An International Comparison of the Ohio Department of Aging-Resident Satisfaction Survey: Applicability in a U.S. and Canadian Sample
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".