Relationship between anhedonia and psychosocial functioning in post-COVID-19 condition: a <i>post-hoc</i> analysis
Bibliographic record
Abstract
BACKGROUND: Post-COVID-19 condition (PCC), also known as "long COVID," is characterized by persistent symptoms, negatively affecting the well-being of individuals with PCC. Anhedonia (i.e. reduced capacity for pleasure) and compromised psychosocial functioning are notable symptoms in those with PCC. We aimed to provide insights to understand the effects of anhedonia and impaired psychosocial functioning of individuals with PCC. METHODS: This post-hoc analysis used data from an 8-week, double-blind, randomized, placebo-controlled trial which evaluated vortioxetine for cognitive deficits in individuals with PCC (Clinicaltrials.gov Identifier: NCT05047952). A total of 147 eligible participants were randomly assigned to receive vortioxetine or matching placebo over eight weeks of double-blind treatment. Our study investigated the relationship between anhedonia, assessed by the Snaith-Hamilton Pleasure Scale (SHAPS), and psychosocial functioning, measured with the Post-COVID Functional Status (PCFS) scale. The analysis was conducted using a generalized linear model, with adjustments for relevant covariates such as age, sex, education, suspected versus confirmed COVID diagnosis, MDD diagnosis, and alcohol consumption. RESULTS: = 0.045, 95% CI). DISCUSSIONS: Our analysis revealed a significant relationship between measures of anhedonia and psychosocial functioning in adults with PCC. Strategies that aim to improve patient-reported outcomes with PCC need to prioritize the prevention and treatment of hedonic disturbances in patients experiencing PCC.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".