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Enregistrement W7037646545

Evaluation of a congregate retirement residence and housing preferences of prospective occupants

2011· article· en· W7037646545 sur OpenAlexaboutno aff

Notice bibliographique

RevueIllinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · 2011
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueBotanical Studies and Applications
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRespondentResidenceQuarter (Canadian coin)Index (typography)Retirement ageRetirement planningNursing homes
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Due to the growing numbers of elderly people, the interest and concern with elderly housing has expanded.The situation of aged people in our modern society is unique.Most often, elderly people who are no longer healthy enough to live alone or no longer wish to maintain a residence must seek some sort of congregate housing.Different types of congregate housing are available -from retirement hotels to nursing homes.The two general purposes of this study were to determine: a) the factors which influence the propensity of an elderly person to move into retirement housing, and b) the features of a particular retirement facility that were important in predicting the satisfaction of pros- pective occupants with that facility.In addition, data concerning housing features preferences of the respondents were collected.This study dealt with a specific facility, called a retirement residence, which provided limited health, personal and social services.The follow- ing categories of variables, which were thought to be related to propensity to move were measured: a) demographic variables, b) respondent's satisfaction with the facility, and c) an index named the ideal resident index.This index was a deviation score computed for each respondent (potential user) which reflected the congruence between the respondent's actual demographic characterisitics and housing preferences, and the characteristics and preferences that the designers thought would be true of the users.The forty elderly people who participated in the study had all been visitors to the retirement residence under study.Questionnaires deal- ing with background information, housing preferences, reasons affecting the decision to move or stay and impressions of this particular retirement residence were mailed to respondents.Later, interviews employing visual displays were conducted with each respondent individually.The purpose of the interview was to a) gain information concerning the preferences of elderly with regard to physical appearance of facilities, b) get feedback on certain design features of this specific retirement residence, and c) to gather data about the respondents' expected usage of different spaces provided in the facility.A step-wise multiple regression analysis on propensity to move revealed that the ideal resident index was the most important predictor, while health and physical strength of the respondent was second most important.Together they accounted for 27.6 percent of the total vari- ance.Satisfaction with the facility was not significantly related to the propensity to move.A step-wise multiple regression analysis was also done on satis- faction with the facility.It was found that the most important factor in predicting satisfaction with the facility was satisfaction with the medical servcies provided at the facility.The second most important factor was a "convenience" factor composed of a) satisfaction with convenience of transportation facilities, b) satisfaction with con- venience of shopping facilities, and c) satisfaction with the amount of rent.Together, these two factors accounted for 47.3 percent of the total variance.with regard to housing preferences, some of the results were that most of our respondents a) did not want to live in a big city or sur- rounding suburb, b) preferred completely private bedrooms and bathrooms, c) wished to be located near shopping facilities and friends, d) thought that home medical care was important, and e) preferred one-story buildings.

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)0,000
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 enseignants0,202
Score d'incertitude au seuil0,348

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,095
Tête enseignante GPT0,254
Écart entre enseignants0,160 · 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

Citations0
Publié2011
Routes d'admission1
Résumé présentoui

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