You discuss content validity and predictive validity. What about convergent and discriminant validity?
These types of construct validity would confirm that the measure correlates with similar concepts (convergent) and does not correlate with unrelated concepts (discriminant). I look forward to your update about what you would look at in relation to our self-esteem measure to determine convergent and discriminant validity.
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Discussion: Data Collection for Self-Esteem
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Discussion: Data Collection for Self-Esteem
Collecting data for self-esteem measures involves various steps, from defining the concept of self-esteem to selecting a data collection method, establishing a sampling plan, collecting the data, and analyzing the information. This will help develop self-esteem measure items to keep, test reliability, and validate the selected tool or instrument. Based on chapter 4 of Kline, (2005) book, it is important to be aware of potential biases, be ethical, and use various methods in sampling plan and data collection. As such, to approach data collection for the self-esteem measure, the first step is its concept. Is self-esteem how one feels in specific areas like physical or is it how people generally feel about themselves, global self-esteem. Understanding what self-esteem means for the measure is essential for effective data collection. This step also involves selecting a validated theoretical framework such as the Coopersmith Self-Esteem Inventory, which will help guide the development of self-esteem measure items.
Secondly, self-esteem measure item development. This process involves developing various mixed measure items for self-esteem to prevent bias. Based on research, all the created measure items should reflect the concept of self-esteem as defined in the first step. After developing the item, a literature review should be conducted in order to identify and understand the current measures or scales for self-esteem, as well as existing knowledge that relevant for successfully collecting the measure items to be used and effectively collecting the data, (Götz et al., 2023).Additionally, literature review also helps with understanding the theoretical foundation of self-esteem such as its various dimension, which help create measure items that align with selected framework. Götz et al., (2023) also emphasizes on the significance of consult or engage experts in self-esteem area like psychologists. Such experts can help review the created items and provide insights into their clarity and relevance, and any potential biases.
After having the measure items, the next step is pre-testing and improving them based on the results. This involves pilot testing, which according to Rajlic et al., (2019) it can be utilize in pre-testing the instrument, in this case, questioners to measure how a small group of participant perceive the self-esteem item. The pilot study involves using a small number of participants from the targeted population, observing and identify any potential issues with the item like clarity problems, administration, wording, and interpretation issues. Using multiple methods to collect the data will help increase findings validity. After collecting the data, one is required to use statistical methods to analyze the information. At this point, factor analysis can be used to assess the items and remove any compromised items, which do not support the validity and reliability of the scale. It is also possible to run a descriptive statistics for the items and use the output to delete, modify, or combine the measure items.
It is also necessary to test the instrument’s reliability measure. In this case, the test can be conducted through the Cronbach’s alpha test, in order to ascertain the internal consistency of the instrument. For instance, if the test result indicates 0.7 and above, this is acceptable or reliable. Aside from that, other tests like test-retest and split-half reliability can be given to examine the stability and consistency of the measure. Next is testing for the instrument’s validity, the most crucial process in the data collection procedure. Validity testing herein is an evaluation of how valid the different factors like the items, measure, and the scale are to effectively guarantee data accuracy. For example, content validity testing through surveys of participants or consultation with experts can be employed in order to ascertain that all the items reflect the self-esteem construct, (Fekih-Romdhane et al., 2023). One also needs to test how well the scale predicts behavior or outcome concerning self-esteem. Finally, there is finalization of the instrument and conducting an evaluation that is continuous. It is during this stage that data gathered is finalized after polishing it. However, self-esteem measures continue to be developed, and it may require regular re-testing in order to be up to date.
References
Fekih-Romdhane, F., Bitar, Z., Rogoza, R., Sarray El Dine, A., Malaeb, D., Rashid, T., … & Hallit, S. (2023). Validity and reliability of the Arabic version of the self-report single-item self-esteem scale (A-SISE).
BMC psychiatry,
23(1), 351.
Götz, F. M., Maertens, R., Loomba, S., & van der Linden, S. (2023). Let the algorithm speak: How to use neural networks for automatic item generation in psychological scale development.
Psychological Methods.
Kline, T. J. (2005). Psychological testing: A practical approach to design and evaluation. Sage publications.
Rajlic, G., Kwon, J. Y., Roded, K., & Hubley, A. M. (2019). Development of the global self-esteem measure: a pilot study.
Journal of Psychoeducational Assessment,
37(7), 863-873.
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