Adaptation and psychometric validation of Diabetes Health Profile (DHP-18) in patients with type 2 diabetes in Quito, Ecuador: a cross-sectional study

Validation of the Chinese version of the diabetes health profile to predict the impact of mobile health education on quality of life in type 2 diabetes patients

Purpose

The Diabetes Health Profile (DHP18), initially created in the United Kingdom, currently lacks a Chinese version. This study endeavors to authenticate the Chinese adaptation of the DHP18 and assess the influence of mobile health (mHealth) education intervention on the quality of life of individuals living with diabetes.

Patients and methods

The study included 470 Type 2 diabetes Mellitus (T2DM) patients (204 men, 266 women), spanning an age range of 19-79 years, with an average age of 54 ± 12.40 years. Data analysis employed Jamovie and Mplus software. Moreover, test-retest reliability was evaluated in 52 hospitalized T2DM patients through two repeated measurements taken 4 weeks apart.

Results

The Chinese version DHP18 scale exhibited high reliability, evidenced by a Cronbach's alpha of 0.88, and coefficient of test-retest reliability of 0.84. Individual subscales also demonstrated strong reliability, ranging from 0.76 to 0.84, with test-retest reliability spanning from 0.71 to 0.74. Confirmatory Factor Analysis (CFA) employing a three-factor structure (χ2 = 294.69, GFI = 0.92, TLI = 0.91, RMSEA = 0.05, SRMR = 0.06) validated the scale's construct validity. Notably, there was a statistically significant difference (p < 0.05) in the quality of life between Type 2 diabetes patients using mHealth education intervention and those without mHealth education intervention. Mediation analysis revealed that Appraisal of Diabetes (ADS) and Self-Management Efficacy (SED) mediated the effects of Psychological Distress (PD) and Behavior Adherence (BA) on quality of life, both significant direct and indirect effects (p < 0.001). In addition, Dietary Abstinence (DE) displayed significant overall impact (β = -0.13, p < 0.001) and indirect influence (β = -0.10, p < 0.01) on diabetic patients' quality of life, though lacking a significant direct effect (β = -0.03, p = 0.38).

Conclusion

The Chinese version of the Diabetes Health Profile Scale meets stringent psychometric standards and stands as an appropriate measurement tool for Chinese T2DM patients, maintaining comparable results to the original scale's structure. The mHealth education intervention yielded a notably positive impact on the quality of life among T2DM patients. Mediation analysis revealed that the three dimensions of the DHP were mediated by Appraisal of Diabetes and Diabetes Self-Management Efficacy, partially mediated by Psychological Distress and Behavior Adherence, and fully mediated by Dietary Abstinence, providing insight into the positive effects of the mHealth model on the quality of life of diabetic patients.

[Predictive factors for the level of knowledge, attitudes and quality of life of Tunisian diabetics : 1007 cases]

AIM OF THE STUDY

To study the predictors of knowledge level, attitudes and quality of life of type 1(T1D) and type 2 (T2D) Tunisian diabetics POPULATION AND METHODS: We undertook an analytical cross-sectional study. The questionnaire was administered in Arabic and contained a section collecting socio-demographic, clinical and diabetes-specific data. The following sections contained the Arabic-translated and validated versions of the "Simplified Diabetes Knowledge Scale", the "Diabetes Attitude Scale-3" and the "Diabetes Health Profile-18" to assess level of diabetes knowledge, attitudes towards the disease and diabetics' quality of life.

RESULTS

We collected 186 T1D (18.5%) and 821 T2D (81.5%) completed questionnaires. A good level of knowledge about diabetes was indicated in T1D patients by glycemic self-monitoring and by secondary and university education, urban housing, stable employment, insulin therapy and prior therapeutic education, while regular medical follow-up was of particular importance in T2DM patients. Smoking and diabetes complications were predictors of a negative attitude towards the disease in T1D and T2D respectively. Diabetics' Impaired quality of life was predicted by age < 40 years and a low level of knowledge about diabetes in T1D and by female sex, insulin therapy and a low level of knowledge about diabetes in T2D.

CONCLUSION

Predictors of the level of knowledge, attitudes and quality of life of diabetics may be a basis for establishing a therapeutic education program tailored to the different populations.

Patient-reported outcome measures for assessing health-related quality of life in people with type 2 diabetes: A systematic review

Patient-Reported Outcome Measures (PROMs) are important tools to assess outcomes relevant to patients, with Health-Related Quality Of Life (HRQOL) as an important construct to be measured. Many different HRQOL PROMs are used in the type 2 diabetes field, however a complete overview of these PROMs is currently lacking. We therefore aimed to systematically describe and classify the content of all PROMs that have specifically been developed or validated to measure (aspects of) HRQOL in people with type 2 diabetes. A literature search was performed in PubMed and EMBASE until 31 December 2021. Studies on the development or validation of a PROM measuring HRQOL, or aspects of HRQOL, in people with type 2 diabetes were included. Title and abstract and full-text screening were conducted by two independent researchers and data extraction was performed independently by one of the researchers. Data were extracted on language in which the PROM was developed, target population, construct(s) being measured, names of (sub)scales and number of items per (sub)scale. In addition, all PROMs and subscales were classified according to specific aspects of HRQOL based on the Wilson & Cleary model (symptom status, functional status, general health perceptions) to aid researchers in PROM selection. In total 220 studies were identified that developed or validated PROMs that measure (aspects of) HRQOL in people with type 2 diabetes. Of the 116 unique HRQOL PROMs, 91 (of the subscales) measured symptom status, 60 measured functional status and 26 measured general health perceptions. In addition, 16 of the PROMs (subscales) measured global quality of life. 61 of the 116 PROMs (subscales) also include characteristics of the individual (e.g. aspects of personality, coping) or environment (e.g. social or financial support) and patient-reported experience measures (PREMs, e.g. measure of a patient's perception of their personal experience of the healthcare they have received, e.g. treatment satisfaction), which are not part of the HRQOL construct. Only 9 of the 116 PROMs measure all aspects of HRQOL based on the Wilson & Cleary model. Finally, 8 of the 116 PROMs stating to measure HRQOL, measured no HRQOL construct. In conclusion, a large number of PROMs are available for people with type 2 diabetes, which intend to measure (aspects of) HRQOL. These PROMs measure a large variety of (sub)constructs, which are not all HRQOL constructs, with a small amount of PROMs not measuring HRQOL at all. There is a need for consensus on which aspects of HRQOL should be measured in people with type 2 diabetes and which PROMs to use in research and daily practice. PROSPERO: CRD42017071012. COMET database: http://www.comet-initiative.org/studies/details/956 .

Content Validity of Patient-Reported Outcome Measures Developed for Assessing Health-Related Quality of Life in People with Type 2 Diabetes Mellitus: a Systematic Review

PURPOSE OF REVIEW

We aimed to systematically evaluate the content validity of patient-reported outcome measures (PROMs) specifically developed to measure (aspects of) health-related quality of life (HRQOL) in people with type 2 diabetes. A systematic review was performed in PubMed and Embase of PROMs measuring perceived symptoms, physical function, mental function, social function/participation, and general health perceptions, and that were validated to at least some extent. Content validity (relevance, comprehensiveness, and comprehensibility) was evaluated using COSMIN methodology.

RECENT FINDINGS

We identified 54 (different versions of) PROMs, containing 150 subscales. We found evidence for sufficient content validity for only 41/150 (27%) (subscales of) PROMs. The quality of evidence was generally very low. We found 66 out of 150 (44%) (subscales of) PROMs with evidence for either insufficient relevance, insufficient comprehensiveness, or insufficient comprehensibility. For measuring diabetes-specific symptoms, physical function, mental function, social function/participation, and general health perceptions, we identified one to 11 (subscales of) PROMs with sufficient content validity, although quality of the evidence was generally low. For measuring depressive symptoms, no PROM with sufficient content validity was identified. For each aspect of HRQL, we found at least one PROM with sufficient content validity, except for depressive symptoms. The quality of the evidence was mostly very low.