OBJECTIVE: To investigate the impact of customized CMI (C-CMI) on health-related quality of life (HRQoL) among type 2 diabetes mellitus (T2DM) patients in Qatar.
METHODS: This was a randomized controlled intervention study, in which the intervention group patients received C-CMI and the control group patients received usual care. HRQoL was measured using the EQ-5D-5L questionnaire and EQ visual analog scale (EQ-VAS) at three intervals [i.e. baseline, after 3 months and 6 months].
RESULTS: The EQ-5D-5L index value for the intervention group exhibited sustained improvement from baseline to the third visit. There was a statistically significant difference between groups in the HRQoL utility value (represented as EQ index) at 6 months (0.939 vs. 0.796; p = 0.019). Similarly, the intervention group compared with the control group had significantly greater EQ-VAS at 6 months (90% vs. 80%; p = 0.003).
CONCLUSIONS: The impact of C-CMI on health outcomes of T2DM patients in Qatar reported improvement in HRQoL indicators among the intervention patients. The study built a platform for health policymakers and regulatory agencies to consider the provision of C-CMI in multiple languages.
METHOD: Initially, the ICQ was translated into Malay and back-translated, and its content and face validity were evaluated. Then, 346 cancer patients with various cancer types received the ICQ-M, and its internal consistency, convergent, discriminant, construct, and concurrent validity were evaluated.
RESULTS: The ICQ-M and its domains had acceptable internal consistency with Cronbach's α ranging from 0.742 to 0.927. Construct validity assessment demonstrated that the ICQ-M consists of 17 items designated in two domains with good convergent and discriminant validity. The ICQ-M and its domains also had moderate correlations with the Acceptance and Action Questionnaire II, which denotes that the ICQ-M had acceptable concurrent validity.
CONCLUSION: The ICQ-M had good psychometric properties and is now available to measure the illness cognition of cancer patients in Malaysia.
Method: This study involves four main steps which translate text-based results from Extensible Markup Language (XML) serialisation format into graphs. The four steps include: (1) conversion of ontological dataset as graph model data; (2) query from graph model data; (3) transformation of text-based results in XML serialisation format into a graphical form; and (4) display of results to the user via a graphical user interface (GUI). Ontological data for plants and samples of trees and shrubs were used as the dataset to demonstrate how plant-based data could be integrated into the proposed data visualisation.
Results: A visualisation system named plant visualisation system was developed. This system provides a GUI that enables users to perform the query process, as well as a graphical viewer to display the results of the query in the form of a network graph. The efficiency of the developed visualisation system was measured by performing two types of user evaluations: a usability heuristics evaluation, and a query and visualisation evaluation.
Discussion: The relationships between the data were visualised, enabling the users to easily infer the knowledge and correlations between data. The results from the user evaluation show that the proposed visualisation system is suitable for both expert and novice users, with or without computer skills. This technique demonstrates the practicability of using a computer assisted-tool by providing cognitive analysis for understanding relationships between data. Therefore, the results benefit not only botanists, but also novice users, especially those that are interested to know more about plants.