|Year : 2021 | Volume
| Issue : 2 | Page : 55-60
Impact on mental health among patients with COVID-19: A study from central India
Arvind Sharma1, Aditi Bharti1, Tej Pratap Singh1, Richa Sharma2, Deepali Soni1, Priyanka Dubey1
1 Department of Community Medicine, NSCB Medical College, Jabalpur, Madhya Pradesh, India
2 Department of Emergency Medicine, NSCB Medical College, Jabalpur, Madhya Pradesh, India
|Date of Submission||09-Feb-2021|
|Date of Decision||18-Apr-2021|
|Date of Acceptance||05-May-2021|
|Date of Web Publication||09-Jun-2021|
Dr. Aditi Bharti
F-722, Swasthik Grand, Doctors Colony, Jabalpur, Madhya Pradesh
Source of Support: None, Conflict of Interest: None
Objective: The objective of the study is to assess mental health status and the severity of the depression in patients of COVID-19 admitted to a tertiary care hospital in Jabalpur district. Settings and Design: This cross-sectional study was conducted over a period from April to June 2020 at the NSCB Medical College and Hospital, Jabalpur. Methodology: Out of 150 participants, 135 participants responded whereas 15 patients did not respond as some of them did not answer the calls and remaining did not give their consent. Participants included confirmed COVID-19 cases admitted at a tertiary care hospital, aged 18 years and above. The Patient Health Questionnaire-9 was used to determine depression and was completed through telephonic platform survey. Statistical Analysis Used: SPSS statistical software was used to analyze the data. P <0.05 and <0.001 with 95% confidence interval was considered statistically significant. Results: Among 135 participants, overall depression was found to be 50.4%, out of which, 29.6% were in mild depression, 8.9% were in moderate depression and 11.8% were in moderately severe to severe depression. Females had approximately four times higher risk for depressive symptoms (P <0.001), and for an age group, more than 45 was found to be significantly associated with depression. Conclusion: The present study suggested that about 50% of the people experienced depression. The significant factors found may reveal that more attention should be given to the mental health of the patients with COVID-19, imperatively with psychological care in the treatment protocol to subdue the effects of the pandemic.
Keywords: Central India, COVID-19, depression, mental health
|How to cite this article:|
Sharma A, Bharti A, Singh TP, Sharma R, Soni D, Dubey P. Impact on mental health among patients with COVID-19: A study from central India. J Prim Care Spec 2021;2:55-60
|How to cite this URL:|
Sharma A, Bharti A, Singh TP, Sharma R, Soni D, Dubey P. Impact on mental health among patients with COVID-19: A study from central India. J Prim Care Spec [serial online] 2021 [cited 2021 Sep 24];2:55-60. Available from: http://www.jpcs.com/text.asp?2021/2/2/55/318000
| Introduction|| |
In December 2019, the novel coronavirus broke out in Wuhan, Hubei province of China. The World Health Organization declared the outbreak of a new coronavirus disease, COVID-19, to be a public health emergency of international concern in January 2020, and in March 2020, COVID-19 was characterized as a pandemic., This pandemic of COVID-19 is implicitly on a different scale. It has shaken the entire world and created global panic. Initially, it slows down but then subsequently spreads at a galloping pace, the country after country. This sudden and unexpected epidemic impact was extremely concerning part and proven to be catastrophic which endangered the physical and psychological health universally.
Mental health issues following the COVID-19 pandemic cause normal people to be exposed to unprecedented situations. The presentations are innumerable and include emotional difficulties such as depression, biological effects, appetite disturbances, and severe mental illness, severe interruption of routines, separation from family members and friends, shortages of daily necessities, remuneration deduction, and social isolation additionally that considerably impacted the quality of life. Most of these symptoms are mild and transient, but a minority may present with severe mental health issues that require additional mental health support.
Perceiving and directing the mental health response of the COVID-19 patient's general public psychological reactions play a critical role in this pandemic and may help out the communities to get better prepared for emergency public health events to get rid of the psychological burden and to promote social stability., Meanwhile, addressing the mental health repercussions of this epidemic now became a nationwide mission, which requires the attention of the entire society.
The studies conducted on the psychological impact of previous infectious outbreaks, such as the severe acute respiratory syndrome which is likely to the COVID-19 pandemic, have found a huge psychological burden among the general public such as depression, fear, or psychotic symptoms.,
Although the correlation between public health emergencies and mental health is well known, most researches focus on evaluating the impact of resilience on physical health, psychological health, and quality of life following a major natural disaster or public event.,
COVID-19 cases are treated in healthcare settings with little or no mental health training. However, to address this gap, we conducted a cross-sectional study to comprehensively describe the mental health status of the patients suffered from the COVID-19 epidemic, so it should be imperative that assessment and intervention for psychological concerns be administered in those settings to provide some improvisation in the mental and physical health of the patients suffered from COVID-19. Therefore, to conclude, this study has been done to assess the mental health status and the severity of the depression in the patients of COVID-19 admitted to a tertiary care hospital in Jabalpur district.
| Methodology|| |
This cross-sectional study was conducted on a total of 150 participants of different areas in the Jabalpur district affected by COVID-19 admitted at the tertiary care facility, out of which only 135 participants responded whereas 15 patients did not respond as some of them did not answer the calls and remaining did not give their consent. All the participants were interviewed in their postdischarge period. In the present study, convenient sampling was used and was conducted from April 2020 to June 2020. The questionnaire was completed through a telephonic survey platform after being taken their verbal consent and making them aware of the purpose of this study. All the participants were ensured to maintain their confidentiality as a whole.
(1) Who gave verbal consent (2) aged 18 years and older, and (3) patients admitted in a tertiary care hospital.
Patients with preexisting mental illness or were on some kind of medications for the same.
Ethical approval was obtained from the hospital authority to conduct this study in a defined period with reference letter no. 12773.
The survey tool for screening depression was determined by using a 9-Item Patient Health Questionnaire (PHQ-9) for 2 weeks as a recall period. PHQ-9 is a validated psychological self-assessment questionnaire used to assess the severity of depression based on the Diagnostic and Statistical Manual of Mental Disorders-IV diagnostic criteria for depression. Each item can receive a level of response from “0” (not at all), “1” (several days), “2” (more than half the days), and “3” (nearly every day) point, and the total score of the questionnaire ranges from 0 to 27 points. The severity of depression for the study was categorized as “minimal = 0–4,” “mild = 5–9,” and “moderate = 10–14,” “moderately severe = 15–19,” and “severe = 20–27.” The depression was defined as a total score of ≥5 points in the PHQ-9 according to the previous study during the COVID-19 epidemic. In the present study, PHQ-9 showed excellent internal consistency (with the Cronbach's alpha coefficients of 0.901).
IBM SPSS statistics software, version 20 (IBM) was used for statistical analysis. Cronbach's alpha coefficient was also used to measure the reliability of the scale. Frequency tabulation was used to summarize demographic information of respondents and the severity of depression among gender and age group. An independent sample t-test was conducted to determine whether there is a difference in PHQ-9 scores for depression between males and females. A one-way ANOVA was conducted to determine the effect of age on scores. Differences between groups were considered statistically significant as the P < 0.001. The percentage of depression was used to estimate according to the severity of the depression by using the PHQ-9 scores. Binary logistic regression analysis was also used to explore the factors associated with depression. A P < 0.001 and < 0.05 was used, and a confidence interval of 95% was adopted for logistic regression.
| Results|| |
Demographic profile of the participants
A total of 135 participants, including 91 males and 44 females, aged ranged from 18 to 78 years were incorporated in the current study. The mean age was 41.86 ± 15.09 years. A high number of respondents, 66% (n = 89), were aged between 26 and 59 years. About 67.4% (n = 91) were male. The majority of the respondents, 74.8% (n = 101), were married. Demographic variables are listed in [Table 1].
Severity of depression using Patient Health Questionnaire-9
[Table 2] shows the severity and percentage of depression by using PHQ-9 scoring. The mean score of the depression scale of all the respondents was 6.49 ± 5.69. It was observed that the 50.4% (n = 68) of participants screened positive for depression, out of which, mild depression were in 29.6%, 8.9% shows moderate depression, and 11.8% were in moderately severe to severe depression. Whereas, 49.7% (n=67) participants were screened with no depression. With the reference to PHQ-9 scoring, as for the depression level in males (n = 91), 55 (40.7%) were in no depression, 32 (23.65%) were in mild-to-moderate depression, 3 (2.2) were in moderately-severe depression, and 1 (0.7%) was in severe. Whereas in females (n=44), 8.9% were screened with no depression, and 23.65% females showed mild to severe depression. Furthermore, among all the age-group, maximum depressive symptoms were shown by 41-59 years with 18.8%.
|Table 2: Depression severity using Patient Health Questionnaire-9 in relation to patient's age and gender (n=135)|
Click here to view
Screening of the depression using Patient Health Questionnaire-9
[Table 3] shows that the participants' scores about the PHQ-9 aimed at depression screening. All participants answered about 100% to every question had a score ranging from 0 to 3. The mean PHQ-9 score was 6.21 ± 5.68. Nearly one-third of the participants, 31.9% (n = 45), felt down, depressed, and hopeless. Likewise, more than one-third of the participants, 37.03% (n = 50), were having difficulties in their sleep with either trouble falling or staying asleep or sleeping too much. Hence, this indicates that sleep disorder is associated with depression for several days. [Table 3] also indicates that nearly 1% of participants, 0.7% (n = 1), thought they would be better off dead or thought about hurting themselves.
|Table 3: Results of depression screening using Patient Health Questionnaire-9 (n=135)|
Click here to view
Comparison in Patient Health Questionnaire-9 score concerning the patient's age and gender
[Table 4] shows an independent sample t-test was conducted to determine whether there is a difference in PHQ-9 score for depression between males and females. The results indicate a significant difference between males (mean = 4.69; standard deviation [SD] =4.58) and females (mean = 9.34; SD = 6.44; t (66.309) = −4.292; P = 0.001). The 95% confidence interval of the difference between means ranged from − 6.812 to − 2.485 and does indicate a significant difference between the sample means. We, therefore, conclude that there is a difference in PHQ-9 scores for depression between males and females.
|Table 4: Independent samples t-test results for gender; one-way ANOVA test results for age|
Click here to view
[Table 4] also shows a one-way ANOVA test, which was conducted to determine the effect of age (18–25, 26–40, 41–59, and ≥60) on PHQ-9 score for depression. The results indicate a nonsignificant effect, F (3, 131) =2.366, P = 0.074. We, therefore, conclude that the different levels of age have the same effect on the PHQ-9 scores for depression.
Factors associated with depression
[Table 5] shows that binary logistic regression analysis was conducted to ascertain the relationship between depression and other variables including patients' age and gender. Taking male as a reference, female patients having a significant relationship showed four times higher risks with depression, odds ratio (OR) =4.074 (95% confidence interval [CI]: 1.86–8.94), P = 0.001. In addition, with the age group of <45 as a reference, the study indicated a significant relationship having two times higher risk in age group >45 with depression, OR = 2.526 (95% CI: 1.24–5.15), P = 0.01.
|Table 5: Logistic regression analysis of depression percentage to patients' age and gender|
Click here to view
| Discussion|| |
Several studies have shown an association of depression to patients with a different disease. This study reported the severity of depression in patients with the COVID-19 pandemic which provides us the impact of the disease on an individual's mental health status.
Similar to the current study, a systematic review studies conducted by Vindegaard and Benros and Rogers et al. showed a significant level of depressive symptoms (P = 0.016), which was about to be 29.2% and 32.6%, respectively., Similarly, a study conducted in China showed around 28.47% of depression in hospitalized patients with COVID-19, whereas the study done in Bangladesh reported 87.3% prevalence of depression in COVID-19 patients., Likewise, a study conducted on mental health of medical students during COVID-19 pandemic in Brazil stated that about 64.41% of students were identified with moderate or severe symptoms of depression by using cut-off score >10 of PHQ-9. Similarly, another study conducted in china by Liu S et al, stated that, the overall prevalence of depression found to be 50.7% in his multicenter survey held in medical staff. In addition, the results from a study done in Rwanda on diabetes concerning with depression revealed that majority of participants had depression which was found to be 83.8%; among them, 17.9% had moderately severe-to-severe depression while 81.9% had minimal-to-moderate depression. With the above-mentioned scenario, the current study showed that around 50% of the patients had symptoms of depression of all grades of severity by using cut off score ≥5 of PHQ-9; among them, 38.5% had mild-to-moderate depression while 11.8% had moderately severe-to-severe depression which is in concordance with study done in Hubei.
Furthermore, in the present study, it is clearly shown that female patient significantly had a higher association with the depression as compared to males. Similar study revealed a positive significant relationship between depressive symptoms and female (P = 0.018). Likewise, a study by Mazza also stated that females had a significant level of depression (P < 0.001). One more study on the psychological responses among the general population during the COVID-19 epidemic in China, where females' patients are prone to develop higher levels of depression. However, a study in China by Hu et al. showed that a higher score of depression was associated with the female gender accounted for around 49.5%.
With an age, various studies showed the statistically significant relation with the depressive symptoms. In the present study, the results indicated that an age group of >45 years had a significant relationship with depression. Similarly, a research revealed that older patients are at increased risk with severe COVID-19 symptoms and had a significant relationship with depression (P < 0.001). Likewise, a study conducted in Denmark reported that age as a risk factor were inconsistent and a study of Italy also showed a nonsignificant relation of depressive symptoms with an age, respectively. However, a study by Gao et al. of China showed that the prevalence of depression was 48.3% (95% CI: 46.9%–49.7%) in age group of <40 which is contradict findings to the current study.,,
The present study provides data about the pandemic-related distress on mental health. However, early prevention of mental health issues is of the utmost importance to have good clinical outcomes and better life quality for patients. As the COVID-19 pandemic escalates, our findings are particularly in consideration to develop safe management of the mentally ill patients and psychological support strategy for patients with COVID-19 and other areas affected by this pandemic. It also emphasizes the mental health professionals to anticipate by taking imperative steps for the patients to think more constructively in the pandemic times.
Strength of the study
The type of methodology we used has been applied in several other studies on COVID-19 patients. Moreover, PHQ-9 is a well-known method of assessment of symptoms of depression. As the COVID-19 upsurges, the patients been suffered from are more vulnerable to go through mental health problems. Therefore, this revelation would help few psychological aids to the clinicians, and to follow an appropriate intervention according to the severity of the depression to the patients along with.
(1) The present study was single-centered, and the sample of this study was not representative of all patients with COVID-19 in Jabalpur but was a convenience sample, so it limits the results generalizability. (2) In this study, all the outcomes were self-reported, which might lead to recall bias. (3) Self-reported tool is used to measure the current depressive episode as it was convenient in this pandemic. (4) This cross-sectional study is not capable to determine a causal relationship between mental health (depression) and sociodemographics.
| Conclusion|| |
Fifty percent of the study participants experienced the symptoms of depression, who suffered with COVID-19. The significant factors found in the present study may reveal that more attention and consideration should be given to the mental health of patients with COVID-19 and imperatively with psychological care in the treatment protocol to subdue the effects of the impact of this pandemic. Considering this unprecedented situation, where there is a limited mental health services to avail, effective screening procedures should be taken by the primary care physicians, which would help COVID-19 patients to combat developing mental health problems. Hence, there is an utmost requirement for primary care physicians to be both aware and skilled enough to address mental health issues arising in infection outbreak situations like COVID-19.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Taylor S. The Psychology of Pandemics: Preparing for the Next Global Outbreak of Infectious Disease. Newcastle upon Tyne, UK: Cambridge Scholars Publishing; 2019.
Cullen W, Gulati G, Kelly BD. Mental health in the COVID-19 pandemic. QJM 2020;113:311-2.
Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al.
Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health 2020;17:1729.
Xiang YT, Yang Y, Li W, Zhang L, Zhang Q, Cheung T, et al.
Timely mental health care for the 2019 novel coronavirus outbreak is urgently needed. Lancet Psychiatry 2020;7:228-9.
Rajkumar RP. COVID-19 and mental health: A review of the existing literature. Asian J Psychiatr 2020;52:102066.
Khan S, Siddique R, Li H, Ali A, Shereen MA, Bashir N, et al.
Impact of coronavirus outbreak on psychological health. J Glob Health 2020;10:010331.
Ran L, Wang W, Ai M, Kong Y, Chen J, Kuang L. Psychological resilience, depression, anxiety, and somatization symptoms in response to COVID-19: A study of the general population in China at the peak of its epidemic. Soc Sci Med 2020;262:113261.
Pfefferbaum B, Schonfeld D, Flynn BW, Norwood AE, Dodgen D, Kaul RE, et al.
The H1N1 crisis: A case study of the integration of mental and behavioral health in public health crises. Disaster Med Public Health Prep 2012;6:67-71.
Inoue T, Tanaka T, Nakagawa S, Nakato Y, Kameyama R, Boku S, et al.
Utility and limitations of PHQ-9 in a clinic specializing in psychiatric care. BMC Psychiatry 2012;12:73.
Kroenke K, Spitzer RL, Williams JB. The PHQ-9: Validity of a brief depression severity measure. J Gen Intern Med 2001;16:606-13.
Liu S, Yang L, Zhang C, Xiang YT, Liu Z, Hu S, et al.
Online mental health services in China during the COVID-19 outbreak. Lancet Psychiatry 2020;7:e17-8.
Vindegaard N, Benros ME. COVID-19 pandemic and mental health consequences: Systematic review of the current evidence. Brain Behav Immun 2020;89:531-42.
Rogers JP, Chesney E, Oliver D, Pollak TA, McGuire P, Fusar-Poli P, et al.
Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: A systematic review and meta-analysis with comparison to the COVID-19 pandemic. Lancet Psychiatry 2020;7:611-27.
Kong X, Zheng K, Tang M, Kong F, Zhou J, Diao L, et al
. Prevalence and Factors Associated with Depression and Anxiety of Hospitalized Patients with COVID-19. medRxiv; 2020. Available from: https://europepmc.org/article/PPR/PPR130587
. [Last accessed on 2021 Feb 04].
Hasan MJ, Tabssum T, Ambia NE, Zaman MS, Rahman M, Khan AS. Mental health of the COVID-19 patients in Bangladesh. Mymensingh Med J 2021;30:189-95.
Sartorão Filho CI, de Las Villas Rodrigues WC, de Castro RB, Marçal AA, Pavelqueires S, Takano L, et al
. Impact of Covid-19 pandemic on mental health of medical students: A cross-sectional study using GAD-7 and PHQ-9 questionnaires. medRxiv 2020;2020.06.24.20138925. Available from: http://medrxiv.org/content/early/2020/06/25/2020.06.24.20138925
. [Last accessed on 2021 Feb 04].
Mukeshimana M, Chironda G. Depression and associated factors among the patients with type 2 diabetes in Rwanda. Ethiop J Health Sci 2019;29:709-18.
Wang M, Hu C, Zhao Q, Feng R, Wang Q, Cai H, et al.
Acute psychological impact on COVID-19 patients in Hubei: A multicenter observational study. Transl Psychiatry 2021;11:133.
Mazza C, Ricci E, Biondi S, Colasanti M, Ferracuti S, Napoli C, et al
. A nationwide survey of psychological distress among Italian people during the COVID-19 pandemic: Immediate psychological responses and associated factors. Int J Environ Res Public Health 2020;17:3165.
Hu Y, Chen Y, Zheng Y, You C, Tan J, Hu L, et al.
Factors related to mental health of inpatients with COVID-19 in Wuhan, China. Brain Behav Immun 2020;89:587-93.
Gao J, Zheng P, Jia Y, Chen H, Mao Y, Chen S, et al.
Mental health problems and social media exposure during COVID-19 outbreak. PLoS One 2020;15:e0231924.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]