Loneliness During Strict and Lifted Social Distancing Protocols Against the COVID-19 Pandemic
NCT ID: NCT04444115
Last Updated: 2020-06-23
Study Results
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Basic Information
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UNKNOWN
10084 participants
OBSERVATIONAL
2020-06-22
2020-07-13
Brief Summary
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An investigation of loneliness persistence in addition to its association with risk factors and the persistence of psychopathology provides a knowledge basis for employing interventions that protect the general public against increased distress and dysfunction during and after society's handling of pandemics.
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Detailed Description
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The hypotheses (Hs) and explorative research questions of the present study were:
H1: The lifting of the social distancing protocols are associated with decreased loneliness. Exploratory question 1. What is the proportion showing a reliable change in loneliness? Exploratory question 2. What are the associations of the stable (demographic) factors age, gender, educational level, civil status, employment status, psychiatric diagnosis status and refugee status with change in loneliness from T1 to T2? H2: Of psychological factors, higher level at T1 and less reduction from T1 to T2 in worry about job and/or economy, worry about health (health anxiety), maladaptive mental and behavioral coping, and negative and positive metacognitions will be associated with less reduction in loneliness from T1 to T2, above and beyond the influence of pre-existing stable risk factors.
Explorative question 3. What are the potential protective effects of doing new positive activities at home, experiencing nature and performing aerobic physical exercise? That is, is higher level at T1 and more increase from T1 and T2 of these activities related to more reduction of loneliness from T1 to T2? H3: More loneliness at T1 will be associated with less reduction of depressive and anxiety symptoms from T1 to T2. Less reduction in loneliness from T1 to T2 will be associated with less reduction of symptoms in the same time frame. Because variables related to loneliness may confound the relationship between loneliness and psychopathology symptoms, the variables showing significant associations for Hypothesis 2 and 3 will be controlled for. However, psychiatric diagnosis will not be included as a control variable because T1 level of depression and anxiety symptoms is controlled.
Study design and participants The design is a longitudinal observational survey of the general adult Norwegian population during the COVID-19 pandemic. Eligible participants are all individuals of 18 years and above, who are living in Norway and thus experience identical distancing protocols, and who provide informed consent to participate in the study. The strict distancing protocols were implemented in Norway at March 12. 2020 and the first data collection in this period has already been done. It lasted seven days and was between March 31st 2020 and April 7th 2020. Thus, the strict protocols had been held constant during the two weeks prior to data collection, as well as during the data collection week. Furthermore, no new information was given by the government during this period with regard to changes of distancing protocols, keeping expectation effects constant. From June 15., the majority of the strict distancing protocols will be lifted in Norway, and lifted distancing protocol period is defined from this date. Data are set to be collected from the sample providing data in the first collection (N = 10 084), starting one week after the lifting data, that is, from 22th of June. The collection will last until enough data has been collected, but no longer than three weeks.
Ethical approval of the study was granted by The Regional Committee for Medical and Health Research Ethics and the Norwegian Centre for Research Data (reference numbers: 125510 and 802810, respectively, where the study protocol and analysis plan was approved prior to data collection. The study is conducted in accordance with the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology statement (STROBE; Von Elm et al., 2007). The pre-registered protocol for a study of loneliness based on the first T1 data collection can be found at Clinicaltrials.gov (Identifier: NCT04365881). The study is part of The Norwegian COVID-19, Mental Health and Adherence Project (Ebrahimi, Hoffart, \& Johnson, 2020).
Procedures The survey was disseminated online in a systematic manner to give the adult population an equal opportunity to participate in the study. The dissemination procedure involved information about the survey through broadcasting on national, regional, and local news channels and provision of the online survey to a random selection of Norwegian adults on Facebook. The dissemination procedure is described in detail elsewhere (Ebrahimi et al., 2020).
The stopping rule for the first data collection was designed to ensure that the social distancing protocols were held constant for two weeks prior to and the week during the data collection period, as well as controlling for expectation effects by stopping data collection instantly once information concerning forthcoming modification of the protocols were given. The second data collection will start one week after the social distancing protocols are lifted (June 22.) and last three weeks.
Inference criteria Given the large sample size in this study, the investigators pre-define their significance level: p \< 0.001 to determine significance.
Sample size and power The sample size T1 included 10 084 participants, ascertaining power for the questions asked. For the present study, all these participants will be invited to participate at T2 in accordance with the study plan.
Statistical analyses 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 least square regression to analyze 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 (ULS-8, PHQ-9, GAD-7), 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 ULS-8 will be tested by using ULS-8 as dependent variable in a model using time (T1 = 0, T2 = 1) as a predictor. Second, demographic group variables will be added as predictors. Third, the T1 levels of worry about job and/or economy, worry about health (health anxiety), maladaptive mental and behavioral coping, and negative and positive metacognitions as constant covariates 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 loneliness. Finally, the T2 levels of worry about job and/or economy, worry about health (health anxiety), maladaptive mental and behavioral coping, and negative and positive metacognitions 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 loneliness from T1 to T2.
To analyze the influence of level and change in loneliness on change in depression and anxiety (H3), depression and anxiety are used as dependent variables in two mixed models, with first the interaction of time with loneliness at T1 and then the interaction of time with loneliness at T2 as covariates. The main effects of these variables are included as well as all significant terms from the analyses of loneliness as dependent variable.
Reliable change in loneliness will be assessed using the formula of Jacobson and Truax (1991). The statistical analyses were done in the program SPSS 25.0 (IBM Corp, 2018).
Sensitivity analyses Sensitivity analyses will be conducted after selecting a random sample of participants to reflect the proportion of subgroups in the Norwegian adult population.
Conditions
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Study Design
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ECOLOGIC_OR_COMMUNITY
PROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
Yes
Sponsors
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University of Oslo
OTHER
Modum Bad
OTHER
Responsible Party
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Asle Hoffart
Prof
Principal Investigators
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Omid Ebrahimi, Cand Psychol
Role: PRINCIPAL_INVESTIGATOR
University of Oslo and Modum Bad
Asle Hoffart, PhD
Role: PRINCIPAL_INVESTIGATOR
Modum Bad and University of Oslo
Sverre Urnes Johnson, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Oslo and Modum Bad
Central Contacts
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References
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Hoffart A, Johnson SU, Ebrahimi OV. Loneliness during the COVID-19 pandemic: change and predictors of change from strict to discontinued social distancing protocols. Anxiety Stress Coping. 2022 Jan;35(1):44-57. doi: 10.1080/10615806.2021.1958790. Epub 2021 Jul 27.
Other Identifiers
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802810-1
Identifier Type: -
Identifier Source: org_study_id
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