Search

Background: Research waste and inefficiency occur when research studies do not contribute to the decisions of patients, clinicians, and policymakers. In this thesis, I examine research waste and inefficiency throughout the stages of cardiovascular clinical prediction rule (CPRs) development and explore their causes and implications. Methods: This thesis includes six research projects. A mixed-methods study, which consists of a review of derivation studies, thematic content analysis, and author survey, assesses justifications for deriving a new cardiovascular CPR. Using survival analysis, I evaluate the probability for a CPR for cardiovascular disease risk to have an independent external validation study after its derivation. I assess whether external validation studies update the Framingham Wilson coronary heart disease (CHD) risk rule when it performs poorly, and external validation studies contribute to understanding the performance in meta- analyses. A systematic review evaluates the design, methods, and reporting of studies assessing the impact of cardiovascular CPRs. I conduct an online survey to understand which cardiovascular CPRs are recognised and used by GPs in the UK. Lastly, an exploratory qualitative interview study with thematic analysis explores how perceptions of and experiences with cardiovascular CPR research influence primary care providers' (PCPs) decisions about using cardiovascular CPRs. Results: I found that the authors of derivation studies do not cite existing evidence when justifying a new cardiovascular CPR even though they believe it is important to do so. Most of cardiovascular CPRs do not have a timely conducted independent external validation study. External validation studies of Framingham Wilson CHD risk rule fail to generate the evidence of generalizability to their full potential because they do not update the CPR when it performs poorly, or do not contribute to understanding the CPR's overall performance. The vast majority of impact studies had flaws in study design, methods or reporting. GPs' use of cardiovascular CPRs in the UK has evolved and is focused on a few CPRs, such as the QRISK scores. PCPs' decisions about using cardiovascular CPRs seem to be influenced by their familiarity, trust, and confidence in using research evidence. Conclusions: To reduce research waste and inefficiency in cardiovascular CPR development, it is necessary to shift the paradigm from deriving new CPRs to externally validating, assessing the impact of, and promoting the adoption of high-quality existing cardiovascular CPRs. Also, systematic efforts are needed to reduce the flaws in design, methods, and reporting of CPR studies, and strengthen evidence-base to support the use of cardiovascular CPRs.

This study aims to investigate the determinants of capital structure in small and medium-sized enterprises (SMEs) in Malaysia and their effect on firms’ performance. The study addresses the following primary question: What are the factors that influence the capital structure of SMEs in Malaysia? The sample of this research is SMEs in the east coast region of Malaysia. Adopting a positivist paradigm, the research design includes a preliminary study comprising 25 interviews with the owner-managers of SMEs, which is analysed using thematic analysis. The results are used to finalise the conceptual framework for the main study, which takes the form of a self-completion questionnaire survey. Usable responses were received from 384 firms, giving a response rate of 75.3%. The survey data is analysed using a series of binomial logistic regression models. Results reveal that there was no indication for the impact of owner’s education and experience on capital structure decisions. Other owner-related factors, firm characteristics, management performance and environment were found to relate to all types of capital structure. Both complete and partial mediating effects are also discovered in this study. The results provide evidence to support the pecking order hypothesis (Myers, 1984; Myers and Majluf, 1984), agency theory (Jensen and Meckling, 1976) and culture model of Schwartz (1994). It appeared that owner-managers in Malaysia do not strive to adjust their capital structure towards some optimal debt ratio, which is contrary to the static trade-off theory (DeAngelo and Masulis, 1980) of capital structure. This study makes several important contributions to the existing studies of capital structure. This research led to the development of a model of capital structure determinants by integrating factors related to owner-managers, firms, culture, and environment. This study incorporates methodological triangulation that may mitigate the problem of the difficulties in accessing financial data of SMEs in Malaysia. This study also provides meaningful insight into the financing preferences of the owner-managers with relevant implementations to academics, business practitioners, financial providers and policymakers. The research findings should assist owner-managers in making optimal capital structure decisions as well as help the policymaker in making an appropriate policy on the financing.

The tumour suppressor p53 protein plays a central role in the DNA damage response/checkpoint pathways leading to DNA repair, cell cycle arrest, apoptosis and senescence. The activation of p53-mediated pathways is primarily facilitated by the binding of tetrameric p53 to two 'half-sites', each consisting of a decameric p53 response element (RE). Functional REs are directly adjacent or separated by a small number of 1-13 'spacer' base pairs (bp). The p53 RE is detected by exact or inexact matches to the palindromic sequence represented by the regular expression [AG][AG][AG]C[AT][TA]G[TC][TC][TC] or a position weight matrix (PWM). The use of matrix-based and regular expression pattern-matching techniques, however, leads to an overwhelming number of false positives. A more specific model, which combines multiple factors known to influence p53-dependent transcription, is required for accurate detection of the binding sites. In this thesis, we present a logistic regression based model which integrates sequence information and epigenetic information to predict human p53 binding sites. Sequence information includes the PWM score and the spacer length between the two half-sites of the observed binding site. To integrate epigenetic information, we analyzed the surrounding region of the binding site for the presence of mono- and trimethylation patterns of histone H3 lysine 4 (H3K4). Our model showed a high level of performance on both a high-resolution data set of functional p53 binding sites from the experimental literature (ChIP data) and the whole human genome. Comparing our model with a simpler sequence-only model, we demonstrated that the prediction accuracy of the sequence-only model could be improved by incorporating epigenetic information, such as the two histone modification marks H3K4me1 and H3K4me3.

The research conducted in this thesis examines the relationship between forms of worklessness (both active unemployment and inactivity due to sickness and disability) and mortality for working age men. Previous research has shown that being out of work is associated with a greater risk of mortality relative to being in work. However, there remains debate as to whether this association is the result of a causal pathway leading from worklessness to mortality or whether it reflects the ‘selection' of individuals who are already at greater risk of mortality from pre-existing poor health or other characteristics. In the UK, many studies rely on the use of ‘wear-off' periods in which mortality events occurring within five years after the observation of employment status are ignored to allow the confounding effects of selection to diminish. Generally these studies concluded in support of a causal relationship. In contrast, more recent studies making use of innovative methodological designs such as natural experiments and linked register and health datasets have found less evidence for this explanation with many emphasising the role of confounding and selection. The thesis aims to firstly, examine the effectiveness of wear-off periods and secondly, to develop an alternative counterfactual approach to examine the relationship between worklessness (both active unemployment and health related inactivity) and mortality. These questions are addressed in three stand-alone papers. In the first paper, data from the Scottish Longitudinal Study and the England & Wales Longitudinal Study was used in logistic regression models which estimated the odds of death in a given time period after the 1991 Census for those aged 35–64 in 1991. The odds ratios for the different economic positions (in work, unemployed, retired, permanently sick and other inactive) were compared, as well as the changes in risk associated with cumulatively increasing the length of wear-off prior to follow-up. No evidence was found of health related selection for the unemployed in 1991 suggesting that the use of the five year wear-off period in many studies of mortality and unemployment may be an ineffective and unnecessary technique for mitigating the effects of health-related selection. The second paper examined men aged between 35 and 54 who were in work in 1991. Subsequent employment status in 2001 was observed (in work or unemployed) and the relative all-cause mortality risk of unemployment between 2001 and 2007 was estimated. To account for potential selection into unemployment of those in poor health, a counterfactual propensity score matching framework was used to construct unbiased and comparable samples of in work and unemployed individuals. Matching was based on a wide range of explanatory variables including health status prior to year of unemployment (hospital admissions and self-reported limiting long term illness) as well as measures of socio-economic position. The findings showed that unemployment was associated with a doubling (hazard ratio 2.1 95% CI 1.30 - 3.38) of the subsequent risk of mortality from all causes relative to employment. This scale of effect was consistent across different samples and was robust controlling for prior health and socio-demographic characteristics. These findings were interpreted as evidence that the often observed association between unemployment and mortality may contain a causal component. The second paper implemented a similar analytical design to address the lack of evidence for the independent mortality effect of inactivity due to sickness. The results showed that the mortality risk of economic inactivity due to sickness relative to active employment was significant (HR. 3.18, 95% CI 2.53-3.98) and suggest that economic inactivity due to sickness poses a mortality risk that is independent of prior health. The findings could be interpreted in two ways; either economic inactivity due to sickness is worse for health than actively seeking work or previous studies of unemployment and mortality have underestimated the true effect of being out of work generally. Across the three studies, the main contribution of the thesis is to reassert the importance of worklessness as a determinant of individual mortality. In doing so the studies also found little evidence of systematic confounding by either health or other characteristics. The thesis concludes with a comprehensive discussion of the wider implications of the findings in relation to both general methodological issues in observational epidemiology and possible policy interventions that could be implemented to tackle work-related inequalities in male mortality.

Introduction:Graves’ Disease is a hyperthyroidism autoimmune disorder that causes symptoms such as changes to the physiology of the eyes and affects vision. This change in vision can lead to patients experiencing migraines or vision loss. I am going to investigate how different populations are affected by migraines caused by Graves’ Disease. More specifically, I will be looking at the differences in the proportion of patients who experience migraines with Graves’ Disease across different racial and socioeconomic groups.Methods:The primary sample for this analysis will contain subsamples from the National Inpatient Sample (NIS) database from the years 2016-2020. For the purposes of this study and analysis, I only included data from hospital records that indicated a diagnosis of Graves’ disease (4030 hospital samples). I obtained demographic data and identified the frequency of each variable found in samples with migraines, in samples without migraines, and in the overall total. In addition, I ran a logistic regression analysis on the NIS dataset to identify which variables could significantly be predicted by the presence of migraines.Results:I did not find a significant relationship between SES and the diagnosis of migraines (p = 0.4109). I did, however, find that Black inpatient hospitalizations were less likely to have migraines than White hospitalizations (OR: 0.668, CI: 0.574 – 0.777). Additionally, Hispanic classified hospitalizations (OR: 0.748, CI: 0.607 – 0.923), Asian/Pacific Islander hospitalizations (OR: 0.451, CI: 0.313 – 0.649), and other hospitalizations (OR: 0.644, CI: 0.450 – 0.921) were also less likely to have migraines than White hospitalizations.Discussion:I found that there was a significant difference between the different races. White hospitalizations were more likely to have migraines than any other race. In addition, I found no statistical difference between the four median income quartile groups. Future research should look deeper into the association between race and migraines and should aim to identify the causes behind this relationship.

Purpose: There is a lack of guidance in referring patients to the clinical pharmacist for diabetes management, which likely results in patients missing out on this beneficial service. It would be useful to know which patients and specific clinical interventions are most likely to show benefit from pharmacy services. To our knowledge, only one study has assessed patient predictors of response to diabetes care provided by a clinical pharmacist, which was limited to baseline variables. Therefore, the primary objective was to describe clinical responses to pharmacist-led diabetes care and to identify baseline and interventional variables that are independently predictive of clinical response. Methods: This was a retrospective cohort study using patient data from two health systems in San Antonio, Texas. Included patients were ≥18 years old with a referral to the pharmacist for Type 2 Diabetes management. Patients were followed for up to 6 months and data were collected at baseline, during follow-up, and at the end of the study. Clinical response was defined as a reduction in the A1C from baseline by ≥1% or meeting the documented A1C goal. Non-responders failed to meet these A1C goals. Variables with P

Fixed-object crashes have long time been considered as major roadway safety concerns. While previous relevant studies tended to address such crashes in the context of roadway departures, and heavily relied on police-reported accidents data, this study integrated the SHRP2 NDS and RID data for analyses, which fully depicted the prior to, during, and after crash scenarios. A total of 1,639 crash, near-crash events, and 1,050 baseline events were acquired. Three analysis methods: logistic regression, support vector machine (SVM) and artificial neural network (ANN) were employed for two responses: crash occurrence and severity level. Logistic regression analyses identified 16 and 10 significant variables with significance levels of 0.1, relevant to driver, roadway, environment, etc. for two responses respectively. The logistic regression analyses led to a series of findings regarding the effects of explanatory variables on fixed-object event occurrence and associated severity level. SVM classifiers and ANN models were also constructed to predict these two responses. Sensitivity analyses were performed for SVM classifiers to infer the contributing effects of input variables. All three methods obtained satisfactory prediction performance, that was around 88% for fixed-object event occurrence and 75% for event severity level, which indicated the effectiveness of NDS event data on depicting crash scenarios and roadway safety analyses.

BACKGROUND Persistent offending has been a topic of interest in the criminal justice literature for some time. Despite its popularity, the concept remains without a consistent or agreed upon definition. For example, persistent offending has been variably defined as offending before and during adulthood (e.g., Bergman & Andershed, 2009), frequent offending (e.g., McGloin & Stickle, 2011), or an early age of first offence (e.g. Hay & Forrest, 2009). In turn, inconsistent methods have been used to operationalise and identify persistent offenders, such as offending before and after the age of 21 (Farrington, Ttofi, & Coid, 2009), the five percent most frequent offenders (Piquero & Lawton, 2002), and multiple offences committed before the age of 14 (Hagell & Newburn, 1994). The definitional inconsistency surrounding the concept of persistent offending poses a significant threat to the generalisability of research, accuracy of theory, and efficacy of policy and interventions. Although previous authors have highlighted their concerns regarding the methodological inconsistencies pertaining to research on persistent offending (Hagell & Newburn, 1994; Piquero, 2009), these concerns seem to have fallen on deaf ears. AIMS This dissertation argues that the use of inconsistent definitions and operationalisations of persistent offending are contributing to the inconsistent findings and competing explanations on the phenomenon. Therefore, more conceptual discussions and empirical observations drawing attention to the ramifications of this issue, as well as methods for rectifying the problem, are needed. Through a series of published and unpublished papers, this dissertation attempts to meet this need by: (1) Highlighting the prevalence of inconsistent definitions, operationalisations, and measures of persistent offending in the literature, and the consequent need for consistency; (2) Empirically demonstrating the flaws associated with these inconsistencies, and; (3) Proposing how to best define, operationalise, and measure persistent offending. The underlying position of this dissertation is that conceptually, persistent offending is best defined and measured by the duration of the criminal career. The arguments and empirical findings in this dissertation support this premise. DATA AND ANALYSES This dissertation uses data from the Cambridge Study in Delinquent Development (CSDD). The CSDD is a longitudinal, population-based study that, to date, has observed the development of offending behaviours in 411 South London males from the age of eight to 56. Boys were interviewed in school at ages eight, ten, and 14 years. Conviction data was recorded annually from the age of 10 to 56. All offences leading to a conviction, excluding minor offences such as traffic infractions and public intoxication, were included in the analyses. The vast majority of men (91 percent) were at risk of conviction at 56 years of age. Chi-square, multiple, and logistic regression analyses were used to examine the association between childhood risk factors and conviction frequency, criminal career duration, and different offending pathways. Descriptive statistics and odds ratios were conducted in order to examine the overlap in the number of offenders identified by different operationalisations of persistent offending. Finally, Pearson’s and partial correlation were used to examine the relationship between criminal career duration, conviction frequency, and age of first conviction. RESULTS Five key findings are reported in this dissertation. First, reviews of the published literature indicated that many of competing empirical findings can be attributed to the use of different definitions and operationalisations of persistent offending. Second, competing measures of persistent offending (i.e., criminal career duration and conviction frequency) are associated with different types and numbers of childhood risk factors. Indeed, not only did offenders with the longest criminal careers have fewer childhood risk factors than offenders with the most convictions, but the childhood risk factors associated with these offenders did not differ to those experienced by one-time offenders. Third, depending on the key measure used, different operationalisations of persistent offending generally identify vastly different offenders as persistent. Fourth, when controlling for offence frequency, onset age is not associated with criminal career duration. Finally, persistent offenders identified by the duration of the criminal career tend to have the longest criminal careers, a more normative age of onset, and vary in their conviction rates. CONCLUSION The collective results of this dissertation support the idea that persistent offending should logically and consistently be defined and measured by the duration of the criminal career. More so, it is proposed that persistent offending should be defined as a criminal career that exceeds the average duration for a criminal career in a population or offender based sample. Nonetheless, a fundamental limitation of proposing a specific definition of persistent offending is that, due to the concepts ambiguity, there are no clear right answers. It may therefore be some time before there is accord on how to define and identify this phenomenon. Nevertheless, it is hoped that, if nothing else, the arguments and findings in this dissertation will spur more scholarly discussions, and help pave the way towards establishing a consistently used definition of persistent offending.

The complexities surrounding public school funding are not unique to Ohio. There have been numerous legal challenges in the State Supreme Courts and seminal cases from the U.S. Supreme Court which have assigned the practices and formulas by which schools are funded to the individual states. Although previous research has investigated voter approval related to school referenda from the 614 public school districts in Ohio, a significant question remains as to which factors are affecting the school districts and their attempts to pass school operating levies. This study focusses on seven typologies developed by the Ohio Department of Education for comparing districts based on nine demographic variables and the factors which predict the outcomes of first attempt school operating levies within each of those typologies.

The main goal of this study is to seek the effects of some risk and prognostic factors contributing to survival of female invasive breast cancer in United States. The study presents the survival analysis for the adult female invasive breast cancer based on the datasets chosen from the Surveillance Epidemiology and End Results (SEER) program of National Cancer Institute (NCI). In this study, the Cox proportional hazard regression model and logistic regression model were employed for statistical analysis. The odds ratios (OR), hazard ratios (HR) and confidence interval (C.I.) were obtained for the risk and prognosis factors. The study results showed that some risk and prognosis factors, such as the demographic factors (race and age), social and family factor (marital status), biomedical factors (tumor size, disease stage, tumor markers and tumor cell differentiation level etc.) and type of treatment patients received had significant effects on survival of the female invasive breast cancer patients.

Studies of sexual dimorphism of the sacrum have generally been conducted as part of broader population research or on living persons and cadavers, making the anthropological literature sparse. The greater sciatic notch and the preauricular sulcus of the ilium have both been found to show sexual dimorphism, although studies of these traits often have ambiguous definitions of characteristics and lack the standardization of measurements. This research was designed to reexamine and test the accuracy of standard scoring systems and measurements of the posterior pelvis used to determine sex and to establish new formulae combining traits and measurements to accurately determine sex using logistic regression analysis. A series of metric measurements and morphological scores were recorded for 104 males and 106 females of both European- and African-American ancestry from the William M. Bass and Terry Collections. In order to reexamine previous research conducted on the posterior pelvis, standard ratios of metric measurements were analyzed to determine ranges and cut-off values for males and females in this sample. The ratio of ala width to the maximum transverse diameter of the sacral base and the ratio of the length and width of the sciatic notch have proven to be the most useful ratios in sex determination, though not as accurate as the formulae created using logistic regression. These data were also analyzed in SPSS using logistic regression to assess the usefulness of metric measurements and morphological scores of the posterior pelvis in sex determination. Using stepwise logistic regression, a combination of traits for both the sacrum and posterior ilium that are the most reliable and accurate for sex determination have been determined. The values for these selected traits can be incorporated into the log odds formulas which will classify an individual as male or female. The ultimate goal of this research was to provide physical anthropologists with iii logistic regression equations that can be used to estimate the sex of the posterior ilium and sacrum. Two equations ranging in accuracy from 79-84% were developed to determine sex of the posterior pelvis.

Background and Objectives Osteopathy in the cranial field (OCF) is a contentious area of manual therapy. The literature base has attracted much debate, and consists of theories, anecdotal claims and limited academic research. As such, the potential mechanisms and effects of OCF remain poorly understood. Current research into the physiological effects of OCF is directed toward changes in measures of autonomic nervous system function. One cranial osteopathic technique, the CV4, is commonly claimed to increase parasympathetic activity. The aim of this study was to determine if the CV4 has the potential to increase parasympathetic nervous system activity in some individuals, to examine the notion of ‘responders’ and ‘non-responders’ to the CV4. Further, this study investigated variables from the participants’ history which predicted response to the CV4, with the objective of identifying responder characteristics in order to assist future research into the mechanisms and effects of OCF techniques. Methods Heart rate variability was measured in thirty participants during an experiment consisting of four phases: baseline, touch control, intervention (CV4) and post-intervention. The CV4 was delivered by one of three registered osteopaths who were experienced in cranial approaches. Response and non-response to the CV4 were operationally defined for the study. Changes in heart rate variability across the phases of the experiment were analysed individually for each participant to determine response or non-response to the CV4. Potential predictor variables for response were collected prior to the experiment. Following allocation of participants into response and non-response categories, logistic regression was used to determine which, if any, variables predicted response to the intervention. Results 14 participants were classified as responders, 16 participants were classified as non-responders. Logistic regression demonstrated predictive value of the variables relating to the individuals’ history of physical trauma and baseline heart rate variability to predict response. The variable height offered marginal predictive value. Conclusion Results of this study support claims that the CV4 has the potential to increase parasympathetic activity in some individuals. Short-term parasympathetic response to the CV4, determined by spectral analysis of heart rate variability, may be associated with an individual’s baseline ANS activity, history of physical trauma, and possibly height. Further research is required to refine understanding of response to the CV4, and to establish the relevance of the prediction models developed in this study.

Recent developments in computing and technology, along with the availability of large amounts of raw data, have contributed to the creation of many effective techniques and algorithms in the fields of pattern recognition and machine learning. Some of the main objectives for developing these algorithms are to identify patterns within the available data or to make predictions, or both. Great success has been achieved with many classification techniques in real-life applications. Concerning binary data classification in particular, analysis of data containing rare events or disproportionate class distributions poses a great challenge to industry and to the machine learning community. This study examines rare events (REs) with binary dependent variables containing many times more non-events (zeros) than events (ones). These variables are difficult to predict and to explain as has been demonstrated in the literature. This research combines rare events corrections on Logistic Regression (LR) with truncated-Newton methods and applies these techniques on Kernel Logistic Regression (KLR). The resulting model, Rare-Event Weighted Kernel Logistic Regression (RE-WKLR) is a combination of weighting, regularization, approximate numerical methods, kernelization, bias correction, and efficient implementation, all of which enable RE-WKLR to be at once fast, accurate, and robust.

This study explores the purchasing determinants affecting red meat in New Zealand. Particular emphasis is placed on disaggregating the attributes determining meat consumption, allowing a better understanding of the causal variables responsible for influencing meat demand. The study consists of both qualitative and quantitative research, with focus groups initially being conducted to form the basis of the quantitative research. Logistic regression analysis is conducted on the data to obtain the determinant variables for twelve commonly consumed red and white meat cuts. A segmentation study is also conducted, to ascertain if these variables are stable determinants of cut selection across different demographic segments. This study suggests that the most influential determinant attribute of meat consumption is convenience, with time-related variables the most important determinants governing red and white meat consumption. Although health concerns are stated as important by consumers, it seems that white meat consumption is increasing at the expense of red meat because it is better able to adapt to consumer's convenience demands.