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The impact of morningness–eveningness on depression through a serial mediation model of resilience and anxiety

Published online by Cambridge University Press:  27 May 2024

Suhyeon Kang
Affiliation:
Department of Psychology, Kyungpook National University, Daegu, Republic of Korea
Huiyeong Kim
Affiliation:
Department of Psychology, Kyungpook National University, Daegu, Republic of Korea
Hyeona Yu
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
Daseul Lee
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
Hyuk Joon Lee
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
Tae Hyon Ha
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
Jungkyu Park*
Affiliation:
Department of Psychology, Kyungpook National University, Daegu, Republic of Korea
Woojae Myung*
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
Hyo Shin Kang*
Affiliation:
Department of Psychology, Kyungpook National University, Daegu, Republic of Korea
*
Corresponding authors: H. S. Kang; Email: [email protected]; J. Park; Email: [email protected]; W. Myung; Email: [email protected]
Corresponding authors: H. S. Kang; Email: [email protected]; J. Park; Email: [email protected]; W. Myung; Email: [email protected]
Corresponding authors: H. S. Kang; Email: [email protected]; J. Park; Email: [email protected]; W. Myung; Email: [email protected]
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Abstract

Objective:

Resilience has been recently considered one of the possible mechanisms for the association between morningness–eveningness and depression. Meanwhile, anxiety is closely associated with mood disorder, but its association with morningness–eveningness is unclear. Therefore, this study aimed to explore the mediating effects of resilience and anxiety on morningness–eveningness and depression as the possible mechanisms.

Methods:

This study included patient group and nonpatient group. Patient group consists of 743 patients with mood disorders [Major Depressive Disorder (MDD), 233; Bipolar Disorder I (BDI), 113; Bipolar Disorder II (BDII), 397] whereas nonpatient group consists of 818 individuals without mood disorder. The Composite Scale of Morningness, Connor–Davidson Resilience Scale, Self-Rating Depression Scale, and Beck Anxiety Inventory were used to evaluate morningness–eveningness, resilience, anxiety, and depression, respectively.

Results:

Our model provided a good fit for the data. The association between morningness–eveningness and depression symptoms was partially serially mediated by resilience and anxiety in both the patient and nonpatient groups. The patient group exhibited significantly stronger morningness–eveningness toward resilience and anxiety than the nonpatient group. In the indirect effect of morningness–eveningness on depression, group differences exist only through each mediation of resilience and anxiety, not through serial mediation.

Conclusion:

Our results expand on the mechanism underlying the association between morningness–eveningness and depression. They highlight the importance of morningness–eveningness modification to increase resilience and the need to consider anxiety jointly in this process.

Type
Original Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Scandinavian College of Neuropsychopharmacology

Significant outcomes

  • This study expanded underlying mechanisms between morningness–eveningness and depression with resilience and anxiety.

  • Resilience and anxiety individually and sequentially mediate between morningness–eveningness and depression in both the patient of mood disorder and the general population.

  • The patient group has stronger paths not only between morningness–eveningness and resilience but between morningness–eveningness and anxiety than the nonpatient group.

Limitations

  • Demographic data of the general population were not collected except sex and age.

  • BDI samples were less compared with those of MDD and BDII patients in patient group.

Introduction

Circadian rhythm refers to biological and behavioural human functions, including sleep–wake patterns, hormone secretion, body temperature moderation, and socialisation. These variances are influenced by morningness–eveningness preference, which can be classified into three typologies: morning, intermediate (or neither), and evening (Roenneberg et al., Reference Roenneberg, Daan and Merrow2003; Adan et al., Reference Adan, Archer, Hidalgo, Di Milia, Natale and Randler2012). In the past 20 years, interests in the investigation of chronotypes have increased and many researchers have explored the effect of morningness–eveningness on mental health issues (Natale et al., Reference Natale, Ballardini, Schumann, Mencarelli and Magelli2008; Broms et al., Reference Broms, Kaprio, Hublin, Partinen, Madden and Koskenvuo2011; Lin & Gau, Reference Lin and Gau2013), particularly depression (Fares et al., Reference Fares, Hermens, Naismith, White, Hickie and Robillard2015). Patients with any type of mood disorder tend to exhibit more delayed circadian rhythms, showing preference for eveningness, than nonpatients (Au & Reece, Reference Au and Reece2017; Meyrel et al., Reference Meyrel, Scott and Etain2022). Previous studies have demonstrated that patients with eveningness preferences tend to experience higher level of depression (Hasler et al., Reference Hasler, Buysse, Kupfer and Germain2010; Seo et al., Reference Seo, Yeom, Cho, Son, Ahn, Kim, Ha, Cha, Moon, Park, Baek, Kang, An and Lee2022), increased suicidality (Chan et al., Reference Chan, Lam, Li, Yu, Chan, Zhang and Wing2014), and more severe circadian rhythm disorders (Mondin et al., Reference Mondin, de Azevedo Cardoso, de Mattos Souza, Jansen, da Silva Magalhães, Kapczinski and da Silva2017) compared with morningness preferences. These results were consistent even after controlling for sleep-related factors (Kitamura et al., Reference Kitamura, Hida, Watanabe, Enomoto, Aritake-Okada, Moriguchi, Kamei and Mishima2010; Chan et al., Reference Chan, Lam, Li, Yu, Chan, Zhang and Wing2014; Antypa et al., Reference Antypa, Vogelzangs, Meesters, Schoevers and Penninx2016b).

Despite the association between morningness–eveningness and mood disorder, the underlying mechanisms for the association between them have not been fully established. Among the potential variables for the aforementioned association, resilience has recently gained increasing attention (Chung et al., Reference Chung, Choi, Kang, Jung and Joo2018). Resilience is a positive ability of an individual to effectively adapt to and overcome adversity (Fletcher & Sarkar, Reference Fletcher and Sarkar2013). A higher level of this positive ability is associated with lesser depression symptoms (Wermelinger Ávila et al., Reference Wermelinger Ávila, Lucchetti and Lucchetti2017) and lower suicidal risks (Sher, Reference Sher2019). In terms of the mechanism variance, previous studies have demonstrated that eveningness is associated with lower resilience (Antúnez et al., Reference Antúnez, Navarro and Adan2015; Lee et al., Reference Lee, Park, Kim, Lee, Cha, Lee, Soh, Park, Park and Song2016; Chung et al., Reference Chung, Choi, Kang, Jung and Joo2018) and even indirectly affects depression symptoms through the mediation (Palagini et al., Reference Palagini, Miniati, Marazziti, Massa, Grassi and Geoffroy2022) or moderation (Zhou et al., Reference Zhou, Hsiao, Shi, Yang, Huang, Jiang, Zhang and Ma2021) of resilience.

Depression exhibited high comorbidity with anxiety, and mood disorder accompanied by anxiety symptoms often resulted in worse prognosis, longer recovery time, and greater risks of suicide when compared with mood disorder alone (Goldberg & Fawcett, Reference Goldberg and Fawcett2012). Furthermore, anxiety symptoms, along with depression, have been shown to be lesser if resilience increases (Hjemdal et al., Reference Hjemdal, Vogel, Solem, Hagen and Stiles2011; Shin et al., Reference Shin, Kim, Kim, Min, Yoo, Kim and Jeon2019). However, most previous studies that have identified the indirect effects of resilience on morningness–eveningness and depression did not consider anxiety severity (Zhou et al., Reference Zhou, Hsiao, Shi, Yang, Huang, Jiang, Zhang and Ma2021; Palagini et al., Reference Palagini, Miniati, Marazziti, Massa, Grassi and Geoffroy2022). Therefore, further study on this matter is warranted.

Although the association between morningness–eveningness and resilience is generally consistent between prior studies, the association between the former and anxiety has not been firmly established. Existing evidence suggest that eveningness is associated with anxiety disorder (Lemoine et al., Reference Lemoine, Zawieja and Ohayon2013; Fares et al., Reference Fares, Hermens, Naismith, White, Hickie and Robillard2015). However, some studies have reported that eveningness and anxiety disorder do not have an association (Antypa et al., Reference Antypa, Vogelzangs, Meesters, Schoevers and Penninx2016b; Danielsson et al., Reference Danielsson, Sakarya and Jansson-Fröjmark2019). Even in patients with bipolar disorder (BD) among mood disorder types, conflicting results of association of morningness–eveningness and anxiety exist. A previous study found that evening chronotypes were associated with higher levels of anxiety and lower levels of functioning (Melo et al., Reference Melo, Garcia, Araújo, Luz, Bruin and Bruin2019). Contrarily, another study showed that patients with BD and eveningness preference did not exhibit higher comorbidity rate of anxiety disorders (Romo-Nava et al., Reference Romo-Nava, Blom, Cuellar-Barboza, Winham, Colby, Nunez, Biernacka, Frye and McElroy2020). Therefore, further investigation is warranted to better understand the association between morningness–eveningness and anxiety.

In this study, we investigated the roles of resilience and anxiety in the association between morningness–eveningness and depressive symptom. Previous studies have suggested that resilience may serve as a one possible protective mechanism factor and anxiety as an important factor in depression, although anxiety has uncertain relevance with morningness–eveningness. Understanding the association between morningness–eveningness and depression is imperative for the establishment of effective interventions related to morningness–eveningness in a mood disorder. However, no studies have examined the associations among morningness–eveningness, resilience, anxiety, and depression jointly. On the basis of past research, we hypothesised that eveningness would increase depression symptoms through the mediation of lower resilience and greater anxiety. Furthermore, we determined whether these associations are applicable to both patients with mood disorder and the general population.

Material and methods

Participants

This study included 743 patients with mood disorder (Major Depressive Disorder (MDD), 233 [31.4%]; Bipolar Disorder I (BDI), 113 [15.2%]; Bipolar Disorder II (BDII), 397 [53.4%]) who were recruited from the clinic of the Seoul National University Bundang Hospital and 818 nonpatients. Data collection was carried out from July 2013 to February 2021. The psychiatric diagnoses of all patients were confirmed by board-certified psychiatrists (THH and WM) through a structured diagnostic interview (Mini-International Neuropsychiatric Interview [MINI]) (Sheehan et al., Reference Sheehan, Lecrubier, Sheehan, Amorim, Janavs, Weiller, Hergueta, Baker and Dunbar1998) or a review of case records. Patient-related information including age, sex, education years, job, marital status, alcohol use, smoking habit, family psychiatric history, and hospitalisation history were collected. The nonpatients were recruited anonymously from an online survey. Some of them were excluded if they self-reported history of any psychiatric disorder and others were used as a comparison group. The requirement for informed consent was waived as data of the patients were collected through a medical chart review whereas those of the comparison group were obtained through an anonymous survey, not directly accessing their personal information. The study protocol was approved by the Institutional Review Board of Seoul National University Bundang Hospital (B-2104-679-103). The descriptive statistics of the study sample are presented in Table 1.

Table 1. Demographic characteristics of patient and nonpatient groups

BD I = Bipolar I Disorder; BD II = Bipolar II Disorder; MDD = Major Depressive Disorder.

Measures

Composite scale of morningness

The Composite Scale of Morningness (CS) is a 13-item self-report scale that assesses the morningness–eveningness preference of an individual (Smith et al., Reference Smith, Reilly and Midkiff1989). Three questions are rated on a five-point Likert scale (1–5) and the remaining 10 questions on a four-point Likert scale (1–4). The total score of the items ranges from 13 to 55, with higher scores denoting greater morningness preference. The Korean version of the CS translated and validated by Kim (Reference Kim1998) exhibits psychometric reliability (Cronbach’s alpha = .81). The reliability of the CS in the present sample was adequate (Mcdonald’s ω = .87).

Self-rating depression scale

The Self-Rating Depression Scale (SDS) (Zung, Reference Zung1965) consists of 20 items, where half questions of the scales are negative and leaving half is positive so needed reversed score. The items are rated on a four-point Likert scale (1–4). The total score of the items ranges from 20 to 80, with higher scores denoting more severe depression symptoms. The Korean version of the SDS exhibited reliable internal consistency (Lee & Song, Reference Lee and Song1991) (Cronbach’s alpha = .80). The reliability of the SDS in the present sample was adequate (Mcdonald’s ω = .89).

Beck anxiety inventory

The Beck Anxiety Inventory (BAI) is a 21-item self-report scale that evaluates the severity of anxiety symptoms (Beck et al., Reference Beck, Epstein, Brown and Steer1988). Each item is rated on a four-point Likert scale (0–3). The total score of the items ranges from 0 to 63, with higher scores denoting higher severity of anxiety symptoms. The Korean version of the BAI exhibited good reliability (Cronbach’s alpha = .90) (Kim et al., Reference Kim, Lee, Hwang and Hong2015). The reliability of the BAI in the present sample was excellent (Mcdonald’s ω = 0.93).

Connor–Davidson resilience scale

The Connor–Davidson Resilience Scale (CD-RISC) is a self-report scale developed by Connor and Davidson (Reference Connor and Davidson2003) that measures an individual’s ability to adapt to change and cope with adversity. It consists of 25 items rated on a five-point Likert scale ranging from 0 to 4. The total score of the items ranges from 0 to 100, with higher scores denoting stronger resilience. The Korean version of the CD-RISC exhibited excellent reliability (Baek et al., Reference Baek, Lee, Joo, Lee and Choi2010) (Cronbach’s alpha = .93). The reliability of the CD-RISC in the present sample was good (Mcdonald’s ω = .93).

Statistical analysis

Before the main analysis, we conducted a confirmatory factor analysis (CFA) to evaluate the construct validity of the measures. To achieve this, we developed a measurement model that includes four factors of interest: morningness, resilience, anxiety, and depression. We incorporated several fit indices, including the chi-squared statistic, CFI, TLI, RMSEA, and SRMR, to evaluate how well the four-factor model fits the data. When fitting the four-factor model, we generated item parcels due to the substantial number of items in each subscale. These parcels represent an aggregated indicator formed by combining two or more items using either the sum or average of individual items. To generate systematically balanced parcels for each factor, we used a factorial algorithm based on the magnitudes of the loadings, as suggested by Little et al. (Reference Little, Cunningham, Shahar and Widaman2002).

We employed a path analysis model to simultaneously estimate all path coefficients using maximum likelihood estimation with robust standard errors. Our hypothesised model suggests that the relationship between morningness and depression is sequentially mediated by resilience and anxiety, as presented in Figure 1. The hypothesised model includes three indirect effects mediated by each mediator (morningness → resilience → depression; morningness → anxiety → depression) and the serial mediation that was mediated by both mediators (morningness → resilience → anxiety → depression). These indirect effects were calculated by multiplying the coefficients along each path.

Figure 1. Hypothesised study model.

To test the indirect effects, we constructed the 95% confidence intervals (CIs) for the average indirect effect via Monte Carlo simulation procedure. This approach accurately reflects the asymmetric nature of the sampling distribution of an indirect effect by producing empirical sampling distributions of the path coefficients used to calculate the indirect effect (Preacher & Selig, Reference Preacher and Selig2012). Furthermore, we incorporated demographic variables, such as sex and age, in the model. We also conducted additional statistical tests to explore the differences in the estimated path coefficients as well as the indirect effects between the patient and nonpatient groups. We used Mplus version 8.6 (Muthén & Muthén, Reference Muthén and Muthén2021) to conduct all the statistical analyses in our study.

Results

The means, standard deviations, and correlations of all study variables for each group are presented in Table 2. The CFA results indicate that the four-factor model exhibited a satisfactory fit to the data (χ 2 = 900.72, df = 113, CFI = 0.96, TLI = 0.95, RMSEA = 0.06, SRMR = .04). In addition, all item parcels were significantly loaded onto their corresponding factors, which ranged from 0.594 to .910. The correlation coefficients among the four factors ranged from − 0.667 to 0.810, indicating that the four-factor model fit the data well.

Table 2. Means, standard deviations, correlations for all study variables

** p < .01.

Coefficient estimates and their 95% CIs in the model for each group are presented in Table 3. As can be seen from the table, morningness is positively associated with resilience in both groups (patient group: β = 0.731, p < .001; nonpatient group: β = 0.447, p < .001) after controlling for age and sex whereas it is negatively associated with anxiety also in both groups (patient group: β = −0.361, p < .001; nonpatient group: β = −0.110, p = .032). Furthermore, the effects of resilience on anxiety and depression are negative and significant in both groups. Table 3 also demonstrates that anxiety is positively associated with depression also in both groups (patient group: β = 0.459, p < .001; nonpatient group: β = 0.498, p < .001).

Table 3. Estimates, standard errors and 95% confidence intervals for path coefficients and indirect effects

M = Morningness; R = Resilience; A = Anxiety; D = Depression.

* p < .05.

** p < .01.

In the patient group, the indirect effect of morningness on depression through the mediation of resilience was negative and significant (estimate = −0.133, 95% CI [−0.168, −.099]), similar to that through the mediation of anxiety (estimate = −0.166, 95% CI [−0.227, −.104]). Furthermore, the findings indicate that the hypothesised serial mediation was significant in the patient group (estimate = −0.062, 95% CI [−0.088, −.041]), fully supporting our hypothesised associations.

Similarly, in the nonpatient group, both resilience and anxiety mediated the association between morningness and depression. Specifically, the indirect effect estimate of morningness on depression through the mediation of resilience was − 0.091 (95% CI [−0.130, −.055]), whereas that through the mediation of anxiety was − 0.055 (95% CI [−0.106, −.007]), both exhibiting significance. The serial indirect effect of morningness on depression through the mediation of both resilience and anxiety was negative and significant (estimate = −0.046, 95% CI [−0.067, −.028]). Furthermore, the direct effect of morningness on depression was statistically significant for the patient group (β = −0.189, p < .001) and nonpatient group (β = −0.151, p < .001).

The differences in the estimated path coefficients and indirect effects between the groups are presented in Table 4. The results indicate that there were no significant differences in the path coefficients between the groups, except for the M→R and M→A paths. As shown in Table 4, the M→R path coefficient was significantly different between the groups (τ = 0.285, p = .019); the difference in the M→A path coefficient was also significant (τ = −0.251, p = .003). Table 4 also demonstrates that the difference in the indirect effect of morningness on depression through the mediation of resilience was statistically significant (diff = −0.008, 95% CI [−0.138, −.016]) whereas that in the indirect effect through the mediation of anxiety was significantly different between the groups (diff = −0.008, 95% CI [−0.148, −.005]).

Table 4. Difference in path coefficients, direct effect, and indirect effects between patient and nonpatient groups

M = Morningness; R = Resilience; A = Anxiety; D = Depression.

* p < .05.

** p < .01.

Discussion

This study aimed to investigate the associations among morningness–eveningness, resilience, anxiety, and depression in patients with mood disorder and the general population. As expected, in both groups, we found that morningness–eveningness was associated with depression. Furthermore, the results of the present study are consistent with the path hypotheses that resilience and anxiety individually and sequentially were mediators between morningness–eveningness and depression in both the patient and nonpatient groups. The results also indicate that the total effects of this model between the groups exhibited significant differences. Specifically, such differences appeared to have resulted from the paths between morningness–eveningness and resilience as well as between morningness–eveningness and anxiety.

The results of this study also indicate that each variable was significantly associated each other, which is consistent with the results of previous studies. Recent studies reported that morningness–eveningness was associated with depression (Müller et al., Reference Müller, Olschinski, Kundermann and Cabanel2016; Daghlas et al., Reference Daghlas, Lane, Saxena and Vetter2021; Seo et al., Reference Seo, Yeom, Cho, Son, Ahn, Kim, Ha, Cha, Moon, Park, Baek, Kang, An and Lee2022) and resilience (Antúnez et al., Reference Antúnez, Navarro and Adan2015; Lee et al., Reference Lee, Park, Kim, Lee, Cha, Lee, Soh, Park, Park and Song2016; Chung et al., Reference Chung, Choi, Kang, Jung and Joo2018). Moreover, in previous studies, the association between resilience and depression has been consistently confirmed not only in mood disorders (Waugh & Koster, Reference Waugh and Koster2015; Masuyama et al., Reference Masuyama, Kubo, Shinkawa and Sugawara2022) but also in various mental disorders (Wingo et al., Reference Wingo, Wrenn, Pelletier, Gutman, Bradley and Ressler2010; Williams & Jahn, Reference Williams and Jahn2017). Despite the existence of associations between these three variables, there were few studies that examined the direction of the variables all at once by postulating a model (Tafoya et al., Reference Tafoya, Aldrete-Cortez, Ortiz, Fouilloux, Flores and Monterrosas2019; Zhou et al., Reference Zhou, Hsiao, Shi, Yang, Huang, Jiang, Zhang and Ma2021; Palagini et al., Reference Palagini, Miniati, Marazziti, Massa, Grassi and Geoffroy2022). In addition to resilience, we extend these associations by presenting a serial mediating effect of anxiety, which is strongly associated with depression symptoms, as seen in high comorbidities (Goldberg & Fawcett, Reference Goldberg and Fawcett2012; Antypa et al., Reference Antypa, Souery, Tomasini, Albani, Fusco, Mendlewicz and Serretti2016a).

Unlike the associations between other variables that are generally consistent, previous studies have yielded conflicting results regarding the association between morningness–eveningness and anxiety (Melo et al., Reference Melo, Garcia, Araújo, Luz, Bruin and Bruin2019; Romo-Nava et al., Reference Romo-Nava, Blom, Cuellar-Barboza, Winham, Colby, Nunez, Biernacka, Frye and McElroy2020). In the present study, we found a significant association between morningness–eveningness and anxiety. Based on these results, we can deduce that aside from resilience, anxiety is also an important mechanism for the association between morningness–eveningness and depression in patients with mood disorders.

The association between morningness–eveningness and resilience can be interpreted from various theoretical perspectives. First, from a biological standpoint, various factors may be involved, including glucocorticoid hormones, sunlight exposure, rapid eye movement sleep, and neural plasticity (Lee et al., Reference Lee, Park, Kim, Lee, Cha, Lee, Soh, Park, Park and Song2016; Chung et al., Reference Chung, Choi, Kang, Jung and Joo2018). We particularly focused on glucocorticoid hormones and sunlight exposure as explications for this model. Glucocorticoid hormones are a major pathway for transmitting information within circadian rhythm (Androulakis, Reference Androulakis2021), the phases of which are related to morningness–eveningness, both intrinsically and through its behavioural traits (Duffy et al., Reference Duffy, Rimmer and Czeisler2001; Adan et al., Reference Adan, Archer, Hidalgo, Di Milia, Natale and Randler2012). Additionally, because glucocorticoid hormones function as both a primary circadian signal and a major stress response indicator (Spencer et al., Reference Spencer, Chun, Hartsock and Woodruff2018), they play a critical role in the fundamental processes of adaptation and resilience (Reul et al., Reference Reul, Collins, Saliba, Mifsud, Carter, Gutierrez-Mecinas, Qian and Linthorst2015). Furthermore, glucocorticoid hormone levels are linked to symptoms of anxiety and depressive disorders via the corticotropin-releasing hormone (Spijker & Van Rossum, Reference Spijker and Van Rossum2012; Raglan et al., Reference Raglan, Schmidt and Schulkin2017). Also, longer sunlight exposure in the daytime is associated with morningness preference (Lee et al., Reference Lee, Park, Kim, Lee, Cha, Lee, Soh, Park, Park and Song2016) and increased resilience (Killgore et al., Reference Killgore, Taylor, Cloonan and Dailey2020). Exposure to natural light is the core zeitgeber of the circadian system as well as can affect depression and associated low anxiety (An et al., Reference An, Colarelli, O.'Brien and Boyajian2016; Blume et al., Reference Blume, Garbazza and Spitschan2019).

Secondly, from a psychological perspective, vulnerabilities such as hopelessness could mediate this relationship. Hopelessness is one of the main symptoms of depression and is defined as an emotional or cognitive condition characterised by negative anticipation about the future (Beck et al., Reference Beck, Weissman, Lester and Trexler1974). Some studies have suggested a relationship between anxiety and hopelessness (Miranda et al., Reference Miranda, Fontes and Marroquín2008; Alali, Reference Alali2016), whereas depression has been shown to have a clear connection with hopelessness (Alloy et al., Reference Alloy, Black, Young, Goldstein, Shapero, Stange, Boccia, Matt, Boland, Moore and Abramson2012; Hamilton et al., Reference Hamilton, Shapero, Stange, Hamlat, Abramson and Alloy2013). Furthermore, previous research has indicated that hopelessness acts as an underlying mechanism mediating between morningness–eveningness and depression (Antypa et al., Reference Antypa, Verkuil, Molendijk, Schoevers, Penninx and Van Der Does2017; Üzer & Yücens, Reference Üzer and Yücens2020) and has also shown a significant association with resilience (Somasundaram & Devamani, Reference Somasundaram and Devamani2016; Nieto et al., Reference Nieto, Visier, Silvestre, Navarro, Serrano and Martínez-Vizcaíno2023). Consequently, vulnerabilities such as hopelessness may impair an individual’s psychological coping ability, which in turn influences their morningness–eveningness, depression, anxiety, and resilience. Therefore, we may be able to promote resilience by manipulating morningness–eveningness-related behaviours, which can help reduce anxiety and depression symptoms.

In this study, we only found significant difference in the pathways from morningness–eveningness to resilience and anxiety in the patient and nonpatient groups. Previous studies have demonstrated that high resilience provides protection against suicidal ideation in patients with depression (Min et al., Reference Min, Lee and Chae2015) and is associated with good self-esteem and physical, mental, and general health (Feggi et al., Reference Feggi, Gramaglia, Guerriero, Bert, Siliquini and Zeppegno2016). Therefore, stronger pathway of morningness–eveningness toward resilience in patients may indicate that not only the severity of depression is minimised (Wingo et al., Reference Wingo, Wrenn, Pelletier, Gutman, Bradley and Ressler2010) but also good overall health and protection against suicidal ideation is provided, by regulating morningness–eveningness preference to promote resilience in patients with depression. Conversely, anxiety was associated with worse prognosis, longer recovery time, and higher risks of suicide (Goldberg & Fawcett, Reference Goldberg and Fawcett2012). Thus, a stronger pathway with morningness–eveningness toward anxiety in patients with mood disorders shows the increased risk of negative outcomes through comorbidity with anxiety. Therefore, the importance of morningness–eveningness and its underlying mechanism in mood disorders were explored, which also increases the need for morningness–eveningness modification intervention.

The present study has several limitations that need to be acknowledged. First, we did not collect demographic variables, except sex and age, in the general population; thus, we were unable to identify and control for additional possible between-group differences in such variables. Second, in our patient samples, the number of BDI patients was relatively small compared with those of MDD and BDII patients. Third, we individually assessed all the variables in this study using self-report scales. Fourth, we conducted a cross-sectional design that cannot provide temporal associations, but mediation analysis revealed partial instead of full causation (Sobel, Reference Sobel2008; Pearl, Reference Pearl2010).

Nevertheless, this study has the following strengths. First, most of the studies that investigated the effect of morningness–eveningness in patients with mood disorders did not consider the role of anxiety, but the present study included anxiety as a variable. Second, few studies have investigated the association between resilience and morningness–eveningness in patients with mood disorders and the general population. Third, this study included a large sample size. Fourth, we examined the path differences between the groups through two statistical steps.

In conclusion, the present study demonstrated that resilience and anxiety were significant mediators between morningness–eveningness and depression in the patient and nonpatient groups. In particular, the effects of morningness–eveningness on resilience and anxiety were greater in the patient than in the nonpatient group. These results could improve the importance of morningness–eveningness preference in patients with mood disorder and the understanding of the possible mechanisms for the association between morningness–eveningness and depression. Modification of morningness–eveningness-related behaviours increases resilience, one of the possible mechanisms between morningness–eveningness and depression, and can ultimately improve the health of individuals, particularly those with mood disorder. In this modification process for promoting their health, it is necessary to also consider anxiety.

Acknowledgements

None.

Author contributions

WM, HSK and JP had full access to all of the data in this study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Conceptualisation: Hyo Shin Kang, Jungkyu Park, Woojae Myung.

Data curation: Suhyeon Kang and Huiyeong Kim.

Funding acquisition: Woojae Myung.

Investigation: Suhyeon Kang, Huiyeong Kim, Hyeona Yu, Daseul Lee, Hyuk Joon Lee, Tae Hyon Ha, Jungkyu Park, Woojae Myung, Hyo Shin Kang.

Supervision: Hyo Shin Kang, Jungkyu Park, Woojae Myung.

Statistical analysis: Suhyeon Kang and Jungkyu Park.

Writing – original draft: Suhyeon Kang and Huiyeong Kim.

Writing – review & editing: All authors.

Financial support

This work was supported by a National Research Foundation (NRF) of Korea Grant, funded by the Korean government (NRF-2021R1A2C4001779; WM). This research was additionally supported by the Korea Medical Device Development Fund grant, funded by the Korean government (the Ministry of Science and ICT; the Ministry of Trade, Industry, and Energy; the Ministry of Health & Welfare; the Ministry of Food and Drug Safety) (Project Number NTIS 9991006915, KMDF_PR_20200901_0250). The funding body had no role in the study design, data collection, data analysis, data interpretation, or writing of this report. The corresponding authors had full access to all the data in this study and had final responsibility for the decision to submit for publication.

Competing interests

None.

Institutional review board statement

This study was conducted according to the guidelines of the Declaration of Helsinki and was approved by the Institutional Review Board of Seoul National Bundang Hospital (protocol code B-2205-756-111, approved May 2, 2022).

Informed consent statement

Patient consent was waived because data was gathered through a medical chart review. Comparison consent was also waived as the researchers did not have direct access to participant personal information and used anonymised survey data for analyses.

Footnotes

Suhyeon Kang and Huiyeoung Kim contributed equally to this work as co-first authors.

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Figure 0

Table 1. Demographic characteristics of patient and nonpatient groups

Figure 1

Figure 1. Hypothesised study model.

Figure 2

Table 2. Means, standard deviations, correlations for all study variables

Figure 3

Table 3. Estimates, standard errors and 95% confidence intervals for path coefficients and indirect effects

Figure 4

Table 4. Difference in path coefficients, direct effect, and indirect effects between patient and nonpatient groups