52 Depressive Symptoms and Subjective Cognitive Decline in Individuals with COVID-19
Bibliographic record
Abstract
Objective: Many individuals with COVID-19 develop mild to moderate physical symptoms that can last days to months. In addition to physical symptoms, individuals with COVID-19 have reported depressive symptoms and cognitive decline, posing a long-term threat to mental health and functional outcomes. Few studies have examined the presence of co-occurring depression and subjective cognitive decline in individuals who tested positive for COVID-19. The current study examined whether having COVID-19 is subsequently associated with greater depressive symptoms and subjective cognitive decline when compared to healthy individuals. Our study also examined differential associations between symptoms of depression and subjective cognitive decline between individuals who have and have never had COVID-19. Participants and Methods: Adults (N = 104; mean age = 37 years, 69% female) were recruited online from Ontario and British Columbia, Canada. Participants were categorized into two groups: (1) persons who tested positive for COVID-19 at least three months prior, had been symptomatic, and had not been ventilated (N = 50); and (2) persons who have never been suspected of having COVID-19 (N = 54). The Center for Epidemiological Studies Depression Scale (CES-D) and the Subjective Cognitive Decline Questionnaire (SCD-Q) were administered to both groups as part of a larger clinical neuropsychological evaluation. Two separate linear regression analyses were conducted to examine the association of COVID-19 with depressive symptoms and subjective cognitive decline. A moderation analysis was performed to examine whether depressive symptoms were associated with subjective cognitive decline and the extent to which this differed by group (COVID-19 and controls). Participants’ age, self-reported sex, and history of depression were included as covariates. Results: The first regression model explained 17.2% of the variance in CES-D scores. It was found that the COVID-19 group had significantly higher CES-D scores (ß = .20, p = .03). The second regression model explained 35.9% of the variance in SCD-Q scores. Similar to the previous model, it was found that the COVID-19 group had significantly higher SCD-Q scores compared to healthy controls (ß = .22 p = .01). Lastly, the moderation model indicated that higher CES-D scores were associated with higher SCD-Q scores (ß = .43, p < .01), but there was no statistically significant group X CES-D score interaction. Conclusions: These findings suggest that individuals who previously experienced a mild to moderate symptomatic COVID-19 infection report greater depressive symptom severity as well as greater subjective cognitive decline. Additionally, while more severe depressive symptoms predicted greater subjective cognitive decline in our sample, the magnitude of this association did not vary between those with and without a previous COVID-19 infection. While the underlying neurobiological and social mechanisms of cognitive difficulties and depressive symptoms in persons who have had COVID-19 have yet to be fully elucidated, our findings highlight treatment for depression and cognitive rehabilitation as potentially useful intervention targets for the post COVID-19 condition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".