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Record W3081865341 · doi:10.14740/ijcp399

Work Engagement as a Measure of Wellness in Pediatric Hospital Medicine

2020· article· en· W3081865341 on OpenAlexvenueno aff
Elise Peterson Lu, Kathryn Leyens, Tony Tarchichi, Sylvia Choi, Sara C. McIntire, Andrew McCormick

Bibliographic record

VenueInternational Journal of Clinical Pediatrics · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsBurnoutWork engagementMedicinePsychological interventionScale (ratio)Family medicineNursingClinical psychologyWork (physics)

Abstract

fetched live from OpenAlex

Background: Literature on wellness in pediatrics is limited and there are no published data specific to pediatric hospital medicine (PHM). Existing literature on wellness focuses largely on physician burnout, but wellness also includes positive traits like work engagement. We sought to assess work engagement and burnout in pediatric hospitalists nationwide. Methods: The study utilized a survey including demographic data, the Utrecht Work Engagement Scale (UWES-17), and the Mini-Z burnout measure. The survey recruited participants via the American Academy of Pediatrics Section on Hospital Medicine Listserv. Results: Totally, 432 of 3,085 (14%) respondents completed the survey with mean total UWES score of 4.36 and 36% reported burnout. As expected, higher work engagement scores correlated with decreased rates of burnout (P < 0.0005). Interestingly, work engagement varied by gender and career stage, with lowest scores found in women in early to mid-career (P < 0.05). Conclusions: In this study we evaluated the wellness of pediatric hospitalists, a group that has not been previously studied, using a combination of burnout and work engagement measures which, while validated, had not been previously used to evaluate physician wellness. This study suggests that wellness interventions could be most effective if targeting women in early to mid-career. Further study is needed to determine causes of decreased work engagement and consider appropriate interventions. Int J Clin Pediatr. 2020;9(4):105-109 doi: https://doi.org/10.14740/ijcp399

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)0.006
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.176
GPT teacher head0.526
Teacher spread0.350 · 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.

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

Citations4
Published2020
Admission routes1
Has abstractyes

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