The medical secretary,

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Portugal : with five new portraits and an additional chapter by Martin Hume. /

Mode of access: Internet.

Using a matrix in life transition research

Life transitions can be planned or can occur unexpectedly. They can cause a major change to a person's life patterns and well-being. Older adulthood is a time for many life transitions as a result of changes in life roles and health status. In this exploratory study, the authors investigate the transition involved in driving cessation for older people. In analyzing and organizing the data, they develop a matrix that incorporated descriptive and temporal factors associated with the transition. This matrix is useful in organizing and communicating the findings as a whole and could be used in describing individual experiences. It might be of use for the organization of qualitative data about other life transitions such as illness, retirement, and the development and adoption of new behaviors.

Young women as smokers and nonsmokers: A qualitative social identity approach

The authors used a social identity perspective to explore young women's perceptions of smoking. They carried out 13 focus groups and 6 intercept interviews with women aged 16 to 28 years in regards to the social identities that might influence young women's smoking behavior. Three identities emerged: the cool smoker applied to the initiation of smoking; considerate smokers, who were older addicted smokers; and the actual and anticipated good mother identity, which applied to young women who quit smoking during pregnancy. These identities add to our understanding of the meaning of smoking within the lives of young women and might allow more focused initiatives with this group to prevent the progression to regular addicted smoking.

Delivering culturally sensitive care: The perceptions of older Arabian Gulf Arabs concerning religion, health, and disease

Health professionals need to be cognizant of the varying perceptions of health shared by people from different religious, sociocultural, and linguistic backgrounds to deliver culturally sensitive health care. In this qualitative study, the authors used semistructured interviews to provide insight into how 10 older Arabian Gulf Muslim persons understand and perceive health and illness with emphasis on the role of Islam in formulating health behaviors. Participants' views were strongly influenced by their religious convictions. Good health was equated with the absence of visible disease, with participants demonstrating limited understanding of silent or insidious disease. They attended doctors for treatment of visible disease rather than seeking preventive health care for diseases such as hypertension, diabetes, and hyperlipidemia. Building oil the results from this study could help inform both health service planners and providers to improve the appropriateness, relevancy, and effectiveness of aged care services for these individuals.

Finding common ground in team-based qualitative research using the convergent interviewing method

Research councils, agencies, and researchers recognize the benefits of team-based health research. However, researchers involved in large-scale team-based research projects face multiple challenges as they seek to identify epistemological and ontological common ground. Typically, these challenges occur between quantitative and qualitative researchers but can occur between qualitative researchers, particularly when the project involves multiple disciplinary perspectives. The authors use the convergent interviewing technique in their multidisciplinary research project to overcome these challenges. This technique assists them in developing common epistemological and ontological ground while enabling swift and detailed data collection and analysis. Although convergent interviewing is a relatively new method described primarily in marketing research, it compares and contrasts well with grounded theory and other techniques. The authors argue that this process provides a rigorous method to structure and refine research projects and requires researchers to identify and be accountable for developing a common epistemological and ontological position.

Enhanced information transmission with signal dependent noise in an array of LIF neurons

Sensory cells usually transmit information to afferent neurons via chemical synapses, in which the level of noise is dependent on an applied stimulus. Taking into account such dependence, we model a sensory system as an array of LIF neurons with a common signal. We show that information transmission is enhanced by a nonzero level of noise. Moreover, we demonstrate a phenomenon similar to suprathreshold stochastic resonance with additive noise. We remark that many properties of information transmission found for the LIF neurons was predicted by us before with simple binary units [Phys. Rev. E 75, 021121 (2007)]. This confirmation of our predictions allows us to point out identical roots of the phenomena found in the simple threshold systems and more complex LIF neurons.

Estimating ECAP threshold from the variability of the response

Electrical compound action potentials (ECAPs) of the cochlear nerve are used clinically for quick and efficient cochlear implant parameter setting. The ECAP is the aggregate response of nerve fibres at various distances from the recording electrode, and the magnitude of the ECAP is therefore related to the number of fibres excited by a particular stimulus. Current methods, such as the masker-probe or alternating polarity methods, use the ECAP magnitude at various stimulus levels to estimate the neural threshold, from which the parameters are calculated. However, the correlation between ECAP threshold and perceptual threshold is not always good, with ECAP threshold typically being much higher than perceptual threshold. The lower correlation is partly due to the very different pulse rates used for ECAPs (below 100 Hz) and clinical programs (hundreds of Hz up to several kHz). Here we introduce a new method of estimating ECAP threshold for cochlear implants based upon the variability of the response. At neural threshold, where some but not all fibers respond, there is a different response each trial. This inter-trial variability can be detected overlaying the constant variability of the system noise. The large stimulus artefact, which requires additional trials for artefact rejection in the standard ECAP magnitude methods, is not consequential, as it has little variability. The variability method therefore consists of simply presenting a pulse and recording the ECAP, and as such is quicker than other methods. It also has the potential to be run at high rates like clinical programs, potentially improving the correlation with behavioural threshold. Preliminary data is presented that shows a detectable variability increase shortly after probe offset, at probe levels much lower than those producing a detectable ECAP magnitude. Care must be taken, however, to avoid saturation of the recording amplifier saturation; in our experiments we found a gain of 300 to be optimal.

Neural population coding is optimized by discrete tuning curves

The sigmoidal tuning curve that maximizes the mutual information for a Poisson neuron, or population of Poisson neurons, is obtained. The optimal tuning curve is found to have a discrete structure that results in a quantization of the input signal. The number of quantization levels undergoes a hierarchy of phase transitions as the length of the coding window is varied. We postulate, using the mammalian auditory system as an example, that the presence of a subpopulation structure within a neural population is consistent with an optimal neural code.

The role of stochasticity in an information-optimal neural population code

In this paper we consider the optimisation of Shannon mutual information (MI) in the context of two model neural systems The first is a stochastic pooling network (population) of McCulloch-Pitts (MP) type neurons (logical threshold units) subject to stochastic forcing; the second is (in a rate coding paradigm) a population of neurons that each displays Poisson statistics (the so called 'Poisson neuron'). The mutual information is optimised as a function of a parameter that characterises the 'noise level'-in the MP array this parameter is the standard deviation of the noise, in the population of Poisson neurons it is the window length used to determine the spike count. In both systems we find that the emergent neural architecture and; hence, code that maximises the MI is strongly influenced by the noise level. Low noise levels leads to a heterogeneous distribution of neural parameters (diversity), whereas, medium to high noise levels result in the clustering of neural parameters into distinct groups that can be interpreted as subpopulations In both cases the number of subpopulations increases with a decrease in noise level. Our results suggest that subpopulations are a generic feature of an information optimal neural population.