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Perceptions of dental healthcare providers about gender based violence in Maharashtra, India

2017· article· en· W2577958957 on OpenAlexaff
Aby Mathews M., Rohini N. Kathavate, Abhishek S. Bendale, Disha Kumar

Bibliographic record

VenueInternational Journal of Community Medicine and Public Health · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsResverlogix (Canada)
Fundersnot available
KeywordsFraternityPreparednessDescriptive statisticsMedicineCross-sectional studyHealth careFamily medicinePsychologyLawPolitical science

Abstract

fetched live from OpenAlex

Background: To assess the level of knowledge and preparedness that the dental practitioners of Maharashtra, India posses in terms of identifying, analyzing, treating and supporting a potential victim of gender based violence (GBV). This study also aims to analyse the present level of confidence the dental fraternity has in the educational, legal and law enforcement systems of India in terms of dealing with GBV issues.Methods: A descriptive cross sectional study involving an anonymous electronic survey of a sample of 156 dental practitioners practicing in Maharashtra India. The survey was designed with two sections. The first section of the survey was designed to collect the demographic data of the respondents and information about their professional background. The second section comprised of 20 questions analysing the respondents level of understanding of the concept of GBV, their familiarity with GBV in practice, their opinion of current education and legal system concerning to GBV issue and their intent to further study in the subject.Results: The response rate was 75.6% and 118 responses were received. Out of the 118 responses, 17 were incomplete and were excluded from the study. Thus only 101 responses were used for analysis. More than 35% of the respondents were aware of the concept of GBV where as almost 20% were completely new to the subject. More than 75% agreed that GBV affects both genders and affects primarily females. More than 80% responded that the victims generally do not tend to disclose who abused them. Majority agreed on the fact that the victims tend to confide with their family and friends other than any other option when affected by GBV. 50% of respondents were confident that they could handle a case of GBV in their clinic effectively. 72.7% responded that they were not aware of the Guidelines & Protocols, Medico-legal care for survivors/ victims of sexual violence, Ministry of health and family welfare, Government of India. More than 40% logged an increase in understanding of GBV after reading the snapshot of Guidelines & Protocols provided with the survey and expressed interest to learn more. 64.6% noted that they were not properly equipped for handling a GBV case but hope to do better with proper trainings. Regarding the present legal system, 54.3% of the respondents categorised it as mature but non-prompt. More than 80% agreed that there should be incorporation of modules on GBV in the academic curriculum and 96% logged interest in having more information on GBV sent to them.Conclusions: Even though there was a consensus among the respondents that females were the primary victims of gender based violence, the study showed that there is only moderate awareness regarding Gender Based Violence amongst the dental practitioners in the state of Maharashtra. Even though a majority of the respondents were not aware of the proper guidelines and protocols for handling a case of GBV, a little over 50% were convinced that they would be able to handle a case of GBV in their practice. A need to update the curriculum and provide the currently practicing dentists with proper training was also identified.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.140
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.184
GPT teacher head0.479
Teacher spread0.295 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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