Development and testing of the Geriatric Care Assessment Practices (G-CAP) survey
Bibliographic record
Abstract
BACKGROUND: While the Resident Assessment Instrument-Home Care (RAI-HC) tool was designed to support comprehensive geriatric assessment in home care, it is more often used for service allocation and little is known about how point-of-care providers collect the information they need to plan and provide care. The purpose of this pilot study was to develop and test a survey to explore the geriatric care assessment practices of nurses, occupational therapists (OTs) and physiotherapists (PTs) in home care. METHODS: Literature review and expert consultation informed the development of the Geriatric Care Assessment Practices (G-CAP) survey-a 33 question, online, self-report tool exploring assessment and information-sharing methods, attitudes, knowledge, experience and demographic information. The survey was pilot tested at a single home care agency in Ontario, Canada (N = 27). Test-retest reliability (N = 20) and construct validity were explored. RESULTS: The subscales of the G-CAP survey showed fair to good test-retest reliability within a population of interdisciplinary home care providers [ICC2 (A,1) (M ICC = 0.58) for continuous items; weighted kappa (M kappa = 0.63) for categorical items]. Statistically significant differences between OT, PT and nurse responses [M t = 3.0; M p = 0.01] and moderate correlations between predicted related items [M r = |0.39|] provide preliminary support for our hypotheses around survey construct validity in this population. Pilot participants indicated that they use their clinical judgment far more often than standardized assessment tools. Client input was indicated to be the most important source of information for goal-setting. Most pilot participants had heard of the RAI-HC; however, few used it. Pilot participants agreed they could use assessment information from others but also said they must conduct their own assessments and only sometimes share and rarely receive information from other providers. CONCLUSIONS: The G-CAP survey shows promise as a measure of the geriatric care assessment practices of interdisciplinary home care providers. Findings from the survey have the potential to inform improvements to integrated care planning. Next steps include making adaptations to the G-CAP survey to further improve the reliability and validity of the tool and a broad administration of the survey in Ontario home care.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".