4 resultados para COGNITIVE THEORY

em Duke University


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Evidence is reviewed that for older adults the period from 10 to 30 years of age produces recall of the most autobiographical memories, the most vivid memories, and the most important memories. It is the period from which peoples' favorite films, music, and books come and the period from which they judge the most important world events to have originated. Factual, semantic, general-knowledge, multiple-choice questions about the Academy Awards, the World Series, and current events from this period were answered more accurately by two different groups of 30 older adults tested 10 years apart. A cognitive theory based on the importance of transitions and several noncognitive theories are considered as explanations of this pervasive phenomenon.

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BACKGROUND/AIMS: The obesity epidemic has spread to young adults, and obesity is a significant risk factor for cardiovascular disease. The prominence and increasing functionality of mobile phones may provide an opportunity to deliver longitudinal and scalable weight management interventions in young adults. The aim of this article is to describe the design and development of the intervention tested in the Cell Phone Intervention for You study and to highlight the importance of adaptive intervention design that made it possible. The Cell Phone Intervention for You study was a National Heart, Lung, and Blood Institute-sponsored, controlled, 24-month randomized clinical trial comparing two active interventions to a usual-care control group. Participants were 365 overweight or obese (body mass index≥25 kg/m2) young adults. METHODS: Both active interventions were designed based on social cognitive theory and incorporated techniques for behavioral self-management and motivational enhancement. Initial intervention development occurred during a 1-year formative phase utilizing focus groups and iterative, participatory design. During the intervention testing, adaptive intervention design, where an intervention is updated or extended throughout a trial while assuring the delivery of exactly the same intervention to each cohort, was employed. The adaptive intervention design strategy distributed technical work and allowed introduction of novel components in phases intended to help promote and sustain participant engagement. Adaptive intervention design was made possible by exploiting the mobile phone's remote data capabilities so that adoption of particular application components could be continuously monitored and components subsequently added or updated remotely. RESULTS: The cell phone intervention was delivered almost entirely via cell phone and was always-present, proactive, and interactive-providing passive and active reminders, frequent opportunities for knowledge dissemination, and multiple tools for self-tracking and receiving tailored feedback. The intervention changed over 2 years to promote and sustain engagement. The personal coaching intervention, alternatively, was primarily personal coaching with trained coaches based on a proven intervention, enhanced with a mobile application, but where all interactions with the technology were participant-initiated. CONCLUSION: The complexity and length of the technology-based randomized clinical trial created challenges in engagement and technology adaptation, which were generally discovered using novel remote monitoring technology and addressed using the adaptive intervention design. Investigators should plan to develop tools and procedures that explicitly support continuous remote monitoring of interventions to support adaptive intervention design in long-term, technology-based studies, as well as developing the interventions themselves.

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BACKGROUND: Many families rely on child care outside the home, making these settings important influences on child development. Nearly 1.5 million children in the U.S. spend time in family child care homes (FCCHs), where providers care for children in their own residences. There is some evidence that children in FCCHs are heavier than those cared for in centers. However, few interventions have targeted FCCHs for obesity prevention. This paper will describe the application of the Intervention Mapping (IM) framework to the development of a childhood obesity prevention intervention for FCCHs METHODS: Following the IM protocol, six steps were completed in the planning and development of an intervention targeting FCCHs: needs assessment, formulation of change objectives matrices, selection of theory-based methods and strategies, creation of intervention components and materials, adoption and implementation planning, and evaluation planning RESULTS: Application of the IM process resulted in the creation of the Keys to Healthy Family Child Care Homes program (Keys), which includes three modules: Healthy You, Healthy Home, and Healthy Business. Delivery of each module includes a workshop, educational binder and tool-kit resources, and four coaching contacts. Social Cognitive Theory and Self-Determination Theory helped guide development of change objective matrices, selection of behavior change strategies, and identification of outcome measures. The Keys program is currently being evaluated through a cluster-randomized controlled trial CONCLUSIONS: The IM process, while time-consuming, enabled rigorous and systematic development of intervention components that are directly tied to behavior change theory and may increase the potential for behavior change within the FCCHs.

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While bonobos and chimpanzees are both genetically and behaviorally very similar, they also differ in significant ways. Bonobos are more cautious and socially tolerant while chimpanzees are more dependent on extractive foraging, which requires tools. The similarities suggest the two species should be cognitively similar while the behavioral differences predict where the two species should differ cognitively. We compared both species on a wide range of cognitive problems testing their understanding of the physical and social world. Bonobos were more skilled at solving tasks related to theory of mind or an understanding of social causality, while chimpanzees were more skilled at tasks requiring the use of tools and an understanding of physical causality. These species differences support the role of ecological and socio-ecological pressures in shaping cognitive skills over relatively short periods of evolutionary time.