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Mapa Mental por shirley.ha, atualizado more than 1 year ago
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Criado por shirley.ha
mais de 11 anos atrás
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Week 6 Bias LO
- •Explain the meaning of bias and
confounding and provide examples
demonstrating these concepts in the
context of health research.
- •Describe the characteristics of the following quantitative
study designs systematic reviews, randomised controlled
trials (RCTs), cohort studies, case control studies,
cross-sectional and case studies.
- •Understand the rationale behind the
hierarchy of research evidence using
quantitative research methodologies and
how it relates to evaluating health claims
from an evidence-based perspective.
- •Utilise the hierarchy of evidence to inform
evidence-based practice (EBP).
- Quantitative
- based on the premise that variables of interest
can be observed and counted
- descriptive
- correlational
- causal analyses
- experimental
- Inferential statistics
- frequently used to examine relationships between variables
- to generalise what is found in the study sample to
the population as a whole.
- frequently used to examine relationships between variables
- statistical section, which may show cause and effect
relationships.
- Subject to bias due to large population size
- To reduce Bias
- ensure samples are as representative as possible
- i.e specific to the study so for breast
cancer research, use people from
hospitals
- i.e specific to the study so for breast
cancer research, use people from
hospitals
- ensuring strict, explicit criteria
- for what constitutes a case and an exposure
- selecting cases of arthritis, explicit guidelines must be followed
when diagnosing participants with arthritis
- Know participants disease status
- prevents the researcher consciously or unconsciously
treating the participants differently
- prevents collecting data differently depending on the group to which the
patient belongs.
- prevents the researcher consciously or unconsciously
treating the participants differently
- Know participants disease status
- for what constitutes a case and an exposure
- ensuring standardised data collection forms and procedures,
and these are used uniformly across all participants
- aim for high participation rates
- participation or response rates are important things to look for
- If the big sample doesn't all participate, it increases
risk of having ppl with different characteristics from
those who don't.
- participation or response rates are important things to look for
- ensure samples are as representative as possible
- To reduce Bias
- based on the premise that variables of interest
can be observed and counted
- Confounding
- variable or factor that confuses the relationship being examined
- Quantitaive
- examine the relationship between an exposure and an outcome
(such as disease).
- when another exposure exists that is associated with the disease or outcome and the
exposure being studied.
- Confounding factor maternal age for Down Syndrome and birth order exposure
- examine the relationship between an exposure and an outcome
(such as disease).
- variable or factor that confuses the relationship being examined
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