Dear Emily,

Ask Anna Westerlund, she is here on RG.

You can see the original here: http://www.stressforskning.su.se/forskning/forskningsomr%C3%A5den/biologisk-psykologi-och-behandling/ksq

Problem is, it's in Swedish. I am not sure if there has been a validated translation into English, I would directly contact the author to find out.

Thank You!

It has been used extensively in English.  On page 31 in Åkerstedt, T., & Gillberg, M., 1990.  ('Subjective and objective sleepiness in the active individual.' The International Journal of Neuroscience, 52(1-2), 29–37) it is described as:

1 Extremely alert

2

3 Alert

4

5 Neither alert nor sleepy

6

7 Sleepy – but no difficulty remaining awake

8

9 Extremely sleepy – fighting sleep

That isn't the KSQ, that is the KSS which, yes, is quite commonly used and is well validated in English.

2012, pp 209-210 Date: 24 Nov 2011

Karolinska Sleepiness Scale (KSS)

Azmeh Shahid M.D, Kate Wilkinson Ph.D, Shai Marcu M.D,

Colin M. Shapiro MBChB.

This scale measures the subjective level of sleepiness at a particular time during the day. On this scale subjects indicate which level best reflects the psycho-physical sate experienced in the last 10 min. The KSS is a measure of situational sleepiness. It is sensitive to fluctuations.

thank you!

Gillberg M, Kecklund G, Akerstedt T. Relations between performance

and subjective ratings of sleepiness during a night awake.

Sleep 1994;17:236-41.

http://link.springer.com/chapter/10.1007/978-1-4419-9893-4_47

http://www.sciencedirect.com/science/article/pii/S1388245706001428

How do you analyze data from such questionnaires? Treat it as continuous and check for differences in means (probably with a Mann-Whitney test), or treat it as interval and do a Fisher's exact test from a contingency table?

Parametric analyses of subjective data lead to too many false positive detections of differences between means.  Use medians and non-parametric analyses.