MétaCan
Menu
Retour à la cohorte
Enregistrement W1672780339

Member wellness -- the art of maintaining your sanity.

2012· editorial· en· W1672780339 sur OpenAlexaboutno aff
Jim Fairles

Notice bibliographique

RevuePubMed · 2012
Typeeditorial
Langueen
DomaineHealth Professions
ThématiqueVeterinary Practice and Education Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMental healthSanitySummitPsychologyPsychiatryCriminologyMedicinePolitical science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

It’s September as I write this. Summer holidays are over and “life” begins to happen again in earnest. A multitude of commitments begins to pile up. It seems like the issues and crises will never end. How do we cope? How do we prevent burnout? At the CVMA convention in July we explored some of these issues at the Summit of Veterinary Leaders forum. The topics of burnout and suicide are long overdue as national discussion points. It has certainly been a difficult area for me to discuss. As a male of the baby boomer generation, we were expected to be strong, and the idea that mental health issues were for others was deeply ingrained in us. Truth be told, in hindsight I was constantly bumping up against the issues of mental health throughout my career. How did I avoid any serious consequences? That is a good question. Health Canada statistics from 2002 indicate that 1 in 5 Canadians will experience a mental illness in their lifetime. The remaining 4 will have a friend, family member or colleague who will. I certainly can relate — a classmate who disappeared for days at a time, a classmate who committed suicide, a family member’s addiction and mental health issues, and more recently, a serious accident and brush with mental health concerns myself. Recent articles and discussions have continued to emphasize the growing issue of mental health issues and suicide in the veterinary profession (1–7). One such article from the United Kingdom (2) by Bartram and Baldwin states, “Veterinary surgeons have a proportional mortality ratio (PMR) for suicide approximately 4 times that of the general population and around twice that of other healthcare professions.” From an article from Australia in 2008 (4); “The estimated suicide rates for western Australian and Victorian veterinarians were respectively 4.0 times and 3.8 times the standardized rate for suicide in the respective state adult populations.” These statistics are alarming indeed. The national member wellness survey conducted by the CVMA this spring showed just how serious these issues are in Canada. (The CVMA gratefully acknowledges the Association des medecins veterinaires du Quebec en practique des petits animaux for the use of its survey template.) With a 20% response rate there were several interesting and surprising findings. This is by no means a statistically valid survey but the general response tallies are quite alarming even considering that those affected by issues would be the most interested in responding. Do you believe that you have suffered burnout in the past? 51% yes Have you had burnout confirmed by physician/psychiatrist? 12% yes Is your profession a major contributing factor of your burnout? 90% yes For more detailed information on the survey have a look at the article found in the news section of this issue entitled “Wellness of Veterinarians: CVMA National Survey Results” on page 1159. Some provinces have developed safety nets and/or piggy backed on existing professional support programs. I am most familiar with the Ontario situation and the Professionals Health Program (PHP). These and other help lines and support services are available for those who need support or are in a crisis situation. How do we develop the tools to prevent us from getting this far? Other countries have expressed concerns as well, have undertaken research and are attempting to address the issues, particularly Great Britain with Vetlife, and Australia with Vet Health. Through discussions with those administering the Australian program the concept of resiliency was raised. How resilient are we to the stress and strain of everyday practice and life? Do we have the tools necessary to be able to cope and bounce back from mental health issues? Over the course of the next year, this issue will be discussed at the CVMA Council table. We must answer some basic questions about this topic and I invite you to share your opinion, starting with — should we get involved? And if so How should we get involved? Are there any current resources that we can make available to members? How should we fund these endeavors? Is a benevolent fund or foundation a viable option for funding for those in distress? The most recent article from the Association of American Veterinary Medical Colleges by Skipper and Williams (7) provides a serious call to action: “There is a critical need for action. For action to be effective, it clearly needs to be undertaken with the involvement of all of the agencies concerned with veterinary medicine, including the Student Chapter of the American Veterinary Medical Association, the American Association of Veterinary State Boards, the Association of American Veterinary Medical Colleges, and the American Veterinary Medical Association, if this ticking time-bomb is to be defused.” To me it is obvious that the respective Canadian organizations must be involved as well. As suggested in my previous editorial — please make your opinions heard, either to the CVMA (gro.vmca-amvc@nimda) or to me directly (www.skyvet.com, moc.tevyks@mij or gro.vmca-amvc@tnediserpamvc) Stay calm! Stay well!

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,077
Score d'incertitude au seuil0,259

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,010
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0090,005
Communication savante0,0080,006
Science ouverte0,0010,008
Intégrité de la recherche0,0030,010
Charge utile insuffisante (le modèle a refusé de juger)0,0770,044

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,281
Tête enseignante GPT0,464
Écart entre enseignants0,183 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revuePubMedMême sujetVeterinary Practice and Education StudiesTravaux en français237 207