
==== Front
Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

MD-D-24-03788
00087
10.1097/MD.0000000000039519
3
5000
Research Article
Observational Study
Depression, anxiety, and stress among vocational college students during the initial stage of post-epidemic era: A cross-sectional study
https://orcid.org/0009-0008-8956-7666
Wu Lanhua MS a*
Liu Yingling PhD 1228170614@qq.com
b
a Department of Mental Health Education, School of Marxism, Zhejiang Technical Institute of Economics, Hangzhou, China
b Editorial Department of Journal, Dali University, Dali, China.
* Correspondence: Lanhua Wu, Department of Mental Health Education, School of Marxism, Zhejiang Technical Institute of Economics, Hangzhou, Zhejiang, China (e-mail: wulanhua1977@126.com).
06 9 2024
06 9 2024
103 36 e3951914 4 2024
03 7 2024
09 8 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

The purpose of this study was to assess the prevalence and sociodemographic determinants of depression, anxiety, and stress among vocational college students. 1255 students participated in the cross-sectional study. The Chinese version of the 21-item the Depression Anxiety Stress Scales (DASS-21) was used. Depression was reported in 37.6% of vocational college students, anxiety in 51.6%, and stress in 38.1%. Logistic regression results showed that a higher degree of depression, anxiety, and stress was associated with female, poor and moderate self-rated health status, from other provinces, poor self-rated family financial status and living off campus (P < .05). Junior and from one-parent or parentless family were more likely to experience depression and stress (P < .05). Additionally, the likelihood of having depression was higher in non-only-child students (P < .01) and rural family location was a risk factor for stress (P < .001). A higher prevalence of depression, anxiety, and stress was found in vocational college students. Timely and targeted psychological interventions should be taken.

anxiety
depression
stress
vocational college students
Zhejiang Province Higher Vocational Education Teaching Reform Project during the14th Five-Year Plan Periodjg20230301 lanhua WUOPEN-ACCESSTRUE
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pmc 1. Introduction

The novel coronavirus infection (COVID-19) suddenly occurred and spread rapidly around the world at the end of 2019. On January 21, 2020, National Health Commission of the People’s Republic of China announced that COVID-19 infection was classified as a Class B infectious disease, and its prevention and control measures will be taken for Class A infectious diseases. COVID-19 has led to substantial global panic. It not only caused a number of physical problems but also affected people’s mental health. People across the globe experienced anxiety, depression, stress and other negative emotions.[1–3] The COVID-19 pandemic also increased risk factors for suicide.[4] The higher education industry is one of the most affected fields. College students are often considered the future of society, and their mental states should be taken seriously. Surveys conducted in mainland China, Japan, and South Korea also showed an increase in the number of students suffering from negative emotions and mental health problems during COVID-19.[5–7]

The psychological symptoms of college students were higher during COVID-19 than before the epidemic.[8–10] As the epidemic stabilized, the psychological health of college students also gradually stabilized.[11] Students’ self-reported levels of mental health symptoms (depression, anxiety and post-traumatic stress disorder) significantly decreased from May 2020 to September 2020.[12] After 3 years of suffering from COVID-19 epidemic, Comprehensive Group of Joint Prevention and Control Mechanism on Coping with the Novel Coronavirus of China’s State Council issued “Notice on Further Optimizing the Implementation of COVID-19 Prevention and Control Measures” (“Ten new guidelines” for short) on December 7, 2022. With the implementation of this policy, COVID-19 infection has been reduced to Class B and Class B, and China’s epidemic control measures have been basically lifted. In this condition, college students may be more prone to mental health problems. Although many studies have explored the mental health of college students during the COVID-19 pandemic,[13–16] there has been little research concerning mental problems during the initial stage of post-epidemic era in vocational college students. Depression, anxiety, and stress are important indicators of common mental health problems.[17] Our study used a cross-sectional design to investigate the prevalence of depression, anxiety, and stress among vocational college students during the initial period of post-epidemic era. In addition, we further analyzed the sociodemographic determinants affecting students’ depression, anxiety, and stress to provide a basis for targeted interventions by colleges and universities.

2. Materials and methods

2.1. Participants

The study used a cross-sectional design. The data was collected from a convenience sample of 1255 students at a higher vocational college in Hangzhou, China. They were invited to complete the questionnaire from December 10 to 30, 2022. Informed consent was obtained from all the participants prior to the study. The study was approved by the Institutional Review Board of the School of Marxism, Zhejiang Technical Institute of Economics (No. 20221101).

2.2. Questionnaire

There are 2 sections to the survey questionnaire. The first segment collected participants’ gender, grade, major, only-child or not, self-rated health status, family location, region of family residence, self-rated family financial status, family structure and “Where do you live now.” The second segment investigated the participants’ depression, anxiety and stress. In our study, we used Chinese version of the 21-item Depression Anxiety Stress Scales (DASS-21).[18] DASS-21 is a self- administered tool used to assess the severity of depression, anxiety, and stress. It comprises 21 items with 3 subscales of depression, anxiety and stress. Each subscale is made up of 7 items.

Each item is rated on 4-point scales from 0 to 3. Scores of each subscale were multiplied by 2 and compared with the cutoff values of conventional severity labels. The following cutoff scores have been developed for defining normal, mild, moderate, severe and extremely severe scores respectively for each subscale: depression (0–9, 10–13, 14–20, 21–27, 28+), anxiety (0–7, 8–9, 10–14, 15–19, 20+), and stress (0–14, 15–18, 19–25, 26–33, 34+). The Cronbach’s alpha is 0.83, 0.80, and 0.82 for the depression, anxiety, and stress subscales, respectively, and 0.92 for the total DASS total.

2.3. Statistical analysis

The analysis was performed in IBM SPSS windows version 22.0. The prevalence of depression, anxiety, and stress was computed with frequency and percentage of cases. The Kruskal–Wallis H test was used to explore the differences in depression, anxiety, and stress based on participants’ characteristics. Ordinal logistic regression was performed to identify the risk factors of depression, anxiety, and stress.

3. Results

3.1. Participants’ characteristics

The participants were largely female (60.4%), freshmen (53.4%), and majored in economy (61.8%); Nearly 3 quarters (73.7%) of respondents were non-only-child, self-rated health status in moderate (48.8%) and came from rural areas (62.7%). Further details are displayed in Table 1.

Table 1 Participant characteristics (n, %).

Variables	n	%	
Gender			
Male	497	39.6	
Female	758	60.4	
Grade			
Freshman	670	53.4	
Sophomore	393	31.3	
Junior	192	15.3	
Specialty			
Liberal arts	175	14.0	
Economy	776	61.8	
Science	304	24.2	
Only-child or not			
Yes	330	26.3	
No	925	73.7	
Self-rated health status			
Poor	65	5.2	
Moderate	613	48.8	
Good	577	46.0	
Family location			
Rural	787	62.7	
Urban	468	37.3	
Region of family residence			
Hangzhou city	184	14.7	
Zhejiang province(non Hangzhou city)	764	60.9	
Other provinces	307	24.4	
Self-rated family financial status			
Poor	188	15.0	
Middle	946	75.4	
Rich	121	9.6	
Family structure			
Two-parent family	1099	87.6	
Single-parent or parentless family	156	12.4	
Where do you live now			
At home	513	40.9	
In dormitory	682	54.3	
Off campus	60	4.8	

3.2. Levels of depression, anxiety, and stress

Based on DASS-21, Figure 1 showed that 37.6% of students suffered from different degrees of depression (mild 21.3%, moderate 11.4%, severe 3.3%, and extremely severe 1.6%). Also, 51.6% of students suffered from different degrees of anxiety (mild 19.3%, moderate 25.3%, severe 4.3%, and extremely severe 2.7%). Moreover, 38.1% suffered from different degrees of stress (mild 19.9%, moderate 10.0%, severe 4.7%, and extremely severe 3.5%).

Figure 1. Depression, anxiety, and stress status of participants. As can be seen from the figure, the prevalence of depression, anxiety, and stress was higher in vocational college students. Anxiety had the highest percentage, followed by depression and stress.

The Kruskal–Wallis H test can be used to determine if there is a statistically significant difference between the 2 or more groups of an independent variable on a continuous or ordinal dependent variable.[19] There were significant differences in gender, grade, only-child or not, self-rated health status, region of family residence, self-rated family financial status, family structure and “where do you live now” (P < .05; Table 2). Gender, grade, self-rated health status, region of family residence, self-rated family financial status, family structure and “where do you live now” influenced anxiety (P < .05; Table 3). The differences in gender, grade, only-child or not, self-rated health status, family location, region of family residence, self-rated family financial status, family structure and “where do you live now” were statistically significant (P < .05; Table 4). There were no significant differences of depression, anxiety, and stress in specialty.

Table 2 Sociodemographical variable’s distribution by different levels of depression (n, %).

Variables	Total participants	0~9 Normal	10~13 Mild	14~20 Moderate	21~27 Severe	28+ Extremely severe	H	P	
Gender							14.126	<.001	
Male	497 (39.6)	338 (68.0)	101 (20.3)	43 (8.7)	10 (2.0)	5 (1.0)			
Female	758 (60.4)	445 (58.7)	166 (21.9)	100 (13.2)	32 (4.2)	15 (2.0)			
Grade							20.537	<.001	
Freshman	670 (53.4)	426 (63.6)	135 (20.1)	73 (10.9)	26 (3.9)	10 (1.5)			
Sophomore	393 (31.3)	264 (67.2)	77 (19.6)	41 (10.4)	6 (1.5)	5 (1.3)			
Junior	192 (15.3)	93 (48.4)	55 (28.6)	29 (15.1)	10 (5.2)	5 (2.6)			
Specialty							4.319	.115	
Liberal arts	175 (14.0)	98 (56.0)	43 (24.6)	19 (10.9)	12 (6.9)	3 (1.7)			
Economy	776 (61.8)	494 (63.7)	168 (21.6)	82 (10.6)	23 (3.0)	9 (1.2)			
Science	304 (24.3)	191 (62.8)	56 (18.4)	42 (13.8)	7 (2.3)	8 (2.6)			
Only-child or not							6.510	<.05	
Yes	330 (26.3)	223 (67.6)	67 (20.3)	30 (9.1)	6 (1.8)	4 (1.2)			
No	925 (73.7)	560 (60.5)	200 (21.6)	113 (12.2)	36 (3.9)	16 (1.7)			
Self-rated health status							34.049	<.001	
Poor	65 (5.2)	28 (43.1)	10 (15.4)	20 (30.8)	4 (6.2)	3 (4.6)			
Moderate	613 (48.8)	356 (58.1)	146 (23.8)	77 (12.6)	25 (4.1)	9 (1.5)			
Good	577 (46.0)	399 (69.2)	111 (19.2)	46 (8.0)	13 (2.3)	8 (1.4)			
Family location							1.377	<.241	
Rural	787 (62.7)	488 (62.0)	153 (19.4)	96 (12.2)	34 (4.3)	16 (2.0)			
Urban	468 (37.3)	295 (63.0)	114 (24.4)	47 (10.0)	8 (1.7)	4 (0.9)			
Region of family residence							25.870	<.001	
Hangzhou city	184 (14.7)	121 (65.8)	43 (23.4)	15 (8.2)	4 (2.2)	1 (0.5)			
Zhejiang province (non-Hangzhou city)	764 (60.9)	503 (65.8)	153 (20.0)	83 (10.9)	13 (1.7)	12 (1.6)			
Other provinces	307 (24.5)	159 (51.8)	71 (23.1)	45 (14.7)	25 (8.1)	7 (2.3)			
Self-rated family financial status							29.402	<.001	
Poor	188 (15.0)	84 (44.7)	59 (31.4)	27 (14.4)	12 (6.4)	6 (3.2)			
Middle	946 (75.4)	618 (65.3)	182 (19.2)	107 (11.3)	28 (3.0)	14 (1.5)			
Rich	121 (9.6)	81 (66.9)	26 (21.5)	12 (9.9)	2 (1.7)	0 (0.0)			
Family structure							15.409	<.001	
Two-parent family	1099 (87.6)	701 (63.8)	242 (22.0)	116 (10.6)	28 (2.5)	12 (1.1)			
One-parent or parentless family	156 (12.4)	82 (52.6)	25 (16.0)	27 (17.3)	14 (9.0)	8 (5.1)			
Where do you live now							18.428	<.001	
At home	513 (40.9)	342 (66.7)	99 (19.3)	57 (11.1)	10 (1.9)	5 (1.0)			
In dormitory	682 (54.3)	418 (61.3)	145 (21.3)	79 (11.6)	28 (4.1)	12 (1.8)			
Off campus	60 (4.8)	23 (38.3)	23 (38.3)	7 (11.7)	4 (6.7)	3 (5.0)			

Table 3 Sociodemographical variable’s distribution by different levels of anxiety (n, %).

Variables	Total participants	0~7 Normal	8~9 Mild	10~14 Moderate	15~19 Severe	20+ extremely severe	H	P	
Gender							9.207	<.01	
Male	497 (39.6)	257 (51.7)	112 (22.5)	100 (20.1)	19 (3.8)	9 (1.8)			
Female	758 (60.4)	350 (46.2)	130 (17.2)	218 (28.8)	35 (4.6)	25 (3.3)			
Grade							11.677	<.01	
Freshman	670 (53.4)	347 (51.8)	104 (15.5)	171 (25.5)	32 (4.8)	16 (2.4)			
Sophomore	393 (31.3)	187 (47.6)	96 (24.4)	93 (23.7)	11 (2.8)	6 (1.5)			
Junior	192 (15.3)	73 (38.0)	42 (21.9)	54 (28.1)	11 (5.7)	12 (6.3)			
Specialty							4.186	.123	
Liberal arts	175 (14.0)	77 (44.0)	31 (17.7)	49 (28.0)	11 (6.3)	7 (4.0)			
Economy	776 (61.8)	390 (50.3)	142 (18.3)	200 (25.8)	28 (3.6)	16 (2.1)			
Science	304 (24.3)	140 (46.1)	69 (22.7)	69 (22.7)	15 (4.9)	11 (3.6)			
Only-child or not							3.088	.079	
Yes	330 (26.3)	173 (52.4)	62 (18.8)	73 (22.1)	14 (4.2)	8 (2.4)			
No	925 (73.7)	434 (46.9)	180 (19.5)	245 (26.5)	40 (4.3)	26 (2.8)			
Self-rated health status							23.673	<.001	
Poor	65 (5.2)	23 (35.4)	15 (23.1)	11 (16.9)	11 (16.9)	5 (7.7)			
Moderate	613 (48.8)	267 (43.6)	125 (20.4)	177 (28.9)	28 (4.6)	16 (2.6)			
Good	577 (46.0)	317 (54.9)	102 (17.7)	130 (22.5)	15 (2.6)	13 (2.3)			
Family location							2.999	.083	
Rural	787 (62.7)	365 (46.4)	165 (21.0)	189 (24.0)	40 (5.1)	28 (3.6)			
Urban	468 (37.3)	242 (51.7)	77 (16.5)	129 (27.6)	14 (3.0)	6 (1.3)			
Region of family residence							27.493	<.001	
Hangzhou city	184 (14.7)	98 (53.3)	34 (18.5)	47 (25.5)	3 (1.6)	2 (1.1)			
Zhejiang province (non-Hangzhou city)	764 (60.9)	396 (51.8)	144 (18.8)	177 (23.2)	32 (4.2)	15 (2.0)			
Other provinces	307 (24.5)	113 (36.8)	64 (20.8)	94 (30.6)	19 (6.2)	17 (5.5)			
Self-rated family financial status							27.918	<.001	
Poor	188 (15.0)	60 (31.9)	46 (24.5)	58 (30.9)	9 (4.8)	15 (8.0)			
Middle	946 (75.4)	480 (50.7)	170 (18.0)	235 (24.8)	43 (4.5)	18 (1.9)			
Rich	121 (9.6)	67 (55.4)	26 (21.5)	25 (20.7)	2 (1.7)	1 (0.8)			
Family structure							11.615	<.01	
Two-parent family	1099 (87.6)	547 (49.8)	215 (19.6)	268 (24.4)	43 (3.9)	26 (2.4)			
One-parent or parentless family	156 (12.4)	60 (38.5)	27 (17.3)	50 (32.1)	11 (7.1)	8 (5.1)			
Where do you live now							17.709	<.001	
At home	513 (40.9)	263 (51.3)	109 (21.2)	121 (23.6)	14 (2.7)	6 (1.2)			
In dormitory	682 (54.3)	330 (48.4)	112 (16.4)	182 (26.7)	34 (5.0)	24 (3.5)			
Off campus	60 (4.8)	14 (23.3)	21 (35.0)	15 (25.0)	6 (10.0)	4 (6.7)			

Table 4 Sociodemographical variable’s distribution by different levels of stress (n, %).

Variables	Total participants	0~14 Normal	15~18 Mild	19~25 Moderate	26~33 Severe	34+ Extremely severe	H	P	
Gender							8.954	<.01	
Male	497 (39.6)	328 (66.0)	101 (20.3)	42 (8.5)	14 (2.8)	12 (2.4)			
Female	758 (60.4)	449 (59.2)	148 (19.5)	84 (11.1)	45 (5.9)	32 (4.2)			
Grade							17.702	<.001	
Freshman	175 (14.0)	434 (64.8)	122 (18.2)	68 (10.1)	26 (3.9)	20 (3.0)			
Sophomore	776 (61.8)	249 (63.4)	81 (20.6)	30 (7.6)	18 (4.6)	15 (3.8)			
Junior	304 (24.3)	94 (49.0)	46 (24.0)	28 (14.6)	15 (7.8)	9 (4.7)			
Specialty							5.098	.078	
Liberal arts	167 (13.3)	94 (53.7)	42 (24.0)	24 (13.7)	10 (5.7)	5 (2.9)			
Economy	783 (62.4)	488 (62.9)	161 (20.7)	69 (8.9)	31 (4.0)	27 (3.5)			
Science	305 (24.3)	195 (61.9)	46 (15.1)	33 (10.9)	18 (5.9)	12 (3.9)			
Only-child or not							4.083	<.05	
Yes	330 (26.3)	218 (66.1)	64 (19.4)	26 (7.9)	13 (3.9)	9 (2.7)			
No	925 (73.7)	559 (60.4)	185 (20.0)	100 (10.8)	46 (5.0)	35 (3.8)			
Self-rated health status							28.064	<.001	
Poor	65 (5.2)	27 (41.5)	15 (23.1)	12 (18.5)	4 (6.2)	7 (10.8)			
Moderate	613 (48.8)	357 (58.2)	134 (21.9)	63 (10.3)	34 (5.5)	25 (4.1)			
Good	577 (46.0)	393 (68.1)	100 (17.3)	51 (8.8)	21 (3.6)	12 (2.1)			
Family location							6.691	<.05	
Rural	787 (62.7)	476 (60.5)	134 (17.0)	97 (12.3)	43 (5.5)	37 (4.7)			
Urban	468 (37.3)	301 (64.3)	115 (24.6)	29 (6.2)	16 (3.4)	7 (1.5)			
Region of family residence							39.646	<.001	
Hangzhou city	184 (14.7)	129 (70.1)	36 (19.6)	13 (7.1)	5 (2.7)	1 (0.5)			
Zhejiang province (non-Hangzhou city)	764 (60.9)	497 (65.1)	148 (19.4)	69 (9.0)	30 (3.9)	20 (2.6)			
Other provinces	307 (24.5)	151 (49.2)	65 (21.2)	44 (14.3)	24 (7.8)	23 (7.5)			
Self-rated family financial status							23.076	<.001	
Poor	188 (15.0)	95 (50.5)	38 (20.2)	19 (10.1)	19 (10.1)	17 (9.0)			
Middle	946 (75.4)	597 (63.1)	184 (19.5)	99 (10.5)	40 (4.2)	26 (2.7)			
Rich	121 (9.6)	85 (70.2)	27 (22.3)	8 (6.6)	0 (0)	1 (0.8)			
Family structure							11.277	<.01	
Two-parent family	1099 (87.6)	700 (63.7)	207 (18.8)	108 (9.8)	48 (4.4)	36 (3.3)			
One-parent or parentless family	156 (12.4)	77 (49.4)	42 (26.9)	18 (11.5)	11 (7.1)	8 (5.1)			
Where do you live now							9.683	<.01	
At home	513 (40.9)	322 (62.8)	114 (22.2)	35 (6.8)	25 (4.9)	17 (3.3)			
In dormitory	682 (54.3)	427 (62.6)	125 (18.3)	79 (11.6)	28 (4.1)	23 (3.4)			
Off campus	60 (4.8)	28 (46.7)	10 (16.7)	12 (20.0)	6 (10.0)	4 (6.7)			

3.3. Significant factors for depression, anxiety, and stress

We further performed multivariate ordinal logistic regression analysis to explore the risk factors associated with depression, anxiety, and stress. The ordinal logistic regression model is used in case where the dependent variable has more than 2 categories. Significant variables in the Kruskal–Wallis H test were selected for the ordinal logistic regression. Table 5 demonstrated that female, poor and moderate self-rated health status, from other provinces, poor self-rated family financial status and living off campus were higher likely to have depression, anxiety, and stress. Junior and from one-parent or parentless family were significantly associated with a more likelihood of having depression and stress (P < .05). The likelihood of having depression was higher in non-only-child students (P < .01) and rural family location was a risk factor for stress (P < .001).

Table 5 Ordinal logistic regression analysis of factors influencing participants’ depression, anxiety, and stress.

Variables	Depression	Anxiety	Stress	
β	OR (95% CI)	P	β	OR (95% CI)	P	β	OR (95% CI)	P	
Gender										
Male	−0.49	0.62 (0.48–0.79)	.000	−0.36	0.70 (0.56–0.87)	.001	−0.31	0.73 (0.58–0.93)	.011	
Female*										
Grade										
Freshman	−0.10	0.91 (0.65–1.28)	.574	−0.18	0.84 (0.61–1.16)	.281	−0.19	0.83 (0.59–1.17)	.283	
Sophomore	−0.56	0.57 (0.39–0.84)	.004	−0.20	0.82 (0.57–1.17)	.274	−0.46	0.63 (0.43–0.93)	.018	
Junior*										
Only-child or not										
Yes	−0.42	0.66 (0.50–0.87)	.004	–	–	–	−0.27	0.76 (0.58–1.01)	.054	
No*										
Self-rated health status										
Poor	1.16	3.20 (1.96–5.23)	.000	0.76	2.15 (1.33–3.47)	.002	1.01	2.74 (1.68–4.47)	.000	
Moderate	0.58	1.79 (1.40–2.28)	.000	0.45	1.57 (1.26–1.96)	.000	0.47	1.59 (1.25–2.03)	.000	
Good*										
Family location										
Rural	–	–	–	–	–	–	0.43	1.54 (1.20–1.98)	.001	
Urban*										
Region of family residence										
Hangzhou city	−0.64	0.53 (0.36–0.78)	.001	−0.55	0.58 (0.40–0.82)	.002	−0.91	0.41 (0.27–0.60)	.000	
Zhejiang province (non-Hangzhou)	−0.65	0.52 (0.40–0.69)	.000	−0.58	0.56 (0.4–0.72)	.000	−0.82	0.44 (0.33–0.58)	.000	
Other provinces*										
Self-rated family financial status										
Poor	0.80	2.21 (1.35–3.62)	.002	0.93	2.55 (1.60–4.04)	.000	0.77	2.17 (1.30–3.61)	.003	
Middle	0.09	1.09 (0.71–1.67)	.691	0.32	1.38 (0.94–2.04)	.104	0.26	1.30 (0.84–2.03)	.224	
Rich*										
Family structure										
Two-parent family	−0.51	0.60 (0.43–0.83)	.002	−0.31	0.74 (0.54–1.01)	.059	−0.38	0.69 (0.49–0.95)	.025	
One-parent or parentless family*										
Where do you live now										
At home	−0.66	0.52 (0.30–0.88)	.016	−0.79	0.45 (0.27–0.76)	.003	−0.58	0.56 (0.33–0.95)	.031	
In dormitory	−0.62	0.54 (0.31–0.92)	.023	−0.53	0.59 (0.35–0.99)	.046	−0.67	0.51 (0.30–0.87)	.014	
Off campus*										
* Control.

4. Discussion

The findings showed, during the initial stage of post-epidemic era, the prevalence of depression, anxiety, and stress among vocational college students was 37.6%, 51.6%, and 38.1%, respectively. The figures were higher than those of previous research conducted before COVID-19 and the period of normalization of epidemic prevention and control. Compared to the studies among college students that used the same scale before COVID-19, the prevalence of depression, anxiety and stress in our study was higher than the rates of 28.7%, 41.7% and 20.2% found in our country,[20] and higher than the depression (18.4%), anxiety (23.6%), and stress (34.5%) found among Spanish undergraduate students.[21] The finding of our research was also higher than another study conducted in the period of normalization of epidemic prevention and control, which showed 27.3%, 33.4%and 12.0% of the university students surveyed had mild to extremely severe complains of depression, anxiety and stress, respectively.[22] Our prevalence rates of depression, anxiety, and stress were also higher than the rate of 37%, 29%, and 23% among college students reported from a meta-analysis.[23] The higher prevalence in our study indicated that vocational college students’ mental health may be adversely affected in the initial implementation of “Ten new guidelines.” After the outbreak of the epidemic, the decisive and rapid measures imposed by the Chinese government were instrumental in reducing further spread of the virus.[24] These measures helped Chinese college students establish a correct view of COVID-19 and maintained a rational and peaceful attitude. They adjusted to “new normal life” under COVID-19 and formed inherent behavior patterns such as mask-wearing, scanning travel codes, and so on. In the initial period of post pandemic era, the above-mentioned measures were basically no longer implemented and college students didn’t adapt to this change. Environmental exposure to COVID-19 may represent a psychosocial stressor.[25] College students were worried about their own health and the health of loved ones. Our survey coincided with the upcoming winter vacation in China, when college students were facing challenges such as final exams and returning home. The higher prevalence of depression, anxiety, and stress in our study highlighted the need for enhanced awareness of mental health screening and more attention should be given to the mental health of vocational college students.

This study showed that female, poor and moderate self-rated health status, from other provinces, poor self-rated family financial status and living off campus were more likely to having depression, anxiety, and stress. Females were more prone to depression, anxiety, and stress than males, which was demonstrated previously in some studies. Female students experienced more depression, anxiety, and stress than male students.[13] Women reported higher levels of stress and depression compared with men.[26–28] A higher genetic susceptibility to depression and anxiety was shown in females.[29]

In addition, females are relatively sensitive, and they are more concerned about their academic performances are affected. Additionally, students with poor and moderate self-rated health status experienced higher degrees of depression, anxiety and stress. This was consistent with the research which revealed physical symptoms, poor or very poor self-rating of health status, and history of chronic illness were significantly associated with higher DASS stress, anxiety or depression subscale scores.[30] The students from other provinces have higher risks of depression, anxiety and stress than those of provincial students. The reason behind the result was their long journeys home increased the risk of contracting COVID-19. In addition, they were far away from their family, relatives and friends and didn’t easily go home to enjoy the material and emotional support from them. Furthermore, consistent with the previous research on the association between pandemic’s economic impacts and mental health among various populations,[31] our study showed that poor self-rated family financial status was correlated with a higher risk of depression, anxiety, and stress. Lower socioeconomic status (SES) is associated with worse health and higher mortality rates at virtually every point along the life course.[32] Other research demonstrated experiencing economic strain would be associated with higher levels of negative mental health.[33,34] Finally, college students who live off campus also had a significantly higher risk of depression, anxiety and stress. They went back and forth to their residence-school or residence- internship unit every day, resulting in the risk of infection with COVID-19. Previous studies also found those students living off campus ranked the highest in levels of stress, anxiety, and depression.[35,36]

Junior and from one-parent or parentless family were significantly associated with a more likelihood of having depression and stress. A study found that an increase in the prevalence and severity of depression levels in older students.[37] The final year of a nursing degree as the 1 in which students face the greatest risk of suffering a deterioration in their psychological well- being.[38] Junior students must do their practice and present the graduation thesis. Furthermore, their employment stress increased for the reduced employment opportunities and intense social competition brought about by the epidemic. Another significant factor for depression and stress was family structure. One-parent or parentless family often lead to impaired family function and decreased parental support. Greater family functionality will be associated with a lower prevalence of anxiety, stress, and depressive symptom.[39] Adolescents’ parental support during the pandemic was associated with emotional problems.[40] Single parents endured more life and economic stress that could have a detrimental effect on the mental health of their children.

College students from non-only-child family had higher levels of depression than those from only-child family. The dilution model says, “The more children, the more these resources are divided (even taking account of economies of scale) and, hence, the lower the quality of the output.”[41] Compared with non-only-child students, only-child students have abundant resources and enjoy all the love and care from their parents.

A higher risk of stress was associated with rural family location. This association was supported by the literature.[42,43] Rural college students were relatively deficient in material and economic resources. There are insufficient basic medical resources and weak preventive capacity of grassroots public health in rural areas.

5. Limitations and strengths

Several limitations should be pointed out. First, the present sample came from Hangzhou, which may influence sample representativeness. Therefore, further studies are needed to confirm the generalizability of the results across a more diverse population. Second, the evaluation of health status and family financial status adopted subjective self-assessment method, which may be susceptible to response bias. Future research should consider measuring these variables through serious and delicate objective data. In addition, the current study is its cross-sectional design. A longitudinal study is needed to further examine the status of depression, anxiety, and stress among vocational college students.

6. Conclusions

The results signified that most vocational college students experienced mild to extremely severe depression, anxiety, and stress levels during the initial stage of post-epidemic era. The study also demonstrated the risk factors associated with higher vocational college students’ mental well-being. This highlighted the importance of taking the necessary proactive steps to identify, address, and nurture college students’ mental health to mitigate the negative impacts. In addition, different psychological intervention methods should be taken according to different psychological problems of different objects, so as to timely solve the psychological problems of college students.

Acknowledgments

The authors express their sincere appreciation to all the students who agreed to participate in the study.

Author contributions

Conceptualization: Lanhua Wu, Yingling Liu.

Data curation: Lanhua Wu.

Formal analysis: Yingling Liu.

Funding acquisition: Lanhua Wu.

Investigation: Lanhua Wu.

Methodology: Lanhua Wu, Yingling Liu.

Project administration: Lanhua Wu.

Supervision: Lanhua Wu, Yingling Liu.

Writing – original draft: Lanhua Wu.

Writing – review & editing: Lanhua Wu, Yingling Liu.

Abbreviations:

COVID-19 coronavirus disease 2019

DASS-21 21-item Depression Anxiety Stress Scales.

The study was funded by the Zhejiang Province Higher Vocational Education Teaching Reform Project during the14th Five-Year Plan Period (No. jg20230301).

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

How to cite this article: Wu L, Liu Y. Depression, anxiety, and stress among vocational college students during the initial stage of post-epidemic era: A cross-sectional study. Medicine 2024;103:36(e39519).
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