Attitude Scale Assessment
For my communications class (COMM333) at Old Dominion University, we are assigned a task that requires us to have an in-depth analysis of two attitude scales of our choosing, and further elaborate on these scales as to what their benefits, weaknesses, and uses can provide to assessing attitudes.. I will be providing examples for each scale, as well as examples for why they can be either effectively efficient or not an accurate form of data collection. For this assignment, I will be covering the Likert scale and the Visually Oriented Self-Report scale, as these two scales are vastly different and can have viable uses within certain contexts. The Likert Scale is often associated as a 5 step rating system, typically used in a standard survey. For example, strongly disagree to the right and strongly agree to the left, with a neutral zone in the middle. As for the VOSR scale, which is typically found used by medical practitioners to assess a patients well being before treating, as a visual construct that relies on expressions to represent degrees of favorability or unfavorability.
The Likert scale can assess attitudes by using the 5 to 7 point scale, rather than yes or no questions, to interpret an average of assessed attitudes towards a specific topic (Sullivan, 2013). These scales are easily accessible/distributable, making it easier to assess an overall attitude from a group of people. Certain contexts this scale might be useful in include:
Class Settings
Workplace
Small Communities
Although the scale has its uses, it certainly contains flaws as well. These flaws stem from the likelihood of being misconstrued through the social desirability bias or the acquiescence bias (Bishop et al, 2015). This means that when someone is attempting to reflect their views within the survey, their answers may vary depending on the environment they are based in, or the certain context of when they are taking the survey that may impact the results they provide. For example, if a student were to take a class survey, their answers may be a reflection of how they perceive how others would respond to their answers. This scale data may also be interrupted through people not properly assessing or critically thinking about their responses, therefore they provide inaccurate data, just as we see within the elaboration likelihood model. This scale, like others, also lacks an open ended response, completely disregarding as to why some respondents may respond the way they are. My main criticism for this scale is that it may represent inaccurate data that is dependent on the context in which it is provided, such as a classroom setting in which students might not feel satisfied with the available responses they can provide given the lack of open-ended responses.
As for the Visually Oriented Self -Report scale, it is beneficial in the way that it can extend past a language barrier, essentially ridding the possibility of misinterpreting certain selective responses. This can be useful in the context of medical practice, where we see it often used with children or illiterate audiences. Due to the visual nature of this scale, participants may respond accordingly to their attitudes that they may be implying. For example, a child comes into the clinic and receives a VOSR from their practitioner, they can assess the images on the ‘Pain Scale’, to intuitively respond with how they are feeling, represented by the faces on the scale that range from “no hurt” to “most hurt”. A common issue for this scale is the given subjectiveness that the scale is built on. Respondents may interpret the images differently, or determine a specific injury as less or more painful than what is typically averaged for that given situation. For example, a man and a child have the same injury, and they receive a VOSR scale to respond to. Their responses may vary depending on how they assess their own pain within their own body, therefore ineffectively providing the data. In that lies my main gripe about this scale because when subjectiveness is a factor into responsive data, it can make for inaccurate assessments of said data. One study by Goyal et al (2022), shows that patients typically provide different responses depending on if the survey is provided by the practitioner or provided by self oriented means.
Throughout my research for this assignment, I have informed myself on the technical pros and cons of these scales, and how their data can be affected by things like the Theory of Reasoned Action or the Elaboration Likelihood Model. In the future, I might look back upon my research, and adjust my responses to accurately reflect my opinions with as little involvement from these theories and models as possible, in order to attain more accurate results.
References
Sullivan, G. M., & Artino, A. R. (2013, December). Analyzing and interpreting data from likert-type scales. Journal of graduate medical education. https://pmc.ncbi.nlm.nih.gov/articles/PMC3886444/
Bishop, P. A., & Herron, R. L. (2015, July 1). Use and misuse of the Likert item responses and other ordinal measures. International journal of exercise science. https://pmc.ncbi.nlm.nih.gov/articles/PMC4833473/
Goyal, A. K., Bakshi, J., Panda, N. K., Kapoor, R., Vir, D., Kumar, K., & Aneja, P. (2022, December 20). Accuracy of a self-reported measure in psychological assessment when the instrument is self-administered by the patient or when administrated by the clinician. Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India. https://pmc.ncbi.nlm.nih.gov/articles/PMC10235333/
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