Comparing Psychological Type and Explanatory Between Nursing Students and Clinical Faculty: A Pilot Study

Negotiation of complex collaboration and effective teamwork among health care providers is essential to patient safety and to quality of care. This study examined characteristics of nursing students and faculty influencing communication between them. Psychological type (Myers-Briggs Type Inventory (MBTI) (Myers, McCaulley, Quenk, & Hammer, 1998) and explanatory style (Attributional Style Questionnaire) (ASQ) (Peterson et al., 1982) were compared for participating first year baccalaureate nursing students (N=286), and clinical nursing faculty (N=59) from both two- and four-year nursing programs. Modal student psychological type was ESFJ; modal faculty psychological type was ISTJ. The two groups demonstrated significant differences in processing information, and making decisions and judgments. Students were slightly more optimistic than faculty. Psychological type and level of optimism did not appear to correlate. Data from this pilot study provide an initial framework on which to base further research that could enhance the quality of teamwork among healthcare providers.

Technical Efficiency in the Indian Textiles Industry: A Nonparametric Analysis of Firm-Level Data

The Indian textiles industry is now at the crossroads with the phasing out of quota regime that prevailed under the Multi-Fiber Agreement (MFA) until the end of 2004. In the face of a full integration of the textiles sector in the WTO, maintaining and enhancing productive efficiency is a precondition for competitiveness of the Indian firms in the new liberalized world market. In this paper we use data obtained from the Annual Survey of Industries for a number of years to measure the levels of technical efficiency in the Indian textiles industry at the firm level. We use both a grand frontier applicable to all firms and a group frontier specific to firms from any individual state, ownership, or organization type in order to evaluate their efficiencies. This permits us to separately identify how locational, proprietary, and organizational characteristics of a firm affect its performance.

Extracting more out of relocation data: building movement models as mixtures of random walks

We present a framework for fitting multiple random walks to animal movement paths consisting of ordered sets of step lengths and turning angles. Each step and turn is assigned to one of a number of random walks, each characteristic of a different behavioral state. Behavioral state assignments may be inferred purely from movement data or may include the habitat type in which the animals are located. Switching between different behavioral states may be modeled explicitly using a state transition matrix estimated directly from data, or switching probabilities may take into account the proximity of animals to landscape features. Model fitting is undertaken within a Bayesian framework using the WinBUGS software. These methods allow for identification of different movement states using several properties of observed paths and lead naturally to the formulation of movement models. Analysis of relocation data from elk released in east-central Ontario, Canada, suggests a biphasic movement behavior: elk are either in an "encamped" state in which step lengths are small and turning angles are high, or in an "exploratory" state, in which daily step lengths are several kilometers and turning angles are small. Animals encamp in open habitat (agricultural fields and opened forest), but the exploratory state is not associated with any particular habitat type.