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      Information bias in health research: definition, pitfalls, and adjustment methods

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          Abstract

          As with other fields, medical sciences are subject to different sources of bias. While understanding sources of bias is a key element for drawing valid conclusions, bias in health research continues to be a very sensitive issue that can affect the focus and outcome of investigations. Information bias, otherwise known as misclassification, is one of the most common sources of bias that affects the validity of health research. It originates from the approach that is utilized to obtain or confirm study measurements. This paper seeks to raise awareness of information bias in observational and experimental research study designs as well as to enrich discussions concerning bias problems. Specifying the types of bias can be essential to limit its effects and, the use of adjustment methods might serve to improve clinical evaluation and health care practice.

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          Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure.

          Questionnaires are used to estimate disease burden. Agreement between questionnaire responses and a criterion standard is important for optimal disease prevalence estimates. We measured the agreement between self-reported disease and medical record diagnosis of disease. A total of 2,037 Olmsted County, Minnesota residents > or =45 years of age were randomly selected. Questionnaires asked if subjects had ever had heart failure, diabetes, hypertension, myocardial infarction (MI), or stroke. Medical records were abstracted. Self-report of disease showed >90% specificity for all these diseases, but sensitivity was low for heart failure (69%) and diabetes (66%). Agreement between self-report and medical record was substantial (kappa 0.71-0.80) for diabetes, hypertension, MI, and stroke but not for heart failure (kappa 0.46). Factors associated with high total agreement by multivariate analysis were age 12 years, and zero Charlson Index score (P < .05). Questionnaire data are of greatest value in life-threatening, acute-onset diseases (e.g., MI and stroke) and chronic disorders requiring ongoing management (e.g.,diabetes and hypertension). They are more accurate in young women and better-educated subjects.
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            Measurement Error Models

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              A new scale of social desirability independent of psychopathology.

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                Author and article information

                Journal
                J Multidiscip Healthc
                J Multidiscip Healthc
                Journal of Multidisciplinary Healthcare
                Journal of Multidisciplinary Healthcare
                Dove Medical Press
                1178-2390
                2016
                04 May 2016
                : 9
                : 211-217
                Affiliations
                Department of Basic Medical Sciences, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
                Author notes
                Correspondence: Alaa Althubaiti, Department of Basic Medical Sciences, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Mail Code: 3127, Riyadh 11481, PO Box 3660, Saudi Arabia, Tel +966 1 1429 9999, Email thubaitia@ 123456ksau-hs.edu.sa
                Article
                jmdh-9-211
                10.2147/JMDH.S104807
                4862344
                27217764
                c7614598-6c59-4dce-a61b-b7b80bd51b27
                © 2016 Althubaiti. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

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                Categories
                Review

                Medicine
                self-report bias,social desirability bias,recall bias,misclassification,measurement error bias,confirmation bias

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