# OToPS/Measures/Creative Adjective Checklist

The Open Teaching of Psychological Science (OToPs) template is a shell that we use for building new Wikiversity instrument pages on Wikiversity.

## Overview

The Gough Creative Personality Scale for the Adjective Checklist (CPS) is a checklist that measures a person’s perception of their creative abilities. It is part of Harrison G. Gough’s Adjective Checklist (ACL), and was created due to higher correlations with measures originally found in the ACL. It is a 30 item checklist that can either be self-reported or administered by a clinician. The scale contains a total of 30 adjectives that the respondent checks if they believe that adjective describes them. 18 of the adjectives are indicative and 12 are contraindicative. This allows the raw scores to range from -12 to +18. It is intended for adolescents and adults, but has modified versions for children. It was developed by Harrison G. Gough at the Institute of Personality Assessment and Research in Berkeley in 1979. The CPS only takes a few minutes to complete, while the full ACL only takes 10 to 15 minutes. It has been translated into 21 languages and claims to be valid across cultures.. It is generally administered in conjunction with the ACL, but can be given individually. It is used in a variety of settings including clinical evaluation settings, clinical research, marketing research, and in businesses where it is advantageous to identify creative abilities in people.

## Psychometrics
#### Reliability

Not all of the different types of reliability apply to the way that questionnaires are typically used. Internal consistency (whether all of the items measure the same construct) is not usually reported in studies of questionnaires; nor is inter-rater reliability (which would measure how similar peoples' responses were if the interviews were repeated again, or different raters listened to the same interview). Therefore, make adjustments as needed.
Reliability refers to whether the scores are reproducible. Unless otherwise specified, the reliability scores and values come from studies done with a United States population sample. Here is the rubric for evaluating the reliability of scores on a measure for the purpose of evidence based assessment.
Evaluation for norms and reliability for the XXX (table from Youngstrom et al., extending Hunsley & Mash, 2008; *indicates new construct or category) :
| Criterion | Rating (adequate, good, excellent, too good*) | Explanation with references |
| Norms | Adequate | Multiple convenience samples and research studies, including both clinical and nonclinical samples[citation needed] |
| Internal consistency (Cronbach’s alpha, split half, etc.) | Excellent; too good for some contexts | Alphas routinely over .94 for both scales, suggesting that scales could be shortened for many uses[citation needed] |
| Interrater reliability | Not applicable | Designed originally as a self-report scale; parent and youth report correlate about the same as cross-informant scores correlate in general |
| Test-retest reliability (stability | Good | r = .73 over 15 weeks. Evaluated in initial studies, with data also show high stability in clinical trials[citation needed] |
| Repeatability | Not published | No published studies formally checking repeatability |

#### Validity

Validity describes the evidence that an assessment tool measures what it was supposed to measure. There are many different ways of checking validity. For screening measures, diagnostic accuracy and w:discriminative validity are probably the most useful ways of looking at validity. Unless otherwise specified, the validity scores and values come from studies done with a United States population sample. Here is a rubric for describing validity of test scores in the context of evidence-based assessment.
Evaluation of validity and utility for the XXX (table from Youngstrom et al., unpublished, extended from Hunsley & Mash, 2008; *indicates new construct or category) :
| Criterion | Rating (adequate, good, excellent, too good*) | Explanation with references |
| Content validity | Excellent | Covers both DSM diagnostic symptoms and a range of associated features |
| Contruct validity (e.g., predictive, concurrent, convergent, and discriminant validity) | Excellent | Shows Convergent validity with other symptom scales, longitudinal prediction of development of mood disorders, criterion validity via metabolic markers and associations with family history of mood disorder. Factor structure complicated; the inclusion of “biphasic” or “mixed” mood items creates a lot of cross-loading |
| Discriminative validity | Excellent | Multiple studies show that GBI scores discriminate cases with unipolar and bipolar mood disorders from other clinical disorders effect sizes are among the largest of existing scales |
| Validity generalization | Good | Used both as self-report and caregiver report; used in college student as well as outpatient and inpatient clinical samples; translated into multiple languages with good reliability |
| Treatment sensitivity | Good | Multiple studies show sensitivity to treatment effects comparable to using interviews by trained raters, including placebo-controlled, masked assignment trials Short forms appear to retain sensitivity to treatment effects while substantially reducing burden |
| Clinical utility | Good | Free (public domain), strong psychometrics, extensive research base. Biggest concerns are length and reading level. Short forms have less research, but are appealing based on reduced burden and promising data |

## Limitations

One of the major limitations about the scale is that there is little research done on reliability and validity of this specific scale, since the majority of the research is done on the complete ACL. Additionally, studies have shown it may need to be altered when used outside of the United States.

## Development and history
### Development of Creativity Scales

The scale was developed to fulfill a research and societal need to identify creative ability and potential within people. Creativity was valued in human endeavors and decision-making; however, there was little research on which factors and traits were most related to creativity. Prior studies had found there was little to no correlation between intellectual functioning and creativity. Research had found that artistic temperament and aesthetic dispositions were related to creativity, which led to the development of the Barron-Welsh Art Scale and Revised Art Scale. Personality traits and dispositions had been examined in regards to creativity using standard personality inventories and special scales and questionnaires. However, the topic of self-concept had not been researched yet. Therefore, Gough & Heilbrun created The Adjective Check List (ACL) in 1965 to assess appraising views of oneself. The ACL is a personality measure for adolescents and adults. It consists of 300 adjectives that describe a person's attributes. There are many subscales, one of which is the Creative Personality Scale.

### Development of the CPS

Creativity had been looked at previously with the ACL. However, reliable and accurate scales had not been made. During the 1950's, six researchers developed their own creative ACL scales. In individual studies, the scales held high levels of validity. However, during the late 1950's a researcher used the 6 scales in a study and found very low correlations with the scales and criterion ratings of creativity. Due to the weak findings, there was a need to develop a stronger measure that was based on larger samples and a broader range of criteria.

## Impact

* What was the impact of this assessment? How did it affect assessment in psychiatry, psychology and health care professionals?
* What can the assessment be used for in clinical settings? Can it be used to measure symptoms longitudinally? Developmentally?

## Use in other populations

There is little information on the use of specifically the CPS. However, the ACL has been used since 1952 by many professionals and is one of the 100 most used and cited psychological tests. The ACL has been translated into 21 languages which include:
* Cantonese
* Danish
* Dutch
* English (UK)
* Finnish
* French
* French (Canada)
* German
* Hungarian
* Italian
* Japanese
* Mandarin
* Polish
* Portuguese
* Portuguese (br)
* Spanish
* Spanish (Argentina)
* Spanish (United States)
* Swedish
* Thai - 330 items
* Vietnamese

## Scoring instructions and syntax

We have syntax in three major languages: R, SPSS, and SAS. All variable names are the same across all three, and all match the CSV shell that we provide as well as the Qualtrics export.

### CSV shell for sharing

Here is a shell data file that you could use in your own research. The variable names in the shell corresponds with the scoring code in the code for all three statistical programs.
Note that our CSV includes several demographic variables, which follow current conventions in most developmental and clinical psychology journals. You may want to modify them, depending on where you are working. Also pay attention to the possibility of "deductive identification" -- if we ask personal information in enough detail, then it may be possible to figure out the identity of a participant based on a combination of variables.
When different research projects and groups use the same variable names and syntax, it makes it easier to share the data and work together on integrative data analyses or "mega" analyses (which are different and better than meta-analysis in that they are combining the raw data, versus working with summary descriptive statistics).