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A comprehensive overview of the structure and evaluation of research articles, covering key elements such as the imrad format, the introduction, methods, results, and discussion sections, as well as the importance of statistical significance, reliability, validity, and trustworthiness in both quantitative and qualitative research. It also discusses the challenges of reading research articles, the process of critiquing research, and the concepts of inference, bias, and generalizability. Particularly useful for students and researchers who need to understand the fundamental principles of research article analysis and evaluation, as it offers insights into the various components and considerations that contribute to the overall quality and credibility of a research study.
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"blind" - reviewers are not told researchers' names and authors are not told reviewers' name IMRAD format - Content of Research Journal Articles Introduction method results and discussion abstract - brief description of the study placed at the beginning of the article the introduction - introduces the reader to the research problem and context descries the following: central phenomena, concepts and variables, the study purpose and research question/hypothesis, a review of the related literature, theoretical or conceptual framework, significance of the and need for the study methods section - in a quant. study it describes: the research design, sampling plan, methods of measuring variables and collecting data, study procedures, including procedures to protect human rights
in qual study it describes: research tradition, sampling approach and description of study participants, setting and context, data collection approaches, study procedures and analytic strategies results section - presents findings level of statistical significance qualitative results section - often provide more information about the study setting and context quantitative results section - the names of statistical test used names the value of the calculated statistic states the significance statistical tests - test quant hypothesis and asess the probability that the results are accurate; helps to prove if a relationship between two things is real statistically significance - means the findings are probably true and replicable with a new sample raw data - directly from the participants; usually in qual studies the discussion section - what the results mean; offer an interpretation of the results; clinical and research implications; study limitations why research articles are hard to read - compactness, jargon, objectivity (impersonal), statistical information is hard to read
credibility - the extent that the research methods inspire confidence that the results and interpretations are truthful and accurate triangulation - a way of improving credibility in a qual study; it is the use of multiple sources or referents to draw conclusions about what constitutes the truth bias - threatens a study's validity and trustworthiness; an influence that results in an error in an inference or estimate; can be a result of participants lack of candor or desire to please, researchers's preconceptions or faulty methods of collecting data research control - involves holding constant influences on the outcome variable (confounding variable) so that the true relationship between the independent and outcome variables can be understood confounding variables - variables that might try and cloud the relationship between the variables that are of central interest two key ways of reducing bias (in quant studies) - randomness and blinding randomness - each person as an equal chance of being selected; therefore there are no systematic biases blinding - also called masking; prevents bias from stemming from people's awareness, done by concealing information from participants, data collectors, care providers or data analysts to enhance objectivity
how to qual studies protect against bias? - by relying on reflexivity (the process of reflecting critically on the self, and of analyzing and making note of personal values that could affect data collection and interpretation generalizability - the criterion used in quantititative studies to asses the extent to which the findings can be applied to other groups and settings how to enhance generalizability - researchers must design studies strong in reliability and validity transferability - the extent to which qualitative findings can be transferred to other settings as another aspect of trustworthiness; an important mechanism for promoting transferability is the amount of rich descriptive information qual researchers provide about the contexts of their studies critiques to inform EPB focus on whether evidence is - accurate, believable, and clinically relevant inferences should be - reliable, valid (quant) and trustworthy (qual) dimensions of trustworthiness - credibility conformability dependability transferability authenticity