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Critical appraisal skills are essential to informed decision-making
Whenever a trial is conducted, there are three possible explanations for the results: a) findings are correct (truth), b) represents random variation (chance) or c) they are influenced by systematic error (bias). Random error is deviation from the ‘truth’ and happens due to play of chance (e.g. tria...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3168054/ https://www.ncbi.nlm.nih.gov/pubmed/21938133 http://dx.doi.org/10.4103/2589-0557.62770 |
Sumario: | Whenever a trial is conducted, there are three possible explanations for the results: a) findings are correct (truth), b) represents random variation (chance) or c) they are influenced by systematic error (bias). Random error is deviation from the ‘truth’ and happens due to play of chance (e.g. trials with small sample, etc.). Systematic distortion of the estimated intervention effect away from the ‘truth’ can also be caused by inadequacies in the design, conduct or analysis of a trial. Several studies have shown that bias can obscure up to 60% of the real effect of a healthcare intervention. A mounting body of empirical evidence shows that ‘biased results from poorly designed and reported trials can mislead decision making in healthcare at all levels’. Poorly conducted and reported RCTs seriously compromise the integrity of the research process especially when biased results receive false credibility. Therefore, critical appraisal of the quality of clinical research is central to informed decision-making in healthcare. Critical appraisal is the process of carefully and systematically examining research evidence to judge its trustworthiness, its value and relevance in a particular context. It allows clinicians to use research evidence reliably and efficiently. Critical appraisal is intended to enhance the healthcare professional's skill to determine whether the research evidence is true (free of bias) and relevant to their patients. |
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