Development and Validation of the DiAbeTes Education Questionnaire (DATE-Q) to Measure Knowledge Among Diabetes and Prediabetes Patients Attending Cardiac Rehabilitation Programs.

PURPOSE: Knowledge assessment tools are highly useful in clinical practice, as they help health care teams to customize education and clinical care plans based on the needs of patients. The objective of this study was to develop and validate the DiAbeTes Education Questionnaire (DATE-Q) to measure knowledge among diabetes and prediabetes patients attending cardiac rehabilitation (CR). METHODS: Based on patient information needs, other validated tools and diabetes education standards and current practices, experts developed 20 items to comprise the first version of the DATE-Q. To establish content validity, they were reviewed by an expert panel (n = 12) and patients. Refined items were psychometrically tested in 84 diabetes and prediabetes patients attending CR. The internal consistency was assessed via regularized factor analysis and Cronbach α, and criterion validity with regard to patient education and family income. For interpretability analysis, the minimal clinically important difference (MCID) was estimated using distribution- and anchor-based methods. RESULTS: All items were appropriate for administration in this population according to experts and patients. Three factors were extracted and were generally internally consistent and well defined by the items. Criterion validity was supported by significant differences in mean scores by family income (P < .05). Results showed that increases in knowledge can moderately increase mean steps/d and peak oxygen uptake, with an MCID of 2.13. CONCLUSIONS: This study demonstrated preliminary validity of the DATE-Q. Future research is needed to assess other measurement properties to confirm the applicability of this tool in clinical and research settings.

Effectiveness of an education intervention associated with an exercise program in improving disease-related knowledge and health behaviours among diabetes patients.

OBJECTIVE: to assess the effectiveness of an education intervention associated with an exercise program in improving knowledge and health behaviours among diabetes patients. METHODS: Diabetes and prediabetes patients were exposed to an evidence- and theoretically-based comprehensive education intervention over 24 weeks. Patients completed surveys assessing knowledge, physical activity, food intake, self-efficacy, and health literacy. Functional capacity was measured by oxygen uptake. All outcomes were assessed pre- and post-CR. Satisfaction about the education provided was assessed at post-CR. Paired t-tests, Pearson correlation coefficients, and linear regression models were computed to investigate the effectiveness of this intervention. RESULTS: 84 patients consented to participate, of which 47(56.0%) completed post-CR assessments. There was a significant improvement in patients' overall knowledge pre- to post-CR, as well as in physical activity, food intake, self-efficacy, and health literacy (p < 0.05). Peak VO2 has clinically significant improved. Results showed a low significant positive correlation was between post-CR knowledge and food intake(r = 0.297;p = 0.04). Linear regression analysis revealed that age(B=-0.051; p = 0.01) was influential in changing post-CR knowledge. CONCLUSION: The benefits of an education intervention designed for diabetes and prediabetes patients associated with an exercise program have been supported. PRACTICE IMPLICATIONS: This work shows one effective education strategy taken in place that can be replicated in different settings.

Computational Simulation Expands Understanding of Electrotransfer-Based Gene Augmentation for Enhancement of Neural Interfaces.

The neural interface is a critical factor in governing efficient and safe charge transfer between a stimulating electrode and biological tissue. The interface plays a crucial role in the efficacy of electric stimulation in chronic implants and both electromechanical properties and biological properties shape this. In the case of cochlear implants, it has long been recognized that neurotrophins can stimulate growth of the target auditory nerve fibers into a favorable apposition with the electrode array, and recently such arrays have been re-purposed to enable electrotransfer (electroporation)-based neurotrophin gene augmentation to improve the "bionic ear." For both this acute bionic array-directed electroporation and for chronic conventional cochlear implant arrays, the electric fields generated in target tissue during pulse delivery are central to efficacy, but are challenging to map. We present a computational model for predicting electric fields generated by array-driven DNA electrotransfer in the cochlea. The anatomically realistic model geometry was reconstructed from magnetic resonance images of the guinea pig cochlea and an eight-channel electrode array embedded within this geometry. The model incorporates a description of both Faradaic and non-Faradaic mechanisms occurring at the electrode-electrolyte interface with frequency dependency optimized to match experimental impedance spectrometry measurements. Our simulations predict that a tandem electrode configuration with four ganged cathodes and four ganged anodes produces three to fourfold larger area in target tissue where the electric field is within the range for successful gene transfer compared to an alternate paired anode-cathode electrode configuration. These findings matched in vivo transfection efficacy of a green fluorescent protein (GFP) reporter following array-driven electrotransfer of the reporter-encoding plasmid DNA. This confirms utility of the developed model as a tool to optimize the safety and efficacy of electrotransfer protocols for delivery of neurotrophin growth factors, with the ultimate aim of using gene augmentation approaches to improve the characteristics of the electrode-neural interfaces in chronically implanted neurostimulation devices.

Computational Simulation of Array-based Electroporation in the Cochlea.

We present a computational model for predicting electric field distributions following array-based closed-loop electroporation in the cochlea. The model geometry was reconstructed from magnetic resonance images of the guinea pig cochlea and an eight-channel electrode array embedded within this geometry. The model's electrode voltage output waveform was obtained from electric potential mapping conducted in physiological solution following constant-current stimulation using the electrode array. Our simulations predict that a tandem electrode configuration with four ganged cathodes and four ganged anodes produces a larger area in target tissue where the electric field is within the range for successful gene transfer compared to an alternate paired anode-cathode electrode configuration. These findings corroborate published in vivo evidence comparing the two configurations and support the utility of the developed model as a tool to optimize the efficacy of electroporation electrodes.