Estructura agraria y dinámica de pobreza rural en el Perú

A partir de un panel provincial para el periodo entre los censos agropecuarios de 1994 y el 2012, este estudio pretende esclarecer el signo de la relación entre estructura agraria y dinámicas de pobreza rural en el Perú. Los resultados descriptivos revelan que las provincias con reducciones importantes en las tasas de pobreza rural son aquellas cuyas unidades agropecuarias tenían, al inicio del periodo, una mayor cantidad de tierra agrícola - en equivalente de riego -, una estructura de propiedad menos fragmentada, una distribución de la tierra más equitativa y una mayor proporción de productores con capacidad de innovación tecnológica. Por otro lado, los resultados econométricos sugieren que un importante determinante de la dinámica de pobreza rural observada es el tamaño de la propiedad, y no la estructura agraria. Asimismo, se muestra que las provincias cuya tasa de emigración es más alta y cuya tasa de inmigración es más baja son las que sufren un mayor aumento de la pobreza rural. Por último, junto con variables que pueden estar determinando un acceso diferenciado a los mercados, persiste un impacto positivo del grado de diversificación de la actividad productiva sobre las posibilidades de generar dinámicas de reducción de la pobreza en áreas rurales

User Image Mismatch in Anesthesia Alarms: A Cognitive Systems Analysis

In this study, principles of Cognitive Systems Engineering are used to better understand the human–machine interaction manifesting in the use of anaesthesia alarms. The hypothesis is that the design of the machine incorporates built-in assumptions of the user that are discrepant with the anaesthesiologist's self-assessment, creating ‘user image mismatch’. Mismatch was interpreted by focusing on the ‘user image’ as described from the perspectives of both machine and user. The machine-embedded image was interpreted through document analysis. The user-described image was interpreted through user (anaesthesiologist) interviews. Finally, an analysis was conducted in which the machine-embedded and user-described images were contrasted to identify user image mismatch. It is concluded that analysing user image mismatch expands the focus of attention towards macro-elements in the interaction between man and machine. User image mismatch is interpreted to arise from complexity of algorithm design and incongruity between alarm design and tenets of anaesthesia practice

"I want to treat the patient, not the alarm": User image mismatch in Anesthesia alarm design.

Although the development of physiologic monitors has improved the safety of patients undergoing anesthesia, a growing body of literature suggests that alarms function sub-optimally in supporting the human operator. A principle of cognitive systems engineering is that there is an image of the user “built in” to the design of any machine used in a joint cognitive (man-machine) system. This study explored the existence of a mismatch between the image of the user built into the anesthesia monitor alarm (machine-embedded image) and the anesthesiologist’s own image of himself (user-described image) and whether any such user image mismatch contributed to coordination failure between anesthesiologist and alarm. The Participant Guide for the Carescape B850 Anesthesia monitor was analyzed to define machine-embedded images. Fourteen anesthesiologists were interviewed to explore user-described images and man-machine coordination. User image mismatch was observed in each of three alarm behaviours studied. Furthermore, user image mismatch was found to be related, as symptom of and contributor to the instances of coordination failure described by interviewees

Anaesthesia monitor alarms: a theory-driven approach

The development of physiologic monitors has contributed to the decline in morbidity and mortality in patients undergoing anaesthesia. Diverse factors (physiologic, technical, historical and medico-legal) create challenges for monitor alarm designers. Indeed, a growing body of literature suggests that alarms function sub-optimally in supporting the human operator. Despite existing technology that could allow more appropriate design, most anaesthesia alarms still operate on simple, pre-set thresholds. Arguing that more alarms do not necessarily make for safer alarms is difficult in a litigious medico-legal environment and a competitive marketplace. The resultant commitment to the status quo exposes the risks that a lack of an evidence-based theoretical framework for anaesthesia alarm design presents. In this review, two specific theoretical foundations with relevance to anaesthesia alarms are summarised. The potential significance that signal detection theory and cognitive systems engineering could have in improving anaesthesia alarm design is outlined and future research directions are suggested

Patient characteristics associated with a poor response to non-surgical multidisciplinary management of knee osteoarthritis: a multisite prospective longitudinal study in an advanced practice physiotherapist-led tertiary service

To explore patient characteristics recorded at the initial consultation associated with a poor response to non-surgical multidisciplinary management of knee osteoarthritis (KOA) in tertiary care.Prospective multisite longitudinal study.Advanced practice physiotherapist-led multidisciplinary orthopaedic service within eight tertiary hospitals.238 patients with KOA.Standardised measures were recorded in all patients prior to them receiving non-surgical multidisciplinary management in a tertiary hospital service across multiple sites. These measures were examined for their relationship with a poor response to management 6 months after the initial consultation using a 15-point Global Rating of Change measure (poor response (scores -7 to +1)/positive response (scores+2 to+7)). Generalised linear models with binomial family and logit link were used to examine which patient characteristics yielded the strongest relationship with a poor response to management as estimated by the OR (95% CI).Overall, 114 out of 238 (47.9%) participants recorded a poor response. The odds of a poor response decreased with higher patient expectations of benefit (OR 0.74 (0.63 to 0.87) per 1/10 point score increase) and higher self-reported knee function (OR 0.67 (0.51 to 0.89) per 10/100 point score increase) (