Reliability and validity of the post COVID-19 condition stigma questionnaire: a prospective cohort study
Bibliographic record
Abstract
Background: Many of the 10-20% percent of COVID-19 survivors who develop Post COVID-19 Condition (PCC, or Long COVID) describe experiences suggestive of stigmatization, a known social determinant of health. Our objective was to develop an instrument, the Post COVID-19 Condition Stigma Questionnaire (PCCSQ), with which to quantify and characterise PCC-related stigma. Methods: We conducted a prospective cohort study to assess the reliability and validity of the PCCSQ. Patients referred to our Post COVID-19 Clinic in the Canadian City of Edmonton, Alberta between May 29, 2021 and May 24, 2022 who met inclusion criteria (attending an academic post COVID-19 clinic; age ≥18 years; persistent symptoms and impairment at ≥ 12 weeks since PCR positive acute COVID-19 infection; English-speaking; internet access; consenting) were invited to complete online questionnaires, including the PCCSQ. Analyses were conducted to estimate the instrument's reliability, construct validity, and association with relevant instruments and defined health outcomes. Findings: Of the 198 patients invited, 145 (73%) met inclusion criteria and completed usable questionnaires. Total Stigma Score (TSS) on the PCCSQ ranged from 40 to 174/200. The mean (SD) was 103.9 (31.3). Cronbach's alpha was 0.97. Test-retest reliability was 0.92. Factor analysis supported a 6-factor latent construct. Subtest reliabilities were >0.75. Individuals reporting increased TSS occurred across all demographic groups. Increased risk categories included women, white ethnicity, and limited educational opportunities. TSS was positively correlated with symptoms, depression, anxiety, loneliness, reduced self-esteem, thoughts of self-harm, post-COVID functional status, frailty, EQ5D5L score, and number of ED visits. It was negatively correlated with perceived social support, 6-min walk distance, and EQ5D5L global rating. Stigma scores were significantly increased among participants reporting employment status as disabled. Interpretation: Our findings suggested that the PCCSQ is a valid, reliable tool with which to estimate PCC-related stigma. It allows for the identification of patients reporting increased stigma and offers insights into their experiences. Funding: The Edmonton Post COVID-19 Clinic is supported by the University of Alberta and Alberta Health Services. No additional sources of funding were involved in the execution of this research study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".