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Record W4313339752 · doi:10.1097/tp.0000000000004477

Caregiver Burden in Adult Solid Organ Transplantation

2022· article· en· W4313339752 on OpenAlexaff
Lisa X. Deng, Arjun D. Sharma, Seren M. Gedallovich, Puneeta Tandon, Lissi Hansen, Jennifer C. Lai

Bibliographic record

VenueTransplantation · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily Caregiving in Mental Illness
Canadian institutionsUniversity of Alberta
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingNational Institutes of Health
KeywordsCaregiver burdenPsychological interventionDyadTransplantationMindfulnessMedicinePsychologyGerontologyNursingClinical psychologyDiseaseDevelopmental psychology

Abstract

fetched live from OpenAlex

The informal caregiver plays a critical role in supporting patients with various end-stage diseases throughout the solid organ transplantation journey. Caregiver responsibilities include assistance with activities of daily living, medication management, implementation of highly specialized treatments, transportation to appointments and treatments, and health care coordination and navigation. The demanding nature of these tasks has profound impacts across multiple domains of the caregiver's life: physical, psychological, financial, logistical, and social. Few interventions targeting caregiver burden have been empirically evaluated, with the majority focused on education or mindfulness-based stress reduction techniques. Further research is urgently needed to develop and evaluate interventions to improve caregiver burden and outcomes for the patient-caregiver dyad.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.285
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations18
Published2022
Admission routes1
Has abstractyes

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