If the sample in a study is not representative of the larger population, what kind of bias does it impose?

A. More time efficient: Designing a rigorous study, obtaining large sample sizes, and performing complex statistical modeling can take months or years. Qualitative research can be time-consuming due to long interviews and transcription, but efficiency depends entirely on the study's scope, not just the method used.

B. Test hypotheses: A central feature of quantitative research is hypothesis testing. Researchers formulate specific, measurable predictions and use statistical methods to determine whether observed data support or reject those hypotheses. This approach aligns with deductive reasoning and theory verification.

C. It is more objective: Quantitative research emphasizes standardized measurement, controlled variables, and statistical analysis to reduce researcher bias. By using numerical data and replicable procedures, it aims to enhance reliability and objectivity in findings. Objectivity is strengthened through consistent data collection methods and validated instruments.

D. Data expressed in numbers, statistics: Quantitative research relies on numerical data that can be measured, compared, and analyzed statistically. Outcomes are often presented as percentages, means, correlations, or other statistical indicators. This numerical framework distinguishes quantitative research from qualitative approaches that focus on descriptive narratives.

A. Participants changed their behavior upon realizing the purpose of the study: This reflects the Hawthorne effect or performance bias, where awareness of being observed alters participant behavior. It involves changes in conduct due to study awareness rather than loss of participants over time. Attrition bias specifically relates to loss of participants, not behavioral modification.

B. Provider in a psychotherapy trial are aware of the investigators' hypotheses, and this knowledge unconsciously influence the way they rate participants' progress: This scenario represents observer bias or detection bias, where knowledge of study expectations influences outcome assessment. It affects the objectivity of measurements rather than participant retention.

C. Some participants leave in the middle of the study because of bad experiences, unwanted side effects, or inadequate incentives for participation, among other reasons: Attrition bias occurs when participants drop out of a study, especially if dropout rates differ between groups. Loss to follow-up can distort results if those who leave differ systematically from those who remain. This can threaten internal validity and lead to inaccurate estimates of treatment effects.

D. Participants enrolled from a specific age group or those with mild symptoms may result in findings that are not generalizable to the broader population: This describes selection bias or limited external validity. It affects how well study results apply to other populations but does not involve differential dropout during the study.