Design and Psychometrics of Diabetes Knowledge Questionnaire

1. Background

Diabetes mellitus is recognized as a major public health concern worldwide, especially in developing countries, due to its high prevalence, severity, and associated complications (1, 2). According to the International Diabetes Association, in 2019, 1 out of every 11 people aged 20 - 79 has diabetes, which is equivalent to 463 million people, and it is estimated that the number of people with diabetes will reach more than 552 million by 2030 (3, 4). Problems with diabetes can be decreased with early detection and proper management, including lifestyle modifications, regular exercise, a healthy diet, weight control, and medication (5). Studies have shown that knowledge plays a central role in diabetes control, and knowledge of medications, diet, physical activity, home blood glucose monitoring, as well as foot care is essential in the management of diabetes (6).

A previous study has revealed that patients with metabolic syndrome and have inadequate knowledge of the disease fail to adhere to necessary lifestyle changes as well as pursue the required treatment (7). People who are not well aware of their illness do not properly understand the risk of disease-related complications and, therefore, have poor motivation for making behavioral changes to the treatment (8).

One of the most important challenges to deal with type 2 diabetes mellitus (T2DM) in developing countries is the adherence to drug treatment in order to prevent complications. In fact, patients’ knowledge of diabetes, education level, and duration of diabetes are recognized as compliance predictors (9).

Due to the significant role of knowledge in controlling and treating the diabetes in most educational interventions, the assessment of the individuals’ levels of knowledge is regarded as a key variable when planning the given interventions. In other words, assessment is a complement to education; however, conducting accurate assessment requires effective tools (10). Therefore, it is essential to develop a valid tool capable of assessing people’s knowledge of diabetes and intervention efficacy.

The first tool is Diabetes Awareness Test (DKT) which was designed by the Michigan Diabetes Education and Research Center in 1981. This questionnaire consists of 38 questions in 5 domains (i.e., carbohydrates, basics, blood glucose, food exchange, and insulin management) and has been widely used by diabetes researchers and educators (11). In 1984 and in Australia, a three-part scale was designed based on the literature reviews and the experts’ knowledge to assess diabetic patients’ knowledge. The questionnaire has 45 questions (i.e., one-third of these items are multiple-choice, one-third are true/false, and the rest are open-ended questions). Validation of this tools has been measured and accepted for the Australian population (12). Another tool, Diabetes Knowledge Questionnaire (DKQ), including 60 items in English, was first designed in 2000, but its concise English and Spanish versions (24 items) were validated later (13). Validity of this questionnaire for Portuguese population has been evaluated and confirmed twice, and it has been used to investigate the patients with type 1 and type 2 diabetes (14).

2. Objectives

Due to the lack of a questionnaire assessing diabetes knowledge standard in Iran as well as the lack of some items considered by the researcher in the previous questionnaires (including physical activity and complications of diabetes), this study aimed to design and evaluate the psychometric properties of the DKQ in Iranian diabetic patients.

3. Methods

3.1. Sample

This cross-sectional study was conducted from March 2020 to May 2021, in Yazd, to explore 400 T2DM using simple random sampling method. First, 2 public clinics and 2 private clinics were randomly selected from among diabetes clinics in Yazd. Then, patients from these clinics who were willing to participate in the study and met the inclusion criteria were selected. Inclusion criteria included age 30 - 65 years, having no cognitive disorder, as well as reading and writing ability. To implement factor analysis, the minimum sample size is determined by factors and not by variables; to implement exploratory factor analysis, 10 or 20 samples are required for each factor; however, the minimum sample size 200 is acceptable (15). In order to meet the minimum sample size, therefore, 400 T2DM (i.e., 200 under insulin therapy and 200 under oral therapy) were selected using simple random sampling method.

3.2. Instrument

Initial questionnaire was developed by the research team (i.e., a health educator, a community and preventive medicine specialist, a nutritionist, and 2 endocrinologists) and based on the literature review (the above-mentioned previous questionnaires and FDA guidelines) and expert panel’s recommendation. This questionnaire, including 34 multiple choice items, explored 6 dimensions, namely glucose monitoring, diet, physical activity, complications, and insulin. Experts evaluated the questionnaire in terms of consistency with scientific texts as well as appropriate words and grammar choices.

3.3. Content Validity

Content validity index (CVI) and content validity ratio (CVR) were calculated in order to evaluate content validity. The questionnaire was sent to 13 experts in endocrinology, nutrition, exercise physiology, and health education, who were requested to rate the questions in terms of their necessity, simplicity, clarity, and relevance. Each item with CVI > 0.79 and CVR > 0.8 was accepted based on the number of experts (16). Finally, face validity was assessed by 30 patients who were not included in the study sample. They confirmed that the questions and answers were clear.

3.4. Reliability

The reliability of the instrument was assessed adopting 2 methods: Test re-test and internal consistency measurement with a one-month interval. The intraclass correlation coefficient (ICC) was calculated using test re-test. The Cronbach’s alpha coefficient was used to measure the internal consistency of each item in each subscale. To this end, 30 diabetic patients not included in the study sample were asked to complete the questionnaire twice at one-month intervals.

3.5. Structural Validity

After the confirmation of the questions regarding content validity and reliability, the construct validity of the questionnaire was evaluated by adopting exploratory factor analysis. Factor analysis enables researchers to come up with a distinct pattern among the many variables and the complex relationships among them. Finally, 400 diabetic patients (oral and insulin therapy) completed the questionnaire.

4. Results

The mean age of participants in this study was 53.98 ± 10.80. As for the gender of participants, 239 (60.1%) were females and 164 (39.9%) were males.

4.1. Content Validity

The CVI results indicated that all questions scored above 0.8 and, therefore, were considered appropriate. The CVR results revealed that all questions were equal to or greater than the number in the Lawshe table (0.62). This indicated that essential and important questions were used in this tool (Table 1) (16).

4.2. Construct Validity

Exploratory and confirmatory factor analysis were used to evaluate the validity of the structure. For the data related to this questionnaire, the Kaiser-Meyer-Olkin (KMO) value was 0.89, which indicated that the suitability of the data reduced a number of key factors. The value of Bartlett’s test of sphericity was obtained at the error level of less than 0.001, which was indicative of a sufficient correlation between variables or questions and factors (Table 2).

Exploratory factor analysis was adopted to analyze the items in the questionnaire by using Varimax method (Table 3). According to Table 3, 6 factors with a specific value greater than 1 were extracted, which included 0.82 total variance. Item 3 was removed due to having a common load on 3 factors; items 11 and 18 were removed due to having a negative factor load from a theoretically incorrect point of view. Therefore, items 3, 11, and 18 were generally removed in factor analysis. Finally, 6 factors were obtained implementing the exploratory factor analysis. The first factor included questions 1, 2, and 4, which were referred to as general knowledge questions; the second factor included the expressions 5, 6, 7, and 8, which were called hypoglycemia knowledge; the third factor included the items 9, 10, 12, 13, and 14, which were termed the knowledge of diabetes complications; the fourth factor included the expressions 15, 16, and 17, which were called nutrition knowledge; the fifth factor included the expressions 19, 20, 21, 22, 23, and 24, which were named physical activity knowledge; and finally, the sixth factor included phrases 25, 26, and 27, which were referred to as insulin knowledge. The results of this analysis are shown in Table 3.

According to the scree plot diagram in Figure 1, the six factors in the second factor analysis had a specific value higher than 1, and this number of the extracted factors confirms the number of sub-tests made by the developer of the questionnaire.

Scree plot diagram (pebble)

Figure 1.

Scree plot diagram (pebble)

Table 3 shows the extracted factors along with the factor load, the percentage of variance, and the correlation of each item with the total score of the questionnaire.

Confirmatory factor analysis was also performed to examine the six-factor model of the knowledge questionnaire. The fit indices of the 6-factor model of the questionnaire are reported in Table 4.

According to this table and regarding the knowledge questionnaire, the root mean square error (RMSEA) was less than 0.08, the goodness-of-fit index (GFI) was 0.91, and the relative chi-square (1.21) was less than 3, based on which the model 6 factors were confirmed. Since the factor loads of all items in the questionnaire were greater than 0.4 and t-values were greater than 1.96, the model obtained from the exploratory analysis was confirmed.

Figure 2 shows all the path coefficients and covariances between the latent (standardized) factors. As shown in this figure, all coefficients were within a reasonable range; in other words, none of the standardized path coefficients had a value greater than 1, and all factor loads were greater than 0.4 (see Figure 2). Therefore, the exploratory model obtained from exploratory factor analysis was confirmed.

Factor Loads of Items in the Knowledge Questionnaire

Figure 2.

Factor Loads of Items in the Knowledge Questionnaire

4.3. Reliability

The internal correlation coefficient (icc) for test-retest relative reliability of the questionnaire’s total score was 0.85, which had an acceptable level of reliability. Furthermore, Pearson correlation coefficient of reliability between test times (test-retest) was calculated to be 0.92. The results of this reliability for all six factors are given in Table 2. The results statistically showed that both correlation coefficient and internal correlation tests had high coefficients, and there was significant reliability between the measures in all subscales (P < 0.05) (Table 5).

In addition, Cronbach’s alpha coefficient index was used to estimate the internal consistency of this questionnaire, and the value of 0.9 was accepted for the whole instrument (Table 6).

5. Discussion

According to our study findings, the DKQ had content validity, form, and structure, as well as internal consistency, reliability, and good stability; therefore, this questionnaire may have assessed the state of knowledge of diabetic patients with a minimum literacy by spending 10 - 15 minutes to complete. According to the researchers, gaining sufficient knowledge about this chronic disease is the cornerstone of empowering people to self-manage diabetes and, thus, to control the disease (17). In order to check the content validity in this study, the CVR and CVI were calculated, which led to the elimination of 8 questions and the confirmation of the acceptable validity of the rest of questions.

According to results of the exploratory factor analysis test, 23 items were placed in 6 areas: General questions, Hypoglycemia, complications of the disease, nutrition, physical activity, and insulin. When designing this questionnaire, an attempt was made to address the factors that were effective in managing diabetes. The scale designed by Eigenmann et al. also examined the normal blood glucose levels, complications, diet, exercise, blood sugar monitoring, annual checkups, support services, and sick days (18).

Blood glucose control indicators were included in the general questions subscale since the knowledge of the optimal level of blood sugar can help patients to perform better in cases of high blood sugar; in other words, this knowledge empowers them to manage their diabetes. Items for monitoring glucose had also been included in previous questionnaires designed for diabetes knowledge (13, 14).

The definition, symptoms, and treatment of hypoglycemia were considered in hypoglycemic subscale. Although hypoglycemia is more common in patients with type 1 diabetes, those with type 2 diabetes who are on insulin therapy are also at high risk. In other words, hypoglycemia is a common side effect of diabetes treatments, especially insulin, and imposes a significant burden on individuals and health care systems (19).

According to ADA, awareness of the signs and symptoms, as well as appropriate measures during hypoglycemia, are key educational points (20). The test-retest correlation coefficient for this subscale was 0.86. In the hypoglycemia knowledge scale designed by Alotaibi for primary school teachers, the correlation coefficient was 0.95 (21). The reason for the higher reliability of the questionnaire in the given study may have been attributed to the higher education level of the samples compared to the samples of the present study.

In the complication subscale, the optimal time to examine the various complications of diabetes was examined. According to the experts, most patients become aware of their diabetes only when a long time has passed since the onset of the disease, and they have already suffered from its side effects. Awareness of the complications helps patients not to loss valuable time to prevent or minimize the complications. Regarding the complications of diabetes, Alzahrani et al. has suggested that controlling modifiable risk factors through periodic eye examinations can delay the progression of retinopathy (22).

Another subscale in the present questionnaire was the one which examined the physical activities of diabetic patients. Although physical activity has not received enough attention in the previous questionnaires (11, 14), it is an important, recommended treatment for diabetes and according to studies, patients’ knowledge about the method of performing physical activities can significantly contribute to blood sugar control (23). Therefore, knowledge of the conditions and the recommended level of physical activities was found necessary to control weight and blood sugar, as well as to prevent muscle atrophy in patients with diabetics.

Acceptable internal consistency for this tool was obtained using Cronbach’s alpha test, which was higher than that for the tools previously designed by Fitzgerald et al. (24) and Eva Menino et al. (14). In general, the different results may have been due to the differences in the studied samples regarding age, educational level, training, quality of treatment, etc.

5.1. Limitations

Attempts were made to improve the quality of the present study; however, it faced some limitations. Since our study participants were only patients with type 2 diabetes and holding at least a primary school diploma, the validity of this questionnaire for patients with type 1 diabetes as well as for illiterate patients remained unknown.

5.2. Suggestions

It was suggested that further studies should be carried out to confirm the instrument developed in this study. It was also recommended that lower age groups, patients with lower and higher levels of education, and larger sample sizes should be selected in order to further investigate this tool.

According to our study findings, the questionnaire was a valid scale designed to assess the knowledge of patients with T2DM about various dimensions related to the disease.