Impact of depressive symptoms on motivation in persons with post-COVID-19 condition
Bibliographic record
Abstract
OBJECTIVE: The World Health Organization (WHO) has defined Post-COVID-19 Condition (PCC) as the onset of symptoms within three months after resolution of an acute SARS-CoV-2 infection, wherein symptoms persist for at least two months and cannot be explained by another medical/psychiatric condition. Persons living with PCC report debilitating symptoms including, but not limited to, depressive symptoms and motivational deficits. The aim of this post-hoc analysis was to evaluate the association between depressive symptoms and motivation in adults with PCC. METHODS: We conducted a post-hoc analysis of an 8-week, double-blind, randomized, placebo-controlled trial evaluating adults (18 years or older) in Canada with WHO-defined PCC and cognitive symptoms. This post-hoc analysis is comprised of baseline data that evaluates the association between depressive symptom severity measured by the 16-item Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR-16) and motivational systems measured by the Behavioral Inhibition System/Behavioral Activation System Questionnaire (BIS/BAS). RESULTS: = 0.196 95% CI [0.061, 0.332], p<0.05). CONCLUSIONS: Depressive symptoms were associated with motivational deficits in persons living with PCC. Optimizing treatment for depressive symptoms may potentially improve aspects of motivational impairment amongst persons with PCC. All patients presenting with MDD and a history of COVID-19 infection should be assessed for the presence of 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".