The Hawthorne effect refers to the phenomenon where individuals modify their behavior simply because they are aware that they are being observed or included in a study. This change in behavior can often obscure the true variable of interest being studied, as the participants may alter their actions to align with what they believe the researchers want to see. This effect highlights the importance of considering the impact of participant awareness and reactivity when conducting research.
Internal validity refers to the extent to which a study can confidently attribute the observed effects to the independent variable, rather than to confounding factors or chance. It ensures that the relationship between the independent and dependent variables is not due to any other extraneous variables. In other words, internal validity ensures that the observed effects are genuine and not a result of random or spurious relationships.
Meta-analysis is a method of integrating the findings of prior research studies using statistical procedures. It involves systematically collecting and analyzing data from multiple studies to draw conclusions about the overall effect or relationship between variables. By combining the results of individual studies, meta-analysis provides a more comprehensive and reliable estimate of the true effect size or relationship. It allows researchers to identify patterns, trends, and inconsistencies across studies, and can help to resolve conflicting or inconclusive findings. Meta-analysis is widely used in various fields of research to synthesize and summarize existing evidence.
Trend studies involve the investigation of samples from a general population over a period of time to observe and analyze changes in a specific phenomenon. This type of research aims to identify patterns, trends, and developments over time, providing valuable insights into the long-term effects of various factors. By studying a representative sample of the population, researchers can make informed predictions and recommendations based on the observed trends.
Assumptions are basic principles that are accepted as being true without proof or verification. They are beliefs or ideas that are taken for granted and form the basis of reasoning or decision-making. Assumptions are made based on logic or reason and are not necessarily proven to be true. They are often used as starting points in various fields such as science, philosophy, and mathematics, and serve as foundational principles for further exploration or analysis.
Maturation refers to the changes that occur naturally over time in the participants of a study, which can potentially influence the results. These changes could be due to physical, psychological, or social factors that are unrelated to the independent variable being studied. Maturation is considered a threat to internal validity because it can confound the results by causing changes in the dependent variable that are not actually caused by the independent variable. This can make it difficult to determine if the observed effects are truly a result of the manipulation or simply due to natural maturation processes.
Bracketing is not related to dealing with extraneous variables in quantitative research. Bracketing is a method used in qualitative research to acknowledge and minimize the researcher's biases and preconceived notions. It involves self-reflection and awareness of the researcher's own beliefs and perspectives. However, when it comes to dealing with extraneous variables in quantitative research, methods such as randomization, repeated measures, homogeneity, and blocking are commonly used to control and minimize their impact on the study's results.
Biophysiologic measures have better subjectivity compared to the other data collection methods listed. This is because biophysiologic measures involve collecting data directly from the body, such as heart rate, blood pressure, or brain activity. These measures provide objective and accurate information about the physiological state of the subject, without relying on subjective interpretation or self-reporting biases. In contrast, self-reports, observation, and questionnaires are more susceptible to subjective biases and may be influenced by individual perceptions, memory, or social desirability.
Carry-over effects refer to the influence of a previous condition or treatment on the subsequent condition or treatment in a study. In a repeated measures design, the same participants are exposed to multiple conditions or treatments, allowing for the examination of carry-over effects. This design is particularly useful when studying within-subject changes over time or when controlling for individual differences. Therefore, the correct answer is repeated measures design.
Beneficence is the correct answer because it refers to the ethical principle of promoting the well-being and welfare of study participants. It emphasizes the importance of maximizing benefits and minimizing potential harm to participants. This principle ensures that researchers prioritize the best interests of participants and take steps to protect their rights and well-being throughout the study. By upholding the principle of beneficence, researchers strive to create a balance between the potential benefits of the study and any potential risks or harm to participants.
This answer is true because a quasi-experimental research design involves manipulation of the independent variable, but does not have a control group or randomization. In a quasi-experimental design, the researcher cannot randomly assign participants to groups, so they have limited control over the variables. However, they can still manipulate the independent variable to observe its effects on the dependent variable. Without a control group or randomization, it is difficult to establish a cause-and-effect relationship between the variables.
