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Record W2163743622 · doi:10.1093/geront/gns146

An International Comparison of the Ohio Department of Aging-Resident Satisfaction Survey: Applicability in a U.S. and Canadian Sample

2012· article· en· W2163743622 on OpenAlexafffundabout
Heather A. Cooke, Takashi Yamashita, J. Scott Brown, Jane Straker, Susan Baiton Wilkinson

Bibliographic record

VenueThe Gerontologist · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Victoria
FundersFraser Health AuthoritySid W. Richardson Foundation
KeywordsSample (material)StandardizationGerontologyRSSPsychologyConfirmatory factor analysisAssisted livingMedicineFamily medicineApplied psychologyPolitical scienceBusinessMarketingComputer scienceService (business)

Abstract

fetched live from OpenAlex

PURPOSE OF THE STUDY: The majority of resident satisfaction surveys available for use in assisted living settings have been developed in the United States; however, empirical assessment of their measurement properties remains limited and sporadic, as does knowledge regarding their applicability for use in settings outside of the United States. This study further examines the psychometric properties of the Ohio Department of Aging-Resident Satisfaction Survey (ODA-RSS) and explores its applicability within a sample of Canadian assisted living facilities. DESIGN AND METHODS: Data were collected from 9,739 residential care facility (RCF) residents in Ohio, United States and 938 assisted-living residents in British Columbia, Canada. Confirmatory factor analysis was used to assess the instrument's psychometric properties within the 2 samples. RESULTS: Although the ODA-RSS appears well suited for assessing resident satisfaction in Ohio RCFs, it is less so in British Columbia assisted living settings. Adequate reliability and validity were observed for all 8 measurable instrument domains in the Ohio sample, but only 4 (Care and Services, Employee Relations, Employee Responsiveness, and Communications) in the British Columbia sample. IMPLICATIONS: The ODA-RSS performs best in an environment that encompasses a wide range of RCF types. In settings where greater uniformity and standardization exist, more nuanced questions may be required to detect variation between facilities. It is not sufficient to assume that rigorous development and empirical testing of a tool ensures its applicability in states or countries other than that in which it was initially developed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.095
GPT teacher head0.429
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2012
Admission routes3
Has abstractyes

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