The SAGE Handbook of Criminological Research Methods

Conducting research into crime and criminal justice carries unique challenges. This Handbook focuses on the application of 'methods' to address the core substantive questions that currently motivate contemporary criminological research. It maps a canon of methods that are more elaborated than in most other fields of social science, and the intellectual terrain of research problems with which criminologists are routinely confronted. Drawing on exemplary studies, chapters in each section illustrate the techniques (qualitative and quantitative) that are commonly applied in empirical studies, as well as the logic of criminological enquiry. Organized into five sections, each prefaced by an editorial introduction, the Handbook covers: • Crime and Criminals • Contextualizing Crimes in Space and Time: Networks, Communities and Culture • Perceptual Dimensions of Crime • Criminal Justice Systems: Organizations and Institutions • Preventing Crime and Improving Justice Edited by leaders in the field of criminological research, and with contributions from internationally renowned experts, The SAGE Handbook of Criminological Research Methods is set to become the definitive resource for postgraduates, researchers and academics in criminology, criminal justice, policing, law, and sociology.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Third international workshop on empirical research in business process management (ER-BPM 2012)

Empirical research in business process management(BPM) is coming of age. In 2009, when the inaugural ER-BPM workshop was held, the field of BPM research was characterized by a strong emphasis on solution development, but also by an increasing demand for insights or evaluations of BPM technology based on dedicated empirical research strategies. The ER-BPM workshop series was created to provide an international forum for researchers to discuss and present such research.

Assessing eco-environmental performance of agricultural production in OECD countries : combination of soil surface, soil system and farm gate methods of nutrient auditing

Nitrogen balance is increasingly used as an indicator of the environmental performance of agricultural sector in national, international, and global contexts. There are three main methods of accounting the national nitrogen balance: farm gate, soil surface, and soil system. OECD (2008) recently reported the nitrogen and phosphorus balances for member countries for the 1985 - 2004 period using the soil surface method. The farm gate and soil system methods were also used in some international projects. Some studies have provided the comparison among these methods and the conclusion is mixed. The motivation of this present paper was to combine these three methods to provide a more detailed auditing of the nitrogen balance and flows for national agricultural production. In addition, the present paper also provided a new strategy of using reliable international and national data sources to calculate nitrogen balance using the farm gate method. The empirical study focused on the nitrogen balance of OECD countries for the period from 1985 to 2003. The N surplus sent to the total environment of OECD surged dramatically in early 1980s, gradually decreased during 1990s but exhibited an increasing trends in early 2000s. The overall N efficiency however fluctuated without a clear increasing trend. The eco-environmental ranking shows that Australia and Ireland were the worst while Korea and Greece were the best.

Professional development using informal learning networks : an empirical study in Australia’s digital content industry

Informal learning networks play a key role in the skill and professional development of professionals working in micro-businesses within Australia’s digital content industry as they do not necessarily have access to a learning and development or a human resources section that can assist in mapping their learning pathway. Professionals working in this environment would typically adopt an informal learning approach to their skill and professional development by utilising their social and business networks. The overall aim of this PhD research project is to study how these professionals manage their skill and professional development, and to explore what role informal learning networks play in this professional learning context. This paper will describe the theme of the research project and how it fits with previous research and other relevant studies. Secondly, it will present the study’s research focus, and the research questions. It will also present relevant theories and perspectives, and the methods for empirical data collection. Data collection will be through three distinct phases using a mixed methods research design: an online survey, interviews, and case studies. It should be noted the findings presented in this paper offer some early results of the research project.

Permeability estimation conditioned to geophysical downhole log data in sandstones of the northern Galilee Basin, Queensland : methods and application

This study uses borehole geophysical log data of sonic velocity and electrical resistivity to estimate permeability in sandstones in the northern Galilee Basin, Queensland. The prior estimates of permeability are calculated according to the deterministic log–log linear empirical correlations between electrical resistivity and measured permeability. Both negative and positive relationships are influenced by the clay content. The prior estimates of permeability are updated in a Bayesian framework for three boreholes using both the cokriging (CK) method and a normal linear regression (NLR) approach to infer the likelihood function. The results show that the mean permeability estimated from the CK-based Bayesian method is in better agreement with the measured permeability when a fairly apparent linear relationship exists between the logarithm of permeability and sonic velocity. In contrast, the NLR-based Bayesian approach gives better estimates of permeability for boreholes where no linear relationship exists between logarithm permeability and sonic velocity.

Bayesian computation via empirical likelihood

Approximate Bayesian computation has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another route to such settings that bypasses simulations from the model and the choices of the approximate Bayesian computation parameters (summary statistics, distance, tolerance), while being convergent in the number of observations. Furthermore, bypassing model simulations may lead to significant time savings in complex models, for instance those found in population genetics. The Bayesian computation with empirical likelihood algorithm we develop in this paper also provides an evaluation of its own performance through an associated effective sample size. The method is illustrated using several examples, including estimation of standard distributions, time series, and population genetics models.

Nurse-administered procedural sedation and analgesia in the cardiac catheterisation laboratory : a mixed methods study

The cardiac catheterisation laboratory (CCL) is a specialised medical radiology facility where both chronic-stable and life-threatening cardiovascular illness is evaluated and treated. Although there are many potential sources of discomfort and distress associated with procedures performed in the CCL, a general anaesthetic is not usually required. For this reason, an anaesthetist is not routinely assigned to the CCL. Instead, to manage pain, discomfort and anxiety during the procedure, nurses administer a combination of sedative and analgesic medications according to direction from the cardiologist performing the procedure. This practice is referred to as nurse-administered procedural sedation and analgesia (PSA). While anecdotal evidence suggested that nurse-administered PSA was commonly used in the CCL, it was clear from the limited information available that current nurse-led PSA administration and monitoring practices varied and that there was contention around some aspects of practice including the type of medications that were suitable to be used and the depth of sedation that could be safely induced without an anaesthetist present. The overall aim of the program of research presented in this thesis was to establish an evidence base for nurse-led sedation practices in the CCL context. A sequential mixed methods design was used over three phases. The objective of the first phase was to appraise the existing evidence for nurse-administered PSA in the CCL. Two studies were conducted. The first study was an integrative review of empirical research studies and clinical practice guidelines focused on nurse-administered PSA in the CCL as well as in other similar procedural settings. This was the first review to systematically appraise the available evidence supporting the use of nurse-administered PSA in the CCL. A major finding was that, overall, nurse-administered PSA in the CCL was generally deemed to be safe. However, it was concluded from the analysis of the studies and the guidelines that were included in the review, that the management of sedation in the CCL was impacted by a variety of contextual factors including local hospital policy, workforce constraints and cardiologists’ preferences for the type of sedation used. The second study in the first phase was conducted to identify a sedation scale that could be used to monitor level of sedation during nurse-administered PSA in the CCL. It involved a structured literature review and psychometric analysis of scale properties. However, only one scale was found that was developed specifically for the CCL, which had not undergone psychometric testing. Several weaknesses were identified in its item structure. Other sedation scales that were identified were developed for the ICU. Although these scales have demonstrated validity and reliability in the ICU, weaknesses in their item structure precluded their use in the CCL. As findings indicated that no existing sedation scale should be applied to practice in the CCL, recommendations for the development and psychometric testing of a new sedation scale were developed. The objective of the second phase of the program of research was to explore current practice. Three studies were conducted in this phase using both quantitative and qualitative research methods. The first was a qualitative explorative study of nurses’ perceptions of the issues and challenges associated with nurse-administered PSA in the CCL. Major themes emerged from analysis of the qualitative data regarding the lack of access to anaesthetists, the limitations of sedative medications, the barriers to effective patient monitoring and the impact that the increasing complexity of procedures has on patients' sedation requirements. The second study in Phase Two was a cross-sectional survey of nurse-administered PSA practice in Australian and New Zealand CCLs. This was the first study to quantify the frequency that nurse-administered PSA was used in the CCL setting and to characterise associated nursing practices. It was found that nearly all CCLs utilise nurse-administered PSA (94%). Of note, by characterising nurse-administered PSA in Australian and New Zealand CCLs, several strategies to improve practice, such as setting up protocols for patient monitoring and establishing comprehensive PSA education for CCL nurses, were identified. The third study in Phase Two was a matched case-control study of risk factors for impaired respiratory function during nurse-administered PSA in the CCL setting. Patients with acute illness were found to be nearly twice as likely to experience impaired respiratory function during nurse-administered PSA (OR=1.78; 95%CI=1.19-2.67; p=0.005). These significant findings can now be used to inform prospective studies investigating the effectiveness of interventions for impaired respiratory function during nurse-administered PSA in the CCL. The objective of the third and final phase of the program of research was to develop recommendations for practice. To achieve this objective, a synthesis of findings from the previous phases of the program of research informed a modified Delphi study, which was conducted to develop a set of clinical practice guidelines for nurse-administered PSA in the CCL. The clinical practice guidelines that were developed set current best practice standards for pre-procedural patient assessment and risk screening practices as well as the intra and post-procedural patient monitoring practices that nurses who administer PSA in the CCL should undertake in order to deliver safe, evidence-based and consistent care to the many patients who undergo procedures in this setting. In summary, the mixed methods approach that was used clearly enabled the research objectives to be comprehensively addressed in an informed sequential manner, and, as a consequence, this thesis has generated a substantial amount of new knowledge to inform and support nurse-led sedation practice in the CCL context. However, a limitation of the research to note is that the comprehensive appraisal of the evidence conducted, combined with the guideline development process, highlighted that there were numerous deficiencies in the evidence base. As such, rather than being based on high-level evidence, many of the recommendations for practice were produced by consensus. For this reason, further research is required in order to ascertain which specific practices result in the most optimal patient and health service outcomes. Therefore, along with necessary guideline implementation and evaluation projects, post-doctoral research is planned to follow up on the research gaps identified, which are planned to form part of a continuing program of research in this field.

Predicting depressive and anxiety disorders with the YASR internalising scales (empirical and DSM-oriented)

Background The Achenbach problem behaviour scales (CBCL/YSR) are widely used. The DSM-oriented anxiety and depression scales have been created to improve concordance between Achenbach’s internalising scales and DSM-IV depression and anxiety. To date no study has examined the concurrent utility of the young adult (YASR) internalising scales, either the empirical or newly developed DSM-oriented depressive or anxiety scales. Methods A sample of 2,551 young adults, aged 18–23 years, from an Australian cohort study. The association between the empirical and DSM-oriented anxiety and depression scales were individually assessed against DSMIV depression and anxiety diagnoses derived from structured interview. Odds ratios, ROC analyses and diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values) were used to report findings. Results YASR empirical internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. DSM-oriented depressive or anxiety scales did not appear to improve the concordance with DSM-IV diagnosed depression or anxiety. The internalising scales were much more effective at identifying those with comorbid depression and anxiety, with Ors between 10.1 and 21.7 depending on the internalising scale used. Conclusion DSM-oriented scales perform no better than the standard internalising in identifying young adults with DSM-IV mood or anxiety disorder.

Empirical evaluation of public transport travel time variability

Although transit travel time variability is essential for understanding the deterioration of reliability, optimising transit schedule and route choice; it has not attracted enough attention from the literature. This paper proposes public transport-oriented definitions of travel time variability and explores the distributions of public transport travel time using the Transit Signal Priority data. First, definitions of public transport travel time variability are established by extending the common definitions of variability in the literature and by using route and services data of public transport vehicles. Second, the paper explores the distribution of public transport travel time. A new approach for analysing the distributions involving all transit vehicles as well as vehicles from a specific route is proposed. The Lognormal distribution is revealed as the descriptors for public transport travel time from the same route and service. The methods described in this study could be of interest for both traffic managers and transit operators for planning and managing the transit systems.

Frontier Techniques for Measuring and Estimating Airport Efficiency : An Empirical Review with Practical Guidelines for Analysis and Future Research

Airport efficiency is important because it has a direct impact on customer safety and satisfaction and therefore the financial performance and sustainability of airports, airlines, and affiliated service providers. This is especially so in a world characterized by an increasing volume of both domestic and international air travel, price and other forms of competition between rival airports, airport hubs and airlines, and rapid and sometimes unexpected changes in airline routes and carriers. It also reflects expansion in the number of airports handling regional, national, and international traffic and the growth of complementary airport facilities including industrial, commercial, and retail premises. This has fostered a steadily increasing volume of research aimed at modeling and providing best-practice measures and estimates of airport efficiency using mathematical and econometric frontiers. The purpose of this chapter is to review these various methods as they apply to airports throughout the world. Apart from discussing the strengths and weaknesses of the different approaches and their key findings, the paper also examines the steps faced by researchers as they move through the modeling process in defining airport inputs and outputs and the purported efficiency drivers. Accordingly, the chapter provides guidance to those conducting empirical research on airport efficiency and serves as an aid for aviation regulators and airport operators among others interpreting airport efficiency research outcomes.

Empirical facts : a rationale for expanding lawyers' methodological expertise

This article examines the importance of the social evidence base in relation to the development of the law. It argues that there is a need for those lawyers who play a part in law reform (legislators and those involved in the law reform process) and for those who play a part in formulating policy-based common law rules (judges and practitioners) to know more about how facts are established in the social sciences. It argues that lawyers need sufficient knowledge and skills in order to be able to critically assess the facts and evidence base when examining new legislation and also when preparing, arguing and determining the outcomes of legal disputes. For this reason the article argues that lawyers need enhanced training in empirical methodologies in order to function effectively in modern legal contexts.

Empirical study to investigate the difficulties of implementing safety practices in the repair and maintenance sector in Hong Kong

Repair, maintenance, minor alteration, and addition work (RMAA) has become more and more important in developed societies, but its safety performance is alarming. For example, RMAA projects accounted for 53.2% of the total construction market and the percentage of RMAA accidents to all construction accidents in the Hong Kong Special Administrative Region (HKSAR) increased considerably in 2007. The RMAA sector has a huge potential for safety improvement. This study aims to explore and evaluate the difficulties of implementing safety practices in RMAA work. The mixed methods approach was adopted, and semistructured interviews and a two-round Delphi survey were conducted for the data collection. Major difficulties were identified, including limited safety resources for small and medium enterprises (SMEs), difficulty in changing the mindset of RMAA workers, and difficulty in performing safety supervision. These obstacles for implementing safety practices in the RMAA sector, if successfully removed, could significantly improve the safety performance of the RMAA sector and the construction industry as a whole.

A comparison of spatially explicit landscape representation methods and their relationship to stream condition

1. Biodiversity, water quality and ecosystem processes in streams are known to be influenced by the terrestrial landscape over a range of spatial and temporal scales. Lumped attributes (i.e. per cent land use) are often used to characterise the condition of the catchment; however, they are not spatially explicit and do not account for the disproportionate influence of land located near the stream or connected by overland flow. 2. We compared seven landscape representation metrics to determine whether accounting for the spatial proximity and hydrological effects of land use can be used to account for additional variability in indicators of stream ecosystem health. The landscape metrics included the following: a lumped metric, four inverse-distance-weighted (IDW) metrics based on distance to the stream or survey site and two modified IDW metrics that also accounted for the level of hydrologic activity (HA-IDW). Ecosystem health data were obtained from the Ecological Health Monitoring Programme in Southeast Queensland, Australia and included measures of fish, invertebrates, physicochemistry and nutrients collected during two seasons over 4 years. Linear models were fitted to the stream indicators and landscape metrics, by season, and compared using an information-theoretic approach. 3. Although no single metric was most suitable for modelling all stream indicators, lumped metrics rarely performed as well as other metric types. Metrics based on proximity to the stream (IDW and HA-IDW) were more suitable for modelling fish indicators, while the HA-IDW metric based on proximity to the survey site generally outperformed others for invertebrates, irrespective of season. There was consistent support for metrics based on proximity to the survey site (IDW or HA-IDW) for all physicochemical indicators during the dry season, while a HA-IDW metric based on proximity to the stream was suitable for five of the six physicochemical indicators in the post-wet season. Only one nutrient indicator was tested and results showed that catchment area had a significant effect on the relationship between land use metrics and algal stable isotope ratios in both seasons. 4. Spatially explicit methods of landscape representation can clearly improve the predictive ability of many empirical models currently used to study the relationship between landscape, habitat and stream condition. A comparison of different metrics may provide clues about causal pathways and mechanistic processes behind correlative relationships and could be used to target restoration efforts strategically.

Methods for sociological inquiry on emotion in educational settings

Sociological approaches to inquiry on emotion in educational settings are growing. Despite a long tradition of research and theory in disciplines such as psychology and sociology, the methods and approaches for naturalistic investigation of emotion are in a developmental phase in educational settings. In this article, recent empirical studies on emotion in educational contexts are canvassed. The discussion focuses on the use of multiple methods within research conducted in high school and university classrooms highlighting recent methodological progress. The methods discussed include facial expression analysis, verbal and non-verbal conduct, and self-report methods. Analyses drawn from different studies, informed by perspectives from microsociology, highlight the strengths and limitations of any one method. The power and limitations of multi-method approaches is discussed.