Estimated Incidence and Factors Associated With Risk of Elder Mistreatment in New York State
Notice bibliographique
Résumé
Importance: Elder mistreatment is associated with major health and psychosocial consequences and is recognized by clinicians, policy makers, and researchers as a pervasive problem affecting a rapidly aging global population. Objective: To estimate the incidence of elder mistreatment and identify factors associated with the risk of new cases. Design, Setting, and Participants: This research is a 10-year, longitudinal, population-based, cohort study of the incidence of elder mistreatment in New York State households conducted between 2009 (wave 1) and 2019 (wave 2). At wave 1, random digit-dial (landline and cellular telephones) stratified sampling was done to recruit English-speaking and/or Spanish-speaking, cognitively intact, community-dwelling older adults (aged ≥60 years) across New York State. The current study conducted computer-assisted telephone interviews with older adults who participated in wave 1 and gave permission to be contacted again for wave 2 interviews (response rate, 60.7%). Data analysis was performed from October 2020 to January 2021. Exposures: Physical factors (health status, functional capacity, and age), living arrangement (coresidence), and sociocultural characteristics (sex, race/ethnicity, geocultural context, and household income). Main Outcomes and Measures: Ten-year incidence for overall elder mistreatment and subtypes (financial abuse, emotional or psychological abuse, physical abuse, and neglect) were measured using adapted versions of the Conflict Tactics Scale, the Duke Older Americans Resources and Services scale, and the New York State Elder Mistreatment Prevalence Study financial abuse tool. Results: The analytical sample included 628 older adults (mean [SD] age at wave 1, 69.20 [6.95] years; age at wave 2, 79.40 [6.93] years; 504 non-Hispanic White individuals [80.9%]; 406 women [64.6%]). Ten-year incidence rates were 11.4% (95% CI, 8.8%-14.3%) for overall elder mistreatment, 8.5% (95% CI, 6.3%-10.9%) for financial abuse, 4.1% (95% CI, 2.6%-5.7%) for emotional abuse, 2.3% (95% CI, 1.2%-3.6%) for physical abuse, and 1.0% (95% CI, 0.3%-1.8%) for neglect. Poor self-rated health at wave 1 was associated with increased risk at wave 2 of new overall mistreatment (odds ratio [OR], 2.86; 95% CI, 1.35-5.84), emotional abuse (OR, 3.67; 95% CI, 1.15-11.15), physical abuse (OR, 4.21; 95% CI, 1.14-13.70), and financial abuse (OR, 2.80; 95% CI, 1.16-6.38). Compared with non-Hispanic White participants, Black participants were at heightened risk of overall mistreatment (OR, 2.61; 95% CI, 1.16-5.70) and financial abuse (OR, 2.80; 95% CI, 1.09-6.91). A change from coresidence to living alone was associated with increased risk of financial abuse (OR, 2.74; 95% CI, 1.01-7.21). Conclusions and Relevance: These findings suggest that health care visits may be important opportunities to detect older adults who are at risk of mistreatment. Race is highlighted as an important social determinant for elder mistreatment requiring urgent attention.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».