Psychometric evaluation
fatigue, pain
Psychometric analyses were conducted using data from participants who completed the SIC in the cross-sectional study and a subset of participants from ENSEMBLE2. The psychometric properties evaluated in each study for all SIC items and candidate composite scores are summarized in Table 
Psychometric Properties Assessed in the Cross-sectional Study and ENSEMBLE2 Phase 3 TrialItem-level known-groups(discriminating ability)Composite-level known-groups(discriminating ability)Descriptive statistics for the SIC were computed in the cross-sectional study for COVID-19 signs and symptoms, including for subgroups based on age (< 65 or ≥ 65 years) and comorbidities (0 vs. ≥ 1); response frequency distributions were calculated for each SIC item. Inter-item correlations for the SIC items were computed and examined for expected patterns of relationships.Construct validity of the SIC was assessed in the cross-sectional study by correlational analyses, with the strength and sign of the predicted correlation depending on the expected pattern of relationship for measures addressing similar constructs. SIC fatigue scores were hypothesized to correlate at least moderately with PROMIS-29 fatigue scores, SIC musculoskeletal items to correlate at least moderately with PROMIS-29 physical function scores, and SIC pain items to correlate at least moderately with PROMIS-29 pain scores. Correlation coefficients were interpreted as follows: r ≥ 0.50, large; 0.30 to 0.49, moderate; 0.10 to 0.29, small; and < 0.10, trivial.Known-groups validity (distinguishing among hypothetically different groups) was evaluated in the cross-sectional study and in ENSEMBLE2 via analysis of variance (ANOVA) to compare mean differences in SIC item scores between subgroups: participants reporting no symptoms or mild compared to those reporting moderate or severe on the PGIS; participants with scores in the top one-third of the PROMIS-29 physical function score distribution versus participants in the bottom one-third; and respondents with PROMIS-29 fatigue scores in the top one-third of the distribution versus those in the bottom one-third.A set of candidate SIC composite scores representing different body systems was analyzed in both studies. Candidate scoring algorithms were evaluated with respect to internal consistency reliability and composite-level analyses that paralleled the item-level validity analyses. Although not ideal for the evaluation of symptom measures such as the SIC, Cronbach’s coefficient alpha was calculated to explore the internal consistency of the candidate SIC composite scores.In the ENSEMBLE2 trial, test-retest reliability (reproduction of identical measurements when no change has occurred between testing) was assessed by calculating intraclass correlation coefficients in the subgroup of participants identified as stable by PGIS response (“no symptom,” “mild,” or same response) at Day 1 and Day 2 of their COVID-19 episode [