Assessing Chronotype: A Complex and Multifaceted Approach
Article information
Abstract
Chronotype, a notion based on circadian rhythms, conceptualizes individual variability in sleep-wake cycles and preferred activities throughout a 24-hour period. Historically, self-reported sleep patterns have been used to determine chronotype, frequently ignoring important physiological and contextual elements including social habits, hormone cycles, and environmental influences. This article discusses the restrictions in the current chronotype models and in measuring instruments that rely on unidimensional frameworks. It puts forward a need for a holistic approach by integrating biological, social, and environmental components to enhance our understanding of chronotype. A suggested multidimensional model draws out the interaction between internal circadian systems and external influences and offers a better perspective. This integrated paradigm has the potential to improve chronobiological research and be used in clinical settings to treat chronotype-related illnesses. Future research directions aim to refine assessment tools and expand cross-cultural studies to fully capture the complexities of chronotype.
INTRODUCTION
Being diurnal creatures, humans usually sleep at night and are active throughout the day. However, industrialization has quickly altered sleep-wake patterns, resulting in excessive nighttime exposure to artificial light, television, and smartphones, irregular lifestyles, innovative eating habits, and a rise in the usage of stimulants like coffee in contemporary society. As a result, people now lead unpredictable lives, work shifts, adopt unusual eating patterns, and drink more coffee and other stimulants [1-4]. Due to social or occupational factors, people have been under tremendous pressure to modify their nocturnal rhythms in order to adapt to current lifestyles and trends. For all, such as healthcare professionals, drivers, and essential service providers, this causes a discrepancy between their professional obligations and their need for sleep, which is contributing to the rise of the chronically sleep-deprived world.
Taillard et al. [5] proposed that an individual’s timing of internal circadian rhythms, directed by the circadian clock, may be in sync or out of sync with their sleep timings based on their daily social interactions. They further suggestedthat a person’s preferred sleep schedule and time may be influenced by social factors. We refer to these sleep schedules or preferences that deviate from biological time as circadian disturbances. Furthermore, everyone has a different preference for sleep or wakefulness in a sleep-deprived world [5]. Over the past few decades, interest has steadily grown in the significance of diurnal preference and chronotype, and how disruptions caused by social factors affect our internal clock [6] but also has significant comorbidity with psychiatric diseases [7], neurodevelopmental disorders [8], cognitive dysfunction, and aberrant emotional processing [9].
In this context, it is crucial to ask if and to what degree a person’s chronotype and individual necessity or preference for sleep interact to affect different aspects of their physical and mental well-being, encompassing the framework and function of the brain. Prior to delving into the solution, it is advisable to determine the most thorough and practical model and chronotype metrics that may be applied in a worldwide study setting.
CIRCADIAN RHYTHMS
A diverse set of biological rhythms, which are cyclic changes in bodily chemicals or functions, can be observed in humans. These rhythms can occur multiple times a day, once every 24 hours, or take weeks to complete. These rhythms are found at various levels, from single cells to social behavior, and nearly all physiological and psychological functions vary in periodicity. Infradian and ultradian rhythms are biological patterns that vary in frequency and duration, affecting bodily chemicals and functions. Multiple instances of ultradian rhythms happen daily, while ultradian rhythms occur once every 24 hours. Infradian cycles, exemplified by the menstrual cycle, extend over weeks to reach completion. These rhythms manifest at various stages, spanning from cellular functions to social interactions, and are essential for maintaining physiological and psychological functions [10].
Circadian rhythms (CRs) are biological processes that operate on a 24-hour cycle, including chemical, physiological, and behavioral rhythms [11]. They are produced by an endogenous pacemaker or the biological timekeeper within the body or internal body rhythm, and they are influenced by environmental and external stimuli. The primary internal biological clock is located in the hypothalamic suprachiasmatic nucleus (SCN), which works closely with the pineal gland to regulate the sleep-wake cycle. The brain and other body cells include peripheral clocks, also known as circadian oscillators, which are genetically preprogrammed to produce CRs and are synchronized by the SCN. Endogenous CRs fluctuate in humans with significant intra-individual variability due to their periodic fluctuation in duration [11].
HUMAN BIOLOGICAL CLOCK
Humans, like many other photoperiodic creatures, have an intricate system for determining day and night duration, which is essential for the coordinated manifestation of physiological functions including body heat and cortisol secretion [12]. The notion of a conduit between the pineal gland and the human eye was first proposed by Descartes in 1662, which sparked interest in the process. Evidence of a multi-synaptic route linking the pineal gland and the SCN of the hypothalamus supports this 17th-century theory [12-14] and demonstrates how the SCN is essential for controlling several endocrine, physiological, and behavioral CRs [15]. The paraventricular nucleus in the retinal ganglion cells detects natural or artificial light signals, which are then sent to the spinal cord. After that, this data is sent to the thoracic spinal cord’s intermediolateral column, where second-order sympathetic fibers and primary sympathetic neurons, respectively, project to the pineal gland and superior cervical ganglion. Norepinephrine, which is released by these nerve fibers, synapses with the surface of pinealocytes to convert serotonin into melatonin, which promotes sleep. Sleep maintenance depends on this mechanism [12,16].
CHRONOTYPE
Chronotype should be defined as both a behavioral preference and a biological trait [11,17-20]. As a behavioral preference, chronotype refers to an individual’s preferred timing of sleep and activity, ranging from morning types to evening types. As a biological trait, chronotype is related to the endogenous circadian rhythm, influenced by factors such as clock genes, cortisol, and melatonin levels [21,22].
Internal and external factors influence chronotype
Internal factors include an individual’s biological clock and its associated hormones [18,22,23]. External factors include the light-dark cycle, temperature, social habits, and geographical location [11,24-27]. For example, exposure to sunlight can affect the circadian rhythm [28,29]. The influence of latitude and longitude has been noted to affect chronotype with eveningness increasing with distance from the equator and morningness increasing in eastern locations.
It is important to clarify the specific measures of chronotype being used in any study. The most common method is self-report questionnaires such as the Morningness–Eveningness Questionnaire (MEQ). The MEQ assesses sleep/wake times, preferred times for activities, and subjective alertness. The Munich ChronoType Questionnaire (MCTQ) is another method that uses specific times for bed, sleep latency, and wake time on both workdays and free days to measure chronotype. Researchers should also consider that some scales focus on preferred times for activities, while others focus on specific sleep times when choosing a measurement.
Chronotype is not static; it has a dynamic nature throughout an individual’s lifespan [30]. There is a general tendency for a delay in the circadian rhythm during adolescence and early adulthood compared to childhood and later adulthood. Chronotype may shift towards eveningness in adolescence and then back towards morningness in older age.
It is important to recognize that the timing of sleep, duration of sleep, and chronotype are all independent in humans [25,31,32]. Although these factors are independent, they influence each other. The timing of sleep is an important component of the entrainment process and can be used to study chronotype [2]. The midpoint of sleep on free days (MSF), corrected for sleep debt (MSFsc), is a reliable marker of the phase of entrainment.
Geographical location should be considered when comparing different populations, as it can influence chronotype [23,33]. Latitude and longitude can affect an individual’s chronotype, and this may account for observed differences across populations.
When examining chronotype, it is important to differentiate between workdays and free days [2,23,34]. Most people accumulate sleep debt during workdays and compensate for it on days off [2,31]. This distinction is important when assessing sleep patterns and chronotype. Sleep times are remarkably stable on free days.
Future studies should include both subjective and objective data. Subjective data can be collected through questionnaires. Objective measures could include actigraphy [35], polysomnography, and dim light melatonin onset [35-37]. Collecting both types of data can help researchers better understand the construct of chronotype.
Hence, assessing chronotype involves considering a wide range of dimensions. These diverse factors contribute to a comprehensive understanding of individual differences. Table 1 presents a detailed overview of these numerous dimensions.
Chronotype assessment methods categorized by key dimensions (biological, social, environmental, or behavioral factors)
Researchers should consider both the physiological and psychological markers of chronotype when choosing a measure for a specific research question [23,38]. For example, the MEQ assesses behavioral preferences, while the MCTQ is thought to provide a more objective measure based on sleep behavior.
Further research is needed to better understand the nature of chronotype and its relationship with various health outcomes [20,31,33]. More research is needed to understand the relationship between chronotype and mental health and other health outcomes, as well as the effects of shift work on chronotype and sleep [39]. There is also a need to investigate interventions to shift the circadian rhythms of people, particularly evening types, who may experience mental health problems.
Chrono-disruption and its health consequences
Any disruption that affects circadian activities, including hormone release and heart rate [40] or the 24-hour wakefulness and sleep pattern, is referred to as “disrupted CRs” or chrono-disruption in an undefined general phrase. The circadian clock is disrupted by a variety of circumstances, such as lifestyle, jet lag, exposure to light before bed, working shifts, and stimulant consumption. Notably, hormone secretion and sleep-wake cycle misalignment or disturbance can have detrimental effects on a person’s physical and mental well-being. According to recent research, disturbed CRs raise the likelihood of developing and making a number of illnesses worse, such as neurodegenerative diseases [41,42], neurodevelopmental disorders [43], and mental disorders like mood disorders and schizophrenia. It is commonly known that disturbed CRs, poor sleep, and a weakened human immune system are all related [44]. Additionally, it has been hypothesized that the virus suppresses the melatonin rhythm and modifies circadian gene activity timing, leading to misalignment and an increase in the expression of harmful inflammatory cytokines [45].
According to Zerón-Rugerio et al. [46], the innate rhythm governing the sleep-wake cycle in healthy individuals is synchronized along changes in the day and night cycle as well as other variables, such as everyday practices and meal time. Maintaining good sleep and waking patterns requires this kind of synchronization since any deviations or misalignments can result in a variety of cognitive, emotional, and sleep-related issues.
Historical perspective of chronotype
Individual variations in self-report questionnaires and CRs have been studied since the early 1870s and up to 1900. The importance of the sleep-wake cycle in the increase and decrease of body temperature was proven. This was further supported by a study in which the sample was categorized into morning and evening workers. Researchers distinguished between two groups of people: those who function well at night, sleep later, and reach their deepest sleep later, and those who feel exhausted at night, sleep earlier, and achieve their deepest sleep earlier. According to the researcher, those who sleep in the morning and those who sleep in the evening react differently to sleep deprivation, with the latter finding it more difficult to endure.
Based on 135 studies [38], a categorization of CRs was developed. However, this division was disputed by Kleitman in his book Sleep and Wakefulness [47], who claimed that it was based on research with small sample sizes. Rather, Kleitman divided people into two general categories: morning types, who had early peaks in their performance and temperature, and evening types, who had later peaks. He also identified a category of intermediate types. According to Putilov [48], MEQ, which distinguished between morning and evening circadian preferences, helped popularize this categorization [48]. In order to examine the CRs of food consumption and oral temperature in morning and evening chronotypes [49], the MEQ scoring method was modified to refine participant classification based on diurnal preferences. In a scientific study, this categorization was the first to be extensively used to conceptualize diurnal preferences. Nonetheless, the words “chronotype” and “diurnal preference” have been used interchangeably by several researchers, which is a fallacy.
Chronotype is a concept that represents an individual’s natural rhythm of activity and rest preferences over a day, influenced by biological CRs. According to Adan et al. [11], chronotype reflects how people differ in their tendency to be active or at rest at certain times within a 24-hour period. This preference is influenced by various physiological rhythms, including body temperature, hormonal and metabolic levels, cognitive functions, as well as eating and sleeping patterns [50].
These biological rhythms tend to follow a regular distribution within the population, meaning most people fall around an average pattern, with fewer people being extreme “morning” or “evening” types. Additionally, some studies [19,27,28,51,52] highlight that these rhythms remain consistent across different geographical regions and cultures, even when assessed using varied tools or measurement scales.
In recent decades, research on chronotypes has gained significant interest. However, this construct has not always been thoroughly integrated into some theoretical models or reliably measured in many earlier studies. Self-report scales address this issue, highlighting that certain models and tools may lack comprehensive approaches to assessing chronotype. As noted by Kerkhof [51], a lack of standardization in chronotype questionnaires and analytic methods has made it difficult to directly compare findings across studies. Additionally, the most widely used self-report chronotype scales mainly measure sleep patterns, overlooking other non-sleep-related biological rhythms and the impact of social or external factors on an individual’s chronotype [50], which we will explore further in the next section.
COMMONLY USED TOOLS FOR ASSESSING CHRONOTYPE
The MEQ, developed by Horne and Ostberg in 1976 [53], was the first validated tool to measure an individual’s morningness–eveningness tendencies or phase preference. This questionnaire classifies individuals into one of three chronotypes: 1) morning type (Larks): people who prefer early bedtimes and rise times, with a tendency to schedule activities earlier in the day; 2) evening type (Owls): people who prefer to sleep and wake later, aligning their activities with later hours; and 3) intermediate type (none of the type): individuals who show flexibility and do not strongly align with either Larks or Owls preferences.
The MEQ includes 14 multiple-choice questions and five open-ended questions that use a Likert scale format to gauge preferences (e.g., “What time would you get up if you were entirely free to plan your day?”). The questions focus on preferred timings for sleep-wake cycles, as well as mental and physical activities and levels of alertness.
Scores on the MEQ range from 16 to 86, where: 16–41 indicates an evening preference, 59–86 reflects a morning preference, and 42–58 represents an intermediate type (neither morning nor evening oriented).
In the initial validation of the MEQ [19,54], conducted with a student sample aged 18–32, the results showed that body temperature peaked significantly earlier in morning types compared to evening types, while intermediate types displayed peak temperatures between these groups. In this sample, 62.1% were classified as morning types, waking an average of 114 minutes earlier than evening types, 36.6% were intermediate types, and only 2.2% were evening types, who went to bed 99 minutes later than morning types.
Later, Taillard et al. [55] suggested updated MEQ cut-off scores based on a study of middle-aged French workers (n=566). They found that a bedtime of 11:30 PM, which might indicate morningness in students, could instead suggest eveningness in adults aged 40–50. They proposed the following MEQ cut-offs: scores 16–53, evening preference; scores 64–86, morning preference; and scores 54–63, no preference (intermediate type).
Using these criteria, they classified 20.2% as evening types, 28.15% as morning types, and 51.7% as intermediate types within their sample.
Studies across various countries consistently report the MEQ as a reliable measure, with internal consistency coefficients between 0.77 and 0.86 [14,27,56,57]. Additionally, it shows strong split-half reliability (0.80) [27] and high test-retest reliability, with coefficient ranges of 0.80–0.95 [51,58].
Several studies incorporated measurable circadian phase indicators, such as body temperature [59], as well as levels of melatonin and cortisol [24,60]. These physiological markers have been found to align well with MEQ scores, indicating that individuals’ reported chronotype preferences correspond to biological indicators of their circadian rhythms. “The MEQ itself has shown high internal consistency, with a Cronbach’s alpha of 0.83” [26]. Additionally, studies report medium-to-large correlations between MEQ scores and these circadian phase markers, supporting the MEQ’s validity in capturing actual physiological patterns of morningness and eveningness [61].
Adan and Almirall [62] developed a shortened version of the original 19-item MEQ, called the Reduced MEQ (rMEQ), which consists of five key self-report items. The first three items prompt individuals to indicate the time of day when they: 1) feel their best, 2) prefer to wake up, and 3) prefer to go to bed. The fourth item assesses the level of tiredness experienced within the first 30 minutes after waking, while the fifth item asks about overall morningness and eveningness preferences.
The rMEQ has proven to be a fast and reliable tool, showing good convergent validity with other measures of chronotype [56]. However, it has relatively low inter-item correlations, with Cronbach’s alpha ranging from 0.08 to 0.46, indicating weaker internal consistency among its items [63].
The Composite Scale of Morningness (CSM), introduced by Smith et al. [64], is a widely used 13-item self-report instrument designed to evaluate an individual’s preferences for various activities, including sleep-wake patterns. They developed the CSM by selecting items through factor analysis from the MEQ by Horne and Ostberg [53] and the Circadian Type Questionnaire by Folkard et al. [65]. It is noteworthy that nine of the items in the CSM are adapted from the MEQ.
The CSM scores range from 13 to 55, with lower scores (≤22) indicating an evening preference, higher scores (≥44) indicating a morning preference, and scores between 23 and 43 indicating an intermediate type. The scale has demonstrated strong reliability [66] with high internal consistency (α=0.87) and psychometric properties comparable to those of the MEQ and the Diurnal Type Scale (DTS). However, the original factor structure proposed by Smith and colleagues [64,67] was not fully replicated in a later study [64], with subsequent research suggesting one-, two-, or three-factor solutions [66,68-70].
Kim and Lee [71] validated the 6-item Evening Chronotype Scale (ECS), a modified version of CSM, by reverse coding six CSM items to assess eveningness. The study evaluated its psychometric properties, validity, and reliability in 472 mood disorder patients (major depressive disorder, bipolar I, and bipolar II). The ECS showed moderate to good internal consistency (Cronbach’s alpha=0.727) and external validity similar to the full 13-item CSM. Evening-oriented individuals had later sleep-wake times, longer sleep latency, more depressive/hypomanic symptoms, lower quality of life, and higher impulsivity. The study highlights the importance of assessing circadian preferences in clinical settings and supports the ECS as a reliable and valid tool for measuring eveningness.
The MCTQ, developed by Roennerberg et al. [32], is a self-report tool that differentiates between individuals’ sleep and wake times on both workdays and free days, allowing a detailed view of these patterns. This distinction between work and free days is one of the MCTQ’s defining features. Chronotype is assessed by calculating the midpoint between sleep onset and offset, adjusted to account for oversleep accumulated during the workweek [72].
According to Roenneberg et al. [73], most individuals, except early chronotypes, display significant differences in sleep timing between work and free days, typically accumulating a sleep deficit on workdays. The MCTQ, therefore, provides a quantitative measure of chronotype based on sleep behaviors rather than preferences and gives population-specific distributions for early and late chronotypes.
MCTQ scores show meaningful correlations with chemical markers such as melatonin [74] and cortisol, as well as behavioral measures like actigraphy [35] and sleep log [75]. Additional versions of the MCTQ have been developed, including the MCTQ Core [72,76] and MCTQ Shift Work [31], which include extra items, such as those related to substance use.
LIMITATION OF ASSESSMENT
Many self-report questionnaires assessing chronotype are well-researched, reliable, and widely used. Instruments like the MEQ and the MCTQ are even considered gold standards in chronotype assessment due to their reliability and validity. However, they still have limitations, which will be discussed further.
The CSM, for instance, derives about two-thirds of its items from the MEQ, potentially inheriting some of its limitations. One specific issue with the MEQ is the inconsistency in scoring across studies. Horne and Ostberg [53] did not provide a clear explanation for certain item weights, such as scoring item 11 as 6, 4, 2, 0, while item 12, which asks about tiredness at 11 PM, uses a different scale: 0, 2, 3, 5 [56]. This inconsistency raises concerns about the validity and reliability of the scoring system across different studies.
Psychometric issues
Several studies have raised concerns about the weak inter-item correlation range of the auto MEQ, which falls between 0.20 and 0.40 [14,27], challenging the assumption that the MEQ is a unidimensional measure of chronotype.
The CSM has demonstrated high convergent and construct validity when compared to the MEQ, which is expected since the CSM and MEQ share nine common items. Despite this, the predictive validity of both the MEQ and CSM has rarely been tested, leaving questions about their ability to predict real-world outcomes or behaviors related to chronotype.
Cut-off values
The threshold values established for the original auto MEQ [19] were based on a student sample aged 18 to 32 years. However, subsequent studies have demonstrated that these cut-offs can vary significantly across different various age categories and cultural contexts [26,55]. In addition, when comparing the frequency of morningness and eveningness using the MEQ scores from Horne and Ostberg’s version [53], morning types were found to be more prevalent, as reported by Paine et al. [26]. This suggests that the MEQ’s categorization of chronotypes may not be universally applicable and may need adjustment based on demographic factors like age and culture.
Social and work schedules excluded
Individuals often adjust their sleep patterns based on work schedules, but the auto MEQ does not account for its variability. This limitation extends to the CSM, which is based on the MEQ, raising concerns about its psychometric adequacy. As Roenneberg et al. [32] pointed out, the MEQ fails to distinguish between workdays and free days, and none of its items inquire about actual sleep times or factors like exposure to outdoor light, which can influence sleep patterns [48]. This oversight limits the ability of the MEQ and CSM to capture the full complexity of chronotype, particularly in individuals whose sleep preferences are influenced by external factors such as work schedules and environmental cues.
Overlooking the impact of demographic and socio-cultural factors
Both the MEQ and the CSM fail to sufficiently consider the influence of geographical location, cultural practices, and variations in sleep habits on chronotype. These factors can significantly influence sleep preferences and timing. For example, afternoon dozing periods are common in Asian, Mediterranean, and American cultures, but are not as frequent in Western societies [77]. Additionally, in developed nations in the West, people tend to prefer sleeping in a climate-controlled, quiet, and dark environment, whereas these preferences may vary in underdeveloped regions or indigenous populations. These cultural and environmental differences can affect sleep phases and, consequently, the distribution of MEQ scores across regions.
For instance, studies have shown that Spanish students are classified as larks types than young learners from Italy [25], despite both groups being from relatively similar geographical locations. This difference can be attributed to cultural practices, standards, and ways of living. Randler et al. [78] found that Indian learners tend to be larks than their German and Slovakian counterparts. Differences in sleep-wake behavior were also reported between Japanese and Korean students, with the former showing significantly higher MEQ scores [79]. These variations could be influenced by cultural practices, climate, and societal habits.
Moreover, factors such as age [55,80], sex [81,82], and eating habits [83] are often not fully considered when analyzing the impact of demographic and socio-cultural factors on MEQ scores, even though they are sometimes included as covariates. These factors underscore the importance of conducting additional cross-cultural studies and developing a more sophisticated, multidimensional perspective on chronotype.
Limitation of MCTQ
The MCTQ was developed to address some of the limitations of the MEQ by focusing on actual sleep-wake behavior rather than preferences. It takes into account sleep timings on both workdays and free days, which is a key feature of this tool. The MCTQ is often used in genetic and epidemiological studies and helps quantify an individual’s chronotype by calculating the midpoint between sleep onset and offset, adjusted for sleep deficits accumulated during workdays. This provides a more accurate reflection of an individual’s chronotype based on real sleep patterns, as opposed to self-reported preferences. It is widely used in hereditary and health related studies. However, this questionnaire still has notable weaknesses.
First limitation is that it does not account for chronological behaviors such as eating schedules or social routines, which can influence an individual’s chronotype. Secondly, the MCTQ’s scoring and calculation depend on fixed work schedules, which limits its applicability to populations with more flexible or unpredictable work hours, such as freelancers or content creators. Thirdly, the MCTQ may not be suitable for populations, where time is not conceptualized through a metric-based framework. This is particularly true for indigenous tribes across the globe, where time perception and daily rhythms may not align with the conventional time metrics used in the MCTQ [84,85]. Lastly, while circadian rhythms influence sleep timing, it is also regulated by homeostatic oscillators [77], which are not considered in the MCTQ. In contrast to the MEQ, which involves elements related to sleep equilibrium such as the gradual buildup of sleep pressure [21,55], the MCTQ does not account for these homeostatic influences on sleep timing.
ENHANCING THE ASSESSMENT OF CHRONOTYPE
Chronotype is a concept that has been understood and defined in various ways, leading to differing views on how it should be measured. “Chronotype generally refers to an individual’s preference for rest and activity within a 24-hour cycle” [11], but this broad definition encompasses a wide range of biological and psychological processes. Consequently, different researchers have chosen to focus on different aspects of chronotype to suit their conceptualization.
For instance, Horne and Ostberg [53] conceptualized chronotype as a “psychological construct,” focusing on the individual’s subjective preferences for sleep-wake patterns and activity levels. On the other hand, Levandovski et al. [50] defined chronotype as an “attribute” of an individual that reflects their sleep-wake cycle phase, emphasizing a biological perspective.
Roenneberg et al. [86] took this biological view further, proposing that chronotype should be seen as a “biological construct” aligned with the idea of “temporal behavior” or “temporal phenotype” [87], highlighting its inherent connection to an individual’s circadian rhythms. Other perspectives describe chronotype as a “dichotomous human trait” [72], or a “behavioral manifestation” and “inherited trait,” underscoring its potential genetic basis and its role as a trait that influences behavioral patterns.
These varying perspectives demonstrate that the construct of chronotype is not only complex but also multifaceted, with researchers from different disciplines interpreting and measuring it in ways that best suit their specific research aims.
The concept of chronotype is indeed multifaceted, and this complexity is reflected in the various models and definitions proposed by researchers. These differing definitions create challenges, particularly when it comes to measuring chronotype, as the measures used may not fully capture its diverse aspects.
For example, as previously mentioned, the MEQ focuses on psychological preferences, specifically assessing an individual’s diurnal preference or the preferred timing for activities like sleep and wakefulness. In contrast, the MCTQ emphasizes actual sleep timings, categorizing individuals into morning, evening, or intermediate chronotypes based on when they sleep on both work and free days.
Many other self-report questionnaires, such as the rMEQ, the CSM (circadian type scale), and MCTQ Core, similarly focus primarily on the sleep dimension of chronotype, often neglecting other important factors. These measures primarily assess sleep patterns without considering physiological markers (such as body temperature, melatonin, or cortisol rhythms) that could offer a more comprehensive understanding of an individual’s chronotype. Furthermore, these tools may overlook external influences, such as social habits, work schedules, and geographical or cultural differences, which can also play a significant role in shaping an individual’s circadian rhythm.
Hence, the reliance on these single-dimensional measures can lead to a mismatch between an individual’s reported chronotype (based on preferences or self-reported sleep data) and their actual biological chronotype (as indicated by physiological markers or behavior). This discrepancy further complicates the accuracy and comprehensiveness of chronotype assessments, highlighting the need for more integrated and multidimensional approaches that consider both subjective and objective factors influencing circadian rhythms.
CONCLUSIONS AND FUTURE DIRECTIONS
The growing body of evidence highlights that “chronotype” not only varies between individuals, but it is also significantly shaped by a variety of environmental, social, and personal factors. This is essential to recognize the complexity of these factors—such as way of life, geographic context, personality features, use of drugs, work routines (freelancing, shift work, regular work, remote work), eating habits, and weight issues—when assessing an individual’s chronotype. Understanding these influences is crucial for developing a more accurate representation of chronotype, beyond sleep preferences alone.
Existing chronotype models, self-assessments, and evidence-based research have significantly deepened our comprehension of the “role of chronotype,” particularly in the context of disrupted CRs and their consequences. However, much of the existing chronotype research has been based on a somewhat simplistic view, primarily focusing on sleep-related aspects of chronotype. This narrow focus may limit the depth of insight into how chronotype influences broader health and well-being.
Building on these insights, it is essential to optimize the chronotype construct through a multifaceted model. In light of these limitations, we propose a more comprehensive, multidimensional model of chronotype, which incorporates a wider range of factors. This model would take into account not only sleep timing and preferences but also variables such as age, health, and other socio-cultural and individual factors. By expanding our understanding of chronotype in this way, future research can better address the complexities of chronotype and its disruptions, offering more tailored and effective strategies for improving health and performance outcomes across different populations.
Notes
The authors have no potential conflicts of interest to disclose.
Availability of Data and Material
Data sharing not applicable to this article as no datasets were generated or analyzed during the study.
Author Contributions
Conceptualization: Yogita Kalra. Data curation: Yogita Kalra. Formal analysis: Yogita Kalra. Investigation: Yogita Kalra. Methodology: Yogita Kalra. Project administration: Yogita Kalra. Resources: Yogita Kalra. Supervision: Prabhjyot Kour. Validation: Yogita Kalra. Visualization: Yogita Kalra. Writing—original draft: Yogita Kalra. Writing—review & editing: Yogita Kalra.
Funding Statement
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Acknowledgements
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