DOI: https://doi.org/10.21203/rs.3.rs-1970519/v1
Background: COVID-19 pandemic had considerable impacts on each aspect of worldwide, especially psychological disorders that would remain influenced in the post-pandemic era. Nursing students were also influenced by some special factors as facing unprecedented challenges.
Objectives: The aim of this study was to evaluate the psychological status and explore the independent influencing factors of pandemic-related experiences, feelings, finance and protective behaviors among nursing students in Inner Mongolia Minzu University in post-COVID-19 era.
Design: The online cross-sectional survey.
Settings: Population-based study in China.
Participants: Nursing undergraduate students (I-Ⅲyear).
Methodology: It was conducted by WeChat platform from December 2021 to January 2022. The questionnaire included General demographic characteristics, Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS). Cronbach's alpha, Bartlett's sphericity tests and KMO were tested the reliability and validity of scales. Descriptive analyses were completed by Mean and Standard Deviation. T-tests and ANOVA were conducted to test influencing factors. And general linear regression analyses were performed to identify the significant independent influencing factors of psychological disorders based on statistically significant results of univariate analysis.
Results: 495 effective questionnaires were received. The prevalence of depression and anxiety disorders among participants was 14.7% and 9.1%, respectively. In our study, “parents with chronic illnesses”, “feeling very stressful due to the specialty of major”, “unstable family incomes” and “paying less attention to protective behaviors” had higher anxiety and depressive levels. Besides, “feeling fearful and unknown about the pandemic development” was significantly impacted on depression only.
Conclusion: The findings obtained that depression was more prevalent among Chinese nursing students than anxiety in post-COVID-19 pandemic. It is essential to take appropriate measurements to alleviate psychological disorders by financial and family-related supports for medical-related students, in order to better respond to public health emergencies in further.
The outbreak of corona-virus disease with high infectious and pathogenic respiratory pathogen (COVID-19) occurred around the world in recent years. And COVID-19 pandemic had overwhelmed the health care systems and led to many negative effects on economy, society, spirit etc, especially for psychological conduction in many countries [1, 2]. In China, the government took preventive measures to limit its continue development, including lockdown, quarantine, social isolation, and movement restrictions during this period [3]. In fact, as we see the actions were recognized as effective control measures to reduce the spread of COVID-19, with only occasional localized epidemics. Therefore “Joint Prevention and Control Mechanism of the State Council” pointed out that prevention and control measures had been transformed from an emergency situation to normalized on May 7th, 2020 in China [4]. However some negative psychological consequences were still remained and serious in post-pandemic era which was exhibited in previous studies [5]. A Chinese study reported that 15.43% college students had anxiety and 62.91% college students were depressed in post COVID-19 pandemic [6].
The focus of this survey was depression and anxiety, as the most common modern psychological disorders, which was characterized by persistent and prolonged negative mood to influence the whole lifetime [7]. What is worse, negative emotion as psychological morbidity was closely well-documented associated with many diseases such as cancer, epilepsy, coronary artery disease etc [8]. Anxiety disorders as the most common negative emotion were defined by the current conceptualization of the etiology includes the interaction of psychosocial factors, eg, childhood adversity, stress, or trauma, and a genetic vulnerability, which manifests in neurobiological and neuropsychological dysfunctions [9]. Liu et al. indicated that anxiety disorder was an unpleasant and complex emotional status of tension, uneasiness, worry, and annoyance that an individual experiences for survival when facing with an imminent potential danger or threat [10]. Depression disorder was highly comorbid with anxiety disorder, which could manifest as a form of metabolic disorder, endocrine disorder, cardiovascular diseases, inflammatory disorders, deficiencies, or neurodegenerative disorders [11]. The anxiety and depression disorders were common which a meta-analysis showed that the overall prevalence of anxiety and depression disorders in the general population were 31.9% and 33.7%, respectively [12]. Anxiety disorder was reported to be most concerned emotion problem (41.6%) followed by depression disorder (36.4%) for college students [13].
Once unprecedented quarantine measures have become commonplace and may lead to a deterioration in students’ psychological disorders [14]. Previous study indicated that psychological disorders among university students were prevalent in China and other countries [15]. In addition, medical students were perceived to experience more and more serious mental and physical disorders than students in other majors [16]. Chinese health care workers suffered more serious burden from the increased workload, being lack of experience and tensions in doctor-patients relationships etc due to a serious imbalance doctor-patient ratio in China facing the public health emergency [16, 17]. These factors might further have impact and aggravate psychological disorders on medical related students. Up to date, several studies have been conducted on nursing students' depression and anxiety disorders rates had been high to be 48.5% and 37.3% respectively as exaggerating by the COVID-19 pandemic [17, 18]. In similar, the Chinese, Japanese and Saudi studies also showed a high prevalence of depression (56.4%, 31.1% and 43.3%) and anxiety (55.0%, 30.5% and 37.2%) among nursing students [19–21]. Due to the pressure and particularity of studies and employment, the psychological health of young people had been the focus of attention, whose mental health was a major public health problem [22]. Especially for college students, Norman Winegar considered that they were vulnerable to be affected by internal and external environment and led to serious psychological problem especially as facing the COVID-19 [23, 34].
A growing number of studies demonstrated that demographic factors like gender, age, and origin place all may have different effects on nursing students' anxiety and depression disorders [24, 25]. Nevertheless, the research aim and context of different participants were not entirely consistent. As COVID-19 entered its normalized epidemic prevention and control phase, little evidence has focused on the relationship between the prevalence of psychological disorders and the questions related to post-COVID-19 pandemic, and targeted to the research participants specially for nursing students. This study hypothesized that the influencing factors with mainly focusing on their experience, feelings, finance and protective behaviors related to post-COVID-19 pandemic had the impact on anxiety and depression disorders among nursing students in the post-pandemic era. The purpose of this cross-sectional study was to evaluate the psychological status and to explore its influencing factors of nursing students after COVID-19 in Inner Mongolia Minzu university. The findings may provide scientific and feasible clues to targeted intervention and further optimization medical education after the COVID-19 pandemic on nursing students, which was important and significantly for making continuous and appropriate guides.
The questionnaire was performed in all nursing undergraduate students from 1st to 3rd grade in Inner Mongolia Minzu University by the cross-sectional research. The research period was from December 2021 to January 2022. A total of 497 students were collected for this research.
The researched questionnaire comprised of three parts in this study.
The first part of the questionnaire was used to survey student demographics, including two aspects: A. Basic demographic information of the participants such as grade, age, gender, major, parents’ height and weight, etc. B. Feelings and situations about post-COVID-19 pandemic period, as well as the changes of lifestyle and behaviors occurred in themselves in post-COVID-19. The questions items related to post-COVID-19 were reviewed, decided and categorized through the Delphi method.
We classified the questions related to post-COVID-19 pandemic in four categories:
Personal or family experiences during the pandemic (6 items), such as “Have you or your family ever been to the former area of the pandemic?”
Changes in personal feelings after the pandemic (2 items), an example of questions asked: “What about the feelings for the development of pandemic?”
Family financial situation during the pandemic (2 items), for example “What about the degree of family income stability during the pandemic?”
Personal daily behaviors after the pandemic (8 items), like “What about the degree of protective behaviors for individuals after the pandemic (such as frequent hand washing, ventilation, etc.)?”
The SAS was an instrument for anxiety disorders and compiled by William W.K. Zung in 1971 [26]. The scale had four dimensions: “Anxious Mood” (4 items: 1, 2, 3, 4), “Autonomic nerve dysfunction” (8 items: 7, 8, 10, 11, 12, 14, 15, 18), “Motor tension” (6 items: 6, 9, 13, 17, 19, 20) and “Mixed symptom of anxiety and autonomic nerve function” (2 items: 5, 16). A total of 20 items was included, among which the reverse score had 5 items (5, 9, 13, 17, 19). The reverse question in the scale was designed to avoid inertial responses from the study participants. The scale was rated by a 4 Likert items with scores ranging from 1 (rarely) to 4 (always). The total standard score was calculated by multiplying the total gross score by 1.25. A total score with less than 50, 50–59, 60–69, and more than 70 means “normal, slight, moderate, and severe anxiety” respectively. The scale is widely used in the field of assessing anxiety among adults in world with a good reliability and validity. In recent studies, SAS has demonstrated good psychometric properties. It has been validated in Chinese, with a Cronbach’s alpha of 0.85 [27].
Depression level was assessed using the SDS [28]. The scale consisted of 20 items covering the emotional, psychological and somatic symptoms associated with depression. It contained four dimensions: “Mental-emotional symptoms” (2 items:1, 3); “Physical” (8 items:2, 4, 5, 6, 7, 8, 9, 10); “Psychomotor disorder” (2 items:12, 13) and “Psychological disorder” (8 items:11, 14, 15, 16, 17, 18, 19 20), a total of 20 items with 10 reverse scored items (2, 5, 6, 11, 12, 14, 16, 17, 18, 20). The items were measured by a 4-item Likert scale with options ranging from 1 (rarely) to 4 (always). The total gross score was multiplied by 1.25 to get the standard score. The norm of SDS in Chinese is: (53 − 61) scores indicated slight depression; (62 − 71) scores indicated moderate depression; and scores > 72 indicated severe depression. Especially during the COVID-19, this scale was widely used to measure students’ depression, which was found to have good reliability and validity [29].
The research was conducted by per-class, and the QR code of the questionnaire was sent to the WeChat group for a online survey. During the investigation, after informing the questionnaire-related aim and content, the students completed questionnaires voluntary and anonymously without any privacy questions. The whole process took about 20–30 minutes. After investigation, the surveyor checked the questionnaire information and eliminated the wrong, disorderly or missing data to ensure a high quality.
The questionnaire data was entered into EpiData and statistical analysis was performed by IBM SPSS 26.0 statistical software. Cronbach alpha values were calculated to examine internal consistency of the scale. Kaiser-Meyer-Olkin (KMO) and Bartlett's sphericity test were used to check the suitability of performing the exploratory factor analysis. Descriptive analysis were represented by Mean ± SD (standard deviation) and Median (min–max). T-test and ANOVA were used to explore the influencing factors of SAS and SDS. If significant differences appeared in results of univariate analysis, post hoc tests were performed to further address the differences. Based on above results, general linear regression was conducted to identify independent factors to influence the level of anxiety and depression among nursing students. Two-tailed p < 0.05 was considered statistically significant.
In this study, a total of 497 questionnaires were returned with the 99.60% effective rate. Among the students, the mean age of them was 20.83 ± 1.55 years, and females accounted for 78.2% in total. For major, around 82.2% of the students were nursing students, 17.8% were rehabilitation students. 106 (21.4%) participants were in grade 1, 99 (20%) participants were in grade 2, and 290 (58.6%) participants were in grade 3. The results of basic demographic information on the students were summarized in Table 1.
Variable |
Category |
N(%) |
---|---|---|
Age |
17–19 |
112 (22.6%) |
20–21 |
196 (39.6%) |
|
22–24 |
187 (37.8%) |
|
Gender |
Male |
108 (21.8%) |
Female |
387 (78.2%) |
|
Major |
Nursing |
407 (82.8%) |
Rehabilitation |
88 (17.8%) |
|
Grade |
First |
106 (21.4%) |
Second |
99 (20.0%) |
|
Third |
290 (58.6%) |
|
Origin place |
Urban |
132 (26.7%) |
Rural |
363 (73.3%) |
|
Father’s height |
<170cm |
113 (22.8%) |
170–174 |
160 (32.3%) |
|
175–179 |
164 (33.1%) |
|
>180 |
58 (11.7%) |
|
One child in family |
Yes |
181 (36.6%) |
No |
314 (63.4%) |
|
Family situation |
Parents not divorced |
414 (83.6%) |
Parents divorced |
39 (7.9%) |
|
Single-parent |
21 (4.2%) |
|
Else |
21 (4.2%) |
|
With family history of cardiovascular-related disease |
Yes |
91 (18.4%) |
No |
404 (81.6%) |
|
Parents with chronic illnesses required long-term treatment or medication |
Neither |
54 (10.9%) |
Father |
66 (13.3%) |
|
Mother |
65 (13.1%) |
|
Both |
310 (62.6%) |
The detailed questions of four categories related to post- COVID-19 pandemic were illustrated in Table 2.
Category |
Questions |
N(%) |
---|---|---|
1. Personal or family experiences during the period of the pandemic. |
||
1.1 Life model during the pandemic. |
||
With parents |
449 (90.7%) |
|
With relatives except parents |
13 (2.6%) |
|
With friends |
7 (1.4%) |
|
Due to special circumstances, with less familiar people |
0 |
|
Else |
26 (5.3%) |
|
1.2 Have you or your family ever been required to spend time in home quarantine? |
||
Yes |
117 (23.6%) |
|
No |
378 (76.4%) |
|
1.3 Have you or your family ever been asked to go to a designated place for quarantine? |
||
Yes |
10 (2.0%) |
|
No |
485 (98.0%) |
|
1.4 Have you or your family ever been asked to take nucleic acid tests? |
||
Yes |
330 (66.7%) |
|
No |
165 (33.3%) |
|
1.5 Have you or your family ever been close contact, secondary contacts or asymptomatic cases? |
||
Yes |
4 (0.8%) |
|
No |
491 (99.2%) |
|
1.6 Have you or your family ever been to the former area of the pandemic? |
||
Yes |
13 (2.6%) |
|
No |
482 (97.4%) |
|
2. Changes in personal feelings after the pandemic. |
||
2.1 What about the feelings for the development of pandemic? |
||
Unknown and fearful |
36 (7.3%) |
|
Unknown, but without fear |
16 (3.2%) |
|
Unknown, occasionally fearful |
69 (13.9%) |
|
Very fear as the pandemic spreads |
154 (31.1%) |
|
Some fear as the pandemic spreads |
177 (35.8%) |
|
Little fear as the pandemic spreads |
43 (8.7%) |
|
2.2 Are you feeling more stressful in the post-pandemic era due to the specificity of your major? |
||
Very stressful |
55 (11.1%) |
|
Sometimes stressful |
253 (51.1%) |
|
Little stressful |
157 (31.7%) |
|
No stress |
24 (4.8%) |
|
Else |
6 (1.2%) |
|
3. Family financial situation during the period of the pandemic. |
||
3.1 What are the sources of family income during the pandemic? |
||
Related social and unit welfare such as allowances or insurance |
28 (5.7%) |
|
Family savings |
121 (24.4%) |
|
Stable income from both parents |
70 (14.1%) |
|
Unilateral less stable income from either parent |
178 (36.0%) |
|
Less stable income from both parents |
98 (19.8%) |
|
3.2 What about the degree of family income stability during the pandemic? |
||
Very stable |
42 (8.5%) |
|
General stable |
232 (46.9%) |
|
Not very stable |
191 (38.6%) |
|
Very unstable |
30 (6.1%) |
|
4. Personal daily behaviors after the pandemic. |
||
4.1 What about the degree of personal protective behaviors after the pandemic (such as frequent hand washing, ventilation, etc)? |
||
Pay more attention |
395 (79.8%) |
|
Pay attention occasionally |
95 (19.2%) |
|
Pay less attention |
5 (1.0%) |
|
4.2 After the pandemic, what about the frequency of your attention to the news of the pandemic? |
||
Every day |
184 (37.2%) |
|
Occasionally |
204 (41.2%) |
|
Pay less attention |
10 (2.0%) |
|
Concerned when there is an outbreak in some areas |
97 (19.6%) |
|
4.3 Hoarding of face masks after the pandemic. |
||
Still storing a lot |
182 (36.8%) |
|
Just storing some for usage |
289 (58.4%) |
|
Purchase as needed |
24 (4.8%) |
|
4.4 Average number of meals per day. |
||
<3 times |
97 (19.6%) |
|
= 3 times |
391 (79.0%) |
|
>3 times |
7 (1.40%) |
|
4.5 Eating at regular times. |
||
Regularly |
220 (44.4%) |
|
Occasionally |
135 (27.3%) |
|
Not occasionally |
98 (19.8%) |
|
Have no specific rules |
42 (8.5%) |
|
4.6 Eating habits each day. |
||
Mainly staple food |
76 (15.4%) |
|
Mainly meat |
37 (7.5%) |
|
Mainly vegetarian food |
29 (5.9%) |
|
Balanced diet |
248 (50.1%) |
|
No specific rules |
105 (21.2%) |
|
4.7 Daily intake of other snacks |
||
Always |
20 (4.0%) |
|
Often |
114 (23.0%) |
|
Occasionally |
297 (60.0%) |
|
Seldom |
60 (12.1%) |
|
Never |
4 (0.80%) |
|
4.8 Specific forms of exercise. |
||
Outdoor sports mostly |
40 (8.1%) |
|
Indoor sports mostly |
40 (8.1%) |
|
Both |
118 (23.8%) |
|
No specific rules |
297 (60.0%) |
The internal consistency of the questionnaire was tested using Cronbach’s alpha, which more than 0.7 indicated an acceptable reliability. The results in our study showed that the Cronbach's alpha coefficients were 0.759 and 0.844 for SAS and SDS, respectively, which indicated a good reliability. The exploratory factor analysis with Kaiser-Meyer-Olkin value (KMO) and Bartlett’s Test of Sphericity were performed to test validity of SAS and SDS. For SAS, the results showed that KMO value was 0.849 and the Bartlett’s Test of Sphericity was 2836.98 (p < 0.001); For SDS, the KMO value was 0.871 and the Bartlett’s Test of Sphericity was 3235.95 (p < 0.001), in which both were satisfied with the adequacy of sampling and the applicability of factor analysis to explore the validity. The contribute of them were 65.84% and 67.67%, respectively.
Among the participants, 34 (6.9%) students were classified as slight anxiety, 8 (1.6%) students had moderate anxiety, and 4 (0.8%) had severe anxiety. The prevalence of anxiety was approximately 9.1% (n = 46). In addition, the incidence rates of slight, moderate and severe depression were 14.7% (n = 73). The results were shown in Table 3 and the detailed scores of SAS/SDS were shown in Table 4.
Categories |
N |
Percentage |
---|---|---|
Self-Rating Anxiety Scale (SAS) |
||
normal |
450 |
90.9% |
slight |
34 |
6.9% |
moderate |
8 |
1.6% |
severe |
3 |
0.6% |
Self-Rating Depression Scale (SDS) |
||
normal |
422 |
85.3% |
slight |
54 |
10.9% |
moderate |
17 |
3.4% |
severe |
2 |
0.4% |
Categories |
Min ~ Max |
M ± SD |
---|---|---|
SAS (Total score) |
25.00 ~ 77.50 |
40.12 ± 7.86 |
SDS (Total score) |
25.00 ~ 76.25 |
44.19 ± 10.08 |
S = standard deviation |
Using t-tests and ANOVA to explore the factors of basic demographic information and post-COVID-19 pandemic questions to influence the level of SAS and SDS scores. The detail results of univariate analyses were shown in Table 5.
For basic demographic information, the results showed that age had statistically significant effect on SDS dimension 1, and grade was significantly associated with SAS dimension 1. Also, gender had a significant effect on SDS dimension 1. Origin place could affect SAS dimension 3 and dimension 4. Notably, those parents with chronic illnesses requiring long-term treatment or medication got higher scores than those without on both total scores of SAS (42.93 ± 9.89 vs 39.06 ± 7.11, p = 0.03) and SDS (7.83 ± 10.90 vs 43.36 ± 9.83, p = 0.01).
For the questions related to post-COVID-19 pandemic, all the four categories were showed significantly associated with SAS total scores or SDS total scores. The significant differences results were shown below in Table 5.
For example, for 1st category: the nursing students with different life models during the pandemic had different levels of anxiety and depression.
Variables |
Statistics |
SAS (M ± SD) |
SDS (M ± SD) |
||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Dimension 1 |
Dimension 2 |
Dimension 3 |
Dimension 4 |
Total score |
Dimension 1 |
Dimension 2 |
Dimension 3 |
Dimension 4 |
Total score |
||
Gender |
|||||||||||
Male |
6.75 ± 2.73 |
12.34 ± 3.12 |
15.35 ± 4.13 |
5.17 ± 1.74 |
39.61 ± 8.13 |
3.32 ± 1.28 |
16.26 ± 3.99 |
4.53 ± 1.50 |
19.38 ± 6.01 |
43.48 ± 10.60 |
|
Female |
6.91 ± 2.25 |
12.82 ± 3.14 |
15.40 ± 3.96 |
5.13 ± 1.73 |
40.26 ± 7.79 |
3.60 ± 1.27 |
16.76 ± 3.94 |
4.65 ± 1.44 |
19.37 ± 5.33 |
44.39 ± 9.95 |
|
t |
-0.64 |
-1.41 |
-0.12 |
0.22 |
-0.77 |
-2.02 |
-1.17 |
-0.81 |
0.03 |
-0.82 |
|
p |
0.52 |
0.16 |
0.90 |
0.82 |
0.44 |
0.04* |
0.24 |
0.41 |
0.99 |
0.41 |
|
Age |
|||||||||||
17–19 |
7.10 ± 2.44 |
13.04 ± 2.93 |
15.29 ± 3.87 |
5.01 ± 1.76 |
40.44 ± 7.74 |
3.79 ± 1.44 |
16.61 ± 3.55 |
4.68 ± 1.35 |
19.24 ± 5.55 |
44.32 ± 9.66 |
|
20–21 |
6.86 ± 2.50 |
12.68 ± 3.29 |
15.35 ± 3.99 |
5.12 ± 1.75 |
40.02 ± 8.13 |
3.54 ± 1.28 |
16.63 ± 4.02 |
4.53 ± 1.50 |
19.23 ± 5.39 |
43.93 ± 10.13 |
|
22–24 |
6.76 ± 2.16 |
12.56 ± 3.10 |
15.48 ± 4.10 |
5.23 ± 1.70 |
40.03 ± 7.77 |
3.39 ± 1.14 |
16.70 ± 4.12 |
4.69 ± 1.45 |
19.61 ± 5.56 |
44.39 ± 10.35 |
|
F |
0.73 |
0.82 |
0.09 |
0.58 |
0.12 |
3.58 |
0.02 |
0.65 |
0.27 |
0.11 |
|
p |
0.48 |
0.44 |
0.91 |
0.56 |
0.89 |
0.03* |
0.97 |
0.52 |
0.77 |
0.89 |
|
Grade |
|||||||||||
First |
6.44 ± 1.82 |
12.37 ± 2.47 |
15.70 ± 3.81 |
4.94 ± 1.72 |
39.45 ± 6.62 |
3.60 ± 1.32 |
16.29 ± 3.50 |
4.85 ± 1.34 |
19.47 ± 5.45 |
44.20 ± 9.04 |
|
Second |
7.46 ± 2.72 |
13.28 ± 3.47 |
15.04 ± 3.81 |
5.10 ± 1.77 |
40.88 ± 8.33 |
3.78 ± 1.31 |
16.88 ± 4.05 |
4.41 ± 1.40 |
18.89 ± 5.57 |
43.95 ± 10.48 |
|
Third |
6.84 ± 2.37 |
12.65 ± 3.23 |
15.39 ± 4.13 |
5.23 ± 1.72 |
40.10 ± 8.11 |
3.44 ± 1.24 |
16.71 ± 4.07 |
4.62 ± 1.49 |
19.50 ± 5.47 |
44.28 ± 10.35 |
|
F |
4.99 |
2.34 |
0.69 |
1.10 |
0.86 |
2.74 |
0.66 |
2.38 |
0.49 |
0.04 |
|
p |
0.01* |
0.09 |
0.50 |
0.33 |
0.43 |
0.07 |
0.46 |
0.09 |
0.61 |
0.96 |
|
Origin Place |
|||||||||||
Urban |
6.97 ± 2.76 |
12.76 ± 3.46 |
14.76 ± 4.16 |
4.71 ± 1.66 |
39.20 ± 8.74 |
3.49 ± 1.24 |
16.52 ± 4.04 |
4.48 ± 1.40 |
18.88 ± 5.15 |
43.38 ± 9.85 |
|
Rural |
6.84 ± 2.24 |
12.70 ± 3.02 |
15.61 ± 3.92 |
5.30 ± 1.73 |
40.45 ± 7.50 |
3.56 ± 1.29 |
16.70 ± 3.92 |
4.68 ± 1.46 |
19.55 ± 5.59 |
44.49 ± 10.17 |
|
t |
0.53 |
0.18 |
-2.10 |
-3.40 |
-1.58 |
-0.49 |
-0.44 |
-1.36 |
-1.20 |
-1.08 |
|
p |
0.60 |
0.86 |
0.04* |
0.00** |
0.12 |
0.63 |
0.66 |
0.17 |
0.23 |
0.28 |
|
Basic demographic information: Parents with chronic illnesses requiring constant treatment or medication. |
|||||||||||
Neither |
6.58 ± 1.97 |
12.35 ± 2.84 |
15.16 ± 3.94 |
4.98 ± 1.75 |
39.06 ± 7.11 |
3.49 ± 1.22 |
16.35 ± 3.70 |
4.52 ± 1.38 |
19.00 ± 5.55 |
43.36 ± 9.83 |
|
Father |
7.33 ± 2.30 |
13.11 ± 3.21 |
15.95 ± 3.55 |
5.32 ± 1.69 |
41.70 ± 7.33 |
3.45 ± 1.08 |
16.63 ± 3.90 |
4.55 ± 1.43 |
19.26 ± 5.33 |
43.88 ± 9.81 |
|
Mother |
6.8 ± 2.205 |
13.19 ± 3.38 |
15.56 ± 4.42 |
5.25 ± 1.65 |
41.86 ± 7.80 |
3.45 ± 1.21 |
16.97 ± 4.24 |
4.70 ± 1.73 |
19.86 ± 5.10 |
44.98 ± 10.12 |
|
Both |
7.87 ± 3.65 |
13.67 ± 3.91 |
15.77 ± 4.33 |
5.63 ± 1.67 |
42.94 ± 9.89 |
3.96 ± 1.66 |
17.87 ± 4.68 |
5.15 ± 1.46 |
20.85 ± 5.46 |
47.83 ± 10.90 |
|
F |
6.49 |
4.28 |
1.00 |
3.00 |
5.89 |
2.78 |
2.79 |
3.59 |
2.20 |
3.70 |
|
p |
0.01* |
0.02* |
0.36 |
0.03* |
0.03* |
0.04* |
0.04* |
0.01* |
0.08* |
0.01* |
|
1.1 Life model during the pandemic. |
|||||||||||
With parents |
6.84 ± 2.39 |
12.66 ± 3.10 |
15.32 ± 3.99 |
5.11 ± 1.73 |
39.93 ± 7.77 |
3.51 ± 1.23 |
16.5 ± 3.91 |
4.60 ± 1.46 |
19.34 ± 5.54 |
43.9 ± 10.09 |
|
With relatives except parents |
7.40 ± 1.65 |
13.75 ± 3.31 |
15.77 ± 4.49 |
5.29 ± 1.92 |
42.21 ± 9.10 |
4.04 ± 2.29 |
18.75 ± 3.89 |
5.19 ± 1.34 |
20.87 ± 4.60 |
48.85 ± 9.97 |
|
With friends |
8.57 ± 3.49 |
15.18 ± 4.30 |
18.39 ± 2.77 |
6.79 ± 0.98 |
48.93 ± 8.52 |
4.64 ± 1.39 |
21.61 ± 3.36 |
4.82 ± 1.52 |
21.61 ± 4.19 |
52.68 ± 7.05 |
|
Else |
6.73 ± 1.70 |
12.55 ± 3.27 |
15.48 ± 4.03 |
5.19 ± 1.68 |
39.95 ± 7.65 |
3.56 ± 1.21 |
16.83 ± 3.84 |
4.66 ± 1.25 |
18.61 ± 5.15 |
43.65 ± 9.68 |
|
F |
1.49 |
2.00 |
1.40 |
2.21 |
3.38 |
2.53 |
5.25 |
0.74 |
0.88 |
2.71 |
|
p |
0.22 |
0.11 |
0.24 |
0.09 |
0.02* |
0.06 |
0.00** |
0.25 |
0.44 |
0.04* |
|
2.1 What about the feelings for the development of pandemic? |
|||||||||||
Unknown and fearful |
6.70 ± 2.05 |
12.18 ± 2.96 |
16.49 ± 4.43 |
5.10 ± 1.83 |
40.49 ± 7.17 |
3.37 ± 0.98 |
17.71 ± 3.94 |
5.49 ± 1.59 |
21.67 ± 5.97 |
48.23 ± 10.09 |
|
Unknown, but without fear |
6.48 ± 2.93 |
12.65 ± 4.05 |
15.23 ± 4.18 |
5.70 ± 2.04 |
40.08 ± 9.96 |
3.20 ± 1.44 |
16.41 ± 5.57 |
3.83 ± 1.80 |
17.97 ± 5.68 |
41.41 ± 12.07 |
|
Unknown, occasionally fearful |
6.93 ± 2.33 |
12.60 ± 2.92 |
15.79 ± 3.94 |
5.27 ± 2.73 |
40.62 ± 7.68 |
3.48 ± 1.07 |
16.97 ± 3.94 |
4.84 ± 1.37 |
19.89 ± 5.75 |
45.18 ± 10.30 |
|
Very fear as the pandemic spreads |
7.30 ± 2.67 |
13.31 ± 3.87 |
16.03 ± 4.01 |
5.47 ± 1.62 |
42.13 ± 8.86 |
3.80 ± 1.44 |
17.39 ± 4.08 |
4.69 ± 1.45 |
19.93 ± 5.07 |
45.80 ± 10.14 |
|
Some fear as the pandemic spreads |
6.64 ± 1.95 |
12.24 ± 2.31 |
14.72 ± 3.89 |
4.70 ± 1.68 |
38.31 ± 6.64 |
3.38 ± 1.12 |
15.67 ± 3.52 |
4.51 ± 1.37 |
18.47 ± 5.37 |
42.03 ± 9.34 |
|
Little fear as the pandemic spreads |
6.51 ± 2.64 |
13.17 ± 3.02 |
14.24 ± 3.44 |
5.35 ± 1.86 |
39.27 ± 7.24 |
3.66 ± 1.55 |
16.77 ± 3.80 |
4.13 ± 1.29 |
18.87 ± 5.79 |
43.43 ± 10.00 |
|
F |
1.73 |
2.36 |
3.27 |
4.09 |
4.21 |
2.36 |
3.99 |
5.35 |
3.00 |
4.12 |
|
p |
0.19 |
0.06 |
0.01* |
0.00** |
0.00** |
0.04* |
0.00* |
0.00** |
0.01* |
0.00** |
|
2.2 Are you feeling more stressful in the post-pandemic era due to the specificity of your major? |
|||||||||||
Very stressful |
8.52 ± 3.45 |
14.00 ± 3.78 |
16.45 ± 3.83 |
65.72 ± 1.67 |
44.70 ± 8.83 |
4.00 ± 1.77 |
18.70 ± 4.11 |
5.02 ± 1.62 |
21.43 ± 6.14 |
49.16 ± 11.79 |
|
Sometimes stressful |
6.87 ± 2.10 |
12.65 ± 2.74 |
15.50 ± 4.19 |
5.15 ± 1.65 |
40.17 ± 7.53 |
3.66 ± 1.22 |
16.61 ± 3.88 |
4.76 ± 1.36 |
19.47 ± 5.23 |
44.49 ± 9.61 |
|
Little stressful |
6.38 ± 2.05 |
12.56 ± 3.52 |
14.59 ± 3.65 |
4.94 ± 1.79 |
38.48 ± 7.66 |
3.26 ± 1.11 |
16.09 ± 3.75 |
4.32 ± 1.45 |
18.69 ± 5.35 |
42.36 ± 9.42 |
|
No stress |
6.41 ± 2.37 |
11.67 ± 2.41 |
16.98 ± 3.93 |
5.26 ± 2.08 |
40.31 ± 7.13 |
3.18 ± 1.10 |
16.30 ± 4.35 |
4.38 ± 1.61 |
18.49 ± 6.61 |
42.34 ± 12.19 |
|
Else |
7.08 ± 2.19 |
11.67 ± 1.88 |
15.21 ± 1.66 |
3.96 ± 1.23 |
37.92 ± 4.66 |
3.33 ± 0.65 |
15.83 ± 3.51 |
4.58 ± 1.51 |
17.92 ± 4.23 |
41.67 ± 6.31 |
|
F |
9.28 |
3.31 |
3.60 |
2.85 |
6.81 |
4.94 |
4.76 |
3.61 |
2.87 |
5.15 |
|
P |
0.03* |
0.01* |
0.01* |
0.02* |
0.00** |
0.00** |
0.00** |
0.01* |
0.02* |
0.01* |
|
3.1 What are the sources of family income during the pandemic? |
|||||||||||
Related social and unit welfare such as allowances or insurance |
6.92 ± 1.82 |
12.77 ± 2.97 |
15.67 ± 4.51 |
5.49 ± 1.64 |
40.85 ± 7.03 |
3.35 ± 0.97 |
17.19 ± 3.67 |
4.87 ± 1.78 |
20.09 ± 5.86 |
45.49 ± 10.55 |
|
Family savings |
6.87 ± 2.23 |
12.71 ± 3.09 |
15.75 ± 3.82 |
4.86 ± 1.59 |
40.19 ± 7.56 |
3.64 ± 1.36 |
16.88 ± 3.90 |
4.70 ± 1.38 |
19.73 ± 5.16 |
44.95 ± 9.61 |
|
Stable income from both parents |
6.43 ± 2.58 |
12.52 ± 3.20 |
14.57 ± 3.72 |
5.04 ± 1.68 |
38.55 ± 7.53 |
3.27 ± 1.05 |
15.84 ± 3.55 |
4.34 ± 1.34 |
17.66 ± 5.31 |
41.11 ± 9.15 |
|
Unilateral less stable income from either parent |
7.15 ± 2.57 |
13.03 ± 3.39 |
15.39 ± 4.18 |
5.25 ± 1.88 |
40.82 ± 8.80 |
3.73 ± 1.44 |
17.07 ± 4.12 |
4.66 ± 1.46 |
19.68 ± 5.32 |
45.14 ± 10.31 |
|
Less stable income from both parents |
6.70 ± 2.05 |
12.28 ± 2.69 |
15.42 ± 3.90 |
5.27 ± 1.68 |
39.67 ± 6.76 |
3.33 ± 0.98 |
16.05 ± 3.95 |
4.60 ± 1.49 |
19.40 ± 6.02 |
43.38 ± 10.45 |
|
F |
1.31 |
1.94 |
1.42 |
2.40 |
2.42 |
2.40 |
2.17 |
2.02 |
2.29 |
2.84 |
|
p |
3.35 |
0.17 |
0.19 |
0.03* |
0.08 |
0.03* |
0.05 |
0.07 |
0.04* |
0.02* |
|
3.2 What about the degree of family income stability during the pandemic? |
|||||||||||
Very stable |
6.19 ± 1.95 |
12.20 ± 2.65 |
14.14 ± 4.62 |
5.00 ± 1.75 |
37.53 ± 7.19 |
3.15 ± 0.84 |
15.77 ± 3.75 |
4.11 ± 1.39 |
17.32 ± 5.67 |
40.36 ± 9.77 |
|
General stable |
6.70 ± 1.98 |
12.33 ± 2.91 |
15.09 ± 3.57 |
5.14 ± 1.67 |
39.26 ± 6.77 |
3.51 ± 1.20 |
16.45 ± 3.91 |
4.60 ± 1.46 |
19.19 ± 5.37 |
43.74 ± 9.89 |
|
Not very stable |
7.21 ± 2.73 |
13.29 ± 3.39 |
15.88 ± 4.21 |
5.23 ± 1.82 |
41.60 ± 8.88 |
3.69 ± 1.40 |
17.00 ± 3.99 |
4.72 ± 1.43 |
19.91 ± 5.47 |
45.32 ± 10.26 |
|
Very unstable |
7.12 ± 2.78 |
12.75 ± 3.41 |
16.29 ± 4.33 |
4.80 ± 1.68 |
40.96 ± 8.14 |
3.38 ± 1.36 |
17.29 ± 4.09 |
5.00 ± 1.47 |
20.21 ± 5.56 |
45.88 ± 9.83 |
|
F |
3.01 |
3.76 |
3.30 |
0.66 |
4.95 |
2.41 |
1.65 |
2.78 |
2.95 |
3.29 |
|
P |
0.03* |
0.02* |
0.02* |
0.57 |
0.01* |
0.06 |
0.17 |
0.04* |
0.03* |
0.02* |
|
4.1 What about the degree of personal protective behaviors after the pandemic? (such as frequent hand washing, ventilation, etc) |
|||||||||||
Pay more attention |
6.67 ± 2.16 |
12.57 ± 3.04 |
15.26 ± 4.04 |
5.76 ± 1.22 |
39.67 ± 7.60 |
3.43 ± 1.18 |
16.53 ± 3.87 |
4.57 ± 1.45 |
18.99 ± 5.37 |
43.53 ± 9.87 |
|
Pay attention occasionally |
7.51 ± 2.76 |
13.13 ± 3.34 |
15.76 ± 4.00 |
4.96 ± 1.70 |
41.37 ± 8.45 |
3.91 ± 1.48 |
16.92 ± 4.18 |
4.78 ± 1.38 |
20.54 ± 5.55 |
46.14 ± 10.18 |
|
Pay less attention |
11.00 ± 3.68 |
15.75 ± 4.72 |
17.75 ± 2.05 |
7.00 ± 1.42 |
51.50 ± 6.69 |
5.50 ± 1.43 |
21.00 ± 3.58 |
6.25 ± 1.53 |
27.25 ± 5.18 |
60.00 ± 9.88 |
|
F |
13.20 |
3.59 |
1.48 |
3.45 |
7.25 |
11.93 |
3.46 |
4.00 |
8.55 |
9.07 |
|
p |
0.00** |
0.03* |
0.23 |
0.03* |
0.00** |
0.00** |
0.03* |
0.02* |
0.00** |
0.00** |
|
4.2 After the pandemic, what about the frequency of your attention to the news of the pandemic? |
|||||||||||
Every day |
6.80 ± 2.22 |
12.72 ± 3.34 |
15.41 ± 3.91 |
5.01 ± 1.77 |
39.95 ± 7.96 |
3.45 ± 1.27 |
16.85 ± 4.11 |
4.67 ± 1.48 |
19.14 ± 5.57 |
44.1 ± 10.441 |
|
Occasionally |
6.77 ± 2.52 |
12.48 ± 2.82 |
15.25 ± 3.91 |
5.22 ± 1.71 |
39.72 ± 7.50 |
3.46 ± 1.24 |
16.30 ± 3.72 |
4.60 ± 1.43 |
19.20 ± 5.27 |
43.55 ± 9.64 |
|
Pay less attention |
9.63 ± 3.39 |
16.50 ± 5.13 |
17.63 ± 2.79 |
6.50 ± 1.42 |
50.25 ± 10.75 |
4.75 ± 1.54 |
21.13 ± 3.97 |
5.13 ± 1.61 |
23.00 ± 6.49 |
54.00 ± 11.19 |
|
Concerned when there is an outbreak in some areas |
6.96 ± 1.98 |
12.80 ± 2.93 |
15.41 ± 1.41 |
5.08 ± 1.69 |
40.24 ± 7.50 |
3.75 ± 1.28 |
16.57 ± 3.85 |
4.55 ± 1.43 |
19.82 ± 5.57 |
44.69 ± 9.84 |
|
F |
4.87 |
5.37 |
1.13 |
2.59 |
5.92 |
4.53 |
5.11 |
0.58 |
1.86 |
3.56 |
|
p |
0.00** |
0.00** |
0.00** |
0.10 |
0.052 |
0.00** |
0.00** |
0.62 |
0.13 |
0.01* |
|
4.3 Hoarding of face masks after the pandemic. |
|||||||||||
Still storing a lot |
6.96 ± 2.32 |
12.93 ± 3.49 |
15.56 ± 4.01 |
5.14 ± 1.72 |
40.58 ± 8.05 |
3.55 ± 1.25 |
17.03 ± 3.85 |
4.78 ± 1.46 |
19.40 ± 5.33 |
44.75 ± 9.85 |
|
Just storing some for usage |
6.78 ± 2.19 |
12.50 ± 2.79 |
15.06 ± 3.92 |
5.09 ± 1.75 |
39.43 ± 7.52 |
3.50 ± 1.23 |
16.26 ± 3.96 |
4.49 ± 1.42 |
19.18 ± 5.48 |
43.44 ± 10.14 |
|
Purchase as needed |
7.45 ± 4.10 |
13.59 ± 4.14 |
18.02 ± 3.95 |
5.78 ± 1.60 |
44.84 ± 8.92 |
3.96 ± 1.83 |
18.54 ± 3.82 |
5.05 ± 1.58 |
21.51 ± 6.28 |
49.06 ± 10.01 |
|
F |
1.06 |
2.04 |
6.48 |
1.77 |
5.86 |
1.45 |
5.05 |
3.29 |
2.01 |
3.93 |
|
p |
0.35 |
0.21 |
0.02* |
0.17 |
0.03* |
0.23 |
0.01* |
0.04* |
1.35 |
0.02* |
|
4.7 Daily intake of other snacks |
|||||||||||
Always |
7.69 ± 2.61 |
14.19 ± 3.92 |
14.00 ± 3.46 |
4.50 ± 1.74 |
40.38 ± 8.78 |
4.13 ± 1.63 |
17.75 ± 3.66 |
5.25 ± 1.75 |
21.19 ± 5.22 |
48.31 ± 9.81 |
|
Often |
7.25 ± 2.79 |
12.81 ± 2.94 |
15.77 ± 4.11 |
5.29 ± 1.81 |
41.11 ± 7.86 |
3.74 ± 1.33 |
16.67 ± 4.01 |
4.71 ± 1.50 |
19.96 ± 5.82 |
45.08 ± 10.86 |
|
Occasionally |
6.73 ± 2.20 |
12.64 ± 3.14 |
15.38 ± 4.06 |
5.16 ± 1.70 |
39.92 ± 7.95 |
3.47 ± 1.27 |
16.68 ± 4.06 |
4.58 ± 1.44 |
19.13 ± 5.35 |
43.86 ± 9.98 |
|
Seldom |
6.69 ± 2.09 |
12.40 ± 3.17 |
14.81 ± 3.41 |
4.90 ± 1.70 |
38.79 ± 7.11 |
3.31 ± 0.97 |
15.81 ± 3.09 |
4.40 ± 1.25 |
18.44 ± 5.03 |
41.96 ± 8.37 |
|
Never |
5.63 ± 1.25 |
12.81 ± 3.29 |
20.31 ± 2.58 |
6.88 ± 0.72 |
45.63 ± 2.39 |
3.44 ± 1.20 |
21.88 ± 1.25 |
5.63 ± 1.25 |
25.63 ± 8.20 |
56.56 ± 6.88 |
|
F |
1.95 |
1.32 |
2.72 |
2.21 |
1.43 |
2.47 |
2.86 |
1.97 |
2.80 |
3.43 |
|
p |
0.11 |
0.26 |
0.03* |
0.07 |
0.22 |
0.04* |
0.02* |
0.09 |
0.03* |
0.01* |
|
a,b pairwise differences at 0.05 level. * p < 0.05, ** p < 0.01. |
Based on the results of t-test and ANOVA, general linear regression analyses were performed to explore independent factors influencing the levels of SAS and SDS. The linear regression analyses showed that parents with chronic illnesses requiring long-term treatment or medication was statistically significant with both SAS and SDS (p < 0.05). Besides, for the questions related to the post-COVID-19 pandemic, the questions in three categories were associated with students SAS total scores and SDS total scores in the general linear regression model. Table 6 showed the results of independent influencing factors of SAS/SDS in the multiple linear regression model. For example, the 3th category: the stability of family income was statistically significant differences to both SAS (β = 0.135, p = 0.002) and SDS (β = 0.116, p = 0.008).
Variables |
SAS |
SDS |
||||||||
---|---|---|---|---|---|---|---|---|---|---|
B |
SE |
β |
t |
p |
B |
SE |
β |
t |
p |
|
Basic demographic information: Parents with chronic illnesses requiring long-term treatment or medication |
0.973 |
0.322 |
0.136 |
3.021 |
0.003** |
0.012 |
0.004 |
0.125 |
2.794 |
0.005* |
2.1: What about the feelings for the development of pandemic? |
-0.488 |
0.272 |
-0.079 |
-1.792 |
0.074 |
-0.009 |
0.003 |
-0.108 |
-2.445 |
0.015* |
2.2: Are you feeling more stressful in the post-pandemic era due to the specificity of your major? |
-1.550 |
0.440 |
-0.155 |
-3.525 |
0.000** |
-0.021 |
0.006 |
-0.161 |
-3.654 |
0.000** |
3.2: What about the degree of family income stability during the pandemic? |
1.445 |
0.470 |
0.135 |
3.075 |
0.002** |
0.016 |
0.006 |
0.116 |
2.652 |
0.008** |
4.1: What about the degree of personal protective behaviors after the pandemic(such as frequent hand washing, ventilation, etc.) |
2.434 |
0.807 |
0.134 |
3.016 |
0.003** |
0.036 |
0.010 |
0.154 |
3.473 |
0.001** |
* p < 0.05, ** p < 0.01. |
Many countries were experiencing varying degrees of suffering due to the COVID-19 pandemic which affected each aspect of society statement or personal life [30]. In our study, the more nursing students impressed psychological disorders of “depression” (14.7%) compared to the “anxiety” (9.1%) in post-COVID-19 era which were in line with previous studies that young people, especially medical university students, were at higher risk of mental health symptom especially anxiety and depression in face of a “Public Health Emergency” [31, 32]. Therefore the aim of this study was to evaluate the current psychological status and explore their important influencing factors in order to develop guidelines for psychological interventions, which was a necessary measure among nursing students in Inner Mongolia Minzu university of China during the post-COVID-19 pandemic.
Based on our study, it was worth to note that “the specificity of major as nursing students” significantly influenced students' anxiety and depression in the post-pandemic era (p < 0.001), which meant psychological disorders were more easily influenced to nursing students in the post-COVID-19 pandemic. Due to the specific characteristics of their major, they may expose to a deeper and broader range of expertise and had deeper understanding the severity of the pandemic than others. Further, they often come in contact with vulnerable patients which may had placed them in a more stressful environment for a long time [19]. Daniel Sperling indicated that nurses had a dilemma over nurses’ duty or self-care during the COVID-19 pandemic, which may increase perceived anxiety for the choice of future career among medical students [33].
The study pointed out that “the degree of family income stability during the pandemic” was an independent influencing factor to affect anxiety and depression (p < 0.05). We found students with unstable family incomes during the pandemic had higher anxiety and depression levels than those with stable family incomes. As mentioned in the literature review, people who had experienced COVID-induced economic shocks, such as income loss, were more likely to have worse mental health [35]. The instability family income viewed as an immediate effect of work and life insecurity which led them to be worried about financial difficulties [36]. In China, most of students indicated that they could complete education mainly depended on family savings or their parents' unstable jobs, which they were lack of confidence and unknown for future due to financially constrained to a certain extent [16]. Especially in our study, Inner Mongolia is located a remote region with a weak economy and has faced many problems in economic development for a long time. While many economic industries in Inner Mongolia have declined slightly to lead tougher social economic situation and more serious family economic burden influenced by the pandemic which may lead a more serious psychological impact [37].
“Parents with chronic illnesses requiring long-term treatment or medication” and “personal protective behaviors” were also important factors to influence the psychological disorders after the pandemic (p<0.05). According to our survey, students had higher levels of anxiety and depression as their parents suffered from chronic illnesses which have confirmed in the previous study [38]. Chinese families played an important role in the overall condition of their children as important economic and spiritual support [16]. Especially, under the influencing of the pandemic, students raised more concerns about the physical situation of their parents with chronic illness, which exacerbated the emotional burden on themselves [39]. In addition, students who paid more attention to protective behaviors had the lowest level of anxiety (39.67 ± 7.60) and depression (43.53 ± 9.87) in our study, which were consistent with previous conclusion [40]. A study found that outbreak could be controlled in a certain level by actively protective behaviors which was associated with a low prevalence of depression and anxiety disorders in China [41]. Therefore we should keep a rational attitude to face the pandemic.
Another interesting finding was that “feelings for the development of pandemic” was associated with depression only (p<0.001). Our study suggested that depression might be more likely to occur and be influenced to those who felt fearful and unknown about the pandemic development. This finding was consistent with the previous results among German and Ecuador college students [42, 43]. In addition, there were also some factors associated with anxiety/depression in the univariate analysis. The results showed that students who chose to “buy face masks when they needed” and “live with friends during the pandemic” might increase the level of anxiety and depression. For depression only, “daily snacks intake” could affect depression independently.
Our study had some limitations that need to be recognized. First, this study used a cross-sectional approach and did not follow up with participants, we suggested that future studies should combine longitudinal with cross-sectional research to explore the influencing factors of students’ psychology over a longer period of time. Second, our questions related pandemic were not comprehensive, which may limited the diversity of their association with anxiety and depression. Third, as the study was conducted in a post-COVID-19 area with low risk, it may be a snapshot to affect the low level of psychological disorders and lead to confounding bias among the nursing students of this university.
To summarize, we reported a cross-sectional analysis about psychological status and explore its influencing factors among nursing students of Inner Mongolia Minzu university in the post-COVID-19 pandemic. Psychological disorders, particularly depression were more common compared to anxiety after the COVID-19 pandemic in our study. We could infer that “the specificity of major”, “the degree of family income stability”, “personal protective behaviors” and “parental health status” might be the main independent influences on both anxiety and depression among nursing students. Based on above results, we proposed that the psychological construction of medical-related students should be encouraged in the future, providing a good environment for their psychological and behavioral guidance. At the same time, the government should adopt relevant policies to support those students with family economic instability and poor physical condition of parents, in order to reduce anxiety and depression in response to public health emergencies.
SAS: Self-Rating Anxiety Scale; SDS: Self-Rating Depression Scale; KMO: Kaiser-Meyer-Olkin; COVID-19: Coronavirus Disease 2019; M+SD: Mean±Standard Deviation.
Ethics Approval and consent to participate
The study was approved by Ethics Committee of Inner Mongolia Minzu University and written informed consent was obtained from all participants. All methods were carried out in accordance with relevant guidelines and regulations. This study was carried out in compliance with the STROBE guidelines.
Consent for publication
Not applicable.
Availability of data and materials
The datasets used and/or analyzed in the present study are available from the corresponding author on reasonable request.
Competing interest
There are no known competitive financial interests or personal relationships that may affect the work described herein.
Funding statement
This survey was financially supported by National Natural Science Foundation of China in 2015[grant number 81560737]/2019[grant number 81960831].
Author’s contributions
XB and HLZ was in charge of the study design. QZ, SZ and CXW contributed to questionnaire survey, data collection and formal analysis. XB and QZ drafting and revising the manuscript. XB, QZ, CXW and HLZ provided some valuable advice and review the manuscript. All authors agreed upon the final form of manuscript before submission.
Acknowledgement
We would like to thank all the participants in this study.