Long-term psychological consequences of long Covid: a propensity score matching analysis comparing trajectories of depression and anxiety symptoms before and after contracting long Covid vs short Covid
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Background
There is a growing global awareness of the psychological consequences of long Covid, supported by emerging empirical evidence. However, the mergence and long-term trajectories of psychological symptoms following the infection are still unclear.
Aims
To examine when psychological symptoms first emerge following the infection with SARS-CoV-2, and the long-term trajectories of psychological symptoms comparing long and short Covid groups.
Methods
We analysed longitudinal data from the UCL Covid-19 Social Study (March 2020-November 2021). We included data from adults living in England who reported contracting SARS-CoV-2 by November 2021 (N=3,115). Of these, 15.9% reported having had long Covid (N=495). They were matched to participants who had short Covid using propensity score matching on a variety of demographic, socioeconomic and health covariates (N=962, n=13,325) and data were further analysed using growth curve modelling.
Results
Depressive and anxiety symptoms increased immediately following the onset of infection in both long and short Covid groups. But the long Covid group had substantially greater initial increases in depressive symptoms and heightened levels over 22 months follow-up. Initial increases in anxiety were not significantly different between groups, but only the short Covid group experienced an improvement in anxiety over follow-up, leading to widening differences between groups.
Conclusions
The findings shed light on the psychobiological pathways involved in the development of psychological symptoms relating to long Covid. The results highlight the need for monitoring of mental health and provision of adequate support to be interwoven with diagnosis and treatment of the physical consequences of long Covid.
Article activity feed
-
SciScore for 10.1101/2022.04.01.22273305: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: The study was approved by the UCL Research Ethics Committee [12467/005] and all participants gave written informed consent.
Consent: The study was approved by the UCL Research Ethics Committee [12467/005] and all participants gave written informed consent.Sex as a biological variable These included gender (women vs men), ethnicity (white vs ethnic minorities), age groups (age 18-29, 30-45, 46-59, 60+), education (up to GCSE levels, A-levels or equivalent, and university degree or above), income (<£16,000, £16,000-29,000, £30,000-59,000, £60-89,000, ≥£90,000 per annum), employment status (employed non-key worker, employed key worker, other), area of living (city, town, rural), living … SciScore for 10.1101/2022.04.01.22273305: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: The study was approved by the UCL Research Ethics Committee [12467/005] and all participants gave written informed consent.
Consent: The study was approved by the UCL Research Ethics Committee [12467/005] and all participants gave written informed consent.Sex as a biological variable These included gender (women vs men), ethnicity (white vs ethnic minorities), age groups (age 18-29, 30-45, 46-59, 60+), education (up to GCSE levels, A-levels or equivalent, and university degree or above), income (<£16,000, £16,000-29,000, £30,000-59,000, £60-89,000, ≥£90,000 per annum), employment status (employed non-key worker, employed key worker, other), area of living (city, town, rural), living situation (living alone, living with adults only, living with children), number of close friends (0 to 10+) and usual social contacts (twice a month or less, once or twice a week, three times a week or more), self-reported diagnosis of any long-term physical health condition or any disability (yes vs no), and self-reported diagnosis of any long-term mental health condition (yes vs no). Randomization not detected. Blinding not detected. Power Analysis not detected. Cell Line Authentication Authentication: 29 To compare mental health growth trajectories between the two matched groups, data were analysed using growth curve models. Table 2: Resources
Software and Algorithms Sentences Resources As sensitivity analyses, (i) we reran the analyses using alternative matching methods, namely one-to-many nearest neighbour matching and kernel matching; (ii) we excluded anyone who said they were ‘unsure’ if they had long Covid; and (iii) we explored further people’s understanding of the term ‘long Covid’. Covid’suggested: NoneResults from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
-
