Relationships Between Remote Learning Modalities and Nursing Students' Perceptions of Their Sleep Quality During the COVID-19 Pandemic

Background:

The relationship between learning modalities and nursing students' sleep quality during the coronavirus disease (COVID-19) pandemic is unknown.

Purpose:

This study examined the relationships between remote learning and the sleep quality of nursing students during the COVID-19 pandemic.

Methods:

Using a cross-sectional descriptive design, 890 nursing students were surveyed online to identify sleeping habits and learning modalities.

Results:

There were no significant correlations between remote learning hours, self-reported sleep hours, and sleep quality. The asynchronous-only group reported better sleep quality than the in-person and online hybrid group after controlling for health conditions and grade point average. Students who reported that remote learning had impacted their sleep had poorer sleep quality.

Conclusions:

This study provides insight into how different learning modalities impact nursing students' sleep quality during the pandemic.

The transition from in-person to remote instruction during the coronavirus disease (COVID-19) pandemic has posed significant challenges to student learning. Nursing programs had to transition to remote instruction exclusively early in the pandemic. As the pandemic became less erratic, many programs started allowing in-person learning, especially in clinical settings, while continuing remote instruction for didactic courses. Although remote instruction allows students to progress in their studies, such transition may impact their academic performance and well-being, including sleep quality.1

Teaching and Learning Modalities

Nursing education encompasses various learning modalities, including remote, in-person, or both. Remote learning (RL) is distance learning that allows online faculty-student interactions, while in-person learning requires face-to-face interactions. Remote learning can be synchronous or asynchronous. Synchronous RL requires faculty and students to meet at the same time in a remote setting, while asynchronous RL does not need a concurrent online meeting. Hybrid learning combines in-person and RL—synchronous, asynchronous, or both.

The shift from in-person to RL requires students to adapt to a new learning environment. Depending on COVID-19 policies mandated by schools and local authorities, students may engage in multiple learning modalities. For example, students may attend in-person clinical while taking didactic courses remotely in different modalities. During such transition, students also face added stress from technological challenges and relationships with peers and faculty.2 Consequently, they may struggle to adapt to various learning environments while overcoming academic and personal barriers.

Sleep Quality

Sleep quality is self-satisfaction with sleep experience, including sleep efficiency, latency, duration, and the amount of wake time after sleep onset.3 College students' sleep quality and duration are critical to their academic success.4,5 For example, nursing students' perceptions of poor sleep habits have been associated with weak academic performance and low confidence in clinical practice.6,7 Furthermore, their poor sleep quality and patterns were more prevalent during the pandemic lockdown.8 Nursing students also experienced psychological symptoms during the pandemic due to academic workload.9 Poor sleep quality, stress, and anxiety may impact students' clinical judgment and impair patient safety.

The current literature indicates that the relationship between RL and sleep quality among college students is inconsistent. Science, technology, engineering, and mathematics (STEM) and psychology students reported getting more sleep,10,11 while medical students reported less sleep during the transition to RL.12 Transitioning to RL has affected students' academic performance.13 A recent study showed that nursing students found it challenging to transition to RL during the pandemic due to different learning styles and instructors' lack of skill in teaching online classes.14 However, little is known about the relationship between RL and sleep quality among nursing students. Thus, addressing this knowledge gap will inform strategies to support student learning and sleep quality.

Purpose and Hypotheses

This study examined the relationship between nursing students' RL and their perceptions of sleep quality during the COVID-19 pandemic. The hypotheses were as follows: (1) there is a significant correlation between the number of RL hours and nursing students' sleep quality, (2) there is a significant correlation between the number of RL hours and sleep hours, (3) there is a significant effect of RL modalities on nursing students' sleep quality after controlling for their age, prior health conditions, grade point average (GPA), and the type of nursing programs they are enrolled in, and (4) students who perceived that RL had impacted their sleep will report poorer sleep quality than those who did not.

Methods

This cross-sectional descriptive study used an anonymous online survey distributed to nursing schools in the United States from March to July 2021. The study was approved by the principal investigator's university's institutional review board.

Participants and Procedure

A convenient sample was used by searching the Internet for nursing schools and programs in the United States. The first and second authors approached at least 3 nursing schools from each state. A total of 161 nursing program directors were contacted to disseminate the online survey to their students. The sample comprised undergraduate and graduate nursing programs from community colleges and universities. The inclusion criteria were (1) students enrolled in a nursing program in the United States during the COVID-19 pandemic and (2) students who self-reported engaging in RL during the COVID-19 pandemic.

RL and Sleep Quality Survey

The online survey had 2 parts. The first part consisted of questions that addressed demographics, health conditions, RL modalities, RL hours, sleep hours, and perceived impact of RL and health conditions on sleep quality. Demographic questions addressed age, gender, race, educational background, nursing program type, and GPA.

The second part of the survey was the Sleep Quality Scale (SQS). The SQS is a 28-item measure of 6 domains of sleep quality: (1) daytime dysfunction or symptoms, (2) restoration after sleep, (3) difficulty in falling asleep, (4) difficulty in waking up, (5) satisfaction with sleep, and (6) difficulty in maintaining sleep.15 Items are rated on a 4-point scale (rarely = 0, sometimes = 1, often = 2, and almost always = 3). Items in the restoration after sleep and satisfaction with sleep domains are reverse scored (rarely = 3, almost always = 0). Total SQS scores range from 0 to 84. The higher the score, the poorer the sleep quality. The instrument has a high degree of internal consistency (Cronbach α= 0.92).15 In this study, Cronbach α was 0.92, showing excellent scale reliability.

Data Analysis

SPSS version 27 (IBM Corp, Armonk, New York) was used to manage and analyze the data. Demographic data were summarized using descriptive statistics. Pearson correlation was conducted to examine relationships between the number of RL hours, the number of sleep hours, and SQS total scores. One-way between-subjects analysis of variance was conducted to examine whether the types of RL modalities have a significant effect on SQS total scores. Previous research has shown that age, health conditions, and GPA affect sleep quality,4–6,16 so a factorial analysis of covariance (ANCOVA) was performed to evaluate whether the type of RL modality affected SQS total scores when controlling these factors. Nursing program type was also included in the analysis because different programs may have different RL modalities that can impact students' sleep quality. An independent sample t test was performed to examine whether students who perceived that RL had impacted their sleep would report higher SQS scores than those who did not.

Surveys with missing data and outliers were omitted from the analyses. Students reporting more than 12 hours of sleep and/or more than 17 hours of online learning were considered outliers. New categories were created for RL: (1) asynchronous-only group, (2) synchronous-only group, (3) online hybrid group, and (4) in-person and online hybrid group. The online hybrid group consisted of students reporting both asynchronous and synchronous RL, whereas the in-person and online hybrid group combined face-to-face and RL.

Results

A total of 1193 survey responses were collected. Missing data and outliers resulted in the exclusion of 303 surveys, leaving 890 surveys for final analysis. The participants were predominantly 18 to 24 years of age (54.8%), female (87.8%), White (71.2%), and enrolled in associate or baccalaureate programs (73%), as shown in Supplemental Digital Content Table, available at: http://links.lww.com/NE/B218. The most-reported RL modality was in-person and online hybrid (57.1%). The average learning hours were 4.83 (SD = 2.51). More than half (54.6%) of the respondents reported less than 7 hours of sleep (M = 5.77, SD = 0.72), less than the Centers for Disease Control and Prevention's sleep recommendation for adults.17 About 23% (n = 201) of respondents reported that their health conditions impacted their sleep.

RL Hours and Sleep Quality

The SQS domain and total scores are reported in the Table. The correlation between RL hours and sleep quality (SQS score) was not statistically significant (r = 0.062, P = .064). More RL hours were not associated with poorer sleep quality.

Table. Sleep Quality Scale Scores.

Domains (n: Number of Items)	M (SD)	Cronbach α
Daytime dysfunction or symptoms (n = 14)	15.91 (7.28)	0.88
Restoration after sleep (n = 4)	7.55 (2.65)	0.83
Difficulty in falling asleep (n = 4)	4.11 (2.64)	0.63
Difficulty in waking up (n = 3)	5.30 (2.36)	0.69
Satisfaction with sleep (n = 3)	5.38 (2.19)	0.75
Difficulty in maintaining sleep (n = 2)	2.61 (1.66)	0.52
Total SQS score	40.86 (13.80)	0.92

Abbreviation: SQS, Sleep Quality Scale.

RL Hours and Sleep Hours

The correlation between RL hours and sleep hours was not statistically significant (r = 0.002, P = .961). More RL hours were not associated with fewer sleep hours. However, there was a significant, negative correlation between sleep hours and SQS total scores (r = −0.396, P < .001), indicating that students who reported more sleep hours also reported better sleep quality.

RL Modalities and Sleep Quality

First, a 1-way between-subjects analysis of variance was conducted using the type of RL modalities as the independent variable and SQS total score as the dependent variable. Results showed that there was a main effect, F_3,886 = 3.22, P = .022, effect size: η2 = 0.011. Post hoc comparisons using the Tukey HSD (Honest Significance Difference) test indicated that the asynchronous-only group reported better sleep quality (M = 36.62, SD = 13.53) than the in-person and online hybrid group (M = 41.67, SD = 13.72). There were no significant differences in SQS total score between other learning modalities groups.

Second, a factorial ANCOVA was conducted to examine whether the type of RL modality still had a significant effect on SQS total score with age, health condition, GPA, or program type as covariates. Tests of between-subjects effects showed that age had a significant effect on SQS total score, F_1,885 = 25.22, P < .001, effect size: η2 = 0.028, but RL modalities did not, F_3,885 = 1.48, P = .218, η2 = 0.005. Levene's test for homogeneity of variances was not significant, indicating that the error variance of the dependent variable was equal across groups. Parameter estimates result showed that sleep quality increased with nursing students' age, β = −.29, t = −5.02, P < .001.

When health condition was used as a covariate, tests of between-subjects effects showed that both RL modalities and health condition had significant effects on SQS total score, F_3,885 = 2.79, P = .04; F_1,885 = 89.04, P < .001, respectively; η2 = 0.101. Levene's test for homogeneity of variances was not significant, indicating that the error variance of the dependent variable was equal across groups. Types of RL modalities still had a significant effect on SQS scores when controlling for nursing students' reported health conditions. Parameter estimates result indicated that the asynchronous-only group had better sleep quality than the in-person and online hybrid group, β= −4.78, t = −2.82, P = .005, and students without prior health conditions had better sleep quality than students with prior health conditions, β= 9.95, t = 9.43, P < .001.

When GPA was used as a covariate, tests of between-subjects effects showed that both RL modalities and GPA had significant effects on SQS total score, F_3,885 = 2.76, P = .041; F_1,885 = 29.21, P < .001, respectively; η2 = 0.043. Levene's test for homogeneity of variances was not significant, indicating that the error variance of the dependent variable was equal across groups. Type of RL modalities still had a significant effect on SQS scores when controlling for nursing students' reported college GPA. Parameter estimates result indicated that the asynchronous-only group had better sleep quality than the in-person and online hybrid group, β= −4.65, t = −2.66, P = .008, and students with higher college GPAs reported better sleep quality, β= −7.41, t = −5.41, P < .001.

When program type was used as a covariate, tests of between-subjects effects showed that program type had a significant effect on SQS total score, F_1,885 = 23.01, P < .001, η2 = 0.025. Levene's test for homogeneity of variances was not significant, indicating that the error variance of the dependent variable was equal across groups. Parameter estimates result demonstrated that type of RL did not have a significant effect on SQS total score. Nursing students who enrolled in the master or doctoral program reported better sleep quality than students who enrolled in the baccalaureate, diploma, or associate program, β= −2.61, t = −4.80, P < .001.

Finally, when incorporating age, health conditions, GPA, and program type in the ANCOVA as multiple covariates, age, health condition, and GPA had significant effects on the SQS total score, F_1,885 = 22.11, P < .001, η2 = 0.025; F_1,885 = 101.64, P < .001, η2 = 0.104; F_1,885 = 15.56, P < .001, η2 = 0.017, respectively. However, types of RL modalities and program type did not show a significant effect. Levene's test for homogeneity of variances was not significant, indicating that the error variance of the dependent variable was equal across groups. Parameter estimates result demonstrated that (1) students who had no prior health conditions reported better sleep quality than those who had health conditions, β= 10.35, t = 10.08, P < .001; (2) students who had a higher GPA reported better sleep quality than those who had a lower GPA, β= −5.57, t = −3.94, P < .001; and (3) older students reported better sleep quality than younger students, β= −0.27, t = −4.70, P < .001.

Impact of RL Modalities and Sleep Quality

The SQS scores of students who reported that RL had impacted their sleep quality were compared with the SQS scores of students who reported no RL impact on sleep quality. Levene's test for homogeneity of variances was significant (P < .001), so the results of Welch's t test were reported. Students who perceived RL had a negative impact on their sleep and had higher SQS scores (M = 47.19, SD = 10.78) than those who reported no negative impact (M = 33.97, SD = 13.41). The difference was statistically significant (t = −16.11, P < .001), indicating poorer sleep quality for students who perceived that RL had a negative impact on their sleep.

Discussion

Learning remotely during the pandemic could be challenging for many nursing students who spend time using and adapting to various instructional modalities, which may impact their sleep quality. This study examined the relationships between nursing students' RL and their perceptions of sleep quality during the COVID-19 pandemic.

RL Hours, Sleep Quality, and Sleep Hours

The hypotheses that there are significant correlations between the number of RL hours and nursing students' sleep quality and sleep hours were not supported. The number of RL hours was not significantly correlated with overall sleep quality and sleep hours. Arguably, nursing students' RL hours did not play a significant role in their sleep quality and sleep hours. One of the reasons could be that the types of learning modalities might impact students' sleep quality, which will be discussed later. As expected, students who reported more sleep hours were more likely to report better sleep quality.

Types of RL Modalities and Sleep Quality

The hypothesis that RL modalities have a significant effect on sleep quality was supported. Students who learned asynchronously reported better sleep quality than students who had in-person and online hybrid learning. One possible explanation is that asynchronous learning does not require students to commute and attend classes at a specific time, allowing more time for sleep and better sleep quality. These findings contrast with a previous study that found that college students reported poorer sleep quality when engaging in asynchronous learning during the peak of the pandemic compared with students in previous semesters prior to the pandemic.18

Although asynchronous learning is increasingly common, hybrid learning is required in most nursing programs, especially among prelicensure students attending in-person clinical. Fixed instructional schedules in hybrid learning do not allow students the flexibility to prioritize sleep when they need it the most (eg, lacking sleep the night before clinical days). Moreover, it requires a joint effort from faculty, administrators, instructional designers, and students for successful hybrid learning.19 Without effective collaboration, student learning may be accompanied by unnecessary stress, potentially impacting sleep.

Students' Perceptions of RL and Sleep Quality

Nursing students who perceived that RL impacted their sleep reported poorer sleep quality than those who perceived otherwise, supporting the hypothesis. A recent study found that although college students perceived that their sleep quality improved and stress levels decreased when transitioning to RL during the pandemic, these effects did not last because students were subjected to other stressors.20 For example, the fear of contracting the COVID-19 virus was one of the primary concerns among nursing students.21,22 Future studies should explore how RL impacts nursing students' sleep quality based on other stressors.

Other Factors Impacting Sleep Quality

This study also investigated the impact of RL on sleep quality when controlling for other significant factors. Age was the most influential predictor of sleep quality among nursing students. Younger nursing students reported poorer sleep quality than their older counterparts, consistent with other studies.8,23 Grade point average and health conditions were also significant predictors of sleep quality, consistent with previous research,24 while types of learning modalities still significantly impacted sleep quality. Students enrolled in master's or doctoral programs reported better sleep quality than those enrolled in a diploma, associate, or bachelor's program. However, the effect was insignificant when age, health conditions, and GPA were considered as control variables. Thus, age, health conditions, and GPA were predictors of nursing students' sleep quality independent of program type.

Implications for Nursing Education

With the emphasis on sleep health by the American Academy of Sleep Medicine and the Healthy People 2030,25,26 knowledge about nursing students' sleep quality and RL is essential. More than half of the participants reported receiving less than 7 hours of sleep, making them vulnerable to poor cognitive function and academic performance. Since many schools adopted RL during the pandemic, this study revealed that different learning modalities affect students' sleep quality. Therefore, nursing programs should support students' learning needs while encouraging sleep hygiene to ensure academic and clinical success. The following strategies are recommended for faculty to enhance nursing students' sleep quality when learning through various RL modalities: (1) discuss the importance of sleep during faculty advising and refer students with poor sleep quality to the school's health services; (2) collaborate among faculty when assigning homework and examinations to avoid conflicting schedules that may hinder sleep; (3) work with instructional designers to streamline RL and minimize unnecessary stress; and (4) provide resources to promote sleep hygiene.

Limitations

Although the sample was relatively large, the sample does not include nursing students from all states. Thus, future studies should ensure an equal distribution of different types of nursing programs in all states. Also, self-reported data are prone to recall and social desirability bias. Because of the survey design limitations, the impact of transitioning from in-person to RL during the pandemic on students' sleep quality was not examined. Also, this study did not explore the types of health conditions (eg, acute or chronic) reported by participants. Still, the SQS scale showed excellent reliability, and a significant effect of RL modalities on sleep quality was found.

Conclusion

Nursing students face a unique learning challenge because they must adapt to different learning modalities to fulfill didactic and clinical coursework during the pandemic. This study addressed the gap in the literature by exploring the relationship between RL modalities and sleep quality among nursing students, including the predictors of their sleep quality. The results will hopefully inform nursing programs and faculty to support student learning, sleep quality, and overall well-being.