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Association of demographic, career, and lifestyle factors with resilience and association of resilience with mental health outcomes in veterinarians in Canada

2020· article· en· W3096781555 on OpenAlex
Jennifer L. Perret, Colleen O. Best, Jason B. Coe, Amy L. Greer, Deep K. Khosa, Andria Jones‐Bitton

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of the American Veterinary Medical Association · 2020
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBurnoutMental healthClinical psychologyPsychological resilienceMedicineAssociation (psychology)AnxietyMultilevel modelPsychologyPerceived Stress ScaleScale (ratio)PsychiatryStress (linguistics)

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the association of demographic, career, and lifestyle factors with resilience and the association of resilience with mental health outcomes in Canadian veterinarians. SAMPLE: 1,130 veterinarians in clinical practice across Canada. PROCEDURES: An online questionnaire was used to collect participant data and included 5 validated psychometric scales to evaluate resilience (through the Connor-Davidson Resilience Scale [CD-RISC]), perceived stress (through the Perceived Stress Scale), emotional distress (through the Hospital Anxiety and Depression Scale), burnout (through the Maslach Burnout Inventory), and secondary traumatic stress (through the Professional Quality of Life Scale). A multivariable linear regression model was used to investigate associations between CD-RISC scores and demographic, career, and lifestyle characteristics. Univariable linear regression models were used to assess the relationship between resilience scores and other mental health outcomes. RESULTS: The strongest positive association was between CD-RISC score and overall health. The level of satisfaction with support from friends and workplace resources had positive associations with the CD-RISC score. The presence of mental illness had the strongest negative association with the CD-RISC score. Being married, working in a small animal practice, or having an associate role were negatively associated with the CD-RISC score. The CD-RISC score had negative associations with scores for perceived stress, anxiety, depression, burnout, and secondary traumatic stress. CONCLUSIONS AND CLINICAL RELEVANCE: Models provided evidence for the role of resilience in protecting against negative mental health outcomes in veterinarians. Both personal and workplace factors were associated with resilience, presenting opportunities for intervention at each of these levels.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.057
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
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 science0.0000.000
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 head0.055
GPT teacher head0.375
Teacher spread0.320 · 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