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Record W4392381573 · doi:10.5770/cgj.27.690

Piloting a Supplemental Assessment Tool with Younger Residents of Long-Term Care

2024· article· en· W4392381573 on OpenAlexaffvenueabout
Erin M. Samson, Elaine Moody, Lori E. Weeks

Bibliographic record

VenueCanadian Geriatrics Journal · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineFlexibility (engineering)Intervention (counseling)Nova scotiaLong-term carePsychological interventionNursingNeeds assessmentSet (abstract data type)Medical educationFamily medicine

Abstract

fetched live from OpenAlex

Background: Young adults living with disabilities may sometimes end up in long-term care facilities which may not always meet their needs. Our project set out to pilot a supplemental assessment tool, a questionnaire to be used upon admission of younger adults into long-term care. We wanted the opinions of both staff and younger residents on what modifications may be needed in the implementation processes to ensure effectiveness of the tool. Methods: This project followed a qualitative design, implementing a previously designed supplemental assessment tool with five staff members and seven younger residents of two long-term care homes in Halifax, Nova Scotia. Residents completed the questionnaire with members of staff involved in admissions. Each group participated in follow-up interviews regarding their thoughts on implementation of the tool. Responses were analyzed using the constructs of the Consolidated Framework in Implementation Research following direct content analysis methods. Results: Feedback from residents and staff suggested that the tool could not be used as a one-size-fits-all solution but that flexibility in the format, content, and structure of the tool would be beneficial to ensure its utility in a variety of settings. Issues raised by staff and residents included, but were not limited to, accessibility of the intervention, the availability of resources, the format of the intervention and topics covered within it, and ensuring that processes for implementation are clearly defined. Conclusions: Both staff and residents approved of the tool for use in the admissions process and agreed that it would enhance the admissions practices already in place.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.370
Teacher spread0.345 · 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.

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

Citations0
Published2024
Admission routes3
Has abstractyes

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