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Record W4200052093 · doi:10.3389/fped.2021.807245

The Relationships Amongst Pediatric Nurses' Work Environments, Work Attitudes, and Experiences of Burnout

2021· article· en· W4200052093 on OpenAlex
Laura Buckley, Whitney Berta, Kristin Cleverley, Kimberley Widger

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers in Pediatrics · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsCentre for Addiction and Mental HealthHospital for Sick ChildrenUniversity of Toronto
FundersHospital for Sick Children
KeywordsBurnoutNursingMedicineDepersonalizationHealth careEmotional exhaustionWork (physics)Pediatric hospitalFamily medicineClinical psychologyPediatrics

Abstract

fetched live from OpenAlex

Background: Pediatric nurses care for some of the most vulnerable patients in our healthcare system. Research on health care provider organizational behavior shows that the quality of care nurses provide is directly related to their well-being, influenced by Burnout and job stress, in the workplace. However, most of the research conducted on nursing populations neglects to separately study nurses who care for children. In a resource limited system where health care provider well-being is recognized as a priority, it is important for administrators to understand the environmental and attitudinal work factors most influential to pediatric nurse work outcomes in order to target optimization strategies. The aim of the study was to identify which modifiable work environment factors, e.g., [Incivility, Perceived Organizational Support, Quality of Work-life] make the greatest contribution to the work outcome of Burnout (i.e., Personal Accomplishment, Emotional Exhaustion, Depersonalization) in pediatric nurses. Methods: A cross-sectional survey design was used at a large quaternary care pediatric hospital in Toronto, Canada. We administered a survey to a convenience sample of all registered nurses with >3 months experience in the Pediatric, Cardiac, and Neonatal Intensive Care Units from January 2021–March 2021. Path analysis was used to test our proposed model which was specified a priori based on a review of the literature. Results: 143 nurses completed the survey. Path analysis of the tested model resulted in good fit. Quality of Work-life had the largest direct effect on Work Engagement (β = 0.582, S.E. = 0.111, p < 0.001). Work Engagement had the largest direct effect on Personal Accomplishment (β = 0.68, S.E. = 0.53, p < 0.001). Quality of Work-life had the largest indirect effect on Personal Accomplishment (β = 0.4, S.E. = 0.65, p < 0.001), Emotional Exhaustion (β = −0.33, S.E. = 0.87, p < 0.001), and Depersonalization (β =−0.17, S.E. = 0.41, p = 0.006), respectively. Work Engagement had the largest total effect on Personal Accomplishment (β = 0.68, S.E. = 0.64, p < 0.001) and the third largest total effect on Emotional Exhaustion (β = −0.57, S.E. = 0.83, p < 0.001). Quality of Work-life had the second largest total effect on Work Engagement (β = 0.58, S.E. = 0.11, p < 0.001) indicating that Quality of Work-life is mediated through Work Engagement for its effect on Burnout. Conclusions: Our results indicate work environment and work attitude factors that can provide organizational leadership with a targeted focus to reduce pediatric critical care nurse Burnout, and thus improve provider well-being, in a resource limited system.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.341
Teacher spread0.310 · 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