Abstract

Aim: This study aimed to find out which group is most affected by psychological distress during the pandemic and determination of MHL level. Methods: This is cross a sectional study. Research sample consisted of 814 voluntary people. The study used descriptive data form, Kessler psychological distress scale and mental health literacy scale. Before the study was conducted, permission was obtained from necessary institutions and then research ethics committee approval was obtained. Also, individuals who were contacted through online platforms were informed about the study and provided informed consent forms by clicking “yes” option which showed their voluntary participation. The data were analyzed using descriptive statistics, t-test, analysis of variance, and Mann Whitney U and Kruskal Wallis tests. To detect correlations, the correlation and regression analyses were used. Results: The study results showed that 28% of the participants had diagnosable psychological distress (30-50) and individuals who received COVID-19 treatment at hospital had the highest median score (30). The mental health literacy of the participants was low (106) and the lowest scores belonged to individuals under treatment of COVID-19 at hospital. The highest psychological distress was in the Black Sea region and the lowest mental health literacy was in Southeastern Anatolia region. There was a significant very weak positive correlation between psychological distress scale and mental health literacy. Conclusion: Individuals who had COVID-19 disease had high psychological distress and low mental health literacy. After the pandemic, the community should be screened for mental illnesses and mental health literacy training should be organized to improve mental health. Nurses need to use their collaborative and advocacy roles regarding mental evaluation, providing consultancy and treatment during nursing care to patients with COVID-19 importance.

Keywords

Psychological Distress, Mental Health, Literacy, Public Health Nursing

Introduction

COVID-19 first outbroke in China, Wuhan in December [1]. COVID-19 spread into many countries and was deemed a global public health problem [2,3]. It was announced as a pandemic on a global scale in March 11, 2020 [4,5]. Since then, a total of 93,529,253 cases have been detected and 2,002,347 people lost their life around the world [6] whereas Turkey has had 2,355,839 cases and 23,325 deaths [7,8]. The new type of COVID-19 has caused political, economic, social and spiritual damage globally. Communities are trying to cope with COVID-19 by taking precautions to prevent the spread of infection. Since the first day of the pandemic, countries try to create their preventive and supportive systems [9]. In particular, prevention of new cases and limiting its spread has been the main objective. In this sense, intensive isolation measures and restrictions have been imposed, which now seems to be necessary. These measures taken during the pandemic have taken and will be taking place at different levels in Turkey as in the world. The isolation measures taken, travel restrictions, lockdown, restrictions/regulations on the operation of businesses have affected people politically, economically, socially and spiritually [10]. The pandemic has exposed the majority of people to obscurity that has never seen before. Such an unfavorable condition has increased people’s anxiety and made it difficult for them to control their anxiety. People are afraid of contracting coronavirus or transmitting it to their immediate environment. They also experience despair as they do not how to manage the process. This fear, anxiety, despair and being out of control create negative influence on individuals’ mental health. Thus, it is necessary to determine individuals’ state of mind and provide first aid based on the results.

During pandemics, the increase in pandemic driven disability, morbidity and mortality causing another pandemic with the increase in mental illnesses is an expected condition [11]. Therefore, determining individuals’ mental health status and mental health knowledge during the pandemic is of importance so that they can receive appropriate and timely treatment. Because it should be known that insufficient Mental Health Literacy (MHL) may take healthy years of individuals as it causes delay in the treatment, disruption of treatment process and high stigmatization.

To eradicate negative effects of mental illnesses, the most efficient method is to increase MHL levels of communities. Increasing individuals’ MHL level defined as “knowledge and belief to recognize, manage and prevent mental health disorders” positively affects understanding of how to be informed about mental health, choosing treatment, adhering to treatment, and maintaining mental health as it promotes mental health, happiness and wellness. High MHL may decrease attitudes towards mental health professionals and stigmatization/prejudice about the patients/illnesses [12-18]. Also, increasing MHL level can help reducing health expenses, creating/applying effective health promoting policies and allow people to find out their own treatment methods [19]. Thus, the fastest intervention for disorders regarding mental health that may arise due to these reasons is to increase MHL level by health professionals. Increasing MHL level is an intervention that may help early detection of any mental problems and preventing their occurrence. Low level of MHL in a community [20]. Detection of mental health problems that may arise after the pandemic and even prevention of these problems is a priority and important for public health professionals [21-23]. In particular, public health nurses who keep the closest contact with patients and their families have a key role. From this viewpoint, this study aimed to find out which group is most affected by psychological distress during the pandemic and detect its relationship with MHL level.

Materials and Methods

Study design

This is a cross sectional descriptive study.

Study sample

The study was conducted with patients hospitalized in a public hospital, those who were under quarantine and individuals from the society between the dates of June 26-August 26, 2020. There was no sample selection for the research. The sample of the study consisted of all COVID-19 patients hospitalized in a public hospital, all contacted people, all individuals under quarantine in the state dormitory and those who accepted to take part in the study online on voluntary basis between the dates above-mentioned. The research sample consisted of 814 people.

Procedure and data collection

The researcher informed the participants about the aim and expectations of the study by face-to-face interview, pointing that participation was not obligatory. The participants who voluntarily accepted to take part in the study were included. Filling out the questionnaire approximately took 15-20 minutes. The forms for those who were not infected were delivered on online platforms. The participants reached out the questionnaire forms using the web page “https://forms.gle/MaNsFDNPEnt7YbfK9”. Those who completed the questionnaires delivered them back to the researcher by clicking on “send” button.

Measures

Personal information form

To determine socio-demographic attributes of the participants, an introductory information form was used.

Kessler psychological distress scale (K10)

The K10 developed by, and adapted to [24]. The study used 10 questions included in the first part of the scale. These questions aim to measure the level of depression levels that an individual has experienced for the last four weeks before the interview and his/her current symptoms. The lowest score is 10 and the highest is 50, with higher scores showing more mental distress. Altun et al. Found sensitivity to be 92% and selectivity to be 90.4% for the K10 score with >20 cut-off point. Altun et al. Found the Cronbach’s alpha coefficient to be 0.95. The Cronbach’s alpha coefficient was found to be 0.94 in the current study.

Mental Health Literacy Scale (MHLS)

The scale has 35 items and it is a Likert type self-assessment tool based on the total score. Some Likert type scale items allow to do assessment ranging from one to four points, some others allow to make assessment from one to five points. The scale has six subscales; F1: Recognizing diseases (items 1-8), F2: Information on how to access information (items 16-19), F3: Information on risk factors and their causes (items 9 and 10), F4: Information on self-support/treatment interventions (items 11 and 12), F5: Information on accessing professional support (items 13-15) and F6: Attitudes that facilitate seeking appropriate support for mental health diseases and attitudes towards mental health diseases (items 20-35) (stigmatizing). Some items in the scale were reverse coded (items 10, 12, 15, 20-28). The scale score is obtained with the summation of all scores in the answers given to the scale items. The minimum obtainable score from the scale is 35 and the maximum score is 160. According to validity and reliability studies of the scale in its original language, the Cronbach’s alpha coefficient was 0.87, while this was found to be 0.89 in the

Turkish adaptation study. The Cronbach’s alpha coefficient was 0.79 in the current study.

Ethical considerations

Before the study, approvals were obtained from the Ministry of Health (This study received ethics approval from Scientific Research Studies on COVID-19 by the Ministry of Health – 2020-05-07T01_31_48.xml), from the institutions where the study was carried out, and from the clinical research ethics committee (Ethical Committee of a Public University–Date: 2020, 06, 22 Number 2020/126). Participants were informed about the study and written consent was obtained from those who agreed to participate in the face-to-face questionnaire. Individuals who participated in the social media and online questionnaires were informed with an informed consent form, and those who confirmed the “I agree to participate in the study” statement were able to participate in the questionnaire. Kessler K 10 Scale usage permission was obtained from Altun and his friends via e-mail.

Data Analysis

The data obtained from the tools were analyzed using SPSS software (version 23.0, SPSS Inc., Chicago, IL, USA) software. Evaluation of age, level of income and scores from the scales was made using number, percentage, mean, standard deviation, median, min-max and Inter Quantile Range (IQR). For the data not distributed normally, the Kruskal-Wallis and Mann-Whitney U tests were used, while the independent samples t-test and one way ANOVA analyses were used for the data normal distributed. The multiple regression analysis was used to determine some attributes having an impact on the MHLS scale. The findings were at 95% confidence interval and p<.05 level.

Results

Of the participants, 102 (12.5%) consisted of individuals under quarantine and 680 (83.5%) were from the community (Table 1). Of them, 519 (63.8%) were female, 311 (38.4%) aged 31-60 years and 502 (61.7) were single. Of them, 239 (29.4%) had an associate degree or higher, 319 (39.2%) were employed, 109 (13.4%) had a chronic disease, 68 (8.4%) had mental health diseases and 154 (4.3%) had substance use (smoked) (Table 1)

n: Number, %: Percent. Percentages were taken over n value. Individuals selected more than one option.

During the COVID-19 pandemic, of the participants, 82.7% obtained information from TV, 50.1% from friends or immediate circle and only 33.9% from scientific publications such as articles (Table 2). As symptoms of COVID-19, 94.6% participants had high fever and 98.2% had difficulty in breathing. Of them, 52.7% (317) felt anxious about the transmission of COVID-19 to themselves or a relative, 4.3% (26) felt anxious of having COVID-19 symptoms (cough, difficulty in breathing, etc.), while 7.5% (45) expressed they had no feeling of anxiety related to COVID-19 (Table 2).

n: Number, %: Percent. Percentages were taken over n value. Individuals selected more than one option.

Table 3 shows the median value of the total score of the scale to be 106 and the median value of the K10 scale to be 22. The scores of individuals from the MHLS subscales are as follows: F1 was 22, F2 was 16, F3 was 5, F4 was 8, F5 was 16, F6 was 50. The number of those scoring 20 points and below from the psychological distress scale was 345 (43.1%) and the number of those scoring 30 to 50 points was 224 (28%). The correlation analyses results between the scales showed a very weak, positive and significant correlation between MHLS and K10 scales (p=0.001) (Table 3).

*Spearman’s correlation analysis **p=0.001

According to the results of the study, the scores of females from the K10 and MHLS scales were significantly higher than those of males (p=0.0001). There was no difference between the scores from the K10 between age groups (p=0.075); however, the scores of individuals aged 18-30 years from MHLS’s accessing information and stigmatization subscales were higher than other age groups (p=0.0001). The K10 scores of individuals having high school or higher education had higher scores from the K10 scale compared to those with lower education (p=0.031). The scores of individuals having high school or higher education from the recognition of diseases and accessing information subscales of the MHLS were found to be significantly higher than those with lower education (p=0.0001, p=0.002, p=0.04). The K10 scores of individuals living with their parents were significantly higher than those living their spouses and children (p=0.001). However, individuals living alone or with their parents had significantly higher scores than those living with their spouses and children (p=0.0001). The scores of individuals living with their spouses and children from MHLS’s accessing information and stigmatization subscales were found to be lower than those living with other individuals (p=0.003, p=0.0001) (Table 4).

IQR; Inter Quantile Range, x: Mean, SS: Standard deviation, n: Number, %: Percent. *: Mann Whitney U **: Independent Samples T Test, ***: Kruskal Wallis test, ****: One Way ANOVA, *****: Adjusted Bonferroni, ******: Bonferroni

There was no significant correlation between profession and K10 scores (p=0.290), however, the total scale scores of health care professionals from MHLS (111.27 ± 12.0) were found to be significantly higher than other professions (p=0.0001) The health care professionals had significantly higher scores from all subscales except for the risk factors and self-aid subscales of the MHLS (p=0.0001). The K10 scores of individuals with mental health diseases were significantly higher than those who did not have mental health diseases (p=0.01). There was no significant correlation between having mental health diseases and MHLS, whereas self-aid scores of individuals with mental health diseases were significantly higher than those of individuals who did not have any mental health diseases (p=0.031). The K10 median value (30) of individuals receiving COVID-19 treatment at hospital was significantly higher than other groups (community: 21, quarantine: 19) (p=0.0001). Individuals under quarantine had the highest score from the MHLS total scale score (112.61 ± 12.4) and this was significantly higher compared to other groups (community: 105.84 ± 12.0 and hospital: 101.65 ± 5.3) (Table 4).

A multiple linear regression analysis was made to explain the effect of K10, gender, chronic disease and having a child on MHLS. The significance level of the model equaling to F value was found to be statistically significant (F=18.593; p<0.05). The K10, gender, education, chronic disease and having a child had significant effect on MHLS (p<0.05) (Table 5).

*p<0.05 (0: Male, 1: Female, 0: Primary school, secondary school, high school, 1: Associate degree, undergraduate, post-graduate, 0: Yes, 1: No; 0: No, 1: yes). The formula; MHLS=104.6180+KESSLER*0.121+gender*4.697+education*3.317+chronic disease*-3.201+having a child*-5.729

The MHLS scores of the participants living in the Southeastern Anatolia region were the lowest and the scores of those living in Aegean region were the highest. This difference was significant between regions (SoutheasternMediterranean, Southeastern) higher (H=20.974, df=7, p=0.004).

Discussion

This study, investigating into finding out the comparison of individuals’ psychological distress and MHL levels showed that the participants mostly felt anxious about the transmission of COVID-19 to themselves or a relative and having COVID-19 symptoms (cough, difficulty in breathing, etc.). Similar results were obtained from the study by Rahman MA et al. yet the participants felt more anxiety compared to those living in Australia [25]. It was observed that high level of fear caused higher stress in Australian individuals too during COVID-19 pandemic. The majority of the participants had fear of the distress in case of getting infected by COVID-19.There have been broadcasts indicating that there is anxiety pandemic in Turkey [26,27]. One of the biggest threats during the pandemic and afterwards was stated to be anxiety pandemic. Thus, whether increasing anxiety of people causes mental illnesses after the pandemic should be determined through community screening. However, during the pandemic, individuals should be provided with mental health promoting interventions. Individuals should be informed about how to mark the mental illness symptoms and which methods to use to cope with stress in later processes. Since the majority of individuals used TV as a source of information, providing these trainings and information through the media may provide faster results. In addition to media campaigns, trainings should be provided along with regulations to detect mental illnesses at the first step. 

The median value of the psychological distress scale (K10) was found to be 22, while proportion of those who pointed out a diagnosable mental health problem was more than one quarter (28%) of the participants. However, only 8.4% of the participants had such diagnosis. The study conducted in Australia showed that the K10 scores of the participants were 19.6 Rahman et al. This result are similar to those of the current study, yet the psychological distress level (median: 22) was found to be higher in the study conducted in Turkey. Whereas the K10 median value of the study was found to be similar to that of the study conducted by Altun et al. (21.8 ± 10.7), it was much lower than that 30 of the study conducted with students by Pehlivan. The proportion of mental health diagnosis determined in this study (8.4%) was found to be much lower than the results of the Mental Health Profile of Turkey and this proportion was found to be 28% according to the K10 scale score. Kilic has stated that there are many people with untreated mental illnesses in the community, which supports the results of this study Kilic et al. Found the number of individuals that could be diagnosed was 71 (13.0%). The proportion of this result equals to less than a half of the study results. It is very natural that the pandemic process creates different influences in different countries. However, similar results from the studies conducted in Turkey led to think that psychological distress experienced in the pre-pandemic period could be more in Turkey. Besides, it was estimated that almost seven million people in Turkey not diagnosed or treated individuals in Turkey might be at greater risk in terms of mental health problems.

The MHLS score median value was found to be 106; this value was even lower than the median of MHLS total score of the study (106) compared to the cut-off point median score (130) determined by Ratnayake et al., [28]. The MHL level was lower than other studies conducted in other countries Gorczynski et al, Marwood et al, O’Connor et al. The MHL, particularly median scores of students were found to be very low (90) in other studies conducted in Turkey. A low MHL is accepted an emergency public health problem. An increased MHL helps in decision-making process regarding mental health, early diagnosis, increasing diagnosis and treatment success and reducing the severity of the disease Hao et al. Furthermore, since attitudes towards mental health professionals, stigmatization and prejudice on patients, and selection of and compliance to treatment affect other aspects of help seeking process help seeking behaviors for improved mental and mental disorders may increase in the long-term. Among the help seeking rates in the literature are systemic barriers that prevent help seeking such as economic difficulties, limited access to psychiatric services or lack of awareness of the services as well as the role of cultural insecurity and skepticism of psychiatry as a science especially among ethnic minority groups. Nurses have a key role in eliminating all these obstacles and promoting MHL. This is because nurses are health care professionals who have direct contact with the patients and their families. The roles of nurses allow early diagnosis and treatment and prevent bad health consequences due to the lack of treatment [29].

The median value of K10 scale was found to be 22 between the participating groups. The number of those scoring 20 points and below from the psychological distress scale was 345 (43.1%) and the number of those scoring 30 to 50 points was 224 (28%). This result is important as it shows that one fourth of the participants are not diagnosed even if they have diagnosable distress. According to 1998 data in Turkey, nearly seven million people with mental illnesses were not diagnosed or treated. Instead of getting professional help for diagnosis and treatment, individuals with mental illnesses seek help from their family members or friends. Thus, it is necessary to train the whole community about

psychobiological bases and effective treatments of mental health disorders [30] and there is need for trainings to increase the MHL level. At that point, factors such as training of the community and primary health care personnel about mental illnesses can be effective in increasing applications and reducing the need for unmet treatments. The first application of Turkish people with mental illnesses is made to psychiatrists and the second is to experts other than these psychiatrists. This shows that mental health services in Turkey should effectively be provided at primary level.

The scores of females from the K10 scale were significantly higher than those of males (p<.05) Unlike the results of this study, the results from the study of Pehlivan found the K10 scores of males to be higher Pehlivan et al. The study of Kilic supporting the results of this study stated that females went through more mental illnesses than males and those having mental illness at least for once doubled males.

The MHL levels of females were found to be higher than those of males (p<.05). Sullivan et al. found that MHL levels of females were higher than those of males Similarly, Furnham et al. Stated that MHL level of females were higher compared to males. Similar results were obtained from the study by Khalil et al. The results of the study were similar to those of Tokur-Kesgin. Higher MHL levels are important as they remove the barriers to help-seeking behavior and increase the facilitating factors to solve mental health problems Sullivan et al. In relation to diagnosis and treatment, men may possibly be regarded a risky group. Poor MHL delays diagnosis and treatment.

According to the analysis results, the MHLS scores of individuals aged 18-30 years besides the scores from accessing information and stigmatization subscales were significantly higher than those of other age groups (p<0.05). The study by Khalil found that the score from stigmatization subscale along with age decreased and a positive attitude appeared. This result supports this study and is associated with decreasing influence of social spiritual ideology with increasing age. Business-related responsibilities of these individuals increase their stress level. The scores of individuals with primary school and high school education from the K10, MHLS scales and subscales were significantly higher than those with lower education background (p<.05). Some studies state that several variables such as age, education, and even personality traits have an impact on HML level. The low level of education affects MHL; in particular it has an impact on the lack of information about the symptoms and prevalence of mental illnesses Bjorsen HN et al. The K10 scores of individuals living with their parents were significantly higher than those living their spouses and children (p<.05). Higher psychological distress levels of those living with their parents may stem from the fact that elder individuals are under greater risk of getting infected by COVID-19. This is because individuals living with their parents feel anxiety of transmitting COVID-19 to their family and in case of its transmission, their parents may have a risk of death. The literature indicates that these individuals may have higher stress and anxiety during the pandemic as they are primary caregivers to their families Langer et al. Found that individuals who live with their spouses and children have higher psychological distress compared to those living alone. This result shows that emotional bonds of family members' presence to individuals affect anxiety levels.

The K10 score of the health care professionals was higher than that of other groups (p>0.05) [31]. Found that four fifths of the health care professionals experience anxiety symptoms during the pandemic. The reason was identified to stem from long working hours and fear of infection during the pandemic. While MHL level of health care professionals was found to be higher than other groups but still low, the stigmatization subscale of the MHLS had the highest score. Found that MHL level of nurses except for psychiatric nurses was insufficient, so they recommended those nurses to be included in MHL training programs. The literature suggests that MHL level of health care professionals except for psychiatry is insufficient [32].

The K10 and MHLS scores of individuals with mental health diseases were higher than those who did not have mental health diseases (p<0.05). This is because the MHL level allows individuals to easily manage mental health-related symptoms and recognize the diseases [33]. The study results are important in terms of showing that individuals can recognize mental illnesses and receive professional support. However, individuals may have problems with receiving appropriate treatment or compliance with the treatment even when diagnosed [34-36]. As stated by Kilic help seeking behavior of individuals is affected by the awareness of individuals at the onset of their mental illness, their affected occupational and social functions, economic reasons and physical conditions. Whether individuals seeking professional help in the upcoming periods will get the right diagnosis and treatment or not affects the course of their illness [37-39]. Some of the individuals diagnosed correctly tend to quit the treatment. In this consideration, the pandemic process might have increased severity of mental illness. There may be a need to reevaluate those with mental illnesses and reconsider their treatment. Rahman found that individuals with a history of mental illness have higher stress level during the pandemic [40-42].

The results showed that the scores of individuals under quarantine from MHLS and subscales were significantly higher than those of other groups. Also, the scores they obtained from MHLS and subscales were significantly higher than those of individuals who were diagnosed to be positive and hospitalized (p<0.05) (Table 4). In particular, the scores of individuals under quarantine from MHLS and subscales were significantly higher compared to other groups. The scores of the community from MHLS and subscales were significantly higher than those of individuals who were diagnosed to be positive and hospitalized (p<0.05). Although individuals under quarantine had high MHL levels, they had negative behaviors and stigmatizing approach. This shows that even if MHL level increases, stigmatization and negative attitudes can still exist. Kilic states that it takes many years to change stigmatization and negative attitudes through MHL trainings where this

dimension of mental health literacy is highly affected by the cultural structure. The MHL levels of the participants were low. Although health care professionals had higher scores than other groups, their scores were still insufficient. In particular, higher stigmatization scores of the health care professionals indicated their negative attitudes towards mental illnesses. This was high in the community and hospital groups too, which shows that the community also has a negative attitude towards mental illnesses. The study conducted by Khalil found that stigmatization of mental illnesses among Saudi people is a major problem. This will lead individuals to feel excluded due to mental illnesses, not to get diagnosed or receive professional help. Instead of seeking professional help for mental illnesses, individuals may seek help of other groups or curatives. To prevent this, people should be trained on MHL and to increase their awareness of mental health and illnesses, community campaigns should be organized, first aid trainings should be provided regarding mental illnesses and MHL trainings should be provided at schools.

The K10 scale median value of the individuals diagnosed with COVID-19 and hospitalized (30.00) and the community (21.00) were significantly higher than that of individuals under quarantine (19.00) (p<0.05). Individuals under treatment of COVID-19 at hospital had the highest K10 scores; however they scored the lowest in the accessing information subscale of MHLS. This finding gives the impression that mental influence of the disease on individuals should be examined and followed up at certain intervals post treatment. In particular, people who have recovered from the disease should be considered that they are under risk of mental illnesses. Inability of these individuals to access information makes this more sensitive. Delay in seeking for treatment can cause their loss of workforce, death and disabilities.

The MHLS scores of the participants living in the Southeastern Anatolia region were the lowest and the scores of those living in Aegean region were the highest. Mental health literacy may differ by gender, nation, region or even religion and this may stem from high MHL in western countries and low MHL in Asian countries. What is important here is that the number of individuals with real mental illnesses cannot be determined since they are not diagnosed or do not seek professional help (WHOCPE, nd).

The actual prevalence is not known since the last study about mental health was conducted in 1998 in Turkey. However, the study showed a significant difference in MHL between the Eastern and Western regions of Turkey too. Based on this result, the MHL level should be promoted throughout Turkey, especially in the Eastern provinces and the mental health should be improved. Low MHL level is influenced by cultural influences (Furnham and Swami. Further studies investigating into these effects should be conducted in Turkey too.

Considering the K10 scores across regions, psychological distress of individuals living in the Black Sea region was significantly higher (p<.05). Contrary to the results of the study, Kilic found that mental health diseases are more common in the western regions of Turkey. This result may help to interpret that higher MHL level in western regions of Turkey increases the rate of getting diagnosis. This is because the failure to recognize the symptoms and to use the right psychiatric labels negatively affects help seeking behaviors for psychiatric symptoms Furnham et al. Determining individuals’ attitudes towards these diseases, opinions about professional help seeking behaviors and approach to treatments of mental illnesses across regions is important.

Research Limitations

The research is limited to the sample that can only be reached because it is conducted online.

Conclusion

Individuals who had COVID-19 disease had high psychological distress and low mental health literacy. After the pandemic, the community should be screened for mental illnesses and mental health literacy training should be organized to improve mental health. Nurses need to use their collaborative and advocacy roles regarding mental evaluation, providing consultancy and treatment during nursing care to patients with COVID-19.

Author Contributions

Senay Akgun and Makbule Tokur-Kesgin designed this study; Hümeyra Hancer-Tok and Lütfiye Nur Uzun collected the data; Senay Akgun and Hümeyra Hancer-Tok analyzed the data; Senay Akgun and Makbule Tokur-Kesgin wrote the manuscript.

Conflict Disclosure

The authors declare no conflicts of interest.

Data Availability

All of the article data are given in the article and in the attached files. The data that support the findings of this study are available from the corresponding author upon reasonable request.

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