Psychometric Evaluation of the Farsi Version of the Self-Care of Diabetes Inventory in Iranian Patients with Diabetes

Introduction

Diabetes (twenty-first century plague) is the most common metabolic disorder that reduces life expectancy in patients.¹ This chronic and progressive disease leads to cardiovascular disease, retinopathy, nephropathy, neuropathy, and increased mortality.² The International Diabetes Federation (IDF) reported that about 451 million patients affected by diabetes around the world, which will rise to 693 million by 2045.³ According to 2008 statistics, more than four million people in Iran have diabetes, which is expected to reach six million due to increased age, prevalence of obesity, sedentary lifestyle, and diet changes in future years.⁴ Lifelong self-care is required for patients with diabetes to prevent short and long-term complications of the disease and improve their quality of life.⁵

The World Health Organization (WHO) defines self-care as the ability of individuals, families, and communities to promote health, prevent disease, maintain health, and cope with illness and disability with or without the support of a health-care provider.⁶ Forbes believes that the concept of self-care refers to lifestyle, managing therapy, being able to understand symptoms and problems and responding to them appropriately.⁷ In fact, self-care is a part of daily life of healthy or ill individuals and includes the implementation of simple (e.g., daily health-related routines and avoidance of environmental hazards) and complicated (e.g., perceiving symptoms and taking suitable measures, selecting the appropriate treatment, using drugs, assessing treatment, and performing variable rehabilitation activities) tasks to restore health.⁸

Lifestyle changes and self-care are key components in preventing the complications of diabetes.⁹ In other words, changes in lifestyle, such as a healthy diet, physical activity, and blood glucose monitoring can reduce the progression of diabetes.¹⁰ However, successful management of diabetes depends on the ability and tendency of patients to adopt complicated and multidimensional self-care behaviors.¹¹ Currently, there are 16 self-care tools for diabetic patients worldwide;^12–27 the majority of which are one-dimensional and mainly focus on diet, physical activity, blood sugar monitoring, as well as oral health and insulin management. Another six multi-dimensional tools have been designed during 1997–2008.^19,28–32 Review of the literature revealed that researchers mostly use the summary of diabetes self-care activities (SDSCA) measure in Iran. Given the establishment of the tool over 13 years ago, and the lack of the theoretical framework to define self-care, it might not be able to properly measure new dimensions of the self-care concept.^9,33

In 2017, the Self-Care of Diabetes Inventory (SCODI) was developed by an Italian team based on the middle-range theory of self-care of chronic illness.³⁴ This tool has received worldwide attention so far that it is currently being translated in 10 languages (http://self-care-measures.com/available-self-care-measures/self-care-of-diabetes-inventory/).

The tool measures self-care maintenance, self-care monitoring, self-care management, and self-care confidence, as key concepts of the theory. Self-care maintenance refers to illness-related behaviors, such as adherence to follow-up visits and examinations, and health-promoting behaviors, such as eating a healthy diet or engaging in physical activity. Self-care monitoring refers to the process of vigilant body monitoring or “body listening” whose purpose is symptom recognition and interpretation and detects changes in the body. Self-care management is said to appropriate behavior in response to health changes and problems to prevent its exacerbation. Self-care confidence influences self-care maintenance, self-care monitoring, and self-care management, and reflects the patients’ self-efficacy or ability to perform a specific action and persist in performing that action or behavior, despite barriers.³³

The SCODI includes 40 items (scored based on a 5-point Likert scale). The SCODI measures self-care behaviors in both groups of patients with type I and II diabetes, where higher scores are indicative of better self-care.³³ As the SCODI was developed based on a robust theoretical background, the use of the tool in clinical practice and research could allow to clearly define concepts, to improve communication both with professionals and patients, and to boost the understanding of the self-care process in diabetes as it happened for other chronic conditions.³⁵ Due to the lack of new, reliable and valid questionnaires to assess the self-care status in patients with diabetes, researcher-made or outdated questionnaires are mostly used that might not be able to satisfactorily measure this complicated and multi-dimensional concept. The translation and validation of SCODI in Farsi will provide researchers with a valid and reliable tool for the Iranian diabetes population. Therefore, in this paper, we aimed to validate a translated Farsi version of SCODI in diabetic patients.

Methods

Ethical Considerations

The research objectives were explained to the participants, and the written informed consent obtained before the start of the study. This study was conducted in accordance with the Declaration of Helsinki. In addition, all participants were ensured of the privacy and confidentiality terms regarding their personal information. It is notable that the present research was approved by Kurdistan University of Medical Sciences with the code of 1395.9221363201.

Sample and Setting

Four hundred diabetic patients (M=168, F=232; mean age = 54.7±13.9 years) were recruited via convenience sampling from center of diabetes of Sanandaj, west of Iran. Inclusion criteria were willingness to participate in the study and age over 18 years. Patients with mental and psychological problems and incomplete questionnaires were excluded from the analysis.

Study Design

This is a cross-sectional study design which was performed to translate and validate a self-care tool for diabetic patients who were referred to the center of diabetes, Tohid Hospital, in Sanandaj, Iran, in 2019.

Development, Validation, and Reliability of Survey Tool

Translation Process

After receiving permission from the original designer of the instrument, the forward and backward translation method was used to translate the tool from English to Farsi by two separate translators.³⁶ The final version was developed based on these two translations. In the next stage, the final Farsi version was translated back into English by two other translators, followed by providing a final Farsi version by a coordinator by comparing the Farsi and English translations. The final version was delivered to and confirmed by the original designers of the questionnaire after assessing the semantic equivalence between the forward and the back-translation.³⁷ The Farsi version of this tool is visible in Appendix 1.

Face and Content Validity

To assess the face validity of the Farsi version, the self-care questionnaire was provided to 10 diabetic patients for pilot testing. Diabetes patients with gender, disease duration, and economic and social/demographic diversity were selected by convenience sampling and were requested to express their opinions about the suitability, difficulty, and ambiguity/clarity of the items in the survey. On the other hand, content validity was evaluated by providing the Farsi version of the tool to nursing experts who were selected by purposive sampling. These experts provided opinions on the use of suitable words/terminologies related to the cultural status/norms of the subjects, and on proper placement of phrases in the tool. Ultimately, the tool was corrected based on the recommendations provided. Due to the cultural characteristics of Iranian society, several items were adjusted. Because in the Iranian society, the role of the physician is more prominent than other health care providers, we used the “doctor” words instead of the “health care provider” words in the items 28, 29 and 34. We also used non-alcoholic drinks containing high sugar levels or alcoholic drinks instead of alcohol intake and we used the pure meats instead of cured meats.

Construct Validity

At first, latent factors were extracted using exploratory factor analysis (EFA). The minimum sample size required for the implementation of EFA is 3–10 samples per item.³⁵ Therefore, 400 patients with type I and II diabetes were enrolled in the study via convenience sampling. Inclusion criteria were the diagnosis of diabetes by a physician and ability to complete the questionnaires. At this stage, the Kaiser Meyer Olkin Index (KMO) and the Bartlett test of sphericity were calculated to determine the sample size adequacy and appropriateness of the factor model (P < 0.05). The closeness of the KMO criterion to one indicates more adequacy of sample size for performing factor analysis.³⁸ KMO is considered good at 0.70 to 0.80 and large at 0.80 to 0.90.³⁷ The maximum likelihood extraction of latent factors was performed using Promax rotation, assuming independent factors and scree plot were generated by SPSS-18 software. Factors with an eigenvalue greater than 1 and factor loading greater than 0.40 indicated good construct validity.³⁹ Hence, the cut-off point for determining the variables loaded by each factor was set at 0.40.⁴⁰

Reliability

We used Cronbach’s alpha and McDonald’s “omega” coefficient to determine reliability. The McDonald’s “omega” coefficient is estimated based on , where a is the number of factor questions, is overall communality, and b is the sum of the factor loadings of that factor.⁴¹ Similar to alpha coefficient, the value of the omega coefficient is between zero and one.⁴² Moreover, the instrument reliability and stability over time was checked by test retest and the use of intraclass correlation coefficient (ICC) using the two-way mixed-effects model and absolute agreement at 95% confidence interval. A computed Cronbach’s alpha higher than 0.70 and an ICC value higher than 0.80 are considered acceptable.⁴³ In total, 30 and 15 sample sizes were selected for evaluation of internal consistency and re-test (with a 2-week time interval), respectively.

Results

Among the diabetic subjects, 168 (42%) were male and 232 (58%) were female with a mean age of 54.7±13.9 years. Additionally, the majority of the participants had type II diabetes (95.2%) and was married (78.5%). Moreover, the mean age of the patients with type I and II diabetes was 43.9±14 and 55.3±13.7 years, respectively. Also, the mean duration of diabetes in patients with type I and II diabetes was 6.4±4.4 and 7.6±4.4 years, respectively. More information is presented in Table 1.

Table 1 Characteristics of Patients with Diabetes Included in the Study (N=400)

Self-Care Maintenance

The scale included 12 items and four factors which are: activity-nutritional behavior, smoking avoidance behavior, illness-related behaviors, and health-promoting behaviors. The KMO was 0.759 and Bartlett’s Test (Chi-square=1635.54, df=66) was significant for this dimension (P=0.001). In EFA, the aforementioned factors had eigenvalues of 4.12, 1.47, 1.34, and 1.14, respectively, all of which determined 52.78% of the total variance of self-care maintenance. Reliability of the four factors based on Cronbach’s alphas was 0.81, 0.684, 0.68, and 0.81, respectively, and McDonald’s Omega coefficients of these factors were 0.83, 0.72, 0.87, and 0.80, respectively. The overall reliability of this factor based on Cronbach’s alpha coefficient was 0.809. The Intra-class Correlation Coefficient (ICC) for this factor was 0.88 (95% CI: 0.77–0.95; P = 0.001).

Self-Care Monitoring

This eight-item dimension had three factors which are: symptom monitoring, symptom assessment, and symptom recognition. In this regard, KMO was estimated at 0.663 and Bartlett’s Test (Chi-square=11323971, df=28) was significant (P=0.001). In EFA, three factors had eigenvalues of 2.98, 1.61, and 1.07, respectively, the sum of which was able to determine 70.93% of the overall self-care monitoring variance.

Reliability of the three factors based on Cronbach’s alphas was 0.59, 0.63, and 0.59, respectively, and McDonald’s Omega coefficients of these factors were 0.95, 0.76, and 0.75, respectively. The overall reliability of the dimension was confirmed at the Cronbach’s alpha of 0.767. The ICC for this factor was 0.82 (95% CI: 0.66–0.93; P = 0.001).

Self-Care Management

This eight-item dimension included two factors which are: autonomous self-care and consultative self-care. In this regard, KMO was estimated at 0.725 and Bartlett’s Test (Chi-square=755.624, df=28) was significant (P=0.001). In EFA, two factors had eigenvalues of 2.83 and 1.47, respectively, the sum of which predicted 40.07% of the overall self-care monitoring variance. Reliability of the two factors based on Cronbach’s alphas was 0.78 and 0.44, respectively, and McDonald’s coefficient omega of these factors was 0.77 and 0.77, respectively. Items 29 and 23 were not included in any factors. The overall reliability of the dimension was confirmed at the Cronbach’s alpha of 0.590. The ICC for this factor was 0.62 (95% CI: 0.22–0.83; P = 0.001).

Self-Care Confidence

This eight-item dimension had two factors which are: task-specific self-care confidence and persistence self-care confidence. In this regard, KMO of the dimension was 0.895 and Bartlett’s Test (Chi-square=2014.596, df=55) was significant (P=0.001). In EFA, two factors had eigenvalues of 5.23 and 1.40, respectively, the sum of which predicted 51.55% of the overall self-care confidence variance. Reliability of the two factors was estimated by the Cronbach’s alphas of 0.84 and 0.84, respectively, and McDonald’s coefficient omega of 0.78 and 0.81, respectively. The overall reliability of the dimension was confirmed at the Cronbach’s alpha of 0.886. The ICC for this factor was 0.92 (95% CI: 0.85–0.97; P = 0.001). The results of exploratory factor analysis and reliability are presented in Tables 2 and 3 in detail.

Table 2 Stability and Internal Consistency of F-SCODI

Table 3 Exploratory Factor Analysis and Item Factor Loadings for the Self-Care Maintenance, Self-Care Monitoring, Self-Care Management, and Self-Care Confidence Scales

Discussion

The present study aimed to translate and validate a new self-care tool for patients with diabetes who speak Farsi. We found that the Farsi version of SCODI had suitable validity and reliability. This is relevant because the tool could be used both in clinical practice and research to improve self-care of patients with diabetes. The availability of the tool could be strategic also for cross-national comparisons measuring self-care maintenance, monitoring, management and confidence in different cultures and languages. This opportunity could boost the comprehension of the self-care process in people with diabetes. Furthermore, communication among professionals and patients could be improved by the use of clear concepts, terms, and measures, according to the SCODI characteristics.

This theory-based instrument involved self-care maintenance, monitoring, management, and confidence. In EFA of self-care maintenance dimension, we retrieved four factors of activity-nutritional behavior (items 1–4), smoking avoidance behavior (items 5 and 7), health-promoting behaviors (items 6, 8, 10, 12) and illness-related behaviors (items 9 and 11). Also similar to the original version of the tool, each of the factors of smoking avoidance behavior and illness-related behaviors had two items. It seems that the items included in the first two factors were more suitable, compared to the original version.

The activity-nutritional behavior better shows the importance of food and activity in self-care of patients with diabetes in the target culture and settings. The reason for this finding can be attributed to the specific lifestyles of the samples and their specific behaviors.

Moreover, the two items of smoking and alcohol avoidance were correctly located in the factor of smoking avoidance behavior, showing the importance of this unhealthy behavior in self-care of patients with diabetes. Studies have shown that cigarette smoking is correlated with diabetes.^44,45 Among all available diabetic self-care instruments, smoking avoidance is only mentioned in the SDSCA tool, which is consistent with our extracted factor.¹⁹ Overall, the results showed a relative difference between the items included in the factors of the Farsi version and items of the original version, which might be due to the culture, social context/norm, and demographic characteristics of the evaluated subjects in the two studies. However, even if factors separated differently if compared with the original context and culture, factor loadings were good in our study, and the Farsi and original versions were homogenous in terms of internal consistency of self-care maintenance dimension (0.81 vs 0.809).³³

Regarding self-care monitoring, we extracted three factors of symptom monitoring (items 13–15), symptom assessment (items 16–18) and symptom recognition (items 19, 20) in EFA. However, the original version has two factors of body listening and symptom recognition in this section. In the current research, item 17 (foot monitoring) was not used along with monitoring of blood sugar, weight, and blood pressure (symptom monitoring factor). Since most of our patients had a low level of education, they considered blood sugar, blood pressure, and weight as raw figures and were unable to interpret them. However, they constantly examined their feet due to performing wudu (ablution) (i.e. washing the face, hands, and legs before prayers) several times a day. In a research by Sedighi Pashaki et al (2019), 43% and 23% of Iranian patients with diabetes had inadequate and borderline health literacy, respectively, and were unable to interpret health information.⁴⁶

The overall internal consistency of the dimension was 0.767 and 0.84 in the present study and the original version, respectively.³³ In addition, Song and Lipman introduced three features for self-care monitoring, including awareness, interpretation, and response to a patient’s particular manifestations, which are affected by culture.⁴⁷ These features are considerably in line with the factors extracted in this area. Of the previous 16 self-care tools, only six had referred to glycemic self-monitoring.^{15,21–23,25,26} Compared to the mentioned tools, this part of the SCODI tool involves self-monitoring of hypertension and weight in addition to glycemic self-monitoring, which shows the comprehensive nature of the instrument.

In terms of self-care management, we extracted two factors of autonomous self-care (items 21, 24–27) and consultative self-care (items 22, 23, 28) in EFA. These two factors are very similar to the two extracted in the original study. Items involved in the consultative self-care factor referred to writing factors related to blood sugar level changes in patients (type of reflection and self-consulting) and consulting with friends, family and doctor, the layout of which seemed more relevant than the original. We believe that the reason for the similarity of the items in the two original and translated versions was due to the nature of diabetes, which was not influenced by the demographic characteristics of the two samples. A review of the previous tools on self-care in diabetic patients showed that three tools referred to management of drugs and weight of patients, and disease management was not assessed in the other 13 tools.^22,23,26 Although item 23 had a factor load of less than 0.3, we kept it because it was considered an important item by the designer of the original SCODI tool.

In terms of self-care confidence, we retrieved two factors of task-specific self-care confidence and persistence self-care confidence. Again, the same two factors were found for this scale in the original study with some differences in the items’ loading. In this section, only three items of 33 (insistence on continuing treatment), 37 (insistence of disease monitoring) and 40 (insistence on performing tasks that improve blood sugar) directly referred to persistence and insistence. In addition, the mentioned factors were properly placed in the factor of persistence self-care confidence in our tool as well as the original version. Items 35 (understanding good or bad blood sugar) and 39 (evaluation of the effectiveness of your actions for blood sugar regulation) in the present study and items 31 (following up recommendations) and 32 (correct method of drug use) in the original version were placed in this factor.³³ This difference in placement of items might be due to the cultural status and perception of patients with diabetes. The overall internal consistency was estimated at 0.886 and 0.89 in the current and original studies, respectively. In a research by Rezaei et al (2019) on Kurdish diabetic patients, diabetic patients did not believe in medical guidelines and recommendations, and they only relied on their physical condition as information required for taking their medications.⁴ Among the available self-care tools, only Diabetes

Self-efficacy Scale (DSES) refers to self-efficacy and confidence in the ability of patients, which is congruent with our findings.²⁰ In this study, more than 40% of diabetic patients were illiterate, so all questionnaires were distributed and read face to face by one researcher. Given that item 23 had a factor load less than 0.3 in this study, we retained it because it was not affected by the cultural factors of the community. We propose to focus more on the face validity of this section in future studies.

Conclusion

The results of exploratory factor analyses showed that the structure of this Farsi version of SCODI has good validity and reliability in measuring self-care in Farsi patients with diabetes. This new and comprehensive instrument includes all factors in the previous 16 self-care tools and can properly evaluate all aspects of self-care in patients with diabetes. This instrument can be used to assess self-care level in patients and plan and implement educational and care interventions for these individuals. Furthermore, the tool can help health care providers evaluate the level of self-care in patients with diabetes to establish and implement suitable educational and care interventions. According to our results, the previous literature using SCODI, and the theoretical background, we recommend to score the 4 SCODI scales using a standardized 0–100 score to measure self-care maintenance, monitoring, management, and confidence, respectively. This will be useful to address how patients perform the different behaviors that the complex and dynamic process requires. Furthermore, this will help to target specific aspects of self-care by tailoring interventions that are effective for that. Having a Persian version of SCODI can help Iranian researchers to better assess the self-care status of patients with diabetes.