Comparing the Effectiveness of Education Versus Digital Cognitive Behavioral Therapy for Adults With Sickle Cell Disease: Protocol for the Cognitive Behavioral Therapy and Real-time Pain Management Intervention for Sickle Cell via Mobile Applications (CaRISMA) Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Patients with sickle cell disease (SCD) experience significant medical and psychological stressors that affect their mental health, well-being, and disease outcomes. Digital cognitive behavioral therapy (CBT) has been used in other patient populations and has demonstrated clinical benefits. Although evidence-based, nonpharmacological interventions for pain management are widely used in other populations, these treatments have not been well studied in SCD. Currently, there are no adequately powered large-scale clinical trials to evaluate the effectiveness and dissemination potential of behavioral pain management for adults with SCD. Furthermore, some important details regarding behavioral therapies in SCD remain unclear—in particular, what works best for whom and when. OBJECTIVE Our primary goal is to compare the effectiveness of two smartphone–delivered programs for reducing SCD pain symptoms: digital CBT versus pain and SCD education (Education). Our secondary goal is to assess whether baseline depression symptoms moderate the effect of interventions on pain outcomes. We hypothesize that digital CBT will confer greater benefits on pain outcomes and depressive symptoms at 6 months and a greater reduction in health care use (eg, opioid prescriptions or refills or acute care visits) over 12 months. METHODS The CaRISMA (Cognitive Behavioral Therapy and Real-time Pain Management Intervention for Sickle Cell via Mobile Applications) study is a multisite comparative effectiveness trial funded by the Patient-Centered Outcomes Research Institute. CaRISMA is conducted at six clinical academic sites, in partnership with four community-based organizations. CaRISMA will evaluate the effectiveness of two 12-week health coach–supported digital health programs with a total of 350 participants in two groups: CBT (n=175) and Education (n=175). Participants will complete a series of questionnaires at baseline and at 3, 6, and 12 months. The primary outcome will be the change in pain interference between the study arms. We will also evaluate changes in pain intensity, depressive symptoms, other patient-reported outcomes, and health care use as secondary outcomes. We have 80% power to detect a difference of 0.37 SDs between study arms on 6-month changes in the outcomes with 15% expected attrition at 6 months. An exploratory analysis will examine whether baseline depression symptoms moderate the effect of the intervention on pain interference. RESULTS This study will be conducted from March 2021 through February 2022, with results expected to be available in February 2023. CONCLUSIONS Patients with SCD experience significant disease burden, psychosocial stress, and impairment of their quality of life. CaRISMA proposes to leverage digital technology and overcome barriers to the routine use of behavioral treatments for pain and depressive symptoms in the treatment of adults with SCD. The study will provide data on the comparative effectiveness of digital CBT and Education approaches and evaluate the potential for implementing evidence-based behavioral interventions to manage SCD pain. CLINICALTRIAL ClinicalTrials.gov NCT04419168; https://clinicaltrials.gov/ct2/show/NCT04419168. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/29014
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.063 | 0.009 |
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".