Nurses’ perceptions of climate and environmental issues : a qualitative study

Aim: The aim of this study was to explore nurses' perceptions of climate and environmental issues and examine how nurses perceive their role in contributing to the process of sustainable development.  Background: Climate change and its implications for human health represent an increasingly important issue for the healthcare sector. According to the International Council of Nurses Code of Ethics, nurses have a responsibility to be involved and support climate change mitigation and adaptation to protect human health.  Design: This is a descriptive, explorative qualitative study.  Methods: Nurses (n=18) were recruited from hospitals, primary care and emergency medical services; eight participated in semi-structured, in-depth individual interviews and 10 participated in two focus groups. Data were collected from April-October 2013 in Sweden; interviews were transcribed verbatim and analysed using content analysis.  Results: Two main themes were identified from the interviews: (i) an incongruence between climate and environmental issues and nurses' daily work; and (ii) public health work is regarded as a health co-benefit of climate change mitigation. While being green is not the primary task in a lifesaving, hectic and economically challenging context, nurses' perceived their profession as entailing responsibility, opportunities and a sense of individual commitment to influence the environment in a positive direction.  Conclusions: This study argues there is a need for increased awareness of issues and methods that are crucial for the healthcare sector to respond to climate change. Efforts to develop interventions should explore how nurses should be able to contribute to the healthcare sector's preparedness for and contributions to sustainable development.

The priority of temporal aspects in L2-Swedish prosody : Studies in perception and production

Foreign accent can be everything from hardly detectable to rendering the second language speech unintelligible. It is assumed that certain aspects of a specific target language contribute more to making the foreign accented speech intelligible and listener friendly, than others. The present thesis examines a teaching strategy for Swedish pronunciation in second language education. The teaching strategy “Basic prosody” or BP, gives priority to temporal aspects of Swedish prosody, which means the temporal phonological contrasts word stress and quantity, as well as the durational realizations of these contrasts. BP does not prescribe any specific tonal realizations. This standpoint is based on the great regional variety in realization and distribution of Swedish word accents. The teaching strategy consists virtually of three directives: · Stress the proper word in the sentence. · Stress proper syllables in stressed words and make them longer. · Lengthen the proper segment – vowel or subsequent consonant – in the stressed syllable. These directives reflect the view that all phonological length is stress-induced, and that vowel length and consonant length are equally important as learning goals. BP is examined in the light of existing findings in the field of second language pronunciation and with respect to the phonetic correlates of Swedish stress and quantity. Five studies examine the relation between segment durations and the categorization made by native Swedish listeners. The results indicate that the postvocalic consonant duration contributes to quantity categorization as well as giving the proper duration to stressed syllables. Furthermore, native Swedish speakers are shown to apply the complementary /V: C/ - /VC:/ pattern also when speaking English and German, by lengthening postvocalic consonants. The correctness of the priority is not directly addressed but important aspects of BP are supported by earlier findings as well as the results from the present studies.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.