PTSD Symptoms Among Health Workers and Public Service Providers After the COVID-19 Outbreak: A 3 Month Follow up
NCT ID: NCT04442243
Last Updated: 2020-06-24
Study Results
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Basic Information
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UNKNOWN
889 participants
OBSERVATIONAL
2020-06-22
2020-07-13
Brief Summary
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Detailed Description
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H1: There will be a significant decrease in PTSD-symptoms, anxiety and depression from T1 to T2.
Exploratory: Examine the differences in levels of trauma, anxiety, depression and quality of life among different health workers, public service providers, demographic subgroups, and between those working directly vs indirectly with COVID-19 patients at T2. Examine the differences in change of trauma, anxiety and depression among different health workers, public service providers, demographic subgroups, and between those working directly vs indirectly with COVID-19 patients.
H2: Higher level at T1 and less reduction from T1 to T2 in metacognition, strategies, burnout, worry about job and economy, interpersonal problems at baseline will be associated with less reduction in PTSD-symptom from T1 to T2, above and beyond direct vs. indirect exposure to trauma, demographic variables (age and gender, living with a partner, living with children).
This study is part of 'The Norwegian COVID-19, Mental Health and Adherence Project', involving multiple studies.
Sample size The sample size at T1 was 1778 participants. The sample size at T2 is not yet clarified, but we expect 50% drop out.
Sample size rationale The mentioned 'Norwegian COVID-19 and Mental Health and Adherence Project' involves multiple studies, where some involve a Complex Systems (Network analysis approach). These multivariate analyses require large samples and power analysis was conducted accordingly. Following power analysis guidelines by Fried \& Cramer (2017), it is recommended that the number of participants be at the very least three times larger than the number of estimated parameters. However, more conservative recommendations by Roscoe (1975) for multivariate research, recommends sample size that is ten times larger than the number of estimated parameters.
Stopping rule:
The data collection will start at June 22th and continue until as many as possible of 1778 respondents at T1 have submitted the questionnaire. The data-collection at T2 will be stopped after three weeks.
Indices:
Given Acceptable Cronbach's alpha (above 0.7) two items was combined to represent worry about work and economy. On the CAS1 four items were combined into the subscale "positive metacognition", four items were combined into the subscale "negative metacognition", and 8 items were combined into the subscale strategies (Nordahl \& Wells, 2019). Interpersonal problems consisted of 17 items selected from the IIP-64. Burnout was measured with a single item. Worry about job and economy were measured with two time-points.
Statistical models:
Descriptive statistics with frequency tables including N, mean and SDs or median and interquartile range depending on the data will be presented. A cut-off of 31 on the PCL-5 will be used together with the DSM-5 diagnostic guidelines applied to the PCL-5 to categorize participants as fulfilling the PTSD symptom criteria or not. Participants indicating scores of 2 or above on at least one of five re-experiencing symptoms, one of two avoidance symptoms, two of seven symptoms of negative alterations in cognition and mood and two of six arousal symptoms were classified as fulfilling the PTSD symptom criteria. Subclinical PTSD will be assessed by specifying how large part of the sample which fulfill parts of the PTSD-criterias, more specifically have at least one symptom above threshold (2 or above) in each symptom-group. The results will be benchmarked against national and international studies.
For PHQ-9, scores above 10 are considered as cut-off indicating that the patient is within the depressive area.
For GAD-7 a cut-off of 8 and above will be used.
Paired sample t-test or paired samples Wilcoxon Test will be used to compare the PTSD-symptoms at T2, depending on the nature of the data.
A One-way ANOVA or Kruskal-Wallis test, depending on level of skewness, will be conducted to exploratory investigate differences between the different types of health-workers (e.g. medical doctor and clinical psychologists) and public service providers (e.g., politicians, social security), working directly vs indirectly. If there is significant differences between the groups the investigators will either use a post hoc test, Tukey (HSD) or Dunn-Bonferroni, depending on wether a parametric or non-parametric test has been used.
Repeated surveys like the present one typically have a lot of drop out and missing data. Therefore, we will use mixed models instead of paired t-tests, repeated measures ANOVAs, and ordinary linear regression to analyze the majority of the data. Mixed models use maximum likelihood estimation, which is the state of the art approach to handle missing data (Schafer \& Graham, 2002). Especially if data are missing at random, which is likely in our survey, mixed models give more unbiased results than the other analytic methods (O'Connel et al., 2017).
In preliminary analyses, and for each of the dependent variables (PCL-5, GAD-7 and PHQ-9), the combination of random effects and covariance structure of residuals that gives the best fit for the "empty" model (the model without fixed predictors except the intercept) will be chosen. Akaike's Information Criterion (AIC) will used to compare the fit of different models. Models that give a reduction in AIC greater than 2 will be considered better (Burnham \& Anderson, 2004). The program SPSS 25.0 will be used (IBM Corp, 2018).
First, H1 about decrease in PCL-5, GAD-7 and PHQ-9 will be tested by using anxiety or depression as dependent variable in a model using time (T1 period = 0, T2 period = 1) as a predictor. Second, demographic group variables will be added as predictors. Third, the initial (T1) levels of metacognition, strategies, burnout, worry about job and economy, interpersonal problems will be added, together with the interactions of these constant covariates with time. These interactions represent tests of H2 about the covariates predicting change in PTSD-symptoms. Finally, the T2 levels of metacognition, strategies, burnout, worry about job and economy, interpersonal problems as constant covariates will be added, together with the interactions of these constant covariates with time. These interactions represent tests of H2 about the change in the covariates from T1 to T2 predicting change in PTSD-symptoms from T1 to T2s.
Transformations Depending on degree of skewness compared to theoretical possibilities and interpretations, variables will be assessed in their original and validated format as is recommended practice, as long as this is possible. As this study examines psychopathology levels amongst a general population (and not a clinical population), we do expect a skewed data PTSD-symptoms on depressive and anxiety levels with most individuals reporting low levels of PTSD -symptoms.
We will attempt to assess these variables in their original and validated format as is recommended practice, as long as this is possible. However, if this is not possible to the statistical assumptions behind the analyses, transformation may be needed to apply interval-based methods. Alternatively a non-parametric test will be used.
Inference criteria
Given the large sample size in this study, we pre-define our significance level:
p \< 0.01 to determine significance
Data exclusion:
All health care or public service provides above 18 are included in this study. Vulnerable health-care or public service providers - in this sample defined as doctors, nurses, psychologists, and any other health-care workers, as well as politicians and social workers. The participants reported if they worked directly or indirectly with COVID-19 patients.
Exploratory:
Questions addressed in the future paper which is not pre-specified will be defined as exploratory.
Conditions
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Study Design
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OTHER
PROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
Yes
Sponsors
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Modum Bad
OTHER
University of Oslo
OTHER
Responsible Party
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Sverre Urnes Johnson
Associate Professer Sverre Urnes Johnson
Principal Investigators
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Omid Ebrahimi, Mr
Role: PRINCIPAL_INVESTIGATOR
University of Oslo & Modum Bad
Asle Hoffart, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Oslo & Modum Bad
Central Contacts
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Other Identifiers
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REK125510 (4)
Identifier Type: -
Identifier Source: org_study_id
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