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Burnout prevalence in medical and radiation oncologists at British Columbia Cancer Agency (BCCA).

2012· article· en· W2601732916 on OpenAlexaffabout
Catherine A. Fitzgerald, Lyly Le, David Petrik, Kevin Murphy

Bibliographic record

VenueJournal of Clinical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsBurnoutMedicineDepersonalizationEmotional exhaustionWorkloadDistressFamily medicineClinical psychology

Abstract

fetched live from OpenAlex

6071 Background: Burnout, reported to affect 30-60% of oncology workers, is a syndrome of psychological distress typically manifesting in three dimensions: Emotional Exhaustion (EE), Depersonalization (DP) and Low Personal Accomplishment (PA). Causal factors include workload, dealing with terminally ill patients and difficulties maintaining a balance between professional and personal life. As workload rises due to increased complexity of therapy and increasing prevalence of cancer patients, burnout may increase, especially in times of financial constraint. We sought to determine the prevalence of burnout in medical and radiation oncologists working at BCCA, which provides all radiation and the majority of medical oncology services to BC’s 4.5 million people. Methods: In March 2011, BCCA oncologists were invited to participate in a confidential online survey consisting of basic demographics and the 22 item MasLach Burnout Inventory (MBI) instrument, the latter a validated tool measuring distress in the three main dimensions of burnout. Normative data for physicians were used to interpret the results. Results: Response rate was 59%, female:male 40:60% with similar response rates for medical and radiation oncology (60 v 59%). Of the 73 who indicated their age range, 34 (47%) were between 35 and 44 years old. Respondents indicated that they had considered reducing their Full Time Equivalent (FTE) (67%) or leaving BC (46%). In those with at least 2 scores at a severe level, these rates were 76% and 71% respectively. Conclusions: Over 60% of responding BCCA oncologists report burnout in at least one domain of the MBI tool. Many have considered leaving the province or reducing their hours. These data are consistent with Grunfeld’s survey of Ontario oncologists (CMAJ 2000), although the rate of burnout is higher in this survey. Further research into ways to lessen burnout in oncology is urgently needed. [Table: see text]

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)0.002
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 score0.295
Threshold uncertainty score0.594

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.065
GPT teacher head0.517
Teacher spread0.452 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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