Specifying sickle cell disease interventions: a study protocol of the Sickle Cell Disease Implementation Consortium (SCDIC)
Bibliographic record
Abstract
BACKGROUND: Sickle cell disease (SCD) is an inherited blood disorder that results in a lifetime of anemia, severe pain, and end-organ damage that can lead to premature mortality. While the SCD field has made major medical advances, much needs to be done to improve the quality of care for people with SCD. This study capitalizes on the Sickle Cell Disease Implementation Consortium (SCDIC), a consortium of eight academic sites aiming to test implementation strategies that could lead to more accelerated application of the NHLBI guidelines for treating SCD. This report documents the process to support the consortium by specifying the interventions being developed. METHODS: This study consists of three steps. The Principal Investigator of each site and two site representatives who are knowledgeable of the intervention (e.g., study coordinator or the person delivering the intervention) will answer an online survey aiming to capture components of the interventions. This survey will be completed by the site representatives three times during the study: during the development of the interventions, after one year of the interventions being implemented, and at the end of this study (after 2 years). A site visit and semi-structured interview (Step 2) in the first year of the process will capture the context of the sites. Step 3 comprises of the development of a framework with the details of the multi-component SCDIC interventions at the sites. DISCUSSION: The outcome of this study, a framework of the SCDIC, will enable accurate replication and extension of published research, facilitating the translation of SCD studies to diverse populations and settings and allowing for theory testing of the effects of the intervention components across studies in different contexts and for different populations. TRIAL REGISTRATION: ClinicalTrial.Gov (# NCT03380351 ). Registered December 21, 2017.
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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 | 0.148 | 0.086 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.043 | 0.013 |
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".