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Record W2588968568 · doi:10.3138/jvme.0116-006r

An Exploration of the Relationship between Psychological Capital and Depression among First-Year Doctor of Veterinary Medicine Students

2017· article· en· W2588968568 on OpenAlexvenueno aff
Dorothy Bakker, Seán Lyons, Peter Conlon

Bibliographic record

VenueJournal of Veterinary Medical Education · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsOptimismDepression (economics)Psychological interventionTypologyPsychological resiliencePsychologyMental healthClinical psychologyMedical educationMedicinePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

This study examined the impact of psychological capital on depressive symptoms among Doctor of Veterinary Medicine (DVM) students (n=84) over their first two semesters of studies. Our results indicated elevated rates of depression in both the first and second semesters relative to published norms. Using the typology developed by Hafen, Reisbig, White, and Rush (2008), students were classified as either "adaptive" (i.e., improving depressive symptomatology from semester to semester) or "struggling" (i.e., worsening depressive symptomatology from semester to semester). All four components of psychological capital (i.e., self-esteem, optimism, hope, and resilience) were positively associated with adaptive response to depression. These results are significant, as the components of psychological capital can be learned and strengthened through deliberate interventions, providing tangible guidance for students, faculty, and health professionals in their efforts to improve student wellness.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.009
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.367
GPT teacher head0.583
Teacher spread0.215 · 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.

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

Citations55
Published2017
Admission routes1
Has abstractyes

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