Notice bibliographique
Résumé
Dear Editor, The world over doctors, medical students, and health-care professionals is recognized by their iconic white coat. Not only does it serve as a uniform that commands respect, but also it is used as a barrier to protect both patients and doctors from transmission of germs and pathogens. Smoking among doctors is a common problem. A question arises how smoke on a doctor's white coat affects his patients. Worldwide, two patterns are seen regarding smoking prevalence. In developed countries such as the United States of America, the United Kingdom, and Canada, there has been a steady decline in smoking rates of <10%. There are developed countries such as France, Italy, and Spain, which do not fall into the same category where smoking prevalence is >25%. On the other hand, developing countries such as India, China, and Turkey have smoking prevalence rates of over 50% among doctors and health-care professionals.[1] Within a society, doctors are not only considered healers but also seen as role models. Being trusted enough by patients to be told about their personal information, doctors take on the responsibility of counseling patients about social harms that have become acceptable in our society such as smoking, excessive drinking, use of illicit drugs, and unsafe sexual practices. Although no study specifically looks at how smoke on a white coat directly affects patients, there have been multiple studies which observed attitudes of doctors who smoke and how it affects their practices. It is believed that their personal use restricts them from counseling patients about the harmful effects of smoking and quitting. A study which looked at the attitudes of general and family practice physicians who smoke and their clinical interactions with patients regarding smoking cessation was conducted across 16 countries. Of the 42% smoking physicians, a significantly lesser number believed smoking to be a harmful activity when compared to nonsmoking physicians. Not only did a greater number of nonsmoking physicians believe that smoking cessation is the single biggest step in improving health, but they also discussed it more at every visit when compared to physicians who smoked.[2] Current physician smokers are less likely to ascertain the smoking status of their patient when compared to never smokers and less likely to provide information on how to quit smoking.[3] With regard to patients, it can be safely assumed that patient's satisfaction with doctors whose white coat stink of smoke will be low and patients would prefer not to consult them in the future. Even if the doctor delivers an excellent counseling, the credibility and respect of the white coat are lost with smoke on it. A simple hospital-based study can be conducted in future, looking at the attitudes of doctors who smoke. Further studies can be done to evaluate patient's willingness and satisfaction to consult with doctors who smoke. In conclusion, hospitals should adopt policies to help doctors quit smoking and implement strict rules regarding no smoking within hospital premises. Doctors should be mindful of the role given to them by the society, and at a minimum should avoid smoking with a laboratory coat on. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,010 | 0,016 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,006 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».