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Record W4307426597 · doi:10.2196/40546

Evaluating Health Care Provider Perspectives on the Use of Mobile Apps to Support Patients With Heart Failure Management: Qualitative Descriptive Study

2022· article· en· W4307426597 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJMIR Cardio · 2022
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSinai Health SystemUniversity of TorontoToronto Metropolitan UniversityOntario Tech University
Fundersnot available
KeywordsMedicineDescriptive statisticsQualitative researchNursingHealth careMobile technologyMobile appsMedical educationMobile devicePsychologyWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Nonadherence to diet and medical therapies in heart failure (HF) contributes to poor HF outcomes. Mobile apps may be a promising way to improve adherence because they increase knowledge and behavior change via education and monitoring. Well-designed apps with input from health care providers (HCPs) can lead to successful adoption of such apps in practice. However, little is known about HCPs' perspectives on the use of mobile apps to support HF management. OBJECTIVE: The aim of this study is to determine HCPs' perspectives (needs, motivations, and challenges) on the use of mobile apps to support patients with HF management. METHODS: A qualitative descriptive study using one-on-one semistructured interviews, informed by the diffusion of innovation theory, was conducted among HF HCPs, including cardiologists, nurses, and nurse practitioners. Transcripts were independently coded by 2 researchers and analyzed using content analysis. RESULTS: The 21 HCPs (cardiologists: n=8, 38%; nurses: n=6, 29%; and nurse practitioners: n=7, 33%) identified challenges and opportunities for app adoption across 5 themes: participant-perceived factors that affect app adoption-these include patient age, technology savviness, technology access, and ease of use; improved delivery of care-apps can support remote care; collect, share, and assess health information; identify adverse events; prevent hospitalizations; and limit clinic visits; facilitating patient engagement in care-apps can provide feedback and reinforcement, facilitate connection and communication between patients and their HCPs, support monitoring, and track self-care; providing patient support through education-apps can provide HF-related information (ie, diet and medications); and participant views on app features for their patients-HCPs felt that useful apps would have reminders and alarms and participative elements (gamification, food scanner, and quizzes). CONCLUSIONS: HCPs had positive views on the use of mobile apps to support patients with HF management. These findings can inform effective development and implementation strategies of HF management apps in clinical practice.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.597

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 head0.083
GPT teacher head0.389
Teacher spread0.306 · 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