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Frontiers in Public Health 01 frontiersin.org
Kairos study protocol: a
multidisciplinary approach to the
study of school timing and its
eects on health, well-being and
students’ performance
DanielGabaldón-Estevan
1
*, DiegoCarmona-Talavera
2,
BelénCatalán-Gregori
3, ElenaMañas-García
1,
VanessaMartin-Carbonell
4, LucíaMonfort
5,
ElviraMartinez-Besteiro
6, MònicaGonzález-Carrasco
7,
MaríaJesúsHernández-Jiménez
8, KadriTäht
9, MartaTalavera
10,
AnaAncheta-Arrabal
11, GuillermoSáez
2,12, NuriaEstany
2,
GonzaloPin-Arboledas
13 and CatiaReis
14,15,16 on behalf of the
Research Group on School Health and Well-being (GISBE)
1 Department of Sociology and Social Anthropology, University of Valencia, Valencia, Spain, 2 Service of
Clinical Analysis, University Hospital Dr. Peset, Valencia, Spain, 3 Department of Education, Valencian
International University, Valencia, Spain, 4 Department of Pediatrics, Dr. Peset University Hospital,
Valencia, Spain, 5 Department of Pediatrics, Clinical University Hospital, Valencia, Spain, 6 Department
of Personality, Assessment and Psychological Treatments, University of Valencia, Valencia, Spain,
7 Research Institute on Quality of Life, University of Girona, Girona, Spain, 8 Faculty of Health Sciences,
Valencian International University, Valencia, Spain, 9 Institute of International Social Studies, School of
Governance, Law and Society, Tallinn University, Tallinn, Estonia, 10 Department of Experimental and
Social Sciences Teaching, University of Valencia, Valencia, Spain, 11 Department of Comparative
Education and History of Education, University of Valencia, Valencia, Spain, 12 Department of
Biochemistry and Molecular Biology, Faculty of Medicine and Dentistry, University of Valencia,
Valencia, Spain, 13 Grupo de Sueño y Cronobiologia de la Asociación Española de Pediatría, Valencia,
Spain, 14 CRC-W- Faculdade de Ciências Humanas, Universidade Católica Portuguesa, Lisbon,
Portugal, 15 Instituto de Medicina Molecular João Lobo Antunes, IMM, Lisboa, Lisbon, Portugal,
16 ISAMB - Faculdade de Medicina Universidade de Lisboa, Lisbon, Portugal
Recent evidence from chronobiology, chssronomedicine and chronopsychology
shows that the organisation of social time (e.g., school schedules) generally
does not respect biological time. This raises concerns about the impact of the
constant mismatch between students’ social and internal body clocks on their
health, well-being and academic performance. The present paper describes a
protocol used to investigate the problem of (de) synchronisation of biological
times (chronotypes) in childhood and youth in relation to school times. It studies
the eects of student chronotype vs. school schedule matches/mismatches
on health behaviours (e.g., how many hours students sleep, when they sleep,
eat, do physical activity, spend time outdoors in daylight) and learning (verbal
expression, spatial structuring, operations) and whether alert-fatigue levels
mediate this eect alignments/misalignments on learning (verbal expression,
spatial structuring, operations) and their mediation by alert-fatigue levels. The
novelty of our protocol lies in its multidisciplinary and mixed methodology
approach to a relevant and complex issue. It draws on up-to-date knowledge
from the areas of biology, medicine, psychology, pedagogy and sociology. The
methods employed include a varied repertoire of techniques from hormonal
analysis (cortisol and melatonin), continuous activity and light monitoring, self-
registration of food intake, sleep timings, exercise and exposure to screens,
alongside with systematic application of cognitive performance tests (e.g.,
OPEN ACCESS
EDITED BY
Kevin Dadaczynski,
Fulda University of Applied Sciences,
Germany
REVIEWED BY
Guadalupe Rodriguez Ferrante,
University of Washington, UnitedStates
Anat Lan,
Academic College Tel Aviv-Yao, Israel
*CORRESPONDENCE
Daniel Gabaldón-Estevan
Daniel.Gabaldon@uv.es
RECEIVED 09 November 2023
ACCEPTED 26 February 2024
PUBLISHED 08 March 2024
CITATION
Gabaldón-Estevan D, Carmona-Talavera D,
Catalán-Gregori B, Mañas-García E,
Martin-Carbonell V, Monfort L,
Martinez-Besteiro E, González-Carrasco M,
Hernández-Jiménez MJ, Täht K, Talavera M,
Ancheta-Arrabal A, Sáez G, Estany N,
Pin-Arboledas G and Reis C (2024) Kairos
study protocol: a multidisciplinary approach
to the study of school timing and its eects
on health, well-being and students’
performance.
Front. Public Health 12:1336028.
doi: 10.3389/fpubh.2024.1336028
COPYRIGHT
© 2024 Gabaldón-Estevan, Carmona-
Talavera, Catalán-Gregori, Mañas-García,
Martin-Carbonell, Monfort, Martinez-Besteiro,
González-Carrasco, Hernández-Jiménez,
Täht, Talavera, Ancheta-Arrabal, Sáez, Estany,
Pin-Arboledas and Reis. This is an open-
access article distributed under the terms of
the Creative Commons Attribution License
(CC BY). The use, distribution or reproduction
in other forums is permitted, provided the
original author(s) and the copyright owner(s)
are credited and that the original publication
in this journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms.
TYPE Study Protocol
PUBLISHED 08 March 2024
DOI 10.3389/fpubh.2024.1336028
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 02 frontiersin.org
memory, reasoning, calculation, attention) and self-reported well-being. This
comprehensive and interdisciplinary protocol should support evidence-based
education policy measures related to school time organisation. Appropriate
and healthier school timetables will contribute to social change, healthier
students and with more ecient learning. The results of studies using a similar
methodology in other countries would ensure replication and comparability of
results and contribute to knowledge to support policy making.
KEYWORDS
childhood, adolescence, circadian rhythms, chronotype, school schedule, social
jetlag, well-being
1 Introduction
Since the 1920s, it has been found that circadian rhythms
inuence more than 100 human functions (1). Circadian rhythms are
synchronised to the 24-h light/dark cycle (solar time), the most visible
circadian rhythm being the sleep-awake cycle. However, people adapt
dierently to the environment and we call these dierences
chronotypes. ere is a physiological response to light exposure, and
a later exposure to light reects in a later sleep–wake behaviour.
Residents in countries located more west of their time zones tend to
exhibit a later sleep–wake behaviour (2). e most extreme west
country in the Central European Time zone (CET) is Spain (3, 4),
which makes its residents more vulnerable to be a late sleep
chronotype and, consequently, more vulnerable to circadian
misalignment (abnormal timing between dierent cycles) (5). In fact,
as pointed out by Pin etal. (6), 37% of adolescents aged 12 to 15 from
the Valencia region (Spain) believe they get little sleep during the
week. Higher misalignment between solar time and clock time (solar
jetlag) has been associated with shorter sleep duration, especially in
late chronotypes (7). e group most aected by sleep loss is
adolescents since during this phase of their development they present
an endogenous delay in their biological rhythms and a greater
diculty to build sleep pressure (5) resulting in a later sleep onset
timing and higher circadian misalignment. A highly used proxy for
circadian misalignment is the so called ‘social jetlag’ that is calculated
by the dierence between the midpoint of sleep on free days and
workdays (3). Circadian misalignment can potentially aect health (8,
9) and well-being during adolescence, a life stage characterised by a
decline in subjective well-being (10, 11). e potential eects of
circadian misalignment on both physical and mental health during
adolescence are likely to bereected by high levels of sleep deprivation
or even school absence (12), while a better alignment between
chronotype and school timing is associated with lower grade retention
in adolescents (13).
As was shown in the 2011 Progress in International Reading
Literacy Study (PIRLS) and Trends in International Mathematics and
Science Study (TIMSS) a gap in reading ability and mathematics (11
points dierence in each case) was associated with sleep deprivation
(14, 15). e number of 4th-year (10 year old) students suering sleep
deprivation was 49%, which increases by 10% for 8th grade students
(14 years old). Meijer (16) pointed out that chronic reductions in sleep
can have direct and indirect negative eects on school performance
through the eect on motivation and attention. Several studies show
that later school starting times improve students’ sleep (17),
performance (18) and life satisfaction (19).
School schedules are the main inuence on the organisation of
time in the lives of children and youth. ey aect how much time
they can sleep (1, 16, 20–23). is inuence has been already reported
in several studies and for dierent ages (24–27). e consequences of
not getting enough rest and going to classes at a time that is out of
kilter with their biological clock (during sleep time) aects students’
school performance, with late chronotypes being the most severely
aected. Andrade and Menna-Barreto’s (28) study of adolescent girls
(16 year olds) showed that they tended to achieve worse scores for tests
held in the morning and higher scores for those held in the aernoon.
Wolfson and Carskadon (29) studied 3,120 students aged between 13
and 19 and found that students awarded the lowest grades (C, D, and
E in the North American system) went to bed 40 min later on average
and slept 25 min less a night on average compared to those students
who obtained the highest grades (A and B) (30). ere is other
evidence linking the late chronotype with poorer academic
performance (12, 31) and the positive eect on student grades of
scheduling exams later in the day and the week. For example, van der
Vinne etal. (32) show that the chronotype eect on academic results
disappears if exams are scheduled aer noon and Pin etal.’s (33) study
shows that moving exams from Monday mornings to Wednesday’s
mid-morning, increased average scores by 1 point (out of 10). School
performance of late chronotypes becomes increasingly worse with age,
being worst at high school which can aect future academic career
and labour earning opportunities (34). Gromada and Shewbridge (30)
found that students attending the morning school schedule but with
later preferences on study time present higher levels of absenteeism.
Contrary to much debate on school timings, it seems that ‘when’
matters as much or even more than ‘how much’ and, to beinclusive,
school timetables would need to betailored to students’ optimum
study times and learning rhythms. Evidence from recent studies in
Latin America also show similar eects of the dierent school timings
on adolescents chronotype, sleep and performance (26, 27, 35–37).
Insucient sleep and being forced to wake in their ‘biological
night’ can also aect students’ nutrition through skipping breakfast
(38) or being forced to eat during their biological night, which aects
insulin sensitivity and increases the risk of diabetes (39). PIRLS 2011
(15) and TIMSS 2011 (14) claim that 27–29% of 4th-year (age 10)
students, on average, are aected ‘somewhat or a lot’ by insucient
food intake before certain classes. is has a negative eect on reading
achievement and mathematics (14, 15). Evening or late chronotype
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 03 frontiersin.org
students are the most disadvantaged; a later chronotype has been
linked to a higher probability of obesity and unhealthy behaviours
such as smoking, drinking and excess consumption of caeine (9,
38, 40).
Psychological and bio-psychological studies have been examining
the link between the time of the day that a task is performed and
performance eciency. Gabaldón-Estevan and Obiol-Francés (41)
point to the consensus about the ultradian oscillation of attention
rhythms among primary school students in terms of identication of
two alert cycles. Up to noon, attention (alertness) increases followed
bea decrease until 1,400 and then another increase which extends into
the evening hours. A study by Testu (42) indicates that children aged
between 10 and 11 years, show low levels of alertness between 0800
and 0900 and then increased alertness which peaks between 1,100 and
noon. Aer the school lunch break, alertness levels are again low, but
then increase and peak around 1,600. Similar alertness patterns have
been found to occur among children in the United Kingdom,
Germany, Spain, Israel and the UnitedStates (30).
How people evaluate their lives, regardless of age—in general and
in relation to specic life domains (family, friends, leisure time, etc.)—
has been described as Subjective Well-Being (SWB) (43). SWB has
both a cognitive (life satisfaction) component and a two dimensional
(positive and negative) aective component, which reects the
acknowledged tripartite structure of SWB theory (44–46). In a parallel
with SWB, Psychological Well-Being (PWB) is also important for
children’s and adolescents’ overall well-being; several scholars suggest
that SWB and PWB are complementary concepts within the broader
construct of well-being (47–49). e current protocol subscribes to
this idea.
In much of the literature, the focus has been either on SWB or
PWB, measured using dierent instruments and dierent
theoretical approaches, depending on the particular philosophical
origin [the hedonic tradition focuses on SWB in terms of feelings
of pleasure (happiness)]; the eudaimonic tradition focuses on the
feeling of happiness derived from feeling fullled as an individual.
In contrast to SWB instruments, PWB are not dierentiated by a
more cognitive or aective aspect but by the concrete dimensions
they include (e.g., self-acceptance, positive relationships with
others, autonomy, etc.).
Most protocols to date are either specic in their scope or limited
in their tools. Most studies use either cortisol or melatonin or
actigraphy or questionnaires to determine chronotype. Some of them
use two or three of these tools, but hardly any of them use the four as
in our proposed protocol. Several important studies relate chronotype
to academic performance, but not many include student wellbeing
with objective measures of aptitude. Finally, the protocol wepropose
is unique in that it also includes a complete study of the subjects’ time
use in connection to all the other tools used. Our proposed protocol
should advance research in this area of the School Health Promotion
by providing dierent objective measures (i.e., actimetry, hormonal
and cognitive function assessment) as well as subjective measures (i.e.,
questionnaires, diaries). Weconsider that our protocol could help
future researchers by providing a common measure which will ensure
the replicability of our method. Wecall the protocol Kairos, aer the
Greek mythological god, because weagree with him that the focus
should beon ‘opportunity’ rather than ‘fate’.
e aim is to provide a reference protocol to promote the
organisation of school schedules that respect the needs and well-being
of children and adolescents. Figure1 depicts the objectives included
in the protocol.
e specic objectives of the Kairos protocol are:
O1—To characterise the chronotypes in the school population
based on the distribution of chronotypes across a sample of students
and applying objective (cortisol/melatonin in saliva, actigraphy data)
and subjective (questionnaire and diary) measures;
O2—To quantify the social jetlag induced by the mismatch
between student chronotype and social (school) schedule based on an
assessment of the occurrence of social jetlag in a sample of students,
measured as the dierence between the midsleep point on non-school
days (waking up without an alarm) and the midsleep point on
school days;
O3—To measure the eect of both chronotype and social jetlag
on sleep (length and quality), eating/mealtime patterns (eating time
and type of food consumed), active (non-sedentary) time and time
spent outside;
O4—To assess the eects of chronotype and social jetlag on
cognitive status (vigilance, alertness, attention) and skills (motor
coordination, simple calculation, memory tasks);
O5—To measure the eect of both chronotype and social jetlag
on the distribution of time use and satisfaction with performance of
activities in the student sample, through self-reported distribution of
the time devoted to sleeping, meals, playing video games, watching
TV/videos (screen time) and doing homework;
O6—To measure the eect of both chronotype and social jetlag
on students’ well-being, comprised by SWB (overall life satisfaction,
satisfaction with specic life domains, positive aect and negative
aect) -thus expanding the traditional tripartite model discussed
above with the quadripartite model recently proposed by Savahl etal.
(50), and PWB;
O7—To measure the eect of the school schedule on the
parameters included in O1 to O6; In the case of education systems
(e.g., Colombia, Germany, Italy, Mexico, Spain, etc.) where school
schedules may dier within a single education system (e.g., split vs.
compact, morning vs. evening, dierent start and/or break times, etc.),
O7 could include the comparison between these; O8—As stated
earlier, the ultimate aim of this Protocol is to contribute to the
promotion of school schedules that are responsive to, and therefore
respectful of, the needs and well-being of children and young people.
To facilitate the dissemination of results and promote social change,
weencourage the design of student-centred school schedules based
on the knowledge gained from the application of the Protocol.
e Kairos Study Protocol proposes a collaborative strategy
related to study design and collection and analysis of replicable and
comparable data. Section 2 describes the protocol in more detail and
Section 3 discusses its pros and cons.
2 Methods and analysis
e Kairos protocol is aimed at addressing the problem of
(de)-synchronised time experienced by children and youth.
We investigate the eects of the social jetlag of students on health
(how much sleep, timing of sleep, timing and quantity of food, time
spent on physical activity and time spent outdoors in daylight),
learning (verbal expression, spatial structuring), mediated by alert/
activation and fatigue levels, day-time activities (studying, socialising,
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 04 frontiersin.org
time spent with family, time watching screens, etc.), and self-reported
well-being. Weexplore the impact of students’ social jetlag on their
lives in terms of health, learning, time use and well-being.
2.1 Target sample
Power analysis can becalculated considering the outcome of
interest and the statistical test to beused (e.g., T-test, ANOVA). e
signicance level is set at p < 0.05, for a power of 0.80. For our study,
the sample was dened as a minimum of 385 measurements/surveys
needed to have a 95% condence level that the true value is within
±5% of the measured/surveyed value. e sample includes school
students (6 to 18 years of age), enrolled in primary schools or
secondary (high) schools. e students are to beselected on the basis
of willingness to participate and agreement from parents or guardians.
e intervention demands informing schools, families and
participants and communication channels with the parties for queries
and to report the general ndings to the schools and participants
involved. Inclusion criteria are children of both sexes over 6 years of
age enrolled in compulsory education, who agree to participate in the
study and are enrolled in schools that agree to participate. Exclusion
criteria will benot in compulsory education, unable or unwilling to
follow the protocol, or not in a school that has agreed to participate.
e most critical aspects are recruitment and respondents’
consistency in following the protocol. To ensure this, it is necessary to
prepare information sheets explaining the use of each instrument, to
hold information meetings with the centre management, with the
teachers of the participating groups, with the students and with the
parents of the students. e schools, teachers, students and parents
must give their consent for the students to participate. is makes
random selection impossible, but to ensure a representative sample,
schools are to beselected based on certain criteria including social
class of student’s families. e recruitment strategy should
be top-down, rst obtaining permission from the Ministry of
Education to carry out the study, then obtaining the agreement of the
school management and class tutors, and only then recruiting families
and students. To do this, information letters and information sessions
FIGURE1
Specific objectives—the Kairos protocol.
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 05 frontiersin.org
should be made available to potential participants, their families
and teachers.
2.2 Logistics for participants
e protocol is suited to both cross sectional and longitudinal
research designs. For example, in the latter case, the rst year’s data
obtained from screening 1 will include the full protocol for children
aged 6, 9 and 12 and the second year’s data obtained from screening 2
will be applied to the same students will then be aged 7, 10 and
13 years, and so on. is allows for collection of longitudinal data
which can beused to propose causality. To compensate for sample
dropout, additional individuals who meet the required criteria can
beincluded in subsequent screenings (see gure Flowchart of study
population in the Supplementary material for target pursue in
Kairos study).
e model explanatory variables are age, gender, chronotype,
social jetlag and school schedule. Our outcome variables are grouped
into health (sleep, eating, activity and time out), learning (cognitive:
wakefulness, alertness and attention; skills: motor coordination,
simple calculations, memory), time use (patterns and satisfaction with
activities) and well-being (SWB and PWB). Figure2 provides an
overview of the protocol.
Figure2 shows that the protocol combines both objective and
subjective measures to assess social jetlag and its eects on students’
health, learning, time use and well-being. It uses a total of 11
instruments which capture the complexity of the topic under study. In
our biological measures/assessments (saliva, anthropometry),
weinclude actigraphy monitoring (of sleep, temperature, activity and
exposure to daylight) along with data derived from the sleep and time
use diaries, the cognitive assessment (attention and aptitude) tests and
questionnaires (Munich Chronotype Questionnaire—MCTQ, food/
eating questionnaire, timetable of activities and well-
being questionnaire).
e protocol is designed to beapplied over a period of 11 days to
allow for ve full schooldays plus four full non-school days, to allow
to test students’ attention on two dierent Mondays and on a ursday.
To maintain data condentiality, students are assigned individual
project codes. To allow for follow ups, the school administrations are
given the list of project codes assigned to participants and the parent
or guardian authorizations. Sociodemographic data and some
additional information (school marks, special needs, etc.) is to
beobtained directly from the relevant school administration. In the
succeeding subsections, wedescribe the individual instruments.
2.3 Instruments
2.3.1 Hormonal assessment based on saliva
samples
Previous studies have used the measurement of salivary cortisol
to assess the dierences between its levels and the correlation of these
dierences with the subjects’ chronotype (51). Measured salivary
cortisol on awakening and 1 h later, on two consecutive days, in 112
subjects who had previously been classied as morning (9 subjects) or
evening (29 subjects) chronotypes according to the Horne and
Ostberg Owl-and-Lark-Questionnaire. ey showed that those who
identied themselves as morning chronotypes had higher salivary
cortisol levels on waking (day 1) or 1 h aer waking (day 2) than those
who identied themselves as evening chronotypes. Petrowski etal.
(52) attempted to replicate the ndings of Kudielka etal. (51) in the
FIGURE2
Calendarization of tools.
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 06 frontiersin.org
controlled environment of a sleep laboratory. In this study, 1,023
participants were classied as morning (29 subjects) or evening (59
subjects) chronotypes using the Morningness-Eveningness-
Questionnaire (MEQ). Saliva samples were taken on waking and aer
15 and 30 min. eir results showed that chronotype inuences
cortisol levels on awakening and subsequent cortisol levels, which
were higher in subjects with a morning chronotype. Weidenauer etal.
(53) found similar results, but they also looked at dierences between
weekdays and weekends. As Kunz-Ebrecht etal. (54) have already
observed, cortisol levels are higher on weekdays than on weekends.
On the other hand, these studies measured cortisol levels early in the
morning without assessing cortisol curves throughout the day. Miller
etal. (55) gather several results that suggest that more negative diurnal
cortisol slopes correlate with adaptive states of the subjects, while
more positive slopes, closer to zero, could indicate altered states of the
cortisol axis.
Regarding melatonin measurement Griefahn etal. (56) carried
out an hourly measurement for 24-26 h of salivary melatonin in a
controlled environment. e results showed that subjects identied
with morning chronotype (7 subjects) using the MEQ showed a
melatonin secretion prole with maximum concentration about 3 h
earlier than subjects with evening chronotype (14 subjects). Another
study with a very similar design with 33 subjects was carried out by
Liu etal. (57). e results of melatonin measurements every hour for
26 h also showed that subjects with morning chronotype according to
the MEQ have the melatonin peak earlier than those with
evening chronotype.
e same results were obtained by Lack etal. (10), showing 2–3 h
earlier in the peak of melatonin for subjects with morning chronotype.
In this protocol, subjects also underwent 27 h of monitoring and
measurement of cortisol every hour. In our study, wewill use the
information discussed above and the recommendation of Pandi-
Perumal etal. (58) on the indications for obtaining partial melatonin
curves. As the approximate time at which the maximum peak of
melatonin and Dim Light Melatonin Onset (DLMO) is obtained for
both subjects with morning and evening chronotype is known, wewill
reduce the intervention on the subjects since it is not feasible to
perform 24-26 h cortisol curves. In addition, wewill carry out the
measurements on three dierent days of the week, with the aim of
looking for possible dierences, as occurs in the case of cortisol.
Saliva samples are collected to measure Dim Light Melatonin
Onset (DLMO) and cortisol peak. To obtain the daily curve for
cortisol the samples will becollected at 0, 1, 4, 9and 13 h aer waking
(51, 55). e minimum saliva DLMO threshold is 4 pg./mL (59) and
the recommended partial melatonin curve to calculate DLMO should
include values between at least 19 and 23 h (probable delayed sleep
phase) or between 16 and 21 h (probable advanced sleep phase) (58),
for a minimum of ve samples in total (60). e relationship between
DLMO and sleep onset timing is on average ~ 2 h before sleep onset
(61, 62), although this value may vary substantially (e.g., DLMO
ranging from ~4.5 h before to 0.5 h aer sleep onset time) (62),
especially for late chronotypes (63, 64). As so, the ideal collection
timing for hourly saliva collections, would start 5 h before sleep onset
time and ends until 1-2 h aer sleep onset time. However, if having
budget restrictions, wemay reduce sample collections until 3 h before
habitual sleep onset and goes until 1 h aer habitual sleep onset time
in order to comply with the 5 timepoints for DLMO determination.
is allows for a combined salivary cortisol and melatonin collection
procedure based on 8 collection times: sleep time-3, sleep time-2,
sleep time-1, sleep time, sleep time + 1, awake time, awake time + 1 and
awake time + 4 (see Figure3). Cortisol and melatonin are measured at
the same time at 20 (sleep time-1) hours; the remaining sampling is
hormone-specic and takes place during execution of daily activities.
It will beanalysed the maximum cortisol levels rst thing in the
morning, the decline curve of cortisol during the day and the
DLMO. e interpretation of these cortisol and melatonin curves will
provide important information about the chronotype of the subjects
and allow their classication according to Kudielka etal. (51) and
Petrowski etal. (52). In addition, they will allow to delve deeper into
participants state of health as, for example, a more negative slope of
cortisol is associated with better health—according to Miller etal.
(55)—and an altered DLMO is associated with circadian imbalances
and sleep and mood disorders—according to Pandi-Perumal
etal. (58).
If the budget does not allow assessment of melatonin, the protocol
applied only to cortisol provides the daily curve for cortisol and
establishes the better-t saliva curve collection protocol for the
standard cortisol pattern. e sampling (collection of saliva in tubes)
should take place during execution of daily activities.
To reduce the level of intervention for the students, wesuggest
that sampling should beconned to Monday, ursday and Sunday
of the same week (see Figure1). is will allow assessment of the
evolution of cortisol and melatonin levels through a week and, also,
dierences across dierent days.
It is recommended that saliva is collected in Sarsted Salivette
Cortisol® tubes, following their sampling protocol. e students
should have not taken in any liquid or solid food (including chewing
gum) for at least 60 min before the samples are taken and must rinse
their mouths with water 10 min before sampling. e evening saliva
collections should beperformed under dim light (< 5lux). e swab
should remain in the mouth for 2 min to allow for maximum possible
sample volume. e tube must record the time of collection and the
nal sample should berefrigerated as soon as possible aer sampling.
Processing of the sample should beas per the tube manufacturer’s
instructions. Samples are centrifuged for 2 min at 1000 g. and the swab
then discarded safely. e sample can then be frozen (but never
refrozen) before the cortisol and melatonin concentrations are
determined, which requires that the samples are completely thawed
and homogenised. Determination of salivary cortisol is performed
using the Roche Cobas 6,000® and electrochemiluminescence
technology. Salivary melatonin is determined using the DRG-SLV-
4779 DRG® Melatonin direct (Salivary) ELISA (Enzyme-Linked
ImmunoSorbent Assay) kit; the plate is read using the Grifols
Trit u r u s ® analyser.
Saliva sampling is non-invasive and is performed by the student
(study subjects); it does not involve blood samples or any other clinical
intervention. In all cases, students or tutors will beinformed verbally
and through a detailed written protocol with pictograms about the
appropriate collection of the sample. In addition, sample collection
during school hours will besupervised by the research group. Finally,
they will beinstructed to remain seated or inactive as much as possible
and to collect saliva samples to measure melatonin in dim light. e
study protocol described above has been approved by the Dr. Peset
Hospital Bioethics Committee, Valencia (Spain).
Regarding the interpretation of the results: Axelsson etal. (65)
and Kudielka etal. (51) showed that early morning cortisol levels
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were higher in subjects with morning chronotype compared to
subjects with aernoon chronotype. Furthermore, several studies
summarised in Miller etal. (55) indicated that a greater (negative)
slope of cortisol decline during the day is indicative of subjects’
adaptation, whereas atter slopes of cortisol decline could indicate
deregulation of the axis. erefore, interpreting the curves with ve
daily cortisol points on three dierent days will allow to know the
patients’ chronotype more accurately. On the one hand, the
concentration of cortisol on waking or the maximum cortisol level
is measured rst thing in the morning, which allows to distinguish
between the morning and evening chronotype of each subject. On
the other hand, the slope of the curve will bestudied to assess the
health status of the subjects and to dierentiate those with alterations
in the cortisol secretion axis that may becaused, for example, by
stress. Furthermore, comparing this information between the
continuous shi and split shi groups can provide information that
allows us to assess which type of shi is most benecial for the
subjects. e data obtained will provide the students’ salivary
cortisol and DLMO and morning melatonin values and allow them
to belinked to their health, stress and sleep quality states. It will
show how these hormone levels are inuenced by or inuence the
other instruments (see Discussion section).
2.3.2 Actigraphy
Actigraphy is used to record the body rhythms that are controlled
by the circadian system (66, 67). ese rhythms are used as markers
and provide information on the working of the circadian system.
ese rhythms are inuenced, also, by other variables, such as light
and sleep, so we recommend recording more than one rhythm
simultaneously. To allow correct measurements and result, these
rhythms must bemonitored over several full days with high sampling
frequency, to reduce the variability inherent in individual lifestyles.
Alongside salivary secretion of melatonin and cortisol, the most
frequent rhythms are related to physical activity and body temperature
and are monitored using actigraphy. Actigraphy is a convenient and
cost-ecient method to record (activity-inactivity, temperature, and
light exposure, body position) over multiple days in a natural
environment. It is especially useful for samples that include infants
and young children whose sleep is likely to beaected by a laboratory
environment (68–70).
e participants follow their usual routines at home and in their
school environment. eir activity is sampled at 10 Hz and stored in
every 30 s epochs. Measurements taken when the actimetry watch is
not being worn are excluded from the analysis and if in 1 day wehave
more than 4 h of missing data that day is eliminated for analysis.
Wecalculate sleep onset, sleep oset and sleep duration for schooldays
and non-school days according to Madrid-Navarro etal. (71). Wealso
measure nap behaviour since many adolescents nap to make up for
lack of sleep at night; this is an indirect indicator of how tired they are,
and the total sleep time should beestimated for the 24 h period. All
individuals involved in the actimetry test will berequired to use the
event marker of the device to provide the following information: sleep
onset and sleep oset times.
To record circadian rhythms and sleep, weuse the actigraphy
device Kronowise Feedback® multichannel device, which allows
simultaneous recording of skin temperature rhythms, physical activity,
position, light exposure (infrared, blue and total visible light) and
sleep over a prolonged time period, allowing, in turn, evaluation of
appearance of chronobiological changes (including sleep changes) and
follow-up over a full week.
e Kronowise Feedback® device (Kronohealth SL, Spain)
includes: 1. a temperature sensor with precision ±0.1°C at 25°C and
0.0635°C resolution, housed in a separate chamber to avoid thermal
interference from the battery and electronic components, and attached
to a metal plate that is in contact with the skin; 2. a triaxial MEMS
(Micro ElectroMechanical System) accelerometer calibrated with
linear and equal sensitivity along all three axes, within the range ± 2 g.
and sensitivity 0.001 g.; 3. 50/60 Hz.
FIGURE3
Saliva sampling procedure.
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e device records approximately 23 million raw data points
related to 14 primary variables and 1 estimated variable (sleep) that
reect the functioning of the circadian system. e information
obtained includes: (1) daily physical rhythms [integrated variable
TAPL—rist skin temperature (T), motor activity (A), body position
(P) and light exposure (L)] (72–74); (2) sleep parameters such as sleep
latency, total sleep time, counts of Waking Aer Sleep Onset (WASO),
sleep eciency, activity during sleep and the timing of sleep (onset,
oset and mid-time); (3) data to allow calculation of the main
indicators of circadian health (regularity, contrast between day and
night, synchronisation and quality of rest).
e main circadian indexes will bedetermined by non-parametric
analysis, including:
− VM5: average value of the variable during the 5 consecutive
hours of maximum values. It applies to variables that increase
during sleep, such as temperature and sleep;
− HM5: central time of the 5 consecutive hours of maximum
values. Values that increase during rest periods;
− VL10: Average value of the variable during the 10 consecutive
hours of minimum values. Variables such as temperature and
sleep, whose values decrease during awake periods;
− HL10: central time of the 10 consecutive hours of minimum
values. Values, such as temperature and sleep, that decrease
during wake periods;
− VM10: average value of the variable during the 10 consecutive
hours of maximum values. Variables such as motor activity,
position and light exposure, whose values increase during
awake periods;
− HM10: central time of the 10 consecutive hours of maximum
values, for values, such as motor activity, position and light
exposure, that increase during awake periods;
− VL5: average value of the variable during the 5 consecutive hours
of minimum values in relation to those variables, such as motor
activity, position and light exposure, whose values decrease
during sleep;
− HL5: central time of the 5 consecutive hours of minimum values.
Values such as motor activity, position and light exposure, that
decrease during rest periods;
− IS (Interdaily Stability): a score of the regularity of circadian
pattern over dierent days. is varies between 0 for a Gaussian
noise to 1 for a total stability, where the rhythm repeats itself
exactly, day aer day, weassess it for skin temperature, physical
activity, position, light exposure (infrared, blue and total visible
light) and sleep;
− RA (Relative Amplitude): for variables that increase during
resting times or during activity times, we assess it for skin
temperature, physical activity, position, light exposure (infrared,
blue and total visible light) and sleep;
− ES (Environmental Synchronisation): degree of synchronisation
between the phase marker of a circadian variable during a rest
phase (HM5 or HL5) and the centre of natural darkness taking
as the reference the Central European Daylight Time (CEDT)
and the location where the event is registered. is variable can
express values between 0 and 1. When the centre of a variable
coincides with the centre of natural darkness, ES is 1.
− CHS or CHI (Circadian Healthy Score/Circadian Healthy Index):
is the main marker of circadian health. Its values range between
0 and 1. e value 1 indicates a rhythm perfectly synchronised
with the natural light–dark cycle in terms of regularity,
environmental synchronisation and normalised relative
amplitude, as described by Martínez Nicolas etal. (75). is value
is used as a global marker of chronodisruption: the closer to 1,
the less chronodisruption.
All in all, wejustify the use of actigraphy because it gives us the
opportunity to study the person over a long period of time in their
usual environment, clearly identifying moments of activity and rest,
and it is also a small, comfortable and portable device (like a watch).
Also, because it provides objective data that wecan compare with
data obtained from other instruments in the protocol
(triangulation). Finally, it allows us to assess the person’s exposure
to light, which allows us to make a good assessment of possible
circadian problems, and, by measuring temperature, wecan nd out
whether the person’s time to go to sleep coincides with their
biological time for doing so.
2.3.3 Sleep diary
e student or tutor must record what time the sleep ‘ritual’
begins, what time the individual estimates to fall asleep and what time
the student wakes up. Daytime naps and any events that occur during
the night must beregistered. Physical activity and use of technology
must also beregistered. ese data should beregistered over a 10-day
period when the student is wearing the actigraph (i.e., school days and
non-schooldays). ose completing the sleep diaries will be the
subjects themselves in the case of secondary school students, and their
parents or guardians in the case of primary school students.
Information sessions will beheld for both groups and members of the
research team will beavailable to answer any questions.
2.3.4 Munich chronotype questionnaire
e core version of the standard MCTQ (Children and
Adolescents version) is used to assess sleep-awake behaviour on
school days and non-schooldays. e MCTQ asks about sleep and
activity times for schooldays and for school-free days: what time the
individual goes to bed; what time heor she decides to go to sleep; how
long it takes to fall asleep; what time the individual wakes up, what
time the student gets up and if an alarm clock is used. e MCTQ is
a validated widely used method to estimate chronotype, based on the
midpoint between sleep onset and sleep termination on school-free
days, ‘corrected’ for sleep debt accumulated across schooldays; this
provides the chronotype estimation in the form of a local time not a
score [for the exact calculation, see (3)]. Additional variables, such as
sleep duration and social jetlag (absolute dierence between mid-sleep
on non-school and school days, i.e., the dierence between biological
and social time) can beretrieved from the MCTQ. Chronotype and
social jetlag calculations are considered only if the participant reports
not using an alarm clock on non-school days. Additional measures
enabled by the MCTQ are sleep latency, sleep onset and wake up
times, sleep midpoint, time in bed, and sleep duration separately for
school-and non-school days.
Finally, wealso include the item “You hear about ‘morning’ and
‘evening’ types of people. Which of these types do youthink youare?”
with four possible answers because it is an item from the Morningness-
Eveningness Questionnaire, which is widely used as a single item to
reect circadian self-perception.
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2.3.5 Eating and food questionnaire
Assessment of food intake and timing is required to understand
eating patterns and the contribution of macro and micronutrients at
the individual and collective levels. e dietary questionnaire allows
an assessment of food intake. To estimate the individual’s usual intake,
the respondent is asked to record all food and drink taken at each meal
on a Monday and a ursday (schooldays) and one non-school day,
Sunday. Prior to the start of the study, the researcher will provide
instructions, an example and three templates for these records to both
the participant and an adult member of the household who will
support the student. e document asks about: (1) amount of food
ingested; (2) all the ingredients in a particular meal; (3) the cooking
method; (4) location of the meal (if at school, attach the school meal
menu); timing of the meal; (5) drinks; (6) snacks taken between meals;
and (7) whether the food and drinks were homemade or processed.
ese data allow two calculations. First, the nutritional
composition of the student’s diet can be measured, based on the
dietary record that can becalculated using a soware such as DIAL
(Alce Ingeniería SA Madrid, Spain). e most relevant diet variables
are kilocalories consumed, percentages of proteins, carbohydrates and
lipids, amounts of sugars, total, soluble and insoluble dietary bre,
cholesterol, and saturated, monounsaturated and polyunsaturated
fatty acids. Second, data on chrononutrition and the timing of intake
on school days and non-school days. e tool is very easy to ll out
because it is a description of what they eat. For elementary school
students, it is completed by their parents, and for high school students,
by themselves. Our experience with the tool so far suggests that it is
an easy task for participants to complete if they are reminded to do so.
Studies suggest that recording daily food intake and calculating
calories using food exchange lists and food composition tables to
estimate caloric intake are within an acceptable range of error and
therefore represent a practical approach to estimating caloric
intake (76).
2.3.6 Anthropometric evaluation
Anthropometric evaluation is used to record the following health
parameters weight and height, body mass index, body composition,
skin folds, waist circumference and is applied to the whole sample.
Anthropometric evaluation has been widely use in the literature for
body composition analysis (77, 78). For this protocol participants
must beweighed and measured, by the same person, under the same
conditions in line with International Society for the Advancement of
Kinanthropometry (ISAK) (79) recommendations. A bioelectronic
scale with a body composition analyser should beused to record body
weight and the other body composition parameters. is is a
non-invasive method to allow evaluation of body composition by
measuring the opposition to the ow of a current through the subject’s
body. More resistance (greater bioimpedance) will be linked to
individuals with large amounts of adipose tissue which is a poor
conductor of electricity due to its low water content. Bioimpedance
allows estimation of total body water and fat-free mass and fat mass
segmented by body areas. Accurate measurement of bioelectrical
impedance requires the student to have urinated immediately before,
bedressed only in underwear, with bare feet, with nothing metallic on
their person or clothing, standing upright with arms outstretched.
Privacy should bemaintained by the use of a 3-leaf paraban or similar.
A stadiometer with 0.1 cm fraction precision should beuse for the
height measurements. Students should bebare foot and standing with
their feet together, with their heels, buttocks, back and occipital region
in contact with the vertical plane of the stadiometer, with the feet
together. When taking the reading, the student must inhale and keep
his or her head in line with the Frankfort plane (imaginary horizontal
line between the lower edge of the orbit and the external auditory
canal). Werecommend that height should berecorded in centimetres.
e height and weight data allow calculation of the z-BMI score
and the corresponding percentiles using the SEGHNP2 Nutritional
Application programme and the reference tables for the focal country’s
paediatric population (in our case Spain) to calculate the percentile
and the equivalent SD for each subject. A child with a BMI greater
than or equal to 1.8 standard deviation (SD) above the mean for age
and sex is classed as obese, according to the World Health Organisation
(WHO) (80). e students’ waist should bemeasured manually using
a non-extensible, exible steel tape calibrated in centimetres with
millimetre graduations in line with ISAK (79) protocols. e waist
measurement should betaken by placing the tape 4 centimetres above
the navel with the student standing upright and breathing normally.
e waist measurement is recorded at the end of an outbreath.
Tricipital, bicipital and abdominal skin folds should also bemeasured
to allow calculation of body fat. ree measurements must betaken
of the waist circumference to obtain the average among the values.
ree measurements of each fold should berecorded by the same
person and under ISAK (79) titration.
2.3.7 Attention test
Attention tests allow estimation of optimal attention time slots to
enable optimal student learning. e tests should beadministered to
each student three times to compare results at the beginning and end
of the rst school-day in the week (Monday—1st and last class session)
and to compare those with mid-morning ursday. Dierent attention
tests have been chosen to avoid a training eect derived from
repetition of the same test within a few days. Werecommend that the
Monday 1st class tests should use the Test of Perception of Dierences
(or FACES-R test) and Monday end of the day tests should use the
d2-R and the ursday attention test should bebased on attention
sub-test included in the Aptitude Assessment test (see Section 3.7).
e Faces-R test is used to evaluate perceptual and attentional
aspects among subjects aged between 6 and 18 years old and is
appropriate for large samples. It comprises 60 graphic elements, each
grouped according to three schematic faces, two of which are identical
and a third which has one dierent feature (mouth, eyebrow, hair,
etc.). e d2-R test is a timed test, suitable for subjects aged 6 years and
older and involves a cancellation task to evaluate selective attention. It
measures processing speed, ability to follow instructions and accuracy
of execution of a task involving discrimination among similar visual
stimuli. Both tests provide scores for speed and accuracy, which are
important aspects of the main score—ability to concentrate.
To observe and record attention changes throughout the day and
the week among a group of students requires administration of the
attention test at dierent times and on dierent days. Werecommend
three tests: rst and last classes on Monday and mid-morning on
ursday. is allows observation of attentiveness and activity at the
beginning and end of the rst school day in the week (Monday) which
can becompared with attentiveness and activity in the middle of the
day on the second to last day of the week (ursday). e results of
these tests will indicate the hours when level of attention is highest,
which will favour understanding and internalisation of new learning,
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and those days in the week when perception is perhaps highest. Both
tests have been used in other protocols with the same population
target (81–84).
e test is conducted in the same way for the whole sample,
regardless of age. First, the test should bedistributed to each individual
in the sample; the subjects will beasked to complete the information
requested on the rst page (identication data). e psychologist or
pedagogist then will explain the test. Aer ensuring all the study
subjects have understood what is required the test should start. e
time allocated to completing the test is 3 min.
Aer 3 min, the test pages will becollected. e responses will
be awarded direct scores, percentile scores or STANdard NINes
(stanines). Higher scores indicate higher capacity for attention and
perception and greater control of impulsivity.
Internal consistency of the FACES-R test will beestablished using
Cronbach’s Alpha coecient; weobtained a score of 0.91 for the whole
sample. However, since the Cronbach’s Alpha coecient is below 0.90
for students aged between 6 and 11 years, weneed to apply some
additional instruments to increase reliability.
Based on the results obtained from summing hits and errors, the
following proles can beidentied.
e results of this test should becorrelated with the results of the
aptitude tests such as BADyG (Bateria de Actividades mentales
Diferenciales y Generales or Dierential and General Skills Battery;
see next instrument) used to detect aptitude levels of sample
participants. BADyG also includes an attention subtest that will
beused as the attention test for ursday. It is useful, also, to cross-
check these data against student chronotype, extracted from the
MCTQ, to verify whether the hours of peak attention correspond to
the individual’s periods of peak energy and activity.
2.3.8 Aptitude assessment
Aptitude is a construct that cannot beobserved directly; therefore,
aptitude should bemeasured using a self-reported questionnaire. e
BADyG aptitude test allows the assessment of academic performance
and special educational needs and has been widely used in research
(85, 86). ere are dierent versions of the BADyG test to suit ages 4
to 18 years. e test is copyright protected and must bepurchased by
the researcher. e test shows good psychometric scores, excellent
reliability at all levels and good internal consistency of Cronbach’s
alpha, Spearman-Brown coecient and Guttman’s two halves
coecient. e BADyG is used to measures cognitive development in
verbal, numerical, spatial and logical reasoning skills and ability to
solve verbal, numerical and spatial syllogisms, and the speed and
eciency with which students solve the academic problems they
encounter. It also provides a score for general intelligence.
BADyG logical reasoning includes inductive operations and
abstract concepts based on grouping visuospatial, numerical and
verbal aspects. It requires ability to solve comprehension problems and
access to memory. e logical reasoning score is obtained by summing
the scores for analogue relations, numerical series and logical matrices.
e verbal score is obtained by combining the content of verbal
compression and analogical reasoning to obtain second-order
relationships between pairs of concepts. is ability is basic and
central to most smart activities. e verbal score also involves
Analogue Relations plus Complete Sentences tests. e numerical part
of the test requires access to memory and recovery of previously
learned knowledge, decoding of numerical codes or symbols and the
related operations. e numerical score is obtained from the
Numerical Series plus Numerical Problems test. e visuospatial test
involves representations of gures that rotate a series of degrees to le
or right which must bepositioned appropriately to complete the
painting. is is like Raven’s Progressive Matrices, which are used as
a non-verbal measure of overall intelligence and are obtained from the
Logical Matrices + Fit gures. General intelligence is considered to
combine all mental abilities: the mind’s relational and abstractive
activities. However, it is current intelligence, not something given at
and immutable since birth. It is based on development phases and
interaction with environmental stimuli and is obtained by summing
the verbal analogies, numerical series, logical matrices, complete
sentences, numerical problems and gure tting scores.
e tests should bescheduled to cover a range of times appropriate
to the student’s age: for example, older aged students will require less
time to complete the test. For a sample with an average age of 12 years,
the basic tests will take 67 min and the complementary tests 24 min,
to a total of 91 min. It should benoted that within each level of the
various tests, the questions are organised in order of diculty, from
easier to more dicult. Correct application of these tests requires
subjects to have a test book and another book in which to record their
answers. Each test must beexplained to participants along with the
time available to complete the test. A computerised version of the tests
is also available.
Interpretation of the results is done based on individual answer
books/sheets.
e results allow automatic generation of reports. e collective
report is generated by the direct scores and the group centile score,
which provide scaled and statistical results. Individual proles are
obtained by comparing a specic student’s percentile with the
percentile assigned to each test scale. e comparative intergroup
report of means is extracted by comparing the mean of each group
with that of the corresponding scale; the means of each test are then
compared to allow observation of those skills that are more developed
and those that require interventions. e intragroup level distribution
report is based on the percentile ranking in the 7 levels: a score of 94
or over is Very High, a score of between 93 and 75 is High, 74 to 61 is
Medium-High, 60 to 31 is Medium, 30 to 16 is Medium-Low level, 15
to 7 is Low and the score of less than 7 is Very Low level. Finally, the
interval between general intelligence and intelligence quotient or IQ
indicates the upper and lower limits of student percentile scores.
One of the limitations of the BADyG and similar tests, is the
length of time involved and the need for some breaks during the tests
to avoid a fatigue eect which could lead to lower test scores.
Werecommend a 30-min break halfway through the battery of tests.
2.3.9 Timetable of activities
e student timetable for a normal week captures their
participation in a range of dierent activities (school hours,
extracurricular activities, sports trainings, etc.). It requires them to
indicate start and nish times for their regular activities and provides
an understanding of how primary and secondary school students
allocate their time, on a weekly basis. Also, and in line with
Csíkszentmihályi’s (87) ‘ow’ concept, students are asked to rank their
level of preparedness (skill) for the individual activities (low, medium
or high skill level) and how dicult (low, medium or high) they found
the activity. Measuring the ‘ow’ related to each activity captures the
student’s subjective evaluation of his or her routine activities.
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2.3.10 Time diary
e Time Diary is used is to measure the student’s participation
in dierent activities based on information on time spent on learning,
socialising, leisure, self-care and other activities. e Time Diary tool
asks participants to indicate their main and secondary activities, who
is involved in these activities and where they take place, on a scale of
10-minute slots, allowing a degree of objectication of non-or
partially-institutionalised social activities and their duration (88). e
Time Diary from the standard Time Use Survey (TUS) provides a
detailed record of the activities undertaken during one school day and
one non-school day. e TUS is administered in numerous countries
and, in the European Union, is coordinated by the Eurostat Working
Party which devised the Harmonised European Time-use Study
(HETUS) in the late 1990s (89).
In the case of primary age children and adolescents, the interest is
in obtaining information on students’ daily routines, with whom they
interact and their assessed level of satisfaction with these activities. To
respond to the specicities of the study subjects and the research
objectives, the TUS Time Diary can be adjusted to include
these aspects.
Students are asked to record their activities over three specic
days, with support from tutors, parents or guardians. Using a 10-min
interval scale, the students are asked to indicate their activities over
the course of two school days (Monday and Tuesday) and one
non-school day (Sunday). Figure1 shows that these 3 days coincide
with the collection of saliva samples, recording of eating in the feeding
questionnaire, wearing the actimetry watches and recording their
sleep/awake behaviours in the sleep diary. is pattern facilitates data
collection, and the range of data allows for data triangulation.
2.3.11 Well-being questionnaire
e literature recommends the use of more than one type of
instrument to allow comparison and allow collection of
complementary information (90). e wellbeing questionnaire uses
the ve scales employed in the third wave of the Children’s Worlds
Project
1
to assess SWB and PWB. e CW-SWBS, CW-DBSWBS,
CW-PNAS and CW-PSWBS are adapted from previously proposed
scales. It also includes four additional satisfactions with life domains
not being part of any scale. e limitations regarding cross-cultural
comparison are discussed later. All of the instruments are answered
under a self-application form and only for students 8-years-old and
older. ey are the following:
2.3.11.1 Overall life satisfaction scale
e importance of a single item scale for overall satisfaction in the
context of the cognitive dimension of SWB was highlighted by
Campbell etal. (43). Although initially formulated for adults, this scale
has been used widely with samples of children and adolescents and
has shown good performance. Weincluded a question asking about
overall satisfaction with life; 10 to 18 year-old students are asked to
indicate their overall satisfaction with their lives on a scale from 0 to
10, where 0 is Not at all satised and 10 “Totally satised” and a scale
of 5 emoticons (from sad to happy) for 8 to 9 year olds. e questions
posed are: for 10 to 18-year-old students—To what extent are
1 https://isciweb.org
you satised with your life in general? And for 8- to 9-year-old
students—Are youhappy with your life in general?
2.3.11.2 The children’s worlds subjective well-being scale
e CW-SWBS consists of six items measuring cognitive SWB,
based on Huebner’s (91) Student Life Satisfaction Scale, Diener etal.’s
(92) Satisfaction With Life Scale, and suggestions made by the children
themselves on how to improve the wording. ey are the following: I
have a good life, e things that happen in my life are excellent,
Iamhappy with my life, Ienjoy my life, My life is going well and Ilike
my life. An 11-point agreement scale was is used from 0 = Not at all
agree to 10 = Totally agree (10 to 18 year olds), and an agreement
5-point scale ranging from “I do not agree” to “Totally agree” (8 to
9 year olds). An overall index is calculated based on summing the six
items and dividing the total by 6.
2.3.11.3 The children’s worlds domain based subjective
well-being scale
e CW-DBSWBS includes ve items measuring domain based
cognitive SWB, based on Seligson etal.’s (93) Brief Multidimensional
Student Life Satisfaction Scale (BMSLSS). e ve items refer to
satisfaction with: e people youlive with; Your friends; Your life as a
student; e area youlive in; and How youlook. e CW-DBSWBS is
scored on an 11-point scale from 0 = Not at all satised to 10 = Totally
satised for 10- to18-year-old students and a scale of 5 emoticons
(from sad to happy) for primary 8- to 9-year-olds school students.
Calculation of an overall index is achieved by summing the ve items
and dividing the total by 5. Again, there are some limitations in
relation to cross-cultural comparison and these are discussed later.
Besides the CW-DBSWBS, the protocol also includes additional
satisfaction with life domains not being part of any scale but also
included in the Children’s Worlds project to cover more aspects of
children’s and adolescents’ lives. ey are measured in the same way
as for the CW-DBSWBS and are analysed separately. ey are
satisfaction with how youuse your time, the freedom youhave, your
health and how are youlistened to by adults in general.
2.3.11.4 The children’s worlds positive and negative
aects scale
e CW-PNAS measures the aective dimension of SWB and is
based on the Core Aect Scale (94, 95). e six items include three for
positive aect (full of energy, happy, calm) and three for negative aect
(stressed, sad, bored). e question posed for 10–18-year-old students
is: Please consider each of these words and then indicate on a scale
from 0 (Not at all) to 10 (Extremely) how much you felt this way
during the last 2 weeks? while 8–9-year-olds students are asked to
indicate frequency of these feelings on a 4-point scale ranging from
“Never” to “Always,” with “Sometimes” and “Oen” as intermediate
options. An overall index can becalculated by summing the three
items on positive aect and the three items on negative aect and
dividing the respective scores by 3. e items can also
beanalysed separately.
2.3.11.5 The children’s worlds psychological subjective
well-being scale
e six-item CW-PSWB psychometric scale measures PWB and
is based on Ry’s (96) model [see (97)]. ey are asked to score the
following items: Ilike being the way Iam; Iamgood at managing my
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Frontiers in Public Health 12 frontiersin.org
daily responsibilities; People are generally friendly towards me; Ihave
enough freedom of choice about how I spend my time; I feel that
Iamlearning a lot at the moment; and I feel positive about my future
on an 11-point unipolar scale from 0 “Totally disagree” to 10 “Totally
agree.” is scale is only administered to the secondary-education
students (12 to 18 year olds). An overall index summing up the six
items on positive aect, on the one hand, and negative aect, on the
other hand, and dividing the respective total scores by six is
generally calculated.
Casas and González-Carrasco (98) investigated the reliability and
comparability of the CW-SWBS, CW-DBSWBS, CW-PNAS and
CW-PSWBS among the 35 countries included in the third wave of the
Children’s Worlds Project, based on the 10- to 12-year-old age groups.
In the CW-SWBS, they suggested that an abridged version of the ve
items, which excluded the item I like my life, would besuitable for both
10 and 12 year olds. Comparison of the data from the dierent
countries based on multi-group equation modelling showed that the
mean scores for the item e things that happen in my life are excellent
was not strictly comparable among countries for either age group,
although the other items were satisfactory. e ve items in the
CW-DBSWBS were deemed appropriate for both age groups.
However, the authors warned against use of a statistic based on an
overall index for cross country comparison, since the meaning diers
across countries.
For both age groups, the explained variance among the
CW-DBSWBS items may besmaller compared to the CW-SWBS
items. For the pooled sample, the CW-PNAS (positive and negative
aect) models are appropriate for both the 10-year-old and 12-year-
old samples. e multiple-group model is appropriate for the 10-year-
olds, but not the 12-year-old group. Again, a statistic based on an
overall index for the scale should not beused for cross country
comparison. e CW-PSWBS is appropriate for both age groups, but
again no statistic based on an overall index should beused for cross
country comparison. For the CW-DBSWBS, CW-PNAS and
CW-PSWBS cross country comparison can bebased on correlations
and regressions. For the primary age students, conrmatory factor
analysis of the CW-SWBS applied to the 8-year-olds group,
corresponding to the third wave of the Children’s Worlds Project
showed adequate t for structural equation modelling while the multi-
group analyses supported scalar invariance if one of the countries was
excluded from the model. erefore, ndings support application of
the CW-SWBS for 8 year olds in both eastern and western
countries (99).
We need to make some comments on the interpretation of the
results of the above instruments. In general terms it could besaid that
the higher the score the better. However, there is a range of values that
are likely to dene most of the sample population’s responses to the
SWB (there is no equivalence for the PWB level). e theory behind
the predicted normative range for the SWB scores is Cummins (100)
homeostatic model. To explain variations in SWB wesuggest the
analogy of deviations in blood pressure and heart rate, which, in
certain circumstances, due perhaps to dierent external and external
factors (e.g., stress, illness) exhibit minimum and maximum values,
and which under normal circumstances, return to their baseline values.
It is assumed that there is a genetic mechanism that controls SWB
homeostatically. ere may berelatively small variations in SWB levels
among individuals belonging to the same culture which can
beexplained by this mechanism, although with the exception of cases
where inbuilt protection mechanisms fail. e range of values for
adults of between 75 and 90 on a 100-point scale, is due to optimism
bias (100, 101) whereas the normal distribution is around 50.
Although some authors suggest that levels of SWB are similar for
younger children and adolescents (102), there is some evidence
suggesting that these set-points are higher among primary age
children and decrease through adolescence before converging, at some
point, with the adult population (10, 11).
Taking the third wave of the Children’s Worlds project and the
only scale that supports mean comparisons across countries, the ve-
item version of the CW-SWBS, as a reference point, this decreasing
with age tendency reported by González-Carrasco etal. (10, 11) with
longitudinal data is observed for the group of 10-year-olds compared
to 12-year-olds (the same scale is used for both). e mean score for
the 8-year-olds ranges from 3.11 to 3.65 out of 4 (with Spain ranked
3rd—mean of 3.59). e means for the 10-year-olds group oscillates
between 7.94 and 9.71 out of 10 (with Spain ranked 4th position). And
the means in the case of the 12-year-olds group (mean of 8.82 out of
10) with means ranging from 7.25 to 9.55 (with Spain ranked 7th
position) (103).
2.4 Ethics and dissemination
e protocol complies with Spanish legislation (Biomedical
Research Law, BOE July 4, 2007, research collecting data on humans),
and the ethical standards articulated in the Helsinki declaration (104).
All the processes involved comply with international ethics of human
genetic studies recommendations (105). Participation carries no risks
for participants; it involves no invasive procedures and no
interventions with known risky side eects. e saliva samples are
used only to collect hormonal indicators.
e data (salivary hormones, actigraphy data, subjective data
collected through questionnaires and diaries, personal data including
age, sex, socioeconomic background, etc.) are collected in line with
the guidelines set by an Ethics Committee. Use of the personal data
collected during application of the protocol should belimited to
project eldwork and is subject to the participants’ informed consent.
Personal identity will beprotected through use of anonymized codes;
only the schools and high schools involved will beable to related the
codes to actual names. e codes will never bemade public. e
documentation and work data will bestored on secure servers to
which only the research team will have access.
At the end of the project, the anonymized data, will bemade
available to the scientic community in line with national legislation.
During the project the members of the research team will not process
data using personal means and will guarantee security through
conformance to legal requirements acknowledging that resources
containing personal data are condential and restricted. At the end of
the project, any personal data collected will bedestroyed.
2.5 Data analysis
e protocol generates a considerable ow of data, which should
berecorded, organised, and stored in a huge set of quantitative and
qualitative variables of dierent nature. e preliminary analysis
should include the initial treatment of records, data cleaning, and
graphical representations. en, marginal and multivariate analysis of
cross-sectional variables of interest should beperformed by using
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 13 frontiersin.org
diverse descriptive and association measures, multiple regression
models, binary choice models, and in the cases of repeated
measurement, panel data methods.
A key assumption in linear regression is that observational units
(e.g., students) are independent, given the values of a set of covariates.
An important violation of the independence assumption is due to
clustered data, when the responses of students are naturally grouped in
classrooms, or schools. e analyst could never hope to observe all the
potentially inuential covariates, such as the classroom atmosphere,
the teacher’s enthusiasm and competence, or the level of parental
involvement, since they cannot bemeasured appropriately. erefore,
there is unobserved heterogeneity between the responses by classrooms
and schools. e consequence is that two observations in same
classroom or school are correlated and more similar than observations
in dierent classrooms or schools, so students in one classroom or
school would tend to have better test results, even aer controlling for
observed covariates, than students in another classroom or school.
Multilevel models allow the processing of data from hierarchical
structures and are especially useful for data processing in educational
research. is analysis complements the previous ones, so that it
considers not only the possibility of treating the rst-level elements that
characterise individual responses, but also the dierent levels of nested
models that can beproposed, considering higher-level eects than the
individual student.
3 Discussion
Epidemiological studies show that chrono disruption is a risk
factor for numerous diseases, including cardiovascular disease,
metabolic syndrome, cognitive and aective disorders, cancer and
immunosuppression, among others (106, 107). Exposure to light and
physical or mental activity at hours when exposure to light is abnormal
for human beings causes alterations to biological rhythms and,
especially, sleep rhythms and biological processes controlled by
endogenous circadian clocks. ese eects are seen particularly
among children and adolescents. e use of electronic technology at
the end of the school day and during extracurricular and family
activities contribute to tiredness during daytime hours and are
contributing factors for school failure (108).
Exposure to articial light (in school, or at home) leads to
changes to clock genes and proteins in the central nervous system and
aects melatonin and other hormones production, which aect the
duration and quality of sleep and changes to central and peripheral
circadian rhythms (109, 110). Activities such as mealtimes and the
type of food consumed also aect peripheral clocks which in turn
aect circadian rhythms (111).
ere are studies that it exemplies some of the eects of the
school schedule in the health, performance and wellbeing of students.
Some studies link delayed intake of food with increased obesity (8, 40)
also in children and youth (112) and some highlight the link between
compact schedule in school with decreased performance and increased
fatigue (113–115). Several works focus on the eects of school time
organisation in schools and its relationship with (de)-synchronisation
with students’ internal body clocks (12, 31, 32). With the eect of
school schedule organisation on academic performance (13, 116) and
the impact of school schedules on sleep (23, 26, 117).
e protocol captures several health measures to evaluate the
eect of school schedules on youth health and wellbeing. e protocol
measures circadian health, amount and quality of sleep, body mass
index, body composition, diet, outdoor light exposure, and minutes
per day of moderate-to-vigorous physical activity, as well as
recreational screen time. As for wellbeing questionnaire, as wealready
mentioned, weintegrate the ve scales employed in the third wave of
the Children’s Worlds Project and include four additional satisfactions
with life domains not being part of any scale.
e protocol allows the comparison of dierent school schedules
(extended vs. compact; morning vs. evening) within an education
system. We propose to measure the eects of dierent school
schedules on students’ health, wellbeing and academic performance
by controlling for the other confounding variables included in the
protocol. Although demanding, compliance with the protocol is
possible with a reasonable degree of success if the research team
carries out its tasks of eld preparation, information, support and
instrument collection properly. Webelieve that the more support
given to students and parents in explaining the purpose of the research
and how the protocol works, the greater the success. In some cases, a
second appointment to retake a test or complete a questionnaire must
begranted if the participating student is ill or unable to attend, and if
this happens, it must beon the same day of the week and at the same
time as the original request.
From a scientic-technical perspective, the combination of
expertise and methodologies proposed in this protocol is novel and
should beof value to both researchers and education institutions. In
2023, we implemented the protocol in two high schools with 49
13-year-old students. e protocol included measuring cortisol levels,
but not melatonin due to budget limitations. is prior experience has
enabled us to adjust logistical aspects of the protocol based on our
eld study. e protocol enables the collection of rich and
complementary data from a sample of students, which will provide a
better understanding of the complexities related to the scheduling of
lesson times for children and adolescents. e statistical analysis
should include both a longitudinal description of each variable and a
multivariate description of the relationships between them based on
extensive correlation analysis. e ability to attribute causality, which
is rare in this eld, is enabled by collection of longitudinal data, which
also enable a better mapping of the changes that occur in childhood
and adolescence. For example, the proposed protocol allows collection
of data on children’s cortisol levels, during two dierent days during
the school week and on a non-school day. ese data related to young
people are unique.
Our protocol allows the interlinking and further development of
several research strands (on sleep, eating, activity, learning,
socialisation, well-being and other patterns) within a comprehensive,
interdisciplinary and complex protocol. e ndings will reinforce
existing research and should beinformative for policies in education
and aspects related to school timings. In turn, this should contribute
to the formulation of more healthy, ecient and satisfying school
schedules. e novelty of our protocol should contribute to research
and education worldwide and the well-being of society and, especially,
students, students’ families and teachers. ese benets may
contribute bemanifested in better student performance in school and
a better school climate and improved health literacy.
We are aware of the inherent challenges in achieving full
synchronisation between the school timetable and individual
chronotypes, and weare also aware that getting the school timetable
right for students’ chronotypes is only part of the problem, but a very
important one. What happens outside of school is very relevant to
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 14 frontiersin.org
what happens inside, and the pedagogy and internal organisation of
academic activities also play an important role in both student
performance and well-being. We believe that both what happens
outside school and what happens inside school will benet greatly
from a better match between the school timetable and the chronotype
of the student. On the other hand, there is a degree of scepticism
about improving school schedules due to the multifactorial nature of
the educational process, especially in education systems with a weak
tradition of evidence-based practise. We believe that it is only
through the development of research and specic educational studies
that wewill beable to guide teachers, families and policy makers in
a research-action process of social change.
Considering the protocol and the accompanying instruments, the
following strengths and weaknesses are identied. At the application
level, one of the protocol’s strengths is its multidisciplinary approach,
encompassing various disciplines and variables to study a broad age
range, with a sample ranging from 6 to 16 years, considering each
developmental and academic stage. On the ip side, one of the most
critical aspects is the recruitment and consistency of the sample
requiring participants to commit to the protocol with up to 12
instruments applied over 10 days. While it is a strength that applied
as a longitudinal study allows the evaluation of the evolution of many
variables over time, maintaining the sample for several years poses a
signicant challenge. To compensate for sample dropout, additional
individuals who meet the required criteria can be included in
subsequent screenings. Additionally, as a weakness, reliance on the
sample’s responsibility in completing instruments is acknowledged,
with increased completeness when applied in the school setting
assisted by the class teacher and/or the research team.
On the instrument level, strengths include obtaining hormones
through non-invasive saliva samples and the actigraphy as a wearable
instrument capable of registering extensive data over an extended
period in student’s natural environment. e feed questionnaire,
attention tests, and well-being questionnaire stand out for their ease
of application, speed, applicability across a wide age range, and
provision of valuable data for student contextualisation. e time
diary with its 10-min interval scale allows triangulation both the
actimetry and the sleep diary facilitating the assessment of data
consistency. One of the cons is that the BADyG test requires a
signicant amount of time for application, leading to decreased
student attention due to fatigue towards the end if a break is
not schedule.
Ethics statement
e studies involving humans have been approved by Dr. Peset
Hospital Bioethics Committee, Valencia (Spain). e studies will
beconducted in accordance with the local legislation and institutional
requirements. Written informed consent will beobtained from the
participants and the participants' legal guardian/next of kin prior
to participation.
Author contributions
DG-E: Conceptualization, Funding acquisition, Methodology,
Supervision, Writing – original dra, Writing – review & editing,
Project administration, Visualization. DC-T: Methodology,
Visualization, Writing – original dra. BC-G: Methodology, Writing
– original dra. EM-G: Methodology, Writing – original dra. VM-C:
Methodology, Writing – original dra. LM: Methodology, Writing –
original dra. EM-B: Methodology, Writing – original dra. MG-C:
Methodology, Writing – original dra. MH-J: Writing – review &
editing. KT: Supervision, Writing – review & editing. MT: Writing –
review & editing. AA-A: Writing – review & editing. GS: Supervision,
Writing – review & editing. NE: Supervision, Writing – review &
editing. GP-A: Supervision, Writing – review & editing,
Conceptualization. CR: Methodology, Supervision, Writing – original
dra, Writing – review & editing, Conceptualization.
Funding
e author(s) declare that nancial support was received for the
research, authorship, and/or publication of this article. e publication
is part of the ‘Student chronotype (mis)match with school time
organisation: its eects on health, learning, time use and satisfaction
[Kairos]’ project and has beneted for the following support: Grant
PID2021-126846NA-I00 funded by MCIN/AEI/10.13039/501100011033
and by ERDF “A way of making Europe”, RC21-019-Recovery,
Transformation and Resilience Plan—funded by the European Union
Next Generation EU/PRTR, and COST Action CA 18236 ‘Multi-
disciplinary Innovation for Social Change’.
Acknowledgments
We would like to thank Ana Adan for her useful comments to a
previous version of the manuscript, Cynthia Little for her English
editing of the manuscript, Olga Minguez for her assistance with the
references management, and Alberto Pérez for his graphic
design assistance.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their aliated organizations,
or those of the publisher, the editors and the reviewers. Any product
that may be evaluated in this article, or claim that may be made by its
manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
e Supplementary material for this article can befound online
at: https://www.frontiersin.org/articles/10.3389/fpubh.2024.1336028/
full#supplementary-material
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 15 frontiersin.org
References
1. Klein J. Planning middle school schedules for improved attention and achievement.
Scand J Educ Res. (2004) 48:441–50. doi: 10.1080/0031383042000245825
2. Roenneberg T, Kumar CJ, Merrow M. e human circadian clock entrains to sun
time. Curr Biol. (2007) 17:R44–5. doi: 10.1016/j.cub.2006.12.011
3. Roenneberg T, Winnebeck EC, Klerman EB. Daylight saving time and articial time
zones – A Battle between biological and social times. Front Physiol. (2019) 10:944. doi:
10.3389/fphys.2019.00944
4. Gabaldón-Estevan D. A deshora en la escuela. Rev Sociol la Educ. (2021) 14:256–71.
doi: 10.7203/RASE.14.3.21626
5. Klerman EB, Brager A, Carskadon MA, Depner CM, Foster R, Goel N, et al.
Keeping an eye on circadian time in clinical research and medicine. Clin Transl Med.
(2022) 12:e1131. doi: 10.1002/ctm2.1131
6. Pin Arboledas G, Cubel Alarcón M, Martin González G, Lluch Roselló A, Morell
SM. Hábitos y problemas con el sueño de los 6 a los 14 años en la Comunidad
Valenciana. Opinión de los propios niños. An Pediatría. (2011) 74:103–15. doi:
10.1016/j.anpedi.2010.08.014
7. Reis C, Pilz LK, Kramer A, Lopes LV, Paiva T, Roenneberg T. e impact of
daylight-saving time (DST) on patients with delayed sleep-wake phase disorder
(DSWPD). J Pineal Res. (2023) 74:e12867. doi: 10.1111/jpi.12867
8. Martínez-Lozano N, Tvarijonaviciute A, Ríos R, Barón I, Scheer FAJL, Garaulet M.
Late eating is associated with obesity, inammatory markers and circadian-related
disturbances in school-aged children. Nutrients. (2020) 12:2881. doi: 10.3390/nu12092881
9. Martínez-Lozano N, Barraco GM, Rios R, Ruiz MJ, Tvarijonaviciute A, Fardy P,
et al. Evening types have social jet lag and metabolic alterations in school-age children.
Sci Rep. (2020) 10:16747. doi: 10.1038/s41598-020-73297-5
10. González-Carrasco M, Sáez M, Casas F. Subjective well-being in early adolescence:
observations from a ve-year longitudinal study. Int J Environ Res Public Health. (2020)
17:8249. doi: 10.3390/ijerph17218249
11. González-Carrasco M, Casas F, Malo S, Viñas F, Dinisman T. Changes with age in
subjective well-being through the adolescent years: dierences by gender. J Happiness
Stud. (2017) 18:63–88. doi: 10.1007/s10902-016-9717-1
12. Zerbini G, Merrow M. Time to learn: how chronotype impacts education. PsyCh
J. (2017) 6:263–76. doi: 10.1002/pchj.178
13. Rodríguez Ferrante G, Goldin AP, Sigman M, Leone MJ. A better alignment
between chronotype and school timing is associated with lower grade retention in
adolescents. npj Sci Learn. (2023) 8:21. doi: 10.1038/s41539-023-00171-0
14. Mullis IVS, Martin MO, Arora A. TIMSS 2011 international results in mathematics.
TIMSS & PIRLS Int Study Center. (2012)
15. Mullis IVS, Martin MO, Foy P, Drucker KT. PIRLS 2011 international results in
Reading. TIMSS & PIRLS Int Study Center. (2012)
16. Meijer AM. Chronic sleep reduction, functioning at school and school
achievement in preadolescents. J Sleep Res. (2008) 17:395–405. doi:
10.1111/j.1365-2869.2008.00677.x
17. Minges KE, Redeker NS. Delayed school start times and adolescent sleep: A
systematic review of the experimental evidence. Sleep Med Rev. (2016) 28:86–95. doi:
10.1016/j.smrv.2015.06.002
18. Kelley P, Lockley SW, Foster RG, Kelley J. Synchronizing education to adolescent
biology: ‘let teens sleep, start school later’. Learn Media Technol. (2015) 40:210–26. doi:
10.1080/17439884.2014.942666_1
19. Chan CS, Poon CYS, Leung JCY, Lau KNT, Lau EYY. Delayed school start time is
associated with better sleep, daytime functioning, and life satisfaction in residential
high-school students. J Adolesc. (2018) 66:49–54. doi: 10.1016/j.adolescence.2018.05.002
20. Carskadon M. When worlds collide: adolescent need for sleep versus societal
demands. Phi Delta Kappan. (1999) 80:348–53.
21. Suchaut B. L’organisation et l’utilisation du temps scolaire à l’école primaire: enjeux
et eets sur les élèves. Conférence à l’initiative la V Cran-Gevrier. (2009)
22. Suchaut B. Pour une nouvelle organisation du temps scolaire a l’école primaire.
(2012). Available from: https://shs.hal.science/halshs-00714043/document
23. Gabaldón-Estevan D, Taht K. e school schedule eect on self-reported sleep
length of children and youth in Spain. J Sleep Res. (2020) 29:180–0.
24. Clara MI, Allen GA. An epidemiological study of sleep−wake timings in school
children from 4 to 11 years old: insights on the sleep phase shi and implications for the
school starting times’ debate. Sleep Med. (2020) 66:51–60. doi: 10.1016/j.
sleep.2019.06.024
25. Estevan I, Silva A, Vetter C, Tassino B. Short sleep duration and extremely delayed
Chronotypes in Uruguayan youth: the role of school start times and social constraints.
J Biol Rhythms. (2020) 35:391–404. doi: 10.1177/0748730420927601
26. Rodríguez Ferrante G, Goldin AP, Sigman M, Leone MJ. Chronotype at the
beginning of secondary school and school timing are both associated with
chronotype development during adolescence. Sci Rep. (2022) 12:8207. doi: 10.1038/
s41598-022-11928-9
27. Rodríguez Ferrante G, Leone MJ. Solar clock and school start time eects on
adolescents’ chronotype and sleep: A review of a gap in the literature. US: John Wiley and
Sons Inc (2023).
28. Andrade MMM, Menna-Barreto L. Diurnal variation in Oral temperature,
sleepiness, and performance of high school girls. Biol Rhythm Res. (1996) 27:336–42.
doi: 10.1076/brhm.27.3.336.12966
29. Wolfson AR, Carskadon MA. Sleep schedules and daytime functioning in
adolescents. Child Dev. (1998) 69:875–87. doi: 10.1111/j.1467-8624.1998.tb06149.x
30. Gromada A, Shewbridge C. Student learning time: A literature review. OECD
Educ. (2016). doi: 10.1787/5jm409kqqkjh-en
31. Zerbini G, van der Vinne V, Otto LKM, Kantermann T, Krijnen WP, Roenneberg
T, et al. Lower school performance in late chronotypes: underlying factors and
mechanisms. Sci Rep. (2017) 7:4385. doi: 10.1038/s41598-017-04076-y
32. van der Vinne V, Zerbini G, Siersema A, Pieper A, Merrow M, Hut RA, et al.
Timing of examinations aects school performance dierently in early and late
chronotypes. J Biol Rhythms. (2015) 30:53–60. doi: 10.1177/0748730414564786
33. Pin G, Gradolí R, García G. Shastu sleep habits in Student’s performance. Final
Report. (2016). Available from: http://shastu.org/wp-content/uploads/2017/02/
SHASTU-FINAL-REPORT-ENGLISH_ok.pdf
34. French MT, Homer JF, Popovici I, Robins PK. What youdo in high school matters:
high school GPA, educational attainment, and labor market earnings as a young adult.
East Econ J. (2015) 41:370–86. doi: 10.1057/eej.2014.22
35. Arrona-Palacios A, Díaz-Morales JF, Parra-Robledo Z, Adan A. Sleep and
depressive symptoms in the Morningness/Eveningness-suicidal ideation relationship
depend on school shi in Mexican adolescents. J Clin Med. (2021) 10:4681. doi: 10.3390/
jcm10204681
36. Carvalho-Mendes RP, Dunster GP, de la Iglesia HO, Menna-Barreto L. Aernoon
school start times are associated with a lack of both social jetlag and sleep deprivation
in adolescents. J Biol Rhythms. (2020) 35:377–90. doi: 10.1177/0748730420927603
37. Estevan I, Silva A, Tassino B. School start times matter, eveningness does not.
Chronobiol Int. (2018) 35:1753–7. doi: 10.1080/07420528.2018.1504785
38. Roenneberg T. Internal time: Chronotypes, social jet lag, and why You’re so tired.
Cambridge, MA (USA): Harvard University Press (2012).
39. Eckel RH, Depner CM, Perreault L, Markwald RR, Smith MR, McHill AW, et al.
Morning circadian misalignment during short sleep duration impacts insulin sensitivity.
Curr Biol. (2015) 25:3004–10. doi: 10.1016/j.cub.2015.10.011
40. Garaulet M, Gómez-Abellán P. Timing of food intake and obesity: A novel
association. Physiol Behav. (2014) 134
41. Gabaldón-Estevan D, Obiol FS. Guía sobre tiempos escolares. Creat Educ Innov
Rev. (2017) 1:12–69. doi: 10.7203/CREATIVITY.1.12062
42. Testu F. Rythmes de vie et rythmes scolaires. aspects chronobiologiques et
chronopsychologiques Masson (2008).
43. Campbell A, Converse PE, Rodgers W. e quality of American life: Perceptions,
evaluations, and satisfactions. New York: Russell Sage (1976).
44. Arthaud-day ML, Rode JC, Mooney CH, Near JP. e subjective well-being
construct: A test of its convergent, discriminant, and factorial validity. Soc Indic Res.
(2005) 74:445–76. doi: 10.1007/s11205-004-8209-6
45. Metler SJ, Busseri MA. Further evaluation of the tripartite structure of subjective
well-being: evidence from longitudinal and experimental studies. J Pers. (2017)
85:192–206. doi: 10.1111/jopy.12233
46. Diener E. Subjective well-being. Psychol Bull. (1984) 95:542–75.
47. Herd SM. Synthesising hedonic and Eudaimonic approaches: A culturally
responsive four-factor model of aggregate subjective well-being for Hong Kong children.
Child Indic Res. (2022) 15:1103–29. doi: 10.1007/s12187-021-09901-5
48. Ryan RM, Deci EL. On happiness and human potentials: A review of research on
hedonic and eudaimonic well-being. Annu Rev Psychol. (2001) 52:141–66. doi: 10.1146/
annurev.psych.52.1.141
49. Strelhow MRW, Sarriera JC, Casas F. Evaluation of well-being in adolescence:
proposal of an integrative model with hedonic and eudemonic aspects. Child Indic Res.
(2020) 13:1439–52. doi: 10.1007/s12187-019-09708-5
50. Savahl S, Casas F, Adams S. e structure of Children’s subjective well-being. Front
Psychol. (2021) 12:691. doi: 10.3389/fpsyg.2021.650691/full
51. Kudielka BM, Federenko IS, Hellhammer DH, Wüst S. Morningness and
eveningness: the free cortisol rise aer awakening in “early birds” and “night owls”. Biol
Psychol. (2006) 72:141–6. doi: 10.1016/j.biopsycho.2005.08.003
52. Petrowski K, Schmalbach B, Stalder T. Morning and evening type: the cortisol
awakening response in a sleep laboratory. Psychoneuroendocrinology. (2020) 112:104519.
doi: 10.1016/j.psyneuen.2019.104519
53. Weidenauer C, Vollmer C, Scheiter K, Randler C. Weak associations of
Morningness-Eveningness and stability with skin temperature and cortisol levels. J
Circadian Rhythms. (2019) 17:8. doi: 10.5334/jcr.182
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 16 frontiersin.org
54. Kunz-Ebrecht SR, Kirschbaum C, Marmot M, Steptoe A. Dierences in cortisol
awakening response on work days and weekends in women and men from the
Whitehall II cohort. Psychoneuroendocrinology. (2004) 29:516–28. doi: 10.1016/
S0306-4530(03)00072-6
55. Miller GE, Cohen S, Ritchey AK. Chronic psychological stress and the regulation
of pro-inammatory cytokines: A glucocorticoid-resistance model. Health Psych ol.
(2002) 21:531–41. doi: 10.1037/0278-6133.21.6.531
56. Griefahn B, Künemund C, Golka K, ier R, Degen G. Melatonin synthesis: A
possible indicator of intolerance to shiwork. Am J Ind Med. (2002) 42:427–36. doi:
10.1002/ajim.10122
57. Liu X, Uchiyama M, Shibui K, Kim K, Kudo Y, Tagaya H, et al. Diurnal preference,
sleep habits, circadian sleep propensity and melatonin rhythm in healthy human
subjects. Neurosci Lett. (2000) 280:199–202. doi: 10.1016/S0304-3940(00)00793-X
58. Pandi-Perumal SR, Smits M, Spence W, Srinivasan V, Cardinali DP, Lowe AD, et al.
Dim light melatonin onset (DLMO): A tool for the analysis of circadian phase in human
sleep and chronobiological disorders. Prog Neuro-Psychopharmacology Biol Psychiatry.
(2007) 31:1–11. doi: 10.1016/j.pnpbp.2006.06.020
59. Keijzer H, Smits MG, Peeters T, Looman CWN, Endenburg SC, Gunnewiek JMTK.
Evaluation of salivary melatonin measurements for Dim Light Melatonin Onset
calculations in patients with possible sleep–wake rhythm disorders. Clin Chim Acta.
(2011) 412:1616–20.
60. Benloucif S, Burgess HJ, Klerman EB, Lewy AJ, Middleton B, Murphy PJ, et al.
Measuring melatonin in humans. J Clin Sleep Med. (2008) 4:66–9. doi: 10.5664/
jcsm.27083
61. Sletten TL, Vincenzi S, Redman JR, Lockley SW, R ajaratnam SMW. Timing of sleep
and its relationship with the endogenous melatonin rhythm. Front Neurol. (2010) 1:137.
doi: 10.3389/fneur.2010.00137
62. Duy JF, Wright KP. Entrainment of the human circadian system by light. J Biol
Rhythms. (2005) 20:326–38. doi: 10.1177/0748730405277983
63. Burgess HJ, Fogg LF. Individual dierences in the amount and timing of salivary
melatonin secretion. PloS One. (2008) 3:e3055. doi: 10.1371/journal.pone.0003055
64. Kennaway DJ. e dim lig ht melatonin onset across ages, methodologies, and sex
and its relationship with morningness/eveningness. Sleep. (2023) 46:zsad033. doi:
10.1093/sleep/zsad033
65. Axelsson J, Åkerstedt T, Kecklund G, Lindqvist A, Attefors R. Hormonal changes
in satised and dissatised shi workers across a shi cycle. J Appl Physiol. (2003)
95:2099–105. doi: 10.1152/japplphysiol.00231.2003
66. Ancoli-Israel S, Cole R, Alessi C, Chambers M, Moorcro W, Pollak CP. e role
of Actigraphy in the study of sleep and circadian rhythms. Sleep. (2003) 26:342–92. doi:
10.1093/sleep/26.3.342
67. Schoch SF, Kurth S, Werner H. Actigraphy in sleep research with infants and young
children: current practices and future benets of standardized reporting. J Sleep Res.
(2021) 30:e13134. doi: 10.1111/jsr.13134
68. Sadeh A, Lavie P, Scher A, Tirosh E, Epstein R. Actigraphic home-monitoring
sleep-disturbed and control infants and young children: A new method for pediatric
assessment of sleep-wake patterns. Pediatrics. (1991) 87:494–9.
69. Tirosh E. Eects of methylphenidate on sleep in children with attention-decit
hyperactivity disorder. Am J Dis Child. (1993) 147:1313–5.
70. Acebo C, Sadeh A, Seifer R, Tzischinsky O, Wolfson AR, Hafer A, et al. Estimating
sleep patterns with activity monitoring in children and adolescents: how many nights
are necessary for reliable measures? Sleep. (1999) 22:95–103.
71. Rodríguez-Morilla B, Martínez-Madrid MJ, Campos Martínez M, Rol de
Lama MA. Monitorización Circadiana Ambulatoria (MCA). Madrid: Kronoscore
(2021).
72. Ortiz-Tudela E, Martinez-Nicolas A, Campos M, Rol MÁ, Madrid JA. A new
integrated variable based on thermometry, Actimetry and body position (TAP) to
evaluate circadian system status in humans. PLoS Comput Biol. (2010) 6:e1000996. doi:
10.1371/journal.pcbi.1000996
73. Ortiz-Tudela E, Martinez-Nicolas A, Albares J, Segarra F, Campos M, Estivill E,
et al. Ambulatory circadian monitoring (ACM) based on thermometry, motor activity
and body position (TAP): A comparison with polysomnography. Physiol Behav. (2014)
126:30–8. doi: 10.1016/j.physbeh.2013.12.009
74. Ortiz-Tudela E, Martinez-Nicolas A, Díaz-Mardomingo C, García-
Herranz S, Pereda-Pérez I, Valencia A, et al. The characterization of biological
rhythms in mild cognitive impairment. Biomed Res Int. (2014) 2014:1–7. doi:
10.1155/2014/524971
75. Martinez-Nicolas A, Martinez-Madrid MJ, Almaida-Pagan PF, Bonmati-Carrion
M-A, Madrid JA, Rol MA. Assessing Chronotypes by Ambulatory Circadian Monitor ing.
Front Physiol. (2019) 10:1396. doi: 10.3389/fphys.2019.01396
76. Petersen R, Kaye WH, Gwirtsman HE. Comparison of calculated estimates and
laboratory analysis of food oered to hospitalized eating disorder patients. J AmDiet
Assoc. (1986) 86:490–2. doi: 10.1016/S0002-8223(21)03963-8
77. Fomon SJ, Nelson SE. Body composition of the male and female reference infants.
Annu Rev Nutr. (2002) 22:1–17. doi: 10.1146/annurev.nutr.22.111401.145049
78. Khoury M, Manlhiot C, McCrindle BW. Role of the waist/height ratio in the
Cardiometabolic risk assessment of children classied by body mass index. J AmColl
Cardiol. (2013) 62:742–51. doi: 10.1016/j.jacc.2013.01.026
79. Marfell-Jones M, Olds T, Stewar A, Carter LEL. ISAK manual, international
standards for anthropometric assessment. Int Society for the Advan Kinanthropometry.
(2012). doi: 10.1016/j.physbeh.2014.01.001
80. World Health Organization. Growth reference data for 5-19 years. BMI-for-age
(5-19 years) (2007). Available from: https://www.who.int/tools/growth-reference-data-
for-5to19-years/indicators/bmi-for-age
81. Santner A, Kopp M, Federolf P. Partly randomised, controlled study in children
aged 6–10 years to investigate motor and cognitive eects of a 9-week coordination
training intervention with concurrent mental tasks. BMJ Open. (2018) 8:e021026. doi:
10.1136/bmjopen-2017-021026
82. Yato Y, Hirose S, Wallon P, Mesmin C, Jobert M. d2-R test for Japanese adolescents:
concurrent validity with the attention decit-hyperactivity disorder rating scale. Pediatr
Int. (2019) 61:43–8. doi: 10.1111/ped.13735
83. Arboix-Alió J, Sagristà F, Marcaida S, Aguilera-Castells J, Peralta-Geis M, Solà J,
et al. Relación entre la condición física y el hábito de actividad física con la capacidad
de atención selectiva en alumnos de enseñanza secundaria. Cuad Psicol del Deport.
(2022) 22:1–13. doi: 10.6018/cpd.419641
84. Méndez-Giménez A, Pallasá-Manteca M. Efecto de los descansos activos sobre
procesos atencionales y la regulación motivacional en escolares. Apunt Educ Física y
Deport. (2023) 151:49–57. doi: 10.5672/apunts.2014-0983.es.(2023/1).151.05
85. Navarro Soria I, García Fernández JM, Inglés Saura CJ, Real FM. Early detection
of learning diculties using the BADyG-E2r battery during primary education. Psicol
Reexão e Crítica. (2020) 33:4. doi: 10.1186/s41155-020-00143-y
86. Lorca Garrido AJ, López-Martínez O, de Vicente-Yagüe Jara MI. Latent inhibition
as a biological basis of creative capacity in individuals aged nine to 12. Front Psychol.
(2021) 12:650541.
87. Csikszentmihalyi M. Flow: e psychology of optimal experience. New York: Harper
and Row (1990).
88. Chenu A, Lesnard L. Time use surveys: A review of their aims, methods, and
results. Eur J Sociol Eur Sociol. (2006) 47:335–59. doi: 10.1017/S0003975606000117
89. Gershuny J. Time-use surveys and the measurement of national well-being. Centre
for time-use research, Department of sociol. (2011)
90. Casas F. Subjective social indicators and child and adolescent well-being. Child
Indic Res. (2011) 4:555–75. doi: 10.1007/s12187-010-9093-z
91. Huebner ES. Initial development of the Student’s life satisfaction scale. Sch Psychol
Int. (1991) 12:231–40. doi: 10.1177/0143034391123010
92. Diener E, Emmons RA, Larsem RJ, Grin S. e satisfaction with life scale. J Pers
Assess. (1985) 49:71–5. doi: 10.1207/s15327752jpa4901_13
93. Seligson JL, Huebner ES, Valois RF. Preliminary validation of the brief
multidimensional students’ life satisfaction scale (BMSLSS). Soc Indic Res. (2003)
61:121–45. doi: 10.1023/A:1021326822957
94. Russell JA. Core aect and the psychological construction of emotion. Psychol Rev.
(2003) 110:145–72. doi: 10.1037/0033-295X.110.1.145
95. Feldman Barrett L, Russell JA. Independence and bipolarity in the structure of
current aect. J Pers Soc Psychol. (1998) 74:967–84.
96. Ry CD. Happiness is everything, or is it? Explorations on the meaning of
psychological well-being. J Pers Soc Psychol. (1989) 57:1069–81. doi:
10.1037/0022-3514.57.6.1069
97. Nahkur O, Casas F. Fit and cross-country comparability of Children’s worlds
psychological well-being scale using 12-year-Olds samples. Child Indic Res. (2021)
14:2211–47. doi: 10.1007/s12187-021-09833-0
98. Casas F, González-Carrasco M. Analysing comparability of four multi-item well-
being psychometric scales among 35 countries using Children’s worlds 3rd wave 10 and
12-year-olds samples. Child Indic Res. (2021) 14:1829–61. doi: 10.1007/
s12187-021-09825-0
99. Blasco-Belled A, González-Carrasco M, Casas F. Changes in the network structure
of well-being components in adolescents in the school context: A 2-year longitudinal
study. J Sch Psychol. (2024) 102:101255. doi: 10.1016/j.jsp.2023.101255
100. Cummins R. Normative life satisfaction: measurement issues and homeostatic
model In: B Zumbo, editor. Social indicators and quality of life research methods:
Methodological developments and issues Dordrecht, e Netherlands: Kluwer (2000)
101. Capic T, Li N, Cummins RA. Conrmation of subjective wellbeing set-points:
foundational for subjective social indicators. Soc Indic Res. (2018) 137:1–28. doi:
10.1007/s11205-017-1585-5
102. Cummins RA. Understanding the well-being of children and adolescents through
homeostatic theory In: A Ben-Arieh, F Casas, I Frønes and J Korbin, editors. Handbook
of child well-being. Dordrecht: Springer Netherlands (2014). 635–61.
103. Rees G, Savahl S, Lee BJ, Casas F. Children’s views on their lives and well-being in
35 countries: A report on the Children’s worlds project countries: A report on the Children’s
worlds project, 2016–19. Israel: Jerusalem (2020).
Gabaldón-Estevan et al. 10.3389/fpubh.2024.1336028
Frontiers in Public Health 17 frontiersin.org
104. World Health Organization. World medical association declaration of Helsinki.
JAMA. (2013) 310:2191. doi: 10.1001/jama.2013.281053
105. Beskow LM. Informed consent for population-based research involving genetics.
JAMA. (2001) 286:2315–21. doi: 10.1001/jama.286.18.2315
106. Reiter RJ, Tan D-X, Korkmaz A, Ma S. Obesity and metabolic syndrome:
association with chronodisruption, sleep deprivation, and melatonin suppression. Ann
Med. (2012) 44:564–77. doi: 10.3109/07853890.2011.586365
107. de Souza CM, Hidalgo MPL. e midpoint of sleep on working days: A measure
for chronodisruption and its association to individuals’ well-being. Chronobiol Int.
(2015) 32:341–8. doi: 10.3109/07420528.2014.979941
108. Owens J, Au R, Carskadon M, Millman R, Wolfson A, Braverman PK,
et al. Insufficient sleep in adolescents and young adults: an update on causes and
consequences. Pediatrics. (2014) 134:e921–32. doi: 10.1542/peds.2014-1696
109. Manoogian ENC, Panda S. Circadian rhythms, time-restricted
feeding, and healthy aging. Ageing Res Rev. (2017) 39:59–67. doi: 10.1016/j.
arr.2016.12.006
110. Takahashi JS. Transcriptional architecture of the mammalian circadian clock. Nat
Rev Genet. (2017) 18:164–79. doi: 10.1038/nrg.2016.150
111. Rijo-Ferreira F, Takahashi JS. Genomics of circadian rhythms in health and
disease. Genome Med. (2019) 11:82. doi: 10.1186/s13073-019-0704-0
112. López-Mínguez J, Gómez-Abellán P, Garaulet MTiming of Breakfast, Lunch, and
Dinner. Eects on obesity and metabolic risk. Nutrients. (2019) 11:2624.
113. Caride Gómez JA. A xornada escolar de sesión única en Galicia. Estudio
avaliativo: conclusións xerais e criterios de actuación. Consellería de Educación e
Ordenación Universitaria. (1993). eaau6200.
114. Asensio Aguilera JM. Cronobiología y educación In: P Fermoso Estébanez,
editor. El tiempo educativo y escolar: estudio interdisciplinar. Promociones y
Publicaciones Universitarias, PPU, Barcelona (1993). 75–110.
115. Estaun FS. Cronopsicología y educación In: P Fermoso Estébanez, editor. El
tiempo educativo y escolar: estudio interdisciplinar. Promociones y Publicaciones
Universitarias, PPU, Barcelona (1993). 111–52.
116. Dunster GP, de la Iglesia L, Ben-Hamo M, Nave C, Fleischer JG, Panda S, et al.
Sleepmore in Seattle: later school start times are associated with more sleep and better
performance in high school students. Sci Adv. (2018) 4:eaau6200. doi: 10.1126/sciadv.aau6200
117. Arrona-Palacios A, Díaz-Morales JF. Morningness–eveningness and sleep habits
at school: a comparative study between Mexico and Spain. Biol Rhythm Res. (2017)
48:175–88. doi: 10.1080/09291016.2016.1245459
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