334 resultados para defensive behaviors


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Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

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The aim of this paper is to utilize a poroviscohyperelastic (PVHE) model which is developed based on the porohyperelastic (PHE) model to explore the mechanical deformation properties of single chondrocytes. Both creep and relaxation responses are investigated by using FEM models of micropipette aspiration and AFM experiments, respectively. The newly developed PVHE model is compared thoroughly with the SnHS and PHE models. It has been found that the PVHE can accurately capture both creep and stress relaxation behaviors of chondrocytes better than other two models. Hence, the PVHE is a promising model to investigate mechanical properties of single chondrocytes.

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The nature of construction projects and their delivery exposes participants to accidents and dangers. Safety climate serves as a frame of reference for employees to make sense of safety measures in the workplace and adapt their behaviors. Though safety climate research abounds, fewer efforts are made to investigate the formation of a safety climate. An effort to explore forming psychological safety climate, an operationalization of safety climate at the individual level, is an appropriate starting point. Taking the view that projects are social processes, this paper develops a conceptual framework of forming the psychological safety climate, and provides a preliminary validation. The model suggests that management can create the desired psychological safety climate by efforts from structural, perceptual, interactive, and cultural perspectives. Future empirical research can be built on the model to provide a more comprehensive and coherent picture of the determinants of safety climate.

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Transit passenger market segmentation enables transit operators to target different classes of transit users for targeted surveys and various operational and strategic planning improvements. However, the existing market segmentation studies in the literature have been generally done using passenger surveys, which have various limitations. The smart card (SC) data from an automated fare collection system facilitate the understanding of the multiday travel pattern of transit passengers and can be used to segment them into identifiable types of similar behaviors and needs. This paper proposes a comprehensive methodology for passenger segmentation solely using SC data. After reconstructing the travel itineraries from SC transactions, this paper adopts the density-based spatial clustering of application with noise (DBSCAN) algorithm to mine the travel pattern of each SC user. An a priori market segmentation approach then segments transit passengers into four identifiable types. The methodology proposed in this paper assists transit operators to understand their passengers and provides them oriented information and services.