This paper analyzes and assesses the success and failures of the implemented methods of two mailed survey research projects conducted in post-Katrina New Orleans. Mailed survey research is an essential part of the recovery process following a major disaster in which people have been displaced. A survey can provide insight into how many residents intend to return to the area as well as resident needs and concerns. Traditional methods alone are inadequate in a post-disaster setting and supplemental measures must be taken. The collected data from a survey in this setting will be unrepresentative of the pre-disaster population. Spatial analysis of the response combined with a comparison of the collected data to known census data identifies the ways in which the data is unrepresentative. Knowledge of the data shortcomings increases its utility in planning and recovery efforts in the affected region.

Developed on the boundary between medicine and sociology, this thesis develops a critique of the perspectives of these disciplines through analysis of a study of women's perspectives on hormone replacement therapy. Women's perspectives are explored through a postal questionnaire survey and a study using individual interviews and focus groups. The survey results provide a measure of women’s attitudes towards, and knowledge of, hormone replacement therapy. The individual interviews detail the way women move towards a decision about the therapy and identifies common themes, particularly women's fears and what influences their fears. The focus groups explore contrasting themes including women's control and choice in decisions about therapy, contrary themes in women’s attitudes and the different ways of thinking used by the women. The results of the studies are assessed for their implications for clinical general practice. The thesis also takes a sociological perspective on women and HRT and on the research process, in particular exploring two themes. Firstly, the interaction between the social context, the research subject and the research process. This includes the social factors influencing the development of the research and choice of research methods, and the influence of the research methods on the results obtained. The second theme is the perspectives and levels of analysis used by the main disciplines contributing to the thesis; biomedicine, biostatistics, general practice and sociology. The thesis explores how the different perspectives and levels of analysis influence research and how they are used to manage the social context. These explorations are used to suggest future directions for research on hormone replacement therapy and for general practice.

In Latin America, the debate on what constitutes a 'good' or 'bad' job has been dominated by the phenomenon of informality. Indicators like the 'informal sector size' or the proportion of workers in 'informal employment' give little attention to the intrinsic features of jobs that affect workers' well-being, thus misleading policy efforts. Validation of alternative and comparable human-centred measures of job quality (JQ) is needed. This study aims to evaluate the validity of a multi-dimensional measure of JQ in developing countries, and its usefulness against narrow indicators of formality/informality. To this end, Sen's capability-approach is used along with Green and Mostafa's operationalisation of JQ (Eurofound, 2012), which considers dimensions as varied as earnings, career prospects, autonomy, intensity, social environment, physical environment, and working time. With Central America as the research setting, I address four questions: (1) does Eurofound's indicator capture JQ inequalities at the individual level? (2) Can we draw meaningful comparisons between countries about their ability to provide good jobs? (3) Are the selected features of what constitutes a good job positively associated with Central American workers' well-being? (4) Is the concept of JQ attuned with what local experts conceive as a 'good job'? The research uses a mixed-methods approach to analyse the First Central American Survey on Working Conditions and Health - conducted in 2011 in Panama, Costa Rica, Nicaragua, Honduras, El Salvador and Guatemala - in addition to semi-structured interviews with selected informants from these six countries. The results obtained show, firstly, a reasonable distribution of JQ across groups of workers. They confirm that formal jobs are not ubiquitously the best quality jobs. Secondly, the results evidenced significant variation at the country level regarding earnings and intrinsic job quality, with Costa Rica often ranking at the top. Interestingly, JQ rankings do not always follow from countries' industrial structure, economic performance, informal sector size, or other developmental indicators of common usage; country differences in JQ appear associated with the practical enforcement capacity of labour institutions like trade unions, inspection systems, and the state itself. Thirdly, I corroborated that the selected job features have a positive impact on Central American workers' well-being (except, puzzlingly, for work-time related aspects). Moreover, the positive health effect associated with performing in an intrinsically good job proved to be greater than the effect of working formally. Lastly, I confirmed that local perspectives about what constitutes a 'good job' are in great part consistent with the features included in Green and Mostafa's JQ scheme, while other intrinsic dimensions of the framework have struggled to enter the public discourse. These findings indicate that a JQ framework is generally valid in the Central American context, and provides more information than a conventional indicator of informality. The study contributes to extend the capability approach to the realm of work and to stress its potential for international comparative research. It is recommended that countries collect richer data about those aspects of jobs that have been proven to affect workers' well-being significantly and are not revealed in unidimensional informality figures.

(1) Aerial survey methods for estimating population size of feral water buffalo in northern Australia were examined. (2) Line transect models underestimated population size. Of six models tested the most accurate underestimated by nearly half. The models give biased estimates most probably because not all animals on the survey line were sighted . (3) Aerial strip transect surveys were also negatively biased. The extent of this bias was estimated in index-removal experiments. Experiments were carried out on two populations in areas of differing obstructive canopy cover. (4) In woodland habitat with a canopy cover of 30- 60%, a correction factor of 3.2 was required to take account of animals not seen. In forest habitat with a canopy cover of 60-100%, a correction factor of 4.9 was required. (5) Using these results, the population size of feral buffalo, cattle and horses in Kakadu National Park was estimated by aerial survey at the end of each year over 6 years. Annual rates of increase for three regions of the Park were estimated, taking into account known removals from the population. The effects of dry season rainfall and population density in the preceding year on rate of increase were examined for each species. (6) The mean annual exponential rate of increase for each species was 0.10 yr-1 for buffalo, 0.23 yr-1 for cattle and -0.14 yr-1 for horses. (7) The annual rates of increase varied greatly between years within all species and were highly correlated with dry season rainfall in the year of survey for buffalo and cattle but not for horses. (8) No significant effect of preceding density on rate of increase was found for any species. A large reduction in buffalo populations did not correspond with an increase in unharvested populations of horses, suggesting the two species do not compete for food or other resources. (9) A campaign to control populations of feral water buffalo in Kakadu National Park was assessed. Between 1979 and 1988, approximately 79,000 animals were removed, 54% by commercial live-capture, 35% by shooting from helicopters and 10% by shooting from the ground. (10) In the period 1983-1988 when population estimates from aerial survey are available, mean buffalo population density was reduced from 5.60 km-2 to 1.17 km-2 over the surveyed area of the Park. (11) The costs of removal by shooting from helicopters, capturing animals alive and shooting from the ground were compared. The mean costs per animal in 1988 were $24.13, $74.53, and $86.02 respectively. (12) The effects of initial density and time spent shooting on number of animals removed by shooting from helicopters were examined. One linear and two curvilinear models were fitted to data from four different removal exercises. The relationship between time spent shooting and number removed was best described by a curvilinear (Ivlev) function. This model was used to estimate costs of control to a specified density. (13) Model regression coefficients differed between removal exercises, suggesting that the number removed may be affected by variables other than time spent shooting and initial density. Data from the range of conditions encountered during removal is thus likely to be required for robust estimation of removal costs.

Background Mortality data are critical to understanding and monitoring changes in population health status over time. Nevertheless, the majority of people living in the world’s poorest countries, where the burden of disease is highest, remain outside any kind of systematic health surveillance. This lack of routine registration of vital events, such as births and deaths, constitutes a major and longstanding constraint on the understanding of patterns of health and disease and the effectiveness of interventions. Localised sentinel demographic and health surveillance strategies are a useful surrogate for more widespread surveillance in such settings, but rigorous, evidence-based methodologies for sample-based surveillance are weak and by no means standardised. This thesis aims to describe, evaluate and refine methodological approaches to mortality measurement in resource-poor settings. Methods Through close collaboration with existing community surveillance operations in a range of settings, this work uses existing data from demographic surveillance sites and community-based surveys using various innovative approaches in order to evaluate and refine methodological approaches to mortality measurement and cause-of-death determination. In doing so, this work explores the application of innovative techniques and procedures for mortality surveillance in relation to the differing needs of those who use mortality data, ranging from global health organisations to local health planners. Results Empirical modelling of sampling procedures in community-based surveys in rural Africa and of random errors in longitudinal data collection sheds light on the effects of various data-capture and quality-control procedures and demonstrates the representativeness and robustness of population surveillance datasets. The development, application and refinement of a probabilistic approach to determining causes of death at the population level in developing countries has shown promise in overcoming the longstanding limitations and issues of standardisation of existing methods. Further adaptation and application of this approach to measure maternal deaths has also been successful. Application of international guidelines on humanitarian crisis detection to mortality surveillance in Ethiopia demonstrates that simple procedures can and, from an ethical perspective, should be applied to sentinel surveillance methods for the prospective detection of important mortality changes in vulnerable populations. Conclusion Mortality surveillance in sentinel surveillance systems in resource-poor settings is a valuable and worthwhile task. This work contributes to the understanding of the effects of different methods of surveillance and demonstrates that, ultimately, the choice of methods for collecting data, assuring data quality and determining causes of death depends on the specific needs and requirements of end users. Surveillance systems have the potential to contribute substantially to developing health care systems in resource-poor countries and should not only be considered as research-oriented enterprises.

Background: Addressing the growing burden of mental diseases is a public health priority. Nevertheless, many countries lack reliable estimates of the proportion of the population affected, which are crucial for health and social policy planning. This study aimed to collect existing evidence on the prevalence of mental diseases in Austria. Methods: A systematic review was conducted using MeSH, EMTREE and free-text terms in seven bibliographic databases. In addition, the references of included papers and relevant Austria-specific websites were searched. Articles published after 1996 pertaining to the Austrian adult population and presenting prevalence data for mental diseases were included in the analysis. Results: A total of 2612 records were identified in the database search, 19 of which were included in the analysis, 13 were community-based studies and 6 examined institutionalized populations. Sample sizes ranged from 200 to 15,474. The evidence was centered around depression (n= 6, 32%), eating disorders (n= 4, 21%) and alcohol dependence (n= 3, 16%). While most studies (n= 10, 53%) used questionnaires and scales to identify mental diseases, seven studies used structured clinical interviews, and two studies examined use of psychotropic drugs. Due to the diversity of methodologies, no statistical pooling of prevalence estimates was possible. Conclusion: Information on the prevalence of mental diseases in Austria is limited and comparability between studies is restricted. A variety of diagnostic instruments, targeted populations and investigated diseases contribute to discrepancies in the prevalence rates. A systematic, large-scale study on the prevalence of mental diseases in Austria is needed for comprehensive and robust epidemiological evidence.

The paper analyses the sources of income measurement error in surveys with a unique data set. We use the Austrian 2008-2011 waves of the European Union "Statistics on income and living conditions" survey which provide individual information on wages, pensions and unemployment benefits from survey interviews and officially linked administrative records. Thus, we do not have to fall back on complex two-sample matching procedures like related studies. We empirically investigate four sources of measurement error, namely social desirabil- ity, sociodemographic characteristics of the respondent, the survey design and the presence of learning effects. We find strong evidence for a social desirability bias in income reporting, whereas the presence of learning effects is mixed and depends on the type of income under consideration. An Owen value decomposition reveals that social desirability is a major expla- nation of misreporting in wages and pensions, whereas sociodemographic characteristics are most relevant for mismatches in unemployment benefits.

This thesis investigated the effects of photographic and text information on respondents' attitudes and willingness-to-pay for a proposed beach protection scheme in the erosion prone Gold Coast region on the east coast of Australia. The research developed two alternative expectancy-value attitude-behaviour models to test residents' attitudes toward relevant targets and behavioural intention, expressed through stated willingness-to-pay, and compared the proposed models with one established attitude-behaviour model. The thesis set out to investigate three central research questions; one question relating to the effects of information on attitudes and willingness-to-pay, and two questions relating to the relationships between attitudes and willingness-to-pay. It was hypothesised that photographs that depicted severe erosion damage would result in more positive attitudes toward, and greater willingness-to-pay for, beach protection than photographs that showed only mild levels of erosion damage. Positive relationships were hypothesised between variables representing attitudes toward beach erosion, attitude toward beach protection, attitude toward paying for beach protection, and willingness-to-pay. Finally, it was hypothesised that the relationships between attitudes and willingness-to-pay could be adequately explained by the proposed attitude-behaviour models. The thesis describes how seven information treatments and eight attitude measurement scales were developed and tested in a pilot experiment before use in a survey of homeowners in the region of interest. Analysis of variance showed that, while respondent's attitude toward beach protection was affected by the information treatments, their willingness-to-pay for the proposed program was insensitive to information. There were no significant effects that could be attributed exclusively to text descriptions of the good but there were significant effects that could be attributed to photographic information treatments. However, none of the effects on attitudes resulted in significant effects on the behavioural intention expressed in stated willingness-to-pay. Analysis of respondents with low previous knowledge of the proposed good revealed more extensive information effects on attitudes, but still not on willingness-to-pay, and this suggests that high levels of previous knowledge in a large proportion of the sample had a moderating effect on attitude change caused by the information treatments. Regression analysis showed that seven of the eight attitude and behaviour variables in the proposed attitude-behaviour model were significant predictors of willingness-to-pay. In the final phase of the analysis, goodness-of-fit indices, estimated using Structural Equation Modelling, indicated a good fit between the data and the attitude-behaviour models tested. Standardised coefficients on the model indicated that perceived behavioural control, expected utility of outcomes, and subjective norms all had strong direct relationships with stated willingness-to-pay, and strong indirect relationships on willingness-to-pay via attitudes toward payment. These results are consistent with the relationships proposed in attitude-behaviour models and the moderating effects of these variables explain why significant information treatment effects were observed on attitude to beach protection but not on willingness-to-pay. This research showed that respondent's willingness-to-pay in a contingent valuation experiment is quite insensitive to photographic treatments when previous knowledge is high and that costly and time consuming testing procedures, recommended by authorities, may not be necessary under these conditions. It also demonstrated that measures of attitude, consistent with an attitude-behaviour model, can be collected easily in a contingent valuation study and can contribute to understanding of participant responses and to identification of protest responses.

An experiment is conducted among male adolescents to assess the impact of data collection methodology toward response quality factors, including completeness of answers, response distortion, response time, and item omissions. Data collection methodologies include in-person interviews, self-administered questionnaires, and use of an electronic form. Results suggest that personal interviews are generally the most effective method for collecting quality data from adolescent males. The impact of warning labels toward product evaluations was also tested using psychological reactance (Brehm 1966) to underpin hypotheses. Results indicate that adolescents rate their preference for entertainment products with restrictive labels higher than products with non-restrictive labels. Implications for public policy makers and both academic and managerial researchers are presented.

Historically, kit foxes (Vulpes macrotis) once occupied the desert and semi-arid regions of southwestern North America, ranging from Idaho to central Mexico. Their range-wide decline has warranted the kit fox to be listed as endangered in Colorado, threatened in California and Oregon, and designated as a state sensitive species in Idaho and Utah. Once considered the most abundant carnivore in western Utah, the kit fox has been in steep decline over the past decade, creating a demand to determine kit fox presence. Currently there is little consensus on which survey methodology is best to detect kit fox presence. We tested 4 survey methods (scat deposition, scent station, spotlight, trapping) along 15 5-km transects within a minimum known population of radio collar kit fox. Home range sizes for kit foxes on the study site were extremely large, averaging 20.5 km2. Scat deposition surveys had both the highest detection probabilities (= 0.88) and were the most closely related to known fox abundance (r2 =0.50, P = 0.001). For detecting kit foxes in a low density population we suggest using scat deposition transects during the breeding season. This method had low costs, was resilient to weather, had low labor requirements, and entailed no risk to the study animals.Next in determining kit fox presence is estimating kit fox distribution. We developed resource selection functions (RSF) using presence data from the noninvasive scat surveys to model kit fox distribution. We evaluated the predictive performance of RSFs built using three popular techniques (Maxent, fixed-effects and mixed-effects general linear models) combined with common environmental parameters (slope, aspect, elevation, soil type). Both the Maxent and fixed-effects models performed to an acceptable level with relatively high area under the curve (AUC) scores of 0.83 and 0.75, respectively. The mixed-effects model over valued higher elevations and had poor model fit. This study demonstrated that it was possible to create valid and informative predictive maps of a species distribution using a noninvasive survey method for detecting a carnivore existing at low density. By demonstrating the application of noninvasive surveying to model habitat quality for a small mesocarnivore, wildlife management agencies will be able to develop predictive maps for species of interest and provide more knowledge to help guide future management decisions.