Introduction on 'assessing the risk of bias of individual studies' in systematic review of healthcare intervention programs revised by the Agency for Healthcare Research and Quality / 中华流行病学杂志

This paper summarizes the Risk of Bias of Individual Studies in Systematic Reviews of Health Care Interventions revised by the Agency for Healthcare Research and Quality (AHRQ) and introduces how to use Revman software make risk of bias graph or risk of bias summary.AHRQ tool can be used to evaluate following study designs:RCTs,cohort study,case-control study (including nested case-control),case series study and cross-sectional study.The tool evaluates the risk of bias of individual studies from selection bias,performance bias,attrition bias,detection bias and reporting bias.Each of the bias domains contains different items,and each item is available for the assessment of one or more study designs.It is worth noting that the appropriate items should be selected for evaluation different study designs instead of using all items to directly assess the risk of bias.AHRQ tool can be used to evaluate risk of bias individual studies when systematic reviews of health care interventions is including different study designs.Moreover,the tool items are relatively easy to understand and the assessment process is not complicated.AHRQ recommends the use of high,medium and low risk classification methods to assess the overall risk of bias of individual studies.However,AHRQ gives no recommendations on how to determine the overall bias grade.It is expected that future research will give corresponding recommendations.

Introduction on 'assessing the risk of bias of individual studies' in systematic review of healthcare intervention programs revised by the Agency for Healthcare Research and Quality / 中华流行病学杂志

This paper summarizes the Risk of Bias of Individual Studies in Systematic Reviews of Health Care Interventions revised by the Agency for Healthcare Research and Quality (AHRQ) and introduces how to use Revman software make risk of bias graph or risk of bias summary.AHRQ tool can be used to evaluate following study designs:RCTs,cohort study,case-control study (including nested case-control),case series study and cross-sectional study.The tool evaluates the risk of bias of individual studies from selection bias,performance bias,attrition bias,detection bias and reporting bias.Each of the bias domains contains different items,and each item is available for the assessment of one or more study designs.It is worth noting that the appropriate items should be selected for evaluation different study designs instead of using all items to directly assess the risk of bias.AHRQ tool can be used to evaluate risk of bias individual studies when systematic reviews of health care interventions is including different study designs.Moreover,the tool items are relatively easy to understand and the assessment process is not complicated.AHRQ recommends the use of high,medium and low risk classification methods to assess the overall risk of bias of individual studies.However,AHRQ gives no recommendations on how to determine the overall bias grade.It is expected that future research will give corresponding recommendations.

Bias in Dental Research / Dentistry.

Bias is an inevitable part of study designs. Despite best efforts of research, scholars and authors biases are bound to occur in research methodology. The aim of this review article is to acquaint the dental authors with various types of bias and methods to reduce these in dental research. To understand the basics of different biases in dental research is hence essential to keep it to minimum in any research for the effectiveness of the study.

Exploring Study Designs for Evaluation of Interventions Aimed to Reduce Occupational Diseases and Injuries

Effective interventions to reduce work-related exposures are available for many types of work-related diseases or injuries. However, knowledge of the impact of these interventions on injury or disease outcomes is scarce due to practical and methodological reasons. Study designs are considered for the evaluation of occupational health interventions on occupational disease or injury. Latency and frequency of occurrence of the health outcomes are two important features when designing an evaluation study with occupational disease or occupational injury as an outcome measure. Controlled evaluation studies-giving strong indications for an intervention effect-seem more suitable for more frequently occurring injuries or diseases. Uncontrolled evaluation time or case series studies are an option for evaluating less frequently occurring injuries or diseases. Interrupted time series offer alternatives to experimental randomized controlled trials to give an insight into the effectiveness of preventive actions in the work setting to decision and policy makers.

Statistics in Clinical Research of Oriental Medicine / 日本東洋医学雑誌

Oriental medicine encompasses various areas including Kampo medicine, and alternative treatments such as acupuncture and massage. Special knowledge of statistics is not necessary to understand in oriental medicine, for which it is sufficient to master general statistics. This review describes statistic fundamentals and important issues for submitting an original article. It describes statistical thinking, data collection, study design, special considerations related to oriental medicine, fundamental statistical methods, multivariate analysis, and statistical software. In particular, it deals with the concept of sample variation, observational and experimental studies, rationale for randomization, sample size determination, t-tests, chi-square tests, paired tests, nonparametric methods, P-values, correlation coefficients, multiple regression, and logistic regression.

Statistics in Clinical Research of Oriental Medicine / 日本東洋医学雑誌

Oriental medicine encompasses various areas including Kampo medicine, and alternative treatments such as acupuncture and massage. Special knowledge of statistics is not necessary to understand in oriental medicine, for which it is sufficient to master general statistics. This review describes statistic fundamentals and important issues for submitting an original article. It describes statistical thinking, data collection, study design, special considerations related to oriental medicine, fundamental statistical methods, multivariate analysis, and statistical software. In particular, it deals with the concept of sample variation, observational and experimental studies, rationale for randomization, sample size determination, t-tests, chi-square tests, paired tests, nonparametric methods, P-values, correlation coefficients, multiple regression, and logistic regression.

Epidemiologic Methods and Study Designs for Investigating Adverse Health Effects of Ambient Air Pollution / 예방의학회지

Air pollution epidemiologic studies are intrinsically difficult because the expected effect size at general environmental levels is small, exposure and misclassification of exposure are common, and exposure is not selective to a specific pollutant. In this review paper, epidemiologic study designs and analytic methods are described, and two nationwide projects on air pollution epidemiology are introduced. This paper also demonstrates that possible confounding issues in time-series analysis can be resolved and the impact on the use of data from ambient monitoring stations may not be critical. In this paper we provide a basic understanding of the types of air pollution epidemiologic study designs that be subdivided by the mode of air pollution effects on human health (acute or chronic). With the improvements in the area of air pollution epidemiologic studies, we should emphasize that elaborate models and statistical techniques cannot compensate for inadequate study design or poor data collection.