59.0 %

6–10 years

66

24.4 %

> 10 years

28

10.3 %

Unknown

17

6.3 %

Income (per month)

   

< 2000 cedis

51

18.8 %

2000–3999 cedis

183

67.5 %

≥ 4000 cedis

37

13.7 %

Number of Dependents

   

None

44

16.2 %

1–3

154

56.8 %

≥ 4

73

26.9 %

Health Expenditure (per year)

   

< 100 cedis

50

18.5 %

100–499 cedis

91

33.6 %

500–999 cedis

52

19.2 %

1000–1999 cedis

31

11.4 %

≥ 2000 cedis

47

17.3 %

Active NHIS

   

No

22

8.1 %

Yes

249

91.9 %

Medical coverage besides NHIS

   

No

210

77.5 %

Yes

61

22.5 %

Table 1: Sociodemographic characteristics of the participants.

Prevalence of self-medication

Figure 1 illustrates the self-medication behaviour among the participants. According to Figure 1, out of the total participants, 219 (81%) had engaged in self-medication within the 12 months preceding the study. Among those who self-medicated (219 participants), 160 (73.1%) did so one to three times during that period, while 13 (5.9%) self-medicated 10 times or more. Among the participants who self-medicated, 120 (54.8%) self-medicated due to their familiarity with the disease and drug used, 34 (15.5%) cited emergency reasons, and 23 (10.5%) mentioned poor services offered at the hospital as their motivation. Only 0.9% of participants reported self-medicating because they were too far from the hospital. Additionally, 94 (42.9%) of the participants obtained information for medication from health professionals, 60 (27.4%) used prescriptions from previous treatments, and 49 (22.4%) relied on their own expertise to self-medicate. The majority of  participants (205, 93.6%) obtained their medication from pharmacies or drug stores.

 

Figure 1: Showing self-medication behaviour among participants in the past 12 months. [ ] represents variables.

Differences in self-medication practice among participants according to predisposing, enabling, and health need factors

Table 2 displays the differences in self-medication practice based on predisposing, enabling, and health need factors among participants. The prevalence rate of self-medication among participants was 81%. In terms of predisposing factors, educational level and occupation did not show significant association with self-medication prevalence (p-values = 0.835 and 0.409, respectively). The practice of self-medication was higher among participants with Masters’ degrees (84%) and lowest among participants with a diplomalevel education (69.2%). The prevalence was 83.7% among nurses and midwives, 83.3% among medical doctors, and 73.8% among administrative staff. With regards to enabling factors, participants’ income and health insurance status did not exhibit significant association with self-medication prevalence (p-values = 0.138 and 0.315, respectively). The prevalence of self-medication was 89.2% among staff who earned 4000 cedis and above per month, and 72.5% among staff who earned below 2000 cedis per month. Regarding health need factors, participants’ perceived health and severity of health needs were significantly associated with self-medication practice (p-value < 0.001 for each). The prevalence of self-medication was higher among participants with health needs (88.3%) compared to those with no health needs (53.4%), and higher among participants who perceived their health needs to be mild (93.3%) compared to the other groups. The prevalence was 76.7% among participants who perceived their health needs to be severe and 53.4% for participants who perceived their overall health to be good. Religion and perceived safety were also significantly associated with self-medication among the participants (p-value = 0.029 and < 0.001, respectively).

Self-medication practice

Variable

No

Yes

p-value

n

%

n

%

Educational level

       

0.835

Basic education

1

25.0 %

3

75.0 %

 

Certificate

4

30.8 %

9

69.2 %

 

Diploma

20

19.4 %

83

80.6 %

 

Degree

23

18.3 %

103

81.7 %

 

Master’s, equivalent or above

4

16.0 %

21

84.0 %

 

Occupation

       

0.409

Administrative staff

17

26.2 %

48

73.8 %

 

Other clinical staff

8

19.5 %

33

80.5 %

 

Medical doctors

5

16.7 %

25

83.3 %

 

Nurses and midwives

22

16.3 %

113

83.7 %

 

Income (per month)

       

0.138

< 2000 cedis

14

27.5 %

37

72.5 %

 

2000–3999 cedis

34

18.6 %

149

81.4 %

 

≥ 4000 cedis

4

10.8 %

33

89.2 %

 

NHIS

       

0.315

No

6

27.3 %

16

72.7 %

 

Yes

46

18.5 %

203

81.5 %

 

Health need

       

<0.001

No

27

46.6 %

31

53.4 %

 

Yes

25

11.7 %

188

88.3 %

 

Perceived severity of health need

       

<0.001

Good

27

46.6 %

31

53.4 %

 

Mild

7

6.7 %

97

93.3 %

 

Moderate

11

13.9 %

68

86.1 %

 

Severe

7

23.3 %

23

76.7 %

 

Age group

       

0.949

< 30 years

21

20.8 %

80

79.2 %

 

30–39 years

27

18.5 %

119

81.5 %

 

40–49 years

3

15.8 %

16

84.2 %

 

≥ 50 years

1

20.0 %

4

80.0 %

 

Gender

       

0.334

Male

23

22.1 %

81

77.9 %

 

Female

29

17.4 %

138

82.6 %

 

Religion

       

0.029

Islam

7

41.2 %

10

58.8 %

 

Christianity

45

18.2 %

202

81.8 %

 

Other

0

0.0 %

7

100.0 %

 

Location

       

0.15

≤ 10 minutes away from the hospital

34

16.6 %

171

83.4 %

 

> 10 minutes away from the hospital

9

25.7 %

26

74.3 %

 

Unknown

9

29.0 %

22

71.0 %

 

Years of work experience

       

0.529

≤ 5 years

34

21.3 %

126

78.8 %

 

6–10 years

11

16.7 %

55

83.3 %

 

> 10 years

3

10.7 %

25

89.3 %

 

Unknown

4

23.5 %

13

76.5 %

 

Number of dependents

       

0.796

None

10

22.7 %

34

77.3 %

 

1–3

28

18.2 %

126

81.8 %

 

≥ 4

14

19.2 %

59

80.8 %

 

Health expenditure (per year)

       

0.984

<100 cedis

9

18.0 %

41

82.0 %

 

100–499 cedis

18

19.8 %

73

80.2 %

 

500–999 cedis

10

19.2 %

42

80.8 %

 

1000–1999 cedis

5

16.1 %

26

83.9 %

 

≥ 2000 cedis

10

21.3 %

37

78.7 %

 

Medical coverage besides NHIS

         

No

43

20.5 %

167

79.5 %

0.318

Yes

9

14.8 %

52

85.2 %

 

Safety of self-medication practice

       

<0.001

Very safe

3

15.0 %

17

85.0 %

 

Safe

3

8.6 %

32

91.4 %

 

Moderate

12

12.5 %

84

87.5 %

 

Harmful

19

26.8 %

52

73.2 %

 

Very harmful

8

21.1 %

30

78.9 %

 

Unknown

7

63.6 %

4

36.4 %

Table 2: Differences in self-medication practice according to predisposing, enabling, and health need factors.

Factors influencing self-medication among participants

Table 3 presents the factors that influence self-medication among participants. In the bivariate logistic regression analysis, only the perceived severity of health need was found to significantly influence self-medication among health professionals. The odds of selfmedicating were higher for participants with mild, moderate, and severe health needs compared with those in good health (OR = 12.07, 95% CI, 4.79 – 30.42; OR = 5.38, 95% CI, 2.37 – 12.22; OR = 2.86, 95% CI, 1.06 – 7.71, respectively). When adjusted for covariates, the odds were even higher among participants with mild, moderate, and severe health needs compared with those in good health (aOR = 18.68, 95% CI, 5.76 – 60.62; aOR = 10.35, 95% CI, 3.36 – 31.88; aOR = 4.91, 95% CI, 1.28 – 18.83, respectively).

95% Confidence interval

95% Confidence interval

Variable

Crude odds ratio

Lower

Upper

p-value

Adjusted odds ratio

Lower

Upper

p-value

Educational level

               

Basic education

1

     

1

     

Certificate

0.75

0.06

9.62

0.83

0.58

0.02

14.97

0.74

Diploma

1.38

0.14

14.01

0.78

2.62

0.11

62.20

0.55

Degree

1.49

0.15

15.01

0.73

3.08

0.13

72.43

0.48

Master’s

1.75

0.14

21.38

0.66

1.91

0.07

55.77

0.71

Occupation

               

Administrative staff

1

     

1

     

Other clinical staff

1.46

0.57

3.78

0.43

0.98

0.26

3.68

0.97

Medical doctors

1.77

0.59

5.36

0.31

0.00

0

-

0.99

Nurses and midwives

1.82

0.89

3.73

0.10

1.45

0.49

4.33

0.50

Income (per month)

               

< 2000 cedis

1

     

1

     

2000–3999 cedis

1.66

0.81

3.4

0.17

0.95

0.28

3.23

0.93

≥ 4000 cedis

3.12

0.93

10.43

0.06

0.00

0

-

0.99

NHIS

               

No

1

     

1

     

Yes

1.65

0.61

4.46

0.32

2.99

0.68

13.25

0.15

Perceived severity of health need

               

Good health

1

     

1

     

Mild

12.07

4.79

30.42

< .001

18.68

5.76

60.62

< .001

Moderate

5.38

2.37

12.22

< .001

10.35

3.36

31.88

< .001

Severe

2.86

1.06

7.71

0.038

4.91

1.28

18.83

0.02

Age group

               

< 30 years

1

     

1

     

30–39 years

1.16

0.61

2.19

0.65

1.73

0.62

4.85

0.29

40–49 years

1.4

0.37

5.26

0.62

1.44

0.16

13.05

0.75

≥ 50 years

1.05

0.11

9.9

0.97

0.13

0.003

4.503

0.26

Gender

               

Male

1

     

1

     

Female

1.35

0.73

2.49

0.34

1.85

0.74

4.64

0.19

Religion

               

Islam

1

     

1

     

Christianity

3.14

1.14

8.7

0.028

2.31

0.56

9.49

0.25

Others

0.00

0

-

0.99

0.00

0

-

0.99

Location

               

≤ 10 minutes away from the hospital

1

     

1

     

> 10 minutes away from the hospital

0.57

0.25

1.33

0.197

0.66

0.22

1.99

0.46

Unknown

0.49

0.21

1.15

0.099

0.41

0.12

1.38

0.15

Years of work experience

               

≤ 5 years

1

     

1

     

6–10 years

1.35

0.64

2.86

0.43

1.2

0.38

3.77

0.76

> 10 years

2.25

0.64

7.9

0.21

1.45

0.13

16.32

0.76

Unknown

0.88

0.27

2.86

0.83

0.75

0.14

3.87

0.73

Number of dependents

               

None

1

     

1

     

1–3

1.32

0.59

2.99

0.5

1.00

0.32

3.13

0.99

≥ 4

1.24

0.5

3.09

0.65

1.09

0.28

4.21

0.90

Health expenditure (per year)

               

< 100 cedis

1

     

1

     

100–499 cedis

0.89

0.37

2.16

0.8

0.40

0.12

1.4

0.15

500–999 cedis

0.92

0.34

2.5

0.87

0.68

0.19

2.48

0.56

1000–1999 cedis

1.14

0.34

3.78

0.83

1.05

0.18

6.18

0.96

≥ 2000 cedis

0.81

0.3

2.22

0.69

0.48

0.12

1.97

0.31

Safety of self-medication practice

               

Very safe

1

     

1

     

Safe

2.07

0.54

7.87

0.29

2.25

0.26

19.46

0.46

Moderate

3.9

1.07

14.22

0.04

0.96

0.17

5.31

0.96

Harmful

2.56

1.15

5.7

0.02

0.38

0.07

2.01

0.26

Very harmful

1.37

0.54

3.51

0.51

0.64

0.10

3.95

0.63

Unknown

0.21

0.05

0.79

0.02

0.08

0.01

0.73

0.025

Table 3: Factors influencing self-medication among participants.

Discussion

This study was conducted to examine the prevalence of and factors associated with self-medication among staff at the Cape Coast Teaching Hospital, Ghana. The prevalence was 81% among the hospital staff, which is similar to other studies conducted in similar settings [12,13]. The disparity in prevalence rates can be attributed to the operational definition of self-medication and recall period used in each study. Findings from this study also showed that most participants (93.6%) obtained their medication from pharmacies or drug stores. This is similar to the findings of studies conducted in South India and Maputo City, Mozambique [14,15]. The lack of strict policies on drug acquisition and use without a prescription in developing countries [16] may enable people, especially health professionals, to easily access and use certain medications without prescription. Education, occupation, income and health insurance showed no significant association with self-medication practice among health professionals in this study. This finding is contrary to findings from other studies [7,17- 21]. The majority of the participants in this study (98.5%) had a tertiary level of education owing to Cape Coast Teaching Hospital being a tertiary hospital. This high educational level among the participants may be the reason for the lack of a significant association between educational level and self-medication. However, the odds of self-medicating were 1.38, 1.49, and 1.75 times higher for participants with a diploma, bachelor’s, and master’s level of education, respectively, compared to participants with basic education, although the association was not significant. Chindhalore, Dakhale and Giradkar [20] found a higher prevalence of self-medication among medical students compared to paramedical students (p-value = 0.019) in a tertiary care teaching institute in India. In this study, nurses and midwives, medical doctors, and other clinical staff were more likely to self-medicate compared to administrative staff, although the association was not significant (OR = 1.82, 95% CI, 0.89 – 3.73; OR = 1.77, 95% CI, 0.59 – 5.36; OR = 1.46, 95% CI, 0.57 – 3.78, respectively). As determined in previous studies, people with a tertiary-level education are more likely to self-medicate. Therefore, the lack of a significant association in the practice of self-medication among the participants in this study, despite the majority having a tertiarylevel education, is notable. Additionally, participants who had active NHIS memberships in this study were more likely to selfmedicate than those who did not (OR = 1.65, 95% CI, 0.61 – 4.46). This finding aligns with those from another study conducted in Ghana. [22]. People self-medicate in Ghana because of the lower costs of drugs in open markets, pharmacies, and chemical shops. Participants’ perceived health needs and health need severity were found to be significantly associated with self-medication practice in this study (p < 0.001 for each). The odds of self-medicating were higher among participants with mild, moderate, or severe health needs, compared with participants who had no health needs (OR = 12.07, 95% CI, 4.79 – 30.42; OR = 5.38, 95% CI, 2.37 – 12.22 and OR = 2.86, 95% CI, 1.06 – 7.71, respectively). When adjusted for covariates, the odds ratio was 18.68, 10.35, and 4.91, respectively, compared with those for participants with no health needs. Although other studies [19,23,24] failed to determine the association between perceived health needs and self-medication, they were able to reveal that participants self-medicated because of the nature of their illness. The government and other stakeholders must consider the regulation of the sale of drugs used for selfmedication, especially antibiotics, in pharmacies and other retail drug outlets to reduce access to such medications without a prescription [25]. Changing the status of some of these drugs from OTC to prescription medication and controlling access to them can limit easy access to these medication without a prescription and encourage people to utilize health facilities. Introducing other financial incentives, such as coverage of medical costs by employers if a copy of a prescription is produced, could encourage staff to utilize health services [26]. Health professionals must be educated on the dangers of self-medicating, especially in relation to misdiagnosis, abuse, and addiction [1]. Educating staff on the dangers of self-medication could help them make safer choices when they have health needs. Further studies must be conducted to identify system gaps such as policies that enable self-medication in Ghana. This study only examined the contextual factors that influence self-medication among health professionals. However, other factors that were not examined in this study are equally important in influencing the practice of self-medication. These factors include the availability of policies and laws that prohibit or encourage the practice and the extent to which they have been implemented. In addition, the stakeholders involved in the practice of self-medication must be examined to determine their level of influence and the appropriate measures needed to properly address the behaviour. Implementing measures that only address the contextual factors without examining and addressing these other factors will not solve the issue.

Study limitations

This study did not examine the policies and laws in Ghana that influence self-medication among the population. The period of data collection was very limited, which likely had an effect on the study’s response rate. Cross-sectional studies are also not useful in establishing clear cause and effect relationships. Additionally, the study focused on health professionals in a teaching hospital, and as such, the sample is not representative of the general population. Although the findings are not generalizable, the study revealed an association between participants’ perceived health needs and selfmedication, which adds to the existing literature. 

Conclusion

This study showed that self-medication is a common practice among the staff at Cape Coast Teaching Hospital, Ghana. Health professionals are more likely to self-medicate when they feel mildly ill, regardless of their educational level, job categorization, income, or health insurance status. The severity of illness also affects the magnitude of self-mediation use. Health professionals primarily self-medicate due to their familiarity with the disease and drugs, emergencies, and poor services offered at the hospital. For health professionals, the perceived safety of the practice was significantly associated with self-medication. It is important to regulate drugs sold over the counter in pharmacies and other retail drug outlets to control access to medication without a prescription. Further studies should be conducted to identify system gaps, such as policies that enable self-medication in Ghana.

Funding: This research was supported by the Korea Health Industry Development Institute (KHIDI), Republic of Korea (HD22C20450012982076870002; Gachon University, 202210380002). .

Acknowledgment: We are grateful to all the participants who willingly took part in the study.

Data Availability Statement: The data are available upon reasonable request from the corresponding author.

Conflict of Interest: The authors declare no conflict of interest.

Disclosure: This article is a condensed form of the first author’s master’s degree for the Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea.

References

  1. Bennadi D (2013) Self-medication: A current challenge. J Basic Clin Pharm, 5: 19-23.
  2. World Health, O, Guidelines for the regulatory assessment of medicinal products for use in self-medication. 2000, World Health Organization: Geneva.
  3. Malik M, Tahir MJ, Jabbar R, Ahmed A, Hussain R (2020) Selfmedication during Covid-19 pandemic: challenges and opportunities. Drugs Ther Perspect, 36: 565-567.
  4. Auta A, Omle S, Folorunsho TJ, David S, Banwat SB (2012) Medicine Vendors: Self-medication Practices and Medicine Knowledge. N Am J Med Sci, 4: 24-28.
  5. Chautrakarn S, Khumros W, and Phutrakool P (2021) Self-Medication With Over-the-counter Medicines Among the Working Age Population in Metropolitan Areas of Thailand. Frontiers in Pharmacology, 12.
  6. Araia ZZ, Gebregziabher NK, and Mesfun AB (2019) Self medication practice and associated factors among students of Asmara College of Health Sciences, Eritrea: a cross sectional study. J Pharm Policy Pract, 12: 3.
  7. Shafie M, Eyasu M, Muzeyein K, Worku Y, Martin-Aragon S (2018) Prevalence and determinants of self-medication practice among selected households in Addis Ababa community. PLoS One, 13: e0194122.
  8. Akweongo P, Aikins M, Wyss K, Salari P, Tediosi F (2021) Insured clients out-of-pocket payments for health care under the national health insurance scheme in Ghana. BMC Health Services Research, 21: 440.
  9. Agblevor EA (2016) Drugstores, self-medication and public health delivery: Assessing the role of a major health actor in Ghana. L’automédication en question: Un bricolage socialement et territorialement situé [Questioning self-medication: Tinkering in the social and territorial realm], 2016: 202-209.
  10. Ruiz ME (2010) Risks of self-medication practices. Curr Drug Saf, 2010. 5: 315-323.
  11. Castillo-Martínez J, and Pérez-Acosta A (2021) Risk Behaviours and Self-medication in Active Workers. 2021: 47-54.
  12. Tobin EA (2020) Self-medication among health care workers in a tertiary hospital in Southern Nigeria: knowledge, attitude, and practices. Medical Journal of Indonesia, 29: 403-409.
  13. Fekadu G, Dugassa D, Negera GZ, Woyessa TB, Turi E, et al (2020)Self-Medication Practices and Associated Factors Among HealthCare Professionals in Selected Hospitals of Western Ethiopia. Patient Prefer Adherence, 14: 353-361.
  14. Balamurugan E, and Ganesh K (2011) Prevalence and pattern of self medication use in coastal regions of south india. British Journal of Medical Practitioners, 2011: 4.
  15. Torres NF, Solomon VP, and Middleton LE (2019) Patterns of selfmedication with antibiotics in Maputo City: a qualitative study. Antimicrob Resist Infect Control, 8: 161.
  16. Sherazi BA, Mahmood KT, Amin F, Zaka M, Riaz M, et al (2012) Prevalence and Measure of Self Medication: A Review. 4: 1774-1778.
  17. Marwa KJ, Njalika A, Ruganuza D, Katabalo D, Kamugisha E (2018) Self-medication among pregnant women attending antenatal clinic at Makongoro health centre in Mwanza, Tanzania: a challenge to health systems. BMC Pregnancy Childbirth, 18: 16.
  18. Gustafsson S, Vikman I, Savenstedt S, Martinsson J (2015) Perceptions of needs related to the practice of self-care for minor illness. J Clin Nurs, 24: 3255-3265.
  19. Soroush A, Abdi A, Andayeshgar B, Vahdat A, Khatony A (2018) Exploring the perceived factors that affect self-medication among nursing students: a qualitative study. BMC Nurs, 17: 35.
  20. Chindhalore CA, Dakhale GN, and Giradkar AB (2020) Comparison of self-medication practices with analgesics among undergraduate medical and paramedical students of a tertiary care teaching institute in Central India - A questionnaire-based study. J Educ Health Promot, 9: 309.
  21. Kifle ZD, Mekuria AB, Antenh DA, Enyew EF (2021) Self-medication Practice and Associated Factors among Private Health Sciences Students in Gondar Town, North West Ethiopia. A Cross-sectional Study. Inquiry, 58: 469580211005188.
  22. Cobbold J, Morgan AK, and Miceli NS (2022) An integrative review of the prevalence, patterns and predictors of self-medication in Ghana. Cogent Public Health, 9.
  23. Sharif (2012) Evaluation of Self-Medication among Pharmacy Students. American Journal of Pharmacology and Toxicology, 7: 135140.
  24. Almasdy D and Sharrif A (2011) Self-Medication Practice with Nonprescription Medication among University Students: A review of the literature. Arch Pharma Pract, 2: 95-100.
  25. Shrivastava, B, Bajracharya O, and Shakya R (2022) Prioritizing intervention measures to prevent inappropriate elf-medication practices using the Analytical Hierarchy Process. Exploratory Research in Clinical and Social Pharmacy, 5: 100117.
  26. DeFulio A, Silverman K (2012) The use of incentives to reinforce medication adherence. Prev Med, 55: S86-94.

© by the Authors & Gavin Publishers. This is an Open Access Journal Article Published Under Attribution-Share Alike CC BY-SA: Creative Commons Attribution-Share Alike 4.0 International License. With this license, readers can share, distribute, download, even commercially, as long as the original source is properly cited. Read More.

Annals of Case Reports

pola slot gacor zeusslot gacor mudah jackpotslot sugar rushslot mahjong thailandmahjong scatter naga hitamslot mahjong ways 2slot pg soft gacorprediksi judi bola sbobetparlay sbobet euro 2024rtp pg softbocoran rtp dan pola gacoragen bola euro terpercayatrik slot mahjong ways 2trik menaklukkan slot mahjong waysbandar bola terpercayaslot gacor gampang menangslot olympus 1000jam gacor pragmaticslot gacor mudah maxwinagen judi bola resmimahjong ways pola jitu maxwinpola gacor starlight princessslot server kambojarahasia scatter hitam mahjong waysturbo spin slot mahjongrtp slot candy villagepola gacor mahjong wins terbaruslot server luar terbarurtp slot olympusslot mahjong waysrtp sweet bonanzaagen sbobet euro 2024judi bola parlay sbobetslot gates of olympus jepe maxwinrtp slot gacorslot starlight christmas pragmatic