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Chapter Nine. Understanding Bias. The Nature of Bias. Research bias may be thought of as a preference or predisposition to favour a particular outcome thus indicating a systematic distortion of research conclusions Typically the distortions are inadvertent, but they can also be intentional
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Chapter Nine Understanding Bias
The Nature of Bias • Research bias may be thought of as a preference or predisposition to favour a particular outcome thus indicating a systematic distortion of research conclusions • Typically the distortions are inadvertent, but they can also be intentional • If bias is not addressed ina study, the reliability of findings is considered suspect
Bias in Quantitative Research • Bias implies there is an unknown truth waiting to be described • In quantitative designs the approach suggests that the researcher “knows” the truth & simply wants to confirm his/her knowledge • eg. Questionnaire responses reflect the researcher’s previous knowledge, values, etc.
Bias in Qualitative Research • In qualitative research the researcher is an integral part of the research design & the participant’s world • To minimize bias in qualitative designs the researcher incorporates it into the design by: • bracketing • audit trail • selecting unfamiliar participants • selecting a topic that is not too close to the researcher on a personal level
Triple Biases: Nursing, Science, & Culture... • We take our nursing predispositions with us to our research projects • We tend to seek corroboration of our preconceptions, helps to make sense of a complicated world, reaffirms our pet theories • Science itself potentially blinds researchers because of the expectations of findings, the belief in certain theories. Like culture, science produces blinders
Sexism: A Form of Bias • Sexism is discrimination on the basis of gender • RCT’s used mainly by medicine have made women victims of this approach, studying women mainly as objects, ignoring their needs & experiences
Types of Sexism in Research • Androcentricity (male perspective)-based on individualism, materialism, & competitiveness - in contrast to the views of women, ethnic groups, & the poor who focus on family concerns rather than themselves • Overgeneralization & overspecificity • Gender Insensitivity • Familism - treating family as unit of analysis, rather than the individual
Sources of Bias... • need to design studies to systematically test alternative explanations • researcher affect refers to the bias that results from a researcher having fallen in love with some pet theory or explanation
Bias: Selection of Problem • Some things judged more important by funding agencies, one’s discipline peers • bias is toward the conventional, standard projects & the selection of variables conventionally considered important & the exclusion of those conventionally considered unimportant • probably still a bias toward quantitative approaches
Bias: Sampling Design • results may be distorted by choosing to study sub-populations with known slants • attitudes toward abortion in an urban community with a free standing abortion clinic vs rural communities • bias is problematic in studies where the sample self-selects to participate
Bias: Funding • SSHRC main funding for social science research • special funding available in “hot” areas • traditional areas better funding • NSERC and CIHR are better funded • research in a social context
Bias: Data Collection • Experimenter effect: reference is to the influence of experimenter preferences and expectations • Robert Rosenthal: the “smart rats” study. • Clever Hans • Expectancy • Demand characteristics
Bias: Data Analysis • Coding Errors • Random Error • Systematic Error • Data Massaging • Hunting
Bias: Reporting of Findings • T.D. Sterling, 1959, 1995. Notes the problem of journals publishing only “statistically significant” findings.
Bias: Funding • Possibility of funding agencies to determine what is important to know; have “they” got it right? • Problems of emerging disciplines in competing with established ones
Advocacy Versus Pure Research • P. 313. • Mainstream research supportive of established interests in society. Is there a legitimate place to support the interests of minorities, women, people with disabilities, the working poor, the homeless…
Rules for Minimizing Bias • Education • Avoid Sexism • Advocacy or Explanation? • Descriptive Accuracy • Let disconfirmation be your guide • Policy Recommendations are Value Based • Be skeptical of Research Findings
Rules Cont • Read Literature Cautiously, Skeptically • Distinguish Advocacy from Pure Research • Use Theory to Generate Testable Hypotheses • Be Sensitive to your own outcome preferences • Do not disclose hypotheses to subjects or assistants
Rules Cont. • Be Accepting of All Responses • Specify Data Analysis Procedures in Advance • Check for Random & Systematic Errors • Report any Data Massaging