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Purpose: The aims of this study were to develop a new instrument for measuring self-management with a hierarchical structure [the Diabetes Self-Management Scale (DSMS)] in patients with type 2 diabetes, and evaluate its psychometric properties. Method: The DSMS instrument was developed in three phases: (1) conceptualization and item generation; (2) content validity and pilot testing; and (3) field testing of its psychometric properties. A convenience sample of 473 participants was recruited in three university hospitals and one regional health center, South Korea. Results: Exploratory and confirmatory factor analyses yielded two second-order component models explaining the common variance among six first-order factors. Principal axis factoring with a varimax rotation accounted for 60.88% of the variance. Confirmatory factor analysis of the hierarchical structure revealed the following fit indices: c 2 /df ¼ 1.373, standardized root-mean-square residual ¼ .050, goodness-of-fit index ¼ .935, incremental fit index ¼ .975, comparative fit index ¼ .974, and root-meansquare error of approximation ¼ .039. All Cronbach' a values for internal consistency exceeded the criterion of .70. All of the intraclass correlation coefficients for testeretest reliability exceeded .70 except that for the taking-medication subscale. The components of the DSMS were moderately correlated with the comparator measures of self-efficacy and health literacy administered for convergent validity. Conclusion: The DSMS is a new instrument for measuring the complex nature of self-management in patients with type 2 diabetes, comprising 17 items scored on a five-point Likert scale. The DSMS exhibits satisfactory psychometric properties for five reliability and validity metrics, and so is a suitable instrument to apply in both research and clinical practices.

Background: This study aims to investigate the relationship of Type D personality to glycated hemoglobin (HbA1c) and health-related quality of life (HRQOL) directly, and also indirectly via diabetes distress and social isolation in people with type 2 diabetes. Methods: Secondary data analysis of a cross-sectional survey was used. Data on 524 people with type 2 diabetes from outpatient clinics were obtained from June 2020 to February 2021. The hypotheses of this study were tested using the PROCESS macro with 10,000 bootstrapping iterations to estimate 95% con dence intervals (CIs) for indirect (mediating) effects.Results: Type D personality was present in 31.3% of the participants, and exerted a signi cant direct effect on HRQOL but not on HbA1c. Type D personality exerted a signi cant indirect effects on HbA1c via diabetes distress and social isolation (95% CI = 0.014 to 0.163 and 0.007 to 0.121, respectively), and on HRQOL via diabetes distress and social isolation (95% CI = -0.335 to -0.178 and -0.056 to -0.008, respectively). The indirect effects of Type D personality on HRQOL via diabetes distress had a greater magnitude than that via social isolation. Conclusion: It is necessary for health professionals to monitor people with type 2 diabetes to determine whether Type D personality is present. Those with Type D personality should be provided with interventions to reduce diabetes distress and alleviate social isolation in order to improve their glycemic control and HRQOL.

Background The internet has become a major source of health information, and obtaining appropriate information requires various abilities and skills, labeled as electronic health literacy (eHealth literacy). The existing instruments for measuring eHealth literacy are outdated because they were developed during the Web 1.0 era, or not sufficiently sensitive for people with a specific condition or disease because they were designed to assess eHealth literacy over a broad range for a general population. Approximately one in ten adults worldwide live with diabetes. Health professionals have a responsibility to identify patients with low eHealth literacy to prevent them from obtaining misleading internet diabetes information. Aims The aims were to develop a condition-specific eHealth literacy scale for diabetes and to evaluate its psychometric properties among people with type 2 diabetes. Methods An instrument development design was used. This study recruited 453 people diagnosed with type 2 diabetes at the outpatient clinics of hospitals in 2021. Psychometric properties (internal consistency, measurement invariance, and content, structural, convergent, and known-groups validities) were analyzed. Results An expert panel assessed content validity. Exploratory factor analysis, exploratory graph analysis, and confirmatory factor analysis (CFA) for structural validity yielded a two-factor solution (CFI = 0.977, SRMR = 0.029, RMSEA = 0.077). Cronbach’s alpha and omega values were excellent for each factor (0.87–0.94). Multigroup CFA yielded configural and metric measurement invariance across the gender, age, and glycemic control status groups. Convergent validity with a comparator instrument to measure health literacy was supported by a moderate correlation, and known-groups validity determined using groups with different internet-use frequencies was satisfied with a high effect size. Conclusion A new condition-specific eHealth literacy scale for people with type 2 diabetes was developed, comprising 10 items. The scale exhibited good psychometric properties; however, test–retest reliability must be determined for the stability of the scale and cross-cultural validity is required among different languages. The brief scale has the merits of being feasible to use in busy clinical practice and being less burdensome to respondents. The scale can be applied in clinical trials of internet-based diabetes interventions for assessing the eHealth literacy of respondents.

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