Sexual Desire in the Time of COVID-19: How COVID-Related Stressors are Associated with Sexual Desire in Romantic Relationships
Bibliographic record
Abstract
The COVID-19 pandemic and the resulting social distancing measures have caused widespread social and economic disruptions, resulting in spikes in unemployment and financial instability, along with drastic changes to people's ability to feel socially connected. Many of the changes resulting from the COVID-19 pandemic are risk factors for depressive symptoms, which are associated with lower levels of sexual desire. The current research (N = 4,993) examined whether responses to external stressors brought on by COVID-19 (i.e., financial concern, worry, loneliness, stress) were associated with sexual desire among a multi-national sample of people in relationships (Studies 1-2), and whether this association was, in part, due to reports of depressive symptoms (Study 2). In the period immediately following the onset of the pandemic, more financial concern (Study 1) and worry (Study 2) were associated with higher sexual desire, while other factors, like stress (Studies 1-2), were associated with lower desire. We also followed a subset of participants every two weeks during the initial stages of the pandemic and at times when people reported greater stress, loneliness, financial strain, or worry than their average, they reported greater depressive symptoms, which, was in turn, associated with lower sexual desire. Results suggest that the social isolation and stress resulting from the COVID-19 pandemic has mixed associations with sexual desire at the onset of the pandemic. But over time, when people report heightened COVID-related stressors, they tend to report lower sexual desire for their partner, in part because these stressors are associated with more depressive symptoms.
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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 | 0.009 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".