title: Physicians' perspectives of managing tensions around dimensions of effective communication in the emergency department

authors: Dean, Marleah

abstract: The purpose of this study was to explore emergency department (ED) physicians' perspectives of guidelines for effective communication. More specifically, the ways in which physicians manage the tensions among effective communication dimensions framed by relational dialectics theory are examined. This study used in-depth interviews with 17 ED physicians and 70 hours of observations to identify five dimensions of effective communication: efficiency, clarity/accuracy, relevance, comprehension, and rapport. Two communication tensions resulted from these dimensions: efficiency versus rapport and efficiency versus comprehension. In almost all instances, physicians chose efficient communication at the expense of comprehension or rapport. In addition, there was a tension between patient and physician perspectives of clarity and relevance that physicians tended to resolve by emphasizing what was relevant and clear from their own perspective. Implications for managing tensions in terms of efficiency and a physician-centered approach are discussed.

text: Physicians' perspectives of managing tensions around dimensions of effective communication in the emergency department The purpose of this study was to explore emergency department (ED) physicians' perspectives of guidelines for effective communication. More specifically, the ways in which physicians manage the tensions among effective communication dimensions framed by relational dialectics theory are examined. This study used in-depth interviews with 17 ED physicians and 70 hours of observations to identify five dimensions of effective communication: efficiency, clarity/accuracy, relevance, comprehension, and rapport. Two communication tensions resulted from these dimensions: efficiency versus rapport and efficiency versus comprehension. In almost all instances, physicians chose efficient communication at the expense of comprehension or rapport. In addition, there was a tension between patient and physician perspectives of clarity and relevance that physicians tended to resolve by emphasizing what was relevant and clear from their own perspective. Implications for managing tensions in terms of efficiency and a physician-centered approach are discussed.

year: 2013

title: How important is selection? Experimental vs. non-experimental measures of the income gains from migration

authors: McKenzie, David

subjects: New Zealand

abstract: How much do migrants stand to gain in income from moving across borders? Answering this question is complicated by non-random selection of migrants from the general population, which makes it hard to obtain an appropriate comparison group of non-migrants. New Zealand allows a quota of Tongans to immigrate each year with a random ballot used to choose among the excess number of applicants. A unique survey conducted by the authors allows experimental estimates of the income gains from migration to be obtained by comparing the incomes of migrants to those who applied to migrate, but whose names were not drawn in the ballot, after allowing for the effect of non-compliance among some of those whose names were drawn. We also conducted a survey of individuals who did not apply for the ballot. Comparing this non-applicant group to the migrants enables assessment of the degree to which non-experimental methods can provide an unbiased estimate of the income gains from migration. We find evidence of migrants being positively selected in terms of both observed and unobserved skills. As a result, non-experimental methods other than instrumental variables are found to overstate the gains from migration by 20–82%, with difference-in-differences and bias-adjusted matching estimators performing best among the alternatives to instrumental variables. (JEL: J61, F22, C21)

text: How important is selection? Experimental vs. non-experimental measures of the income gains from migration How much do migrants stand to gain in income from moving across borders? Answering this question is complicated by non-random selection of migrants from the general population, which makes it hard to obtain an appropriate comparison group of non-migrants. New Zealand allows a quota of Tongans to immigrate each year with a random ballot used to choose among the excess number of applicants. A unique survey conducted by the authors allows experimental estimates of the income gains from migration to be obtained by comparing the incomes of migrants to those who applied to migrate, but whose names were not drawn in the ballot, after allowing for the effect of non-compliance among some of those whose names were drawn. We also conducted a survey of individuals who did not apply for the ballot. Comparing this non-applicant group to the migrants enables assessment of the degree to which non-experimental methods can provide an unbiased estimate of the income gains from migration. We find evidence of migrants being positively selected in terms of both observed and unobserved skills. As a result, non-experimental methods other than instrumental variables are found to overstate the gains from migration by 20–82%, with difference-in-differences and bias-adjusted matching estimators performing best among the alternatives to instrumental variables. (JEL: J61, F22, C21)

year: 2010

title: Mana Motuhake Ringa: The non-invasive neural interface based artificial hand

authors: Owen, Mahonri W.

subjects: Prosthetics

abstract: Ten million people on the earth at any given time suffer from the loss or lack of a limb. Three million of these are upper extremity amputees. No matter the cause or reason for amputation the amputees’ life is never the same again. Independence can be lost and never regained. The loss of a limb can be an overpowering event that effects the mental, social, and physical well-being of a person. Although there has been many attempts to restore hand function through neural prosthetics there is little to no credible solutions to regain it. This thesis presents methods to restore hand function based on the human grasping system and addresses key challenges in the practical application of those methods. The contribution of this work lies in improving artificial hand function by mimicking the human grasping system. The human grasping system consists of the brain, the nervous system and the hand. The methods used investigate: biomechanical design principles for artificial hands, the limitations of machine learning in non-invasive neural interfaces (NI’s) and the development of an autonomous hand control framework for artificial hand control. 

The application of the Support Vector Machine (SVM) to a non-invasive neural interface is principally limited to binary applications in the real world. In order to overcome this limitation an autonomous approach is developed to achieve better response and accuracy from NI control frameworks. In binary applications the SVM performed well with a classification accuracy of around 80% accompanied by a response time of just under 5 seconds. When applied to multiple classifications the SVM decreased in accuracy and response dramatically. The accuracy of the autonomous hand control framework had a classification accuracy of 95% with a response time comparable to that of the SVM. This outcome has the potential to move non-invasive NI research into the real world and to restore hand function in an intuitive and meaningful way. A key learning of this research is that machine learning methods for non-invasive neural interfaces are not the best way to restore hand function for amputees. Hand function is best restored through the combining of machine learning and machine vision into a single NI based control framework. Additionally, this work is based in Mātauranga Māori with a western science approach. By so doing, amputees will be empowered, have increased independence and enjoy a better quality of life.

The scope of this work is limited to the consideration of hand function restoration for upper extremity amputees. In particular trans-radial amputees. Focus is given to non-invasive methods of control, therefore, investigations are limited to the electroencephalography (EEG) signal. Mimicking the human grasping system is a complex and difficult process, therefore, the attempts in this work to restore hand function only consider mechanisms and processes related directly to the motor control of the human hand.

text: Mana Motuhake Ringa: The non-invasive neural interface based artificial hand Ten million people on the earth at any given time suffer from the loss or lack of a limb. Three million of these are upper extremity amputees. No matter the cause or reason for amputation the amputees’ life is never the same again. Independence can be lost and never regained. The loss of a limb can be an overpowering event that effects the mental, social, and physical well-being of a person. Although there has been many attempts to restore hand function through neural prosthetics there is little to no credible solutions to regain it. This thesis presents methods to restore hand function based on the human grasping system and addresses key challenges in the practical application of those methods. The contribution of this work lies in improving artificial hand function by mimicking the human grasping system. The human grasping system consists of the brain, the nervous system and the hand. The methods used investigate: biomechanical design principles for artificial hands, the limitations of machine learning in non-invasive neural interfaces (NI’s) and the development of an autonomous hand control framework for artificial hand control. 

The application of the Support Vector Machine (SVM) to a non-invasive neural interface is principally limited to binary applications in the real world. In order to overcome this limitation an autonomous approach is developed to achieve better response and accuracy from NI control frameworks. In binary applications the SVM performed well with a classification accuracy of around 80% accompanied by a response time of just under 5 seconds. When applied to multiple classifications the SVM decreased in accuracy and response dramatically. The accuracy of the autonomous hand control framework had a classification accuracy of 95% with a response time comparable to that of the SVM. This outcome has the potential to move non-invasive NI research into the real world and to restore hand function in an intuitive and meaningful way. A key learning of this research is that machine learning methods for non-invasive neural interfaces are not the best way to restore hand function for amputees. Hand function is best restored through the combining of machine learning and machine vision into a single NI based control framework. Additionally, this work is based in Mātauranga Māori with a western science approach. By so doing, amputees will be empowered, have increased independence and enjoy a better quality of life.

The scope of this work is limited to the consideration of hand function restoration for upper extremity amputees. In particular trans-radial amputees. Focus is given to non-invasive methods of control, therefore, investigations are limited to the electroencephalography (EEG) signal. Mimicking the human grasping system is a complex and difficult process, therefore, the attempts in this work to restore hand function only consider mechanisms and processes related directly to the motor control of the human hand.

year: 2019