Biases in research - Sampling Bias

Cultural Bias - Qualitative

• YAVIS (young, affluent, verbal, intelligent, social)

  • University students

  • WEIRD (western, educated, industrialized, rich, democratic)

Influence selection and representation of participants leading to skewed sample that fails to be representative of a population

Preventing cultural bias

Reflexivity

Self-Selection Bias - Both

Volunteers tend to be more highly motivated than the average person or have specific reasons why they want to be in this particular study. Creating an unrepresentative sample where participants actively choose to be included, leading to a skewed and inaccurate reflection of the broader population. When the characteristics or behaviors of volunteers differ systematically from non-volunteers in a way that impacts the study's outcome, leading to skewed results that can be measured or compared

Preventing self-selection bias

• Use random sampling techniques to select participants. Ensure the sample is representative of the population.

• Offer incentives to encourage participation, attracting individuals who might not otherwise have volunteered.

• Conceal information (deception) about the study from participants or researchers, using blinding techniques to reduce the influence of expectations and biases on the outcome.

Ascertainment Bias - Both

When a particular group is left out from research. E.g. when looking at why relationships fall apart, often people in healthy relationships are not included in the study. Non-representative sample, where certain individuals or groups from the target population are systematically more or less likely to be included in the final results, leading to distorted measures and inaccurate conclusions. They involve non-random and systematic differences in who gets included in a study sample, leading to a sample that isn't representative of the target population