How Can Bias Be Recognized by Literature Reviewer
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In research, bias is a systematic error that leads to the acceptance of outcomes and conclusions of a study without giving proper consideration to the possibility of unfair or misleading presentation. Bias is potentially introduced at any stage of the research process, from deciding what your research question is to how you measure your outcomes and choosing which findings to publish.
Equally we indicated in an earlier postal service, the authentication of a systematic review is to reduce bias at all stages of the review process. Although less robust study designs are more likely to contain bias, systematic reviews are not immune to the possibility or risk of introducing bias.
Much of the literature effectually bias in systematic reviews concerns itself mainly with the assessment of bias within the primary inquiry reports included in systematic reviews; still, this mail service volition appraise the types of bias that can creep in during the systematic review procedure itself. As bias tin can announced at any phase, authors should exist enlightened of the specific risks at each phase of the review procedure, and we volition provide tips on how to avoid this.
Types of bias
Bias in review design. Bias can occur at the very start of a systematic review. During this initial stage, review authors should determine key characteristics of the review through PICO, refine the research question, and predetermine inclusion and exclusion criteria. Notwithstanding, sometimes authors have knowledge of a particular type of intervention and therefore know which outcomes are more likely to produce positive findings for this intervention, or mayhap the author has preconceived ideas near the literature of interest and allow these prejudices to determine the type of question asked. For example, prior to a systematic review being conducted an author may believe that in that location have been no master studies conducted on females and therefore include only males in the population of interest.
Bias in locating studies. When locating relevant studies for the systematic review, many biases are possible. First, review authors may include arbitrary search limiters such every bit geographical location of report, or twelvemonth of publication. Imposing these constraints on the population of potential studies volition undoubtedly produce a biased sample considering the authors are potentially ignoring a relevant torso of prove. Second, review authors may restrict their search to only those major databases known to them or non fully include a representation of the databases bachelor. For instance, a database search using just MEDLINE will render but 30-eighty% of relevant trials (see here). Third, publication bias most but refers to the likelihood that those studies with negative effects or non-statistically significant findings will not be published (Rosenthal, 1979). This means that the research bachelor in peer-reviewed journals is skewed towards research with positive results and may not be an accurate representation of totality of the existing enquiry bear witness.
Bias in selecting studies. Threats to the construct validity of a systematic review may occur if a key concept has non been clearly described past a review team and, as a result, relevant studies are screened out in error. For instance, inconsistencies may announced where a review team is interested in measuring prosocial behaviours in children with Autism Spectrum Disorders, however, the person screening studies may non understand or non accept been told that authors intended prosocial behaviours to include peer relationships. Related to construct validity is reviewer bias. This personal bias is introduced by the person screening the studies and is related to how and why they make decisions on the potential eligibility or ineligibility of a study.
Bias in synthesising studies. A major threat in systematic reviews is selective event reporting. This bias is where the review author/s presents only a selection of outcomes and findings based on the statistical significance constitute through their analyses. This bias may as well include selective reporting on subgroups of a population or the exclusion of nonsignificant outcomes measured by the report. Bias may likewise appear when authors appraise the quality of included studies, possibly awarding a lower take a chance of bias score to preferred interventions or primary researchers. Finally, decision bias relates to the way the writer relays the conclusions drawn from the systematic review to the reader. The findings should be presented in lite of all the potential biases included in the review, drawing reference to any limitations uncovered in a transparent way.
Assessing bias
Although diverse tools exist for assessing bias in principal studies, fewer exist for assessing bias in systematic reviews. The checklist AMSTAR has been the most commonly used tool to critically assess the quality of systematic reviews since 2007. Nonetheless, major limitations of this tool have been discussed here, here, and here. A newer tool, ROBIS (risk of bias in systematic reviews), assesses the bias within a systematic review using a domain-based approach. The developers of ROBIS describe their audience as authors of overviews of systematic reviews (review of reviews), those who develop evidence- based guidelines, and systematic review authors who wish to assess risk of bias within their own review.
This report is the first one to compare AMSTAR and ROBIS using eight Cochrane and eight non-Cochrane systematic reviews. The authors found like reliability between the tools merely state that although the tools overlap considerably, there are some conceptual differences. The authors highlight that ROBIS focuses more on the take a chance of bias in reviews than AMSTAR does. They conclude that ROBIS is a more detailed tool than AMSTAR and may be more than appropriate for experienced reviewers.
Since this written report has been conducted AMSTAR 2 has been released, this update seems to take added many of the domains that were missing, notwithstanding, all-encompassing validation of AMSTAR 2 has not been conducted (withal) and no comparative study of AMSTAR 2 and ROBIS exists.
Addressing bias
Top tip one: Accost bias when designing the review. To address potential bias in the pattern of a study review authors should present a research question and PICO that is clear, structured, and objective. This thoughtful consideration of PICO will also let the reviewer to build a search strategy with reduced bias and helps to avoid missing potentially relevant studies. When determining the inclusion and exclusion criteria, authors should be articulate and transparent almost why these decisions were made and include this every bit a table in the systematic review protocol.
Meridian tip two: Address bias when locating studies. Sometimes information technology is appropriate to limit the search to a particular language or timeframe if the review is only interested in studies conducted in a certain geographical location or during a item time. However, if the review is described as a synthesis of global interventions then the bias of selecting merely a grouping of studies from a item language or time must be acknowledged in the limitation section of the review. Searches for relevant articles should exist conducted in multiple commercial and grayness literature sources, it is imperative to utilise as many relevant subject area databases equally possible, not just to ensure that relevant papers have been located, but as well to reduce the bias of selection (Dickersin et al., 1994). To annul the negative furnishings of publication bias, diverse grey literature sources should be included. At a minimum, researchers should search for dissertations and theses, and hand search relevant systematic reviews.
Top tip 3: Address bias when selecting studies. To counteract the bias associated with construct validity authors should be careful to minimise ambiguity in key concepts. This tin be achieved through careful planning of a companion transmission for the screener/s to employ, or via weekly squad meetings to discuss difficult concepts. Empirical evidence suggests that using two or more than independent reviewers throughout the screening and data collection process reduces reviewer bias, and so using a single reviewer should be avoided (Buscemi, Hartling, Vandermeer, Tjosvold, & Klassen, 2006). As well, Cochrane's minimal standards affirm that two people are mandatory for screening and extracting outcome information, and highly desirable for the extraction of all other study variables.
Superlative tip 4: Addressing bias when synthesising studies. Ane way to annul the biases associated with synthesising studies is to prospectively register the protocol. This will better the quality of the review, promote transparency and replicability, and avoid duplication of effort. Importantly, this publication of a protocol will ensure that post hoc analyses are minimal as both the Campbell Collaboration and Cochrane enquire that deviations from protocol be indicated in the final written report. To reduce bias when appraising the quality of studies, this assessment should be carried out by ii reviewers and consensus reached through word. Finally, in respect of conclusion bias, a sensitivity analysis volition assess potential biases inside a single or small number of SMDs that may exert asymmetric influence on the combined SMD. This is possible by determining how the information may be unlike if the underlying assumptions alter. This statistical analysis is oft carried out past identifying outliers and removing these studies from the analysis, past removing studies that are low in quality, or leaving studies out which exercise not fulfil some desired characteristic (Cooper, 2010). If the effectiveness or heterogeneity drastically changes due to a sensitivity analysis, this indicates that findings are not robust and should be interpreted with caution.
Blog post written past Ciara Keenan
References
Buscemi, Northward., Hartling, Fifty., Vandermeer, B., Tjosvold, L., & Klassen, T. P. (2006). Single information extraction generated more than errors than double data extraction in systematic reviews. Journal of clinical epidemiology, 59(vii), 697-703. doi:10.1016/j.jclinepi.2005.11.010
Cooper, H. (2010). Research synthesis and meta-analysis: A step-by-step approach (Vol. 2). Sage publications.
Dickersin, K., Scherer, R., & Lefebvre, C. (1994). Identifying relevant studies for systematic reviews. BMJ: British Medical Journal, 309(6964), 1286. Retrieved from ncbi.nlm.nih.gov
Rosenthal, R. (1979). The file drawer trouble and tolerance for zero results. Psychological Bulletin, 86(3), 638. doi:10.1037/0033-2909.86.3.638
Source: http://meta-evidence.co.uk/assessing-and-addressing-bias-in-systematic-reviews/
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