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Enregistrement W2577958957 · doi:10.18203/2394-6040.ijcmph20170064

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

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

Notice bibliographique

RevueInternational Journal of Community Medicine and Public Health · 2017
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueSexual Assault and Victimization Studies
Établissements canadiensResverlogix (Canada)
Organismes subventionnairesnon disponible
Mots-clésFraternityPreparednessDescriptive statisticsMedicineCross-sectional studyHealth careFamily medicinePsychologyLawPolitical science

Résumé

récupéré en direct d'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.

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)0,002
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: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,002
Communication savante0,0020,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

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 Opus0,184
Tête enseignante GPT0,479
Écart entre enseignants0,295 · 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'étudeQualitatif
Domainenon disponible
GenreEmpirique

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
Publié2017
Routes d'admission1
Résumé présentoui

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