Randomized controlled trial is widely accepted as the best design for evaluating the efficacy of a new treatment because of the advantages of randomization (random allocation). Randomization eliminates accidental bias, including selection bias, and provides a base for allowing the use of probability theory. Despite its importance, randomization has not been properly understood. This article introduces the different randomization methods with examples: simple randomization; block randomization; adaptive randomization, including minimization; and response-adaptive randomization. Ethics related to randomization are also discussed. The study is helpful in understanding the basic concepts of randomization and how to use R software.
Bias (Epidemiology) ; Ethics ; Probability Theory ; Random Allocation ; Selection Bias

No abstract available.
Bias (Epidemiology)*

This study investigated the management importance and performance level of foodservice managers at senior centers. Using the survey, perceived importance and performance levels of seven foodservice management areas were evaluated and analyzed. Data showed the foodservice facilities were being managed by dietitians (61.6%) or non-dietitians (38.9%). The result indicated that overall importance level (3.43) was higher than performance level (3.02) (p<.01). As of the IPA result, dietitians and non-dietitians had different perspectives in terms of managing the eight categories of foodservice areas. The differences in the IPA results between the two groups may reflect bias attributable to the respondents' degrees of knowledge and professional preparation. The research findings could enhance our understanding of importance of hiring professional dietitians to operate foodservice at senior centers and find out which management area should be concentrated for more effective foodservice management.
Bias (Epidemiology)

Propensity score matching method (PSM) is widely used in observational study to reduce selection bias. Observational study lacks randomization, hence, statistical inferences without bias adjustments usually include observed or unobserved effects of covariates. If a subject with specific characteristics has a higher chance to be selected for a specific treatment, the characteristics have a possible effect on statistical results. PSM is the method for controlling covariate imbalance that produces the selection bias. In this paper, we introduce the basic concepts of PSM and simplified methods of PSM process. However, PSM is a rapidly developing statistical area with many limitations and some disadvantages. These points are described in the concluding section to emphasize the importance of considering the various features of PSM in the study design.
Bias (Epidemiology) ; Methods* ; Observational Study ; Propensity Score* ; Random Allocation ; Selection Bias

The cohort study is an observational epidemiological study which selects the specific study population attempting to study the relatiqnship between an exposure to the purported cause and the subsequent risk of developing disease in accordance of time direction. Since Doll and Hill had studied the association between lung cancer and smoking behavior among the British medical doctors in the years of the last fifties, the defined group cohort studies analysing the relationship between an exposure and the occurence of a disease have become very popular. Cohort studies can be classified as either prospective or retrospective, depending on the temporal relationship between the initiation of the study and the occurence of the disease. Cohort studies are admitted as the very valuable studies for demonstrating the association between an exposure and a disease because it is possible to drive relative and attributable risks and often incidence measures. They can even examine multiple effects of a single exposure. However, they are usually expensive to carry out and large cohorts are required for rare diseases in addition to the time consum ing works. There are also very significant problems associated with selection of appropriate groups to be studied as far as complete ascertainment of disease occurence in them. Usually it is necessary that we must compromise to provide the opportunity for various types of bias such as selection bias, follow-up bias, information bias or misclassification, confounding bias and post hoc bias to occur which can result in incorrect conclusions. Only the success of a cohort study would be expected when the investigator pay the deep care in recognizing and correcting for these biases.
Bias (Epidemiology) ; Cohort Studies* ; Humans ; Incidence ; Lung Neoplasms ; Rare Diseases ; Research Personnel ; Selection Bias ; Smoke ; Smoking

PURPOSE: The objective structured clinical examination (OSCE) is considered to be one of the most robust methods of clinical assessment. One of its strengths lies in its ability to minimise the effects of examiner bias due to the standardisation of items and tasks for each candidate. However, OSCE examiners' assessment scores are influenced by several factors that may jeopardise the assumed objectivity of OSCEs. To better understand this phenomenon, the current review aims to determine and describe important sources of examiner bias and the factors affecting examiners' assessments. METHODS: We performed a narrative review of the medical literature using Medline. All articles meeting the selection criteria were reviewed, with salient points extracted and synthesised into a clear and comprehensive summary of the knowledge in this area. RESULTS: OSCE examiners' assessment scores are influenced by factors belonging to 4 different domains: examination context, examinee characteristics, examinee-examiner interactions, and examiner characteristics. These domains are composed of several factors including halo, hawk/dove and OSCE contrast effects; the examiner's gender and ethnicity; training; lifetime experience in assessing; leadership and familiarity with students; station type; and site effects. CONCLUSION: Several factors may influence the presumed objectivity of examiners' assessments, and these factors need to be addressed to ensure the objectivity of OSCEs. We offer insights into directions for future research to better understand and address the phenomenon of examiner bias.
Bias (Epidemiology) ; Humans ; Leadership ; Patient Selection ; Problem Solving ; Recognition (Psychology)

PURPOSE: This study was a systematic review to evaluate the effects of aromatherapy on menopausal symptoms, perceived stress and depression in middle aged-women. METHODS: Eight databases were searched from their inception September 8, 2015. Two reviewers independently performed the selection of the studies, data abstraction and validations. The risk of bias was assessed using Cochrane criteria. For analysis of the data, a meta-analysis of the studies was performed. RESULTS: From the electronic databases, 73 articles were selected, and 19 removed due to duplication. After two reviewers read the abstracts of 54 studies, 34 studies were selected. Complete papers for 34 original articles were read and, 12 studies which met selection criteria were reviewed and the effects of aromatherapy on menopausal symptoms, stress and depression analyzed using meta-analysis with RevMan. In the 2 studies which included Randomized Controlled Trials testing of aromatherapy on menopausal symptoms and comparison of control and placebo groups were done. Aromatherapy massage was favorably effective in reducing the menopausal symptoms compared to the control group (n=118, MD=-6.33; 95% CI -11.51 to -1.15), and compared to the placebo group (n=117, MD=-4.14; 95% CI -7.63 to -0.64). Also aromatherapy was effective in reducing stress (n=72, SMD=-0.64; 95% CI -1.12 to -0.17) and depression (n=158, MD=-5.63; 95% CI -10.04 to -1.22). CONCLUSION: There is limited evidence suggesting that aromatherapy for middle-aged women may be effective in controlling menopausal symptoms, perceived stress and depression.
Aromatherapy* ; Bias (Epidemiology) ; Depression* ; Female ; Humans ; Massage ; Menopause ; Patient Selection

Evaluation of scientific evidence in the medical literature is based on the research methodology, which can be the fundamental tool for medical professionals to improve their practice. Since analytic studies usually provide evidence for generating hypotheses and selecting appropriate research designs, this article aims to review the methods for evaluating the study quality in randomized controlled trials (RCTs), cohort studies, and case-control studies. Critical appraisal of systematic errors including selection bias, performance bias, attrition bias, detection bias, and publication bias are the essential elements of the evaluation. Clinical trials need to have an adequate description of sequence generation and allocation concealment, blinding for exposure measurement, completeness of follow-up and intention to treat analysis, and blinding for outcome evaluation. For cohort studies, like RCTs, appropriate control of confounding variables is needed to prevent selection bias, and blinding and completeness of follow-up are also very important. Matching of the case group to the control group, blinding of interviewers, and proper definition of the cases and controls are important to prevent bias in a case-control study. Since the process of critical appraisal depends on the quality of reporting, there have been efforts to improve the reporting quality of the medical literature. However, reporting all of the elements necessary to avoid bias does not automatically guarantee an exclusion of bias or the quality of a study; instead, what is important is the logical connection of the elements of a study and the eventual lucid expression of the elements.
Bias (Epidemiology) ; Case-Control Studies ; Cohort Studies ; Confounding Factors (Epidemiology) ; Follow-Up Studies ; Intention to Treat Analysis ; Logic ; Preventive Medicine ; Publication Bias ; Research Design ; Selection Bias

Bias is the main problem that should be considered in epidemiologic research. Information bias caused by measurement error and confounding caused by total energy intake are listed as the main biases in nutritional epidemiology and the concept, fact and the methods for adjusting effects of these biases are discussed. The biases which can be caused during the nutritional epidemiologic research process are listed and discussed. The pros and cons of the continuous data and categorical data of the nutrients and the ways how to categorize the data are reviewed. During the analysis of food and nutrient data, multiple comparison and publication bias are prone to be encountered, and these should be considered in interpretation of the results. Understanding of the biases will lead us to make valuable nutritional epidemiologic research and these lead the application of the research results to control the prevalent noncommunicable diseases.
Bias (Epidemiology)* ; Energy Intake ; Epidemiology* ; Publication Bias

Systematic review had become one of the important research area in medicine. Systematic review can be demonstrating benefit or harm of an intervention when results of individual studies are inconclusive. While narrative reviews can often include an element of selection bias, systematic reviews typically involve a comprehensive plan and search strategy with the goal of reducing bias by identifying, appraising, and synthesizing all relevant studies on a particular topic and investigation of heterogeneity among included studies. Systematic reviews typically include a meta-analysis component which involves using statistical techniques to synthesize the data from several studies into a single quantitative estimate or summary effect size. Systematic review overcomes the limitation of small sample sizes by pooling results from a number of individual studies to generate a single best estimate. Although systematic reviews are published in academic forums, the Cochrane Collaboration is a widely recognized international and not-for-profit organization that promotes, supports, and disseminates systematic reviews and meta-analyses on the efficacy of interventions in the health care field. Systematic review has become a popular and powerful tool. If rigorously conducted, it is essential for evidence-based decision making in clinical practice as well as on the health policy level.
Bias (Epidemiology) ; Cooperative Behavior ; Decision Making ; Delivery of Health Care ; Evidence-Based Medicine ; Health Policy ; Meta-Analysis as Topic ; Population Characteristics ; Publication Bias ; Sample Size ; Selection Bias