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response bias: when a researcher wants to investigate on young peoples' use of condom, some may intentionally state that they always practice safe sex while in reality they don't necessarily do that.

attention bias: a woman who doesn't breastfeed her baby on a regular basis in a pro-breastfeeding community may start breastfeeding more frequently due to the presence of an observer.

recall bias: sometimes, a participant cannot recall a particular piece of information regarding their disease that might be very important to a researcher.

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attention bias: it involves changes of behavior by participants because they know they are being observed. eg: reducing handshaking as observed during the COVID-19 pandemic, which immediately resumed after COVID-19 vaccination and a fall in the death rate

2. response bias: sometimes studies participants provide responses that are morally acceptable yet sometimes far from the truth. eg: being involved in morally judged sexual activities, casual sex with strangers without protection,..

3. lead time bias: many times the prevalence of diseases is underestimated especially for diseases that are only detected at late stages.

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to mitigate against these bias is to have a well defined research question and prepare before hands tools that will be necessary, plan to blind the study, and if possible use prospective study design

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Selection bias occurs when the study population is not representative of the target population.

Recall bias occurs when participants remember past events or exposures inaccurately, skewing results.

Observer bias occurs when researchers' expectations, beliefs, or knowledge about the study influence their observations, interpretations, or measurements.

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Recall bias

Ask about recent events rather than those from a long time ago, as recent events are remembered more accurately

using standardized questionnaires with clear, specific questions to reduce variability in how participants recall information

Selection bias

Broaden criteria to include people/individuals from different backgrounds, not just a single area or type and also using Random or Stratified Sampling

Observer bias

Having more than one observer can reduce bias, as differences in their observations can help identify and account for subjective influences.

Blinding: Researchers or participants (or both) do not know which group participants belong to. This reduces the influence of expectations on observations or measurements.

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Participant related: Recall bias where data is collected retrospectively and participants do not remember their activities well resulting in inaccurate responses.

Researcher related: Observer bias where the researcher is aware of the exposure and outcome being measured and tends to see what they want to see.

Instrument related bias: verification bias where there are different gold standards to an outcome resulting in inaccurate data.

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Recall bias- prospective collection of data and blinding so that no one is aware of what exposure or outcome is being measured.

Observer bias- blinding so that the researcher just collects all data as it is

Verification bias- use of a standardized tool for all participants in a trial

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1. Recall bias applies when the participant in a study is expected to recall information from previous experience because the information will be collected retrospectively. It's usually a problem when the participant is the one telling their own story as they have remember more routine or dominant aspects of the information required. For example, a cancer patient may remember the routine aspects of the treatments they received in the past and not more intimate details about how they felt or behaved.

2. Attention bias applies when the the participant changes their behaviour because they know that they are being observed. For example in a study that is observing the lifestyle patterns of people living with HIV, the study participants may pretend to be practising responsible lifestyles when in actual fact they live reckless lives.

3. Confounding Bias occurs when an outside factor is related to both the exposure and the outcome, distorting the perceived association between them. For example, if studying the link between exercise and heart disease, age might be a confounder because older individuals might exercise less and also have a higher risk of heart disease.

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Research biases and minimization strategy

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Research biases and minimization strategy

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1. selection bias happens when the participants involved are not true representative of the general population or the target population being studied.

MINIMIZATION STRATEGY

Use of random sampling techniques whereby every individual have the chance of being included in the study.

2. INFORMATION BIAS happens whe there are inaccuracies in the data collected about participants leading to misclassification of exposure and outcome status.

MINIMIZATION STRATEGY: employment of validated and standardized tools and protocols for data collection by the researcher

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Selection bias: Occurs when the participants included in a study are not representative of the target population, often due to how they are selected.

Information Bias: Results from inaccurate measurement or classification of study variables.

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Randomly assign participants to study groups (e.g., exposed vs. unexposed) to reduce selection bias.

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Bias in epidemological study

1. Recall bias

2. Observer bias

3. Expectation bias

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1. Recall bias can be countered by collecting data in real time also referred to as Prospective data collection

2. Attention bias can be addressed through randomization of the participants to groups

3. Confounding bias can be addressed through stratification of the samples

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1.Selection bias

2. Recall Bias

3. Lead time bias

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1. Recall Bias: Occurs when participants remember past events inaccurately.

2. Observer Bias: Occurs when researchers’ expectations influence how they interpret or record observations.

3. Attention Bias: Occurs when participants in a study change their behavior because they are aware they are being observed.

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Selection Bias: is a bias that arises when the participants chosen for a study are not representative of the target population. This can be minimised by random sampling and also through stratification including all the necessary features in a stratum.

Recall Bias: This is bias introduced when a participant has inaccurate memory or recollection of the exposure. This can be minimised by prospective data collection, blinding or using multiple data sources to confirm findings.

Lead time Bias: This is bias that occurs when early diagnosis of a disease makes it look like the patients are surviving longer. In this case early detection is confused with increased survival. It can be minimised through cohort studies where participants are followed over a long time to compare survival times.

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Recall Bias: Use blinding and prospective data collection to gather information in real-time rather than relying on participants' memories of past events.

Observer Bias: Blinding

Attention Bias: Observe participants in ways that don’t make them feel watched or aware of which part of their behavior is being studied.

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1. Selection bias can be minimised by randomly assigning participants to different study groups to ensure that each group is similar in all respects except for the exposure or intervention being studied

2. Publication bias can be minimised by subjecting the study to peer review and encouraging replication by other researchers to validate findings and ensure they are robust and reliable.

3. Information bias can be minimised by using standardised and validated data collection methods to ensure consistency and accuracy.

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1. Selection bias refers to a situation where the participants selected for a study are not representative of the target population.

2. Publication bias occurs when the studies with positive or significant results are more likely to be published than those with negative or null results, leading to a distorted view of the evidence.

3. Information bias:Often known as measurement bias, this arises when there are systematic errors in data collection.

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1. In a study that's recording individual GBV contribution, respondents may give morally acceptable responses just to avoid looking bad to the researcher.

2. Asking leading questions that require yes/no responses can introduce measurement bias in the outcome as well. especially if there is no space provided for respondents to elaborate more on their responses.

3. In a focus group discussion, asking sensitive questions especially of bad personal experiences (eg. asking young mother how many children they have had before reaching 18)can introduce measurement bias if no individual probing is scheduled.

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1, Response bais : it happens when participants give false response to please the researcher.

2, Selection bais : this occurs when the participants included of a study do not represent the targeted population.

3, Observer bais : happens when data interpretation is influence by his/her beliefs.

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1, Response bias: to minimize response bias, there should be anonymity and confidentiality.

2, Selection bias: random sampling should be used.

3, Observer bias: employ standardized data collection procedures.