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Record W3021522778 · doi:10.1136/oem-2019-epi.168

O7B.2 Pilot project for identifying psychosocial risk factors among senior physicians in the pediatric medical center of a university hospital center

2019· article· en· W3021522778 on OpenAlexaffabout
Marie-Agnès Denis, Fabienne Dumetier, Ghislaine Poyard-Berger, Marie-Michèle Mantha-Bélisle, Michel Vézina

Bibliographic record

VenueOccupational and Environmental Medicine · 2019
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsInstitut National de Santé Publique du QuébecInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsPsychosocialThematic analysisContext (archaeology)PsychologyFeelingMedical educationNursingApplied psychologyMedicineFamily medicineQualitative researchSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Context After several warning signals coming from senior physicians working in a Department of pediatrics at a large university hospital, the Department of occupational health decided to assess objectively the psychosocial risks to which this personnel was exposed. Methods A research team from the scientific unit of the Institut National de Santé Publique du Québec has developed an identification grid with markers that help understanding and limiting physical and psychological risks at work. This grid includes characteristics of the workplace environment and various aspects of management practices. It is based on theoretical models such as ‘Demand-Latitude-Support’ (Karasek & Theorell, 1990), ‘effort-reward imbalance’ (Siegrist, 1996), ‘organizational justice’ (Adams, 2000), and ‘prevention’ (Kristensen, 1999). The assessment involved an interview guide with a scoring system of data collected from credible persons familiar with the working environment. After adequate training in the use of the interview guide, an occupational physician and an occupational psychologist interviewed jointly each of 34 pediatricians and 3 managers and scored the 12 items of the guide according to specific recommendations. The data collected from the interviews were submitted to a thematic analysis. Results The analysis showed that the working environment of the Department was not favorable to the return to work or work-life balance. Regarding management, the warning signals pointed to heavy workloads, lack of recognition, and communication problems. There were some protecting factors such as support from colleagues, some decision latitude (but limited possibilities of knowledge development) and, unevenly between wards, support from the hierarchy. The most negative indicators were reported by junior doctors and, as expected, by temporary personnel. Discussion According to these results, group involving the assessment team, pediatricians, and ward managers will be formed to suggest improvements in the fields of human-resource management, communication, recognition, workloads, and occupational health.

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)0.007
metaresearch head score (Gemma)0.003
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 score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.048
GPT teacher head0.391
Teacher spread0.343 · 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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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