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Record W2940847638 · doi:10.2196/13452

A Multidimensional Electronic Hydroxyurea Adherence Intervention for Children With Sickle Cell Disease: Single-Arm Before-After Study

2019· article· en· W2940847638 on OpenAlexvenueno aff
Susan E. Creary, Deena J. Chisolm, Joseph Stanek, Jane S. Hankins, Sarah H. O’Brien

Bibliographic record

VenueJMIR mhealth and uhealth · 2019
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsMedicineIntervention (counseling)PharmacyMedication adherenceMedical recordDirectly Observed TherapyDiseaseSickle cell anemiaInternal medicinePhysical therapyPediatricsFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Hydroxyurea is a disease-modifying medication for patients with sickle cell disease (SCD). Despite demonstrated efficacy, hydroxyurea nonadherence in clinical practice is common and results in worse health outcomes for nonadherent patients. Mobile Directly Observed Therapy (Mobile DOT) is a pilot-tested, electronic, multidimensional hydroxyurea adherence intervention for children with SCD. Mobile DOT includes sending daily text message reminders to patients to take hydroxyurea, patients recording and sending daily videos that capture their hydroxyurea administrations for the research team to review and track adherence, providing personalized feedback to patients about their adherence, and providing small monetary incentives to patients if they achieve high hydroxyurea adherence. OBJECTIVE: This study aimed to determine if Mobile DOT increases hydroxyurea adherence in children with SCD and to explore its impact on hematologic and clinical outcomes. METHODS: This was a single-arm, 6-month intervention study of patients with SCD on hydroxyurea who were aged ≤19 years and reported having access to an electronic device. Participants' hydroxyurea adherence when they received Mobile DOT was compared with their adherence 6 months before and after receiving Mobile DOT. Participants' medication possession ratio (MPR) was calculated from their pharmacy dispensing records and was used to measure adherence. Laboratory and clinical outcomes were abstracted from participants' electronic medical records. Infrequently hospitalized patients who received at least 160 days of the intervention were considered to be engaged participants. RESULTS: Of 91 patients who were approached, 55 enrolled and 34 engaged with Mobile DOT. The median age of the engaged participants was 10 years (range 2-18.8 years), and 21 (62%, 21/34) participants were male, 28 (82%, 21/34) had hemoglobin SS SCD, and 19 (56%, 19/34) were prescribed hydroxyurea for at least a year before enrollment. With Mobile DOT, engaged participants' median MPR increased from 61.7% to 84.4% (P<.001) and significantly more (67% vs 30%; P=.002) achieved ≥80% hydroxyurea adherence compared with baseline values. Engaged participants' mean fetal hemoglobin (HgbF) levels and mean corpuscular volumes (MCV) improved significantly after 6 months of Mobile DOT (P=.04 and P=.001, respectively), but their adherence, HgbF levels, and MCV returned to baseline values during the 6 months after the intervention. Hospitalizations and the clinical outcomes that were measured occurred infrequently during the study. Nonengagement was associated with being female and having a recent SCD complication. In addition, having insufficient electronic data, being unable to quickly complete Mobile DOT each day, and not perceiving that Mobile DOT was beneficial may have further decreased engagement. CONCLUSIONS: Mobile DOT shows promise as an effective intervention for some children with SCD. Modifications that may improve recruitment, reduce attrition, and increase engagement were identified and could increase the impact that Mobile DOT has on children with SCD. TRIAL REGISTRATION: ClinicalTrials.gov NCT02578017; https://clinicaltrials.gov/ct2/show/NCT02578017.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.299
Teacher spread0.288 · 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 teacher head, 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".

Quick stats

Citations24
Published2019
Admission routes1
Has abstractyes

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