DOI: https://doi.org/10.21203/rs.3.rs-2192821/v1
Students' fatigue is a serious problem which affects the quality of teaching and the physical and mental health of students and must be paid attention to by the whole society and medical workers. This study was a prospective cohort study of fatigue related problems among computer science majors at a university. With reference to "Fatigue scale-14", combining with the learning characteristics of students in Chinese education system and applying the statistical principle, the "Fatigue Scale-18" was developed. In spring, summer, autumn and winter, 319 and 1276 college students were monitored for fatigue incidence, fatigue degree and gender differences. The incidence of fatigue was 64.97%, 70.73% in boys and 61.46% in girls. Psychological fatigue accounted for 79.33% and physiological fatigue accounted for 20.67%. The main causes of fatigue were analyzed. The influence of fatigue on teaching effect is empirically studied, and the influence of fatigue on learning of students with different learning foundations is studied. Effects of fatigue incidence in different climates on learning outcomes. Based on the above research, the quantitative relationship between academic performance and fatigue degree and gender was listed as follows: academic performance =90.208—2.906× fatigue grade—4.380× gender (boy 1, girl 2). Corresponding preventive measures are put forward in view of the causes of fatigue among college students, and it is suggested that the incidence of fatigue should be controlled below 30%; it is proposed that college education should pay attention to student fatigue, monitor students' fatigue status regularly or irregularly, and take corresponding preventive measures for the causes of fatigue. Reduce the impact of student fatigue on learning and health. It provides theoretical and empirical basis for preventing students' fatigue, improving teaching quality and ensuring students' health.
Fatigue is common regardless of age, sex, health or occupation. Fatigue is the physiological process of the body can not be sustained at a specific level or organs can not maintain its predetermined exercise intensity and the impact on people's production, life, work and study. Fatigue IS divided into physiological fatigue and psychological fatigue, which subjectively is a kind of fatigue, fatigue discomfort feeling. However, fatigue is a comprehensive representation of the imbalance of internal stability of the body, and its causes involve neurology, psychology, psychiatry, endocrinology, geriatrics, cardiovascular, digestion, respiration and other specialties. Although a lot of researches have been carried out in many disciplines and majors, the breadth and depth of the researches are not enough, and there are some misunderstandings and blind spots. In different age, gender, occupation, environment, climate and different health conditions, the causes and appearance of fatigue are slightly different, but its consequences are quite different.
At present, based on the population health and production safety, domestic and foreign scholars focus on fatigue research on disease fatigue and labor fatigue. To study the influence of fatigue on production and traffic safety. To study the effect of pathologic fatigue on disease diagnosis and treatment. To study the effect of occupational fatigue on occupation. Research shows that the health of working people is not good. All these studies have made positive contributions to improving the health level of the professional population, among which teachers are the most prone to excessive fatigue [1]. However, there are few researches on students' fatigue.
Students are a huge group. There are more than 14 million students in all kinds of schools in Hunan Province of China, among which there are more than 1.4 million college students. Students are a special group, with mature physical development, healthy body, energetic, vigorous, thinking, lively and upward common characteristics. The fatigue that they APPEAR SHOULD BE different from the life SEX fatigue of other crowd and work sex fatigue, more different from disease sex fatigue and labor sex fatigue. The causes, consequences and preventive measures of fatigue are quite different between students and other adults. Students of different ages have different causes, probabilities and consequences of fatigue. But the effect of fatigue on learning is indisputable. Therefore, we conducted a prospective cohort study on the incidence of fatigue among students of different genders and climatic seasons and its impact on teaching quality.
This study used a prospective cohort study design to observe the incidence of fatigue and its effect on teaching quality in different genders and seasons in the same population. The aim is to evaluate the fatigue status of college students, the causes of fatigue, the influence of fatigue on teaching quality, and take corresponding preventive measures to reduce the impact of fatigue on learning and health. In order to prevent students from fatigue, improve the quality of teaching, to ensure the health of students to provide theoretical and empirical basis.
Zhang Zhiyuan [2] made a quantitative analysis of 76 studies on learning fatigue from 1992 to 2013.From the perspective of the annual change trend of studies on learning fatigue, the number of studies on learning fatigue published since 2000 showed an obvious growth trend, while there were less than 10 studies on learning fatigue in the previous 10 years. Studies on student fatigue mainly focus on the incidence, causes and health promotion methods of fatigue [3–9]. The incidence of fatigue was 49.6%. 45.8% in males and 51.6% in females. Females were more prone to fatigue than males. The prevalence rates of fatigue were 49.4%, 48.1% and 52.1%, respectively. There was no significant difference among different grades. Jieyao Shi et al., conducted a cross-sectional study on the prevalence of chronic fatigue syndrome (CFS) and its associated factors among 18139 middle and high school students aged 10 to 18 years in Suzhou from September 2010 to January 2011. The results showed that 163 of them (0.9%) met the definition of CFS, mainly high school students and boys. The prevalence of CFS in middle school students increased with age. In addition to the symptoms prescribed by the Centers for Disease Control and Prevention (CDC), the main symptoms of CFS in these students included fear of going to school, depression, and irritability. Studies have shown that CFS is prevalent among Chinese adolescents and requires appropriate intervention and treatment.
There are many researches on fatigue caused by mental stress in medical students. Zahra Daya [10] believes that in the process of medical career, medical students face higher risks of stress, fatigue, burnout and depression than the general population, and 14.3% of these students meet the diagnostic criteria of moderate to severe depression [11–14]. Domestic journals reported [15–17] that 50.8% ~ 56% of college students detected sickness fatigue different from ordinary people, and up to 79.8% and 87.7% of medical majors and student cadres detected sickness fatigue. The incidence of fatigue was different in different majors, 43.3% in clinical majors, 48.7% in nursing majors and 58.0% in pharmacy majors. Logistic regression analysis showed that the influencing factors of college students' fatigue were different, and univariate analysis was mainly related to sleep quality, worry about employment, sleep time, precise life goals, professional, lack of leisure activities. Multivariate analysis showed that sleep quality was the main factor affecting fatigue. Self-actualization, sports and exercise, and stress management can be used to improve the level of health-promoting lifestyle and prevent fatigue.
Systematic searches were conducted using the online databases MEDLINE and PubMed from inception until May 28, 2022. The search term student fatigue identified 263 references, with 110 studies in the last five years. Nine of these studies were eligible and analyzed in this study. Kilic B [18] conducted a 48-item questionnaire survey on 114 flying cadets (88 males and 26 females). SPSS was used for factor analysis. The results showed that seven performance factors (flight type, training arrangement, crew composition, aircraft environment, accommodation type, flight training-related issues, and biological issues) influenced the fatigue of de novo pilots at different levels. Daya Z [19] studied the effectiveness of mindfulness intervention in alleviating psychological distress of undergraduate medical students. Decker A [20] studied the sleep and fatigue of 92 art school students (60 males, 32 females) during training, and believed that although sleep could reduce fatigue, the strategy of optimizing load curve and other recovery techniques might be A better method. Van Laethem M, et al [21]. 44 doctoral students completed the evening and morning questionnaire survey within 8 days from 1 month before to 1 month after the thesis defense. It is believed that stress may build up long before the event but can recover quickly from temporary stress. Positive anticipation of stressful events may be an important factor leading to reduced daytime stress and improved daytime sleep quality during stressful events. Ezati M, et al [22]. The study evaluated the effect of regular aerobic exercise on sleep quality and fatigue of female students (18–26 years old) living in dormitories. The results: Four weeks of light aerobic exercise had no significant effect on sleep duration. But eight weeks of intensive aerobic exercise can affect sleep quality. Labrague LJ, et al. [23]. A study was conducted on 243 college students in the central Philippines during the sixth month of COVID-19 lockdown and the relationship between fatigue and individual resilience, coping skills and health. Findings: College students experienced moderate levels of fatigue during the mandatory lockout period. Improved individual resilience and coping skills are associated with lower levels of lock-in fatigue. This fatigue can be addressed by developing and implementing interventions to improve the personal resilience and coping skills of college students. Kutyło ł[24] et al. 298 full-time second-and third-year college students were randomly selected to analyze the fatigue status of working and non-working students and its determinants. The results showed that the fatigue degree of non-working students was significantly higher than that of working students. In the first group, fatigue was negatively correlated with learning satisfaction (r = -0.264) and satisfaction with the instructor (r = -0.281). In addition, there was a positive correlation between fatigue and taking the second course (r = 0.170). In the second group, fatigue was negatively correlated with learning satisfaction (r = -0.310) and with atmosphere satisfaction (r = -0.216) in one group. Working female students are more tired than working male students.
3.1 Research Objects The study protocol was discussed and approved by the "Ethics Committee" of Hunan S University. To participate in the study, students should understand the research methods and content, and fill in the "informed consent form" to participate voluntarily. The study subjects were the second semester students of the first year of the class of 2021. With grade as unit, the random cluster sampling method was used to select 319 students in 6 classes from 2101 to 2106 non-computer majors. There were 121 boys (37.9%) and 198 girls (62.1%). The students come from more than 10 provinces and cities in China, including Hunan, Shandong, Guangdong, Guangxi, Jiangxi, Yunnan, Guizhou, Henan, Hebei and Xizang. The average age was 18.7 ± 2.3 years.
3.2 Courses and teachers This research course takes "Film and Television Production Case Course —Chinese Premiere Pro CS6 Practical Essence" edited by Kai-hai Lee, "video editing and production" as the research context. This course is a public elective course available to all non-computer majors in the university, with a total of 32 hours and 2 credits. Two teachers involved in this study have 10 years of college computer basic teaching experience, rich teaching experience, good comprehensive quality, and can skillfully use online and offline teaching platform to teach.
3.3 Preparation of student fatigue scale "Fatigue Scale-14" is a fatigue monitoring scale developed by Trudie et al., Department of Psychological Medicine, Royal Hospital of England, which has been widely used in fatigue monitoring. But it is mainly designed for chronic fatigue syndrome and cancer patients and other aspects of pathological fatigue. It is mainly applied in medical diagnosis, clinical efficacy evaluation and disease epidemiology research, so it is not suitable for measuring students' fatigue. Therefore, according to the physiological and psychological characteristics of young students, this study aims to develop a self-rating scale of student fatigue with good reliability and validity for this group, and to study and analyze the impact of student fatigue on teaching effect.
The fatigue scale was compiled by 2 professors, 1 associate professor, 2 teachers and 12 student representatives, a total of 17 people formed the "student fatigue scale research group". SPSS 21.0 was used for data entry and processing, and LISREL 11.0 was used for confirmatory factor analysis. The Cronbach coefficient α was calculated by the Cronbach coefficient method (Cronbach) for reliability analysis. After multiple screenings, the validity analysis was carried out. Finally, a fatigue status questionnaire with 18 questionnaire contents was obtained. The content includes recent sleep time, study time, exercise time, mood, mental state, feeling of fatigue, appetite and sleep state, physical discomfort, etc. Each survey result is divided into 4 levels, in which level 1, normal, scored 0; level 2, mild abnormality, scored 1 point; level 3, moderate abnormality, scored 2 points; level 4, severe abnormality, scored 3 The total score is 54 points. A total score of ≤ 5 is considered normal; 6–18 is considered mild fatigue; 19–36 is considered moderate fatigue; ≥37 is considered severe fatigue.
3.4 Cohort study design This study included 319 students from 6 classes (2101 to 2106). We will observe the incidence and degree of fatigue of students in different climates and seasons (spring, summer, autumn and winter), and understand the differences in the incidence of fatigue of students in different genders, the current situation of fatigue of students and the related factors affecting fatigue. This paper studies the influence of fatigue on teaching effect and the degree of influence of different basic students' grades, analyzes the influence of different nature and degree of fatigue on different teaching scenes and the learning effect of theoretical and practical courses. To explore the causal relationship between fatigue and teaching effect.
3.5 Data Analysis SPSS 21.0 was used to sort out and analyze the data. Mean ± standard deviation (‾x ± s) and constituent ratio were used for descriptive data. Analysis of variance was used for quantitative data, and χ2 test and Spearman correlation analysis were used for qualitative data. The test level α = 0.05. Multivariate linear regression was used for quantitative analysis and Logistic regression was used for qualitative analysis. P < 0.05 was considered statistically significant.
4.1 Incidence of fatigue among students Students fill in the "Fatigue Scale-18" by themselves online or offline, and the project team teachers collect, sort out and fill in the data. In September and December 2021, March and June 2022, autumn, winter, spring and summer, students were tested for fatigue. A total of 319 survey forms were issued online each time, which were required to be uploaded after being completed within the specified time. A total of 1276 questionnaires were distributed and 1236 valid questionnaires (96.87%) were recovered. Among them, 303 (94.98%) students completed the standardized "fatigue Scale-18" test; 308 (96.55%); 310 (97.18%) and 315 (98.75%). The valid questionnaires were sorted out, counted and analyzed by full-time teachers. After deleting the incorrectly filled and incompletely filled forms, the questionnaire showed that a total of 803 people suffered from fatigue, accounting for 64.97%. The incidence of fatigue was similar to that reported in recent Chinese literature (49.6%-83.5%) [4, 5, 8, 15]. Among them, 428 (53.30%) were mild; 319 person-times (39.73%); Severe 56 times (6.98%). 331 male students were tired, accounting for 70.73%. Among them, 182 (54.99%) were mild; 121 (36.56%) moderate; Severe 28 times (8.46%). Female students fatigue 472 times, accounting for 61.46%. Among them, 246 (52.12%) were mild; Moderate 198 (41.95%); Severe 28 times (5.94%). The incidence of fatigue in boys was higher than that in girls with statistical significance, but there was no statistical significance in the degree of fatigue between boys and girls. Figure 1.
climate, abundant rain, rain hot at the same time. In spring (March), the temperature is cool (the average temperature is 14.3 ℃ ~ 23.63 ℃), and the spring breeze is permeable, making people sleepy. In early summer (June), the climate is pleasant (average temperature 17.52 ℃ ~ 24.97 ℃), refreshing and conducive to study. In autumn (September), the temperature rises (the average temperature is 23.83 ℃ ~ 31.4 ℃). In summer, the average daily temperature is above 30℃ for 85 days, and the average hot day is higher than 35℃ for about 30 days. Winter (December) average daily minimum temperature 4℃ ~ 11℃, slightly cool, cold period is very short, the climate is suitable for learning. Therefore, four seasons with different climatic characteristics, March, June, September and December, were selected to monitor the incidence of fatigue, and there was a slight difference in the incidence of fatigue in different seasons, but there was no statistical significance (P > 0.05). Figure 2.
4.1.2 Incidence of fatigue in different genders Students of different genders have different living habits and lifestyles, and their tolerance to fatigue is also different. Therefore, the incidence and degree of fatigue of students of different genders were analyzed. The results showed that the incidence of fatigue in men was higher than that in women, and mild fatigue and moderate to severe fatigue were significantly higher than those in women. The difference was statistically significant (P < 0.001), as shown in Table 1.
| Gender | people | No fatigue | Mild fatigue | Moderate fatigue | severe fatigue |
|---|---|---|---|---|---|
| Male | 468 | 137(29.27) | 182(38.89) | 121(25.85) | 28(5.98) |
| Female | 768 | 296(38.54) | 246(32.03) | 198(25.78) | 28(3.65) |
| total | 1236 | 433(35.03) | 428(34.63) | 319(25.81) | 56(4.53) |
| χ2 = 13.367 p = 0.004 | |||||
4.2 Causes of fatigue We divide the causes of student fatigue into two parts. One is that the study burden is too heavy and the study time is too long; Lack of learning methods, learning interest is not strong; Too much time playing video games or nightlife and not enough sleep; A few because of personal emotional imbalance or because of family conditions and other factors caused by psychological fatigue. The second is due to running, playing, swimming and other physical exercise caused by physical fatigue. The former mainly shows irritability, poor mood, slow thinking, slow reaction and so on. The latter basically expresses FOR limb or whole body is weak, muscle ache, spirit dispiritedly. The main cause of fatigue in this study was psychological fatigue. Figure 3~5.
around the propaganda subject, different videos are edited into a complete video. Video clip material is very important, but on the basis of mastering basic skills and learning editing tools well, ideas and inspiration in the process of production are more important. Four teaching courses with 2 class hours (1 class hour for theory and 1 class hour for practice) were randomly selected. The content and requirements are shown in Table 2.
| Time | Content | Requirements |
|---|---|---|
| September 2021 | Extreme sports | Familiarize yourself with editing tools and settings such as the Rate Stretch Tool, the Razor Tool, and the Clip Speed/Duration when making video productions. |
| December 2021 | Page curl, dissolve and shrink class transitions | Master the method of adding and editing video transition effects; understand the role of common video transition effects. |
| March 2022 | keyframe animation | Learn how to create keyframe animations; apply video effects. |
| June 2022 | Video Keying and Compositing | Master the relevant knowledge of video synthesis; understand the alpha channel; master the use of color keying and keying effects; master the use of mask keying and keying effects. |
4.3.2 Method The four courses selected in this study were all taught online by the same teacher. Before each class, students were given a "Student Fatigue Scale" and required to complete it within 5 minutes. Then the theory teaching for 1 hour, and then according to the teaching content, the examination questions are arranged, requiring students to complete the independent hand in within 1 hour. To understand the learning effect of students.
4.3.3.1 Assessment results of different fatigue degrees In spring, summer, autumn and winter, the results showed that fatigue had a great influence on the learning effect. The students without fatigue had the best test scores, and the more severe the fatigue, the worse the test scores, and the difference was statistically significant (P < 0.001). Table 3.
| Time | No fatigue | Mild | Moderate | Severe | Statistical processing |
|---|---|---|---|---|---|
| September | 88.54 ± 5.95 | 86.90 ± 7.33 | 80.98 ± 8.64 | 71.00 ± 6.89 | χ2 = 2979.0 P༜0.001 |
| December | 87.93 ± 6.71 | 84.99 ± 9.03 | 80.07 ± 8.60 | 74.63 ± 6.02 | |
| March | 88.87 ± 5.45 | 85.35 ± 7.23 | 83.38 ± 7.90 | 80.19 ± 5.80 | |
| June | 90.32 ± 4.28 | 86.61 ± 5.73 | 82.19 ± 5.83 | 78.32 ± 7.12 |
4.3.3.2 Assessment results of different learning foundations According to the examination results of students in the second half of 2021 and the first half of 2022, we divided each class into two groups, A and B, with group A performing better and group B performing worse. After the online teaching in 2022 and June, the scores of students in groups A and B were statistically analyzed to understand the influence of fatigue on students with different learning foundations. The results showed that fatigue had A slight effect on group A students, but there was no statistical significance (P > 0.05). Fatigue had a significant impact on group B (P < 0.001). See Table 4.
| Grouping | Group A(157 people) | Group B(158 people) | ||||
|---|---|---|---|---|---|---|
| normal(55) | fatigue(102) | Statistical processing | normal(56) | fatigue(102) | Statistical processing | |
| Score | 92.80 ± 3.56 | 91.99 ± 4.11 | t = 1.232 p༞0.05 | 83.59 ± 8.24 | 70.15 ± 6.28 | t = 4.866 p༜0.001 |
4.4 Multivariate analysis In this study, the influence of student fatigue on learning effect, and the dependent variables such as fatigue degree, gender and time are continuous variables, so multiple regression was used to analyze. The analysis results are shown in Table 5. The standardized residual distribution diagram (PP diagram) is shown in Fig. 6.
| Variable Name | Coefficient | Standard Error | t | p |
|---|---|---|---|---|
| Constant | 90.208 | 5.951 | 15.158 | 0.000 |
| Degree | -2.906 | 0.735 | -3.956 | 0.001 |
| Gender | -4.380 | 1.643 | -2.666 | 0.015 |
| Season | 1.266 | 1.006 | 1.259 | 0.223 |
Analysis of variance F = 8.115, P = 0.000. The adjusted fitting degree of the regression model R2 = 0.481, indicating that the fitting degree is good, and the independent variable can explain the change of the dependent variable. Through the diagnostic analysis of regression model, VIF < 5, there is no multicollinearity; The residuals are normally distributed (PP figure). Durbin - Watson = 1.812. To sum up, it shows that the analysis results are accurate and reliable with high credibility.
The regression results showed that the degree of fatigue was negatively correlated with the test scores, and the degree of fatigue of the independent variable was − 2.906, P = 0.001. The more serious the fatigue, the greater the impact on the academic performance. The gender coefficient was − 4.380, t =-2.666, P = 0.015. The performance of boys was less affected by fatigue, and the performance was higher than that of girls. Season had no significant effect on academic performance (P = 0.659). Based on the above analysis, the quantitative relationship (regression equation) between fatigue related factors and academic performance is as follows:
Academic Performance = 90.208-2.906× Fatigue Grade།4.380×Sex (Boy 1, Girl 2)
4.5 Suggestions and measures According to the results of this study, the common causes of students' fatigue and their preventive measures should include correct learning attitude, rational view of honor, reducing excessive expectations; Develop good study and living habits, and ensure 7 to 8 hours of sleep every day; Abandon smoking, drinking, indulge in cards, games, play and other bad habits; Set up correct values, love view, do have ambition, ideal, have the pursuit of modern youth; Appropriate participation in recreational and sports activities, edify sentiment, enhance physical fitness; Reasonable diet, adjust nutrition balance; Pay attention to environmental hygiene and maintain a good learning environment; Timely diagnosis and treatment of diseases to avoid pathological fatigue.
Fatigue is a common health condition for everyone, and excessive or chronic fatigue can lead to various diseases [25]. It is suggested that colleges and universities should pay attention to students' fatigue, monitor students' fatigue status through "Student Fatigue Scale" regularly or irregularly every year, and take corresponding preventive measures according to the causes of fatigue, so as to reduce the impact of students' fatigue on study and health. The incidence of fatigue in college students should be controlled below 30%, and the occurrence of severe fatigue should be avoided as far as possible.
Students are a huge group, they are the backbone of national construction and social development. The high incidence of student fatigue seriously affects teaching quality and teaching effect. Long-term fatigue will affect students' physical and mental health. Therefore, the problem of student fatigue must be highly concerned by the whole society and medical workers. This study was a prospective cohort study of fatigue related problems among computer science majors at a university. With reference to "Fatigue scale-14", combining with the learning characteristics of students in Chinese education system and applying the statistical principle, the "Fatigue Scale-18" was developed. In spring, summer, autumn and winter, 319 students (1276) were monitored for the incidence of fatigue, fatigue degree and gender differences. The main causes of fatigue were analyzed. The influence of fatigue on teaching effect is empirically studied, and the influence of fatigue on learning of students with different learning foundations is studied. The quantitative relationship between academic performance and fatigue degree and gender was listed. According to the causes of fatigue in college students, the corresponding preventive measures are put forward, and it is suggested that the incidence of fatigue should be controlled below 30%. It is proposed that college education should pay attention to students' fatigue, monitor students' fatigue regularly or irregularly and take corresponding preventive measures against the causes of fatigue to reduce the impact of students' fatigue on learning and health. It provides theoretical and empirical basis for preventing students' fatigue, improving teaching quality and ensuring students' health.
Data Availability
The data used to support the finding of this study are included within the article.
Ethical Approva
The research protocol was approved by the Ethics Committee of Hunan University of Foreign Economics. The students in the study were informed and filled out an "informed consent form."
Conflict of interest
The authors have no conflict of interest to declare.