Analyzing and interpreting data from likert type scales journal of graduate medical education

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Article citationsMore>>

Sullivan, G. M., & Artino Jr., H. R. (2013). Analyzing and Interpreting Data from Likert-Type Scales. The Journal of Graduate Medical Education, 5, 541-542.
https://doi.org/10.4300/JGME-5-4-18

has been cited by the following article:

  • TITLE: Empirical Evidence for a New Class of Personality Disorder: The Safety-Oriented Personality Style or Phobicentric Psychopathology (SOPS/PCP) and Impact on Personality Psychology

    AUTHORS: Patrick Bickersteth, Xinxin Zhang, Qi Guo

    KEYWORDS: Fear-Anxiety, Big 5, DSM, Emotion-Based, Contemporary Integrative Interpersonal Theory, Interpersonal Relatedness & Self-Definition

    JOURNAL NAME: Psychology, Vol.9 No.7, July 10, 2018

    ABSTRACT: This study is aimed at establishing that the Safety-Oriented Personality Style (SOPS) or Phobicentric Psychopathology (PCP) is an actual mental disorder representing a disproportionate, self-focused pattern of reacting to ordinary fear-anxiety situations. SOPS/PCP is most similar to Neuroticism in the widely accepted Big 5 model. The presentation of personality within a dimensional structure is in contradistinction to that of the lately criticized category-based Diagnostic and Statistical Manual (DSM). Nonetheless contrasting both Big 5 and DSM, a neuro-biological theory provided the SOPS/PCP construct with etiological capability to empirically explain progress of the condition from normal to dysfunctional functioning, thus linking it with day-to-day emotional life. From a sample of 406 adults, who participated in confirming respectively that SOPS/PCP is present outside the clinical setting and is a real-world empirical condition, 100 individuals were randomly selected to examine the reliability and validity of the SOPS/PCP Individual Questionnaire (SOPSIQ). The results confirmed SOPS/PCP is an actual mental disorder, which is absent in some people and supported all the hypotheses in relation to the research objectives. In rivalry with three prominent formulations of personality, DSM, Big 5 and Interpersonal Relatedness & Self-Definition (IR), which is related to Contemporary Integrative Interpersonal Theory (CIIT), that of SOPS/PCP is presented as aspiring to be a more accurate elucidation of personality. Implications discussed also include suggesting DSM’s new categorical-dimensional platform is fatally flawed and questioning the investigative legitimacy of both the Big 5 and IR/CIIT. Among other ideas, it is suggested that SOPS/PCP might provide Big 5 with a presumptive etiological base; and that the behavior-to-theory approach of SOPS/PCP would be more research-friendly than the theory-to-behavior orientation prevalent in personality research. By describing personality functioning and its supporting theory as emotion-rooted this study recommends such a perspective makes it more practical to reliably define, track and eventually treat personality disorders.

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How do you analyze Likert scale data?

A Likert scale is composed of a series of four or more Likert-type items that represent similar questions combined into a single composite score/variable. Likert scale data can be analyzed as interval data, i.e. the mean is the best measure of central tendency. use means and standard deviations to describe the scale.

How do you interpret Likert scale data for correlation analysis?

There is no problem in using the likert scale but i can recommend you to use the 5 points scaled as 1=strongly disagree, 2=agree; 3=not sure; 4=disagree; and 5=strongly disagree. and in using this make sure that you provide the mean ranges of the scales and their interpretations.

How do you read a 5 point Likert scale?

How to Interpret a 5 Point Likert Scale Questionnaire. Assign each response a point value, from 1 to 5, based on the number of responses. Common values for the options start with “strongly disagree” at 1 point and “strongly agree” at 5.

What statistical test do you use for Likert scale?

Data from Likert scales are sometimes reduced to the nominal level by combining all agree and disagree responses into two categories of "accept" and "reject". The chi-square, Cochran Q, or McNemar test are common statistical procedures used after this transformation.