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Record W1940443344 · doi:10.2196/resprot.3715

Patient-Centered mHealth Living Donor Transplant Education Program for African Americans: Development and Analysis

2015· article· en· W1940443344 on OpenAlexvenueno aff
John C. Sieverdes, Lynne S. Nemeth, Gayenell Magwood, Prabhakar K. Baliga, Brenda Brunner-Jackson, Sachin Patel, Kenneth J. Ruggiero, Frank A. Treiber

Bibliographic record

VenueJMIR Research Protocols · 2015
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthMedical University of South Carolina
KeywordsFocus groupmHealthMedicineDonationEthnic groupSession (web analytics)Formative assessmentTelemedicineMedical educationFamily medicineGerontologyNursingPsychologyHealth carePsychological interventionPedagogySociology

Abstract

fetched live from OpenAlex

BACKGROUND: There is a critical need to expand the pool of available kidneys for African Americans who are on the transplant wait-list due to the disproportionally lower availability of deceased donor kidneys compared with other races/ethnic groups. Encouraging living donation is one method to fill this need. Incorporating mHealth strategies may be a way to deliver educational and supportive services to African American transplant-eligible patients and improve reach to those living in remote areas or unable to attend traditional group-session-based programs. Before program development, it is essential to perform formative research with target populations to determine acceptability and cultivate a patient-centered and culturally relevant approach to be used for program development. OBJECTIVE: The objectives of this study were to investigate African American kidney transplant recipients' and kidney donors'/potential donors' attitudes and perceptions toward mobile technology and its viability in an mHealth program aimed at educating patients about the process of living kidney donation. METHODS: Using frameworks from the technology acceptance model and self-determination theory, 9 focus groups (n=57) were administered to African Americans at a southeastern medical center, which included deceased/living donor kidney recipients and living donors/potential donors. After a demonstration of a tablet-based video education session and explanation of a group-based videoconferencing session, focus groups examined members' perceptions about how educational messages should be presented on topics pertaining to the process of living kidney donation and the transplantation. Questionnaires were administered on technology use and perceptions of the potential program communication platform. Transcripts were coded and themes were examined using NVivo 10 software. RESULTS: Qualitative findings found 5 major themes common among all participants. These included the following: (1) strong support for mobile technology use; (2) different media formats were preferred; (3) willingness to engage in video chats, but face-to-face interaction sometimes preferred; (4) media needs to be user friendly; (5) high prevalence of technology access. Our results show that recipients were willing to spend more time on education than the donors group, they wanted to build conversation skills to approach others, and preferred getting information from many sources, whereas the donor group wanted to hear from other living donors. The questionnaires revealed 85% or more of the sample scored 4+ on a 5-point Likert scale, which indicates high degree of interest to use the proposed program, belief that other mHealth technologies would help with adherence to medical regimens, and doctors would make regimen adjustments quicker. In addition, high utilization of mobile technology was reported; 71.9% of the participants had a mobile phone and 43.9% had a tablet. CONCLUSIONS: Our study supports the use of an mHealth education platform for African Americans to learn about living donation. However, potential recipients and potential donors have differing needs, and therefore, programs should be tailored to each target audience.

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: Other design · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.844
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.214
GPT teacher head0.525
Teacher spread0.311 · 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 designOther design
Domainnot available
GenreProtocol

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

Citations28
Published2015
Admission routes1
Has abstractyes

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