The effect of the COVID-19 pandemic on self-management in patients with type 2 diabetics

      Highlights

      • Diabetes self-management is presented with new difficulties during the COVID-19 pandemic.
      • It can be said that the traditional face to face treatment needs of type 2 diabetics cannot be met during the pandemic.
      • The COVID-19 pandemic reduces self-management levels in individuals with type 2 diabetes.

      Abstract

      Aims

      The research was conducted with the aim of determining the effect of the COVID-19 pandemic on levels of self-management in individuals with type 2 diabetes.

      Methods

      This cross-sectional descriptive type of study was conducted between 21 December 2020 and 1 April 2021. It was performed with 378 individuals with type 2 diabetes attending the endocrinology clinic and outpatients’ department of a government hospital who agreed to participate in the research. In the collection of data, a Patient Identification Form, Visual Analog Scales (an Anxiety VAS and a Stress VAS), and the Diabetes Self-Management Questionnaire (DSMQ) were used. The Wilcoxon test, Independent Sample t test, One-Way Anova and binary logistic regression were used in the analysis of data.

      Results

      The Diabetes Self-Management Questionnaire (DSMQ) total mean score of the individuals with type 2 diabetes participating in the study during the COVID-19 pandemic was 5.25 ± 1.04. Their anxiety total mean score was 0.32 ± 1.56, and their total mean stress score was 7.06 ± 1.62. Being male, over the age of 65, married and having a diagnosis of diabetes for 6–11 years, increased smoking, the COVID-19 pandemic, reduced physical activity (not walking) and support obtained from health professionals, and increased anxiety and stress levels were found to be risk factors affecting diabetic self-management.

      Conclusions

      The findings show that the COVID-19 pandemic has had a negative effect on the self-management levels of individuals with type 2 diabetes.

      Keywords

      1. Introduction

      COVID-19 first appeared in China, then became a public health threat to the whole world, and in March 2020 was declared a pandemic by the World Health Organization (WHO) [
      • Haybar H.
      • Kazemnia K.
      • Rahim F.
      Underlying chronic disease and COVID-19 ınfection: a state-of-the-art review, Jundishapur.
      ]. People of all ages are susceptible to COVID-19, but diabetic patients are at greater risk because they have many accompanying chronic illnesses and their immune systems are under pressure [
      • Shi C.
      • Zhu H.
      • Liu J.
      • Zhou J.
      • Tang W.
      Barriers to self-management of type 2 diabetes during covid-19 medical isolation: a qualitative study.
      ,
      • Kang J.
      • Chen Y.
      • Zhao Y.
      • Zhang C.
      Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic.
      ,
      • Riddle M.C.
      • Buse J.B.
      • Franks P.W.
      • Knowler W.C.
      • Ratner R.E.
      • Selvin E.
      • Wexler D.J.
      • Kahn S.E.
      COVID-19 in people with diabetes: urgently needed lessons from early reports.
      ]. The COVID-19 pandemic has led to more variable blood sugar levels in diabetic patients, and to an increase in HbA1c levels, hospitalization and intensive care needs [
      • Barone M.T.U.
      • Ngongo B.
      • Harnik S.B.
      • de Oliveira L.X.
      • Végh D.
      • de Luca P.V.
      • Pedrosa H.C.
      • Giraudo F.
      • Cardona-Hernandez R.
      • Chaudhury N.
      • Menna-Barreto L.
      COVID-19 associated with diabetes and other noncommunicable diseases led to a global health crisis.
      ].
      There are 463 million people with diabetes in the world [
      • Boulton A.
      Why access to diabetes care must not be another victim of the COVID-19 pandemic.
      ]. It is estimated that the prevalence of diabetes will rise to 10.2% (578 million) by 2045, and to 10.9% (700 million) by 2045 [
      • Saeedi P.
      • Petersohn I.
      • Salpea P.
      • Malanda B.
      • Karuranga S.
      • Unwin N.
      • Colagiuri S.
      • Guariguata L.
      • Motala A.A.
      • Ogurtsova K.
      • Shaw J.E.
      • Bright D.
      • Williams R.
      Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas, 9(th) edition.
      ]. In 72 314 COVID-19 case reports published by the Chinese Disease Control and Prevention Center, it is shown that the mortality of persons with diabetes (7.3%) is approximately three times higher than that of persons without diabetes (2.3%) [
      • Wu Z.
      • McGoogan J.M.
      Characteristics of and ımportant lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese center for disease control and prevention.
      ].
      Type 2 diabetes is a disease which necessitates constant medical and individual care in order to prevent and slow acute and chronic complications [
      • Stryker L.S.
      Modifying risk factors: strategies that work diabetes mellitus.
      ,
      • Onmez A.
      Management of microvasculer complications in diabetes mellitus.
      ]. Diabetes is a disease which is steadily increasingly seen, and which entails complications and the need for lifelong treatment and care. Thus, it is a significant health problem which constitutes a heavy burden on society [
      • Eroglu N.
      • Sabuncu N.
      The effect of education given to type 2 diabetic individuals on diabetes self-management and self-efficacy: randomized controlled trial.
      ,
      • Totesora D.
      • Ramos-Rivera M.I.
      • Villegas-Florencio M.Q.
      • Reyes-Sia P.N.
      Association of diabetes-related emotional distress with diabetes self-care and glycemic control among adult filipinos with type 2 diabetes mellitus at a tertiary hospital in manila.
      ,
      • Eroglu N.
      • Sabuncu N.
      Adaptation of diabetes self management questionnaire to turkish society: validity and reliability study.
      ]. The worry of diabetic individuals about going to a hospital during the pandemic makes it more difficult for health professionals to monitor them and to support their self-confidence [
      • Kang J.
      • Chen Y.
      • Zhao Y.
      • Zhang C.
      Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic.
      ,
      • Sayeed K.A.
      • Qayyum A.
      • Jamshed F.
      • Gill U.
      • Usama S.M.
      • Asghar K.
      • Tahir A.
      Impact of diabetes-related self-management on glycemic control in type II diabetes mellitus.
      ]. Holistic self-management in diabetes includes regular glucose monitoring, medical nutrition treatment, adherence to regular drug use, and self-care behaviors ensuring adherence to physical activity [
      • Eroglu N.
      • Sabuncu N.
      The effect of education given to type 2 diabetic individuals on diabetes self-management and self-efficacy: randomized controlled trial.
      ,
      • Eroglu N.
      • Sabuncu N.
      Adaptation of diabetes self management questionnaire to turkish society: validity and reliability study.
      ]. Among other factors affecting self-management behaviors in diabetes are diabetes education, the duration of the illness, the presence of comorbid conditions, body mass index (BMI), foot care and smoking [
      • Al-Qahtani A.M.
      Frequency and factors associated with inadequate self-care behaviors in patients with type 2 diabetes mellitus in Najran, Saudi Arabia. Based on diabetes self-management questionnaire.
      ]. In order for a diabetic individual to be able to carry out self-management, it is of great importance to have sufficient knowledge concerning diabetes management and to always keep blood sugar within normal limits, to have cooperation from family members and the support of physicians and diabetes nurses, and to make self-management skills into a lifestyle and maintain them in order to prevent complications. In this way, the quality of life will be improved [
      • Shi C.
      • Zhu H.
      • Liu J.
      • Zhou J.
      • Tang W.
      Barriers to self-management of type 2 diabetes during covid-19 medical isolation: a qualitative study.
      ,
      • Eroglu N.
      • Sabuncu N.
      Adaptation of diabetes self management questionnaire to turkish society: validity and reliability study.
      ,
      • Al-Qahtani A.M.
      Frequency and factors associated with inadequate self-care behaviors in patients with type 2 diabetes mellitus in Najran, Saudi Arabia. Based on diabetes self-management questionnaire.
      ,
      • Khalooei A.
      • Benrazavy L.
      Diabetes self-management and ıts related factors among type 2 diabetes patients in primary health care settings of kerman, Southeast Iran.
      ,
      • Sireci E.
      • Yilmaz Karabulutlu E.
      Diabetes mellitus type ıı patients’ acceptance of illness and determination of self efficacy levels for their car.
      ].
      The fear of COVID-19 infection, the constant and immediate flow of news concerning the epidemic, the measures taken throughout the epidemic to prevent its spread, isolation, uncertainty and loneliness bring about radical changes in daily life [
      • Kang J.
      • Chen Y.
      • Zhao Y.
      • Zhang C.
      Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic.
      ,
      • Banerjee M.
      • Chakraborty S.
      • Pal R.
      Diabetes self-management amid COVID-19 pandemic.
      ]. It has been reported that these changes can result in a reduction in communication between individuals with diabetes and health professionals, limited access to health services, a reduction in family support and limited physical activity, as well as problems such as anxiety, insomnia and a disruption of blood sugar control [
      • Shi C.
      • Zhu H.
      • Liu J.
      • Zhou J.
      • Tang W.
      Barriers to self-management of type 2 diabetes during covid-19 medical isolation: a qualitative study.
      ,
      • Kang J.
      • Chen Y.
      • Zhao Y.
      • Zhang C.
      Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic.
      ,
      • Banerjee M.
      • Chakraborty S.
      • Pal R.
      Diabetes self-management amid COVID-19 pandemic.
      ,
      • Mukona D.M.
      • Zvinavashe M.
      Self-management of diabetes mellitus during the Covid-19 pandemic: recommendations for a resource limited setting.
      ].
      It is thought that all of these changes and problems during the COVID-19 outbreak may affect diabetic self-management. In the literature, only one study was found on the perceived hindrances to type 2 diabetes self-management in the COVID-19 outbreak [
      • Shi C.
      • Zhu H.
      • Liu J.
      • Zhou J.
      • Tang W.
      Barriers to self-management of type 2 diabetes during covid-19 medical isolation: a qualitative study.
      ]. It is necessary for nurses working in this field to know how the COVID-19 epidemic affects patients’ self-management. This study was planned with the aim of determining the sociodemographic and disease-related characteristics of individuals with type 2 diabetes, and the effect on their diabetes self-management of the changes which the COVID-19 pandemic has caused in their lives.

      2. Methods

      The research was a cross-sectional descriptive type of study.

      2.1 Research hypotheses

      H0: The COVID-19 pandemic has no effect on self-management in patients with type 2 dibetics.

      H1: The COVID-19 pandemic has an effect on self-management in patients with type 2 dibetics.

      2.2 Study sample and participants

      The population of the research comprised a minimum of 295 individuals from among those (N = 1250) who attended an endocrinology clinic and outpatients’ department in 2019 and 2020, with an error margin of 0.05 and a confidence interval of 95%. The research sample consisted of the 378 individuals with type 2 diabetes who attended the endocrinology clinic and outpatients’ department of a government hospital between 21 December 2020 and 1 April 2021.

      2.3 Inclusion criteria

      Individuals were included in the study who had received a diagnosis of type 2 diabetes at least one year previously, who were aged 18 or more, who were literate and had no communication problems, whose physical and cognitive levels were such that they could answer the forms which were planned for use in the research, and who agreed to participate in the research.

      2.4 Exclusion criteria

      Those who had recently had a running nose, a fever, a cough or breathing difficulties, those with a diagnosis of type 1 diabetes, those who were under the age of 18, those with a communication problem, and those who did not agree to participate in the study were not included. Seven individuals who refused to take part in the study were not included.

      2.5 Data collection tools

      2.5.1 Patient identification form

      This form was prepared by the researchers in accordance with the literature [
      • Shi C.
      • Zhu H.
      • Liu J.
      • Zhou J.
      • Tang W.
      Barriers to self-management of type 2 diabetes during covid-19 medical isolation: a qualitative study.
      ,
      • Eroglu N.
      • Sabuncu N.
      Adaptation of diabetes self management questionnaire to turkish society: validity and reliability study.
      ,
      • Sayeed K.A.
      • Qayyum A.
      • Jamshed F.
      • Gill U.
      • Usama S.M.
      • Asghar K.
      • Tahir A.
      Impact of diabetes-related self-management on glycemic control in type II diabetes mellitus.
      ,
      • Al-Qahtani A.M.
      Frequency and factors associated with inadequate self-care behaviors in patients with type 2 diabetes mellitus in Najran, Saudi Arabia. Based on diabetes self-management questionnaire.
      ], and consisted of questions on information concerning sociodemographic characteristics and characteristics relating to illness and COVID-19.

      2.5.2 Visual analog scale (VAS)

      A visual analog scale was used in the research to evaluate anxiety and stress. The VAS was presented as a horizontal graph from 1 (nothing) to 10 (extreme) [
      • Lesage F.-X.
      • Berjot S.
      • Deschamps F.
      Clinical stress assessment using a visual analogue scale.
      ]. The individuals with type 2 diabetes were asked to mark their levels of stress and anxiety during the COVID-19 pandemic on the scale.

      2.5.3 Diabetes Self-Management Questionnaire (DSMQ)

      This scale was developed by Schmitt et al. in 2013 with the aim of investigating the relation between diabetic self-management in diabetic patients and glycemic control [
      • Schmitt A.
      • Gahr A.
      • Hermanns N.
      • Kulzer B.
      • Huber J.
      • Haak T.
      The diabetes self-management questionnaire (DSMQ): development and evaluation of an instrument to assess diabetes self-care activities associated with glycaemic control.
      ]. Validity and reliability were tested for Turkish by Eroglu and Sabuncu in 2018 [
      • Eroglu N.
      • Sabuncu N.
      Adaptation of diabetes self management questionnaire to turkish society: validity and reliability study.
      ].
      The DSMQ is an individual evaluation scale of 16 items. Item 16 is not included in any subscales. The scale includes four subscales: glucose management (1, 4, 6, 10, 12), diet control (2, 5, 9, 13), physical activity (8, 11, 15), and use of health services (3, 7, 14). Participants were asked to answer taking into account their condition in the preceding eight weeks. The scale was of four-way Likert type, and each item on the scale was scored from 0 to 3 (0 does not apply to me, 1 applies to me a little, 2 apples considerably to me, 3 very much applies to me). Items 5, 7, 10, 11, 12, 13, 14, 15 and 16 on the scale were scored in reverse. The lowest possible score on the scale was 0, and the highest was 10. A score approaching 10 indicated greater diabetic self-management. The Cronbach alpha coefficient of the scale was 0.850, and was found to be 0.875 in our study.

      2.6 Data collection

      During the research, care was taken to take protective measures regarding the COVID-19 pandemic. Data collection was performed on the five working days of the week between 13.00 and 17.00 in the afternoon when there were fewer patients. Because of the COVID-19 pandemic, the researcher and the patients wore masks and social distancing of at least 1.5 m was maintained during data collection. The researcher handed out the data collection forms to the patients for them to complete, and took them back after completion. Form completion took approximately 10–15 min.
      The most recently measured values of patients’ pre and post-COVID-19 HbA1c, fasting blood sugar (FBS), diastolic blood pressure and systolic blood pressure were taken from their files. FBS levels were calculated from the mean of the patients’ FBS levels of the previous seven days.

      2.7 Data analysis

      Data analysis was performed with the program IBM SPSS v25 (Chicago, USA). Examination for normal distribution of data was performed with skewness–kurtosis and the Kolmogorov–Smirnov test. For descriptive statistics, arithmetic mean ± standard deviation, numerical values and percentages were used. The Wilcoxon test was used for data which did not show normal distribution in the statistical analysis, while in the analysis of data which showed normal distribution, the independent sample t test, the one-way anova test and binary logistic regression were used. The level of statistical significance was taken as p < 0.05.

      2.8 Ethics

      This study was carried out in accordance with the principles of the Helsinki Declaration. Permission to conduct the study was obtained from the Scientific Research Studies Commission on COVID-19 from the internet site of the Ministry of Health of the Republic of Turkey. Also, written permission No. 2020/13-58 was obtained from the Human Research Ethics Committee of a university. Institutional permission No. 7201737-604.02 dated 29 December 2020 was also obtained in writing from the relevant Province Health Directorate of the government hospital where the research was conducted. Written approval was obtained from the individuals with type 2 diabetes who voluntarily participated in the study after they had been given information on the aims of the research.

      3. Results

      The mean age of the individuals with type 2 diabetes who participated in the research was 52.37 ± 11.37 years, and 47.8% were aged between 31 and 65 years. It was found that 56.8% were overweight, 62.7% were male, 90.5% were married, 50.5% lived in the provincial capital, 29.9% were educated to primary school level, 54% had lower income than expenditure, 48.4% were working and 35.7% were retired. Also, 44.7% had first-degree relatives with diabetes, 37.3% had had a diagnosis of diabetes for 12 years or more, 24.6% used insulin, and 88.4% had received education regarding diabetes (Table 1).
      Table 1Sociodemographic and COVID-19 pandemic-related characteristics of individuals with type 2 diabetes (n = 378).
      CharacteristicsMean ± SD
      Age52.37 ± 11.37
      n%
      Age
      31−6518147.8
      >6516944.7
      Body mass index (kg/m2)
      18.9–24.9 (normal)16343.1
      25.0 or over (overweight)21556.8
      Sex
      Male23762.7
      Female14137.3
      Marital status
      Married34290.5
      Single369.50
      Place of residence
      City19150.5
      Town13535.7
      Village5213.8
      Education level
      Literate6517.2
      Primary school11329.9
      High school10828.6
      University9224.3
      Monthly income
      Income less than expenses20454
      Income equal to expenses16142.6
      Income greater than expenses133.4
      Work
      Working18348.4
      Not working16543.7
      No longer working307.9
      Profession
      Retired13535.7
      Office worker10427.5
      Housewife6617.5
      Manual worker4311.4
      Self-employed307.9
      Family history of diabetes
      First degree relatives16944.7
      Second degree relatives11630.7
      None9324.6
      Time since diabetes diagnosis
      1–5 years12633.3
      6–11 years11129.4
      12 years or more14137.3
      Diabetes treatment
      Insulin therapy9324.6
      Medical nutrition treatment8322
      Oral hypoglycemic agents7319.3
      Medical nutrition + insulin therapy6216.4
      Insulin + oral hypoglycemic agents369.5
      No treatment318.2
      Education on diabetes
      Yes33488.4
      No4411.6
      Variablesn%
      Effect of COVID-19 pandemic on diabetes disease management
      Yes21456.6
      No16443.4
      If yes, how has it affected diabetes disease management?
      Negatively17179.9
      Positively4320.0
      Positive effects of the COVID-19 pandemic on diabetes disease management
      Exercising by walking more regularly164.3
      Going to the hospital for check-ups more often154
      Spending more time with the family123.2
      Negative effects of the COVID-19 pandemic on diabetes disease management
      Inability to exercise by walking8841.1
      Worry about COVID-19 infection when gong to the doctor5224.2
      Arguing with family3516.3
      Wanting to eat more2813
      Low morale from staying at home for a long time115.1
      Smoking
      I don’t smoke19050.3
      No change13535.7
      I smoke less359.3
      I smoke more184.8
      Going to health institutions
      I go less21757.4
      No change14538.4
      I go more164.2
      Support from health professionals
      Less17646.6
      No change17045
      More328.5
      Support from family members
      No change13034.4
      More12633.3
      Less12232.3
      Anxiety
      More23361.6
      No change12132
      Less246.3
      Stress
      More23461.9
      No change12031.7
      Less246.3
      Sleep quality
      Worse17446
      No change10327.2
      Better10126.7
      The COVID-19 pandemic had affected the diabetes management of 56.6% of the individuals with type 2 diabetes, and 79.9% of these stated that this effect had been negative. It was stated that this negative effect mostly (41.1%) arose from not being able to exercise by walking. According to their statements, 9.3% were smoking more during the COVID-19 pandemic, 57.4% went to health institutions less and 46.6% sought less support from health professionals, while 34.4% stated that there was no change in the support which they obtained from family members. Finally, 61.6% of the individuals stated that during the COVID-19 pandemic their anxiety increased, 61.9% that their stress increased, and 46% that their sleep quality was worse (Table 1).
      The total mean score on the DSMQ during the COVID-19 pandemic of the individuals with type 2 diabetes who participated in the research was 5.25 ± 1.04. Examining the mean scores of the DSMQ and its subscales, the following scores were found: glucose management 5.18 ± 0.24, diet control 5.20 ± 1.15, physical activity 5.10 ± 0.22, and use of health services 5.24 ± 0.56. The individuals with type 2 diabetes had a total mean VAS anxiety score during the pandemic of 7.32 ± 1.56, and a total mean stress VAS score of 7.06 ± 1.62.
      Significant differences were found when comparing the values before and during the COVID-19 pandemic of HbA1c, fasting blood sugar, diastolic blood pressure and systolic blood pressure (p < 0.001, p < 0.001, p = 0.004, p < 0.001) (Table 2).
      Table 2Metabolic variables of individuals with type 2 diabetes before and during the COVID-19 pandemic.
      VariablesPre-testPost-test
      Median(min–max)Median (min–max)Z(p)
      HbA1c (%)7.03(5.08−8.24)8.4(5.12−8.28)−3.522(0.000)
      Z: Wilcoxon test.
      Fasting blood sugar (mg/dl)130(92−170)135(95−199)−11.644(0.000)
      Z: Wilcoxon test.
      Diastolic blood pressure (mmHg)89.00(60.00−123.00)91.00(65.00−125.00)−2.906(0.004)
      Z: Wilcoxon test.
      Sistolic blood pressure (mmHg)129.00(90.00−170.00)131.50(92.00−174.00)−5.349(0.000)
      Z: Wilcoxon test.
      a Z: Wilcoxon test.
      Table 3 shows whether there was a difference in the participants’ DSMQ total and subscale mean scores according to their sociodemographic and COVID-19-related characteristics. According to this, The DSQ total and diet control and physical activity subscale mean scores of those aged over 65 were significantly lower than those in the 31−65-year age group. Mean scores of total DSMQ and glucose management and physical activity were significantly lower in those with a body mass index (kg/m2: BMI) of 25.0 or more than in those with a BMI of 18.9–24.9. Mean scores of total DSMQ and the subscale of use of health services were significantly lower in males than in females. Mean DSMQ total and glucose management subscale scores were significantly lower in those who were married than in those who were single, and in those whose receipt of support from health professionals decreased compared with those in whom it increased or did not change. The mean scores for the subscales of glucose management and use of health services was significantly lower in those who lived in a village or small town compared to those who lived in a larger town or city. In those who had been diagnosed with diabetes 1–5 years previously, the mean score for the subscale of use of health services was significantly lower than in those who had received a diagnosis 6–11 years previously or 12 or more years previously. The means on the subscale of physical activity were significantly lower in those who were smoking more than in those who were smoking the same or less. A significant difference was found in the total DSMQ and diet control and physical activity subscale mean scores of those who said that the COVID-19 pandemic had had a negative effect on their diabetes management compared with those who said it had not. The mean scores on the subscales of diet control and use of health services were significantly lower in those who worried about getting infected with COVID-19 if they went to a doctor, while the total DSMQ and physical activity subscale mean scores were significantly lower in those who could not exercise by walking. In individuals whose anxiety increased, DSMQ total and diet control and physical activity subscale mean scores were significantly lower than in those in whom it lessened or remained the same. In those whose stress increased or whose sleep quality was worse, total DSMQ and glucose management and physical activity subscale mean scores were found to be significantly lower.
      Table 3Comparison of various socio-demographic and COVID-19 pandemic-related characteristics and total Diabetes Self-Management Questionnaire (DSMQ) and subscale mean scores.
      CharacteristicsGlucose management subscaleDietary control subscalePhysical activity subscaleHealthcare use subscaleDSMQ total
      Mean ± SDMean ± SDMean ± SDMean ± SDMean ± SD
      Age
      31−654.74 ± 0.945.71 ± 0.965.82 ± 0.965.72 ± 1.025.17 ± 2.13
      >654.69 ± 0.925.32 ± 0.955.11 ± 0.845.59 ± 0.905.00 ± 1.95
      Test valuet = −0.518
      Independent Sample t test.
      , p = 0.605
      t = −3.458
      Independent Sample t test.
      , p = 0.001
      t = −2.912
      Independent Sample t test.
      , p = 0.004
      t = 0.268
      Independent Sample t test.
      , p = 0.789
      t = −3.729
      Independent Sample t test.
      , p = 0.000
      Body mass index (kg/m2)
      18.9−24.9 (normal)5.75 ± 0.995.57 ± 1.075.98 ± 0.965.74 ± 1.035.55 ± 2.15
      25.0 and over (overweight)5.57 ± 0.915.45 ± 1.025.93 ± 0.845.66 ± 0.925.52 ± 2.06
      Test valuet = −9.547
      Independent Sample t test.
      , p = 0.045
      t = −0.250
      Independent Sample t test.
      , p = 0.124
      t = −10.390
      Independent Sample t test.
      , p = 0.047
      t = −0.055
      Independent Sample t test.
      , p = 0.956
      t = −11.405
      Independent Sample t test.
      , p = 0.001
      Sex
      Male5.71 ± 0.935.43 ± 1.055.93 ± 0.845.60 ± 0.955.36 ± 1.97
      Female5.71 ± 0.975.59 ± 1.065.97 ± 0.965.88 ± 0.975.82 ± 2.15
      Test valuet = −0.065
      Independent Sample t test.
      , p = 0.948
      t = −1.339
      Independent Sample t test.
      , p = 0.182
      t = −0.394
      Independent Sample t test.
      , p = 0.694
      t = −2.700
      Independent Sample t test.
      , p = 0.007
      t = −2.079
      Independent Sample t test.
      , p = 0.038
      Marital status
      Married5.15 ± 0.925.47 ± 0.925.25 ± 0.915.70 ± 0.985.44 ± 1.86
      Single5.66 ± 1.085.71 ± 1.065.90 ± 0.955.84 ± 0.845.50 ± 2.09
      Test valuet = −2.795
      Independent Sample t test.
      , p = 0.005
      t = −1.246
      Independent Sample t test.
      , p = 0.214
      t = −0.276
      Independent Sample t test.
      , p = 0.783
      t = −0.790
      Independent Sample t test.
      , p = 0.430
      t = −2.737
      Independent Sample t test.
      , p = 0.007
      Place of residence
      City5.82 ± 0.965.55 ± 1.075.98 ± 0.975.93 ± 1.005.71 ± 2.28
      Town5.64 ± 0.945.46 ± 1.055.97 ± 0.945.79 ± 0.915.61 ± 2.06
      Village5.48 ± 0.885.46 ± 1.045.90 ± 0.885.51 ± 0.915.27 ± 2.04
      Test valueF = 2.279
      One-way ANOVA F test.
      , p = 0.054
      F = 0.261
      One-way ANOVA F test.
      , p = 0.770
      F = 0.324
      One-way ANOVA F test.
      , p = 0.723
      F = 4.689
      One-way ANOVA F test.
      , p = 0.010
      F = 1.672
      One-way ANOVA F test.
      , p = 0.189
      Time since diabetes diagnosis
      1−5 years5.76 ± 0.925.47 ± 1.115.02 ± 0.855.41 ± 0.915.18 ± 1.90
      6−11 years5.74 ± 0.895.39 ± 1.075.03 ± 0.905.79 ± 0.975.67 ± 2.23
      12 years or more5.65 ± 1.005.59 ± 0.985.83 ± 0.975.87 ± 0.965.72 ± 2.06
      Test valueF = 0.453
      One-way ANOVA F test.
      , p = 0.636
      F = 1.146
      One-way ANOVA F test.
      , p = 0.319
      F = 1.865
      One-way ANOVA F test.
      , p = 0.157
      F = 7.375
      One-way ANOVA F test.
      , p = 0.001
      F = 2.272
      One-way ANOVA F test.
      , p = 0.105
      Smoking
      I don’t smoke5.71 ± 0.945.58 ± 1.045.20 ± 0.925.71 ± 0.975.66 ± 2.13
      No change5.63 ± 0.935.40 ± 1.015.06 ± 0.895.78 ± 0.955.42 ± 2.01
      I some more5.90 ± 0.955.56 ± 1.074.56 ± 1.204.46 ± 1.074.81 ± 2.53
      I smoke less5.93 ± 0.995.06 ± 1.385.87 ± 0.895.62 ± 0.885.66 ± 1.86
      Test valueF = 0.995
      One-way ANOVA F test.
      , p = 0.395
      F = 1.737
      One-way ANOVA F test.
      , p = 0.159
      F = 2.710
      One-way ANOVA F test.
      , p = 0.045
      F = 0.921
      One-way ANOVA F test.
      , p = 0.431
      F = 1.016
      One-way ANOVA F test.
      , p = 0.386
      Effect of COVID-19 pandemic on diabetes disease management
      Yes5.71 ± 0.975.56 ± 1.085.00 ± 0.945.71 ± 1.015.66 ± 2.16
      No5.70 ± 0.905.40 ± 1.015.88 ± 0.905.70 ± 0.945.38 ± 2.04
      Test valuet = −1.070
      Independent Sample t test.
      , p = 0.284
      t = −2.150
      Independent Sample t test.
      , p = 0.032
      t = −1.918
      Independent Sample t test.
      , p = 0.055
      t = −0.337
      Independent Sample t test.
      , p = 0.736
      t = −2.049
      Independent Sample t test.
      , p = 0.040
      Negative effect of COVID-19 pandemic on diabetes disease management
      Inability to exercise by walking4.05 ± 0.944.95 ± 0.754.28 ± 1.254.60 ± 0.944.14 ± 2.60
      Fear of COVID-19 infection when visiting the doctor4.14 ± 0.374.39 ± 9.774.76 ± 1.014.55 ± 0.994.16 ± 2.03
      Arguing with family4.40 ± 0.884.61 ± 0.964.78 ± 0.944.65 ± 0.955.75 ± 2.44
      Wanting to eat more4.56 ± 0.914.75 ± 0.915.05 ± 0.885.85 ± 0.895.13 ± 2.18
      Low morale because of staying at home for long periods4.65 ± 0.924.71 ± 1.115.20 ± 0.955.38 ± 1.215.30 ± 2.10
      Test valueF = 2.215
      One-way ANOVA F test.
      , p = 0.073
      F = 2.583
      One-way ANOVA F test.
      , p = 0.042
      F = 2.854
      One-way ANOVA F test.
      , p = 0.011
      F = 2.485
      One-way ANOVA F test.
      , p = 0.021
      F = 2.775
      One-way ANOVA F test.
      , p = 0.031
      Support from health professionals
      Less4.35 ± 0.934.32 ± 1.204.78 ± 0.955.53 ± 0.884.57 ± 2.23
      No change4.71 ± 0.944.51 ± 1.024.88 ± 0.955.70 ± 1.035.48 ± 2.00
      More4.90 ± 1.024.51 ± 1.095.06 ± 0.875.75 ± 1.105.77 ± 2.11
      Test valueF = 6.602
      One-way ANOVA F test.
      , p = 0.002
      F = 0.420
      One-way ANOVA F test.
      , p = 0.658
      F = 2.083
      One-way ANOVA F test.
      , p = 0.126
      F = 0.630
      One-way ANOVA F test.
      , p = 0.533
      F = 3.237
      One-way ANOVA F test.
      , p = 0.011
      Anxiety
      More4.72 ± 1.044.61 ± 1.054.20 ± 0.954.82 ± 1.284.19 ± 2.05
      No change4.72 ± 0.954.83 ± 1.114.80 ± 0.654.71 ± 0.974.87 ± 2.21
      Less4.71 ± 0.925.38 ± 0.965.08 ± 0.865.67 ± 0.945.08 ± 2.03
      Test valueF = 0.036
      One-way ANOVA F test.
      , p = 0.965
      F = 3.114
      One-way ANOVA F test.
      , p = 0.046
      F = 7.632
      One-way ANOVA F test.
      , p = 0.001
      F = 1.459
      One-way ANOVA F test.
      , p = 0.234
      F = 7.343
      One-way ANOVA F test.
      , p = 0.001
      Stress
      More4.57 ± 0.894.83 ± 1.094.71 ± 0.825.87 ± 1.024.28 ± 1.98
      No change4.71 ± 0.994.59 ± 1.055.08 ± 0.935.79 ± 0.974.79 ± 2.16
      Less4.93 ± 1.014.40 ± 0.995.07 ± 0.875.65 ± 0.955.62 ± 2.26
      Test valueF = 6.255
      One-way ANOVA F test.
      , p = 0.002
      F = 2.451
      One-way ANOVA F test.
      , p = 0.088
      F = 5.835
      One-way ANOVA F test.
      , p = 0.003
      F = 1.1163
      One-way ANOVA F test.
      ,p = 0.314
      F = 5.783
      One-way ANOVA F test.
      , p = 0.003
      Sleep quality
      Worse4.65 ± 0.874.32 ± 0.994.73 ± 0.855.71 ± 0.884.25 ± 0.86
      No change4.76 ± 0.954.42 ± 1.065.04 ± 0.995.73 ± 0.974.44 ± 1.91
      Better4.77 ± 1.005.63 ± 1.135.03 ± 0.895.75 ± 1.025.76 ± 2.14
      Test valueF = 2.836
      One-way ANOVA F test.
      , p = 0.047
      F = 2.808
      One-way ANOVA F test.
      , p = 0.062
      F = 3.829
      One-way ANOVA F test.
      , p = 0.023
      F = 0.607
      One-way ANOVA F test.
      , p = 0.545
      F = 3.894
      One-way ANOVA F test.
      , p = 0.022
      a Independent Sample t test.
      b One-way ANOVA F test.
      Risk factors affecting the diabetic self-management of individuals with type 2 diabetes in the COVID-19 pandemic were found to be being over the age of 65, male and married, and having had a diagnosis of diabetes for 6–11 years, not being able to exercise by walking in the COVID-19 pandemic, a reduction in support received from health professionals, and increased anxiety and stress (Table 4).
      Table 4Binary logistic regression analysis on COVID-19 pandemic of factors influencing diabetes self-management.
      Univariate
      VariablesBPOR95% CI
      Age >650.195<0.0011.2161.093−1.351
      BMI 25.0 or over−0.0070.9701.0080.686−1.480
      Male gender−0.1080.0430.8980.808−0.997
      Being married−0.2530.0080.7770.645−0.935
      Living in a village or small town−0.0200.7941.0200.880−1.181
      Diabetes diagnosis 6–11 years ago−0.1190.0350.8880.794−0.992
      Circle of friends giving diabetes education−0.0550.4810.9470.813−1.102
      Smoking (increase)−0.1310.0071.0320.862−1.234
      COVID-19 pandemic−0.1640.0211.1380.847−1.039
      Increased immobility in the COVID-19 pandemic (inability to exercise by walking)−0.186<0.0011.0020.770−1.093
      Less support from health professionals during the COVID-19 pandemic−0.2460.0120.7820.646−0.947
      Increased anxiety during the COVID-19 pandemic−0.202<0.0010.8170.733−0.910
      Increased stress during the COVID-19 pandemic−0.1530.0050.8580.772−0.954
      Less sleep during the COVID-19 pandemic−0.0300.6040.9700.866−1.087
      *Significant at level of p < 0.05. OR: odds ratio.

      4. Discussion

      The basis of controlling diabetes in those with type 2 diabetes is the possibility of achieving self-management and making this a lifestyle [
      • Khalooei A.
      • Benrazavy L.
      Diabetes self-management and ıts related factors among type 2 diabetes patients in primary health care settings of kerman, Southeast Iran.
      ]. The restrictions brought in to combat the COVID-19 pandemic have caused a repositioning of health service resources and an interruption of access to care during the pandemic. Strict isolation has had a greater effect on people with non-infectious diseases who need constant care and support [
      • Boulton A.
      Why access to diabetes care must not be another victim of the COVID-19 pandemic.
      ]. In this way, there is concern in Turkey as to how the measures and restrictions regarding COVID-19 are affecting the self-care of individuals with type 2 diabetes. Research on determining the factors affecting diabetes self-management in the COVID-19 pandemic will open new perspectives to the literature.
      Self-management programs arranged to bring under control the health of individuals with type 2 diabetes in situations such as a pandemic serve to strengthen patients. A score approaching 10 on the Diabetes Self-Management Questionnaire (DSMQ) is taken as showing an improvement in diabetes self-management, and so the self-management levels of the individuals with type 2 diabetes participating in our research were low. Studies were found in the literature which were conducted before the COVID-19 pandemic which had similar findings to our research [
      • Totesora D.
      • Ramos-Rivera M.I.
      • Villegas-Florencio M.Q.
      • Reyes-Sia P.N.
      Association of diabetes-related emotional distress with diabetes self-care and glycemic control among adult filipinos with type 2 diabetes mellitus at a tertiary hospital in manila.
      ,
      • Sayeed K.A.
      • Qayyum A.
      • Jamshed F.
      • Gill U.
      • Usama S.M.
      • Asghar K.
      • Tahir A.
      Impact of diabetes-related self-management on glycemic control in type II diabetes mellitus.
      ,
      • Al-Qahtani A.M.
      Frequency and factors associated with inadequate self-care behaviors in patients with type 2 diabetes mellitus in Najran, Saudi Arabia. Based on diabetes self-management questionnaire.
      ]. In a qualitative study by Shi et al. [
      • Shi C.
      • Zhu H.
      • Liu J.
      • Zhou J.
      • Tang W.
      Barriers to self-management of type 2 diabetes during covid-19 medical isolation: a qualitative study.
      ], 11 participants stated that they had inadequate contact concerning their self-management of diabetes during the COVID-19 pandemic. It can be said that the quality of life and health outcomes of individuals with type 2 diabetes are made worse by the COVID-19 pandemic. It is thought that the reason for the low levels of self-management found in individuals with type 2 diabetes may be the uncertainty, fear, anxiety and stress experienced during the COVID-19 pandemic in relation both to disease management and to the pandemic itself.
      In the assessment of the subscales of the DSMQ in our study, the highest mean subscale score was use of health services, and the lowest was physical activity. Although the mean subscale score for use of health services was higher than the other subscales in our study, it is low in comparison with pre-pandemic mean scores in the literature [
      • Totesora D.
      • Ramos-Rivera M.I.
      • Villegas-Florencio M.Q.
      • Reyes-Sia P.N.
      Association of diabetes-related emotional distress with diabetes self-care and glycemic control among adult filipinos with type 2 diabetes mellitus at a tertiary hospital in manila.
      ,
      • Al-Qahtani A.M.
      Frequency and factors associated with inadequate self-care behaviors in patients with type 2 diabetes mellitus in Najran, Saudi Arabia. Based on diabetes self-management questionnaire.
      ]. This shows that the use of health services by individuals with type 2 diabetes and their physical activity levels decreased during the pandemic. In the qualitative study by Shi et al. [
      • Shi C.
      • Zhu H.
      • Liu J.
      • Zhou J.
      • Tang W.
      Barriers to self-management of type 2 diabetes during covid-19 medical isolation: a qualitative study.
      ], a participant with type 2 diabetes stated, “I have a bit of knowledge about physical exercise during the COVID-19 pandemic. I pay a lot of attention to this in my daily life.” This shows that participants had limited knowledge concerning physical exercise during the COVID-19 pandemic. Regular physical activity is an important factor in improving metabolic outcomes and may increase insulin sensitivity and lead to glycemic control. Therefore, physical exercise is of great benefit in preventing the development of complications relating to type 2 diabetes [
      • Pamungkas R.A.
      • Chamroonsawasdi K.
      Self-management based coaching program to improve diabetes mellitus self-management practice and metabolic markers among uncontrolled type 2 diabetes mellitus in Indonesia: a quasi-experimental study.
      ]. In order to protect themselves during the outbreak, diabetic patients are spending more time indoors. Measures taken during the COVID-19 pandemic, isolation and social distancing restrictions have made it difficult for people with diabetes to exercise regularly and remain physically active [
      • Kang J.
      • Chen Y.
      • Zhao Y.
      • Zhang C.
      Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic.
      ,
      • Boulton A.
      Why access to diabetes care must not be another victim of the COVID-19 pandemic.
      ]. In this time, many diabetics have chosen to delay or cancel their health service appointments. This may lead to a reduction in the support which diabetic individuals need to manage their disease and to an increase in the risk of developing complications [
      • Boulton A.
      Why access to diabetes care must not be another victim of the COVID-19 pandemic.
      ].
      In a study by Sayeed et al. [
      • Sayeed K.A.
      • Qayyum A.
      • Jamshed F.
      • Gill U.
      • Usama S.M.
      • Asghar K.
      • Tahir A.
      Impact of diabetes-related self-management on glycemic control in type II diabetes mellitus.
      ], sociodemographic characteristics of the participants such as age, gender, marital status, and time since diabetes diagnosis were similar to those in our study. Also similar to our study, a significant difference was found between the total score on the DSMQ scale and age, gender, marital status and time since diabetes diagnosis. In a study by Al-Qahtani [
      • Al-Qahtani A.M.
      Frequency and factors associated with inadequate self-care behaviors in patients with type 2 diabetes mellitus in Najran, Saudi Arabia. Based on diabetes self-management questionnaire.
      ], a significant difference was found between the total DSMQ scale score and marital status and time since diagnosis of diabetes. A significant difference was reported in a study by Totesora et al. [
      • Totesora D.
      • Ramos-Rivera M.I.
      • Villegas-Florencio M.Q.
      • Reyes-Sia P.N.
      Association of diabetes-related emotional distress with diabetes self-care and glycemic control among adult filipinos with type 2 diabetes mellitus at a tertiary hospital in manila.
      ] between the total DSMQ scale score and age. The mean age of the individuals participating in our research was 52.37 ± 11.37 years and that of the participants in the study by Totesora et al. [
      • Totesora D.
      • Ramos-Rivera M.I.
      • Villegas-Florencio M.Q.
      • Reyes-Sia P.N.
      Association of diabetes-related emotional distress with diabetes self-care and glycemic control among adult filipinos with type 2 diabetes mellitus at a tertiary hospital in manila.
      ] was 54.0 ± 11.5 years. The similar result to that of our study may have arisen from the closeness in the mean ages.
      Only 9–15% of individuals with type 2 diabetes achieved optimal glycemic control [
      • Alshahri B.K.
      • Bamashmoos M.
      • Alnaimi M.I.
      • Alsayil S.
      • Basaqer S.
      • Al-Hariri M.T.
      • Vallaba Doss C.A.S.
      Assessment of self-management care and glycated hemoglobin levels among type 2 diabetes mellitus patients: a cross-sectional study from the kingdom of Saudi Arabia.
      ], and poor glycemic control in diabetic individuals can lead to greater sensitivity to the effects of COVID-19. A viral infection in diabetic individuals can make treatment more difficult because of sudden fluctuations in blood sugar levels and the presence of diabetes complications [
      • Barone M.T.U.
      • Ngongo B.
      • Harnik S.B.
      • de Oliveira L.X.
      • Végh D.
      • de Luca P.V.
      • Pedrosa H.C.
      • Giraudo F.
      • Cardona-Hernandez R.
      • Chaudhury N.
      • Menna-Barreto L.
      COVID-19 associated with diabetes and other noncommunicable diseases led to a global health crisis.
      ]. Diabetes management has become a comprehensive approach which includes lifestyle changes, pharmacological treatment and sometimes surgical interventions [
      • Alshahri B.K.
      • Bamashmoos M.
      • Alnaimi M.I.
      • Alsayil S.
      • Basaqer S.
      • Al-Hariri M.T.
      • Vallaba Doss C.A.S.
      Assessment of self-management care and glycated hemoglobin levels among type 2 diabetes mellitus patients: a cross-sectional study from the kingdom of Saudi Arabia.
      ]. Thus, it is necessary in difficult conditions like the pandemic to encourage lifestyle changes in individuals with type 2 diabetes by defining targets. The HbA1c levels of the type 2 diabetics participating in our research were 7.03% before the pandemic, but rose to a level of 8.4% during the pandemic. The fasting blood sugar levels of the individuals participating in our study were 130 mg/dl before the pandemic, but rose during the pandemic to 135 mg/dl. Also, significant increases were seen in diastolic and systolic blood pressure values during the pandemic compared with the pre-pandemic values. It can be said that factors such as inadequate self-management skills, irregular nutrition, a decrease in physical activity and an increase in stress and anxiety levels make the management of blood sugar and blood pressure more difficult. In a randomized controlled study, Kang et al. [
      • Kang J.
      • Chen Y.
      • Zhao Y.
      • Zhang C.
      Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic.
      ] researched the effectiveness in diabetic individuals of management at a distance over a period of three months by mobile phone using the WeChat app on comprehensive diabetic management. It was found that the fasting blood sugar values of individuals in the control group were higher than those of individuals in the intervention group. Also, although no significant difference was found in diastolic and sistolic blood pressure values in the control group in the COVID-19 pandemic compared with the beginning, a significant decrease was seen in the intervention group [
      • Kang J.
      • Chen Y.
      • Zhao Y.
      • Zhang C.
      Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic.
      ]. Thus, it can be said that the traditional face-to-face medical treatment needs of the individuals with type 2 diabetes participating in our study could not be met.
      In the study by Al-Qahtani [
      • Al-Qahtani A.M.
      Frequency and factors associated with inadequate self-care behaviors in patients with type 2 diabetes mellitus in Najran, Saudi Arabia. Based on diabetes self-management questionnaire.
      ], it was determined that being married and having had a diabetes diagnosis for more than five years were risk factors affecting diabetes self-management. It was determined in a study by Almigbal et al. [
      • Almigbal T.H.
      • Almutairi K.M.
      • Vinluan J.M.
      • Batais M.A.
      • Alodhayani A.
      • Alonazi W.B.
      • Sheshah E.
      • Alhoqail R.I.
      Association of health literacy and self-management practices and psychological factor among patients with type 2 diabetes mellitus in Saudi Arabia.
      ] that age and gender were risk factors affecting diabetes self-management. The results of our study are similar to the pre-COVID-19 period. Also, a reduction in physical activity and the support received from health professionals and an increase in smoking anxiety and stress levels in the COVID-19 pandemic were added to the existing picture. Support from health professionals is important for diabetic patients to develop their self-management. In a study by Khalooei and Benrazavy [
      • Khalooei A.
      • Benrazavy L.
      Diabetes self-management and ıts related factors among type 2 diabetes patients in primary health care settings of kerman, Southeast Iran.
      ] conducted with diabetic individuals, the state of receiving support from health professionals was determined to be a significant risk factor with regard to diabetes self-management. In the pre-COVID-19 period, routine follow-up and home visits were important strategies to support elf-management. These strategies increase individuals’ trust and expectations with regard to maintaining positive behaviors [
      • Pamungkas R.A.
      • Chamroonsawasdi K.
      Self-management based coaching program to improve diabetes mellitus self-management practice and metabolic markers among uncontrolled type 2 diabetes mellitus in Indonesia: a quasi-experimental study.
      ]. However, health outcomes have deteriorated in the COVID-19 period because of factors such as increasing anxiety, stress and social isolation, difficulty in adhering to drug treatment, reduced physical activity, increased periods of immobility and changing eating habits which affect lifestyle behaviors, and disrupted sleep quality [
      • Highton P.J.
      • Hadjiconstantinou M.
      • Schreder S.
      • Seidu S.
      • Davies M.
      • Khunti K.
      COVID-19, ethnicity and cardiometabolic disease self-management in UK primary care.
      ]. The results of the research supported H1: The COVID-19 pandemic has an effect on self-management in people with type 2 diabetes.

      4.1 Limitations

      A limitation of this study is that because it was conducted in one government hospital in the south-east of Turkey, it cannot be generalized. Another limitation is that because the pandemic emerged suddenly, pre-pandemic diabetic self-management could not be assessed.

      5. Conclusions

      It was found as a result of the research that the diabetes self-management levels of individuals with type 2 diabetes during the COVID-19 pandemic were low. Being male, over the age of 65, married, and having had a diagnosis of diabetes for 6–11 years, increased smoking, the COVID-19 pandemic, a reduction in physical activity and support from health professionals, and an increase in anxiety and stress levels were determined to be risk factors affecting diabetes self-management.
      The results of this study show that it is necessary to comprehensively address the factors affecting diabetes self-management in the COVID-19 pandemic and to take the necessary measures. In this regard, it is necessary to plan and implement measures for individuals with type 2 diabetes in particular to take responsibility for their own care and to increase self-management in the COVID-19 pandemic. In order for self-management levels to increase in individuals with type 2 diabetes, it is important that they should be ready to change their self-care plans, that they should easily obtain support from family members and health professionals, and that their skills in increasing physical exercise, managing stress and self-motivation should be developed. It can be said that during the pandemic, it has not been possible to meet the needs of individuals with type 2 diabetes for traditional face-to-face medical treatment. For this reason, self-management skills can be increased by widening access to services such as telemedicine and e-health in order for individuals with type 2 diabetes to manage their own conditions, to determine problems which arise, and in the long term to encourage behavioral changes.

      Funding

      This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

      Declaration of interests

      The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

      CRediT authorship contribution statement

      Hediye Utli: Investigation, Data curation, Methodology, Formal analysis, Writing - original draft preparation. Birgül Vural Doğru: Conceptualization, Validation, Supervision, Writing - reviewing and editing.

      Acknowledgements

      The authors thank all patients for their participation in the study.

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