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Record W4417015871 · doi:10.1182/blood-2025-4366

A pilot study evaluating the feasibility and usability of an mHealth application: SCD warrior

2025· article· en· W4417015871 on OpenAlexaff
Nancy Asomaning, Mingjie Xu, Ingrid Frey, Raquel Andres

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsmHealthUsabilityLife expectancyDiseaseDigital healthDisease managementChronic diseaseMEDLINE

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Sickle cell disease (SCD) is an inherited blood disorder that affects over 7 million individuals worldwide, including an estimated 100,000 in the US. Since the late 20th century, the survival rates for patients with sickle cell disease (SCD) in high-income countries have significantly improved. Previously referred to as a “disease of childhood,” it is now estimated that 94-99% of individuals with HbSS live into adulthood although life expectancy for SCD patients remains 20-30 years shorter than that of the general population. Adults with SCD, however, continue to suffer from pain - acute and chronic – in addition to fatigue compounded by multiple organ complications. Effective self-care and self-management are essential for managing and mitigating complications in chronic conditions such as SCD. Digital health technologies, including wearables and mobile health (mHealth) applications, have gained signification attention in recent years as potential solutions to improve the management of chronic conditions such as SCD. Specifically, they have been shown to improve patient-driven disease tracking and management, thereby enhancing self-care. Here, we conducted a pilot study to evaluate the feasibility and usability of SCD Warrior, an mHealth application, in helping individuals with SCD manage their disease. METHODS Eleven SCD (HbSS, mean age 44 years [28-60 years], 7 male) patients of African descent, enrolled under the IRB-approved protocol NCT04610866 at the NIH Clinical Center, participated in the study. After obtaining informed consent, participants were trained and onboarded onto the SCD Warrior application (SWA). They were instructed to use SWA daily (Mon-Fri) for 12 weeks, to record their pain, medication usage, and other lifestyle variables of personal interest. Each participant was linked to a clinician via the provider dashboard, who reviewed participant entries and followed up if necessary. A product feedback questionnaire was administered to each participant at baseline and at the end of the 12-week period. Data was analyzed via Stata (v. 18.5) and a paired t-test and Wilcoxon signed-rank test were used for significance testing. RESULTS Nine (81.8%) of the 11 participants utilized SWA throughout the 12-week study period. The 2 remaining subjects did not submit any entries to SWA once enrolled and were considered lost to follow up. All 9 active subjects were adherent (logging medication usage or another health factor in SWA at least 4 days each week, over the study period), with a mean daily adherence rate of 89.9% (SD = 15.3%). The mean application satisfaction score rose from 7.1 (SD=2.70) to 7.7 (SD=1.49) over the study (t=0.970, p value =0.357) period. There was a significant (z=-2.041, p-value=0.0412) change in the mean number of features participants found useful in SWA, with the mean increasing from 2.8 at baseline to 4.3 at the end of the 12-week study period. At baseline, 77.8% (7/9) of participants found the application useful for tracking their medications, 55.6% (5/9) for messaging their care team, and 44.4% (4/9) for tracking their sickle cell-related pain. By the end of the 12-week study period, these percentages increased to 88.8% (8/9), 66.7% (6/9), and 66.7% (6/9), respectively. Most subjects (77.8%, 7/9) agreed that SWA was easy to integrate into their daily and weekly routine and that the logging features were quick and easy to complete. Five of the 9 (55.6%) of the participants agreed that using SWA encouraged them to take better care of their health. Suggestions for improving SWA included integrating more educational information about SCD and better guidance for self-care into the application. CONCLUSIONS SWA was well-received by study participants, achieving an 89.9% adherence rate over 12 weeks. Positive feedback on ease of use, safe-care management, and integration into daily routines indicates that SWA is feasible and useful for managing SCD. However, future improvements should include more educational content on SCD and enhanced self-care features. Overall, SWA shows potential as an effective mHealth tool for health management in individuals with SCD.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.054
GPT teacher head0.379
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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