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Record W4281259576 · doi:10.1016/j.xkme.2022.100486

Living Kidney Donation Stories and Advice Shared Through a Digital Storytelling Library: A Qualitative Thematic Analysis

2022· article· en· W4281259576 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueKidney Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
FundersHealth Resources and Services Administration
KeywordsThematic analysisDonationPsychological interventionStorytellingMedicineNarrativeQualitative researchPsychologyNursingMedical educationFamily medicineSociologyPolitical science

Abstract

fetched live from OpenAlex

Rationale & Objective: Despite the development of numerous educational interventions, there has been limited change in actual living donor kidney transplant (LDKT) rates over time. New strategies, such as the inclusion of patient stories in patient education, show promise to inspire more people to donate kidneys. This study identified the challenges faced, coping strategies used, and advice shared by transplant donors and recipients. Study Design: Qualitative thematic analysis. Setting & Participants: One hundred eighteen storytellers across the United States and Canada, including 82 living donors and 36 kidney recipients of living donor transplants who shared their stories on the Living Donation Storytelling Project (explorelivingdonation.org), an online digital storytelling platform and library. Analytical Approach: A poststorytelling survey assessed participant demographics. Two coders conducted tool-assisted (Dedoose v.8.3.35) thematic analysis on narrative storytelling videos and transcripts. Results: Storytellers were predominantly White (79/118, 66.95%), female (76/118, 64.41%), and non-Hispanic (109/118, 92.37%) with college/vocational education (50/118, 42.37%). Common themes were found related to living donation challenges for donors and recipients (eg, the fear of not being able to complete the LDKT process, of unsupportive family or rejected donation requests, and of unknown or adverse surgical outcomes and graft rejection) and recommended coping strategies (eg, seeking LDKT information, using prayer, and relying on a support network). Recipients provided advice that included being proactive and staying hopeful, whereas donors recommended seeking support, researching LDKT to comprehensively learn, and building a community of support. Limitations: Limited representation of diverse demographics. Conclusions: Although supplementary to traditional education about LDKT, digital storytelling provides a source of peer support that can enhance the experience of donors and recipients and encourage autonomy and self-management after transplant.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.311
Teacher spread0.284 · 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