Ultimately, after the above steps, the final version of the questionnaire was prepared without any changes to assess construct validity and reliability. A cross-sectional study was designed to perform construct validity and reliability. Using convenient sampling method, 400 literate patients with T2D (aged over 25 years) and a history of diabetes for at least one year were selected from among the patients admitted to the specialized diabetes clinic of Khoy, Iran. Of these, 37 were not willing to participate in the study, and finally, 363 people entered the study. Then, 50 patients performed a test-retest at two-week intervals to determine the reliability of stability, 30 patients participated in completing questionnaires to determine internal consistency, and the remaining 283 participated in construct validity. The sample size in this section was determined according to at least ten samples for each item of the questionnaire (
28) (
Figure 1).
As in the psychometric evaluation of the original version of the questionnaire by instrument designers, exploratory factor analysis (EFA) was carried out to summarize and categorize the data and determine the aspects of the questionnaire. Having an accepted default, it was used to confirm it through convergent validity by the internal consistency method and determine the pattern fit. The model fit was the extent to which a model was compatible with the relevant data. Thus, in this section, the fit of the assumed research model was evaluated to ensure its compatibility with the research data, and finally, the answers to the research questions were inferred (
29).
Factor loadings are measured by calculating the correlation of the characteristics of a construct with that construct. If this value is equal to or greater than 0.4, it confirms that the variance between the construct and its parameters is greater than the variance of the measurement error of that construct, and the reliability of model is acceptable (
30). The important point is that if the researcher faces values less than 0.4 after calculating the factor loadings between the construct and its indices, s/he must modify those indices (questions) or remove them from his model (
30), that was not the case in our study. It has been suggested that researchers consider some indices to determine the pattern fit (
31). The indices used in this study were standardized root mean squared residual (SRMR), normalized fit index (NFI), goodness of fit (GOF), d-ULS, and d-G. NFI and GOF indices are from 0 to 1, and the closer the values are to 1, the more appropriate and fit the model (
32). The acceptable values for SRMR less than 0.08 show adequate fit, and values less than 0.05 indicate good fit (
33,
34). Moreover, the value of Q
2 (Stone- Geisser) statistic, determining the predictive power of the model in endogenous structures, was calculated. The models with an acceptable structural fit should be able to predict the endogenous variables of the model. This means that if the relationships between constructs are properly defined in a model, the constructs will have a sufficient effect on each other, and thus the hypotheses are correctly confirmed. Henseler et al. determined the values 0.02, 0.15, and 0.35 as low, medium, and strong predictive power, respectively (
35).