Impact of Baseline Anxiety on Well-being in People with Post-COVID-19 Condition: A Secondary Analysis
Bibliographic record
Abstract
BACKGROUND: Post-COVID-19 condition (PCC) is associated with a host of psychopathological conditions including prominent anxiety symptoms. However, it is not known what effect anxious symptoms have on measures of well-being in individuals living with PCC. This study aims to evaluate anxiety's association with measures of well-being in people with PCC. METHODS: This is a post hoc analysis utilizing data from a placebo-controlled, randomized, double-blind clinical trial assessing the effect of vortioxetine on cognitive impairment in individuals with PCC (NCT05047952). Baseline data with respect to anxiety and well-being were collected using the Generalized Anxiety Disorder Scale, 7-Item (GAD-7), and the World Health Organization (WHO) Well-Being Index, 5-Item (WHO-5), respectively. A generalized linear model (GLM) analysis on baseline GAD-7 and WHO-5 scores was conducted with age, sex, employment status, education level, previous major depressive disorder (MDD) diagnosis, and confirmed COVID-19 cases as covariates. RESULTS: = <0.001), signifying that increased anxiety had adverse effects on the overall well-being of individuals with PCC. CONCLUSION: Herein, we observed a clinically meaningful level of anxiety in individuals with PCC. We also identified a robust correlation between anxiety in PCC and measures of general well-being. Our results require replication, providing the impetus for recommending screening and targeting anxious symptoms as a tactic to improve general well-being and outcomes in individuals with PCC.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".