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Record W4220798022 · doi:10.2196/33152

An mHealth App to Support Caregivers in the Medical Management of Their Child With Cancer: Co-design and User Testing Study

2022· article· en· W4220798022 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Cancer · 2022
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
FundersNational Cancer InstituteNational Science Foundation
KeywordsUsabilitymHealthFocus groupMedicinePediatric cancerNursingPsychologyCancerComputer sciencePsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Caregivers face new challenges and tasks when their child is diagnosed with cancer, which can be overwhelming. Mobile technology has the capacity to provide immediate support at their fingertips to aid in tracking symptoms, managing medication, and planning for emergencies. OBJECTIVE: The objective of this study is to engage directly with end users and proxies to co-design and create a mobile technology app to support caregivers in the medical management of their child with cancer. METHODS: We engaged directly with caregivers of children with cancer and pediatric oncology nurse coordinators (proxy end users) to co-design and create the prototype of the Cope 360 mobile health app. Alpha testing was accomplished by walking the users through a series of predetermined tasks that encompassed all aspects of the app including tracking symptoms, managing medications, and planning or practicing for a medical emergency that required seeking care in the emergency department. Evaluation was accomplished through recorded semistructured interviews and quantitative surveys to capture demographic information and measure the system usability score. Interviews were transcribed and analyzed iteratively using NVivo (version 12; QSR International). RESULTS: This study included 8 caregivers (aged 33-50 years) of children with cancer, with most children receiving chemotherapy, and 6 nurse coordinators, with 3 (50%) of them having 11 to 20 years of nursing experience. The mean system usability score given by caregivers was 89.4 (95% CI 80-98.8). Results were grouped by app function assessed with focus on specific attributes that were well received and those that required refinement. The major issues requiring refinement included clarity in the medical information and terminology, improvement in design of tasks, tracking of symptoms including adjusting the look and feel of certain buttons, and changing the visual graph used to monitor symptoms to include date anchors. CONCLUSIONS: The Cope 360 app was well received by caregivers of children with cancer but requires further refinement for clarity and visual representation. After refinement, testing among caregivers in a real-world environment is needed to finalize the Cope 360 app before its implementation in a randomized controlled trial.

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.

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)0.002
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 score0.052
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.053
GPT teacher head0.381
Teacher spread0.329 · 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