This article shows a possible workaround to a common problem encountered when dealing with a standard Munich ChronoType Questionnaire (MCTQ) and \(\mu\)MCTQ data.
It’s a good idea to have the standard MCTQ questionnaire and the guidelines for the standard MCTQ variable computation open while reading this article/vignette. That way you can have a better understanding of the data objects we are going to deal with. You can download a copy of the MCTQ full standard version here. Click here to download a copy of the guidelines for the standard MCTQ variables.
Although the standard and micro versions of the MCTQ asks for
respondents to complete the workdays and work-free days sections, even
when they do not have a regular work schedule (wd = 0) or
have a 7 day/week work schedule (wd = 7), some of them may
still end skipping one of this parts of the questionnaire. In those
cases, sd_week(), sloss_week(),
le_week(), msf_sc(), sjl_rel(),
sjl(), sjl_sc_rel(), and sjl_sc()
will produce NA (Not Available) as output. That’s because
those computations combine workdays and work-free days variables.
For those special standard and micro MCTQ cases, where one section is
missing, a NA value is the correct output for the functions
mentioned above when wd (number of workdays per week) are
wd > 0 & wd < 7, but it may not be when
wd == 0 or wd == 7. While some researchers may
just invalidate these latter cases, we propose a different approach.
To illustrate this approach, consider the following.
If a respondent does not have a regular work
schedule (wd == 0), only answered the
work-free days section, and does not use an alarm clock
on their free days (i.e., alarm_f == FALSE), it
would be fair to assume that there’s no sleep correction
(sc) to be made, therefore, their chronotype
(msf_sc) must be equal to their midsleep on work-free days
(msf).
Following this same line of thought, we can also say that:
sd_week (average weekly sleep duration) must be equal
to sd_f (sleep duration on work-free days) since the
respondent does not have workdays.sloss_week (weekly sleep loss) must be equal to
0s since there’s no sleep debt.le_week (average weekly light exposure) must be equal
to le_f (light exposure on work-free days) since there are
no workdays.sjl_rel (relative social jet lag), sjl
(absolute social jet lag), sjl_sc_rel (Jankowski’s relative
sleep-corrected social jetlag), and sjl_sc (Jankowski’s
sleep-corrected social jetlag) must be equal to 0s since
there’s no discrepancy between social and biological time.Note that the chronotype computation follows a similar line of thought.
The opposite scenario, i.e., when the respondent works 7 days
per week (wd == 7) and only answered the
workdays section, can also have different outputs.
sloss_week(), msf_sc(),
sjl_rel(), sjl(), sjl_sc_rel(),
and sjl_sc() should still produce a NA as
output since there’s no way to know the real behavior of the
respondent’s sleep-wake cycle. But, according to this reasoning,
sd_week and le_week can have different
outputs.
sd_week (average weekly sleep duration) must be equal
to sd_w (sleep duration on workdays) since the respondent
does not have work-free days.le_week (average weekly light exposure) must be equal
to le_w (light exposure on work-free days) since the
respondent does not have work-free days.If you agree with this line of thought, we recommend creating dummy
variables to identify those two situations and then change the values as
mentioned. You can see this procedure in action with the data
wrangling algorithms made to produce the fictional
std_mctq dataset, provided by the mctq
package.
Please note that this workaround is not mentioned or endorsed by the MCTQ authors. If you use it, you must mention this reasoning in your methods section.