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107.8: Developing a coping strategies toolkit for organ and tissue donation coordinators: A quality improvement initiative.

2025· article· en· W4416839521 on OpenAlexaff
Amina Silva

Bibliographic record

VenueTransplantation · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsBrock University
Fundersnot available
KeywordsTissue DonationQuality managementOrgan donationCoping (psychology)MEDLINEQuality (philosophy)

Abstract

fetched live from OpenAlex

Introduction: Organ and tissue donation coordinators, often with backgrounds in acute and critical care (ACC) nursing, face unique workplace stressors in their critical roles. These professionals manage emotionally charged, complex situations, which can lead to significant stress and burnout. Despite the need for effective coping strategies to maintain their well-being, there is a lack of targeted support mechanisms in the field. This quality improvement initiative aims to develop a toolkit designed to enhance coping strategies for organ and tissue donation coordinators, informed by a scoping review focused on ACC RNs due to the scarcity of specific literature on donation coordinators. Method: Multi-phased research consisting of (1) Scoping Review - completed, and (2) Toolkit Development - ongoing. A scoping review was conducted following the JBI methodology, encompassing major databases such as Medline, Embase, CINAHL, Web of Science, and the Cochrane Library. The review focused on coping strategies employed by RNs in ACC settings to manage workplace stressors. A total of 168 documents published between 2003 and 2023 were included, with data analyzed by two independent reviewers. Based on these findings, we are in the process of developing a comprehensive toolkit that integrates evidence-based coping mechanisms identified in the review. This toolkit will be tailored to the unique challenges faced by organ and tissue donation coordinators, incorporating problem-focused, emotion-focused, meaning-focused, and support-seeking approaches. Results: The review identified a range of stressors experienced by RNs, including high workloads, inadequate staffing, insufficient support, and environmental challenges. The coping strategies identified were categorized into problem-focused, emotion-focused, meaning-focused, and support-seeking approaches. Social support and organizational resources were key facilitators of effective coping, while workload pressures and lack of institutional support acted as barriers. The development of the toolkit is underway, and it will include practical tools for stress management, organizational support strategies, and methods to foster a supportive work environment. Conclusion: The toolkit, once developed and implemented, aims to significantly reduce burnout, enhance job satisfaction, and improve overall performance among organ and tissue donation coordinators. By providing evidence-based coping mechanisms and fostering a supportive organizational culture, the initiative will contribute to better outcomes in organ and tissue donation processes and promote the well-being of professionals dedicated to this critical work. This quality improvement strategy has the potential to impact the field by addressing the unique challenges faced by donation coordinators and offering targeted support for their well-being.

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)0.144
metaresearch head score (Gemma)0.156
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.144
Threshold uncertainty score0.759

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1440.156
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0090.008
Science and technology studies0.0030.002
Scholarly communication0.0080.008
Open science0.0060.012
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0070.003

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 head0.034
GPT teacher head0.317
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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