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Record W4407894288 · doi:10.2196/66847

Supporting Medication Adherence in Pediatric Patients Undergoing Hematopoietic Stem Cell Transplant Using the BMT4me mHealth App: Mixed Methods Usability Study

2025· article· en· W4407894288 on OpenAlexvenueno aff
Mariam Kochashvili, Parishma Guttoo, Emre Sezgın, Ahna L. H. Pai, Rajinder Bajwa, Wendy Landier, Cynthia A. Gerhardt, Micah Skeens

Bibliographic record

VenueJMIR Cancer · 2025
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsnot available
FundersNational Institute of Nursing Research
KeywordsUsabilityPreprintmHealthHematopoietic stem cellMedicineMedication adherenceStem cellWorld Wide WebHaematopoiesisInternal medicineComputer scienceOperating systemNursingPsychological interventionBiology

Abstract

fetched live from OpenAlex

Background: Due to multifaceted outpatient regimens, children receiving hematopoietic stem cell transplants (HCTs) are at high risk of medication nonadherence, leading to life-threatening complications. Mobile health (mHealth) interventions have proven effective in improving adherence in various pediatric conditions; however, adherence intervention literature on HCT is limited. Objective: This study aimed to assess the usability of a mHealth intervention (BMT4me) designed to serve as a real-time, personalized tool for medication management or adherence, symptom tracking, and journal keeping. Methods: Following a mixed methods approach, 14 caregivers (n=11, 79% female; n=10, 71% White) of children aged 2-18 (mean age 8.51, SD 5.18) years in the acute phase (first 100 d) post-HCT were recruited. Caregivers were asked to use the BMT4me app for 100 days or until weaning of the immunosuppressant medications to measure usability. The System Usability Scale (assessing functionality and acceptability), reaction cards (assessing desirability), caregiver satisfaction (assessing satisfaction) with the app, and semistructured interviews (assessing participant experience using the app and feedback regarding features) were conducted at two time points, at enrollment and study completion. Results: The mean System Usability Scale score was 86.15 (SD 12.81) at enrollment and 73.13 (SD 16.13) at study completion, with most participants reporting the app easy to use and accepable during both time points. At enrollment, 80% (n=12) of caregivers reported that the app was effective in motivating them to stay on schedule, and 87% (n=13) indicated they would recommend it to others. At study completion, 75% (n=6) of caregivers found the app helpful for tracking their child's medication schedule, and 64% (n=5) would recommend it to others. Caregivers described the app as "accessible," "useful," and "valuable." Qualitative interviews during both time points revealed caregivers' positive reactions to the app, particularly regarding medication reminders, tracking symptoms, and notes features, while also providing suggestions for improvements, such as integrating the BMT4me app with electronic medical records, incorporating educational content, adding fields for recording vital signs, and important phone numbers. Conclusions: The BMT4me app demonstrated promising usability as a mHealth intervention among pediatric patients undergoing HCT. Caregivers considered the app user-friendly and valuable, with positive feedback on its features, such as medication reminders and symptom tracking. Despite minor reported issues with app functionality, the overall acceptance of the app suggests its potential to support families in managing complex treatment. The findings from this study will inform the feasibility of testing in larger randomized controlled trials.

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)0.001
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 score0.019
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.061
GPT teacher head0.438
Teacher spread0.377 · 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

Citations6
Published2025
Admission routes1
Has abstractyes

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