Parental Diabetes Knowledge and its Association with Glycaemic Control in Finnish Children with Type 1 Diabetes

Riina Pironetti^1*, Marja-Terttu Saha², Tiina Luukkaala^3,4, Nina Vuorela^1,2 and Paivi Keskinen^1,2
*Correspondence: Riina Pironetti, Faculty of Medicine and Health Technology, Tampere University, Kauppi Campus, Arvo Building, Arvo Ylpön katu 34, 33520 Tampere, Finland, Email:

Keywords

Diabetes • Paediatrics • Glycaemia • Education • Caregivers • Knowledge • Finland

Glossary

T1D = Type 1 Diabetes; HbA1c = glycosylated haemoglobin; TIR = Time in Range; ISPAD = Intenational Society for Pediatric and Adolescent Diabetes; T2D = Type 2 Diabetes; r = Pearson correlation coefficient; CI = Confidence Intervals; OR = Odds Ratio; IQR = Interquartile Range; SD = Standard Deviation

Introduction

Type 1 Diabetes (T1D) is one of the most common chronic diseases in childhood [1,2]. In 2021, approximately 108,300 children and adolescents aged < 15 years were diagnosed with T1D globally. An estimated 1,211,900 children and adolescents aged < 20 years are living with the condition [2,3]. In Finland, the incidence of T1D in children aged < 15 years has been the highest in the world for several decades, with 52.2 cases per 100,000 recorded in 2018 [4]. Glycated haemoglobin (HbA1c) < 53 mmol/mol and a Time in Range > 70% are recommended by the American Diabetes Association and the International Society for Pediatric and Adolescent Diabetes (ISPAD) for most children with T1D [5,6]. The Diabetes Control and Complication Trial was the first study to clearly demonstrate that prolonged optimal glycaemic control reduces the risk of microvascular and macrovascular complications in patients with T1D [7].

As stated in the ISPAD Guidelines, education is the foundation of effective diabetes care [8]. Family-oriented self-management education is a key component in achieving treatment goals in T1D [6,8]. Nutritional education, including systematic carbohydrate assessment and the use of insulin-to-carbohydrate ratios, supports the optimisation of insulin treatment [9,10]. Interpretation of glucose self-monitoring data, increasingly carried out by continuous glucose sensoring, requires an advanced skill to guide adjustment of insulin treatment and maintain target glycaemia. Age-appropriate physical activity is also an important component of T1D management [6,11]. The use of hybrid closed-loop systems has shown potential to improve both glycaemic outcomes and quality of life in children with TID [12,13]. To achieve these outcomes, it is crucial to apply all available methods to enhance adherence to intensive insulin therapy. Therefore, structured and ongoing diabetes education for patients and families is essential [6,8]. The goal is to help families integrate diabetes-specific knowledge into daily diabetes management tasks.

This study aimed to determine whether caregiver knowledge of diabetes affects glycaemic control in children and adolescents with T1D. We also assessed the factors associated with parental knowledge of diabetes.

Materials and Methods

Participants and protocol

This cross-sectional study was conducted at the paediatric diabetes outpatient clinic of Tampere University Hospital, Finland. Children and adolescents with T1D and their families were invited to participate in the study. Eligibility criteria included age between 1 and 16 years, a T1D duration of at least 1 year and Finnish-speaking family members. If multiple siblings in a family had T1D, only the oldest was included. The study was approved by the Ethics Committee of the Pirkanmaa Hospital District.

During an outpatient clinic visit, children and their guardians received information about the study and gave their written informed consent to participate. Caregivers completed a questionnaire on family background information and one or both guardians completed the diabetes knowledge test during the same appointment. If there was not enough time to complete the questionnaire at the clinic, participants were given a pre-paid envelope to mail their responses from home. A healthcare professional collected diabetes-related information from the patient’s medical records. Data collection took place during 2020–2021.

At the time of the study, 429 children aged < 16 years were followed up in the paediatric diabetes clinic of the Tampere University Hospital. Of these, 334 children were eligible for inclusion. The most common reason for ineligibility was a short duration of diabetes. Among the invited families, 199 (60%) agreed to participate in the study (Figure 1). No information was collected from those patients who declined to participate.

Measurements

Background information questionnaire: The questionnaire was developed specifically for this study to collect background information. It included the caregivers’ level of education (primary school, high school graduate, college, university of Applied Sciences, university, or other) and caregivers’ diabetes status (diabetes: yes/no, type of diabetes: T1D / Type 2 Diabetes (T2D) / other, duration of diabetes, mode of treatment, the most recent glycosylated haemoglobin (HbA1c) and possible complications related to diabetes).

Diabetes knowledge test: A diabetes knowledge test for parents was specifically developed for this study. Prior to recruitment, the questionnaire was tested in our clinic by paediatric diabetes nurses (n = 7) and nurses from the paediatric neurological clinic (n = 6). The paediatric neurology nurses were selected as controls because they are healthcare professionals without specific expertise in T1D and their background was considered most comparable to that of the parents of children with T1D. In contrast, the diabetes nurses from the paediatric clinic were considered the most competent controls to complete the questionnaire and their diabetes-related knowledge was assumed to be at a high level. The diabetes nurses achieved an average score of 97% correct answers (range: 93–98%), whereas the paediatric neurology nurses achieved an average of 64% (range: 56–82%). These results suggest that the test was sufficiently specific and appropriately challenging to assess diabetes knowledge and thus suitable for use in this study.

The diabetes knowledge test (Supplementary material) was intended to be completed by one parent; however, completion by both parents was also permitted. Caregiver 1 was designated as the female parent and caregiver 2 as the male parent. In the case of a female couple, the second mother was designated as caregiver 2. We primarily used the percentage of correct answers from caregiver 1. The questionnaire consisted of multiple-choice questions and true-false-uncertain questions, with each correct answer awarded one point. The questionnaire consisted of nine items that focused on daily life with T1D: glucose monitoring and self-analysis (2 questions), insulin (12 questions), diet (3 questions), targets of glycaemic control (8 questions), causes and treatment of hyperglycaemia (8 questions), ketones and diabetic ketoacidosis (9 questions), hypoglycaemias and use of glucagon (9 questions), physical activity (7 questions) and infections (3 questions) (Supplementary Material). Higher scores indicated better diabetes knowledge. The sum score of the scale ranged from 0 to 61. For data analysis, scores were converted to percentages of correct answers (0–100 %).

Demographic and diabetes measures

Demographic data (sex and age) and data related to diabetes (HbA1c, insulin delivery method and time from diagnosis) were collected from the patients’ medical records at the time of recruitment. HbA1c was determined using either a point-of-care analyser (Siemens DCA Vantage) or a standard immunological assay in a laboratory. The insulin pumps and sensors in use at the time of recruitment were MiniMed™ 640G, MiniMed™ 670G (Medtronic), Omnipod® Eros, Omnipod DASH® (Insulet Corporation); and respectively FreeStyle Libre 1 or 2 (Abbott), Dexcom G6 (Dexcom Inc.) and Guardian™ 3 or 4 (Medtronic).

Data analysis

Participant characteristics were described by using frequencies with percentages, means with standard deviation, or medians with interquartile ranges and/or ranges. For continuous variables, differences between groups were tested using an independent samples t-test or one-way analysis of variance. For categorical variables, Pearson’s chi-square or Fisher’s exact test was used.

In the subgroup analysis of parental T1D, the data of caregivers with other types of diabetes than T1D (T2D n=6, gestational diabetes n=8, other n=1) were excluded to focus specifically on T1D.

Differences in the percentage of correct answers on the knowledge test between caregivers were tested using a paired samples t-test. The correlation between caregiver 1 and caregiver 2 scores was calculated using the Pearson correlation coefficient (r) with 95% Confidence Intervals (CI), p-values and the number of paired responses reported.

For analysis of the combined dataset, we primarily used the percentage of correct answers from caregiver 1. If caregiver 1 data were missing, caregiver 2 responses were used. This approach was justified by a moderate correlation between the two caregivers' scores (Figure 2).

The risk factors for achieving optimal glycated haemoglobin (HbA1c) levels were examined using logistic regression analyses. The threshold for the optimal HbA1c level (<53 mmol/mol) was defined according to the current guidelines [5,6]. Both unadjusted and multivariable adjusted logistic regression models were conducted to explain an optimal glucose level using insulin delivery method (multiple-dose injections/pump), sex (girl/boy), continuous age of children, time from T1D diagnosis and caregiver’s knowledge of diabetes as candidates for explanation. Owing to the skewed distribution of time since diagnosis, values were log-transformed using the natural logarithm. Results were reported using Odds Ratios (OR) with 95% Confidence Intervals (CI) and p-values. To confirm the findings, we also used backward stepwise linear regression analysis (data not shown).

Statistical analyses were carried out with SPSS (SPSS Inc., IBM Corp, Armonk, NY, USA), version 28.0. The two-sided p-value <0.05 was considered statistically significant. No adjustment for multiple tests was applied and p-values should be interpreted exploratorily only.

Results

General characteristics

Altogether, 199 children and adolescents (52% boys) with a median age of 11 years participated in the study. At recruitment, the median time since T1D diagnosis was 4 years and the median HbA1c was 59 mmol/mol (range 39–130). The most common mode of insulin delivery was an insulin pump (54%, n=107). The remaining children were treated with multiple daily insulin injections.

The diabetes knowledge test was completed by 187 female caregivers, referred to here as caregiver 1. The number of responses from caregiver 2 was 184. Two of the caregivers 2 were females (1%). The background information questionnaire was completed by at least one of the caregivers in all 199 families. More detailed demographic and diabetes-related data of the caregivers are presented in Table 1.

Parental educational level and diabetes knowledge

Table 2 shows that a higher level of education led to a better score on the diabetes knowledge test in both caregivers (p=0.020 for caregiver 1 and p=0.014 for caregiver 2).

Parental diabetes knowledge within the same family

The diabetes knowledge test was completed by both caregivers in 74 families. The mean difference between the correct response rates of the caregivers was 4.9 percentage points (p<0.001, n=74). The mean percentage of correct answers in the knowledge test was better for the caregiver 1, of whom 100% were females (mean 84.4%, SD 8.5%), than for the caregiver 2 (99% males, mean 79.4%, SD 8.1%).

The percentages of correct answers in the diabetes knowledge test of caregivers correlated moderately and explained each other 24.4% (Figure 2).

Child’s T1D duration and parental diabetes knowledge

The percentage of correct answers in the parental diabetes knowledge test correlated positively with the duration of the child’s T1D. For caregiver 1, the Pearson correlation coefficient r = 0.339 (95% CI 0.197-0.468, p<0.001, n = 165), caregiver 2: r =0.251 (95% CI 0.065-0.420, p = 0.009, n = 108) and combined version of caregivers 1 and 2: r = 0.273 (95% CI 0.139-0.397, p<0.001, n = 199). The association between diabetes knowledge of caregivers and the child’s duration of T1D was not linear. The knowledge seemed to improve with the duration of the disease of the child up to 6 years but then started to decline (Figure 3). Nevertheless, the linear increase in caregiver diabetes knowledge was observed across all age groups during the first 6 years after diagnosis (Figure 4).

Effects of parental T1D on diabetes knowledge among caregivers and glycaemic control of children

Among the study population, 12.6% of the children had a parent with T1D. Parental TID was not associated with higher caregivers’ knowledge of diabetes or improved glycaemic control in the child.

The mean percentage of correct answers for caregiver 1 with T1D was 85.1% (SD 7.8, n=20) and the mean percentage of correct responses of caregiver 2 with T1D was 77.9% (SD 8.0, n=13). No differences were found when these results were compared with caregivers without T1D (caregiver 1: 82.5%, SD 8.8, n = 145, p = 0.226 and caregiver 2: 79.2%, SD 7.7, n = 95, p = 0.570).

The mean HbA1c of children having a parent with T1D was 64.1 mmol/mol (SD 14.2, n = 25) and the mean HbA1c of those without a parent with T1D was 60.4 mmol/mol (SD 12.3, n = 174, p = 0.175).

Glycaemic control of the child and parental diabetes knowledge

We found no linear relationship between the HbA1c values of children and the percentages of correct answers provided by caregivers. For caregiver 1, the Pearson correlation coefficient was r = 0.057 (95% CI: -0.097 to 0.208), with n = 165 and p = 0.470. Similarly, for the second caregiver, the correlation coefficient was r = -0.081 (95% CI: -0.266 to 0.110), with n = 108 and p = 0.406. Additionally, the combined responses from both caregivers showed no significant positive correlation with the glycaemic control of the children (Figure 5).

The glycaemic control deteriorated as the child grew and when the time from diagnosis increased (Table 3). However, the interaction of greater parental diabetes knowledge together with insulin pump treatment was associated with better T1D control.

Discussion

In the early years following diagnosis, parents are usually responsible for their child’s therapy and glycaemic control. Structured education covering both the medical and psychosocial aspects of diabetes and its treatment, provided by a multidisciplinary paediatric diabetes team, is essential for developing adequate treatment skills and supporting families in achieving and maintaining optimal glycaemic control.

We did not find a correlation between parental diabetes knowledge and glycaemic control of the child, which is consistent with findings by Stefanowicz, et al. [14]. However, other studies have reported that greater parental knowledge is associated with lower HbA1c [15-18]. Given the relatively high level of diabetes knowledge among parents in our study population, reflected by their higher average scores compared to health care personnel not daily involved in diabetes care, further improvement in knowledge may not significantly impact the metabolic control of the children. The metabolic control of the child may depend more on other factors such as parent-child relationship, balance of parental involvement and acceptance of the disease [19].

In our cohort, only insulin pump users appeared to benefit from higher diabetes knowledge of the parents. This may be owing to retraining in diabetes skills or increased motivation for diabetes care at the time of switching to pump treatment. After several years of managing T1D within the family, caregivers’ daily diabetes care may have become a routine without motivation to acquire further knowledge. At this stage, switching to a different insulin delivery modality may improve both caregiver knowledge and motivation, potentially leading to better metabolic control of their child. The use of hybrid closed-loop insulin pump systems has already changed the standard of diabetes knowledge needed in daily diabetes care. In the future, as fully closed-loop insulin pumps become available, achieving glycaemic control may depend even less on the user’s knowledge and depend more on other factors such as acceptance of the disease as well as trust in the device.

In our study, we found a significant association between higher parental educational levels and better knowledge of diabetes among caregivers. However, previous studies have reported conflicting results regarding the influence of parental academic background on their understanding of diabetes and treatment proficiency [15,16,20,21]. Differences in parental educational level should likely be considered more carefully by diabetes care teams when designing and delivering family education.

There was a positive correlation between the test scores of the two caregivers within the same family. However, the primary caregivers who were mothers in our study had slightly better knowledge of diabetes, probably reflecting their greater responsibility for the daily care of the child with diabetes. This finding aligns with previous studies [15,18,22]. In clinical practice, mothers tend to attend outpatient visits more frequently than fathers, thereby receiving more training in diabetes management skills. Additionally, mothers may be more likely to seek out additional information on diabetes care through social media or the internet.

As parents are responsible for, or at least play a major role in the daily treatment of their child’s diabetes during the early years after diagnosis, it was reassuring to observe that parents’ diabetes knowledge improved over time. The downward trend in parental knowledge after the child has had the disease for > 9–10 years may be related to the increased responsibility of older children and adolescents for managing their own diabetes as well as the reduced involvement of parents in daily treatment decisions. However, it is unlikely that the often-deteriorating glycaemic control observed during adolescence could be significantly improved by increasing their parents’ knowledge of diabetes. This is likely influenced more by psychosocial and family-related factors [23,24].

In the present study, the caregiver’s own diabetes did not improve either the metabolic control of the child or the diabetes knowledge of the parent. Owing to the small number of caregivers with diabetes, these findings did not reach statistical significance. This aligns with earlier studies demonstrating that a family history of diabetes does not necessarily improve the metabolic control of a child with T1D [25-28]. However, the level of diabetes competency of caregivers was not assessed in those studies. Therefore, our study provides new and valuable insights into the diabetes knowledge of caregivers with T1D. Outdated care practices, higher glycaemic targets, or a heightened fear of hypoglycaemia among caregivers with T1D may partly explain the poorer diabetes management in their children. Emphasizing the importance of modern, tighter glycaemic targets [5,6] at the time of a child’s diagnosis is essential, particularly when a parent has T1D, to prevent the transfer of outdated or incorrect practices and treatment goals into the child’s diabetes care.

This study had certain limitations. First, a validated diabetes knowledge test specifically for Finnish paediatric patients with T1D and their caregivers is currently unavailable for evaluating knowledge of daily diabetes care. Most existing T1D knowledge instruments are outdated, few are designed for paediatric populations and none have been translated into Finnish [29-34]. In research contexts, the most widely used tool is the Revised Diabetes Knowledge Test, which targets general diabetes knowledge test for both T1D and T2D [34]. Among the instruments developed specifically for paediatric T1D, most focus primarily on nutrition or carbohydrate counting, or are too time-consuming to be feasible within the time constraints of outpatient visits [22,35,36].The M-WIKAD instrument, a shorter assessment designed for paediatric T1D, similarly focuses on general diabetes knowledge and does not cover topics such as diabetes technology [29]. The recent validation of the KAT-1 paediatric T1D knowledge test [37] represents a valuable advancement, but the instrument contains questions that limit its feasibility for clinical use, including items specific to US healthcare systems (e.g., insurance) and differences in units used. Additionally, it is available only in English. For this study, we developed a brief and practical knowledge assessment tailored to paediatric diabetes. Owing to limited validation, precise thresholds for excellent or poor performance on the test could not be established. However, pre-testing of the assessment with paediatric diabetes nurses and paediatric neurological nurses suggested that it functioned adequately. Second, the relatively limited sample size limited the statistical power of our analyses. For example, the number of participants with familial diabetes was small, so those findings should be interpreted with caution. Moreover, of the study sample lacked ethnic diversity. Evaluating the diabetes knowledge of caregivers from a broader range of cultural and linguistic backgrounds would be valuable, as their knowledge levels and, consequently, the glycaemic control of their children, may differ from those of Finnish-speaking parents.

Conclusion

Comprehensive diabetes education is essential for developing treatment competencies, fostering motivation and promoting family involvement in achieving treatment goals. In this study, once parents had attained a basic understanding of diabetes and its management, further increases in parental diabetes knowledge did not appear to enhance the metabolic control of their children, except among insulin pump users. Therefore, improving a child’s glycaemic control may require approaches beyond strengthening parental diabetes education. These findings should be considered when prioritising healthcare resources aimed at improving diabetes management in children and adolescents to achieve optimal glycaemic control. Diabetes care teams should be aware that parental diabetes does not inherently improve a child’s glycaemic control or enhance parental knowledge of diabetes care.

Data Availability

The data generated and analysed during the current study are available from the corresponding author upon reasonable request.

Conflict of Interest

The authors declare no potential conflict of interest.

Funding Source

This work was supported by The Foundation for Paediatric Research and The Finnish Medical Foundation [Grant agreement number 5687].

Author Contributions

Credit

Acknowledgement

All families participating in the study are acknowledged for their valuable contribution. The authors also thank the personnel in the study clinic for recruiting the families.

Results

1. “Consensus Statement – Core Tenets of CCMS 2021-08.”
2. Ogle, G.D., S. James, D. Dabelea and C. Pihoker, et al. “Global estimates of incidence of type 1 diabetes in children and adolescents: Results from the International Diabetes Federation Atlas.” Diabetes Res Clin Pract 183 (2022): 109083.

Google Scholar, Cross Ref, Indexed at

3. Magliano, Dianna J. and Edward J. Boyko. “IDF Diabetes Atlas.” Diabetes Res Clin Pract 186 (2022): 109785

Google Scholar, Indexed at

4. Parviainen, Anna, Anna But, Heli Siljander and Mikael Knip. “Decreased incidence of type 1 diabetes in young Finnish children. ” Diabetes care 43 (2020): 2953-2958.

Google Scholar, Cross Ref, Indexed at

5. DiMeglio, Linda A., Carlo L. Acerini, Ethel Codner Dujovne and Maria E. Craig, et al. “ISPAD Clinical Practice Consensus Guidelines 2018: Glycemic Control Targets and Glucose Monitoring for Children, Adolescents and Young Adults with Diabetes.” Pediatr Diabetes 19 (2018): 105–114.

Google Scholar, Cross Ref, Indexed at

6. American Diabetes Association Professional Practice Committee. “14. Children and Adolescents: Standards of Medical Care in Diabetes—2022.” Diabetes Care 45 (2022): S208–S231.

Google Scholar, Cross Ref, Indexed at

7. Nathan, David M. and DCCT/EDIC Research Group. “The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study at 30 Years: Overview.” Diabetes Care 37 (2014): 9–16.

Google Scholar, Cross Ref, Indexed at

8. Olinder, Anna Lindholm, Matthew DeAbreu, Stephen Greene and Anne Haugstvedt, et al. “ISPAD Clinical Practice Consensus Guidelines 2022: Diabetes Education in Children and Adolescents.” Pediatr Diabetes 23 (2022): 1229.

Google Scholar, Cross Ref, Indexed at

9. Bayram, Sinem, Gül Kızıltan and Onur Akın. “Effect of Adherence to Carbohydrate Counting on Metabolic Control in Children and Adolescents with Type 1 Diabetes Mellitus.” Ann Pediatr Endocrinol Metab 25 (2020): 156–162.

Google Scholar, Cross Ref, Indexed at

10. Marigliano, Marco, Anita Morandi, Maddalena Maschio and Alberto Sabbion, et al. “Nutritional Education and Carbohydrate Counting in Children with Type 1 Diabetes Treated with Continuous Subcutaneous Insulin Infusion: The Effects on Dietary Habits, Body Composition and Glycometabolic Control.” Acta Diabetol 50 (2013): 959–964.

Google Scholar, Cross Ref, Indexed at

11. Moser, Othmar, Michael C. Riddell, Max L. Eckstein and Peter Adolfsson, et al. “Glucose Management for Exercise Using Continuous Glucose Monitoring (CGM) and Intermittently Scanned CGM (isCGM) Systems in Type 1 Diabetes: Position Statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) Endorsed by JDRF and Supported by the American Diabetes Association (ADA).” Diabetologia 63 (2020): 2501–2520.

Google Scholar, Cross Ref, Indexed at

12. Breton, Marc D., Lauren G. Kanapka, Roy W. Beck and Laya Ekhlaspour, et al. “A Randomized Trial of Closed-Loop Control in Children with Type 1 Diabetes.” N Engl J Med 383 (2020): 836–845.

Google Scholar, Cross Ref, Indexed at

13. DeBoer, Mark D., Marc D. Breton, Christian Wakeman and Elaine M. Schertz, et al. “Performance of an Artificial Pancreas System for Young Children with Type 1 Diabetes.” Diabetes Technol Ther 19, (2017): 293–298.

Google Scholar, Cross Ref, Indexed at

14. Stefanowicz, Anna, Malgorzata Mysliwiec and Elzbieta Adamkiewicz-Drozynska. “Parental Knowledge and Metabolic Control of Children and Young Adults with Type 1 Diabetes.” Arch Med Sci 14 (2018): 52–59.

Google Scholar, Cross Ref, Indexed at

15. Martin, Delphine, Caroline Elie, Claire Dossier and Cécile Godot, et al. “Diabetes Knowledge in Adolescents with Type 1 Diabetes and Their Parents and Glycemic Control.” Pediatr Diabetes 18 (2017): 559–565.

Google Scholar, Cross Ref, Indexed at

16. Stallwood, Lynda. “Relationship Between Caregiver Knowledge and Socioeconomic Factors on Glycemic Outcomes of Young Children with Diabetes.” J Spec Pediatr Nurs 11 (2006): 158–165.

Google Scholar, Cross Ref, Indexed at

17. Butler, Deborah A., Jessica B. Zuehlke, Alison Tovar and Lisa K. Volkening, et al. “The Impact of Modifiable Family Factors on Glycemic Control Among Youth with Type 1 Diabetes.” Pediatr Diabetes 9 (2008): 373–381.

Google Scholar, Cross Ref, Indexed at

18. Martín, Daniel E. Alonso, M. Belén Roldán Martín, M. Ángeles Álvarez Gómez and Rosa Yelmo Valverde, et al. “Impact of Diabetes Education on Type 1 Diabetes Mellitus Control in Children.” Endocrinol Nutr (Engl Ed) 63 (2016): 536–542.

Google Scholar, Cross Ref, Indexed at

19. Farthing, Pamela, Jill Bally, Donna C. Rennie and Marie Dietrich Leurer, et al. “Type 1 Diabetes Management Responsibilities Between Adolescents with T1D and Their Parents: An Integrative Review.” J Spec Pediatr Nurs 27 (2022): e12395.

Google Scholar, Cross Ref, Indexed at

20. Al-Odayani, Abdulrahman Nasser, Omar Zayyan Alsharqi, Ala’Eddin Mohammad Khalaf Ahmad and Abdulrahman Khazim Al-Asmari, et al. “Children’s Glycemic Control: Mother’s Knowledge and Socioeconomic Status.” Glob J Health Sci 5 (2013): 214.

Google Scholar, Cross Ref, Indexed at

21. Mahfouz, Eman Mohamed, Nashwa Nabil Kamal, Eman Sameh Mohammed and Sara Ahmed Refaei. “Effects of Mothers’ Knowledge and Coping Strategies on the Glycemic Control of Their Diabetic Children in Egypt.” Int J Prev Med 9 (2018): 26.

Google Scholar, Cross Ref, Indexed at

22. Heidgerken, Amanda D., Lisa Merlo, Laura B. Williams and Adam B. Lewin, et al. “Diabetes Awareness and Reasoning Test: A Preliminary Analysis of Development and Psychometrics.” Child Health Care 36 (2007): 117–136.

Google Scholar, Cross Ref, Indexed at

23. Yamaguchi, Miku, Junko Honda and Minae Fukui. “Effects of Parental Involvement on Glycemic Control in Adolescents with Type 1 Diabetes Mellitus: A Scoping Review.” J Fam Nurs 29 (2023): 382–394.

Google Scholar, Cross Ref, Indexed at

24. Pironetti, Riina, Marja‐Terttu Saha, Tiina Luukkaala and Päivi Keskinen. “Sociodemographic Factors Affecting Glycaemic Control in Finnish Paediatric Patients with Type 1 Diabetes.” Endocrinol Diabetes Metab 6 (2023): e452.

Google Scholar, Cross Ref, Indexed at

25. Karges, Beate, Nicole Prinz, Kerstin Placzek and Nicolin Datz, et al. “A Comparison of Familial and Sporadic Type 1 Diabetes Among Young Patients.” Diabetes Care 44 (2021): 1116–1124.

Google Scholar, Cross Ref, Indexed at

26. Fox, Larry A., Mohamed Mubasher, Joseph I. Wolfsdorf and Bruce A. Buckingham, et al. “Characteristics of Youth with Type 1 Diabetes (T1D) with and without a Parent with T1D in the T1D Exchange Clinic Registry.” J Diabetes 8 (2016): 834–838.

Google Scholar, Cross Ref, Indexed at

27. Vakharia, Janaki D., Sungeeta Agrawal, Janine Molino and Lisa Swartz Topor. “Family History of Diabetes Is Associated with Increased Risk of Recurrent Diabetic Ketoacidosis in Pediatric Patients.” Endocr Pract 26 (2020): 305–311.

Google Scholar, Cross Ref, Indexed at

28. Lebenthal, Yael, Shlomit Shalitin, Michal Yackobovitch-Gavan and Moshe Phillip, et al. “Retrospective Comparative Analysis of Metabolic Control and Early Complications in Familial and Sporadic Type 1 Diabetes Patients.” J Diabetes Complications 26 (2012): 219–224.

Google Scholar, Cross Ref, Indexed at

29. Tsai, Sarah, Susana Patton, Stephen DeLurgio and David D. Williams, et al. “A New Paediatric Diabetes Knowledge Test – M-WIKAD Development and Factor Analysis.” Eur Endocrinol 15 (2019): 1.

Google Scholar, Cross Ref, Indexed at

30. Eigenmann, C. A., Timothy Skinner and R. Colagiuri. “Development and Validation of a Diabetes Knowledge Questionnaire.” Pract Diabetes Int 28 (2011): 166–170d.

Google Scholar, Cross Ref, Indexed at

31. Dunn, Stewart M., Janet M. Bryson, Penelope L. Hoskins and Jan B. Alford, et al. “Development of the Diabetes Knowledge (DKN) Scales: Forms DKNA, DKNB and DKNC.” Diabetes Care 7 (1984): 36–41.

Google Scholar, Cross Ref, Indexed at

32. Zuniga, Julie A., Ya-Ching Huang, So Hyeon Bang and Heather Cuevas, et al. “Revision and Psychometric Evaluation of the Diabetes Knowledge Questionnaire for People With Type 2 Diabetes.” Diabetes Spectr 36 (2023): 345–353.

Google Scholar, Cross Ref, Indexed at

33. Fitzgerald, James T., Martha M. Funnell, George E. Hess and Patricia A. Barr, et al. “The Reliability and Validity of a Brief Diabetes Knowledge Test.” Diabetes Care 21 (1998): 706–710.

Google Scholar, Cross Ref, Indexed at

34. Fitzgerald, James T., Martha M. Funnell, Robert M. Anderson and Robin Nwankwo, et al. “Validation of the Revised Brief Diabetes Knowledge Test (DKT2).” Diabetes Educ 42 (2016): 178–187.

Google Scholar, Cross Ref, Indexed at

35. Rovner, Alisha J., Tonja R. Nansel, Sanjeev N. Mehta and Laurie A. Higgins, et al. “Development and Validation of the Type 1 Diabetes Nutrition Knowledge Survey.” Diabetes Care 35 (2012): 1643–1647.

Google Scholar, Cross Ref, Indexed at

36. Koontz, Michaela B., Leona Cuttler, Mark R. Palmert and MaryAnn O'Riordan, et al. “Development and Validation of a Questionnaire to Assess Carbohydrate and Insulin-Dosing Knowledge in Youth with Type 1 Diabetes.” Diabetes Care 33 (2010): 457–462.

Google Scholar, Cross Ref, Indexed at

37. Albanese‐O'Neill, Anastasia, Jann MacInnes, Michael J. Haller and Janey Adams, et al. “Type 1 Diabetes Knowledge Assessment: The KAT‐1 Validation Study.” Pediatr Diabetes 23 (2022): 1687–1694.

Google Scholar, Cross Ref, Indexed at