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Record W2606719182 · doi:10.2196/resprot.6198

Mobile Application to Promote Adherence to Oral Chemotherapy and Symptom Management: A Protocol for Design and Development

2017· article· en· W2606719182 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 Research Protocols · 2017
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsnot available
FundersPatient-Centered Outcomes Research Institute
KeywordsMedicineChemotherapyIntervention (counseling)Protocol (science)Intensive care medicineUsabilityPhysical therapyAlternative medicineSurgeryNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Oral chemotherapy is increasingly used in place of traditional intravenous chemotherapy to treat patients with cancer. While oral chemotherapy includes benefits such as ease of administration, convenience, and minimization of invasive infusions, patients receive less oversight, support, and symptom monitoring from clinicians. Additionally, adherence is a well-documented challenge for patients with cancer prescribed oral chemotherapy regimens. With the ever-growing presence of smartphones and potential for efficacious behavioral intervention technology, we created a mobile health intervention for medication and symptom management. OBJECTIVE: The objective of this study was to develop and evaluate the usability and acceptability of a smartphone app to support adherence to oral chemotherapy and symptom management in patients with cancer. METHODS: We used a 5-step development model to create a comprehensive mobile app with theoretically informed content. The research and technical development team worked together to develop and iteratively test the app. In addition to the research team, key stakeholders including patients and family members, oncology clinicians, health care representatives, and practice administrators contributed to the content refinement of the intervention. Patient and family members also participated in alpha and beta testing of the final prototype to assess usability and acceptability before we began the randomized controlled trial. RESULTS: We incorporated app components based on the stakeholder feedback we received in focus groups and alpha and beta testing. App components included medication reminders, self-reporting of medication adherence and symptoms, an education library including nutritional information, Fitbit integration, social networking resources, and individually tailored symptom management feedback. We are conducting a randomized controlled trial to determine the effectiveness of the app in improving adherence to oral chemotherapy, quality of life, and burden of symptoms and side effects. At every stage in this trial, we are engaging stakeholders to solicit feedback on our progress and next steps. CONCLUSIONS: To our knowledge, we are the first to describe the development of an app designed for people taking oral chemotherapy. The app addresses many concerns with oral chemotherapy, such as medication adherence and symptom management. Soliciting feedback from stakeholders with broad perspectives and expertise ensured that the app was acceptable and potentially beneficial for patients, caregivers, and clinicians. In our development process, we instantiated 7 of the 8 best practices proposed in a recent review of mobile health app development. Our process demonstrated the importance of effective communication between research groups and technical teams, as well as meticulous planning of technical specifications before development begins. Future efforts should consider incorporating other proven strategies in software, such as gamification, to bolster the impact of mobile health apps. Forthcoming results from our randomized controlled trial will provide key data on the effectiveness of this app in improving medication adherence and symptom management. TRIAL REGISTRATION: ClinicalTrials.gov NCT02157519; https://clinicaltrials.gov/ct2/show/NCT02157519 (Archived by WebCite at http://www.webcitation.org/6prj3xfKA).

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.961
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.373
GPT teacher head0.594
Teacher spread0.221 · 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