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. 2023 Sep 19;36(6):711–721. doi: 10.1080/08995605.2023.2259778

Sleep quality and duration: A key to life satisfaction among military students

Jiri Nema a,✉, Denisa Mankova b, Miroslav Bures c, Jan Novak d,e
PMCID: PMC11622618  PMID: 37725691

ABSTRACT

Military service is a demanding profession that requires high physical preparedness and mental endurance. At the same time, the demands of military duties often require early rising and shortened sleep duration. Such a reduction in sleep can reduce physical and mental performance, and these changes can be reflected in life satisfaction. For this reason, soldiers’ life satisfaction is a crucial variable for their success and long-term service. This study examined the relationship between sleep quality, sleep duration, and life satisfaction in military medical students. The results on 35 military students showed that greater sleep quality corresponded to greater life satisfaction; this relationship was moderate and significant (r = −460, p = .005). Notably, participants (n = 17) who began to wake up without the use of an alarm clock reported an average of 11% higher life satisfaction than the participants who woke to an alarm clock; this difference between participants was statistically significant (p = .011, Cohen’s d = .911). Pre- and post-intervention showed that sleep hygiene education could be a suitable solution to prevent sleep deprivation and positively impact life satisfaction. Our findings emphasize the importance of increased sleep hygiene education, especially in preparing future military officers and during military exercises. Prioritizing sleep hygiene in these ways can significantly increase soldiers’ life satisfaction.

KEYWORDS: Life satisfaction, sleep quality, sleep deprivation, chronotype, military

What is the public significance of this article?— The study’s results show that sleep quality is an important factor influencing perceived life satisfaction, and as sleep quality meliorates, perceived life satisfaction improves. However, an alarm clock artificially interrupts sleep and can diminish life satisfaction, despite adequate sleep quality and duration. This insight is vital for military training planning, implying that simply allotting sufficient sleep time might not facilitate soldiers’ full recovery. This underlines the need for revising current military sleep and rest strategies. Furthermore, by bringing to light the counterproductive effects of artificial sleep interruptions, the study initiates a necessary dialogue about reevaluating societal norms and routines around sleep.

Introduction

Quality sleep is one of the basic subdeterminants of a healthy lifestyle, which to the greatest extent affects an individual’s health, and this, as one of the highest human values, affects life satisfaction and its particular areas (Kloudova et al., 2020; Krivohlavy, 2013; Vašek et al., 2019). Additionally, circadian rhythms and chronotype affiliation are critically important for optimal physical performance and injury prevention, which is a significant factor in soldiers (McGinnis et al., 2022).

Insufficient sleep negatively impacts safety and readiness through reduced cognitive function (such as impaired attention, concentration, responsiveness, judgment, and critical thinking), more accidents, and increased military friendly-fire incidents (Kong et al., 2011; Van Dongen et al., 2003; Yarnell & Deuster, 2016). In the military, lack of sleep not only diminishes performance by increasing fatigue, which in turn impairs the execution of combat tasks (McGinnis et al., 2022) but can also be considered a form of deprivation. Sleep deprivation is also recognized as a prohibited torture technique under international law (Cakal, 2019). A study on a large number of US Army soldiers described a significant relationship between sleep quality, sleep duration and high-risk behavior where shorter or less quality sleep was associated with a higher incidence of high-risk behavior even when demographic circumstances or PTDS were included (Mantua et al., 2021).

Unfortunately, poor sleep quality is regarded as “normal” and “unavoidable” because of the nature of military operations and special missions that frequently require shift work, long-term field training, and rapid deployment across multiple time zones (Yarnell & Deuster, 2016). For these reasons, unsatisfactory sleep, sleep disorders and their negative impact on physical and mental health are still underestimated. The missions are always a priority, not sleep (Wang et al., 2020).

The negative impact of sleep deprivation (SD) on an individual’s health, regardless of age, sex or profession, is proven. For example, SD has been described as a risk factor for cardiometabolic diseases (mainly because of the correlation between SD and glucose metabolism, diabetes and hypertension) (Cappuccio & Miller, 2017; Quist et al., 2016). SD has been also shown to increase vulnerability to adult acute psychosocial stress (Schwarz et al., 2018). The negative influences of SD affect the decision-making process on many levels, which in the case of soldiers can have disastrous consequences (threat assessment, weapon manipulation, and decision to remove wounded soldiers). This decision-making bias comes primarily from the planes of temporal memory, insight into own performance, communicating effectively, controlling mood and uninhibited behavior, and others (Harrison & Horne, 2000). Since SD impacts affectivity, there have been studies conducted to map the relationship between SD and life satisfaction (Brand et al., 2014; Ness & Saksvik-Lehouillier, 2018; Paunio et al., 2008; Piper, 2016; Totterdell et al., 1994).

The authors believe that high life satisfaction can only be achieved in conditions not influenced by negative elements of SD or impaired sleep quality, which is also supported by the work of other authors (Carciofo & Song, 2019; Kim & Ko, 2018; Kloudova et al., 2020; Ness & Saksvik-Lehouillier, 2018; Shin & Kim, 2018). Therefore, the level of life satisfaction can serve as a litmus test, indicating whether soldiers are getting adequate sleep and achieving sufficient physical and mental recovery.

The group under study in this research is military students. Students’ sleep patterns are generally well described, and although sleep quality plays a critical role in increasing academic efficiency and learning outcomes (Ahrberg et al., 2012; Roustaei et al., 2017; Safhi et al., 2020), it is common for students to experience a decline in sleep quality due to academic stress and poor sleep habits (Almojali et al., 2017; Owens et al., 2017).

This study tries to verify the hypothesis that improvements in sleep habits, including sleep quality and sleep duration, lead to increased life satisfaction. This hypothesis was examined through a pre-post intervention utilizing a control group and measuring each variable over time. It is important to remark that this is not a randomized controlled trial (RCT) study.

Methods

Research design and population

The entire research was conducted from January to May 2022, organized by the Faculty of Military Health Sciences with the approval of the university’s Ethics Committee (No. 5/2021). This research is part of a larger investigation using other research methods. Military general medicine students from Faculty of Military Medicine (FMHS) participated in the research. The study participants are full-time military personnel, their primary obligation being academic pursuits.

A total of 35 participants (18 women and 17 men, mean age 22.57, SD = 2.70) took part in the study. Students were approached to participate in the study via e-mail, social media and the project website.

The inclusion criteria for participation in the study were good physical and mental condition, not taking any medication or suffering from an acute or chronic disease, being undergraduate students at FMHS and getting up for the alarm on work days. All students who enrolled in the study also completed it.

In the conducted intervention, 18 participants (9 women and 9 men) were actively engaged, whereas the remaining individuals served as the control group. Selected questionnaires listed below were completed by participants at the beginning and end of the intervention. The intervention group underwent an 8-week sleep program which aimed to learn rules of sleep hygiene and to set sufficiently long sleep duration. Control group members underwent measurements at the same regular intervals as the intervention group, but without any direct sleep intervention. They were simply asked to record their usual sleep habits.

8-week sleep program - the intervention group received a four-hour lecture on sleep hygiene and its importance for learning and mental and physical recovery. After that, they received weekly (always on Sundays) individual sleep hygiene guidelines and recommendations and followed it for the rest of the weeks (Consensus Conference Panel, 2015). Wear a sleep mask, Limit caffeine after a certain hour, Limit alcohol, Take a walk during midday, Last meal at least 3 hours before sleep and Go to bed at the same time; the participant’s task was to follow these recommendations. After eight weeks, they followed all the principles of healthy sleep hygiene. The program flow is described in Figure 1

Figure 1.

Figure 1.

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8-week sleep program at Faculty of Military Health Sciences.

Research methods

Life satisfaction was assessed using the Life Satisfaction Questionnaire (LSQ) designed by Fahrenberg et al. (2001). This questionnaire is used to obtain a picture of an individual’s overall life satisfaction, assessing significant areas of the individual’s life. It comprises the ten domains, only seven domains are included in the calculation of overall life satisfaction. In the questionnaire, respondents answer each of the seven statements within a domain on a 7-point scale, ranging from very dissatisfied to very satisfied. Higher scores indicate higher life satisfaction. The questionnaire has previously been used in mapping the life satisfaction of soldiers (Holmquist et al., 2021; Pavelková, 2013; Vašek, 2014; Vašek et al., 2019). The original version of the questionnaire had high internal consistency (for the total LSQ, Cronbach’s alpha was .95, and for the individual components, Cronbach’s alphas were > .82). In this study, only overall life satisfaction is used.

Munich Chronotype Questionnaire (MCTQ) (Roenneberg et al., 2003) examines a person’s sleep patterns and allows for the calculation and scaling of a chronotype based on the mean sleep time on days off. It is also able to calculate the value of social jetlag based on the difference between hours of sleep on work and free days. The following items from the questionnaire were used for sleep habits: = Total bed time work/free days (TBTW/F), Sleep Duration work/free days (SDW/F), Social JetLag (SJL), Average weekly sleep duration (SDweek), Mid-Sleep work/free days (MSW/F). This questionnaire contains additional questions mapping unhealthy behaviors, but these were not used in this research. For our research, we used the Czech version of this Questionnaire (Fárková et al., 2020).

Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), a 19-item questionnaire that measures several different aspects of sleep. It offers scores for seven components: subjective sleep quality, sleep latency (i.e., how long it takes to fall asleep), sleep duration, habitual sleep efficiency (i.e., the percentage of time in bed when a person is asleep), sleep disturbances, use of sleep medications, and daytime dysfunction. The total score is then calculated by summing these components and takes a value from 0 to 21 (higher the score, the worse the resulting sleep quality); the authors report poor sleep quality for values of 5 or more (Buysse et al., 1989). The Czech version of the questionnaire was used for the research and Cronbach’s alfa in overall internal consistency of Czech version was .75 (Manková et al., 2021).

Morningness-Eveningness Questionnaire (MEQ) was used to determine the chronotype and is considered the fundamental questionnaire to determine circadian preference. It consists of 14 multiple-choice questions and five open-ended questions. Scores range from 16–86 (lower values indicate an evening chronotype, and higher values indicate a morning chronotype). According to the reached score, we recognize 5 following types: definitely evening type (16–30), moderately evening type (31–41), neither type (42–58), moderately morning type (59–69), definitely morning type (70–86) (Horne & Östberg, 1976). This questionnaire has been translated into Czech, and earlier studies confirm its possible use in the Czech population (Fárková et al., 2020). Acceptability of the Czech translation MEQ version has already been demonstrated in a previous study, and Cronbach’s alpha was .87 (Plháková et al., 2013). This questionnaire was completed by the participants only once, before the start of the intervention. The results from this questionnaire were used in all measurements.

In addition, after the intervention, we asked whether participants would continue with the sleep recommendations, were happy to have completed a similar program, and would recommend it to other students.

Statistics

The collected data was processed in SPSS version 28.0 statistical software from IBM. The data distribution of continuous variables was tested using diagnostic plots, and the Shapiro-Wilk test and all tests were set at a significance level of alpha = 0.05. The variables measured using the MCTQ, PSQI, LSQ overall score and MEQ questionnaires at the beginning and end of the intervention, showed a normal distribution (Shapiro Wilk p  > .099). We used parametric tests – paired and unpaired t-test. Two values (in average sleep duration on work days) and three values (in mid-sleep on work days) had to be removed because they severely skewed the normal distribution of the data. Bonferroni’s and Holm’s corrections were implemented to adjust for multiple testing and to reduce Type I Errors (Chen et al., 2017). Bonferroni’s correction was applied to the test statistics for correlation under the assumption of interdependence among the following suspect domains: life satisfaction, chronotype, and sleep quality. Conversely, Holm’s correction was utilized for unpaired t-tests when comparing differences between groups across 9 tests. The relationships between the observed variables were examined using Pearson’s correlation coefficient. The magnitude of the relationship was determined by applying the ranges, r = .00–.19 “very weak,” r = .20–.39 “weak,” r = .40–.59 “moderate,” r = .60–.79 “strong,” r = .80–1.00 “very strong” (Evans, 1996). Size effect was determined by Cohen’s d for unequally sized samples. We determined the effect size for Cohen’s d as a small effect size d = .2, a medium effect size d = .5 and a large effect size d = .8 (Cohen, 1988; Lenhard & Lenhard, 2016). We recorded the value of Cohen’s d in absolute value.

Results

Before the intervention

Sleep habits

The mean sleep duration for both groups at the beginning of the study was 6:47 (SD = 0:48) on work days and 8:22 (SD = 0:46) on free days. All participants woke up on work days using an alarm clock, which is reflected in mild social jet lag (M = 0:59, SD = 0:39). The group did not show significant differences in average weekly sleep duration between genders (t(33) = .212, p = .833, Cohen’s d = .072) or groups (t(33) = .073, p = .942, Cohen’s d = .025) (Table 1).

Table 1.

Difference in age, sleep quality and chronotype, sleep habits, overall life satisfaction between men and women.

Variables All (n = 35)
 Men (n = 17)
 Women (n = 18)
 t(33) p Cohen’s d
M SD M SD M SD
LSQ 250.29 32.67 258.82 32.76 242.22 31.35 −.877 .135 .518
PSQI 5.89 2.35 5.71 1.90 6.06 2.75 .435 .666 .147
MEQ 52.86 8.97 50.65 8.33 54.94 9.29 1.438 .160 .486
SDW 6:47 0:48 6:44 0:41 6:49 0:54 .290 .774 .101
SDF 8:22 0:46 8:25 0:39 8:20 0:53 −.302 .765 .102
SJL 0:59 0:39 0:59 0:42 0:59 0:36 −.011 .991 .004
SDweek 7:05 0:43 7:04 0:43 7:07 0:44 .212 .833 .072
MSW 2:37 0:49 2:51 0:44 3:25 0:52 −1.591 .244 .401
MSF 3:36 1:00 3:48 0:58 3:24 1:03 −1.185 .121 .538
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M = Mean, SD = Standard Deviation, LSQ = Overall Life satisfaction, PSQI = Quality of sleep, MEQ = Chronotype, TBTW/F= Total bed time work/free, SDW/F = Sleep Duration work/free days, SJL = Social JetLag – the difference between hours of sleep on work and free days, SDweek = Average sleep Duration week, MSW/F = Mid-Sleep work/free days.

Sleep quality

The mean PSQI score for the study group was 5.89 points (SD = 2.35), and the prevalence of poor sleep quality (total PSQI score > 5) was 57.14%. We found no significant differences in sleep quality between the genders (t(33) = .44, p = .666) (Table 1). Specifically, the mean PSQI value for the control group was 6.12 (SD = 2.2) and for the intervention group was 5.67 (SD = 2.52). It was found that the poorer sleep quality students reported, the lower life satisfaction they felt (a moderate relationship was found, r = −.460, p = .005). Moreover, PSQI scores were moderately negatively correlated with average sleep duration on work days (r = −.639, p = .001), MSF (r = .450, p = .007); and MEQ (r = −.371, p = .028); the morning types had better sleep quality. Furthermore, PSQI scores were in a moderately strong negative relationship with SDweek (r = −.401, p = .017). However, MEQ relationship, SDweek relationship and MSF relationship lost significance after applying the Bonferroni correction for multiple comparisons (Table 2).

Table 2.

Correlations life satisfaction/sleep quality and sleep habits before intervention.

Variable n M SD LSQ PSQI MEQ SDW SDF SDweek SJL MSF MSW
LSQ 35 250.29 32.67 —                
PSQI 35 5.89 2.35 −.46** —              
MEQ 35 52.86 8.97 .31 −.37* —            
SDW 33 6.79 .81 .33 −.64** .31 —          
SDF 35 8.38 .78 −.08 .31 −.10 −.22 —        
SDweek 35 7.10 .72 .16 −.40* .30 −.92** .12 —      
SJL 35 .99 .65 −.04 −.08 −.29 −.09 .15 .11 —    
MSF 35 3.60 1.00 −.19 .29 −.55** −.46** .17 −.40* .59** —  
MSW 35 2.31 .61 −.23 .45** −.44** .54 .13 −.57** .10 .74** —
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LSQ = Overall Life satisfaction, PSQI = Quality of sleep, MEQ = Chronotype, SDW/F= Sleep Duration work/free days, SDweek = Average sleep duration week, SJL = Social JetLag – the difference between hours of sleep on work and free days, MSW/F = Mid-sleep work/free days.

*p < .05, **p < .01, Bold - Still significant after applying the Bonferroni correction for multiple comparisons.

Chronotype

The mean MEQ score of the participants was 52.86 points (SD = 8.97). The distribution of the individual chronotypes in the whole group: definitely evening type 0, moderately evening type = 11.43%, neither type = 67.71%, moderately morning type = 20.00%, definitely morning type = 2.86%. Thus, the tested group was predominantly neither, tending toward morning chronotypes. We did not find significant differences in MEQ between the genders (t(33) = 1.438, p = .160) (Table 1). MEQ was a moderate significantly negative related with MSW (r = −.443, p = .008) and MSF (r = −.548, p < .001) and MSF was still significant after Bonferroni’s correction (Table 2). We found no significant differences in chronotype preference between groups (t(33) = .095, p = .925), for control group (M  = 52.71, SD  = 8.97) and for intervention group (M  = 53.00, SD  = 9.24).

Life satisfaction

We found no significant differences between genders in overall life satisfaction (t(33) = −.877, p = .135) (Table 1). The mean raw score of perceived the overall life satisfaction of the whole group was 250.29 points (SD = 32.67). There was only a moderate significant negative relationship between life satisfaction and sleep habits (between PSQI and LSQ scores) (r = −.460, p = .005), and it was still significant after Bonferroni’s correction (Table 2).

We found no significant differences in overall life satisfaction (t(33) = .090, p = .929) between the intervention and control groups at the beginning of the intervention.

After the intervention

Sleep habits

At the end of the intervention, both groups showed changes in sleep habits. Sleep duration on workdays increased by 43 minutes for graduates of the sleep program, and on free days, the time in bed decreased by 6 minutes. The average weekly sleep duration increased by 40 minutes. Concurrently, there was a significant shift in mid-sleep time on both workdays and free days, with an average advance of 35 minutes toward the earlier morning hours.

In the control group, there was a notable increase in sleep duration of 25 minutes on workdays and an increase of 15 minutes on free days. The average weekly sleep duration increased by 27 minutes. However, it was found only a significant change in MSF (t(30) = 3.702, p < .001) and MSW (t(33) = 2.728, p = .010); only MSF was still statistically significant after Holm’s correction (Table 3).

Table 3.

Comparative impact of the intervention: sleep habits, sleep quality, and life satisfaction differences in control vs intervention groups.

Changes between post-pre Control group
 Intervention group
      
n M SD n M SD t test
 Holm’s Correction Levels Cohen’s d
t value df p
PSQI 17 −1.18 2.19 17 −1.83 1.87 .337 32 .738 0.025 .557
LSQ 17 5.65 20.98 18 15.17 17.08 −1.476 33 .149 0.008 .499
SDW 16 .42 .51 17 .72 .86 −1.213 31 .234 0.010 .423
SDF 17 .26 1.08 18 −.10 1.00 1.034 33 .309 0.013 .350
SJL 17 −.10 .77 18 −.02 .64 −.308 33 .760 0.050 .102
SDweek 17 .46 .53 18 .67 .93 −.832 33 .411 0.017 .282
MSW 17 −.06 −.50 18 −.56 .57 2.728 33 .010 0.007 .923
MSF 15 −.16 .40 17 −.73 .47 3.702 30 <.001* 0.006 1.311
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LSQ = Overall Life Satisfaction, PSQI = Sleep Quality, SDW/F= Sleep Duration work/free days, SJL = Social JetLag – the difference between hours of sleep on work and free days, SDweek = Average sleep duration week. MSW/F = Mid-sleep work/free days.

*Statistically significant after Holm’s correction.

The majority (94%) of participants in the intervention group started getting up before the alarm and only 5.88% in the control group did so.

Sleep quality

At the end of the intervention, the mean PSQI was 4.4 points (SD = 1.74), and the prevalence of poor sleep quality decreased to 22,86% (from 5.9 points, SD = 2.34) for the entire group (intervention + control). The most significant improvement in sleep quality was achieved by the intervention group, where the mean PSQI score decreased significantly (t(17) = 3.051, p = .007, Cohen’s d = .719) by 1.83 points it means decreased by 32.25% (from M = 5.67, SD = 2.52, to M = 3.83, SD = 1.62). The control group members also had a significant difference in PSQI (t(16) = 2.301, p = .041, Cohen’s d = 538), but only by 1.18 points it means decreased by 19.23% (from M = 6.12, SD = 2.20 to M = 4.94, SD = 1.72). After adjusting for external influences, we found no significant differences in pre- and post-intervention sleep quality between the control and intervention groups (Table 3).

Sleep quality was still related to life satisfaction, but the strength of the relationship decreased from moderately strong to mildly strong (r = −.335, p = .049). On the second measurement, the relationship between the mid-sleep on free days increased and was now significant and moderately strong (r = .518, p = .001). We observed the same results in mid-sleep on work days (r = .486, p = .003). Sleep quality was also affected by method affiliation, and a weakly strong relationship (r = −.358, p = .035) between sleep quality and method affiliation emerged. The relationship of social jetlag was still not significant (r = .331, p = .052).

Chronotype

Chronotype at the end of the study did not have a significant relationship with the PSQI (r = −.324, p = .075), and the strength and significance of the relationship on perceived life satisfaction decreased too (r = .209, p = .229).

Life satisfaction

For the intervention group, overall life satisfaction increased by 6.05% from baseline (from M = 250.78, SD = 33.81, to M = 265.94, SD = 33.52), and this change was significant (t(17) = −3.77, p = .002). The affiliation to the intervention group had a large effect size (Cohen’s d = .888). In the control group, overall life satisfaction increased by 2.26% (from M = 249.76, SD = 32.45 to M  = 255.41, SD = 34.44), but it was not a significant change (t(16) = −.11, p = .284) and affiliation to the control group had small effect size (Cohen’s d = .256). However, after comparing differences between groups, no significant difference was found (t(33) = −1.476, p = .149), but Cohen’s d remained moderately strong (d = .499) (Table 3).

After the intervention’s conclusion, we observed a decreased correlation between sleep quality and life satisfaction. Although this relationship was initially statistically significant, albeit weak (r = −.335, p = .049), its significance did not withstand the application of the Bonferroni correction for multiple comparisons. There was also a relationship between life satisfaction and mid-sleep time on work days; this relationship was significant and weak (r = −.368, p = .030). However, this relationship no longer remained significant after applying the Bonferroni correction for multiple comparisons. Finally, modifying sleep habits led to a notable change in the behavior of some participants. Specifically, before the intervention, these participants typically relied on an alarm to wake up. However, after the intervention, they were able to wake up naturally before the alarm sounded. This newfound ability was linked to overall life satisfaction and sleep quality improvements.

Waking up to an alarm clock and the impact on life satisfaction and sleep quality

Individuals waking naturally (before the alarm clock rang) reported a mean overall life satisfaction of 275 (SD = 26.02) a mean PSQI of 3.76 (SD = 1.64), and a mean weekly sleep duration of 7.14 hours (SD = .85), while individuals waking to use the alarm clock achieved a mean life satisfaction of 247.88 (SD = 33.75), a mean PSQI of 4.94 (SD = 1.66) and an average weekly sleep duration of 7.05 (SD = .61). Between-group differences were statistically significant for the LSQ (t(33) = 2.693, p = .011, Cohen’s d = .911) for the PSQI (t(33) = −2.112, p = .042, Cohen’s d = .714) and for average week sleep duration (t(33 = −.377, p = .709, Cohen’s d = .127), LSQ was statistically significant also after Holm’s correction, but PSQI not.

Sustainability of sleep habits

One week after the end of the intervention, we asked the intervention group if they continued the set routine and sleep habits further; 88.89% said yes and would recommend it to their classmates and friends.

Discussion

Our research supported the hypothesizes on the importance of sleep quality and duration as factors related to life satisfaction. Sleep quality at the beginning of the intervention was moderately related to overall life satisfaction (r = −.460, p = .005) and appeared to be the major factor influencing LSQ. After the end of the intervention, the PSQI-LSQ relationship was maintained but decreased in strength (r = −.335, p = .049); we still consider it an essential relationship. Sleep quality as a factor significantly contributing to life satisfaction (measured by Satisfaction with life scale (SWLS)) in military personnel was also found in the study by Hoseinpour et al. (2021). We have provided evidence to support the assumption because of the effect of the 8-week sleep program in the intervention group on the significant reduction in PSQI score (by −32.25%, p = .007, Cohen’s d = .719) sleep quality and increased sleep duration on work days (by 10.87%, p = .003, Cohen’s d = .840) and the subsequent increase in overall life satisfaction (by 6.05%, p = 002, Cohen’s d = .888). However, we cannot claim that the 8-week sleep program alone was responsible for such large positive changes, as improvements were also seen in the control group. Concretely it was observed in terms of sleep quality (with a decrease in PSQI by 19.23%, p = .041 Cohen’s d = .538) and sleep duration on working days (increasing by 6%, Cohen’s d = .840). Furthermore, this may have subsequently led to an increase in life satisfaction in the control group (by 2.26%, Cohen’s d = .269). The individual changes are not statistically significant after subtracting the changes before and after the intervention. The only statistically significant factor was the change in the mid-sleep on free days (it was also significant on work days but no longer statistically significant after Holm’s correction for multiple tests) (Table 3). The improvement in sleep habits in the control group may have been due to one or a combination of the following factors. The first factor is that both groups are in the same environment (accommodation, study, activities) and the transfer of sleep recommendations from the intervention group to the control group. The second factor is that the control group knew they were in an study and wanted to please the experimenter (Rosenthal, 1963). Lastly, other factors may be, natural changes in students over the course of the semester, or seasonal fluctuations (Barley et al., 2023).

Nevertheless, results indicate a trend in the importance of the intervention sleep program for the improvement of the observed variables, but it should be noted that after adjusting for external influences and accounting for multiple testing corrections, only Mid-sleep on free days stayed statistically significant. We attribute the persistence in the significance of these relationships to the increase in sleep duration and decrease in social jet lag, particularly in the intervention group and the effect of shifting mid-sleep free days in the intervention group (Table 3). We are persuaded that the military should focus on reducing social jetlag. It turns out, for example, that SJL could be one of the behavioral biomarkers for the risk of musculoskeletal injury (McGinnis et al., 2022). Therefore, we recommend verifying the sleep program on a larger group of subjects, ideally in a randomized study. Additionally, it should be mentioned that a threshold of 5 points in the PSQI score may not be appropriately set, as indicated by another study that favors a value of 10 points or more to identify poor sleep quality (Manková et al., 2021). A different study also came up with a similar proposal (cutoff score ≥ 10) in their research on a sample of US military personnel (Matsangas & Mysliwiec, 2018).

Compared to other investigations conducted in the Czech Armed Forces (Vašek, 2014), we do not find significant differences in life satisfaction at the beginning of the research compared to the average values measured in the military population (for officers, n = 35, was the gross score of overall life satisfaction M = 241.66, SD = 35.07, p = .319 and for other soldiers, n = 38 was M = 252.89, SD = 30.71, p = .679). Major differences in mean life satisfaction scores were not found for students in our study when compared to the norming sample for the LSQ (women: n = 1578, M = 255.79; men: n = 1292, M = 257.57) (Fahrenberg et al., 2001). However, after the end of the intervention, the mean overall life satisfaction increased to 265.94, SD = 33.52 in the intervention group and to 255.41, SD = 34.44 in the control group, a significant increase compared to the previous results. However, we do not have exact data on the sleep habits of the groups that have been studied so far in the military population, from whom the average life satisfaction values were determined.

An individual’s chronotype can play an important role in sleep quality and its mismatch with social time may lead to disturbances in sleep quality. The effect of chronotype itself on sleep quality has also been described in a similar group of students (Litwic-Kaminska & Kotysko, 2020), and our results confirm it. Given the distribution of chronotypes in the observation group (predominantly of neither type), prolonging sleep duration by early bedtime was acceptable for the intervention participants. In addition, students are limited by early rising due to military duties (onset times), so it was not possible to shift the wake-up time for the intervention group. Of course, we are aware that not all chronotypes (extreme chronotypes were not highly represented in our study) can start sleeping earlier, and a blanket determination of sleep onset time might not yield the desired results. Ideally, it would also be advisable to shift the start of work/study duties to later in the morning to respect the individual’s chronotype (Enright & Refinetti, 2017; Montaruli et al., 2019; Preckel et al., 2011).

From these results and relationships, we can confirm that sleep quality is one of the basic prerequisites for life satisfaction in our study group. These results are consistent with other studies focused on the general population (João et al., 2018; Kim & Ko, 2018) as well as on the military one (Hoseinpour et al., 2021). Any intervention to promote healthy and quality sleep would benefit students, institutions, and future employers (García-Buades et al., 2019; Salas-Vallina et al., 2020). Moreover, high life satisfaction may be one of the protective factors against acute stress that individuals may be exposed to, and that cannot always be prevented especially in military operations (Gori et al., 2020). Acute stress relates to the decision-making process, which is greatly influenced by sleep deprivation. Practical research suggests possible solutions to counteract the influence of sleep deprivation, such as a longer time to master tasks, selection of motivating tasks, and awareness of lower performance, but at the same time, none are as effective as avoiding the occurrence of sleep deprivation (Harrison & Horne, 2000). These findings could also be practiced in a military environment. Because special military operations usually do not allow for enough regular rest, let alone sleep, the undesirable effects of sleep deprivation could be prevented by detailed planning and appropriate preparation. That would include various methods to promote stable performance. The authors agree that it should be, for example, periods of “banking” or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss, implementing on-call periods of no more than 12 hours in duration, with adequate rest periods every 24 hours (Parker & Parker, 2017; Yarnell & Deuster, 2016). A sleep program in a military setting should combine; detailed sleep education, noninvasive monitoring of sleep habits, and assessment of the impact of sleep on daytime efficiency (Wesensten & Balkin, 2013).

After the intervention, many students in the intervention group stated that they would continue the set regimen. We take this as confirmation that longer sleep does not interfere with the amount of leisure activities and thus healthy sleep is sustainable. Given the link between inappropriate behaviors and sleep quality in the military population (Mantua et al., 2021), a similar 8-week sleep program could be used as a prevention program. In addition, in military universities, future officers would benefit from gaining sleep hygiene knowledge through soft-skills training. Finally, a sure way to check the success of similar programs is to use data from wearable electronics capable of measuring sleep habits and sporting activities.

Limitations

The specific selection of study participants and the size of this cohort may limit the wider/general applicability of our findings to everyday practice. Additionally, the participants knew they were in a research study about sleep; we assume they were trying to get more sleep. Thus, an increase in sleep duration could also be observed in the control group, but there was not as much improvement in sleep quality.

The research was conducted in a faculty with a small number of students, and the students were accommodated in the same place. Thus, there is a possibility that some of the recommendations given to the intervention group students may have been copied by the control group. Due to capacity and space constraints, it was not within our power to split the groups so that no influences would permeate. To refine the results, it would have been necessary to select a control group that exhibited the same sample characteristics but was also completely separated by location.

In any case, we do not anticipate that the affected control group would bias the results of the research itself since the latter was aimed at clarifying the relationships between sleep duration/quality and perceived life satisfaction.

Conclusion

Our study explored the relationship between sleep quality, sleep duration, and life satisfaction among military students. Moreover, the pre-post intervention measurements revealed a consistency in these relationships that does not contradict the thesis that life satisfaction is, to some extent, influenced by sleep quality. We have found that longer, better quality sleep can lead to increased life satisfaction. However, an increase in sleep duration alone does not necessarily increase life satisfaction unless it is accompanied by an improvement in sleep quality. Interestingly, higher levels of life satisfaction were reported by individuals who could wake up naturally without the use of an alarm clock.

In the context of military planning and preparation, these findings are crucial, particularly in training future military physicians. Therefore, we recommend that when planning military training, sufficient time for recovery is created to create an environment in which soldiers can take advantage of the full restorative capacity of sleep without the negative effects of sleep deprivation.

At the same time, this recommendation is crucial in peacetime, when life satisfaction is increasingly seen as a motivation for recruitment. It is also particularly important for students in military schools, where theoretical knowledge is essential in addition to physical readiness.

Acknowledgments

We would like to thank all the students and colleagues at the Faculty of Military Health Sciences.

Funding Statement

The work was supported by the Ministry of Defence of the Czech Republic – DRO of the University of Defence, Faculty of Military Health Sciences Hradec Kralove, Czech Republic – Medical issues of WMD II, [DZRO-FVZ22-ZHN II].

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethics approval

Study and was approved by the Ethics Committee on 4 January 2022 of the University of Defence under the reference number 5/2021.

Ethics statements

All participants consented to the research.

Data availability statement

Data are available upon reasonable request.

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Associated Data

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Data Availability Statement

Data are available upon reasonable request.

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