The Morningness-Eveningness Questionnaire (MEQ) is a self-assessment created by Horne and Ostberg in the 1970s to measure preferences for morning versus evening in relation to human circadian rhythms. In creating the MEQ, the authors used a population of people ages 18-32 to ascertain validity, but, since its creation, it has been expanded to older populations. Each item measures an individual's ability to wake up at a certain time, how alert they feel when they wake, what time they sleep, and what times they feel most alert. The MEQ contains 19 multiple choice items and takes approximately 10-15 minutes to complete. The MEQ is used mostly by researchers to measure a research participant's morning-evening preference, and has been used as the "gold standard" measure of morningness preference of an individual.
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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.
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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 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.
Development and history
The creators of the MEQ, J. Horne and O. Ostberg, designed the MEQ to assess the theory of a two category chronotype, Morning or Evening.  The original MEQ was created by Oquist in 1970 in an attempt to distinguish between a morning and evening chronotype.  Ostberg later adapted Oquist's version for a study looking at the relationship between circadian rhythms, food intake, oral temperature, and the two chronotypes.  Ostberg later, once again, adapted the MEQ for a study looking at people's suitability for shift work in relation to their morning-evening chronotype.  The present MEQ is an adaptation of the Swedish version, with some items re-written to adjust for cultural differences between Sweden and England. 
In revising the questionnaire, Horne and Ostberg also revised the clarity, length, and scoring of the questionnaire and its items.  Each item is constructed such that the response to the item will add to a total score. The higher the score, the more "morningness" the chronotype is. The final item number of the MEQ is 19. Since its creation, the MEQ has been translated and validated in multiple languages, and has been widely regarded as the gold standard assessment of the morning-evening chronotype. 
The MEQ is widely considered the gold standard assessment for assessing morning-evening chronotypes.  As a result, other measures of circadian typology such as the Composite Scale of Morningness, Preference Scale, and Munich Chronotype Questionnaire are validated against the MEQ.  Because of its strong psychometric properties, the MEQ has been used in a multitude of sleep research studies to further the understanding of the relationship between circadian typology and other biological systems.
Furthermore, research indicates a relationship between circadian typology and risk of developing mental illnesses. A meta-analytic review of the relationship of circadian typology and a diagnosis of an Axis-I disorder in the DSM-IV report that those with an evening chronotype more often had Axis-I diagnoses, namely anxiety, depression, and substance use disorders.  Another review reported that a disturbance in circadian rhythms was strongly related to a diagnosis of bipolar disorder.  The existing relationship between chronotype preference and mental illness can aid clinicians in the assessment and diagnosis of various mental disorders. Furthermore, knowing that there is a connection between chronotype preference and mental illness can inform sleep-targeted treatment options to treat and prevent symptoms of a mental illness.
Use in other populations
The MEQ has been translated and validated in many different languages including French, German, Korean, Japanese, Italian, Spanish, Thai, and Turkish. 
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.
Hand scoring and general instructions
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The MEQ is a self-report, multiple choice survey. None of the items are reverse scores. Each item will add to the total score for the user. The recommended cut-offs created by Horne and Ostberg is as follows:
However, these cut-off values were calculated using participants between the ages 18-32. Participants who are older tend to be more of the morning preference. Research suggests an adjusted cut-off scores for users 40 and older. They are as follows:
CSV shell for sharing
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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).
|Click here for R code|
# Note: creating variable to reference data set meq <- read_csv("~/Desktop/395.299/MEQ/meq.csv") # Note: attach variables to variable names in data set so that you can call variables by their name attach(meq) # Note: finding score for MEQ meqScore = meq01+meq02+meq03+meq04+meq05+meq06+meq07+meq08+meq09+meq10+meq11+meq12+meq13+meq14+meq15+meq16+meq17+meq18+meq19 show(meqScore)
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|Click here for SAS code|
data MEQ_score; set main.meq; Total = SUM(of meq01 - meq19); run; * Note: Eric's score is 58, which is expected!; * Note: to get Cronbach's Alpha ; proc corr data= main.meq alpha; var meq01 - meq19; run; * Cronbach's Alpha is 0.809; * Note: correlation should be 1.0 between them all; proc reg data = MEQ_score; model total = meq01 - meq19; run; * Note: and it is, so this verifies that our model (straight adding) is correct;
OToPS usage history
(when was measure added to OTOPS Survey?
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(when was measure dropped from OTOPS survey?)
|Qualtrics scoring||Variable name of internally scored variable:
Notes on internal scoring:
- Is it piped?
- Is it POMP-ed?
- Any transformations needed to make it comparable to published benchmarks?
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