The psychological impact of fertility treatment suspensions during the COVID-19 pandemic
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To examine the psychological impact of fertility treatment suspensions resulting from the COVID-19 pandemic and to clarify psychosocial predictors of better or worse mental health. METHODS: 92 women from Canada and the United States (ages 20-45 years) whose fertility treatments had been cancelled were recruited via social media. Participants completed a battery of questionnaires assessing depressive symptoms, perceived mental health impact, and change in quality of life related to treatment suspensions. Potential predictors of psychological outcomes were also examined, including several personality traits, aspects of social support, illness cognitions, and coping strategies. RESULTS: 52% of respondents endorsed clinical levels of depressive symptoms. On a 7-point scale, participants endorsed a significant decline in overall quality of life (M(SD) = -1.3(1.3), p < .0001) as well as a significant decline in mental health related to treatment suspensions on a scale from -5 to +5 (M(SD) = -2.1(2.1), p < .001). Several psychosocial variables were found to positively influence these outcomes: lower levels of defensive pessimism (r = -.25, p < .05), greater infertility acceptance (r = .51, p < .0001), better quality social support (r = .31, p < .01), more social support seeking (r = .35, p < .001) and less avoidance of infertility reminders (r = -.23, p = .029). CONCLUSION: Fertility treatment suspensions have had a considerable negative impact on women's mental health and quality of life. However, these findings point to several protective psychosocial factors that can be fostered in the future to help women cope.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it