As one of the most recommended strategies in decision making of contemporary medicine, evidence-based medicine (EBM) is attracting more and more attention. For EBM, the scientific evidences are obtained mainly from the randomized controlled trials (RCTs), systematic review and meta-analysis. In particular, meta-analysis can help researchers statistically combine several independent studies for a same clinical problem. In meta-analysis, Cohen's d and Hedges' g are among the most commonly used effect size measurements for continuous data. To compute these mean difference criteria, the sample mean and standard deviation are two conventional statistics reported in the literature. However, some other clinical studies may instead report the median, minimum and maximum values, and/or sample quartiles. Such a situation requires researchers to estimate the sample mean and standard deviation from these reported summary statistics. We note, however, that most existing estimators in the literature have some serious limitations. For this, we propose to improve the existing methods and extend them to three frequently encountered scenarios. In this thesis, we developed the optimal sample mean estimators, the normality test statistics and the updated Cohen's d mean difference criterion for three commonly encountered scenarios in meta-analysis. In Chapter 1, we gave a brief introduction on evidence-based medicine, meta-analysis and the summary data. In Chapter 2, we introduced our optimal estimators of the sample mean under the three scenarios, respectively. In Chapter 3, we proposed several methods for testing the normality of the underlying data. And in Chapter 4, we proposed to improve the famous Cohen's d and its relevant parameters. To assess the practical performance of our newly proposed methods, we also chose a few real data at the end of each chapter as illustrating examples. Numerical results of those studies indicated that our proposed methods have satisfactory performance both in theory and in practice. Following our new methodology, we also recommended an improved procedure for medical researchers to conduct meta-analysis. For illustration, we chose a meta-analysis in Chapter 5 on the effect of phytosterols to plasma CRP level (Rocha et al., 2016) to compare the results obtained from our recommended procedure and from the original methods. The results showed that our recommended procedure may lead to distinctly different results for a same clinical problem. To conclude the thesis, we expect that our newly proposed methods can be regarded as "rules of thumb" and will soon be widely applied in meta-analysis and evidence-based medicine.

No description available.

Publicly available datasets in health science are often large and observational, in contrast to experimental datasets where a small number of data are collected in controlled experiments. Variables' causal relationships in the observational dataset are yet to be determined. However, there is a significant interest in health science to discover and analyze causal relationships from health data since identified causal relationships will greatly facilitate medical professionals to prevent diseases or to mitigate the negative effects of the disease. Recent advances in Computer Science, particularly in Bayesian networks, has initiated a renewed interest for causality research. Causal relationships can be possibly discovered through learning the network structures from data. However, the number of candidate graphs grows in a more than exponential rate with the increase of variables. Exact learning for obtaining the optimal structure is thus computationally infeasible in practice. As a result, heuristic approaches are imperative to alleviate the difficulty of computations. This research provides effective and efficient learning tools for local causal discoveries and novel methods of learning causal structures with a combination of background knowledge. Specifically in the direction of constraint based structural learning, polynomial-time algorithms for constructing causal structures are designed with first-order conditional independence. Algorithms of efficiently discovering non-causal factors are developed and proved. In addition, when the background knowledge is partially known, methods of graph decomposition are provided so as to reduce the number of conditioned variables. Experiments on both synthetic data and real epidemiological data indicate the provided methods are applicable to large-scale datasets and scalable for causal analysis in health data. Followed by the research methods and experiments, this dissertation gives thoughtful discussions on the reliability of causal discoveries computational health science research, complexity, and implications in health science research.

This project was undertaken to provide the Family Practice residency evaluation committee with a better means of studying resident progress.An attempt is made herewith to describe the project so that future personnel with use of this paper and minimal use of the system manuals can continue operation of this system and accomplish the ultimate goal of the project.A talley of resident experience with pricare problems, drug categories, procedures, and use of laboratory examinations is maintained. The same computer file also stores his patient profile. The programs are written in Fortran l.0 for the DEC system at Ball State University.Ball State UniversityMuncie, IN 47306

This thesis seeks to demonstrate, by way of a multidisciplinary study, that consent is, despite its legal definition which refers to the free and enlighted expression of individual will, in fact, at times limited if not eliminated, by social considerations, arising from the medical, economic and legal context. These considerations reflect what one might call the social norm. An appropriate understanding of consent serves, therefore, to express the social norm as a constraint, which, in turn, acts as a measure of what it means to belong in society. Thus, while consent is often presented as the fundamental principle to be respected in biomedical research, it is in reality, merely one principle to respect among others. These limitations connected to consent are exacerbated in emergency situations where consent is sometimes reduced to mere signature, and in some cases it has been recognized that research can be undertaken without the subject's prior consent.

This thesis analyses the state of health care in South Africa with particular reference to a clinic and the Provincial Hospital in Port Elizabeth, Eastern Cape. The complexities of health care provision in a diverse sociolinguistic environment where certain languages are emphasized over others, forms the cornerstone of the research. The research focuses on health care in a complex multi-cultural environment. The goal of the research is to present a coherent and robust translation framework for the development of suitable materials to enhance communication across language and cultural barriers in the health care sector. A model (based on research completed in the USA) is presented as a possible alternative in the final chapter of the thesis.

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The aims of this thesis are to investigate the factors influencing treatment fidelity of health behaviour change (HBC) interventions. The thesis will focus on HBC interventions delivered by practice nurses (PNs) and health care assistants (HCAs) to patients within general practice, although the findings will be explored within the context of the wider treatment fidelity literature. The thesis comprises five studies, focussed on exploring, enhancing and assessing fidelity of delivery and receipt of HBC interventions. Through developing an enhanced understanding of these areas of treatment fidelity, the thesis will also make recommendations for strategies to enhance and assess fidelity of delivery and receipt of future HBC interventions. Study one is a meta-synthesis of qualitative studies that explored the views and experiences of nurses who had delivered HBC interventions with a focus on how this can inform future delivery of HBC interventions. Study two is an Interpretative Phenomenological Analysis of PNs’/HCAs’ experiences of helping patients to change their health behaviours within the context of their routine care, and before and after delivery of an intervention to facilitate increased walking. Study three reports a quantitative assessment of delivery of intervention techniques to facilitate increased walking, as specified in an intervention protocol, by PNs/HCAs. Study four explores PNs’/HCAs’ views and experiences of the factors that influenced their delivery of the walking intervention. Study five investigates treatment receipt, by exploring patients’ understanding of, and experiences of receiving the walking intervention. The key findings from this research are that delivery and receipt of HBC interventions within general practice are influenced by a range of factors that include the providers’ confidence and skills, the patients’ expectations and/or engagement with the intervention and the general practice within which the intervention is delivered. A number of these factors are difficult to influence and so research teams need to develop a range of strategies to enhance delivery and receipt of HBC interventions. These may include appropriate preparation for providers to deliver the intervention, the provision of a simple intervention resource to support delivery of the intervention and the development of strategies to enhance patients’ understanding of intervention techniques.

Introduktion: Fysisk inaktivitet och stillasittande beteende är två av de största riskfaktorerna för ohälsa, sjukdom och död i västvärlden idag. Många människor uppfyller inte riktlinjerna kring regelbunden fysisk aktivitet, och studenter är inget undantag. Aktiva studenter var ett projekt på KTHhallen i Stockholm som bedrevs för sjätte året i rad med syftet att få fysiskt inaktiva studenter att bli aktiva. Syfte: Syftet med denna studie var att undersöka varför deltagarna valde att delta i Aktiva studenter, hur de upplevde projektet samt om de upplevde några effekter av sitt deltagande och i så fall på vilket sätt.  Metod: Studien genomfördes som en kvalitativ intervjustudie med sex semistrukturerade intervjuer. Materialet sorterades med hjälp av studiens syfte och diskuterades sedan med hjälp av Deci och Ryans Self-Determination Theory och tidigare forskning inom ämnet. Resultat: Alla deltagare brukade vara fysiskt aktiva när de var yngre, men hade de senaste åren varit inaktiva. De definierade sig ändå som aktiva personer, vilket var en av huvudanledningarna till att de ansökte till Aktiva studenter. De ville återfå sina gamla vanor. Studien visade att Aktiva studenter hade positiva effekter på deltagarnas fysiska aktivitetsvanor. Nästan alla deltagare trodde att de skulle fortsätta med dessa vanor om ett och tio år. Studien visade också att den ökade fysiska aktivitetsnivån hade positiva effekter på deras fysiska och mentala hälsa.  Konklusion: Genom deltagande i Aktiva studenter ökade deltagarnas motivation till fysisk aktivitet, och då främst den yttre motivationen. Studenterna som deltog i studien hade varit aktiva tidigare i livet men var inaktiva vid projektets start. Det är därför inte möjligt att utifrån denna studie säga om och hur studenter som aldrig varit fysiskt aktiva tidigare, och som är fullständigt omotiverade till att bli detta, skulle påverkas av ett liknande projekt då de inte förekom som deltagare i studien, men trots detta kan ha deltagit i projektet.

Background Selective reporting of outcomes within a published study based on their nature or direction can result in systematic differences between reported and unreported data. Direct evidence of outcome reporting bias is limited to case reports. Objective To study empirically the nature of outcome reporting bias in randomised controlled trials (RCTs). Methods Three cohorts of RCTs were identified: PubMed-indexed RCTs published in December 2000; trial protocols approved by a Danish ethics committee from 1994-95; and trial protocols funded by a government agency in Canada from 1990-98. Data on reported and unreported outcomes were recorded from all trial publications and a survey of authors. An outcome was considered incompletely reported if insufficient data were presented for meta-analysis. Odds ratios relating the completeness of outcome reporting to statistical significance were calculated for each trial, and then pooled using a random effects meta-analysis. Protocols and publications were also reviewed for discrepancies in primary outcome reporting. Results 519 trials with 10,557 outcomes, 102 trials with 3613 outcomes, and 48 trials with 1390 outcomes were identified for the PubMed, ethics committee, and funding agency cohorts respectively. 22%-35% of outcomes per parallel group study were, on average, incompletely reported for meta-analysis. Fully reported outcomes had a two- to three-fold higher odds of being statistically significant compared to incompletely reported outcomes. The most common reasons given for omitting outcomes included a lack of clinical importance, lack of statistical significance, and space constraints. Major discrepancies between primary outcomes in protocols and publications were found in one half of trials. Discussion and conclusions The reporting of trial outcomes is frequently inadequate for meta-analysis; is biased to favour statistical significance; and is inconsistent with pre-specified protocol outcomes. Unacknowledged modifications to outcomes specified in trial protocols constitute scientific misconduct. Meta-analyses may therefore produce inflated and unreliable estimates of treatment effect.