MétaCan
Menu
Back to cohort
Record W2889674800 · doi:10.1177/1043454218794881

The Social Determinants of Nursing Retention in a Pediatric Hematology/Oncology Unit

2018· article· en· W2889674800 on OpenAlexaff
Paula Mahon

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPediatric oncologyAttritionDiversity (politics)NursingMedicineHealth carePsychologyJob satisfactionUnit (ring theory)Family medicineMedical educationInternal medicineSocial psychology

Abstract

fetched live from OpenAlex

Pediatric hematology/oncology units (PHOUs) are highly paced, stressful environments and can be difficult areas to work. Thus, these units can present issues when it comes to both recruiting and retaining health care professionals (HCPs). There is scant research addressing how the environment of a PHOU contribute to a HCP's desire to stay or leave this environment. To conduct this project, a critical ethnographic approach was used. The researcher conducted semistructured interviews ( n = 29), which included nurses ( n = 21), physicians ( n = 4), and allied health care staff ( n = 4). This sample represented approximately one third of staff in each category. Participants identified that their ability to develop long-term relationships with children and families as a significant source of satisfaction. Belonging to the oncology team was seen as extraordinarily important to all the participants. The majority of the participants also felt that working in this ever-evolving dynamic medical field afforded them with ongoing learning opportunities. The main frustration described by participants pertained to administrative involvement in the everyday workings of the PHOU, potentially leading to attrition. It is important to note that there was also diversity among and between the categories of HCPs when describing the work environment and the issues that most influence them. While similarities among participants were found between satisfaction and dissatisfaction, significant differences between them led us to believe it would be unreasonable to attempt to compare the three groups here. Thus, in this article the author focused primarily on nursing while noting related observations from physicians and allied health professions.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.177
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.076
GPT teacher head0.439
Teacher spread0.364 · 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 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

Citations9
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pediatric Oncology NursingSame topicChildhood Cancer Survivors' Quality of LifeFrench-language works237,207