Chapter 13: Bias in Research Flashcards
What is a bias in research?
It is a form of systematic error in the research process that consistently shifts results in one direction.
When can bias occur in research?
It can occur in all phases of research: • Planning; • Data collection and intervention; • Data analysis and publication.
What is the consequence of bias in a study?
• A study loses validity according to the degree of bias.
Why is it essential to understand how bias might influence a study’s results and conclusions?
To understand how bias might influence a study’s results and conclusions is essential for evidence-based practice.
What are the biases that can occur in planning the research?
- Design bias
- Selection bias (Self-selection, convenient sample, non-response)
What are the biases that can occur in data collection/intervention in a study?
- measure bias
- interviewer bias
- recall bias
- compliance bias
- attrition bias
What are the biases that can occur in data analysis/publication in a study?
- confounding bias
- publication bias
What are the two types of study designs?
- observational
- experimental
What are the types of study designs that fall under observational studies?
- cross-sectional
- cohort (longitudinal)
- case-control (longitudinal)
- case-report series (longitudinal)
What are the types of study designs that fall under experimental studies?
- Randomized controlled trials (RCT)
What is design bias?
flawed study design
How to avoid design bias?
Select the adequate study design for the research question.
What type of study design should I use if I am interested in prevalence?
cross-sectional
What type of study design should I use if I am interested in incidence?
cohort
What type of study design should I use if I am interested in cause (in order of reliability)?
- cohort
- case-control
- cross sectional
What type of study design should I use if I am interested in prognosis?
cohort
What type of study design should I use if I am interested in treatment effect?
RCT
What is selection bias and what are the types?
Occurs during identification of study population, when some individuals are more likely to be selected for the study than others.
- Self-selection (volunteer participation)
- Convenient Sample
- Non-response
What is self-selection (volunteer participation) and convenient sample bias?
characteristics of those who volunteer (or are referred) to participate in a study are often different from the non-volunteers (not referred).
What is a non-response bias?
those who do not respondent/participate often have characteristics from those who respondent/participate.
different
How to avoid selection bias?
Randomly selection of the sample: each individual is chosen entirely by chance and each member of the study population has an equal chance of being included in the sample.
How to avoid non-response bias?
- Provide incentives for completing survey
- Explain why survey is important
- Keep survey short
What is measure bias? Give an example.
Occurs when the measurement tool is not sensitive enough to detect the exposure or outcome of interest.
Example: a study aims to assess vitamin D intake but the FFQ does not include all major sources of vitamin D.
How to avoid measure bias?
Using validated measurement tools that have a high sensitivity and specificity to minimize bias
What is interviewer bias? Give an example.
Occurs when there is a systematic difference between how information is asked, recorded, or interpreted. Interviewer may probe for certain risk factors.
Example:
A case-control study aims to verify if the consumption of dairy products increases the risk for respiratory allergy.
If the interviewer is aware that the respondent is one of the “cases” (individuals with respiratory allergy) he/she may give more emphasis on the risk factor investigated, by asking “Are you sure you rarely consume dairy products?”, than when interviewing one of the “controls” (individuals without respiratory allergy).
How to avoid interviewer-bias?
- Standardizing protocols for data collection
- Training interviewers
- Blinding the interviewers to the study hypothesis.
What is recall bias? Give an example
Occurs when measuring the outcome or the exposure requires individuals to remember past events.
Example: Diet assessment methods
• Food Frequency Questionnaire (FFQ)
• 24-hour recall
• Dietary history
How to avoid recall bias?
- Using a well-structured questionnaire that has been validated against direct measures.
- Giving the participants enough time to reflect before answering.
- Verifying the reported-data by using a reference criterion (e.g. medical records, data from another family member).
What is compliance bias? Give an example
Occurs when some subjects do not adhere to the planned treatment (experimental studies).
Example:
A RCT is investigating the efficacy of a low-carb diet on weight loss. However, some subjects allocated in the intervention group did not follow the diet prescribed by the researchers.
How to avoid compliance bias?
- Designing protocols that are simple and easy to follow and comply with.
- Identifying subjects who are unable or unmotivated to comply (with the intervention) during the enrollment process.
- Contacting subjects frequently to maintain interest and motivation.
What is attrition bias?
Occurs when subjects who leave the study (drop- outs) differ significantly from those that remain (common in cohorts and RCT).
How to avoid attrition bias?
- Using protocols to contact participants by email, post, telephone, etc.
- Providing incentives (monetary, gifts).
- Keeping the interviews short.
What is confounding bias?
Occurs when an estimated association between exposure and outcome is biased by a third factor associated with both exposure and outcome.
How to avoid confounding bias?
- Identified confounders can be controlled with study design (case control or randomization) and during data analysis (regression analysis).
- Unidentified confounders can only be controlled with randomization during participants selection and enrollment.
What is publication bias?
Occurs when researchers and research sponsors are unwilling to publish unfavorable results.
Positive results are more likely to be reported and accepted for publication in scientific journals, than negative results.
