Healthcare worker stress, anxiety and burnout during the COVID-19 pandemic in Singapore: A 6-month multi-centre prospective stud

doi:10.25540/DAX0-K3ZFStudy design This study used the convenience sampling method to prospectively follow HCWs from four tertiary hospitals in Singapore that provided care to COVID-19 patients during the pandemic. Recruitment occurred throughout the duration of the study. The self-reported data was collected from 12 March - 31 August 2020, which included the peak of the pandemic that year and the nationwide lockdown period that occurred between April 7-June 1, 2020. Participants & data collection Doctors, nurses, allied health professionals, administrative and operations staff from several institutions (Singapore General Hospital, KKH Women’s & Children’s Hospital, Changi General Hospital, Sengkang General Hospital) within the largest public healthcare group in Singapore were invited through work email and/or staff portals to participate. There were no exclusion criteria. Participation was voluntary and those who were interested accessed the study through a web link or QR code. Participants provided their consent online before completing the initial survey and monthly follow-ups which took 15 and 10 minutes to complete, respectively. Follow-up survey links were sent directly to participants’ email address, which served as a way to link the responses over time. No other personal identifying information was collected. Research assistants who managed the data collection on the Qualtrics platform were not involved in data analyses. The survey was administered in English. The study was approved by the National University of Singapore IRB (S-20-081) and exempted from review by the SingHealth Centralized IRB (2020/2160). Measures Study outcomes. Stress was measured using the 4-item Perceived Stress Scale (PSS-4) [12]. A summed score ranging from 0-16 was calculated, and a median score threshold of ≥ 8 was used to indicate stress. Anxiety was measured using the 7-item Generalized Anxiety Disorder (GAD-7) scale [13]. A summed score ranging from 0-21 was calculated and the recommended threshold score of ≥ 10 was used. Job burnout was measured using a one-item burnout question from the Physician Work Life Scale where a score ≥ 3 indicated presence of job exhaustion [14]. The measure has been used with a range of HCWs including doctors, nurses, and administrative personnel [14]. Higher scores on all study outcomes indicated greater severity. Objective job characteristics. Participants reported their number of working years in healthcare. The responses to the following questions were coded “yes”/ “no”: whether they had a supervisory role, experienced the 2003 SARS outbreak as a HCW, worked night-shifts in the past month and worked longer than usual hours in the past month. Exposure to COVID-19 was assessed by “How often does your job require you to come in contact with suspected/ confirmed COVID-19 patients/ specimens?” with the response options being “not at all”, “occasionally”, and “daily”.   HCW-perceived job factors. Perceived job risk was assessed using the item “I feel that my job puts me at great risk of exposure to COVID-19” where responses ranged from “strongly agree” to “strongly disagree” on a 6-point scale which was later recoded into a binary variable (high risk vs. low risk) [15]. Effective COVID-19 communication in the workplace was assessed using three items: availability/ timeliness of updates, trustworthiness of information, and clarity of policies and protocols. Teamwork was assessed via the statement “My work team has been working well together”. The response options were “yes”, “neutral”, and “no”. These workplace support questions were considered to have face validity and adapted from a previous SARS outbreak study [16]. Job dedication was measured using the subscale from the Utrecht Work Engagement Scale-9 [17], where a higher summed score indicated higher job dedication, which consisted of feelings of enthusiasm, inspiration and pride for one’s job. Feeling appreciated was assessed by the statement “I feel appreciated by my department/ hospital/ employer” where the responses were coded into a binary variable: “never”/ “rarely” vs. “sometimes”/ “always”. Personal resources. The 4-item short forms of the Patient-Reported Outcomes Measurement Information System (PROMIS) [18] measures of emotional support [19] and general self-efficacy [20] were used. The Emotional Support scale assesses perceived feelings of being cared for and valued as a person, while the General Self-efficacy scale measures confidence in exerting control over one’s situation. Both measures were rated to on a 5-point scale, with higher scores indicating increase in the construct measured. Summed scores were converted into T-scores.   Health. Presence of a chronic health condition was assessed by the question “In your lifetime, have you ever been diagnosed by a physician as having a chronic disease or medical condition?” with the response options “yes”, “no” and “neutral”. Whether a participant had been quarantined during the duration of the study was coded as “yes”/ “no”. Data analysis A random-intercept logistic regression model, which is robust when missingness depends only on observed data (i.e., missing at random [MAR]), was used to investigate two questions: (1) whether rates of stress, anxiety, and job burnout among HCWs were increasing over time, and (2) what were the predictors of stress, anxiety, and job burnout among HCWs. To address the first question, we regressed the psychological outcomes of interest on calendar month. Calendar months were initially specified as a categorical variable to visualize trends, and later as a continuous variable to test for any statistically significant linear or quadratic trends.   To address the second question, we regressed the psychological outcomes of interest on potential predictors, while controlling for calendar month, demographic factors (age, gender, marital status, presence of a chronic health condition and living with children, elderly, or vulnerable persons), and placement on quarantine related to COVID-19. Predictors considered include objective job characteristics, HCW-perceived job factors and personal resources which were described earlier. Regression models omitting HCW-perceived job factors and personal resources were also estimated to investigate how predictive objective job characteristics are of the outcomes in the absence of information on subjective factors. Analyses were conducted using Stata version 15·1 [21] and statistical inference were based on cluster-robust standard errors (SEs) and the 5% significance level.  </p

A hybrid equity release plan for retirement financing

Ministry of Education, Singapore under its Academic Research Funding Tier 3, Tier

The Economic Burden of Self-Reported and Undiagnosed Cardiovascular Diseases and Diabetes on Indonesian Households

<div><p>Objectives</p><p>The goal of this study is: (1) to estimate the current direct out-of-pocket (OOP) and indirect non-communicable diseases (NCD) burden on Indonesian households and (2) to project NCD prevalence and burden in 2020 focusing specifically on hypertension, diabetes, heart problems and stroke.</p><p>Methods</p><p>This study relies on econometric analyses based on four waves of the Indonesian Family Life Survey (IFLS).</p><p>Results</p><p>In aggregate, of the NCDs studied, heart problems exert the greatest economic burden on households, costing Int$1.56 billion in OOP and indirect burden in 2010. This was followed by hypertension (Int$1.36 billion), diabetes (Int$0.81 billion) and stroke (Int$0.29 billion). The OOP and indirect burden of these conditions is estimated to be Int$4.02 billion. Diabetes and stroke are expected to have the largest proportional increases in burden by 2020; 56.0$1.27 billion and Int$0.45 billion respectively. The burden of heart problems in 2020 is expected to increase by 34.4$2.09 billion and hypertension burden will increase by 46.1% to Int$1.99 billion. In 2020, these conditions are expected to impose an economic burden of Int$5.80 billion.</p><p>Conclusion</p><p>In conclusion, this study demonstrates the significant burden of 4 primary NCDs on Indonesian households. In addition to the indirect burden, hypertension, diabetes, heart problems and stroke account for 8% of the nation's OOP healthcare expenditure, and due to rising disease prevalence and an aging population, this figure is expected to increase to 12% by 2020 without a significant health intervention.</p></div

National NCD prevalence and burden in 2010 and 2020 among those aged 40+.

<p>National NCD prevalence and burden in 2010 and 2020 among those aged 40+.</p

Sample demographics (n = 10,795).

<p>Sample demographics (n = 10,795).</p

Annual per capita NCD burden in 2007/08 by type of disease and disease awareness.

<p>SR Self-reported; UD Undiagnosed.</p><p>Two-tailed significance test from zero were performed. P-values below 5% is indicated with an asterisk.</p>†<p>Sum of out-of-pocket expenditures for outpatient, inpatient and self-treatment rounded to the nearest Int$10.</p>§<p>Sum of monetized indirect burden, rounded to the nearest Int$10. Each day of lost primary activity was valued at the average expected daily wage (Int$3.86) and each of hour of required assistance valued at the hourly market rate for paid assistance (Int$0.34).</p>‡<p>Sum of direct and indirect burdens, rounded to the nearest Int$10.</p>#<p>A percentage of mean annual household income among each NCD status.</p

Sample prevalence of risk factors and NCDs from IFLS and Riskesdas.

§<p>Household were sampled from the entire Republic of Indonesia.</p