University of Rhode Island

About: University of Rhode Island is a education organization based out in Kingston, Rhode Island, United States. It is known for research contribution in the topics: Population & Bay. The organization has 11464 authors who have published 22770 publications receiving 841066 citations. The organization is also known as: URI & Rhode Island College of Agriculture and the Mechanic Arts.

Values in Health Care Professional Socialization: Implications for Geriatric Education in Interdisciplinary Teamwork

Abstract: Collaboration among different health professions will take on greater importance as geriatric care moves increasingly into the realm of quality of life and not simply life extension (Clark, 1995). Of necessity, quality of life deals with the qualitative dimensions of care, including values, meaning, attitudes, and preferences — all of which are created and shaped by life experience, professional training, and interaction between the individual and his or her broader social environment. In particular, the education and training of health care professionals shape their identities, values, and norms of practice in certain ways that may either enhance or inhibit effective communication and collaboration in clinical practice settings, where these skills are crucial to the effective care of elderly persons. This article proposes that the process of acquiring a professional identity and norms of practice is an ongoing dialectic of professional socialization that is both reflective and dynamic, in that it involves interaction between the self and others in the environment. The development of personal and professional values as they relate to patient care is an essential element of this identity and the hallmark of the artistry of professional practice (Schon, 1987). The implications of this interpretation of professional socialization are important to an understanding of communication between providers, as well as between providers and consumers of care. Such

A decisional balance measure and the stages of change model for weight loss.

Abstract: Two studies were conducted to explore the cognitive and motivational aspects related to progression through the stages of intentional change in weight loss and control. Study I developed a Decision...

Diapiric Flow at Subduction Zones: A Recipe for Rapid Transport

Abstract: Recent geochemical studies of uranium-thorium series disequilibrium in rocks from subduction zones require magmas to be transported through the mantle from just above the subducting slab to the surface in as little as ∼30,000 years. We present a series of laboratory experiments that investigate the characteristic time scales and flow patterns of the diapiric upwelling model of subduction zone magmatism. Results indicate that the interaction between buoyantly upwelling diapirs and subduction-induced flow in the mantle creates a network of low-density, low-viscosity conduits through which buoyant flow is rapid, yielding transport times commensurate with those indicated by uranium-thorium studies.

Stages of change for reducing dietary fat to 30% of energy or less.

Abstract: Objective To develop an algorithm that defines a person's stage of change for fat intake ≤30% of energy. The Stages of Change Model describes when and how people change problem behaviors; change is defined as a dynamic variable with five discrete stages. Design A stage of change algorithm for determining dietary fat intake ≤30% of energy was developed using one sample and was validated using a second sample. Subjects Sample 1 was a random sample of 614 adults who responded to mailed questionnaires. Sample 2 was a convenience sample of 130 faculty, staff, and graduate students. Statistics Subjects in sample 1 were initially classified in a stage of change using an algorithm based on their behavior related to avoiding high-fat foods. Dietary markers were selected for a Behavioral algorithm using logistic regression analyses. Sensitivity, specificity, and predictive value of the Behavioral algorithm were determined, then compared between samples using the Z test. Results The following dietary markers predicted intake ≤30% of fat ( Ξ 2 = 131; P 30% of energy from fat with 93% specificity in sample 1 and 87% in sample 2 ( Z = 1.36; P > .05). Predictive value was also validated; 64% and 58% of subjects meeting the behavioral criteria had fat intakes ≤30% of energy ( Z = 1.1; P > .05). The algorithm was not sensitive, however; most subjects with fat intakes ≤30% of energy from fat failed to meet the behavioral criteria. The sensitivity differed between samples 1 and 2 (44% and 27%, respectively; Z = 3.84; P Applications The Behavioral algorithm determines stage of change for fat reduction to ≤30% of energy in populations with high fat intakes. The algorithm could be used in dietary counseling to tailor interventions to a patient's stage of change.