5-2 Discussion_ PSY 510

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Good afternoon, class, Psychological experiments frequently utilize self-reports for measurement, as they are generally more cost-efficient and produce larger data samples. The factor of self-report measurement in experimental designs can offer anonymity, which can promote more truthful responses. Despite this, accumulating evidence suggests that self-reports in psychological experiments have weak correlations with behavioral measures of consistent constructs (Dang et al., 2020). Self-reports are limited in their ability to index traits and symptoms (Diener et al., 2022). The majority of psychological researchers understand the impact of a question structure on the given response, meaning it is understood that “questions shape answers” (Diener et al., 2022). Self-reports and behavioral measures are the two most common factors in psychological experimental designs; however, these measures are frequently used interchangeably, which can amalgamate results across various measurement types. A meta-analysis on the correlation between self-reports and behavioral measurements found that the average correlation between self-reports and behavioral measurements of self-control, emotional intelligence, empathy, risk preference, and creativity was 0 to 0.20 (Dang et al., 2020). Indicative of a weak or nonexistent correlation, the data suggests that these two measurements are of the same construct. Self- reports are further limited in their ability to screen or prevent bias, as individuals are more likely to be biased in reporting on their own thoughts, behaviors, and experiences regardless of anonymity. Experimental design in research is referred to as the process in which participants are assigned to various conditions within an experiment. The key factor in experimental design is the control over the independent variable, which permits the analysis of the cause-and-effect relationship. Randomized experiments are the most effective experimental design, as they utilize randomization to assign participants to the conditions within an experiment (Rosnow & Rosenthal, 2014). Randomized experiments or randomized control trials (RCTs) are understood to be the superior standard for causal inference, as these trials empirically assess the validity and reliability of treatment upon a representative sample population (Rosnow & Rosenthal, 2014). There are both benefits and disadvantages to using randomized experiments. The randomization of participants into treatment and control groups allows for the minimization of selection bias, as it ensures the treatment and control groups produce comparable data for known and unknown predictive factors (Saldanha et al., 2022). Furthermore, randomized trials allow researchers to control extraneous variables, which promotes the inference of causality. This form of experimental design further allows for the research to be replicated or reproduced for verification and continued research. Randomized clinical trials are the “gold standard” for examining the effectiveness and causal inference of interventions or treatments. Despite the advantages of RCTs, they are limited in the ability to assess the harms of interventions or treatments, as they are frequently small or too short of duration; therefore, they are unable to assess long-term harm or uncommon harms to

be detected (Saldanha et al., 2022). Furthermore, RCTs are limited by their, generally, small sample populations, which limits the ability to detect differences among several measures of effectiveness (Saldanha et al., 2022). RCTs are also limited in generalizability, as they impose “ narrow eligibility criteria for participants, tightly controlled implementation of interventions and comparators, smaller sample size, shorter duration, and focus on short-term, surrogate, and/or composite outcomes” (Saldanha et al., 2022, Strengths and Limitations of RCTs ). As with all experimental designs and forms of measurement, there are benefits and limitations in their application. Although randomized clinical trials have various limitations, they provide the most effective way to measure causal inference within the clinical community, including the field of psychology. The ability of researchers to limit selection bias is an important factor to consider, particularly in psychological research. In matters concerning conscious factors, the use of self-reports allows researchers to generate rich, detailed data from participants. Furthermore, self-reports provide an easier, cost-efficient method of data collection compared to behavioral observation. Behavioral observation does not allow for subjective data on personal experiences to be reported. Behavioral measures record responses to uncommon stimuli in a specific and highly structured situation, whereas self-report measures ask participants to reflect on their behaviors across a variety of unstructured real-life situations (Dang et al., 2020). As such, the difference in the degree of measurement is greatly dependent upon what the researcher is seeking to understand and the intended or hypothesized outcome. In my opinion, the use of randomized control trials in psychological research is the most effective experimental design, as it ensures there is no bias in the selection process and allows for control of extraneous variables often present in matters of the psyche. Self-reports are a formidable form of measurement in research that seeks to understand individual inferences of thoughts or feelings; however, it would not be an effective measurement in distinguishing correlation with behavior, as bias is more likely to be present. The experimental design and form of measurement in psychological experiments is a matter that should be carefully considered, as it can negatively affect a study's validity and reliability. Thank you for reading! - Rachel M. References: Dang, J., King, K. M., & Inzlicht, M. (2020). Why Are Self-Report and Behavioral Measures Weakly Correlated? Trends in Cognitive Sciences , 24 (4), 267–269. https://doi.org/10.1016/j.tics.2020.01.007 Diener, E., Northcott, R., Zyphur, M. J., & West, S. G. (2022). Beyond Experiments. Perspectives on Psychological Science , 17 (4), 1101–1119. https://doi.org/10.1177/17456916211037670

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