Effects of a diabetes education program integrated with text-message support for lifestyle change among older individuals with type 2 diabetes in communities: a randomised controlled trial.

OBJECTIVE: The objective of this study was to investigate the effects of self-management education integrated with text-message support (SME-TMS) on glycaemic control in individuals with type 2 diabetes. STUDY DESIGN: a randomized, controlled trial. METHODS: Patients from two communities were randomized into the intervention group (n = 53) or the control group (n = 52). The six-month intervention included the culturally tailored diabetes education and text-messaging support for behaviour changes. The control group received treatment as usual. The primary outcome was reductions in HbA1c and fasting blood glucose at six-month non-intervention follow-up. Secondary outcomes were reductions in body weight, body mass index (BMI), blood pressure, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, physical activity, and health beliefs. RESULTS: The intervention led to substantially increase days of weekly physical activity (42% vs. 0%, P < 0.001) and health beliefs (coefficient = 7.0, 95% confidence interval [CI]: 4.4 to 9.6, P < 0.001). However, no greater reduction was found in HbA1c at six months after the intervention, compared with the control group (0.13%, 95% CI: -0.20 to 0.46, P = 0.443). The reductions of blood pressure, TC, and LDL-C were greater in the control group than in the intervention group (all P < 0.050). Within the intervention group, participants had significant reduction in BMI, whereas the control group had greater reductions in TC and LDL-C (all P < 0.050). CONCLUSIONS: The SME-TMS intervention led to a greater increase in the weekly physical activity and health belief score in the older patients at 6-month follow-up than with the usual care. Further research is needed to ascertain how these benefits could be translated into favorable medium-and long-term glycaemic control. TRAIL REGISTRATION NUMBER: This study was registered on Chinese Clinical Trials Registry (ChiCTR2300075112).

Fourier based partial least squares algorithm: new insight into influence of spectral shift in "frequency domain".

Developments in analytical chemistry technology, especially the combination between the partial least squares and spectroscopy, have contributed significantly to predicting the chemical concentrations and discriminating similar chemical analytes. However, spectral shift is an unwanted but inevitable factor for the spectroscopic analyzer, especially in practical application, which decreases the method's accuracy and stability. To remove the term of spectral shift completely and increase the robustness of spectroscopic analysis method, Fourier transform based partial least squares method was proposed. The approach used Fourier transform first to transform the spectral shift in the "time domain" to the phase term in the "frequency domain." The module of the Fourier transformed spectra was then calculated. As a result, the phase term was removed (the module of the phase term is 1), which means the spectral shift term was removed completely. Finally, the spectra modules were used to build the model and validate. The approach's advantages are: (i) that the approach provides a new insight to treat the spectral shift in spectroscopic analyzer; (ii) that the model is insensitive to spectral shift; (iii) that the approach makes partial least squares combined with spectroscopy more suitable for practical application, rather than lab experiment, because spectral shift is permitted, which means the decreased requirements of measure environment. As an example, blood species discrimination, using Raman spectroscopy, was used in order to demonstrate this approach's effectiveness.