Exploring the temporal relationship between stigma, disease manifestations, and health outcomes in post COVID-19 condition: a longitudinal descriptive study
Bibliographic record
Abstract
Background: Stigma is defined as a deeply discrediting attribute. Post COVID-19 Condition (PCC) is now recognized to be a source of health-related stigma and discrimination capable of negatively impacting the well-being of those affected. Our purpose was to explore the relationship between PCC-related stigma, disease manifestations, and health outcomes over time. Methods: Using previously validated instruments to measure PCC-related stigma, symptoms, depression, quality of life, function, and occupational status, we conducted a longitudinal descriptive study in a cohort of individuals with confirmed PCC between May 12 and August 13, 2023 in the Canadian city of Edmonton. Findings: Ninety-nine consenting participants completed study questionnaires 3-24 months following an initial diagnosis of PCC (enrollment) and again a mean (SD) of 1.6 (0.26) years later (follow-up). Individuals experienced marked variability in study scores over time. Measures of central tendency proved inadequate to detect changes within the cohort. There was minimal attenuation of stigma scores between enrollment and follow-up despite a "return to normal" from earlier pandemic responses: the change in mean stigma score from enrollment to follow-up was -0.2 (p = 0.97). Significant correlations were found between enrollment stigma and symptoms, depression, function, and quality of life measured at follow-up (r = 0.45-0.55). Similar correlations were noted between enrollment stigma and follow-up composite disease manifestation, health outcome, and global well-being scores (r = 0.39-0.54). Multivariate multiple regression demonstrated statistically significant associations between the change in stigma from enrollment to follow-up and symptoms, depression, functional status, and quality of life (B = -0.45 to -0.11). When participants were categorized as "improved stigma at enrollment" vs. "unchanged or worse stigma at enrollment", changes in stigma over time appeared to be predictive of disease manifestations and health outcomes at follow-up (Cohen's d = 0.43-0.77). Interpretation: This study provides insights into the temporal relationship between PCC-related stigma, disease manifestations, and health outcomes and could establish a foundation for screening, prognostication, treatment, and other efforts to mitigate the impact of stigma. Funding: The Long COVID Web is funded by the Canadian Institute of Health Research (CIHR)-Grant #185352.
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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 | 0.003 | 0.002 |
| 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 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".