47 The Impact of COVID-19 Infection on Objective and Subjective Cognitive Functioning: Resilience as a Protective Factor
Bibliographic record
Abstract
Objective: Growing evidence indicates that COVID-19 infection adversely impacts cognitive functioning, with COVID-19 patients demonstrating high rates of objective and subjective cognitive impairments (Daroische et al., 2020; Miskowiak et al., 2021). Given the prevalence and potentially debilitating nature of post-COVID-19 cognitive symptoms, understanding factors that mitigate the impact of COVID-19 infection on cognitive functioning is paramount to developing interventions that facilitate recovery. Resilience, the ability to cope with and grow from challenges, has been associated with improved cognitive performance in healthy adults and linked to decreased perceived cognitive difficulties in post-COVID-19 patients (Connor & Davidson, 2003; Deng et al., 2018; Jung et al., 2021). However, resilience has not yet been examined as a potential attenuator of the relationship between COVID-19 and either perceived or objective cognitive function. This study aims to investigate the role of resilience as a protective factor against experience of cognitive function difficulties in COVID-19 patients by probing the role of resilience as a moderator of the relationship between COVID-19 diagnosis and cognitive functioning (both perceived and objective). Participants and Methods: Participants (mean age=36.93, 30.10% male) were recruited from British Columbia and Ontario. The sample included 53 adults who had never been diagnosed with COVID-19 and 50 adults diagnosed with symptomatic COVID-19 at least three months prior and not ventilated. Participants completed online questionnaires (n=103) to assess depression (the Center for Epidemiological Studies Depression Scale), anxiety (7-item Generalized Anxiety Disorder Scale), subjective cognitive functioning (The Subjective Cognitive Decline Questionnaire), and resilience (2-item Connor-Davidson Resilience Scale). Participants then completed neuropsychological tests (n=82) measuring attention, processing speed, memory, language, visuospatial skills, and executive function via teleconference, with scores averaged to create a global objective cognition score. Moderated multiple regression was employed to assess the impact of resilience on the relationship between COVID-19 diagnosis and both objective and perceived cognition, controlling for gender, ethnicity, income, age, anxiety, and depression. Results: Average scores in the COVID-19 group exceeded diagnostic cut-offs for clinical depression (M=16.67, SD=10.77) and mild anxiety (M=5.27, SD=4.99), while the control group scored below diagnostic thresholds for depression (M=11.96, SD=9.76) and mild anxiety (M=4.48, SD=5.07). Controlling for sociodemographic and mental health characteristics, COVID-19 diagnosis was not associated with objective global cognitive functioning (b=-.07, se=1.71, p=.624) or subjective cognitive functioning (b=.16, se=1.32, p=.12), nor was resilience associated with objective global cognitive functioning (b=.19, se=1.50, p=.44) or subjective cognitive functioning (b=-.02, se=1.09, p=.89). Conclusions: Findings indicate that COVID-19 patients may be at risk for depression and anxiety. Results of this study fail to support a relationship between COVID-19 and cognitive functioning beyond the impact of sociodemographic and mental health variables. Thus, the role of resilience as a protective factor against COVID-19 related cognitive difficulties could not be fully explored. However, findings should be considered in the context of study limitations, including a small sample size. Future research should employ larger samples to further examine the relationship between COVID-19 infection and cognition, focusing on mental health characteristics and resilience as potential risk and protective factors.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".