sjl | R Documentation |
sjl()
computes the relative or absolute social jetlag for standard,
micro, and shift versions of the Munich ChronoType Questionnaire (MCTQ).
sjl_rel()
is just a wrapper for sjl()
with abs = FALSE
.
sjl(msw, msf, abs = TRUE, method = "shorter") sjl_rel(msw, msf, method = "shorter")
msw |
An |
msf |
An |
abs |
(optional) a |
method |
(optional) a string indicating which method the function must
use to compute the social jetlag. See the Methods section to learn
more (default: |
Standard MCTQ functions were created following the guidelines in Roenneberg, Wirz-Justice, & Merrow (2003), Roenneberg, Allebrandt, Merrow, & Vetter (2012), and from The Worldwide Experimental Platform (theWeP, n.d.).
μMCTQ functions were created following the guidelines in Ghotbi et al. (2020), in addition to the guidelines used for the standard MCTQ.
MCTQ Shift functions were created following the guidelines in Juda, Vetter, & Roenneberg (2013), in addition to the guidelines used for the standard MCTQ.
See the References section to learn more.
The mctq
package works with a set of object classes specially created to
hold time values. These classes can be found in the
lubridate and hms
packages. Please refer to those package documentations to learn more about
them.
Some operations may produce an output with fractional time (e.g.,
"19538.3828571429s (~5.43 hours)"
, 01:15:44.505
). If you want, you
can round it with round_time()
.
Our recommendation is to avoid rounding, but, if you do, make sure that you only round your values after all computations are done. That way you avoid round-off errors.
If abs = TRUE
, a Duration
object corresponding
to the absolute social jetlag.
If abs = FALSE
, a Duration
object
corresponding to the relative social jetlag.
The output may also vary depending on the method
used.
Roenneberg, Allebrandt, Merrow, & Vetter (2012), Juda, Vetter, & Roenneberg
(2013), and The Worldwide Experimental Platform (n.d.) guidelines for sjl()
(SJL_rel and SJL) computation are as follows.
For MCTQ Shift, the computation below must be applied to each shift section of the questionnaire.
Due to time arithmetic issues, sjl()
does a slightly different
computation by default than those proposed by the authors mentioned above.
See vignette("sjl-computation", package = "mctq")
for more details.
If you are visualizing this documentation in plain text, you may have some trouble understanding the equations. You can see this documentation on the package website.
SJL_{rel} = MSF - MSW
SJL = | MSF - MSW |
Where:
SJL_{rel} = Relative social jetlag.
SJL = Absolute social jetlag.
MSW = Local time of mid-sleep on workdays.
MSF = Local time of mid-sleep on work-free days.
* W = Workdays; F = Work-free days.
SJL_{rel}^{M/E/N} = MSF^{M/E/N} - MSW^{M/E/N}
SJL^{M/E/N} = | MSF^{M/E/N} - MSW^{M/E/N} |
Where:
SJL_{rel}^{M/E/N} = Relative social jetlag in a particular shift.
SJL^{M/E/N} = Absolute social jetlag in a particular shift.
MSW^{M/E/N} = Local time of mid-sleep between two days in a particular shift.
MSF^{M/E/N} = Local time of mid-sleep between two free days after a particular shift.
* W = Workdays; F = Work-free days, M = Morning shift; E = Evening shift; N = Night shift.
There are different approaches to compute the social jetlag (SJL). By
default, sjl()
uses an approach that we call "the shorter interval
approach" ("shorter"
).
The topics below provide a simple explanation of each method supported by
sjl()
. To get a detail understating of this methods, see
vignette("sjl-computation", package = "mctq")
.
"difference"
By using method = "difference"
, sjl()
will do the exact computation
proposed by the MCTQ authors, i.e., SJL will be computed as the linear
difference between MSF and MSW (see the Guidelines section).
We do not recommend using this method, as it has many limitations.
"shorter"
This is the default method for sjl()
. It's based on the shorter
interval between MSW and MSF, solving most of the issues
relating to SJL computation.
"longer"
The "longer"
method uses the same logic of the "shorter"
method, but,
instead of using the shorter interval between MSW and MSF, it
uses the longer interval between the two, considering a two-day window.
This method may help in special contexts, like when dealing with shift-workers that have a greater than 12 hours distance between their mid-sleep hours.
Ghotbi, N., Pilz, L. K., Winnebeck, E. C., Vetter, C., Zerbini, G., Lenssen, D., Frighetto, G., Salamanca, M., Costa, R., Montagnese, S., & Roenneberg, T. (2020). The μMCTQ: an ultra-short version of the Munich ChronoType Questionnaire. Journal of Biological Rhythms, 35(1), 98-110. doi: 10.1177/0748730419886986
Jankowski K. S. (2017). Social jet lag: sleep-corrected formula. Chronobiology International, 34(4), 531-535. doi: 10.1080/07420528.2017.1299162
Juda, M., Vetter, C., & Roenneberg, T. (2013). The Munich ChronoType Questionnaire for shift-workers (MCTQ Shift). Journal of Biological Rhythms, 28(2), 130-140. doi: 10.1177/0748730412475041
Roenneberg T., Allebrandt K. V., Merrow M., & Vetter C. (2012). Social jetlag and obesity. Current Biology, 22(10), 939-43. doi: 10.1016/j.cub.2012.03.038
Roenneberg, T., Pilz, L. K., Zerbini, G., & Winnebeck, E. C. (2019). Chronotype and social jetlag: a (self-) critical review. Biology, 8(3), 54. doi: 10.3390/biology8030054
Roenneberg, T., Wirz-Justice, A., & Merrow, M. (2003). Life between clocks: daily temporal patterns of human chronotypes. Journal of Biological Rhythms, 18(1), 80-90. doi: 10.1177/0748730402239679
The Worldwide Experimental Platform (n.d.). MCTQ. https://www.thewep.org/documentations/mctq/
Other MCTQ functions:
fd()
,
gu()
,
le_week()
,
msf_sc()
,
msl()
,
napd()
,
sd24()
,
sd_overall()
,
sd_week()
,
sdu()
,
sjl_sc()
,
sjl_weighted()
,
so()
,
tbt()
## Scalar example msw <- hms::parse_hm("03:30") msf <- hms::parse_hm("05:00") sjl(msw, msf) #> [1] "5400s (~1.5 hours)" # Expected sjl(msw, msf, abs = FALSE) #> [1] "5400s (~1.5 hours)" # Expected sjl_rel(msw, msf) # Wrapper function #> [1] "5400s (~1.5 hours)" # Expected msw <- hms::parse_hm("04:30") msf <- hms::parse_hm("23:30") sjl(msw, msf) #> [1] "18000s (~5 hours)" # Expected sjl(msw, msf, abs = FALSE) #> [1] "18000s (~-5 hours)" # Expected sjl_rel(msw, msf) # Wrapper function #> [1] "18000s (~-5 hours)" # Expected msw <- hms::as_hms(NA) msf <- hms::parse_hm("05:15") sjl(msw, msf) #> [1] NA # Expected ## Vector example msw <- c(hms::parse_hm("02:05"), hms::parse_hm("04:05")) msf <- c(hms::parse_hm("23:05"), hms::parse_hm("04:05")) sjl(msw, msf) #> [1] "10800s (~3 hours)" "0s" # Expected sjl(msw, msf, abs = FALSE) #> [1] "-10800s (~-3 hours)" "0s" # Expected sjl_rel(msw, msf) # Wrapper function #> [1] "-10800s (~-3 hours)" "0s" # Expected ## Using different methods msw <- hms::parse_hm("19:15") msf <- hms::parse_hm("02:30") sjl(msw, msf, abs = FALSE, method = "difference") #> [1] "-60300s (~-16.75 hours)" # Expected sjl(msw, msf, abs = FALSE, method = "shorter") # Default method #> [1] "26100s (~7.25 hours)" # Expected sjl(msw, msf, abs = FALSE, method = "longer") #> [1] "-60300s (~-16.75 hours)" # Expected msw <- hms::parse_hm("02:45") msf <- hms::parse_hm("04:15") sjl(msw, msf, abs = FALSE, method = "difference") #> [1] "5400s (~1.5 hours)" # Expected sjl(msw, msf, abs = FALSE, method = "shorter") # Default method #> [1] "5400s (~1.5 hours)" # Expected sjl(msw, msf, abs = FALSE, method = "longer") #> [1] "-81000s (~-22.5 hours)" # Expected ## Converting the output to 'hms' msw <- hms::parse_hm("01:15") msf <- hms::parse_hm("03:25") sjl(msw, msf) #> [1] "7800s (~2.17 hours)" # Expected hms::as_hms(as.numeric(sjl(msw, msf))) #> 02:10:00 # Expected ## Rounding the output at the seconds level msw <- hms::parse_hms("04:19:33.1234") msf <- hms::parse_hms("02:55:05") sjl(msw, msf) #> [1] "5068.12339997292s (~1.41 hours)" # Expected round_time(sjl(msw, msf)) #> [1] "5068s (~1.41 hours)" # Expected
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