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ATTITUDE OF HEALTH PROFESSIONALS TOWARDS REASONABLE CONSUMPTION

2023· article· en· W4390713232 on OpenAlexaboutno aff
A.V. Zubko, T.P. Sabgayda, Konstantin E. Khomanov, Yulia Dzyuba

Bibliographic record

VenueSocial Aspects of Population Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Resources and Workforce
Canadian institutionsnot available
Fundersnot available
KeywordsDeclarationTest (biology)Consumption (sociology)PopulationPsychologyHealth careQuarter (Canadian coin)NursingMedical educationMedicineEnvironmental healthSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Significance. “Responsible consumption and production”, numbered 12, is one of the 17 Sustainable Development Goals established by the United Nations. Health professionals are part of the social circle of the majority of the country's population. The level of trust in health professions makes it possible to believe that the lifestyle of doctors and people associated with healthcare (as well as the lifestyle of teachers, educators, media personalities) can often serve as an example to follow in terms of responsible consumption provided the media develops and raises awareness of its significance. The purpose of this study is to measure the attitude of health professionals towards responsible consumption. Material and methods. Attitudes were measured via a questionnaire developed by the research team. The electronic survey included 2923 respondents signed in the "Doctor's guide" mobile application, including doctors - 65% (Group 1), nursing staff -9% (Group 2) and students and technical staff - 26% (Group 3). Frequency comparison was undertaken using Chi-squared test. Relevant risk and potential error were calculated. Data analysis was carried out using Microsoft Excel 2016. Results. With a more frequent declaration of the need for waste sorting, doctors in everyday life practice it less often than nurses: 39.7% vs. 46.6%. More than 5% of the respondents believe that there are no waste processing enterprises in Russia at all. Only a quarter of the respondents explain their disengagement in waste sorting for recycling by personal traits and motives. More than a tenth of the respondents are ready to engage in waste sorting only if there are incentives or prohibitions, more than 5% associate their unwillingness with the lack of skills to sort waste, as well as the presence of strong opponents to waste sorting in their inner circle. There was no difference in the distribution of the responses across all three groups of the respondents about the dual system of municipal waste sorting (everything that belongs to the category of “recyclables” must be thrown in the blue container) operating in the Republic of Tatarstan and the Moscow region. Almost 14% of the surveyed health professionals neither had the slightest idea about this system or plan to sort waste, while about 55% did not know, but are going to use this system. Half of those who knew about the dual sorting system (15.9% of the respondents) doubt that it can be trusted. A fifth of the respondents do not know where to dispose of hazardous household waste that cannot be thrown in a regular waste container and note that there are no hazardous waste drop-off sites. Conclusion. The study demonstrates that health professionals have a low commitment to responsible consumption. As to medical disposables, doctors consider their replacement with reusable analogues acceptable and rational more often than nurses. In general, health professionals do not share the idea of a long-term and careful use of household items with a possible subsequent donation or re-sale.

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)0.004
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.099
GPT teacher head0.447
Teacher spread0.347 · 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 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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