SOLUTION: responses to infectious disease outbreaks | My Assignment Tutor

https://doi.org/10.1177/0020764020961790International Journal ofSocial Psychiatry1–10© The Author(s) 2020Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/0020764020961790journals.sagepub.com/home/ispE CAMDEN SCHIZOPHIntroductionPsychosocial responses to infectious disease outbreakshave the potential to inflict acute and longstanding mentalhealth consequences (Van Bortel et al., 2016). To reducepsychological distress, individuals can utilise a range ofcoping strategies. Some coping styles are ineffective andmay exacerbate mental health problems while other coping styles may be effective at mitigating the nature andimpact of these psychological responses. A better understanding of the psychosocial responses across the community and beneficial coping strategies are crucial to managethe current pandemic optimally, as well as develop mentalhealth response plans for future pandemics.Evidence from previous infectious disease outbreaks,including the 2003 severe acute respiratory syndrome(SARS), the 2009/2010 H1N1 influenza pandemic, and the2012 Middle East respiratory syndrome reveal variablepsychological symptoms including anxiety, fear, depression, anger, irritability, helplessness, grief and loss (Chewet al., 2020). The psychological consequences of infectiousCoping styles and mental health inresponse to societal changes duringthe COVID-19 pandemicCaroline Gurvich1 , Natalie Thomas1, Elizabeth HX Thomas1,Abdul-Rahman Hudaib1, Lomash Sood1, Kali Fabiatos1,Keith Sutton2, Anton Isaacs2, Shalini Arunogiri1,Gemma Sharp1 and Jayashri Kulkarni1AbstractBackground: Psychosocial responses to infectious disease outbreaks have the potential to inflict acute and longstandingmental health consequences. Early research across the globe has found wide ranging psychological responses to thecurrent COVID-19 pandemic. Understanding how different coping styles can be effective in mitigating mental ill healthwould enable better tailored psychological support.Aims: The aim of this study was to gain an understanding of psychosocial responses to the COVID-19 pandemic,including depression, anxiety and distress, as well as effective coping styles in an Australian sample.Method: A sample of 1,495 adults, residing in Australia between April 3rd and May 3rd 2020, completed an onlinesurvey which measured psychological distress (Impact of Events Scale-Revised), depression, anxiety, stress (DASS-21),as well as coping strategies (Brief COPE).Results: 47% of the respondents were experiencing some degree of psychological distress. Females experienced higherlevels of depression, anxiety and stress than males. Coping strategies associated with better mental health were positivereframing, acceptance and humour. Conversely, self-blame, venting, behavioural disengagement and self-distraction wereassociated with poorer mental health.Conclusion: Rates of psychological symptoms amongst the Australian population are similar to those reported inother countries. Findings add to the growing literature demonstrating a gender disparity in the mental health impactsof COVID-19. Positive emotion focused coping strategies may be effective for reducing psychological symptoms.Understanding psychosocial responses including beneficial coping strategies are crucial to manage the current COVID-19situation optimally, as well as to develop mental health response plans for future pandemics.KeywordsCOVID-19, depression, anxiety, mental health, coping1Monash Alfred Psychiatry Research Centre, The Alfred Hospital andMonash University, Central Clinical School, Melbourne, Victoria,Australia2Department of Rural Health, Monash University, Melbourne, Victoria,AustraliaCorresponding author:Caroline Gurvich, Central Clinical School, Faculty of Medicine,Nursing and Health Sciences, Monash University, 4/607 St Kilda Road,Melbourne VIC 3004, Australia.Email: caroline.gurvich@monash.edu961790 ISP0010.1177/0020764020961790International Journal of Social PsychiatryGurvich et al.research-article2020Original Article2 International Journal of Social Psychiatry 00(0)disease outbreaks are not limited to those infected, caregivers and healthcare workers. Rather, the mental healthand well-being of the general population can be affected asa result of disruption to daily life, fear, uncertainty, stigmatisation and concerns relating to job and financial security(Chew et al., 2020).The current COVID-19 pandemic is unique in relationto the number of countries affected, its high transmissibility; potential infectivity via people who are mildly symptomatic or asymptomatic; and the absence of a vaccine (atthe time of writing). As of May 3rd 2020, COVID-19 hasaffected 3,349,786 people, with 238,628 reported deaths(COVID-19 National Incident Room Surveillance Team.,2020a). Within Australia, a multi-cultural island nation,there have been 6,784 cases of COVID-19 reported, with89 deaths (as of May 3rd, 2020) (COVID-19 NationalIncident Room Surveillance Team., 2020b) have been alower number of COVID-19 cases compared to other comparable high-income countries (COVID-19 NationalIncident Room Surveillance Team., 2020b). The immediate psychological impact of the COVID-19 outbreak hasbeen measured using online surveys, primarily withinChina. A survey conducted in China two weeks after theinitial outbreak of COVID-19 revealed that out of a total of1,120 respondents more than half rated the psychologicalimpact of outbreak as moderate or severe, 16.5% ofrespondents reported moderate to severe depressive symptoms; 28.8% of respondents reported moderate to severeanxiety symptoms; and 8.1% reported moderate to severestress levels (Wang et al., 2020a). Levels of depression,anxiety and stress remained elevated and stable when thesurvey was repeated 4 weeks later (Wang et al., 2020b).Predictors of poorer mental health included female gender,student status, and COVID-19 related somatic symptoms.In an attempt to reduce psychological distress, a rangeof coping strategies can be adopted, only some of whichare effective (Mahmoud et al., 2012; Main et al., 2011).Coping strategies are characterised as dynamic responsesto a specific situation, namely the COVID-19 pandemic,where an effort is made to reduce or avoid the effects of astressor. Common coping strategies that have been adoptedin response to previous pandemics include problemfocused coping (an active effort to manage the stressfulsituation by engaging in problem-focused efforts to alterthe situation or seek alternatives (Stanislawski, 2019));seeking social support; and, positive appraisal of the situation (construing the stressful situation in positive light(Chew et al., 2020; Stanislawski, 2019)). Coping strategiesassociated with better mental health outcomes during thecurrent pandemic have not been reported.The aim of the current study was to examine psychosocial responses within an Australian population and gain anunderstanding of coping strategies that are effective, aswell as coping strategies that are ineffective for minimising psychological symptoms.Materials and methodsWe adopted a prospective online survey. The analysis presented in the current study is cross-sectional data based ona sample of the Australian public’s psychological responsesto the COVID-19 pandemic from April 3rd to May 3rd.During this time, Australia was in a stage of enforcedrestrictions, including physical distancing, cancellation ofmass gatherings as well as confinement and isolation forthose who may have been exposed to people infected withCOVID-19. Sampling strategies included social mediaadvertising as well as snowball techniques to recruit members of the general public, aged 18 years and over living inAustralia during the COVID-19 pandemic.This study was approved by the Monash UniversityHuman Research Ethics Committee (MUHREC: 23963)and conforms to the provisions of the Declaration ofHelsinki. All participants provided consent prior to commencing the survey.Demographic informationDemographic information on the sample was collectedincluding, age, gender, education, ethnicity, self-reportedcurrent diagnosis of a mental illness; government subsidies sought in the past month as a result of pandemicrelated employment changes and loneliness (questionasked – ‘Compared to the month prior to the COVID-19outbreak, have you felt an increased sense of lonelinessover the past 7 days – Yes or No?’)Psychological impact of COVID-19The psychological impact of COVID-19 was measuredusing the Impact of Event Scale-Revised (IES-R). TheIES-R is a self-administered 22 item questionnaire that hasbeen extensively used for determining the extent of psychological impact after exposure to a public health crises,including infectious disease outbreaks (Reynolds et al.,2008; Wang et al., 2020a). The total IES-R score wasdivided into 0–23 (normal), 24–32 (mild/moderate psychological impact, scores in this range suggest PTSD is aclinical concern (Asukai et al., 2002)), 33–38 (moderatepsychological impact, scores in this range represent aprobable diagnosis of PTSD (Creamer et al., 2003)), and>39 (severe psychological impact) (Creamer et al., 2003).Mental health status was measured using the Depression,Anxiety and Stress Scale (DASS-21) (Lovibond &Lovibond, 1995). The DASS-21 is a set of three self-reportscales designed to measure the emotional states of depression, anxiety and stress. Questions 3, 5, 10, 13, 16, 17 and21 formed the depression subscale. The total depressionsubscale score was divided into normal (0–4), mild depression (5–6), moderate depression (7–10), severe depression(11–13) and extremely severe depression (14+). QuestionsGurvich et al. 32, 4, 7, 9, 15, 19 and 20 formed the anxiety subscale. Thetotal anxiety subscale score was divided into normal (0–3),mild anxiety (4–5), moderate anxiety (6–7), severe anxiety(8–9) and extremely severe anxiety (10+). Questions 1, 6,8, 11, 12, 14 and 18 formed the stress subscale. The totalstress subscale score was divided into normal (0–7), mildstress (8–9), moderate stress (10–12), severe stress (13–16) and extremely severe stress (17+). The DASS hasbeen previously used in research related to infectious disease outbreaks, including SARS (McAlonan et al., 2007)and early studies in China in relation to COVID-19 (Wanget al., 2020a).Suicidal thoughts were measured using Beck DepressionInventory (BDI) suicide item (item 9) (Beck et al., 1996).The BDI suicide item assesses suicidal ideation and israted on a 4-point scale, with higher scores indicatinggreater intent. The use of this single item as a brief, efficient screen for suicide risk has been previously demonstrated (Green et al., 2015).Coping measuresThe Brief COPE Inventory (Carver, 1997) is an abbreviated version of the original 60-item COPE inventory(Carver et al., 1989). The Brief COPE is a 28 item, selfreport 4-point Likert instrument that was used to measureeffective and ineffective ways to cope or minimise distressassociated with the current COVID-19 pandemic. TheBrief COPE has been validated to assess different types ofstressors and to evaluate functionality or dysfunctionalityof the use of certain strategies indifferent contexts (Meyer,2001). The 28 items load onto 14 factors or coping styles:Self-distraction; Active Coping; Denial; Substance use;Use emotional support; Use of Instrumental support;Behavioural disengagement; venting; Positive reframing;Humour; Acceptance; Religion and Self-blame. The BriefCOPE has been used to evaluate coping strategies duringprevious infectious disease outbreaks (Wong et al., 2005).DataStudy data were collected and managed using REDCap(Research Electronic Data Capture), a secure, web-basedsoftware platform hosted at Monash University REDCap(Harris et al., 2009, 2019).Data availability statementThe data that support the findings of this study are availablefrom the corresponding author upon reasonable request.Analysis strategyWe aimed to compare gender groups across a number ofpsychological ratings by reducing covariates or confoundersimbalance (standardised mean differences, Table 2) throughthe propensity score weights (Austin, 2011). In this analysis,the rationale behind using propensity score weights is thatthere were still significant differences in some covariatescharacteristics between female and male respondents(>0.25) even after applying sampling weights for gender(Table 1). Therefore, we formulated the propensity scoresfor gender groups using 14 covariates, and then we calculated the standardised differences again after obtaining thepropensity score weights (Table 2). Further, we obtained thefinal weights for group imbalance by multiplying the sampling weights by the propensity score weights. Furthermore,for each outcome in Table 3, we used the final weights tomodel the effects of gender (female vs male), adjusting forthe 14 covariates. The final models are displayed in Table 3.Analyses for propensity score weights were performed withPSMATCH procedure in SAS (SAS institute, Cary NC).Path analysis was performed on variables correlationmatrix using structural equations model (SEM) to estimatesimultaneous gender adjusted effects of coping (as measured by Brief COPE Inventory) on depression, anxiety andstress constructs (DASS-21). Analyses with latent variables path models are preferred for population-based studies because they allow for associative or parallel estimationof variables at the same time and fitting errors or disturbances of measurements as freely parameterised quantities. We used robust maximum likelihood, ML (lavaanpackage (Rosseel, 2012)) as the model estimator. The finalmodel was assessed using multiple fit indices; Chi-squaretest(χ2), comparative fit index (CFI), Tucker-Lewis index(TLI), root mean square error of approximation (RMSEA),and standardised root mean square residual (SRMR). Weopted not to use the modification indices (Chi-square estimates for addition or inclusion of parameters or patharrows), to improve the statistical fitness. All analyseswere written in R (R Core Team).ResultsWe received responses from 1,790 participants. Of these,1,495 participants, all residing in Australia at the time ofthe survey, were included in the final analysis. The 295excluded participants had missing data with more than80% of survey items.Demographic variables and psychologicalimpactThe majority of respondents identified as female,n = 1,226 (81·6%); Caucasian n = 1,242 (82·7%); andwere University educated with a Bachelors degreen = 730 (48·6%). The distribution of sociodemographicfactors, depression, anxiety and stress scores as well asdegree of psychological impact scores weighted by gender are presented in Table 1.4 International Journal of Social Psychiatry 00(0)Table 2. Sample characteristic standardised mean differences between female and males.SMD (sample weighted) SMD (Propensity score weighted)Age -0.34695 0.00814Education: university -0.02598 -0.02636Current diagnosis of a mental illness (Yes vs No) -0.25795 0.06958IES-R category (normal range – scores 39) -0.31590 0.05131Ethnicity representation (Caucasian) -0.04561 0.05974Ethnic representation (Asian) 0.20120 -0.02512Government subsidies or centre link access as a result ofCOVID-19 employment change-0.08194 -0.04046DASS_21 depression moderate to severe category (7–14+) -0.35866 0.01973DASS_21 anxiety moderate to severe category (6–10+) -0.32890 -0.00709DASS_21 stress moderate to severe category(10–17+) -0.45359 0.04275Suicide ideation (BDI item 9) -0.07924 -0.02924Loneliness (Yes vs No) -0.24881 -0.03885SMD = standardised mean differences.Table 1. Demographic and Psychological measures† by Gender.Characteristic Male FemaleMean(%) SE Mean (%) SEAge (years) 44.3 1.024804 40.7 0.169196Age category (18–24 years) 0.149573 (14.96%) 0.021411 0.155918 (15.59%) 0.004151Age category (25–39 years) 0.294872 (29.49%) 0.027374 0.354286 (35.43%) 0.005473Age category (40–54 years) 0.239316 (23.93%) 0.025614 0.293061 (29.31%) 0.005208Age category (55–69 years) 0.200855 (20.08%) 0.024052 0.161633 (16.16%) 0.004212Age category (70–85 years) 0.115385 (11.54%) 0.019180 0.035102 (3.51%) 0.002106Ethnicity representation (Caucasian) 0.820513 (82.05%) 0.023038 0.831974 (83.20%) 0.004277Ethnicity (Asian) 0.115385 (11.54%) 0.019180 0.086460 (8.65%) 0.003215Current diagnosis of a mental illness (Yes vs. No) 0.291845 (29.18%) 0.027351 0.390701 (39.07%) 0.005581Government subsidies or centre link access as aresult of COVID-19 employment change0.126126 (12.61%) 0.020464 0.134860 (13.49%) 0.003984Loneliness (Yes vs. No) 0.463519 (46.35%) 0.030001 0.577396 (57.74%) 0.005662Education (primary or secondary school vsuniversity level – bachelor or above)0.773504 (77.35%) 0.025128 0.782219 (78.22%) 0.004721IES-R 13.767677 0.954943 21.864683 0.210698IES-R category(normal range 39)0.080808(8.08%) 0.017794 0.181382(18.14%) 0.004781DASS_21 Depression subscale 4.057143 0.290561 6.112988 0.068195DASS_21 Anxiety subscale 1.531073 0.181202 3.147679 0.046908DASS_21 Stress subscale 4.615819 0.287383 6.958904 0.058966DASS_21 Depression Moderate to severe 0.194286 (19.42%) 0.027486 0.352693 (35.27%) 0.006219DASS_21 AnxietyModerate to severe0.090395 (9.01%) 0.019807 0.206751 (20.68)% 0.005268DASS_21 StressModerate to severe0.101695 (10.17%) 0.020877 0.269758 (26.98%) 0.005771Suicide ideation(BDI item 9)0.136646 (13.66%) 0.024883 0.174112 (17.41%) 0.005141†Means and standard errors (in italics) are calculated with survey package in R.Gurvich et al. 5Analysis of covariate imbalanceResults from Table 2 suggest that weighting with the propensity score reduced covariate imbalance between thegenders in such a way that made the psychological ratingsor outcome means more comparable (all standardisedmean differences