Abstract
Background
Psychological flexibility has considerable effects on medical and psychosocial outcomes in youth with type 1 diabetes mellitus (T1DM). This study aimed to evaluate the psychometric properties of the Persian versions of the Acceptance and Action Diabetes Questionnaire (AADQ) and the Diabetes Acceptance and Action Scale for children and adolescents (DAAS), the measures of diabetes-specific psychological flexibility.
Methods
196 youth with T1DM completed the DAAS, AADQ (youth-report), Child and Adolescent Mindfulness Measure (CAMM), Emotion Regulation Questionnaire for Children and Adolescents (ERQ-CA), and the Avoidance and Fusion Questionnaire for Youths (AFQ-Y8). Also, their parents completed AADQ (parent-report). Data analyzed by SPSS V.26 and LISREL 8.8.
Results
The mean and standard deviation of participants’ age was 14.7 ± 2.08.The internal consistency due to Cronbach’s alpha method was 0.87, 0.8, 0.84, and 0.83 for DAAS total scores, avoidance, values impairment, and fusion, respectively. The internal consistency of AADQ (both parent-report and youth report) was above 0.8. Test-retest reliability (from 45 participants) with a one-week interval was assessed by the interclass correlation coefficient (ICC). The DAAS, AADQ-parent report, and AADQ-youth report’s reliability coefficients were 0.93, 0.82, and 0.92, respectively. The AADQ (both forms) and DAAS evidence good content validity based on correlations with other measures. Confirmatory factor analysis (CFA) and Exploratory Factor Analysis (EFA) showed DAAS has the three-factor model, which strongly a suitable model is fitting. EFA also verified the AADQ model fitting.
Conclusions
In general, these results support the psychometric properties of the Persian versions of DAAS and AADQ among the Iranian youth patients with T1DM.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40200-021-00796-1.
Keywords: Diabetes mellitus, Psychometric, Risk assessment, Pediatrics, Psychological tests
Introduction
Type 1 diabetes is one of the most common chronic diseases in children and adolescents. Diabetes poses a wide range of personal, social, and economic risks [1].
Diabetes is a group of diseases including type 1 diabetes, type 2 diabetes, and gestational type diabetes. There are also informal or less common categories, such as Latent Autoimmune Diabetes in Adults (LADA). Unlike type 2 diabetes and gestational diabetes, type 1 diabetes has been less studied. In short, type 1 diabetes occurs when the pancreas does not produce the hormone insulin [2]. It is estimated that 128,900 children and adolescents under the age of 20 are diagnosed with type 1 diabetes worldwide each year [3]. In Iran, the annual incidence in children and adolescents under 15 years of age is estimated at 13.35 cases per 100,000 people [4]. The prevalence of T1DM is increasing in all children and adolescents worldwide [5]. This disease has adverse effects on all aspects of a person’s life, including physical and mental health. Stress, anxiety, and depression are common problems that affect these patients. There is also a direct and two-way relationship between physical and psychiatric symptoms in these people. An increase in physical symptoms causes the severity of psychological symptoms and vice versa [6].
The best way to reduce the effects of type 1 diabetes is to keep HbA1c close to the same level as non-diabetics through intensive treatment [7]; Insulin should be injected daily into people with diabetes to maintain optimal blood glucose levels [8]. Besides, proper diet and daily physical activity should be considered in these interventions [9]. Also, complementary therapies are used to reduce HbA1c. HbA1c levels are also sensitive to psychological issues [9]. Also, there are direct and indirect links between HbA1c levels and psychiatric disorders [10]. Studies have shown that using psychotherapy interventions improves HbA1c in both cases. First, psychotherapy interventions reduce HbA1c by improving self-care behaviors, physical exercise, self-efficacy, and mental health, thereby increasing patients’ quality of life with type 1 and type 2 diabetes [10, 11].
On the other hand, psychological interventions reduce the functional defects caused by diabetes by reducing the levels of common psychiatric problems in diabetic patients (such as stress, depression, anxiety, sleep problems) [11, 12]. This result also indirectly affects HbA1c and quality of life. Based on these studies and results, clinicians in clinics and researchers have recently been widely encouraged to use psychological therapies as an adjunct to medical treatment in patients with diabetes [6, 7, 13].
One of these psychological therapies is Acceptance and Commitment Psychotherapy (ACT). ACT is an empirically supported treatment that works for a wide range of psychological and physical problems. The purpose of ACT is to increase psychological flexibility [14]. Psychological flexibility refers to focusing on the present and acting effectively in an accepting and non-judgmental manner, even when one’s thoughts and feelings are contrary to one’s values [15, 16]. In a study on adults with diabetes, Gregg et al. concluded that psychological flexibility, as the primary mechanism of change, was involved in ACT-based interventions. Thus, it plays a mediating role in changes in blood glucose after ACT treatment [17]. On the other hand, studies have shown that cognitive flexibility (the result of the act) improves self-care behaviors and adaptation to psychiatric problems. Psychological flexibility reduces HbA1c and increases the quality of life in patients with type 1 diabetes [17]. With increasing psychological flexibility, distress problems decrease in young people with type 1 diabetes, and self-care behaviors increase in these people [7].
Assessment tools are needed to compare changes in children and adolescents’ psychological flexibility before and after ACT treatment. One of the tools used to measure psychological flexibility is the Avoidance and Fusion Questionnaire for Youth (AFQ-Y8). This questionnaire was developed by Greco et al. In 2008. AFQY8 has shown good validity and reliability in the non-clinical population of children and adolescents. This questionnaire has been standardized in different countries, including the United States, Sweden, the Netherlands, etc. [18, 19]. In Iran, this tool was standardized in 2018 to measure psychological flexibility in the non-clinical population of children and adolescents [19]. Despite the widespread use of this tool, measurement by this tool has some limitations:
This tool is used for all disorders and is not specific to diabetes.
New studies of ACT processes have shown that these processes are different in different disorders.
Our clinical experience shows that no valid results are achieved when we use items unfamiliar with diabetes for children and adolescents with diabetes.
Because it is challenging for the child and adolescent respondent to link this flexibility with diabetes problems. In order to address these limitations and to develop patient-centered tools, recently in 2020, two tools, the Acceptance and Action Diabetes Questionnaire (AADQ) (two forms of parent and child) and the Diabetes Acceptance and Action Scale (DAAS), for the measure of psychological flexibility of children and adolescents with type 1 diabetes was validated by Berlin et al. The results showed that these two tools have good internal stability, structural validity, and content validity [8]. This study aimed to determine the psychometric properties of these two instruments in the Iranian population. To date, there has been no measurement tool specifically designed for children and adolescents with type 1 diabetes in the Iranian population to assess changes in their psychological flexibility before and after ACT treatment. Since the prevalence of type 1 diabetes in children and adolescents is high [5], and this disease puts a lot of financial and psychological pressure on children and their families [4], and also through ACT treatment that results in increasing their psychological flexibility, the subsequent consequences can be prevented, It was important to provide such a tool in Iranian society.
Materials and methods
Study design and process
The study population includes Iranian children and adolescents with diabetes who is chosen by internet advertising in October to November 2020 . 205 youth with T1DM between the ages of 12 and 18 were considered by the convenience sampling method, and 200 samples were selected, taking into account the probability of attrition. Then the children answered the relevant online questionnaires. After discarding incomplete or contradictory answers, 196 people met the study criteria and were analyzed. Inclusion criteria include type 1 diabetes, reading literacy, and age under 18 years. Exclusion criteria were severe mental and cognitive disorders, illiteracy in youth and their parents, history of receiving developmental disorders diagnosis.
Instruments
Participants’ demographic information, including age, sex, and blood hbA1c level, was placed at the beginning of the online form.
Diabetes acceptance and action scale
The DAAS is a 42-item questionnaire that Berlin et al. developed the 22-item form of it, and we used the 22-item questionnaire in this study. Respondents answered questions on a Likert scale (4 = never, 0 = always). This questionnaire is used to measure three dimensions: 1- How much do participants believe that diabetes has jeopardized their values? 2- How much has diabetes caused their cognitive fault? 3- How much has diabetes caused avoidance behaviors in them? The scores of this questionnaire range from 0 to 88. Higher scores indicate higher levels of acceptance and action related to diabetes. According to a study by Berlin et al., this questionnaire’s internal consistency was between 0.84 and 0.92 for three factors and equal to 0.92 for the total score. Form 22 has acceptable construct validity questions [8]. In this study, the psychometric properties of this instrument was examined.
Acceptance and action diabetes questionnaire (AADQ)
AADQ is a 9-item one-factor questionnaire. This questionnaire is used to measure diabetes rejection. Questionnaire items are scored in reverse (never = 5, always = 1). That is, higher scores indicate higher levels of acceptance. In this study, two forms of self-assessment (AADQ-YR) and parental reporting (AADQ-PR) have been used. According to a study by Berlin et al., AADQ had a significant positive correlation with the Child and Adolescent Mindfulness Measure (CAMM) and the Diabetes-Related Quality of Life Questionnaire. It had a significant negative correlation with the Avoidance and Fusion Questionnaire for Youth (AFQY), indicating good convergent validity, divergent validity, and content validity of this questionnaire. The internal consistency of the child and parent forms of this questionnaire were 0.86 and 0.87, respectively. In the original version, the self-report questionnaire and the parents’ report have a moderate correlation (r = 0.35) [8]. In the present study, the psychometric properties of this tool were examined in the Iranian children with T1DM (Youth-report) and their parents (parent-report).
Avoidance and fusion questionnaire for youth (AFQY)
This questionnaire was developed by Greco et al. In 2008 and translated into Persian in 2018. This test’s items are scored on a 5-point Likert scale (0 = strongly disagree, four = strongly agree). Higher scores indicate higher levels of psychological inflexibility. In Persian version the internal consistency of this questionnaire was 0.71 by Cronbach’s alpha method. Test-retest reliability for this measure at four weeks was 0/65. In the case of the construct validity, the numerical value of the KMO coefficient was 0.79 [19].
Emotion regulation questionnaire for children and adolescents (ERQ-CA)
This questionnaire is self-report and has two factors (reassessment and repression). It includes ten items. It is used to evaluate children and adolescents’ emotional regulation strategies. This test’s items are scored on a seven-point Likert scale (strongly disagree = 1 and strongly agree = 7). 6 questions are for the reassessment and four questions are for the repression subscale. This questionnaire has desirable psychometric properties for the Iranian population. Cronbach’s alpha is 0.81 for the whole questionnaire and 0.79 and 0.68 for the reassessment and repression factors, respectively [20].
Child and adolescents mindfulness measure
This questionnaire is used to assess the level of mindfulness of children and adolescents. This scale has ten items that are scored on a Likert scale (never = 0 and always = 4). The minimum score in this questionnaire is 0, and the maximum is 40. This scale’s items are coded and summarized in reverse, which indicates that the higher a person’s score, the more person’s mindfulness and acceptance. According to Shabani and Zanjani’s study, this questionnaire has acceptable psychometric properties in the Iranian population [21].
Linguistic validation
The linguistic validation of the Scales from English to Persian consisted of three steps: a forward translation, a backward translation, and a brief interview. One independent, bilingual Persian-native speaker with medical backgrounds (psychologists) translated the original English versions into Persian. An accorded version of scales was generated by revisions and discussion among authors. Backward translation of the consensus versions was conducted by one English speaker without a psychology background, familiar with the linguistic and cultural differences of the English and translated (Persian) language. The Persian versions’ sufficiency was determined by a comparison of the English version with the backward-translated versions. Then participant’s experiment was conducted for five patients. These interviews were completed during which the interviewer asked whether the patients and their parents had any problem in reading the scales and checked the participant’s understanding of all items. Finally, proofreading was completed.
Statistical analyses
Data have been analyzed through SPSS (version 26) and LISREL (version8.8) software. Descriptive statistics (mean, standard deviation (SD), frequency, and percentage) were utilized to analyze the data. Cronbach’s alpha method was used to evaluate internal consistency. Pearson’s coefficient was utilized for reliability and convergent correlation. To examine the latent structure of the scale, Exploratory Factor Analysis (EFA), (IBM SPSS 23.0) and Confirmatory factor analysis (CFA) (R 3.5.1, lavaan package) were used. The sample was randomly divided into two subsamples with sizes 196 and 197. EFA was carried out using principal component analysis and the varimax rotation method to allow correlations between the factors. Kaiser Meyere Olkin test (KMO) and Bartlett’s Test were checked. In order to confirm the extracted factors, CFA was used. Appropriateness of the model was assessed by the root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR), which should be smaller than .08, Bentler’s Comparative Fit Index (CFI), which should be larger than .90 and Sattora-Bentler χ2(S-B χ2), which should not be statistically significant.
Results
Descriptive measures
The present study was performed on 196 children and adolescents aged 12 to 18 years. Of these, 104 subjects (53.1%) were girls, and the rest were boys. The mean and standard deviation of participants’ age was 14.7 ± 2.08.
Internal consistency
Cronbach’s alpha was used to assess the internal consistency of the DAAS questionnaire. The results demonstrated that Cronbach’s alpha method’s internal consistency for all 22 items was 0.872, and each question, if removed, leads to a decrease in the value of alpha, which means that items are appropriate (Table 1). Examining the internal consistency of each of the subscales showed that the subscales have suitable internal consistency. The Cronbach’s alpha for avoidance was 0.8, for values impairment was 0.84, and for fusion was 0.83.
Table 1.
Cronbach’s alpha coefficient for DAAS
| Scale mean if item deleted | Scale variance if item deleted | Corrected item-total correlation | Cronbach’s Alpha if item deleted | |
|---|---|---|---|---|
| DAAS1 | 44.2959 | 185.297 | .484 | .865 |
| DAAS2 | 44.4184 | 183.034 | .503 | .865 |
| DAAS3 | 44.2041 | 187.291 | .429 | .867 |
| DAAS4 | 44.4796 | 181.461 | .566 | .863 |
| DAAS5 | 44.1276 | 188.902 | .367 | .869 |
| DAAS6 | 44.2704 | 187.080 | .447 | .867 |
| DAAS7 | 44.4592 | 186.906 | .393 | .868 |
| DAAS8 | 44.4796 | 185.564 | .445 | .867 |
| DAAS9 | 44.4490 | 185.059 | .515 | .864 |
| DAAS10 | 44.2908 | 189.100 | .366 | .869 |
| DAAS11 | 44.4235 | 182.820 | .573 | .863 |
| DAAS12 | 44.4133 | 186.080 | .438 | .867 |
| DAAS13 | 44.3980 | 185.810 | .456 | .866 |
| DAAS14 | 44.4235 | 181.938 | .533 | .864 |
| DAAS15 | 44.2704 | 186.506 | .414 | .868 |
| DAAS16 | 44.3724 | 190.532 | .297 | .871 |
| DAAS17 | 44.4541 | 184.782 | .432 | .867 |
| DAAS18 | 44.3316 | 183.577 | .483 | .865 |
| DAAS19 | 44.2398 | 187.650 | .437 | .867 |
| DAAS20 | 44.2245 | 186.195 | .441 | .867 |
| DAAS21 | 44.1582 | 186.626 | .426 | .867 |
| DAAS22 | 44.1378 | 183.760 | .521 | .864 |
Another test was the AADQ-youth report. The cronbach’s alpha was used to examine the internal consistency of this test. This test was integrated and had no subscales. Cronbach’s alpha results for this test were 0.881. Another test was the AADQ-parent report. Cronbach’s alpha was used to examine the internal consistency of this test. This test was integrated and had no subscales. Cronbach’s alpha results for this test were 0.825. The Persian version of these two tests showed that both parent reports and youth reports have excellent internal consistency.
The AADQ-youth report and AADQ-parent report results demonstrated that each questions was removed, leads to a decrease in alpha value, which means that items are appropriate (Table 2).
Table 2.
Cronbach’s alpha coefficient for AADQ forms
| AADQ-parent report | Scale mean if item deleted | Corrected item-total correlation | Cronbach’s Alpha if item deleted | AADQ-youth report | Scale mean if item deleted | Corrected item-total correlation | Cronbach’s Alpha if item deleted |
|---|---|---|---|---|---|---|---|
| AADQ.P.1 | 21.9184 | .519 | .808 | AADQ.youth.1 | 21.5714 | .669 | .865 |
| AADQ.P.2 | 21.9490 | .546 | .805 | AADQ.youth.2 | 21.5561 | .715 | .861 |
| AADQ.P.3 | 21.7755 | .504 | .810 | AADQ.youth.3 | 21.6327 | .553 | .875 |
| AADQ.P.4 | 21.8061 | .538 | .806 | AADQ.youth.4 | 21.6327 | .570 | .873 |
| AADQ.P.5 | 21.8878 | .492 | .811 | AADQ.youth.5 | 21.6429 | .620 | .869 |
| AADQ.P.6 | 21.8214 | .519 | .808 | AADQ.youth.6 | 21.6020 | .597 | .871 |
| AADQ.P.7 | 21.9388 | .492 | .812 | AADQ.youth.7 | 21.5612 | .642 | .867 |
| AADQ.P.8 | 21.7194 | .630 | .795 | AADQ.youth.8 | 21.6378 | .623 | .869 |
| AADQ.P.9 | 21.7959 | .509 | .809 | AADQ.youth.9 | 21.4898 | .654 | .866 |
AADQ.P AADQ parent-report, AADQ.Youth: AADQ youth-report
Test-retest reliability
Test-retest reliability (from 45 participants) with 1 week was assessed by the interclass correlation coefficient (ICC). The reliability coefficient of the DAAS, AADQ-parent report and AADQ-youth report were 0.93, 0.82, and 0.92, respectively.
Validity
The correlation between the AADQ-youth report, AADQ-parent report, DAAS, AFQ-Y8, ERQ-CA, and CAMM was calculated to investigate the validity. As shown in Table 3, most convergent and divergent correlations are significant at the 0.01 level. Therefore, AADQ-YR, AADQ-PR, DAAS, and its subscales have appropriate Validity levels.
Table 3.
Pearson’s coefficient correlations among variables
| 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ||
|---|---|---|---|---|---|---|---|---|---|
| 1 | AADQ-YR | 0.68** | 0.16* | 0.22** | 0.21** | −0.16* | 0.13 | 0.15* | −0.15* |
| 2 | AADQ-PR | 1 | 0.08 | 0.162* | 0.15* | −0.16* | 0.17* | 0.25** | −0.22** |
| 3 | DAAS-Avoidance | 1 | 0.339** | 0.32** | −0.17* | 0.15* | 0.22** | −0.15* | |
| 4 | DAAS-values impairment | 1 | 0.29* | −0.22** | 0.07 | 0.15* | 0.007 | ||
| 5 | DAAS-fusion | 1 | −0.21** | 0.19* | 0.14* | 0.24** | |||
| 6 | AFQ-Y8 | 1 | 0.13 | 0.15* | 0.13 | ||||
| 7 | CAMM | 1 | 0.23** | −0.18* | |||||
| 8 | ERQ-CA. reappraisal | 1 | 0.29** | ||||||
| 9 | ERQ-CA. suppression | 1 |
**Correlation is significant at the 0.01 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed)
AADQ-YR Acceptance and Action Diabetes Questionnaire Youth Report, AADQ-PR Acceptance and Action Diabetes Questionnaire Parent Report, AFQY Avoidance and Fusion Questionnaire for Youth, CAMM Child and Adolescent Mindfulness Measure, DAAS Diabetes Acceptance and Action Scale for Children and Adolescents
Exploratory factor analysis (EFA)
As DAAS has three subscales, we decided to evaluate the EFA of DAAS. KMO test showed perfect sampling adequacy (0.866). Bartlett’s Test was significant (chi-square value = 1589.894, P value<0.05) that explained the items are correlated, and factor analysis can be fitted. Latent factors were obtained from the principal components analysis. The extracted factors were rotated with the varimax method. This criterion suggested the three-factor, which explained 51.83% of the variance (Table 4 & Fig. 1). The pattern matrix of extracted factors is shown in Table 5. As shown in Table 5, exactly three sub-factors were detected for the DAAS test. These factors were the same dimensions discovered by the original version of the questionnaire. Therefore, in terms of confirmatory factor analysis, this tool has three separate sub-factors.
Table 4.
Extracted principal components with Eigenvalues, Cumulative percentage of explained variance
| Component | Initial solution | Rotated solution | |
|---|---|---|---|
| Cumulative % of variance explained | Eigenvalue | Eigenvalue | |
| 1 | 6.065 | 27.570 | 27.570 |
| 2 | 2.852 | 12.964 | 40.534 |
| 3 | 2.321 | 10.549 | 51.083 |
Fig. 1.
Scree plot to three factors of DAAS extracted by EFA with eigenvalues larger than 1.
Table 5.
Rotated component matrix for DAAS
| Component | |||
|---|---|---|---|
| 1 | 2 | 3 | |
| DAAS2 | .705 | ||
| DAAS18 | .675 | ||
| DAAS4 | .659 | ||
| DAAS16 | .657 | ||
| DAAS8. | .637 | ||
| DAAS7 | .616 | ||
| DAAS17 | .612 | ||
| DAAS12 | .611 | ||
| DAAS13 | .577 | ||
| DAAS14 | .572 | ||
| DAAS1 | .826 | ||
| DAAS9 | .801 | ||
| DAAS10 | .764 | ||
| DAAS6 | .758 | ||
| DAAS19 | .677 | ||
| DAAS11 | .672 | ||
| DAAS3 | .754 | ||
| DAAS22. | .731 | ||
| DAAS21 | .727 | ||
| DAAS5 | .705 | ||
| DAAS15 | .704 | ||
| DAAS20 | .704 | ||
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization
aRotation converged in 4 iterations
Confirmatory factor analysis
To confirm the latent structure of AADQ-YR, AADQ-PR, and DAAS, the CFA was evaluated. The analysis was carried out on the sample (n = 196). For DAAS, a factor solution with two to three factors was modeled to check if the 3-factor is the best. Indicators of models were shown in Table 4. AIC, BIC, RMSEA, and Standardized Root Mean Residual (SRMR) for the three-factor model are smaller than other models, and CFI is larger. Also, the model has the best indexes that show the three-factor extracted model is the best representation of the data structure. Figure 2 showed the best model fit for a three-factor solution. Also, For AADQ-YR, AADQ-PR, results showed that models are suited. These results also showed in Table 6 and Fig. 3.
Fig. 2.
Confirmatory factor analysis for DAAS
Table 6.
indicators to comparing for factor models in scales
| Fit indexes | X2 | P | X2/df | RMR | GFI | AGFI | NFI | CFI | IFI | PGFI | RMSEA |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 3 factors (DAAS) | 267.81 | 0.001 | 1.3 | 0.089 | 0..892 | 0.867 | 0.839 | 0.957 | 0.957 | 0.726 | 0.039 |
| AADQ-YR | 54.32 | 0.001 | 2.01 | 0.082 | 0.944 | 0.566 | 0.883 | 0.936 | 0.937 | 0.566 | 0.072 |
| AADQ-PR | 61.74 | 0.001 | 2.28 | 0.079 | 0.938 | 0.896 | 0.914 | 0.949 | 0.95 | 0.536 | 0.081 |
Fig. 3.
Confirmatory factor analysis for AADQ-YR and AADQ-PR
Discussion
The present study showed that the Persian version of DAAS and AADQ reliably and validly measures psychological flexibility in type 1 diabetes in children and adolescents. Flexibility is the main construct of change in the ACT. The results showed that these tools have an acceptable internal consistency. For DAAS, Cronbach’s alpha for all three subscales and the whole test was between 0.8 and 0.87. Also, in each AADQ form, Cronbach’s alpha was obtained above 0.8. All items in all three questionnaires had a significant role in internal consistency, because according to the results, by removing each item, the Cronbach’s alpha is reduced. Therefore, all items are decisive and should be included in the questionnaire.
Test-Retest Reliability also indicates the appropriate reliability of all three tools. The results showed that the obtained correlations indicate valid discriminant validity in all three tests regarding the validity. Regarding the DAAS, both confirmatory factor analysis and exploratory factor analysis were used. In the case of DAAS, the results of exploratory factor analysis showed that three subscales obtained by the original version of the questionnaire were also discovered in the Persian version. Three subscales, Values impairments, Fusion, and Avoidance, in the Persian version, explained more than half of the DAAS variance. Confirmatory factor analysis also indicated that the DAAS questionnaire was appropriate. In the factor analysis, the chi-square rate was 267.81, which was acceptable at a significant level. Other indicators obtained by confirmatory factor analysis indicated the fit of the analysis and the correlations obtained. For both forms of AADQ, confirmatory factor analysis showed that the chi-square rate was at a significant level (54.32 for youth report version and 61.75 for parent-report version). These results generally indicate the suitability of the model obtained for both forms of AADQ. In general, the results are in line with the findings of the main study of this tool design. In the main study conducted by berlin et al. (2020), the results showed that all three questionnaires AADQ-YR, AADQ- PR, and DAAS, can assess the degree of psychological flexibility in children and adolescents [8].
As the present study results showed, Cronbach’s alpha (internal consistency) in the DAAS questionnaire was higher than AADQ. One of the reasons for this is the existence of three almost separate subscales in DAAS. At DAAS, patients are evaluated for their degree of fusion with diabetes-related thoughts, avoidance of diabetes-related thoughts, and distorted values. Previous studies showed that inflexibility in the ACT model is a multidimensional and complex structure [22]. Psychological flexibility requires relating to thoughts and worries as integral parts of life. Therefore, cognitively flexible people have lower avoidance of unpleasant feelings, images, and thoughts [23]. Also, another component of psychological flexibility in the ACT context is cognitive defusion [24]. Higher scores on defusion indicate higher individuals separate thoughts, emotions, and mental images from reality [8, 25]. Just imagining an event is not considered as happening. In the DAAs tool, both of these structures are examined separately. Another cognitive flexibility is communication with goals [23, 24]. People need to set goals and stay on track. Moving in the direction of goals leads to committed action, as another component of cognitive flexibility [25]. DAAS also examines this structure. In total, these cases show that, both theoretically and operationally, the DAAS questionnaire measures cognitive flexibility more comprehensively. The AADQ tool also has advantages. For example, this tool has only nine items. Shorter questions are effective in hospital settings where treatment time and cost are important factors [26].This tool quickly performs a kind of screening of psychological flexibility. It also exists in two forms: youth-report and parent-report form. Therefore, psychological flexibility problems can be examined from two different perspectives (parent and patient), so a more comprehensive view with less error can be considered.
Besides, previous studies have shown that psychological flexibility reduces HbA1c and increases life quality in patients with type 1 diabetes [17]. Also, with the increase of psychological flexibility, the problems of distress in young people with type 1 diabetes will decrease, and self-care behaviors will increase [7]. Therefore, it is crucial to have a tool to evaluate psychological flexibility, as one of the important goals in patients with type 1 diabetes.
Limitation and future directions
Despite the promising results, the present study faced some limitations. The most important limitation was the cross-sectional study of psychological flexibility in these individuals. Also, due to the problems caused by the covid19 epidemic, no additional studies were conducted on the relationship between the severity of psychological flexibility problems and the severity of people’s problems. It is suggested that a youth-report form for DAAS should be developed in future studies. The long-term effect of flexibility on physical and psychological symptoms can also be examined in a longitudinal study. Besides, interventions based on increasing psychological flexibility can be developed, and their effectiveness can be predicted by ACT treatment. The study of neuropsychological and neuroimaging correlations with psychological flexibility provides more accurate results in understanding this psychological construct.
Supplementary Information
(DOCX 22 kb)
Acknowledgements
We want to express our gratitude to the all participants that participate in this study.
Declaration
Ethical consideration
Before administering the investigation, one telephone-based session was held to justify all patients and their parents. In these sessions, ethical matters and explanations about the investigation were given to the individuals. Then, a consent form was given from all parents by WhatsApp platform. Participants were convinced that their data and identities would be kept private. Also, their medical information will not be given to a third party. Also, all procedures used in collecting survey data on which this paper relies on, are in accordance with the ethical standards of the Helsinki Declaration of 1964 and subsequent amendments or ethical standards.
Conflict of interest
The authors report no conflicts of interest in this project.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Faulkner MS, Chang L-I. Family influence on self-care, quality of life, and metabolic control in school-age children and adolescents with type 1 diabetes. J Pediatr Nurs. 2007;22(1):59–68. doi: 10.1016/j.pedn.2006.02.008. [DOI] [PubMed] [Google Scholar]
- 2.Diabetes: Risks for children https://www.who.int/news-room/q-a-detail/diabetes-risks-for-children2016.
- 3.Patterson CC, Karuranga S, Salpea P, Saeedi P, Dahlquist G, Soltesz G, et al. Worldwide estimates of incidence, prevalence and mortality of type 1 diabetes in children and adolescents: Results from the International Diabetes Federation Diabetes Atlas. Diabetes Res Clin Pract. 2019;157:107842. doi: 10.1016/j.diabres.2019.107842. [DOI] [PubMed] [Google Scholar]
- 4.Vasigh A, Abdi A, Borji M, Tarjoman A. The prevalence of neuropathy among type 1 diabetic adolescents in Iran: a systematic review and meta-analysis. Int J Adolesc Med Health. 2019;1(ahead-of-print). [DOI] [PubMed]
- 5.Carroll AE, Marrero DG. The role of significant others in adolescent diabetes. Diabetes Educ. 2006;32(2):243–252. doi: 10.1177/0145721706286893. [DOI] [PubMed] [Google Scholar]
- 6.Murillo M, Bel J, Pérez J, Corripio R, Carreras G, Herrero X, Mengibar JM, Rodriguez-Arjona D, Ravens-Sieberer U, Raat H, Rajmil L. Health-related quality of life (HRQOL) and its associated factors in children with type 1 diabetes mellitus (T1DM) BMC Pediatr. 2017;17(1):16. doi: 10.1186/s12887-017-0788-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kamody RC, Berlin KS, Rybak TM, Klages KL, Banks GG, Ali JS, Alemzadeh R, Ferry RJ, Jr, Diaz Thomas AM. Psychological flexibility among youth with type 1 diabetes: relating patterns of acceptance, adherence, and stress to adaptation. Behav Med. 2018;44(4):271–279. doi: 10.1080/08964289.2017.1297290. [DOI] [PubMed] [Google Scholar]
- 8.Berlin KS, Keenan ME, Cook JL, Ankney RL, Klages KL, Semenkovich K, Rybak TM, Banks GG, Alemzadeh R, Eddington AR. Measuring psychological flexibility in youth with type 1 diabetes. Pediatr Diabetes. 2020;21(8):1566–1574. doi: 10.1111/pedi.13110. [DOI] [PubMed] [Google Scholar]
- 9.Nikkhah Ravari O, Mousavi SZ, Babak A. Evaluation of the effects of 12 weeks mindfulness-based stress reduction on glycemic control and mental health indices in women with diabetes mellitus type 2. Adv Biomed Res. 2020;9:61. doi: 10.4103/abr.abr_133_20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Ngan HY, Chong YY, Chien WT. Effects of mindfulness- and acceptance-based interventions on diabetes distress and glycaemic level in people with type 2 diabetes: Systematic review and meta-analysis. Diabetic Med. 2021:e14525. [DOI] [PubMed]
- 11.Ni Y, Ma L, Li J. Effects of mindfulness-based stress reduction and mindfulness-based cognitive therapy in people with diabetes: a systematic review and meta-analysis. J Nurs Scholarsh. 2020;52(4):379–388. doi: 10.1111/jnu.12560. [DOI] [PubMed] [Google Scholar]
- 12.Fanning J, Osborn CY, Lagotte AE, Mayberry LS. Relationships between dispositional mindfulness, health behaviors, and hemoglobin A1c among adults with type 2 diabetes. J Behav Med. 2018;41(6):798–805. doi: 10.1007/s10865-018-9938-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Miller F, Anderson M, Tucker D, Vaz K, Brown J, Anderson-Jackson L, et al. Diabetes: biopsychosocial features affecting metabolic control and treatment adherence. Biopsychosocial Perspectives and Practices for Addressing Communicable and Non-Communicable Diseases: IGI Global; 2020. p. 106–33.
- 14.Dindo L, Van Liew JR, Arch JJ. Acceptance and commitment therapy: a transdiagnostic behavioral intervention for mental health and medical conditions. Neurotherapeutics. 2017;14(3):546–553. doi: 10.1007/s13311-017-0521-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Bai Z, Luo S, Zhang L, Wu S, Chi I. Acceptance and commitment therapy (ACT) to reduce depression: a systematic review and meta-analysis. J Affect Disord. 2020;260:728–737. doi: 10.1016/j.jad.2019.09.040. [DOI] [PubMed] [Google Scholar]
- 16.Lloyd J, Bond FW, Flaxman PE. The value of psychological flexibility: examining psychological mechanisms underpinning a cognitive behavioural therapy intervention for burnout. Work Stress. 2013;27(2):181–199. doi: 10.1080/02678373.2013.782157. [DOI] [Google Scholar]
- 17.Gregg JA, Callaghan GM, Hayes SC, Glenn-Lawson JL. Improving diabetes self-management through acceptance, mindfulness, and values: a randomized controlled trial. J Consult Clin Psychol. 2007;75(2):336–343. doi: 10.1037/0022-006X.75.2.336. [DOI] [PubMed] [Google Scholar]
- 18.Greco LA, Lambert W, Baer RA. Psychological inflexibility in childhood and adolescence: development and evaluation of the avoidance and fusion questionnaire for youth. Psychol Assess. 2008;20(2):93–102. doi: 10.1037/1040-3590.20.2.93. [DOI] [PubMed] [Google Scholar]
- 19.Shabani MJ, Mohsenabadi H, Zanjani Z. Psychometric properties of the Persian version of the avoidance and fusion questionnaire for youth. J Mazandaran Univ Med Sci. 2018;28(164):91–101. [Google Scholar]
- 20.Lotfi M, Bahrampouri L, Amini M, Fatemitabar R, Birashk B, Entezari M, et al. Persian adaptation of emotion regulation questionnaire for children and adolescents (ERQ-CA) J Mazandaran Univ Med Sci. 2019;29(175):117–128. [Google Scholar]
- 21.Mohsenabadi H, Shabani MJ, Assarian F, Zanjani Z. Psychometric properties of the child and adolescent mindfulness measure: A psychological measure of mindfulness in youth. Iran J Psychiatry Behav Sci. 2020;14(1).
- 22.Ciarrochi J, Bilich L, Godsell C. Psychological flexibility as a mechanism of change in acceptance and commitment therapy. Assessing mindfulness and acceptance processes in clients: Illuminating the theory and practice of change 2010:51–75.
- 23.Bond FW, Hayes SC, Barnes-Holmes D. Psychological flexibility, ACT, and organizational behavior. J Organ Behav Manag. 2006;26(1–2):25–54. [Google Scholar]
- 24.Scott W, McCracken LM. Psychological flexibility, acceptance and commitment therapy, and chronic pain. Curr Opin Psychol. 2015;2:91–96. doi: 10.1016/j.copsyc.2014.12.013. [DOI] [Google Scholar]
- 25.Kashdan TB, Rottenberg J. Psychological flexibility as a fundamental aspect of health. Clin Psychol Rev. 2010;30(7):865–878. doi: 10.1016/j.cpr.2010.03.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Stuart GW. Principles and practice of psychiatric nursing-e-book: Elsevier Health Sciences; 2014.
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
(DOCX 22 kb)