Escalating progression of mental health disorders during the COVID-19 pandemic: Evidence from a nationwide survey

Li Ping Wong; Haridah Alias; Afiqah Alyaa Md Fuzi; Intan Sofia Omar; Azmawaty Mohamad Nor; Maw Pin Tan; Diana Lea Baranovich; Che Zarrina Saari; Sareena Hanim Hamzah; Ku Wing Cheong; Chiew Hwa Poon; Vimala Ramoo; Chong Chin Che; Kyaimon Myint; Suria Zainuddin; Ivy Chung

doi:10.1371/journal.pone.0248916

. 2021 Mar 25;16(3):e0248916. doi: 10.1371/journal.pone.0248916

Escalating progression of mental health disorders during the COVID-19 pandemic: Evidence from a nationwide survey

Li Ping Wong ^1,^*, Haridah Alias ¹, Afiqah Alyaa Md Fuzi ², Intan Sofia Omar ², Azmawaty Mohamad Nor ³, Maw Pin Tan ⁴, Diana Lea Baranovich ³, Che Zarrina Saari ⁵, Sareena Hanim Hamzah ⁶, Ku Wing Cheong ⁷, Chiew Hwa Poon ⁷, Vimala Ramoo ⁸, Chong Chin Che ⁸, Kyaimon Myint ⁹, Suria Zainuddin ¹⁰, Ivy Chung ^2,^*

Editor: Chung-Ying Lin¹¹

¹Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia

²Department of Pharmacology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia

³Department of Educational Psychology and Counselling, Faculty of Education, University of Malaya, Kuala Lumpur, Malaysia

⁴Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia

⁵Department of Akidah and Islamic Thought, Academy of Islamic Studies, University of Malaya, Kuala Lumpur, Malaysia

⁶Centre for Sport and Exercise Sciences, University of Malaya, Kuala Lumpur, Malaysia

⁷Department of Music, Cultural Centre, University of Malaya, Kuala Lumpur, Malaysia

⁸Department of Nursing Science, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia

⁹Department of Physiology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia

¹⁰Department of Accountancy, Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, Malaysia

¹¹National Cheng Kung University College of Medicine, TAIWAN

Competing Interests: The authors have declared that no competing interests exist.

^✉

* E-mail: wonglp@ummc.edu.my (LPW); ivychung@ummc.edu.my (IC)

Roles

Li Ping Wong: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

Haridah Alias: Data curation, Formal analysis, Methodology, Visualization

Afiqah Alyaa Md Fuzi: Investigation, Project administration

Intan Sofia Omar: Investigation, Project administration

Azmawaty Mohamad Nor: Conceptualization, Investigation, Writing – review & editing

Maw Pin Tan: Conceptualization, Investigation, Writing – review & editing

Diana Lea Baranovich: Conceptualization, Investigation, Writing – review & editing

Che Zarrina Saari: Conceptualization, Investigation, Writing – review & editing

Sareena Hanim Hamzah: Conceptualization, Investigation, Writing – review & editing

Ku Wing Cheong: Conceptualization, Investigation, Writing – review & editing

Chiew Hwa Poon: Conceptualization, Investigation, Writing – review & editing

Vimala Ramoo: Conceptualization, Investigation, Writing – review & editing

Chong Chin Che: Conceptualization, Investigation, Writing – review & editing

Kyaimon Myint: Conceptualization, Investigation, Writing – review & editing

Suria Zainuddin: Conceptualization, Investigation, Writing – review & editing

Ivy Chung: Conceptualization, Funding acquisition, Investigation, Resources, Writing – review & editing

Chung-Ying Lin: Editor

PMCID: PMC7993793 PMID: 33765039

Abstract

Since the first nationwide movement control order was implemented on 18 March 2020 in Malaysia to contain the coronavirus disease 2019 (COVID-19) outbreak, to what extent the uncertainty and continuous containment measures have imposed psychological burdens on the population is unknown. This study aimed to measure the level of mental health of the Malaysian public approximately 2 months after the pandemic’s onset. Between 12 May and 5 September 2020, an anonymous online survey was conducted. The target group included all members of the Malaysian population aged 18 years and above. The Depression Anxiety Stress Scale (DASS-21) was used to assess mental health. There were increased depressive, anxiety and stress symptoms throughout the study period, with the depression rates showing the greatest increase. During the end of the data collection period (4 August–5 September 2020), there were high percentages of reported depressive (59.2%) and anxiety (55.1%) symptoms compared with stress (30.6%) symptoms. Perceived health status was the strongest significant predictor for depressive and anxiety symptoms. Individuals with a poorer health perception had higher odds of developing depression (odds ratio [OR] = 5.68; 95% confidence interval [CI] 3.81–8.47) and anxiety (OR = 3.50; 95%CI 2.37–5.17) compared with those with a higher health perception. By demographics, young people–particularly students, females and people with poor financial conditions–were more vulnerable to mental health symptoms. These findings provide an urgent call for increased attention to detect and provide intervention strategies to combat the increasing rate of mental health problems in the ongoing COVID-19 pandemic.

Introduction

In March 2020, the World Health Organization declared coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a pandemic [1, 2]. COVID-19 has since caused major disruptions throughout the world, including in Malaysia. On 25 January 2020, Malaysian authorities reported the first SARS-CoV-2 infection; subsequently, on 17 March 2020, the first death was reported. Henceforth, the number of infections and deaths has increased exponentially in Malaysia. In the absence of pharmaceutical treatments and a vaccine for COVID-19, community containment measures are essential to limit the spread of SARS-CoV-2. The Malaysian government has implemented several movement control orders (MCOs) based on the current COVID-19 situation in the country. The first MCO included the closure of schools, higher education institutions and non-essential businesses (namely businesses that geared toward recreation or entertainment and those that provide services beyond the basic necessities), as well as a general prohibition of mass movements and gatherings across the country, including religious, sports, social and cultural activities. The first nationwide MCO was implemented on 18 March 2020. Since then, the country has gone through four MCO phases, all of which include the strict actions recommended by the WHO. A conditional movement control order (CMCO) was implemented from 13 May to 9 June 2020, and a recovery movement control order (RMCO) took effect from 10 June 2020 and lasted until 31 August 2020; it had more lenient restrictions. Subsequently, the RMCO was extended until 31 December 2020. To date, the Malaysian government has continuously stressed to the general public the use of face masks in public spaces, frequent hand washing and social distancing in the current ongoing pandemic. Large-scale gatherings are prohibited, but social and recreational activities and businesses are allowed to operate with social distancing measures and temperature checks in place.

Worldwide, measures to fight the COVID-19 outbreak have had tremendous social and economic impacts at both individual and country levels [3, 4]. Social distancing, self-isolation and travel restrictions have led to a reduced workforce across all economic sectors and employment loss. Closure of schools and working from home have impacted business operations, with a consequent decrease in the demand for commodities. In Malaysia, like other countries around the world, the COVID-19 pandemic has caused catastrophic economic and social disruptions [5–7]. The distancing measures, together with employment and financial insecurity, represent a massive mental health crisis affecting the wellbeing of populations throughout the world [8]. In Malaysia, the negative impact on mental health was evident during the early stages of the COVID-19 pandemic [5, 9, 10]. To date, nearly a year after the onset of the pandemic, to what extent the unpredictability and uncertainty of the COVID-19 pandemic and its prolonged physical distancing and containment measures, along with the resulting impact of the economic breakdown, has affected the mental health of the Malaysian public has never been investigated.

Therefore, the main aim of this study was to examine the level and temporal trend of mental health of the Malaysian public during the COVID-19 pandemic. In addition, factors potentially contributing to poor mental health were investigated. These findings will provide insights for the formulation of mitigation measures to help the public cope with the negative mental health effects in the currently unpredictable situation of the COVID-19 pandemic.

Materials and methods

An anonymous Internet-based, cross-sectional survey was commenced on 12 May 2020 and ended on 5 September 2020. The inclusion criteria were that the respondents were from the general Malaysian public and ≥ 18 years old. The exclusion criteria were as follow: having chronic medical conditions, pregnancy or breastfeeding, and have never had SARS-CoV-2 infection. The researchers used social network platforms (Facebook, Twitter, Instagram and WhatsApp) to disseminate and advertise the survey, entitled ‘COVID-19 Health and Wellbeing Survey’, to the public. Questions were presented in both English and Bahasa Malaysia in the survey link. Pilot testing was performed with 30 participants to ensure the clarity of the items and also gather suggestions for improvement. A minor revision was made based on the results of the pilot. Subsequently, the revised questionnaire was further pretested before field administration.

The first section of the survey collected demographic characteristics, participants’ health status and their COVID-19 experience. Health status included participants’ existing chronic diseases and self-perceived overall health status. The participants were asked to indicate whether they know of friends, neighbours or colleagues who had been diagnosed with COVID-19.

The second section assessed mental health using the Depression Anxiety Stress Scale (DASS-21) [11], which is a well-established instrument for measuring depression, anxiety and stress with good reliability and validity. Scores on three subscales–namely Depression (DASS-21-D), Anxiety (DASS-21-A) and Stress (DASS-21-S)–were generated. There are seven items in each subscale; the score of each subscale ranges from 0 to 21. The cut-offs for depression (moderate 7–10, severe 11–13 and extremely severe ≥ 14), anxiety (moderate 6–7, severe 8–9 and extremely severe ≥ 10) and stress (moderate 10–12, severe 13–16 and extremely severe ≥ 17) were calculated [12]. The English version of the DASS-21 has been validated for use in many Asian populations, including Malaysia [13]. The DASS-21 English version has been translated into Bahasa Malaysia and validated [14]; the Bahasa Malaysia DASS-21 has been used in many studies in Malaysia. A recent study evaluated the psychometric properties of the Bahasa Malaysia DASS-21 among non-Malays in Malaysia and revealed good reliability and validity, implying the scales can be used in a multiethnic population in Malaysia [15].

Data analysis

Cronbach’s alpha was calculated for the overall scale and the three subscales to assess reliability in terms of internal consistency. In this study, the DASS-21 had adequate to very good internal consistency, with Cronbach’s alphas of 0.956 for the overall scale, 0.927 for the DASS-21-D, 0.865 for the DASS-21-A and 0.882 for the DASS-21-S.

The temporal trend of the DASS-21-D, DASS-21-A and DASS-21-S scores over the 16-week data collection period was computed. The mean and standard deviation (SD) of the DASS-21 subscale scores were divided into four equal time periods of 4-week intervals: 12 May–7 June, 8 June–5 July, 6 July–3 August and 4 August–5 September. Univariable analyses followed by multivariable logistic regression analyses, using a simultaneous forced-entry method, was used to determine the factors influencing depression, anxiety and stress. Significant predictors at p < 0.05 in a bivariate analysis were exported to the multivariable logistic regression model. The DASS-21-D, DASS-21-A and DASS-21-S scores were grouped into two categories: 1 = moderate/severe/extremely severe and 0 = mild/normal. Odds ratios (ORs), 95% confidence intervals (95% CIs) and p values were calculated for each independent variable. The model fit was assessed using the Hosmer−Lemeshow goodness-of-fit test [16]. Small p values (< 0.05) mean that the model is a poor fit. All statistical analyses were performed using the Statistical Package for the Social Sciences version 20.0 (IBM Corp., Armonk, NY, USA). The level of significance was set at p < 0.05.

Ethical considerations

This research was approved by the University of Malaya Research Ethics Committee (UM.TNC2/UMREC– 884). Participants were informed that their participation was voluntary, and consent was implied by completing the questionnaire.

Results and discussion

Demographics

A total of 1,163 complete responses were received in the 16-week data collection period. Table 1 shows the demographics of the study participants compared with the general adult population in Malaysia [17, 18]. Compared with the general Malaysian population, there was a higher percentage of female respondents, Malay ethnicity, those from the central region and those in the bottom 40% (B40) income group (< MYR4850 [USD1200] per month). The age of the participants ranged from 18 to 84 years (M = 35.2, SD = 11.9). As shown in the first and second columns in Table 2, the majority of the study participants had a diploma or were university graduates. Based on the occupation categories, nearly half were in professional and managerial occupations (50.6%), while general workers and students comprised 7.2% and 29.2%, respectively, of the participants. For all participants, 44.9% reported an average monthly household income of < MYR4000, while 31.8% reported an average monthly household income of MYR4001–8000. The majority of participants were from urban (66.1%) and suburban (26.1%) areas. The majority perceived their overall health as very good/good (85.9%) and the majority (91.5%) did not have any chronic diseases. Only 23.4% reported knowing someone (family members, friends, neighbours or colleagues) who had been diagnosed with or died from COVID-19.

Table 1. Comparison of demographic characteristics of the study population and the general adult population in Malaysia, 2019.

Characteristics	n	% Study population, n = 1163	% Total population, n = 24510400 ^*
Age group (years)
18–29	425	36.5	38.0
30–39	357	30.7	22.0
40–49	217	18.7	15.3
≥ 50	164	14.1	24.7
Gender
Male	217	18.7	51.6
Female	946	81.3	41.4
Ethnicity
Malay	882	75.8	59.1
Chinese	100	8.6	37.4
Indian	108	9.3	29.4
Others	73	6.3	11.3
Average monthly household income (MYR) (Income category group) ^†
Below MYR4850 (B40)	651	56.0	16.0
MYR4850-10959 (M40)	365	31.4	37.2
MYR 10600 and above (T20)	147	12.6	46.8
Region^‡
Northern	157	13.5	20.9
Central	697	59.9	29.7
East coast	186	16.0	13.8
Southern	80	6.9	14.5
Borneo	43	3.7	21.1

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*Total number of adults 15 to 79 years of age as of 31 December 2019. Source: The 2019 Population and Housing Census of Malaysia (Census 2010) Department of Statistics Malaysia.¹⁷

^†Three category of income groups: Top 20% (T20), Middle 40% (M40), and Bottom 40% (B40) in Malaysia. Source: Department of Statistics Malaysia. Household Income and Basic Amenities Survey Report 2019.¹⁸

^‡Northern region (Perlis, Kedah, Perak, Penang); Central (Wilayah Persekutuan Kuala Lumpur, Selangor, Negeri Sembilan, Putrajaya); East coast (Terengganu, Kelantan, Pahang); Southern (Melaka, Johor); Borneo (Sabah, Sarawak, Labuan)

Table 2. Univariable and multivariable analyses of factors associated with symptoms of depression, anxiety and stress (N = 1163).

		Depression			Anxiety			Stress
Socio demographic characteristics	Overall N(%)	Moderate/ Severe/ Extremely severe (n = 344)	p-value	Adjusted OR (95%CI)^a	Moderate/ Severe/ Extremely severe (n = 461)	p-value	Adjusted OR (95%CI)^b	Moderate/ Severe/ Extremely severe (n = 202)	p-value	Adjusted OR (95%CI)^c
Age group (years)
18–25	322 (27.7)	156 (48.4)		2.03 (1.06–3.91)^*	182 (56.5)		1.35 (0.76–2.39)	96 (29.8)		2.73 (1.19–6.23)^*
26–45	592 (50.9)	155 (26.2)	p<0.001	2.07 (1.30–3.30)^**	219 (37.0)	p<0.001	1.43 (0.99–2.08)	93 (15.7)	p<0.001	3.23 (1.72–6.31)^***
> 45	249 (21.4)	33 (13.3)		Ref	60 (24.1)		Ref	13 (5.2)		Ref
Gender
Male	217 (18.7)	56 (25.8)	0.188		73 (33.6)	0.046	Ref	27 (12.4)	0.037	Ref
Female	946 (81.3)	288 (30.4)			388 (41.0)		1.49 (1.06–2.10)^*	175 (18.5)		1.83 (1.14–2.95)^*
Ethnicity
Malay	882 (75.8)	254 (28.8)			362 (41.0)		1.09 (0.64–1.86)	154 (17.5)
Chinese	100 (8.6)	34 (34.0)	0.320		39 (39.0)	0.039	0.69 (0.35–1.36)	22 (22.0)	0.202
Indian	108 (9.3)	29 (26.9)			29 (26.9)		0.50 (0.25–0.99)^*	12 (11.1)
Bumiputera Sabah/ Sarawak/ Others	73 (6.3)	27 (37.0)			31 (42.5)		Ref	14 (19.2)
Marital Status
Never married	490 (42.1)	223 (45.5)	p<0.001	1.71 (0.92–3.16)	262 (53.5)	p<0.001	1.40 (0.82–2.40)	136 (27.8)	p<0.001	2.05 (0.94–4.46)
Ever married	673 (57.9)	121 (18.0)		Ref	199 (29.6)		Ref	66 (9.8)		Ref
Have child/ children
Yes	595 (51.2)	104 (17.5)	p<0.001	Ref	172 (28.9)	p<0.001	Ref	58 (9.7)	p<0.001	Ref
No	568 (48.8)	240 (42.3)		1.17 (0.65–2.09)	289 (50.9)		1.17 (0.71–1.92)	144 (25.4)		0.93 (0.44–1.96)
Highest educational level
Secondary and below	78 (6.7)	12 (15.4)	0.004	Ref	18 (23.1)	0.002	Ref	6 (7.7)	0.019	Ref
Tertiary	1085 (93.3)	332 (30.6)		1.82 (0.89–3.71)	443 (40.8)		1.80 (0.99–3.250	196 (18.1)		1.85 (0.72–4.71)
Occupation type
Professional and managerial	589 (50.6)	116 (19.7)		Ref	187 (31.7)		Ref	66 (11.2)		Ref
General worker	84 (7.2)	16 (19.0)	p<0.001	0.85 (0.45–1.62)	21 (25.0)	p<0.001	0.71 (0.41–1.23)	4 (4.8)	p<0.001	0.39 (0.13–1.14)
Housewife/ Retired/ Other	150 (12.9)	38 (25.3)		1.20 (0.73–1.96)	51 (34.0)		1.04 (0.68–1.60)	21 (14.0)		1.39 (0.77–2.52)
Student	340 (29.2)	174 (51.2)		1.79 (1.12–2.86)^*	202 (59.4)		1.84 (1.19–2.85)^**	111 (32.6)		2.03 (1.18–3.56)^*
Monthly average household income (MYR)
4000 and below	522 (44.9)	199 (38.1)		0.90 (0.59–1.39)	244 (46.7)		1.03 (0.70–1.52)	113 (21.6)		0.49 (0.30–0.80)^**
4001–8000	370 (31.8)	76 (20.5)	p<0.001	0.81 (0.53–1.24)	120 (32.4)	p<0.001	0.92 (0.64–1.32)	36 (9.7)	p<0.001	0.43 (0.26–0.71)^**
>8000	271 (23.3)	69 (25.5)		Ref	97 (35.8)		Ref	53 (19.6)		Ref
Perceived current financial status
Poor	125 (10.7)	71 (56.8)		2.63 (1.51–4.59)^**	67 (53.6)		1.28 (0.76–2.14)	40 (32.0)		1.93 (1.03–3.61)^*
Medium	732 (62.9)	211 (28.8)	p<0.001	1.36 (0.93–1.98)	296 (40.4)	p<0.001	1.27 (0.92–1.76)	124 (16.9)	p<0.001	1.46 (0.93–2.29)
Good	306 (26.3)	62 (20.3)		Ref	98 (32.0)		Ref	38 (12.4)		Ref
Locality
Urban	723 (62.2)	212 (29.3)			268 (37.1)			126 (17.4)
Sub-urban	304 (26.1)	91 (29.9)	0.969		137 (45.1)	0.053		54 (17.8)	0.919
Rural	136 (11.7)	41 (30.1)			56 (41.2)			22 (16.2)
Region
Northern	157 (13.5)	56 (35.7)		0.70 (0.36–1.33)	61 (38.9)			33 (21.0)
Southern	80 (6.9)	23 (28.8)		0.95 (0.62–1.45)	34 (42.5)			11 (13.8)
Central	697 (59.9)	214 (30.7)	0.042	0.66 (0.38–1.14)	278 (39.9)	0.877		127 (18.2)	0.212
East Coast	186 (16.0)	39 (21.0)		1.12 (0.49–2.55)	69 (37.1)			23 (12.4)
Borneo Island	43 (3.7)	12 (27.9)		Ref	19 (44.2)			8 (18.6)
Health status
Diagnosed with any chronic diseases
Yes	99 (8.5)	35 (35.4)	0.205		45 (45.5)	0.238		21 (21.2)	0.331
No	1064 (91.5)	309 (29.0)			416 (39.1)			181 (17.0)
Perceived health status
Very good/ Good	999 (85.9)	233 (23.3)	p<0.001	Ref	351 (35.1)	p<0.001	Ref	133 (13.3)	p<0.001	Ref
Fair/ Poor/ Very poor	164 (14.1)	111 (67.7)		5.68 (3.81–8.47)^***	110 (67.1)		3.50 (2.37–5.17)^***	69 (42.1)		3.66 (2.46–5.45)^***
COVID-19 experience
Ever known anyone infected or died of COVID-19
Yes	272 (23.4)	70 (25.7)	0.129		114 (41.9)	0.396		38 (14.0)	0.100
No	891 (76.6)	274 (30.8)			347 (38.9)			164 (18.4)

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*,p<0.05

**p<0.01

***p<0.001

^aHosmer–Lemeshow test, chi-square: 8.048, p-value: 0.429; Nagelkerke R²: 0.280

^bHosmer–Lemeshow test, chi-square: 9.609, p-value: 0.294; Nagelkerke R²: 0.180

^cHosmer–Lemeshow test, chi-square: 6.584, p-value: 0.582; Nagelkerke R²: 0.229

Fig 1 shows the trend of confirmed COVID-19 cases in Malaysia and the recruitment period. Fig 2 shows the temporal trend of the average DASS-21-D, DASS-21-A and DASS-21-S subscale scores across the four successive time periods in the 16-week data collection period. The average DASS-21-S score (M = 10.1, SD = 7.6) during the first four weeks of data collection was higher than the average DASS-21-D (M = 7.5, SD = 7.7) and DASS-21-A (M = 7.0, SD = 6.7) scores. The average DASS-21-D score was markedly elevated across the data collection period. The average DASS-21-D score (M = 17.9, SD = 11.8) was highest in the last four weeks of the data collection period, followed by the DASS-21-S (M = 15.6, SD = 9.6) and DASS-21-A (M = 11.9, SD = 10.0) scores. Fig 3 shows the percentage of participants with depressive, anxiety and stress symptoms according to the DASS-21 scores for each time period. The highest percentage of respondents reported anxiety (32.3%), followed by depressive (20.6%) and stress (11.5%) symptoms in the first time period (12 May–7 June 2020). In the fourth time period (4 August–5 September 2020), a higher percentage reported depressive (59.2%) and anxiety (55.1%) symptoms compared with stress (30.6%) symptoms.

Table 2 shows the percentage of participants with depressive, anxiety and stress symptoms and their associated factors during the 16-week study period. On average, depressive, anxiety and stress symptoms were reported in 21.3% (n = 344), 28.6% (n = 461) and 12.5% (n = 202), respectively, of the participants during the study period. Multivariable logistic regression analysis showed that the 18–25-year-old and 26–45-year-old groups had twice the odds for depressive symptoms than the > 45-year-old group. Students and participants who perceived a poor financial status reported a significantly higher likelihood of depressive symptoms. Females reported a significantly higher likelihood of having anxiety disorder than males (OR = 1.49, 95% CI 1.06–2.10). Students had higher odds of anxiety symptoms than the professional and managerial occupational groups (OR = 1.84, 95% CI 1.19–2.85).

In the multivariable regression analysis of factors influencing stress symptoms, the 25–45-year-old group (OR = 3.23, 95% CI 1.72–6.31) and the 18–25-year-old group (OR = 2.73, 95% CI 1.19–6.23) showed higher odds of stress symptoms than the > 45-year-old group. Those who perceived a poor financial status (OR = 1.93, 95% CI 1.03–3.61) had nearly 2 times higher odds of stress symptoms than those who perceived a good financial status. Although a higher percentage of participants with a monthly income < MYR4000 reported stress symptoms, in the multivariable logistic regression analysis, the highest income group had higher odds of stress symptoms. Perceived health status was the strongest significant predictor for depressive and anxiety symptoms. The odds of depression (OR = 5.68, 95% CI 3.81–8.47) and anxiety (OR = 3.50, 95% CI 2.37–5.17) were markedly higher in respondents who perceived a poorer health status.

This study examined the depressive, anxiety and stress symptoms of the Malaysian public during the implementation of a CMCO and RMCO and explored its associated factors using a cross-sectional study design. The data collection period was between the second and third waves of the COVID-19 pandemic in Malaysia, and the country is still facing the continuous threat of the disease.

In this study, responses were obtained during the period when the government imposed more lenient containment measures, and the results revealed increasing levels of depressive, anxiety and stress symptoms throughout the study duration. In line with previous studies from Hong Kong [19] and the United Kingdom [20], the public seemed to experience increased symptoms of mental illness as the pandemic progressed over time. Although psychological well-being of the public is expected to improve when restrictions were lifted, nonetheless, the negative mental impact of the people in this study did not decline despite the shift from CMCO to RMCO. The psychological impact continues to rise across the CMCO and RMCO phase. The increase in mental disorders over time can perhaps be seen as part of the continuous economic and societal consequences as the pandemic has progressed. Many countries, including Malaysia, continue to adopt unprecedented physical distancing policies. As the banning of mass gatherings, work-from-home policies and virtual meetings have been put into place during the COVID-19 pandemic, many industries have been affected negatively. Many individuals continue to suffer mentally as economic consequences continue, in addition to restrictions on social activities and prolonged confinement to their homes.

It is worth highlighting the marked increase in depressive symptoms compared with anxiety and stress symptoms. This finding implies that the Malaysian public became increasingly vulnerable to depressive disorder as the pandemic continued. Furthermore, during the last four weeks of data collection, when the COVID-19 pandemic moved into its seventh month in Malaysia, the percentage of participants with depressive symptoms was highest: the prevalence of depression among the study participants was close to 60% based on the DASS-21-D score. Of note, depression is a leading cause of disability around the world and contributes greatly to the global burden of disease [21]. In addition, the percentage of anxiety (55.1%) and stress (30.6%) symptoms were highest at the end of the data collection period. These findings further indicate the seriousness of overall mental health problems as the COVID-19 pandemic has progressed. There is evidence that mental disorders are associated with suicidal ideations and attempts [22]. Specifically, depression was found to be the main risk factors associated with suicidal behaviours [23, 24]. Malaysia has seen a rise in suicide cases and attempts during the COVID-19 pandemic [25, 26]. These findings warrant urgent monitoring of the Malaysian population’s mental health and prompt provision of counselling to mitigate the detrimental impact on society.

In this study, the 18–25-year-old group, followed by the 26–45-year-old group, reported more anxiety, depressive and stress symptoms. Most of the 18–25-year-old respondents were college or university students. Several population-based surveys have also revealed that students report a higher prevalence of depressive, anxiety and stress symptoms [27, 28]. Studies on student populations throughout the world [29–31], including in Malaysia [32], have shown that the COVID-19 pandemic has put a strain on their mental health. The main reasons for students experiencing heightened psychological distress include economic effects, changes in academic activities, difficulties adapting to online distance learning methods and uncertainty about the future with regard to academics and careers. Given the unprecedented COVID-19 crisis and uncertainly with regard to how long schools will remain closed, the findings suggest the importance of closely monitoring students’ mental health status and providing psychological counseling or mental health services. Schools and health authorities should work together to deliver prompt psychological support to affected students.

This study found a higher prevalence of depressive, anxiety, stress symptoms in women compared with men. Specifically, the multivariable analyses revealed a significant increased risk of anxiety and stress in females compared with males. These findings are in line with previous studies from around the world [33–36] as well as Malaysia [5], where women seem to have experienced elevated psychological symptoms related to the COVID-19 pandemic compared with men. The sex difference is in line with evidence suggesting that women are generally more vulnerable to stress and anxiety disorders in response to traumatic events, while men show better resilience [37, 38]. It has been suggested that intervention strategies and policies for public health emergencies should consider a gender-specific approach to address mental health inequities [39].

Financial distress due to the pandemic has been reported as a key correlate of poor mental health [40]. In this study, univariable analyses revealed that higher income and perceived financial status were well associated with better mental health outcomes. However, in the multivariable analyses, only perceived financial status was a significant predictor of better mental health outcomes. This could possibly be explained because being a high-income earner does not necessarily imply a strong financial situation. By contrast, people with strong financial situations–for example, with adequate savings–showed stronger resilience to the financial crisis during the COVID-19 pandemic. The findings indicate that minimising financial disruption during the COVID-19 pandemic should be a central goal of public health policy.

In this study, people with a fair, poor or very poor health status were more likely to report negative mental health impacts compared with those with a very good or good health status. In addition, health status was the strongest predictor for depressive and anxiety symptoms in the multivariable regression findings. These findings are in line with a recent study reporting that individuals with more medical comorbidities were more likely to report elevated depressive symptoms during the COVID-19 pandemic [41]. A study found that reduced access to routine medical care during the pandemic resulted in greater mental health among people with medical comorbidities [41]. This could be the indicator that psychological strain of pre-existing medical comorbidities may have been further increased during the COVID-19 pandemic. Other unprecedented life situations during the pandemic, including job loss, financial hardship and sedentary behaviours, may also worsen preexisting comorbidities and thereby exacerbate mental health problems. The consequences of the COVID-19 pandemic on the mental health of people with pre-existing health conditions warrant ensuring patients’ are sufficiently self-aware to realise when they need to seek help. In addition, family members and providers should be encouraged to support individuals to promote help-seeking behaviour. People with pre-existing comorbidities would need extra support to cultivate resilience, coping, mindfulness and healthy adjustment with the change to an inactive, sedentary lifestyle to enhance their mental wellbeing during the pandemic.

Some limitations of our study should be noted. The first limitation is the cross-sectional design: we identified associations but could not infer cause and effect. Another potential issue is the influence of selection bias on the prevalence of mental health problems seen in this sample. We were careful to ensure that the recruitment advertisement did not mention the topic of mental health; we advertised the study as a ‘COVID-19 Health and Wellbeing Survey’. Nonetheless, it is possible that people experiencing psychological distress or mental health consequences were more likely to respond to the survey. It is also important to note that online survey methods may lead to a biased response towards people who have good Internet literacy and access as well as those who are more educated. This bias may have a disproportionate impact on subsections of the population, such as high percentage of participants in this study who have a diploma or are university graduates. The study also has a higher representation of female participants. Nonetheless, we did obtain a sample that was relatively representative of the Malaysian population based on age and location. It is also important to note that our study used both the English and the Bahasa Malaysia version of DASS-21 in the same questionnaire. To our best knowledge, the measurement of invariance across the English and Bahasa Malaysia version of DASS-21 has never been examined before. Unfortunately, the measurement invariance across the English and Bahasa Malaysia version of DASS-21 was unable to be determined in our bilingual survey link. In the absence of measurement invariance procedures across the English and Bahasa Malaysia version of DASS-21 in this study, the psychometric robustness associated with different interpretations of items in the two languages was unknown. Testing for and assuring measurement invariance across different languages, culture or group comparisons is essential [42–44]. Future studies on DASS-21 should include validation across different group comparisons and testing of invariance of all versions. Lastly, the study is also limited by the small number of responses in the last two time periods, hence results should be interpreted with caution. Despite these limitations, our results are in line with many previous studies.

Conclusion

Our study shows that mental health symptoms, especially depression and anxiety, have been overwhelmingly prevalent in the Malaysian population as the COVID-19 pandemic has progressed. Although the number of COVID-19 cases during the data collection period was relatively low, there was a continuous increase in the percentage of respondents with depressive, anxiety and stress symptoms, implying a cumulative mental health burden. The increase in the rate of depression was most rapid, and the rate of depression was dramatically high as the COVID-19 pandemic moved into its seventh month in Malaysia. Poor health status was the strongest significant predictor for depressive and anxiety symptoms. By demographics, young people, particularly students, females and people with poor financial conditions, were more vulnerable to mental health symptoms. These findings emphasise the necessity of monitoring mental health disorders among the public during the COVID-19 pandemic and subsequently providing targeted interventions for people at elevated risks, as identified in this study.

Acknowledgments

We thank the assistance provided by all members in the Caring Together team.

Data Availability

All data files are available in the Kaggle database (www.kaggle.com/dataset/47a1daa9618fcb790d61e4c5cfa20363f2404c334e982d5499bf73aa8966179a).

Funding Statement

This research was supported by Universiti Malaya COVID-19 Implementation Research Grant (RG564-2020HWB), which was granted to Ivy Chung. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0248916.r001

Decision Letter 0

Chung-Ying Lin

26 Feb 2021

PONE-D-21-02085

Escalating progression of mental health disorders during the COVID-19 pandemic: evidence from a nationwide survey

PLOS ONE

Dear Dr. Wong,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

One expert and I have reviewed your submission and both of us agree that your submission has some merits. However, there are some serious concerns raised by the reviewer and you have to carefully consider them and address them in your revision. Among these good comments made by the reviewer, I would like to highlight the problem of using two versions of DASS-21 in the present study. The authors should have justified why the two language versions can be combined using in the present study. If the authors failed to provide a good justification, I am afraid that it will be hard to accept this paper.

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Reviewer #1: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: General comment:

The manuscript entitled “Escalating progression of mental health disorders during the COVID-19 pandemic: evidence from a nationwide survey” highlighted the mental health concerns of the Malaysian population in the COVID-19 pandemic. The strength of the manuscript is the timely assessment during COVID-19 with large sample size. However, some parts of the manuscript should be elucidated and clarified.

Mainly, different MCOs was introduced, yet the purpose of this introduction was not clear. Furthermore, the rationale of dividing four time periods was not explained well. Is it related to the MCOs, or due to other reasons? Please see the specific comments for details.

Specific comments:

Introduction

(1) For the first paragraph, “The first MCO included the closure of schools, higher education institutions and ‘non-essential’ businesses”.

Why quotation mark was used? Is there any special meaning for the non-essential? Authors may provide examples for the non-essential businesses.

(2) Authors introduced different MCOs in the first paragraph. Is the author simply tried to illustrate the situation in Malaysia, or tried to illustrate the impact of COVID-19 and related MCOs?

If authors think MCOs is important in this study, they should discuss the results incorporate with MCOs. For example, authors mentioned RMCO had more lenient restrictions compared to CMCO. Should we expect the negative impact on people’s daily living was reduced under RMCO, and hence, may influence mental health?

Materials and methods

(1) Any exclusion criteria for the recruitment?

(2) “The participants were asked to indicate whether they know of friends, neighbours or colleagues who had been diagnosed with COVID-19.”

How about the participants themselves? Whether participants had been diagnosed with COVID-19 might be important to their mental health.

(3) In this study, both English version and Bahasa Malaysia version of DASS-21 were used and pooled for analysis. Could authors provide reference to support the measurement invariance across these two language versions?

Data analysis

(1) I suggest to report internal consistency for English version and Bahasa Malaysia version separately.

(2) Could authors explain the rationale of dividing four time periods? Without any explanation, it made me wonder whether it was related to the MCOs. However, it seems that they did not match.

Results and discussion

(1) As the study divided four time periods, the number of participants in each period should be provided.

(2) For those who reported their gender, most of them were female. Authors may consider to discuss it in the limitation.

**********

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Reviewer #1: No

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PLoS One. 2021 Mar 25;16(3):e0248916. doi: 10.1371/journal.pone.0248916.r002

Author response to Decision Letter 0

2 Mar 2021

In your revised cover letter, please address the following prompts:

Reply: We do not have ethical or legal restrictions on sharing a de-identified data set, we noted in the cover letter. We have also uploaded our data in data repository Havard dataverse (https://doi.org/10.7910/DVN/COITOK)

Reply: The data is uploaded in the following data repository Havard dataverse

Link database: https://doi.org/10.7910/DVN/COITOK

We will update your Data Availability statement on your behalf to reflect the information you provide.

Reply: Added

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

________________________________________

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

________________________________________

3. Have the authors made all data underlying the findings in their manuscript fully available?

Data has been deposited in data repository (https://doi.org/10.7910/DVN/COITOK)

Reviewer #1: Yes

________________________________________

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

________________________________________

5. Review Comments to the Author

Reviewer #1: General comment:

Specific comments:

Introduction

(1) For the first paragraph, “The first MCO included the closure of schools, higher education institutions and ‘non-essential’ businesses”.

Why quotation mark was used? Is there any special meaning for the non-essential? Authors may provide examples for the non-essential businesses.

Reply: We remove ‘ ‘

Added: meaning of non-essential businesses, line 72-74

�The first MCO included the closure of schools, higher education institutions and non-essential businesses (namely businesses that geared toward recreation or entertainment and those that provide services beyond the basic necessities),……..

(2) Authors introduced different MCOs in the first paragraph. Is the author simply tried to illustrate the situation in Malaysia, or tried to illustrate the impact of COVID-19 and related MCOs?

Reply: Thank you for highlighting the shortcoming. In line 135-6, we noted “The temporal trend of the DASS-21-D, DASS-21-A and DASS-21-S scores over the 16-week data collection period was computed”. Hence we added in line 98 the objective of investigating the temporal trend of mental health.

�Therefore, the main aim of this study was to examine the level and temporal trend of mental health of the Malaysian public during the COVID-19 pandemic.

In Introduction, we provide a snapshots of the different phases of MCOs in Malaysia, however, the data collection was conducted after during CMCO and RMCO, where the government imposed more lenient containment measures.

Added, although ideally when restrictions were lifted, mental health improve, but out study found otherwise. The possible reasons were noted in line 245-252.

Added line 242-245

�Although psychological well-being of the public is expected to improve when restrictions were lifted, nonetheless, the negative mental impact of the people in this study did not decline despite the shift from CMCO to RMCO. The psychological impact continues to rise across the CMCO and RMCO phase.

Materials and methods

(1) Any exclusion criteria for the recruitment?

Reply: Added exclusion criteria, line 108

�The exclusion criteria were as follow: having chronic medical conditions, pregnancy or breastfeeding, and have never had SARS-CoV-2 infection.

(2) “The participants were asked to indicate whether they know of friends, neighbours or colleagues who had been diagnosed with COVID-19.”

How about the participants themselves? Whether participants had been diagnosed with COVID-19 might be important to their mental health.

Reply: The study did not include people who have had been diagnosed with COVID-19 as noted in the added exclusion criteria.

Reply: To our best knowledge, to date, there is no reference to support the measurement invariance across the English and Bahasa Malaysia version of the DASS-21. Unfortunately, in our study, the English and Bahasa Malaysia questions of the DASS-21 were place side by side and hence the measurement of invariance across the English and BM versions of the DASS-21 is unable to be calculated in the current study.

We reported the limitation of the measurement invariance across these two language versions.

Added line 329

�It is also important to note that this study used both the English and the Bahasa Malaysia version of FASS-21, however, the measurement invariance across the English and Bahasa Malaysia version of DASS-21 was unable to be both version of the DASS-21 were included in the same survey link.

Data analysis

(1) I suggest to report internal consistency for English version and Bahasa Malaysia version separately.

Reply: Thank you for suggestion, unfortunately in our survey, both Bahasa Malaysia and English questions were incorporated into our sole survey link. Each questions is bilingual, hence we are unable to report internal consistency for both version. We are unsure if the respondent were reading the English or BM version when answering the questions.

(2) Could authors explain the rationale of dividing four time periods? Without any explanation, it made me wonder whether it was related to the MCOs. However, it seems that they did not match.

Reply: The four time periods were divided by equal time intervals. We introduces the phases of MCO, CMCO and RMCO in the Introduction to provide information of all stages of movement control in Malaysia during the pandemic, however, our data collection was conducted during CMCO and RMCO. Hence, rational of dividing to four time periods was not the sequence of the MCO, CMCO and RMCO. We could only relate the findings on the two phases of MCOs.

Added “by equal intervals”, hence added the word “equal” line line 138

�The mean and standard deviation (SD) of the DASS-21 subscale scores were divided into four equal time periods of 4-week intervals….

Results and discussion

(1) As the study divided four time periods, the number of participants in each period should be provided.

Reply: We noted the number of participants in each phases in Fig. 2. We made minor typo mistakes on the number of responses, corrected them in text and tables, and shown in the correction tracking. The rest of the information is accurate.

We added in the limitation of the low number of responses in the last two time periods. Line 332.

�Lastly, the study is also limited by the small number of responses in the last two time periods, hence results should be interpreted with caution.

(2) For those who reported their gender, most of them were female. Authors may consider to discuss it in the limitation.

Added in line 327.

�The study also has a higher representation of female participants.

________________________________________

Attachment

Submitted filename: Response to reviewers 02.03.2021.docx

Click here for additional data file.^{(21.6KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0248916.r003

Decision Letter 1

Chung-Ying Lin

4 Mar 2021

PONE-D-21-02085R1

Escalating progression of mental health disorders during the COVID-19 pandemic: evidence from a nationwide survey

PLOS ONE

Dear Dr. Wong,

==============================

In general, the responses are decent and I only have one concern regarding the measurement invariance.

Apparently, the authors cannot justify why the two language versions can be combined used and thus they put this into their limitation. I think that putting this as one of the limitations is appropriate. However, the authors should emphasize this issue and encourage future studies to investigate the measurement invariance. The authors should also mention why it is important to investigate measurement invariance with proper citation. They can take reference from Leung et al. (2020).

Leung, H., Pakpour, A. H., Strong, C., Lin, Y. C., Tsai, M. C., Griffiths, M. D., Lin, C. Y., & Chen, I. H. (2020). Measurement invariance across young adults from Hong Kong and Taiwan among three internet-related addiction scales: Bergen Social Media Addiction Scale (BSMAS), Smartphone Application-Based Addiction Scale (SABAS), and Internet Gaming Disorder Scale-Short Form (IGDS-SF9) (Study Part A). Addictive behaviors, 101, 105969. https://doi.org/10.1016/j.addbeh.2019.04.027

==============================

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PLoS One. 2021 Mar 25;16(3):e0248916. doi: 10.1371/journal.pone.0248916.r004

Author response to Decision Letter 1

5 Mar 2021

Reply: We emphasized the importance of the issue and the importance of future studies to investigate the measurement invariance.

�Testing for and assuring measurement invariance across different languages, culture or group comparisons is essential [42-44]. Future studies on DASS-21 should include validation across different group comparisons and testing of invariance of all versions.

Reply: We noted that the importance of investigating measurement invariance to ensure psychometric robustness.

� In the absence of measurement invariance procedures across the English and Bahasa Malaysia version of DASS-21 in this study, the psychometric robustness associated with different interpretations of items in the two languages was unknown.

Reply: We rephrased the limitation section as follow.

To our best knowledge, the measurement of invariance across the English and Bahasa Malaysia version of DASS-21 has never been examined before. Unfortunately, the measurement invariance across the English and Bahasa Malaysia version of DASS-21 was unable to be determined in our bilingual survey link. In the absence of measurement invariance procedures across the English and Bahasa Malaysia version of DASS-21 in this study, the psychometric robustness associated with different interpretations of items in the two languages was unknown. Testing for and assuring measurement invariance across different languages, culture or group comparisons is essential [42-44]. Future studies on DASS-21 should include validation across different group comparisons and testing of invariance of all versions.

Attachment

Submitted filename: Response to Reviewers 5March 2021.docx

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PLoS One. doi: 10.1371/journal.pone.0248916.r005

Decision Letter 2

Chung-Ying Lin

9 Mar 2021

Escalating progression of mental health disorders during the COVID-19 pandemic: evidence from a nationwide survey

PONE-D-21-02085R2

Dear Dr. Wong,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Chung-Ying Lin

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0248916.r006

Acceptance letter

Chung-Ying Lin

15 Mar 2021

PONE-D-21-02085R2

Escalating progression of mental health disorders during the COVID-19 pandemic: evidence from a nationwide survey

Dear Dr. Wong:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Chung-Ying Lin

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: Response to reviewers 02.03.2021.docx

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Attachment

Submitted filename: Response to Reviewers 5March 2021.docx

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Data Availability Statement

All data files are available in the Kaggle database (www.kaggle.com/dataset/47a1daa9618fcb790d61e4c5cfa20363f2404c334e982d5499bf73aa8966179a).

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PERMALINK

Escalating progression of mental health disorders during the COVID-19 pandemic: Evidence from a nationwide survey

Li Ping Wong

Haridah Alias

Afiqah Alyaa Md Fuzi

Intan Sofia Omar

Azmawaty Mohamad Nor

Maw Pin Tan

Diana Lea Baranovich

Che Zarrina Saari

Sareena Hanim Hamzah

Ku Wing Cheong

Chiew Hwa Poon

Vimala Ramoo

Chong Chin Che

Kyaimon Myint

Suria Zainuddin

Ivy Chung

Roles

Abstract

Introduction

Materials and methods

Data analysis

Ethical considerations

Results and discussion

Demographics

Table 1. Comparison of demographic characteristics of the study population and the general adult population in Malaysia, 2019.

Table 2. Univariable and multivariable analyses of factors associated with symptoms of depression, anxiety and stress (N = 1163).

Fig 1. Data collection period and the trend of confirmed cases of COVID-19 in Malaysia.

Fig 2. Temporal changes in mean total DASS-21 score at different time point.

Fig 3. Proportion of participants with the presence of depressive, anxiety and stress symptoms by the four time point of the study period.

Conclusion

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Chung-Ying Lin

Roles

Author response to Decision Letter 0

Decision Letter 1

Chung-Ying Lin

Roles

Author response to Decision Letter 1

Decision Letter 2

Chung-Ying Lin

Roles

Acceptance letter

Chung-Ying Lin

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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