ABSTRACT
Background
Social jetlag in nurses is a long-standing challenge for nursing management. It has been attributed to the effects of shift work that disrupts nurses’ circadian rhythms, may be detrimental to their health, and can lead to rapid turnover.
Aim
We aimed to identify the association between social jetlag, affect, depression, and quality of life of early career nurses.
Methods
In this cross-sectional study, 201 early career nurses at three tertiary hospitals in South Korea were included. Data were collected from May to July 2018. Social jetlag, affect, depression, and quality of life were measured using the Munich Chronotype Questionnaire (shift version), the Positive and Negative Affect Scale, the Centre for Epidemiological Studies Depression Scale (Korean version), and the Korean World Health Organization Quality of Life Scale (abbreviated version), respectively.
Findings
Participants’ mean overall social jetlag and quality of life scores were 4 hours 28 minutes and 80.21, respectively. Multiple regression analyses identified overall social jetlag, positive and negative affect, and depression as factors influencing the nurses’ quality of life.
Discussion
Understanding the implications of factors affecting early career nurses’ quality of life, including social jetlag, is vital to ensure staff retention. Nursing management should consider the individual social jetlag of nurses when scheduling shifts and accordingly create institutional human resources management strategies to reduce negative affect and depression while promoting positive affect in early career nurses.
Conclusion
Social jetlag, negative affect, and depression negatively impact early career nurses’ quality of life, whereas positive affect positively impacts their quality of life.
Keywords
Summary of relevance
Problem or Issue
Early career nurses experience burnout, which increases their risk of turnover and may impact patient outcomes and safety.
What is already known
Due to their dynamic work-shifts schedule, nurses are severely affected by social jetlag. This has been a challenge for nursing management, warranting a deeper understanding of its effects on nurses’ quality of life.
What this paper adds
Social jetlag, negative and positive affect, and depression impact early career nurses’ quality of life. Nursing management should effectively manage nurses’ shift schedules and implement strategies to reduce negative affect and depression while promoting positive affect in nurses.
1. Introduction
Shift work disrupts circadian rhythms and increases the prevalence of chronic diseases such as diabetes (
Kecklund and Axelsson, 2016
) and all-cause mortality (Books, Coody, Kauffman and Abraham, 2020
). Social jetlag has been identified as a key risk factor for depression (Lee et al., 2016
) and adversely affects nurses’ physical and mental health (Books, Coody, Kauffman and Abraham, 2020
; Lee et al., 2016
). It has been a long-standing challenge for nursing management, and a deeper look at the effects of shift work on nurses’ quality of life is required.The measurement of shift workers’ circadian rhythm dysregulation has changed over time. Researchers have explored the effects of shift worker chronotype by classifying participants into different chronotypes (i.e., morning and evening types;
Rodwell and Fernando, 2016
) and investigating its influence on negative affect, subjective well-being, and sleep (Lee et al., 2015
). Studies also examined the relationship between chronotype and tolerance for shift work (Lee et al., 2015
) and found that evening types experienced more negative effects of shift work than did morning types. However, research regarding circadian rhythms has transformed since the concept of social jetlag was introduced (Wittmann, Dinich, Merrow and Roenneberg, 2006
). Social jetlag refers to asynchrony between an individual's internal and external clock (social working hours; Wittmann, Dinich, Merrow and Roenneberg, 2006
). Accordingly, research focus has shifted from using the simple classification of chronotypes to calculating more specific and individualised social jetlag (Roenneberg, Pilz, Zerbini and Winnebeck, 2019
). Social jetlag is a sensitive indicator of misalignment between the sleep-wake cycle and circadian rhythm (Roenneberg, Pilz, Zerbini and Winnebeck, 2019
). Owing to the nature of their work shifts, nurses are at a high risk of developing physical and mental health problems and experiencing severe levels of job stress and burnout (Chen et al., 2020
). As this leads to turnover (Brook, Aitken, MacLaren and Salmon, 2021
), the inflow of new nurses inevitably surges, thus increasing the proportion of young nurses. Xie, Wang and Chen, 2011
indicated that young nurses who work shifts in high-grade hospitals experience severe work stress, which often leads to burnout, and that policies or interventions are required for them. Research targets young nurses to understand their transition experiences (Kaihlanen et al., 2020
) and the factors that influence their job stress and mental health (- Kaihlanen A.M.
- Elovainio M.
- Haavisto E.
- Salminen L.
- Sinervo T.
The associations between the final clinical practicum elements and the transition experience of early career nurses: A cross-sectional study.
Nurse Education in Practice. 2020; 42102680https://doi.org/10.1016/j.nepr.2019.102680
Chen et al., 2020
).1.1 Background
Research indicates that social jetlag is an inevitable, generalised phenomenon experienced by most regular and shift workers (
Rutters et al., 2014
; Vetter, Fischer, Matera and Roenneberg, 2015
). Nurses are affected by social jetlag more severely than non-shift workers, owing to the dynamic shift work schedule compared to a temporary disturbance of their circadian rhythm (Kang, Lee and Jang, 2020
). - Kang H.
- Lee M.
- Jang S.J.
The impact of social jetlag on sleep quality among nurses: a cross-sectional survey.
International Journal of Environmental Research and Public Health. 2020; 18: 47https://doi.org/10.3390/ijerph18010047
Uekata et al., 2019
reported that the social jetlag of nurses working three-shift rotations was 1.5 times that of nurses who only worked during the day. Moreover, social jetlag negatively affected the sleep quality of young nurses working three-shift rotations (- Uekata S.
- Kato C.
- Nagaura Y.
- Eto H.
- Kondo H.
The impact of rotating work schedules, chronotype, and restless legs syndrome/Willis-Ekbom disease on sleep quality among female hospital nurses and midwives: a cross-sectional survey.
International Journal of Nursing Studies. 2019; 95: 103-112https://doi.org/10.1016/j.ijnurstu.2019.04.013
Kang, Lee and Jang, 2020
). Nurses’ abilities to perform their jobs decreased as social jetlag increased, suggesting that it affected nurses’ health and patient outcomes (- Kang H.
- Lee M.
- Jang S.J.
The impact of social jetlag on sleep quality among nurses: a cross-sectional survey.
International Journal of Environmental Research and Public Health. 2020; 18: 47https://doi.org/10.3390/ijerph18010047
Yong et al., 2016
). Higher social jetlag was further associated with burnout among evening shift workers (Cheng and Hang, 2018
). However, allowing shift workers to schedule their shifts using participatory scheduling software directly improved sleep, health, and quality of life, compared to traditional scheduling methods (Karhula et al., 2020
).- Karhula K.
- Turunen J.
- Hakola T.
- Ojajärvi A.
- Puttonen S.
- Ropponen A.
- et al.
The effects of using participatory working time scheduling software on working hour characteristics and wellbeing: a quasi-experimental study of irregular shift work.
International Journal of Nursing Studies. 2020; 112103696https://doi.org/10.1016/j.ijnurstu.2020.103696
Notably, nurses aged younger than 35 years and with less than 10 years of experience account for 50% of all nurses in the Western Pacific regions (
World Health Organization 2021
). Early career nurses who experience burnout have a higher risk of job turnover (World Health Organization. (2021). State of the world's nursing 2020: Investing in education, jobs, and leadership. Available from: https://www.who.int/publications/i/item/9789240003279, accessed date: July 31, 2021.
Marufu et al., 2021
), which directly impacts patient outcomes and safety (Duffield et al., 2014
). Accordingly, a World Health Organization (WHO) policy report suggested that strategies should target nurses aged younger than 35 years to improve health outcomes worldwide, thereby benefiting society in general (World Health Organization 2021
). Therefore, this study aimed to identify the association between social jetlag (i.e., discrepancies in circadian rhythms), affect, depression, and quality of life of early career nurses.World Health Organization. (2021). State of the world's nursing 2020: Investing in education, jobs, and leadership. Available from: https://www.who.int/publications/i/item/9789240003279, accessed date: July 31, 2021.
2. Methods
2.1 Design
This was a cross-sectional study.
2.2 Participants and data collection
Based on previous studies (
Chen et al., 2020
; Cho, Pavek and Steege, 2020
), we defined ‘early career’ as less than 10 years of accrued experience and an age younger than 35 years. The inclusion criteria were nurses (i) working three-shift rotations (transition times: 07:00, 15:00, and 22:30) in tertiary hospitals for one year to 10 years; and (ii) who understood the purpose and content of this study and agreed to participate voluntarily. The sample size required for the multiple regression analyses was 199 people, given a significance level of .05, power of .95, 15 variables, and medium effect size f2 of 0.15 according to G*power 3.1.9.2. The questionnaire was distributed to 222 people, assuming a dropout rate of 10%.Data were collected at three tertiary hospitals in South Korea from May to July 2018. The nursing departments of the hospitals reviewed the IRB approval letter, study proposal, and questionnaires, and then granted research permission. Questionnaires, including consent form and study information, were delivered to the nursing departments in-person. Nursing department officials (not related to this study) delivered the same to the unit managers and requested their cooperation. Additionally, the research assistants explained the study's purpose and method to the participants; an anonymous collection envelope along with $10 gift card as reward and questionnaires were provided to the participants after obtaining written informed consent. In total, 201 responses were retrieved (response rate 90.5%).
2.3 Measures
Referring to previous studies, sex (
Tang, Thomas and Larkin, 2019
), age (Chang and Jang, 2019
), marital status (Han et al., 2014
), and participation in religious services (Ferriss, 2002
) were included as general characteristics. Furthermore, the study's major variables—stress, social jetlag, chronotype, affect, depression, and quality of life—are defined in Supplementary Table 1.2.3.1 Stress
We measured fasting salivary cortisol levels to evaluate participants’ stress levels. Cortisol is a stress hormone that serves as a signalling molecule in the hypothalamic-pituitary-adrenocortical axis in response to stress (
Holsboer and Ising, 2010
). Participants’ saliva samples were collected 30 minutes after waking on the second day of their two consecutive free days using Salivette®, consisting of a tube with a cotton swab.2.3.2 Social jetlag
The Munich Chronotype Questionnaire (MCTQshift) was developed by
Juda, Vetter and Roenneberg, 2013
based on the MCTQ (Roenneberg, Allebrandt, Merrow and Vetter, 2012
) to measure the social jetlag of shift workers. The MCTQshift measures sleep-wake patterns, such as the time of preparing to fall asleep, sleep onset, sleep latency, time of awakening, time to get up, and nap time. Working days and holidays are divided by day work, evening work, and night work to calculate the time of mid-sleep on free days, corrected for sleep debt accumulated over the workdays during day/evening/night shifts. Accordingly, the overall social jetlag and the social jetlag for each shift of the shift worker can be calculated (Juda, Vetter and Roenneberg, 2013
).2.3.3 Chronotype
The Morningness–Eveningness Questionnaire (MEQ) is a chronotype evaluation tool developed by
Horne and Östberg, 1976
. We used the Korean version (MEQ-K; Lee et al., 2014
). The MEQ is the predominant measure used to study individual differences in the circadian rhythm (Lee et al., 2014
). It classifies chronotypes into five types: extreme evening (16–30 points), moderate evening (31–41 points), neither (42–58 points), moderate morning (59–69 points), and extreme morning (70–86 points). The higher the score, the greater the extent that the respondent is a morning type. Cronbach's α was .82 at the time of development and .77 for the MEQ-K. In this study, Cronbach's α was .71.2.3.4 Affect
The Positive and Negative Affect Scale (
Watson, Clark and Tellegen, 1988
) used to measure affect comprises 20 items, with 10 measuring negative affect and 10 measuring positive affect. Items are rated using a five-point Likert scale (1 point = strongly disagree, 5 points = strongly agree). Scores range from 10 to 50 points each for both positive and negative affect. Higher scores indicate more positive or more negative affect. At the time of development, Cronbach's α was .86 and .87 for positive and negative affect, respectively (- Watson D.
- Clark L.A.
- Tellegen A.
Development and validation of brief measures of positive and negative affect: the Panas scales.
Journal of Personality and Social Psychology. 1988; 54: 1063-1070https://doi.org/10.1037//0022-3514.54.6.1063
Watson, Clark and Tellegen, 1988
). In this study, Cronbach's α was .89 for positive affect and .87 for negative affect.- Watson D.
- Clark L.A.
- Tellegen A.
Development and validation of brief measures of positive and negative affect: the Panas scales.
Journal of Personality and Social Psychology. 1988; 54: 1063-1070https://doi.org/10.1037//0022-3514.54.6.1063
2.3.5 Depression
The Korean version of the Centre for Epidemiological Studies Depression Scale (CES-D;
Chon, Choi and Yang, 2001
), used to measure participants’ level of depression, comprises 20 items rated on a four-point Likert scale (0 points = 1 day or less per week, 3 points = 5 days or more per week). Scores range from 0 to 80 points. Higher scores indicate more severe depression. Cronbach's α was .91 for the Korean version of CES-D (Chon, Choi and Yang, 2001
) and .89 in the current study.2.3.6 Quality of life
The Korean World Health Organization Quality of Life (WHOQOL) Scale abbreviated version (
Min et al., 2002
), used to measure the participants’ quality of life, comprises 26 questions in four sub-domains: physical health, psychological health, social relationships, and environment. Two questions query the overall quality of life. At the time of the WHOQOL scale development, Cronbach's α was .90. In this study, Cronbach's α was .88.- Min S.K.
- Kim K.I.
- Lee C.I.
- Jung Y.C.
- Suh S.Y.
- Kim D.K.
Development of the Korean versions of WHO quality of life scale and WHOQOL-BREF.
Quality of Life Research. 2002; 11 (abbreviated version): 593-600https://doi.org/10.1023/a:1016351406336
2.4 Ethical considerations
The research was conducted after receiving approval from the institutional review board of Euji University (approval number: *** 18-2; date of approval: 3 January 2018). Participants whose autonomy and anonymity were guaranteed provided informed consent to participate. The completed self-report questionnaires were sealed in anonymous collection envelopes, submitted to the nursing department, and collectively recovered by the researchers. The study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.
2.5 Data analysis
Data analysis was performed using SPSS Statistics 24.0 (IBM, Armonk, NY). Participants’ general characteristics, circadian type, social jetlag, and quality of life were summarised using descriptive statistics. Differences in quality of life according to general characteristics were analysed with t-tests and one-way analyses of variance. Relationships between significant variables were analysed using Pearson's correlation coefficients. The Kolmogorov–Smirnov test was used to assess the normality of variable distributions. Multiple stepwise regression analyses were used to identify the factors affecting the nurses’ quality of life. Missing data were handled using the listwise deletion method.
3. Results
3.1 Participants’ general characteristics and circadian sleep parameters
Participants’ mean age was 26.48 years; 94.5% were women and 56.2% were moderate evening chronotype (Table 1). The mean overall social jetlag calculated by integrating all shifts was 4 hours and 28 minutes (Table 2).
Table 1Participants’ general characteristics (N = 201).
| Variable | Category | n (%) | M (SD) |
|---|---|---|---|
| Sex | Men | 11 (5.5) | |
| Women | 190 (94.5) | ||
| Age (years) | 26.48 (2.63) | ||
| Marital status | Married | 17 (8.5) | |
| Single | 184 (91.5) | ||
| Participation in religious services | No | 127 (63.2) | |
| Yes | 74 (36.8) |
Note. M, mean; SD, standard deviation.
Table 2Cortisol level, circadian parameters, and social jetlag (N = 201).
| Variable | Category | n (%) | M (SD) |
|---|---|---|---|
| Cortisol (saliva; µg/dl) | 0.24 (0.29) | ||
| Chronotype (MEQ) | Extreme evening type | 10 (5.0) | |
| Moderate evening type | 113 (56.2) | ||
| Neither | 75 (37.3) | ||
| Moderate morning type | 1 (0.5) | ||
| Extreme morning type | 2 (1.0) | ||
| Sleep duration (h:min) | Morning shift | 6:39 (1:50) | |
| Evening shift | 6:36 (1:39) | ||
| Night shift | 8:00 (2:04) | ||
| Overall | 6:49 (1:26) | ||
| SJL (absolute) (h:min) | Morning shift | 3:40 (1:53) | |
| Evening shift | 4:40 (1:50) | ||
| Night shift | 6:11 (1:56) | ||
| Overall | 4:28 (1:13) |
Note. M, mean; MEQ, Morningness–Eveningness Questionnaire; SD, standard deviation; SJL, social jetlag.
3.2 Quality of life according to general characteristics and chronotype
Differences in quality of life according to the general characteristics and chronotype of the participants were statistically non-significant (Table 3).
Table 3Comparison of quality of life based on participants’ general characteristics and chronotype (N = 201).
| Variable | Category | n (%) | M (SD) | t/F | p |
|---|---|---|---|---|---|
| Sex | Men | 11 (5.5) | 82.82 (12.25) | 0.81 | .417 |
| Women | 190 (94.5) | 80.06 (10.84) | |||
| Marital status | Married | 17 (8.5) | 84.53 (8.54) | 1.71 | .088 |
| Single | 184 (91.5) | 79.82 (11.03) | |||
| Participation in religious services | No | 127 (63.2) | 79.93 (10.61) | 0.48 | .629 |
| Yes | 74 (36.8) | 80.70 (11.46) | |||
| Chronotype (MEQ) | Extreme evening | 10 (5.0) | 74.40 (8.13) | 0.94 | .443 |
| Moderate evening | 113 (56.2) | 80.07 (10.60) | |||
| Neither | 75 (37.3) | 81.04 (11.51) | |||
| Moderate morning | 1 (0.5) | 86.00 | |||
| Extreme morning | 2 (1.0) | 83.50 (19.09) |
Note. M, mean, MEQ, Morningness–Eveningness Questionnaire; SD, standard deviation.
3.3 Correlations among variables
Social jetlag was negatively correlated with age (r = -.16, p = .020), chronotype (r = -.23, p = .001), and quality of life (r = -.29, p < .001), and positively correlated with cortisol level (r = .26, p < .001) and depression (r = .14, p = .042; Table 4).
Table 4Correlation among variables (N = 201).
| Age | Cortisol | Social jetlag | Chronotype | Positive affect | Negative affect | Depression | QoL | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| M | E | N | Overall | |||||||||
| r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | |||
| Age | 1 | |||||||||||
| Cortisol | -.05 (.496) | 1 | ||||||||||
| Social jetlag | M | -.11 (.109) | .34 (<.001) | 1 | ||||||||
| E | -.16 (.023) | .11 (.137) | .47 (<.001) | 1 | ||||||||
| N | .04 (.587) | -.09 (.225) | -.20 (.004) | -.43 (<.001) | 1 | |||||||
| Overall | -.16 (.020) | .26 (<.001) | .87 (<.002) | .77 (<.001) | -.09 (.214) | 1 | ||||||
| Chronotype | .00 (.983) | .00 (.984) | -.26 (<.001) | -.24 (.002) | .28 (<.001) | -.23 (.001) | 1 | |||||
| Positive affect | -.02 (.806) | .06 (.387) | -.12 (.098) | -.10 (.171) | .11 (.137) | -.11 (.117) | .07 (.340) | 1 | ||||
| Negative affect | -.07 (.322) | -.16 (.023) | -.03 (.643) | -.03 (.642) | .02 (.834) | -.04 (.544) | -.10 (.165) | .13 (.072) | 1 | |||
| Depression | -.12 (.088) | -.08 (.288) | .26 (<.001) | .08 (.264) | -.21 (.003) | .14 (.042) | -.12 (.080) | -.16 (.026) | .49 (<.001) | 1 | ||
| QoL | .08 (.234) | -.01 (.939) | -.32 (<.001) | -.20 (.005) | .11 (.132) | -.29 (<.001) | .15 (.038) | .47 (<.001) | -.25 (<.001) | -.49 (<.001) | 1 | |
Note. E, evening shift; M, morning shift; N, night shift; QoL, quality of life.
3.4 Factors affecting quality of life
Multiple stepwise regression analyses were performed. The factors that influenced the quality of life of the participants were positive affect (β = .42, p < .001), depression (β = -.31, p < .001), overall social jetlag (β = -.21, p < .001), and negative affect (β = -.16, p = .011). The model explained 44.0% of the variance (Table 5).
Table 5Factors influencing the early career nurses’ quality of life (N = 201).
| Step 1 | Step 2 | Step 3 | Step 4 | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Variables | B | β | p | Variables | B | β | p | Variables | B | β | p | Variables | B | SE | β | t | p | VIF | 95% CI | |
| (Constant) | 88.48 | (Constant) | 71.86 | < .001 | (Constant) | 79.64 | < .001 | (Constant) | 83.06 | 3.57 | 76.02 | < .001 | 76.02 | 90.10 | ||||||
| Depression | -0.61 | -.49 | < .001 | Depression | -0.54 | -.43 | < .001 | Depression | -0.50 | -.40 | < .001 | Depression | -0.40 | 0.08 | -.31 | 4.93 | < .001 | 1.45 | -0.55 | -0.24 |
| Positive affect | 0.61 | .40 | < .001 | Positive affect | 0.59 | .38 | < .001 | Positive affect | 0.64 | 0.08 | .42 | 7.52 | < .001 | 1.09 | 0.47 | 0.80 | ||||
| Overall SJL | 0.00 | -.19 | .001 | Overall SJL | -0.00 | 0.00 | -.21 | 3.79 | < .001 | 1.04 | -0.00 | 0.00 | ||||||||
| Negative affect | -0.24 | 0.09 | -.16 | 2.56 | .011 | 1.41 | -0.42 | -0.06 | ||||||||||||
| Adjusted R2 = 0.24 | Adjusted R2 = 0.39 | Adjusted R2 = 0.42 | Adjusted R2 = 0.44 | |||||||||||||||||
| F = 62.32, p < .001 | F = 64.81, p < .001 | F = 49.64, p < .001 | F = 39.92, p < .001 | |||||||||||||||||
| Durbin-Watson's du = 1.90 (du = 1.81, 4-du = 2.19) | ||||||||||||||||||||
| Breusch–Pagan's χ2 = 1.62 (p = .805) | ||||||||||||||||||||
| Kolmogorov–Smirnov test (Z = 0.04, p = .952) | ||||||||||||||||||||
Note. Stepwise method entered variables: marital status, saliva cortisol (µg/dl), morning shift SJL, evening shift SJL, night shift SJL, overall SJL, chronotype, positive affect, negative affect, and depression. CI, confidence interval; SE, standard error; SJL, social jetlag; VIF, variance inflation factor.
4. Discussion
In this study, a statistically significant positive correlation between social jetlag and fasting salivary cortisol levels was found. Although this result is consistent with the findings of
Rutters et al., 2014
, Polugrudov et al., 2016
found no evidence of a link between social jetlag and cortisol levels. Moreover, salivary cortisol negatively affects the quality of life (Hagger-Johnson, Whiteman, Wawrzyniak and Holroyd, 2010
) and plasma cortisol is found to have a negative association with psychological quality of life (Tang, Thomas and Larkin, 2019
). Nevertheless, salivary cortisol had no significant relationship with quality of life in this study. The studies may have yielded inconsistent results because cortisol levels fluctuate considerably throughout the day, displaying substantial differences depending on the sampling time, and are highly sensitive to the surrounding environment (Holsboer and Ising, 2010
). Although each fasting salivary cortisol sample was collected simultaneously, participants’ individual circumstances differed; for example, the participants may have performed different duties before the sample collection.The mean overall social jetlag of early career nurses was 4 hours 28 minutes. A similar finding with two-shift rotation workers (
Fischer et al., 2016
) has been reported—with 2 hours 33 minutes for the day shift and 5 hours 1 minute for the night shift. Social jetlag for the day shift was similar to that reported by Choi, Suh and Joo, 2017
at 3 hours 18 minutes. In a study on social jetlag among workers with a two-shift rotation (Uekata et al., 2019
), the average social jetlag was 1 hour (range = 30–120 minutes), which differs from the overall social jetlag we found. As - Uekata S.
- Kato C.
- Nagaura Y.
- Eto H.
- Kondo H.
The impact of rotating work schedules, chronotype, and restless legs syndrome/Willis-Ekbom disease on sleep quality among female hospital nurses and midwives: a cross-sectional survey.
International Journal of Nursing Studies. 2019; 95: 103-112https://doi.org/10.1016/j.ijnurstu.2019.04.013
Uekata et al., 2019
did not use the MCTQ shift version for the calculations, their results may have incorrectly represented social jetlag regarding nurses’ complex working schedules. In addition, the average age of the participants was 34.0 years (range = 27–42 years) and 41.0 years in studies by - Uekata S.
- Kato C.
- Nagaura Y.
- Eto H.
- Kondo H.
The impact of rotating work schedules, chronotype, and restless legs syndrome/Willis-Ekbom disease on sleep quality among female hospital nurses and midwives: a cross-sectional survey.
International Journal of Nursing Studies. 2019; 95: 103-112https://doi.org/10.1016/j.ijnurstu.2019.04.013
Uekata et al., 2019
and - Uekata S.
- Kato C.
- Nagaura Y.
- Eto H.
- Kondo H.
The impact of rotating work schedules, chronotype, and restless legs syndrome/Willis-Ekbom disease on sleep quality among female hospital nurses and midwives: a cross-sectional survey.
International Journal of Nursing Studies. 2019; 95: 103-112https://doi.org/10.1016/j.ijnurstu.2019.04.013
Fischer et al., 2016
, respectively.Typically, social jetlag tends to be higher with a late chronotype (
Roenneberg, Pilz, Zerbini and Winnebeck, 2019
) which is associated with younger age in adults (Roenneberg, Allebrandt, Merrow and Vetter, 2012
). For adults in their early 20s, social jetlag is remarkably high, being approximately twice that of persons in their 40s and thrice that of those in their 60s (Foster et al., 2013
). The social jetlag in the current study may have been higher owing to the relatively young age of the participants. Among persons with an average age of 43.5 years, the overall social jetlag of those working three-shift rotations was 3 hours 6 minutes (Hulsegge et al., 2019
), which was lower than that in the current study. Social jetlag increased in the order of day shift, evening shift, and night shift. As shift workers have been largely disregarded in chronotype research (Rodwell and Fernando, 2016
), and few studies examine social jetlag among three-shift rotation workers, it is challenging to draw robust conclusions.The multiple regression analyses results indicated that social jetlag was associated with the early career nurses’ quality of life. Similar to the present study, chronotype did not influence the quality of life in a systematic review of studies of the chronotype and shift work tolerance of shift workers (
Saksvik et al., 2011
) because two-thirds of the participants belonged to neither type group. Instead, social jetlag (Roenneberg, Pilz, Zerbini and Winnebeck, 2019
), a more specific and individually calculated value than chronotype, was associated with quality of life. This is consistent with (i) predictions made at the time of the MCTQ development (Roenneberg, Wirz-Justice and Merrow, 2003
); and (ii) studies involving nursing students (Chang and Jang, 2019
) and patients with sleep problems (Kayaba, Sasai-Sakuma and Inoue, 2018
). However, there is no extant research on social jetlag and quality of life among shift work nurses; thus, comparative discussions must be conducted in the future.Additionally, multiple regression analyses revealed that positive and negative affect and depression were significantly associated with the quality of life of early career nurses. This is consistent with a prior study involving nursing students (
Chang and Jang, 2019
). As negative affect and depression influence the quality of patient care and the health of individual nurses (Lee et al., 2016
; Chen et al., 2020
), the personal well-being of nurses was added to the standards of the American Nurses Credentialing Centre's Pathway to Excellence Program. As such, the dispositional characteristics of shift nurses can affect the outcomes for both nurses and patients. The shift work schedule should consider the characteristics of shift work and individual nurses’ chronotype and negative affect (Rodwell and Fernando, 2016
).Moreover, as the circadian clock and human health are inseparable, strategies are needed to minimise the misalignment of the human circadian rhythm (i.e., social jetlag) to promote health in all relevant disciplines (
Roenneberg and Merrow, 2016
). Rosa, Terzoni, Dellafiore and Destrebecq, 2019
systematically reviewed the effects of shift work on health and emphasised that ergonomic changes are needed to schedule nurses’ shift work to decrease adverse health effects. Vetter, Fischer, Matera and Roenneberg, 2015
applied a chronotype-adjusted schedule designed to minimise social jetlag in individuals, which led to an improved quality of sleep with reduced circadian disruption in shift workers, resulting in an improved quality of life. Nurses’ quality of life was also significantly enhanced when shift work nurses directly participated in shift work schedules that considered their circadian rhythm (Karhula et al., 2020
).- Karhula K.
- Turunen J.
- Hakola T.
- Ojajärvi A.
- Puttonen S.
- Ropponen A.
- et al.
The effects of using participatory working time scheduling software on working hour characteristics and wellbeing: a quasi-experimental study of irregular shift work.
International Journal of Nursing Studies. 2020; 112103696https://doi.org/10.1016/j.ijnurstu.2020.103696
4.1 Limitations
The generalisability of the results is limited because self-reported data on the sleep-wake time were used rather than objective data, such as actigraphy or continuous melatonin sampling. In addition, since participants were conveniently sampled from two regions of South Korea, there was a possibility of selection bias, resulting in limited overall generalisability. Since nursing remains a highly gendered profession with associated biases in the workplace as women make up approximately 90% of the global nursing workforce (
World Health Organization 2021
), it was difficult to generalise the results for men. Furthermore, as this study employed a cross-sectional design, there were limits to establishing causal relationships between the variables. Future research could address the limitations by using a longitudinal cohort study to examine the long-term effects of social jetlag.World Health Organization. (2021). State of the world's nursing 2020: Investing in education, jobs, and leadership. Available from: https://www.who.int/publications/i/item/9789240003279, accessed date: July 31, 2021.
5. Conclusions
Social jetlag, positive and negative affect, and depression impact early career nurses’ quality of life. Therefore, early career nurses’ shift schedules should be managed with consideration for social jetlag to promote their quality of life. Nursing managers must accordingly create institutional human resource management strategies to reduce negative affect and depression while promoting positive affect in early career nurses.
Data availability statement
The data presented in this study are available on request from the corresponding author and with permission of the Institutional Review Board of Eulji University.
Authorship contribution statement
S.J.C. and S.J.J.: Conceptualisation, methodology, formal analysis, investigation, resources, writing—original draft preparation, writing—review and editing. Funding acquisition S.J.J. All authors have read and agreed to the published version of the manuscript.
Funding
Grants were provided by the National Research Foundation of Korea (2016R1D1A1B03932923 and 2020R1F1A1049756). The funder had no role in the collection of data, its analysis and interpretation, and in the right to approve or disapprove publication of the finished manuscript.
Ethical statement
This study was approved by the institutional review board at Eulji University (approval number: EU18-2; date of approval: 3 January 2018).
Conflict of interest
The authors have no conflict of interest to declare.
Acknowledgements
We thank the nurses for their participation in this study.
Appendix. Supplementary materials
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Article info
Publication history
Published online: November 17, 2022
Accepted:
October 28,
2022
Received in revised form:
September 28,
2022
Received:
November 23,
2021
Publication stage
In Press Corrected ProofIdentification
Copyright
© 2022 Australian College of Nursing Ltd. Published by Elsevier Ltd.
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