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Record W2594147553 · doi:10.4103/2249-4863.201160

Smoke on a white coat

2016· article· en· W2594147553 on OpenAlexaboutno aff
Salman Assad, Immad Arif, Touqeer Sulehria

Bibliographic record

VenueJournal of Family Medicine and Primary Care · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWhite (mutation)ChinaHealth careFamily medicineWhite coatEnvironmental healthLaw

Abstract

fetched live from OpenAlex

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.

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)0.001
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0100.016
Insufficient payload (model declined to judge)0.0090.006

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 head0.600
GPT teacher head0.632
Teacher spread0.032 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2016
Admission routes1
Has abstractyes

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