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      Prevalence and correlates of positive and negative psychological effects of bereavement due to COVID-19: A living systematic review

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          Abstract

          Background: The coronavirus disease 2019 (COVID-19) pandemic is associated with an increase in mortality rates globally. Given the high numbers of deaths and the potentially traumatic characteristics of COVID-19 deaths, it is expected that grief-related distress levels are higher in COVID-19 bereaved (compared to non-COVID-19 bereaved) people. This living systematic review (LSR) investigates the empirical evidence regarding this claim. More specifically, this LSR summarizes studies evaluating prevalence and correlates of positive and negative psychological effects of COVID-19 bereavement. This iteration synthesizes evidence up to July 2022. Methods: Systematic searches were conducted in PsychInfo, Web of Science, and Medline by two independent reviewers. Eligible studies included quantitative peer-reviewed articles reporting on positive and/or negative psychological outcomes, using validated measures, in COVID-19 bereaved adults. The primary outcome was prolonged grief symptoms (PG). Results: Searches identified 9871 articles, whereof 12 studies met the inclusion criteria. All studies included prevalence rates and/or symptom-levels of psychological outcomes after COVID-19 losses. Prevalence rates of psychological outcomes were primarily reported in terms of (acute) PG, pandemic grief, depression, anxiety, and functional impairment, and varied widely between studies (e.g., ranged between 29% and 49% for acute PG). No studies reported on prevalence rates of positive psychological outcomes. Closer kinship to the deceased, death unexpectedness, and COVID-19 stressors were identified as correlates of increased psychological symptoms. Conclusions: Due to the small number and heterogeneity of studies, knowledge about psychological effects of COVID-19 bereavement is limited. This LSR offers a regular synthesis of up-to-date research evidence to guide clinicians, policy makers, public health professionals, and future research on the psychological effects of COVID-19 bereavement.

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          Most cited references73

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          The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

          The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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            The psychological impact of quarantine and how to reduce it: rapid review of the evidence

            Summary The December, 2019 coronavirus disease outbreak has seen many countries ask people who have potentially come into contact with the infection to isolate themselves at home or in a dedicated quarantine facility. Decisions on how to apply quarantine should be based on the best available evidence. We did a Review of the psychological impact of quarantine using three electronic databases. Of 3166 papers found, 24 are included in this Review. Most reviewed studies reported negative psychological effects including post-traumatic stress symptoms, confusion, and anger. Stressors included longer quarantine duration, infection fears, frustration, boredom, inadequate supplies, inadequate information, financial loss, and stigma. Some researchers have suggested long-lasting effects. In situations where quarantine is deemed necessary, officials should quarantine individuals for no longer than required, provide clear rationale for quarantine and information about protocols, and ensure sufficient supplies are provided. Appeals to altruism by reminding the public about the benefits of quarantine to wider society can be favourable.
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              Interrater reliability: the kappa statistic

              The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability. While there have been a variety of methods to measure interrater reliability, traditionally it was measured as percent agreement, calculated as the number of agreement scores divided by the total number of scores. In 1960, Jacob Cohen critiqued use of percent agreement due to its inability to account for chance agreement. He introduced the Cohen’s kappa, developed to account for the possibility that raters actually guess on at least some variables due to uncertainty. Like most correlation statistics, the kappa can range from −1 to +1. While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations. Judgments about what level of kappa should be acceptable for health research are questioned. Cohen’s suggested interpretation may be too lenient for health related studies because it implies that a score as low as 0.41 might be acceptable. Kappa and percent agreement are compared, and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.

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                Journal
                F1000Research
                F1000Res
                F1000 Research Ltd
                2046-1402
                2023
                March 3 2023
                : 12
                : 237
                Article
                10.12688/f1000research.130397.1
                72fd5143-d6dd-4e4b-83e7-5dcaa669aa0b
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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