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Purpose of this sheet

This short guide gives prospective NextGen IACC Scholars enough information to propose a thoughtful research direction. It is not the complete SC4D data dictionary or codebook, and applicants are not expected to know the full dataset before applying.

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What is SC4D?

Symptom Cluster Characterization in Complex Chronic Disease (SC4D)—also known as the Chronic Illness Survey Adventure—is a large, patient-centered, questionnaire-based study designed to characterize symptoms, function, diagnoses, and illness experience across infection-associated chronic conditions (IACCs).

The dataset contains approximately 1.5 million data points from more than 2,200 adult respondents who completed a multi-section survey. Respondents include people reporting clinical diagnoses of myalgic encephalomyelitis, Long COVID, postural orthostatic tachycardia syndrome (POTS), mast cell activation syndrome/disease (MCAS/MCAD), or hypermobile Ehlers-Danlos syndrome or other hypermobility disorders, and healthy controls.

Data collection is complete. The dataset has been cleaned and de-identified and will be accessed through C-BIG, an approved, secure data platform.

Study design applicants should understand:

SC4D is an observational, participant-reported survey dataset. It is well suited to symptom characterization, functional-impact analyses, subgroup comparisons, exploratory phenotype development, measurement work, and hypothesis generation.

SC4D does not contain laboratory biomarkers, biospecimens, genomic data, treatment assignments, or prospectively collected clinical outcomes. Associations in SC4D generally cannot establish causation.

Participants were recruited through community, clinician, and partner-organization outreach. Relevant diagnoses are primarily based on participant report of a clinical diagnosis. The survey also includes symptom-based items that may support exploratory classification against operationalized diagnostic criteria, but these classifications should not automatically be treated as independently validated clinical diagnoses.

Broad information available

The final availability and coding of every variable must be confirmed in the data dictionary. Broad domains represented in SC4D include:

• Reported IACC and non-IACC diagnoses and comorbidities, including rare diseases and disorders;
• Illness onset, possible onset-related events, time since onset, and COVID-19 history;
• Symptom presence, frequency, severity, and functional impact across multiple body systems;
• Post-exertional symptom worsening following physical or cognitive activity;
• Fatigue and energy impact;
• Pain distribution and severity;
• Sleep and unrefreshing sleep experiences;
• Cognitive, neurological, sensory, and sensory-reactivity symptoms;
• Autonomic, orthostatic, circulatory, heart-rate, and blood-pressure-related symptoms or diagnoses;