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Enregistrement W2529372398

Personal Characteristics and Risk Factors Associated with Economic Trade-offs and Financial Management Difficulties in Older Adult Home Care Populations

2013· dissertation· en· W2529372398 sur OpenAlexfundaboutno aff
Lee Anne Davies

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2013
Typedissertation
Langueen
DomaineHealth Professions
ThématiqueHealth and Wellbeing Research
Établissements canadiensnon disponible
Organismes subventionnairesUniversity of Waterloo
Mots-clésBusinessFinancial riskRisk managementFinanceMedicine
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

People are living longer and this increases the risk of encountering financial difficulties when trying to make fixed retirement incomes stretch over additional years. Increased life expectancies also increase the likelihood of encountering a health issue including cognitive or functional declines that can affect money management capabilities. There are government entitlement programs available to assist retired Canadians but these programs are under review and new policies are being considered in order to reduce fiscal pressures. At the same time, family roles and structures are changing and informal supports available to previous generations may be reduced. As well, if an older person’s money is poorly managed there will be fewer options for maintaining quality of life in the retirement years. This increases the risk of poverty for older Canadians. 
\nThe goals of this research are to: understand individual risk factors including demographic, clinical and social support characteristics among Canadians age 55 and over who are experiencing poverty; to understand the predictive characteristics for moving into or exiting from poverty; and, to develop a comprehensive description of those who have great difficulty managing their finances. In order to achieve this, data from the interRAI Home Care (RAI-HC) assessment instrument were used. Three regions, Winnipeg Regional Health Authority (WRHA), Nova Scotia and Ontario, were analyzed in order to understand the characteristics of those making economic trade-offs (N=345,678). Data from the province of Ontario was used to understand predictors of poverty transitions (N=47,653) and to develop a profile of those having great difficulty managing their finances (N=321,816). In order to answer each question of interest multivariable logistic regression modeling was used. 
\nResults from the analyses found that those most at risk for making economic trade-offs were in the age 55 to 64 group, had three or more depressive symptoms and were separated or divorced. Gender was not a risk factor. Regional differences for poverty risks were also identified showing greater risks for those experiencing mental health issues in WHRA, for those with more clinical indicators in Ontario, and for younger residents (age 55 to 64) in Nova Scotia. The longitudinal analyses on poverty transitions revealed that females who had completed at least a grade eight education were more likely to exit poverty. The younger group (age 55 to 64 years) with three or more depressive symptoms and experiencing unstable health were more likely to enter poverty. Marriage and older age were protective from the risks of entering poverty. Results from the analyses of those likely to have great difficulty with financial management indicated that deficits in cognition, procedural memory and function increased the risk of being unable to manage personal finances. Gender and marital status were not associated with financial management difficulty.
\nThe development of a profile of those who are making economic trade-offs and those at risk of having difficulty with financial management provides the opportunity for early intervention. Those who have not reached the traditional retirement age of 65 have an increased risk of poverty. Understanding characteristics of those who exit poverty will help establish policies and programs that will assist older Canadians. These are important issues due to the increased number of post-employment years that Canadians are living and the national focus on fiscal restraints. The management of finances has received minimal scientific research and evidence is needed to understand when changes in capability occur and how these changes may be supported by appropriate levels of assistance and supportive devices.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,208
Score d'incertitude au seuil0,921

Scores Codex et Gemma par catégorie

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

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 Opus0,019
Tête enseignante GPT0,275
Écart entre enseignants0,257 · 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'étudeObservationnel
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

Citations1
Publié2013
Routes d'admission2
Résumé présentoui

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