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Enregistrement W3202574516 · doi:10.1080/07853890.2021.1896175

Elder abuse: the hidden face of domestic violence

2021· article· en· W3202574516 sur OpenAlexaboutno aff
Iris Almeida, Ana Filipa Carreiro, Ana Filipa Fernandes, Catarina Frade, Carolina Nobre, Lúcia Osório, Margarida Pereira, Ricardo Ventura Baúto

Notice bibliographique

RevueAnnals of Medicine · 2021
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueElder Abuse and Neglect
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésElder abuseNeglectContext (archaeology)PopulationHarmWorkplace violenceDeclarationDomestic violenceCriminologySexual abusePhysical abuseHuman rightsMedicinePsychologyPsychiatryPoison controlSuicide preventionPolitical scienceSocial psychologyMedical emergencyLawEnvironmental healthGeography

Résumé

récupéré en direct d'OpenAlex

Introduction Violence against the elderly constitutes an undeniable and serious violation of human rights and affects the physical and psychological integrity of the victim. Is not a new phenomenon, is a worldwide problem that has become more pronounce in contemporary societies because of the ageing of the population. World Health Organization [1 World Health Organization (WHO). The Toronto declaration on the global prevention of elder abuse. Geneva: World Health Organization; 2002. [Google Scholar]] defines elder violence as a single or repeated action, or the absence of an appropriate action, arising in the context of a relationship where there is an expectation of trust that causes suffering or harm to an elderly person. Occurs through several behaviours involving psychological, physical, sexual, financial violence, neglect and self-neglect [2 National Research Council (NRC). Elder mistreatment: abuse, neglect, and exploitation in an aging America. Washington, DC: The National Academies Press; 2003. [Google Scholar]]. The purpose of this paper is to demonstrate the work developed by the Victims Information and Assistance Office (GIAV) and by Forensic Psychology Office (GPF) at Egas Moniz Higher Education School about elder abuse.Materials and methods The sample (n = 14) is derived from the domestic violence risk assessments of GIAV and GPF. We assessed 6 victims: 2 women and 4 man, aged between 64 and 95 years old (M = 76.67, sd = 10.71); and 8 defendants: 6 women and 2 man, aged between 24 and 77 years old (M = 46.13, sd = 15.52). The relationship between victims and defendants are 13 sons/daughters and 1 tenant. Data were collected from lawsuits, semi-structured interviews of the victims and defendants, collateral information and criminal record. All ethical issues have been taken due to the sensitive nature of the involved data involved and the respective informed consentient which contained the purpose of the assesses, the confidentiality limits, and information about the ethics and technician’s impartiality was sign by all participants.Results The results demonstrated physical and psychological abuse (in all cases), followed by economical abuse (n = 13, 92.9%) and social abuse (n = 3, 21.4%). It is possible to identify several victims’ risk factors, namely gender (female victims – n = 11, 78.6%), physical problems/limitations (n = 11, 78.6%), age above 75 years old (n = 8, 57.1%) and previous abuse (n = 6, 42.9%). The most relevant offender’s risk factors are financial problems (n = 12, 85.7%), deficit in the coping skills (n = 12, 85.7%), others blame (n = 10, 71.4%), history of violence against others (n = 8, 57.1%), aggressiveness (n = 8, 57.1%), criminal history (n = 6, 42.9%), victim of domestic violence in the past (n = 8, 35.7%) and perpetrator of domestic violence in the past (n = 5, 35.7%). Finally external/relational factors are: offender’s dependence (n = 11, 78.6%), cohabitation (n = 11, 78.6%), history of conflicts between victim and offender (n = 10, 71.4%), poor emotional attachment or low family cohesion (n = 10, 71.4%), social isolation or lack of social support (n = 8, 57.1%), intergenerational transmission of violence (n = 7, 50%), inability in the performance of caregiver tasks (n = 5, 35.7%) and inexperience as caregiver (n = 5, 35.7%).Discussion and conclusions Portugal it’s one of the top five European Countries with higher percentage (39%) of elderly mistreated [3 Associação Portuguesa de Apoio à Vítima. Pessoas idosas vítimas de crime e violência 2013/2017. Lisboa: APAV; 2018. [Google Scholar]], however, elder abuse is still the hidden face of domestic violence. The data show several risk factors for elder abuse. These results demonstrated the urgency about elder abuse risk assessment in criminal justice system and the need of a good articulation between Forensic Psychology and Law in order to demystify the hidden face of elder abuse.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,445
Score d'incertitude au seuil0,686

Scores Codex et Gemma par catégorie

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

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 Opus0,068
Tête enseignante GPT0,396
Écart entre enseignants0,328 · 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 tête enseignante, 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

Citations2
Publié2021
Routes d'admission1
Résumé présentoui

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Même revueAnnals of MedicineMême sujetElder Abuse and NeglectTravaux en français237 207