Cognitive and Emotional Disturbances Due to COVID-19: An Exploratory Study in the Rehabilitation Setting
Bibliographic record
Abstract
The coronavirus disease 19 (COVID-19) can cause neurological, psychiatric, psychological, and psychosocial impairments. Literature regarding cognitive impact of COVID-19 is still limited. The aim of this study was to evaluate cognitive deficits and emotional distress among COVID-19 and post–COVID-19 patients who required functional rehabilitation. Specifically, this study explored and compared cognitive and psychological status of patients in the subacute phase of the disease (COVID-19 group) and patients in the postillness period (post–COVID-19 group). Forty patients admitted to rehabilitation units were enrolled in the study and divided into two groups according to the phase of the disease: (a) COVID-19 group (n= 20) and (b) post–COVID-19 group (n= 20). All patients underwent a neuropsychological assessment including Mini-Mental State Evaluation (MMSE), Montreal Cognitive Assessment (MoCA), Hamilton Rating Scale for Depression, and Impact of Event Scale–Revised (IES-R). A larger part of the COVID group showed neuropsychological deficits in the total MMSE (35%) compared to the post-COVID group (5%), whereas the majority of both groups (75–70%) reported cognitive impairments in the total MoCA. The post-COVID group reported significantly higher score in MMSE subtests of language (p= 0.02) and in MoCA subtests of executive functions (p= 0.05), language (p= 0.01), and abstraction (p= 0.02) compared to the COVID group. Regarding emotional disturbances, ~40% of patients presented with mild to moderate depression (57.9–60%). The post–COVID-19 group reported significantly higher levels of distress at the IES-R compared to the COVID group (p= 0.02). These findings highlight the gravity of neuropsychological and psychological symptoms that can be induced by COVID-19 infection and the need for tailored rehabilitation, including cognitive training and psychological support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".