The Impact of Health Literacy on Medication Adherence and Acceptance in COVID-19 Patients With Home Monitoring
Abstract
Background: Health literacy plays a critical role in ensuring adequate medication adherence and acceptance, especially during pandemics like COVID-19, where misinformation is prevalent.
Objective: To evaluate the relationship between health literacy levels, medication adherence, and acceptance among COVID-19 patients managed with home-based treatment protocols.
Methods: This study was conducted through an online questionnaire with a random sampling method. Data were collected using the Identifying Characteristics Form and the Turkish Health Literacy Scale, and 279 COVID-19 patients were included in this study. Descriptive and correlation statistics were used to analyze the data.
Results: The results showed that 72.8% of the patients used drugs, and the drug use level was also high. In examining the relationship between COVID-19 drug therapy and the participants’ health literacy, the total score of the Turkish Health Literacy Scale, the Treatment and Service subscale score, and the Preventing Diseases and Promoting Health subscale score were found to be significantly higher.
Conclusion: While adequate health literacy was noted among the participants, its impact on medication acceptance was insignificant. Further research is warranted to identify additional factors influencing adherence and acceptance of treatment protocols during public health crises like COVID-19.
1. Introduction
Health literacy (HL) is the ability to access, understand, evaluate, and use information and services in ways that promote and sustain health and wellness [1]. According to the World Health Organization (WHO), HL is defined as representing the personal knowledge and competencies that accumulate through daily activities, social interactions, and across generations [1]. This concept has gained further prominence during the COVID-19 pandemic, where misinformation and disinformation have exacerbated public health challenges [2, 3].
During the COVID-19 pandemic, rapid dissemination of unverified information through digital and traditional media created significant confusion among individuals in distinguishing credible sources. For example, misleading claims about preventive measures and treatment options, such as improperly using hydroxychloroquine, have posed serious risks to public health [4]. Such challenges underscore the importance of strengthening HL to enhance public resilience and ensure informed decision-making during health crises.
Empirical evidence indicates that individuals with inadequate HL are likelier to engage in risky health behaviors, exhibit poor adherence to treatment protocols, and experience worse health outcomes [5, 6]. For instance, a recent survey in eight European countries revealed that 12.4% of participants had inadequate HL, while 35% displayed problematic levels [5]. Similarly, the Turkish Ministry of Health reported that approximately 70% of the population has limited or inadequate HL levels [7].
An individual’s level of HL is considered an important factor associated with one’s level of medication knowledge, medication adherence, health outcomes, encounters with medication errors, and premature mortality [8, 9]. Medication adherence, an essential component of effective disease management, is heavily influenced by HL. According to the results of various studies in the literature that examine the HL levels of patients, it has been shown that patients’ HL levels affect their medication use and adherence during illness [6, 10–13]. This relationship becomes particularly critical during pandemics like COVID-19, where adherence to prescribed medication regimens is vital to reducing disease severity and preventing transmission. During global health crises like COVID-19, the rapid dissemination of misinformation and misleading information can make it difficult for individuals to access reliable sources and can lead to an increase in risky health behaviors [4, 14]. Throughout this period, numerous claims have emerged regarding medications that could be used to treat COVID-19 infection. The literature indicates that during the pandemic, individuals with low HL were often not adequately informed about antibiotic resistance and usage [4].
In Turkiye, COVID-19 patients receiving home treatment were prescribed medications such as favipiravir, hydroxychloroquine Sulfate, oseltamivir, lopinavir, and azithromycin delivered directly to their homes by contact tracing teams [15]. However, the impact of HL on patients’ adherence to these medications and their acceptance of prescribed treatments still needs to be explored. However, the Ministry of Health did not disclose data on the use of drugs at home by the treatment protocol. In pandemics that affect the entire world, such as COVID-19, understanding the impact of HL on medication usage and treatment adherence is anticipated to contribute to improving future healthcare services and developing health policies. In this context, this study aims to determine the rate of correct medication usage according to the treatment protocol among COVID-19 patients and to assess the impact of HL levels on medication usage and treatment adherence.
1.1. Research Questions
- 1.
What is the rate of acceptance of drug therapy and the correct drug use by the treatment protocol in COVID-19 patients?
- 2.
What are the HL levels of COVID-19 patients?
- 3.
Is there a relationship between the HL levels of COVID-19 patients, their acceptance of drug treatment, and their proper drug use per the treatment protocol?
2. Methods
2.1. Design
The descriptive-correlational design was used in this study.
2.2. Sample
The study population consisted of individuals living in various provinces of Turkiye, who had COVID-19 infection between April 2021 and July 2021, when the data were collected, and who met the inclusion criteria and volunteered to participate in the study. The inclusion criteria of the study were to have a positive polymerase chain reaction (PCR) test maximum 15 days prior, to be over 18 years old, to spend the isolation period at home, to be able to use a smartphone, to have no barriers to participating in the research, to volunteer to participate in the research, and not to be a healthcare worker. Between the data collection dates, the researchers reached 367 patients who were recorded as positive for PCR test in the Ministry of Health COVID-19 Information System, who were not hospitalized but were treated at home, whose drugs were delivered to them by the contact tracing teams, and informed them via telephone about the study, and a total of 279 patients who agreed to participate were included in the study.
Due to the inability to collect face-to-face data during the COVID-19 pandemic, online surveys were preferred as a safe and practical method. However, limitations such as excluding individuals without internet access or lacking technological skills could impact the generalizability of research findings; nevertheless, under pandemic conditions, online surveys were the most suitable method.
2.3. Measures
The data of the study were collected by applying the Identifying Characteristics Form and the Turkish Health Literacy Scale (TSOY-32), developed by the researchers as a result of the literature review on the subject, to the patients who had COVID-19 infection with the online questionnaire technique since the patients were in quarantine.
2.3.1. Identifying Characteristics Form
The Identifying Characteristics Form consisted of 24 questions prepared by the researchers in line with the literature about the sociodemographic characteristics of the participants, their health information sources, and their use of COVID-19 drug therapy [16–19].
2.3.2. TSOY-32
The Health Literacy Scale, developed by the European Health Literacy Research Consortium, was validated by Abacıgil, Parlak, and Okyay to evaluate HL among literate individuals over the age of 15 based on the conceptual framework [19]. The scale is structured as a 2 × 4 matrix, considering two primary dimensions. Accordingly, the matrix consists of eight components: two subdimensions, Treatment and Service (TS) and Preventing Diseases and Promoting Health (PDPH), and four processes (accessing health-related information, understanding health-related information, evaluating health-related information, and using/applying health-related information) [19]. The Likert-type scale is scored as “(1) Very easy, (2) Easy, (3) Difficult, and (4) Very difficult.” When calculating the score, the codes should be recorded as 1–4 and 4–1. In order to facilitate the calculation, the total score has been standardized with the help of the “Index = (arithmetic mean − 1) × [50/3]” formula to take values between 0–50. On the scale, 0 points indicate the lowest HL and 50 points indicate the highest HL. HL level is evaluated in four categories: inadequate health literacy (0–25 points), problematic limited health literacy (> 25–33 points), adequate health literacy (> 33–42 points), and excellent health literacy (> 42–50 points). The Cronbach’s alpha value of the scale was found to be 0.93 for the total score, 0.88 for the TS subdimension, and 0.86 for the PDPH subdimension [19]. In this study, the TS and PDPH subdimensions of the scale were used. In the research sample, the total Cronbach’s alpha value of the scale was 0.96, Cronbach’s alpha value of the TS subdimension was 0.93, and Cronbach’s alpha value of the PDPH subdimension was 0.94.
2.4. Analytic Strategy
The data were analyzed using the SPSS 21.0 program (IBM Corp., Armonk, NY). Descriptive statistics (percentage, mean, standard deviation, minimum, and maximum) were used for the questionnaire and the TSOY-32. Data were tested for normality analysis with Kolmogorov–Smirnov tests. Since the data did not show normal distribution as a result of the analysis, nonparametric tests (Kruskal–Wallis and Mann–Whitney U) and Pearson correlation test were used. Significance level was calculated as p < 0.05 [21].
2.5. Ethical Issues
Ethical permission was granted by the Ethics Committee for Social and Human Sciences Research Ethics Committee of Istanbul University–Cerrahpasa (2021/27), and institutional permission was granted by the Turkish Ministry of Health COVID-19 Scientific Research Platform (2021-01-20T03_11_15). In addition, all the patients who agreed to participate in the study were asked to sign a volunteer consent form and an informed consent form, and their verbal and online written consent was obtained.
3. Results
The mean age of the individuals participating in the study was 33.67 ± 12.49 (18–80 years); 65.2% were female; 51.3% were married; and 52% had no children. A total of 38.7% of the participants stated that they had a bachelor’s degree, 32.3% of them were white-collar workers, and 88.9% of them stated that they lived with their families. A total of 63.8% of the participants stated that their health status before the diagnosis of COVID-19 was good, and 81.7% stated that they did not have any chronic diseases. In those with chronic disease, the highest rate was of cardiovascular diseases with 5.9%, diabetes mellitus with 3%, and asthma with 1.9% (Table 1).
| Variables | Categories | n | Frequency (%) |
|---|---|---|---|
| Gender | Female | 204 | 67.1 |
| Male | 100 | 32.9 | |
| Marital status | Married | 155 | 51.0 |
| Single | 145 | 47.7 | |
| Other (widowed, divorced, etc.) | 4 | 1.3 | |
| Educational status | Literate | 3 | 1.0 |
| Primary education graduate | 36 | 11.8 | |
| High school graduate | 70 | 23.0 | |
| Associate degree | 23 | 7.6 | |
| Bachelor’s degree | 119 | 39.1 | |
| Postgraduate education | 53 | 17.4 | |
| Used medication after being diagnosed with COVID-19 infection? | Yes | 223 | 73.4 |
| No | 81 | 26.6 | |
| Did you use the medications given to you by the treatment protocol? | Yes | 191 | 68.5 |
| Partially | 19 | 6.8 | |
| No | 69 | 24.7 | |
| What are your reasons for not using the drugs by the treatment protocol?∗ | I do not like to take medicine | 30 | 10.8 |
| Medicines are not helpful. | 28 | 10 | |
| Drugs are harmful | 39 | 14 | |
| I forgot to take the medicine | 7 | 2.5 | |
| Medicines make me nauseous | 4 | 1.4 | |
| A lot of medication is taken in one powder. | 24 | 8.6 | |
| I left feeling good. | 20 | 7.2 | |
| I have not used it as I am pregnant or breastfeeding. | 12 | 3.6 | |
| Which drug(s) were given to you after you were diagnosed with COVID-19?∗ | Favipiravir | 247 | 88.5 |
| Hydroxychloroquine sulfate | 45 | 16.1 | |
| Ritonavir/lopinavir | 7 | 2.5 | |
| Oseltamivir | 4 | 1.4 | |
| Azithromycin | one | 0.4 | |
| No medicine given | 9 | 3.2 | |
| Which of the given drugs did you use?∗ | Favipiravir | 200 | 71.7 |
| Hydrocycloquine sulfate | 25 | 9.0 | |
| Ritonavir/lopinavir | 4 | 1.4 | |
| Oseltamivir | 2 | 0.7 | |
| Azithromycin | 2 | 0.7 | |
| I did not use drugs | 62 | 22.2 | |
| Do you think the medications given are effective? | Yes | 178 | 58.6 |
| No | 126 | 41.4 | |
| Did you use any alternative method(s) after being diagnosed with COVID-19? | Yes | 259 | 85.2 |
| No | 45 | 14.8 | |
| Have any of your family members been infected with COVID-19? | Yes | 220 | 78.9 |
| No | 59 | 21.1 | |
| COVID-19 symptoms∗ | Fire | 126 | 45.2 |
| Cough | 141 | 50.5 | |
| Headache | 146 | 52.3 | |
| Throat ache | 113 | 40.5 | |
| Dyspnea | 73 | 26.2 | |
| Chest pain | 62 | 22.2 | |
| Sputum | 47 | 16.8 | |
| Impaired consciousness | 14 | 5.8 | |
| Muscle or joint pain | 188 | 67.4 | |
| Loss of taste and smell | 172 | 61.6 | |
| Nausea and vomiting | 65 | 23.3 | |
| Shivering | 66 | 23.7 | |
| Nasal obstruction | 66 | 23.7 | |
| Fatigue/weakness | 198 | 71 | |
| Diarrhea | 76 | 27.2 | |
- ∗More than one option checked.
While 90.7% of the participants chose health workers as the most reliable source of information, 11.5% preferred the recommendations of family members and friends as the least reliable information source.
The most common symptoms experienced by the participants after being diagnosed with COVID-19 were fatigue/weakness (71%), muscle and joint pain (67.4%), loss of taste and smell (61.6%), headache (52.3%), cough (50.5%), throat ache (40.5%), and dyspnea (26.2%) (Table 1). A total of 78.9% of them reported that at least one member of their family had a COVID-19 infection. A total of 73.4% of the participants stated that they used medication after being diagnosed with COVID-19, and 68.5% stated that they used the given drugs in accordance with the treatment protocol. A total of 4% of those who did not use the drugs in accordance with the treatment protocol think that the drugs are harmful; 10.8% stated that they did not like to use drugs; 10% stated that they did not think that drugs were beneficial; 8.6% stated that too many drugs were used in a single dose; and 67.2% stated that they did not use because they felt better (Table 1). The participants stated that the contact tracing team most frequently gave favipravir (88.5%) and hhydroxychloroquine sulfate (16.1%) after they were diagnosed with COVID-19, and among the drugs administered, they most frequently used favipravir (71.7%) and hydroxychloroquine sulfate (9%), and 22.2%. and 57.3% of them stated that they thought that the drugs given were effective (Table 1).
The mean TSOY scale total index score of the patients diagnosed with COVID-19 was 35.07 ± 10.10, the mean TS index score was 35.85 ± 10.04, and the mean PDPH score was 34.29 ± 11.23. According to the scale mean scores of the patients, their HL levels were measured as adequate. A significant negative correlation was determined between the age of the participants and the total score of the TSOY scale (r = -0.148, p = 0.010), TS (r = −0.129, p = 0.025), and PDPH (r = −0.151, p = 0.009) subdimensions. HL increases as the age of the patients decreases. HL total and subscale scores of the participants who were single were found to be significantly higher compared with those who were married (KW = 11.33, p = 0.003), HL total and subscale scores of those who had no children were found to be significantly higher compared with those who had children (Z = −2.40, p = 0.017), HL total and subscale scores of those who were students were found to be significantly higher compared with those living with their family and friends (KW = 10.58, p = 0.005), and HL total and subscale scores of those who obtained health information from the print media were found to be significantly higher (Z = −3.22, p = 0.001). In addition, it was found that the total TSOY score (KW = 11.42, p = 0.044) of those who had a high school and bachelor’s degree were significantly higher compared with primary school graduates, and the total TSOY score (KW = 9.50, p = 0.050) and the PDPH subscale score (KW = 12.56, p = 0.014) of those who had a very good health perception before COVID-19 was found to be significantly higher compared with those who had good health perceptions (Table 2). In the examination of the relationship between the COVID-19 drug therapy and HL of the participants, it was found that the TSOY scale total score (Z = −2.20, p = 0.028), the TS subscale score (Z = −2.03, p = 0.042) and the PDPH subscale score (Z = −2.20, p = 0.027) were found to be significantly higher in the patients using antibiotics of azithromycin group (Table 3).
| TS | PDPH | Total | |||||
|---|---|---|---|---|---|---|---|
| M ± SD | p | M ± SD | p | M ± SD | p | ||
| Gender∗ | Female | 34.8 ± 10.4 | 0.213 | 36.5 ± 9.5 | 0.777 | 35.6 ± 9.4 | 0.388 |
| Male | 33.7 ± 12.7 | 34.6 ± 10.9 | 34.0 ± 11.3 | ||||
| Marital status∗∗ | Married | 32.1 ± 12.0 | 0.002 | 33.9 ± 10.0 | 0.010 | 33.0 ± 10.5 | 0.003 |
| Single | 36.7 ± 9.9 | 37.8 ± 9.7 | 37.3 ± 9.3 | ||||
| Other | 32.5 ± 8.9 | 39.3 ± 6.1 | 35.9 ± 67 | ||||
| Status of having children∗ | Yes | 32.5 ± 12.2 | 0.049 | 34.6 ± 9.3 | 0.032 | 33.6 ± 10.8 | 0.025 |
| No | 35.9 ± 10.0 | 36.9 ± 9.6 | 36.4 ± 9.3 | ||||
| Educational status∗∗ | Literate | 31.0 ± 9.8 | 0.052 | 32.4 ± 10.1 | 0.056 | 31.7 ± 9.6 | 0.033 |
| Primary education graduate | 35.7 ± 10.2 | 36.6 ± 9.6 | 36.2 ± 9.2 | ||||
| High school graduate | 34.3 ± 15.0 | 36.7 ± 13.4 | 35.5 ± 13.9 | ||||
| Associate degree | 35.3 ± 11.7 | 36.9 ± 9.8 | 36.1 ± 10.2 | ||||
| Bachelor’s degree | 32.4 ± 10.2 | 34.6 ± 8.8 | 33.5 ± 8.9 | ||||
| Job∗∗ | Not working | 33.6 ± 10.1 | 0.019 | 31.5 ± 10.0 | 0.001 | 32.6 ± 9.8 | 0.003 |
| Worker | 34.9 ± 9.9 | 33.1 ± 11.4 | 34.0 ± 10.0 | ||||
| Retired | 29.9 ± 10.0 | 28.2 ± 7.7 | 29.1 ± 7.9 | ||||
| Student | 38.3 ± 8.5 | 38.9 ± 8.2 | 35.7 ± 7.8 | ||||
| Office worker | 36.9 ± 10.6 | 34.6 ± 15.5 | 35.1 ± 11.1 | ||||
| Who do you live with at home?∗∗ | Alone | 41.8 ± 10.9 | 0.025 | 39.1 ± 10.8 | 0.049 | 40.4 ± 10.7 | 0.029 |
| With her/his friend | 31.1 ± 10.3 | 30.5 ± 8.2 | 30.8 ± 8.7 | ||||
| With her/his family | 35.5 ± 9.8 | 34.0 ± 11.3 | 34.7 ± 10.1 | ||||
| Where do you get information about your health?∗∗ | Health employee | 35.6 ± 10.1 | 0.180 | 34.1 ± 11.4 | 0.420 | 34.9 ± 10.2 | 0.315 |
| Radio/television | 34.3 ± 9.4 | 0.199 | 36.2 ± 10.1 | 0.443 | 33.8 ± 9.0 | 0.299 | |
| Newspaper, journal | 38.6 ± 8.3 | 0.004 | 37.6 ± 9.2 | 0.001 | 38.1 ± 8.3 | 0.001 | |
| Internet | 36.5 ± 9.0 | 0.609 | 35.4 ± 9.4 | 0.372 | 35.9 ± 8.7 | 0.536 | |
| Family members, friend | 34.1 ± 10.8 | 0.307 | 31.8 ± 12.5 | 0.229 | 33.0 ± 11.4 | 0.254 | |
| Health perception∗∗ | Very good | 37.0 ± 32.7 | 0.067 | 37.9 ± 9.1 | 0.010 | 37.5 ± 9.2 | 0.017 |
| Good | 32.7 ± 11.6 | 34.7 ± 10.4 | 33.7 ± 10.3 | ||||
| Bad | 39.6 ± 8.8 | 38.0 ± 11.0 | 38.8 ± 9.9 | ||||
| Too bad | — | — | — | ||||
- Note: M = mean. Bold values indicate statistically significant relationships (p < 0.05).
- Abbreviations: PDPH = preventing diseases and promoting health, SD = standard deviation, TS = treatment and service.
- ∗t-test.
- ∗∗One-way ANOVA.
| TS | PDPH | Total | |||||
|---|---|---|---|---|---|---|---|
| M ± SD | p value | M ± SD | p value | M ± SD | p value | ||
| Acceptance of drug therapy | Yes | 36.5 ± 9.8 | 0.147 | 34.7 ± 10.7 | 0.556 | 35.6 ± 9.8 | 0.298 |
| No | 34.1 ± 10.5 | 33.1 ± 12.6 | 33.6 ± 10.8 | ||||
| Compliance with treatment | Yes | 36.5 ± 9.2 | 0.705 | 34.7 ± 9.2 | 0.984 | 35.6 ± 9.0 | 0.927 |
| Irregular | 33.8 ± 15.2 | 33.8 ± 15.2 | 33.5 ± 15.8 | ||||
| No | 34.6 ± 10.4 | 33.4 ± 13.1 | 34.0 ± 11.0 | ||||
| Reasons for not using medication | Dislike of taking medication | 33.2 ± 10.4 | 0.165 | 31.9 ± 13.2 | 0.427 | 32.5 ± 11.5 | 0.280 |
| I do not think drugs will be helpful | 31.7 ± 11.9 | 0.076 | 33.1 ± 10.5 | 0.653 | 32.4 ± 10.6 | 0.175 | |
| Thinking that the drugs will harm you | 32.5 ± 12.8 | 0.211 | 33.6 ± 13.9 | 0.643 | 33.0 ± 13.0 | 0.796 | |
| Do not forget to use medicines | 25.0 ± 19.2 | 0.085 | 22.2 ± 21.1 | 0.086 | 23.6 ± 19.8 | 0.076 | |
| Not using drugs because they make you nauseous | 38.3 ± 12.3 | 0.598 | 38.5 ± 12.2 | 0.590 | 38.4 ± 10.9 | 0.503 | |
| Not using because the number of drugs swallowed in a single dose is too high | 35.2 ± 10.5 | 0.697 | 35.6 ± 12.5 | 0.597 | 35.4 ± 11.1 | 0.848 | |
| Not using it because it feels good | 33.6 ± 14.1 | 0.698 | 32.6 ± 14.9 | 0.711 | 33.1 ± 13.9 | 0.857 | |
| Medications given after diagnosis of COVID-19 infection | Favipravir | 35.9 ± 9.8 | 0.538 | 34.2 ± 11.3 | 0.664 | 35.1 ± 10.1 | 0.525 |
| Hydroxychloroquine sulfate | 36.5 ± 11.0 | 0.330 | 35.9 ± 10.9 | 0.224 | 36.2 ± 10.4 | 0.275 | |
| Ritonavir/lopinavir | 40.3 ± 6.9 | 0.270 | 40.2 ± 9.5 | 0.143 | 40.2 ± 8.0 | 0.188 | |
| Oseltamivir | 29.7 ± 18.3 | 0.119 | 37.5 ± 8.3 | 0.705 | 33.6 ± 12.6 | 0.196 | |
| Azithromycin | 47.9 ± 10.0 | 0.142 | 50.0 ± 11.2 | 0.194 | 48.9 ± 10.1 | 0.128 | |
| No medicine given | 32.5 ± 9.3 | 0.338 | 31.7 ± 11.2 | 0.466 | 32.1 ± 9.9 | 0.387 | |
| Status of using prescribed drugs | Favipravir | 36.1 ± 10.1 | 0.448 | 34.4 ± 10.9 | 0.825 | 35.3 ± 10.1 | 0.614 |
| Hydroxychloroquine sulfate | 36.4 ± 10.9 | 0.475 | 35.0 ± 10.6 | 0.633 | 35.7 ± 10.3 | 0.490 | |
| Ritonavir/lopinavir | 37.2 ± 5.9 | 0.911 | 34.4 ± 7.9 | 0.954 | 35.8 ± 6.8 | 0.993 | |
| Oseltamivir | 29.7 ± 8.1 | 0.390 | 33.3 ± 0.0 | 0.229 | 31.5 ± 4.0 | 0.088 | |
| Azithromycin | 48.9 ± 1.5 | 0.040 | 50.0 ± 0.0 | 0.028 | 49.5 ± 0.7 | 0.028 | |
| No drug used | 34.8 ± 9.2 | 0.565 | 33.4 ± 12.7 | 0.914 | 34.1 ± 10.1 | 0.720 | |
| Thinking that the medications given are effective | Yes | 36.5 ± 10.2 | 0.148 | 34.1 ± 10.8 | 0.680 | 35.3 ± 10.1 | 0.628 |
| No | 34.9 ± 9.7 | 34.6 ± 11.9 | 34.8 ± 10.2 | ||||
| Using any alternative method(s) after being diagnosed with COVID-19 | Yes | 36.1 ± 9.7 | 0.267 | 34.7 ± 10.8 | 0.431 | 35.4 ± 9.6 | 0.395 |
| No | 34.4 ± 12.0 | 31.9 ± 13.6 | 33.4 ± 12.4 | ||||
- Note: M = Mean. Bold values indicate statistically significant relationships (p < 0.05).
- Abbreviations: PDPH = preventing diseases and promoting health, SD = standard deviation, TS = treatment and service.
4. Discussion
In this study, the relationship between the HL levels of COVID-19 patients receiving home treatment and their acceptance of using the drugs for the treatment of COVID-19 given by the Ministry of Health and their use of these drugs by the treatment protocol was examined. According to the results of the studies in the literature, a relationship was found between the health-related media that the patients followed and their behavior during the pandemic [14, 22].
Accordingly, it has been reported that those who follow news sites related to COVID-19 exhibit more risky behavior and disobey the mask, distance, and hygiene rules [22]. In the study of Gautam et al., participants stated their ways of obtaining information about COVID-19 as news (80.3%), friends/relatives (72.3%), social media (44.9%), and healthcare professionals (13.4%) [14]. In the United States, during the COVID-19 pandemic, the most frequently used sources of information were mass media channels such as television, radio, podcasts, and newspapers. It was reported that government websites were predominantly used as online information sources [23]. Contrary to the studies, it was reported in this study that the most reliable source of information was health professionals, and the least reliable source of information was the recommendations of family and friends. The contact tracing teams in Turkiye delivered the drugs to COVID-19 patients by going to their homes. Meanwhile, patients had the opportunity to obtain information about the disease and the treatment of COVID-19. Thus, it is seen that the confidence in the knowledge of healthcare professionals, especially of individuals who have had COVID-19, has increased.
Patients diagnosed with COVID-19 frequently exhibited symptoms such as fever, cough, fatigue, dyspnea, muscle pain, sore throat, diarrhea, nausea, vomiting, and dizziness [24, 25]. Similarly, those monitored at home after a COVID-19 diagnosis also experienced symptoms including fatigue, muscle and joint pain, sore throat, cough, dyspnea, and loss of taste and smell. In Turkiye and other countries, antiviral, anti-inflammatory, and immunomodulatory treatment methods that were previously licensed for the treatment of other diseases have been widely used and shown to be safe in similar indications and have been employed in the treatment of COVID-19 [26]. Drugs such as hydroxychloroquine sulfate, favipiravir, remdesivir, and lopinavir–ritonavir were determined to be effective against SARS-CoV and were recommended and used [13]. In addition, in line with the data obtained from SARS and influenza epidemics, early initiation of antiviral drugs was recommended in the treatment of COVID-19, considering that early initiation of antiviral therapy prevents the progression of the disease [26, 27]. For this reason, favipiravir, hydroxychloroquine sulfate, ritonavir/lopinavir, oseltamivir, and azithromycin drugs used to treat COVID-19 in Turkiye were included in the study.
During the study’s data collection period, hydroxychloroquine sulfate was used to treat COVID-19, and the Ministry of Health stopped using the drug during the data collection process [15]. Upon examining the study findings, it was observed that the vast majority of participants were administered favipiravir and hydroxychloroquine sulfate. When the study findings were examined, it was found that favipiravir was given to 88.5% of the participants and 71.7% of them used the drug (Table 1). It was reported in a study conducted in Spain that paracetamol (60.5%), antibiotics (14.8%), and hydroxychloroquine sulfate (6.2%) were mainly prescribed for those receiving COVID-19 treatment at home. No drug was administered for the young population (14–29 years old), and hydroxychloroquine Sufhate and/or antibiotics were frequently prescribed for elders [28]. These findings are consistent with protocols in Turkiye, as the Turkish Ministry of Health has followed and implemented the COVID-19 treatment protocols of the WHO. Therefore, it is not surprising that similar medications are used in both countries. Several clinical studies conducted by the WHO working groups with four antiviral drugs (remdesivir, hydroxychloroquine sulfate, lopinavir, and interferon beta-1a) reported that they did not reduce mortality in general or in any of its subgroups did not reduce the initiation of mechanical ventilation or the duration of hospital stay [29].
In addition to the use of prescribed medications, it has been reported that in Poland, there was a significant increase in self-medication during the COVID-19 period due to difficulties in accessing healthcare services, uncertainties brought about by the pandemic, and fear of death [30]. In Bangladesh, there was an increase in the unnecessary and inappropriate use of antibiotics aimed at preventing COVID-19 infection, which subsequently led to higher rates of antibiotic resistance [31]. In Turkiye, after a positive COVID-19 diagnosis, the individual’s medical history is assessed by the Ministry of Health’s contact tracing teams, who then decide on further tests or home medication. Individuals participating in this study are monitored at home by the contact tracing team, which also ensures that the required medications are provided to them. It is believed that most patients adhere to the recommended treatment protocol due to their trust in the contact tracing team. However, some COVID-19 patients who did not follow the treatment protocol reported discontinuing or not using the medication due to feeling well or believing the medication to be harmful [30, 31]. Consistent with previous findings, the present study demonstrated a medication adherence rate of 73.4% in COVID-19 patients, with some individuals declining to use drugs perceived as potentially harmful.
In this study, it was determined that COVID-19 patients had sufficient HL and a high adherence rate to the treatment protocol. Although no studies specifically examining HL levels in patients diagnosed with COVID-19 were found in the literature, research conducted during the pandemic has similarly reported that individuals generally had adequate levels of HL [32–37]. Adequate HL has also been observed to be effective in promoting adherence to preventive behaviors [32, 34]. However, other studies in the literature have identified inadequate or limited HL levels among adult or elderly individuals during the pandemic [14, 33, 37, 38]. These differing results across studies may be attributed to variations in data collection methods, cultural differences, and the use of different measurement tools to assess HL.
During the pandemic, efforts by the Turkish Ministry of Health, including public information campaigns, guidance provided by contact tracing teams to patients and their families, and health information disseminated through the media, may have contributed to improving participants’ HL. The Turkiye Health Literacy (TSOY) survey conducted by the Ministry of Health found that 68.9% of the participants had inadequate or problematic levels of HL [39]. The discrepancies between the findings of this study and the TSOY study are thought to be due to differences in the socio-demographic characteristics of the participants, as well as the increased accessibility of health information during the pandemic.
The ages of COVID-19 patients participating in the study ranged from 18 to 80 years, and it was found that the HL level of the elderly individuals was lower than the younger ones. Similarly, studies have reported that as age increases, HL levels decrease [36, 38]. It is predicted that with the advancement of age, the cognitive and sensory functions of individuals decrease, and the possibility of deficiencies in literacy levels increases as a result of being away from the education process.
The total and subscale scores of HL were found to be significantly higher in those who were single compared to those who were married, in those who had no children compared to those who had children, in those who were students compared to those who did not work; in those who lived alone compared with those who lived with their family and friends; and in those who obtained health information from the print media. In addition, the TSOY total score of those with a high school or bachelor’s degree was found to be significantly higher compared with primary school graduates. The TSOY total and PDPH subscale scores of those with an excellent health perception before COVID-19 were significantly higher than those with good health perceptions. Similar to the study’s findings, it was stated in the literature that the level of HL increased significantly as the level of education increased [14, 33, 36, 38].
HL is defined as the capacity of individuals to have basic health information necessary to make the right decision about their health, to use this information, to convey it appropriately, and to address or solve a health-related problem [40]. HL is critical in reducing the adverse effects of the COVID-19 pandemic, as in all diseases [41, 42]. It has been stated that increased levels of HL can be an effective way to comply with treatment and medication [43]. A higher level of HL has also been reported to be consistently and positively associated with using drugs and adhering to treatment appropriately [43, 44]. Similarly, it was found that the individuals participating in this study had a high level of HL and drug use in the treatment of COVID-19. According to the results of the studies in the literature, people with a low level of HL have difficulty understanding and following health-related recommendations incorrectly in COVID-19 and have worse health levels compared to people with a high level of HL [14, 41]. In addition, it has been reported that individuals with low HL levels have more difficulty accessing health services, sharing their disease history with health personnel, reaching preventive services, and complying with drug treatment [45]. In the literature, it has been reported that people with low or limited health literacy have a low level of awareness of COVID-19 and exhibit protective behavior, and 41.7% of them have problems accessing health personnel and drugs in primary health care institutions during the quarantine period [14]. It means that individuals with low HL have difficulty comprehending health-related information holistically, affecting health behaviors. During the pandemic period, the importance of HL is emphasized because it is crucial to take appropriate measures to reduce transmission [41].
No significant relationship was found between the status of the use of the drugs, compliance with drug therapy, reasons for not using drugs, and the use of alternative treatment after the diagnosis of COVID-19 and the HL levels of the individuals participating in this study. Physicians and scientists around the world are warning about alternative treatment methods used for the prevention and treatment of COVID-19. Alternative treatment for COVID-19 can lead to a false belief in protection and worsen the pandemic crisis [46]. In the study by Dehghan et al., 84% of the participants stated that they used at least one alternative treatment method during the COVID-19 pandemic. It was stated that 61.3% of the most used alternative treatment methods they used were dietary supplements, 57.9% were prayer, and 48.8% were herbal medicine [11]. Similar to the literature, it was determined that 85.3% of the individuals participating in our study used one of the alternative treatment’s methods.
5. Conclusions and Recommendations
This study evaluated the effects of the use of drugs given to patients receiving home treatment by the Ministry of Health for COVID-19 treatment and HL levels on drug use. No significant relationship was found between the drug use status, treatment compliance, reasons for not using drugs, and alternative treatment use of the individuals participating in the study and HL levels. However, the HL levels of COVID-19 patients were found to be sufficient, and drug use rates were found to be high. When the relationship between sociodemographic characteristics and HL levels was examined, it was found that the HL total and subscale scores of single individuals, individuals without children, high school and undergraduate graduates, and those who received health information from the written press were significantly higher. Since the vaccination program in Turkiye was only launched for healthcare workers when the research data were collected, the vaccination status of the patients could not be examined. Examining the relationship between COVID-19 vaccine acceptance and HL levels is recommended in this context. Finally, the relationship between HL and treatment adherence should be considered when developing health policies. Long-term strategies aimed at increasing the general HL of the population can provide better preparation for future health crises.
5.1. Limitations
The data collection survey was applied only with the online random sampling method, as COVID-19 patients were in quarantine at home, and collecting data face-to-face would increase infection. Using online surveys was a barrier to access people without Internet access. It limited the representation of this group.
Conflicts of Interest
The authors declare no conflicts of interest.
Author Contributions
All authors contributed to the study’s conception and design. Feyza Demir Bozkurt, Çiçek Önder, Cumali Yıldızdal, and Aysun Ardıç performed material preparation, data collection, and analysis. Feyza Demir Bozkurt wrote the first draft of the manuscript, and all authors commented on previous versions. All authors read and approved the final manuscript.
Funding
No funding was received for this manuscript.
Acknowledgments
We would like to thank the research participants for their time and responses.
Open Research
Data Availability Statement
The data supporting this study’s findings are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
